general public T cell based-immunotherapies represent a promising approach for cancer treatment.

Despite impressive successes for the treatment of hematologic cancers, it has been less fruitful on solid tumors. This is in part due to the altered metabolism generated in the tumor microenvironment that impairs T cell anti-tumor function. To overcome this problem, I have focused during my PhD on understanding the impact of metabolic parameters on T cell effector function. Our results demonstrate that glutamine availability plays a crucial role in the acquisition of effector T functions with, alpha-ketoglutarate, a glutamine-derived metabolite, acting as a metabolic regulator of T cell differentiation. In parallel, we show that T cells with distinct effector functions can be identified based on the surface expression of the glucose transporter, GLUT1. Altogether, targeting T cell metabolism could represent an original angle to modulate T cell anti-tumor function and improve cancer immunotherapies.

Résumé grand public

Malgré d'impressionnants succès pour des cancers hématologiques, les immunothérapies par transfert de cellules T s'avèrent peu efficaces pour le traitement de tumeurs solides. Ceci est en partie dû à l'altération du métabolisme par l'environnement tumoral qui limite l'efficacité anti-tumorale des cellules T. Durant ma thèse, j'ai ainsi étudié l'importance du métabolisme dans les fonctions effectrices des cellules T. Nos résultats montrent que la disponibilité en glutamine est essentielle pour l'acquisition des fonctions effectrices des cellules T et que, l'alpha-cétoglutarate, un métabolite dérivé de la glutamine, agit comme régulateur dans leur processus de différenciation. En parallèle, nous montrons que les cellules T, identifiées sur la base de l'expression du transporteur de glucose GLUT1, possèdent des fonctions effectrices distinctes. Le ciblage du métabolisme pourrait donc représenter un angle thérapeutique original pour améliorer la réponse anti-tumorale des cellules T.

Targeting the metabolic environment to modulate T cell effector function Abstract T cells are stimulated upon interaction with their cognate antigen. While much research has focused on the role of antigen presenting cells (APC) and cytokines as important components of the T cell microenvironment, recent data highlight the importance of the metabolic environment in sustaining the energetic and biosynthetic demands that are induced upon antigen stimulation. The subsequent metabolic reprogramming of the T cell is conditioned by the nutrient composition and oxygen levels. Notably, this environment can be altered by pathological conditions such as tumors and data from our group, as well as others, have shown that the competition of T cells and tumor cells for limiting amounts of nutrients has a negative impact on T cells, inhibiting their anti-tumor effector functions. This effect is due, at least in part, to the distinct metabolic profiles of T lymphocyte subsets; T effector cells (including Th1 cells) are highly glycolytic while suppressive FoxP3 + regulatory T cells (Tregs) display a mixed metabolism with increased levels of lipid oxidation. It is therefore important to determine how changes in the metabolic programming of anti-tumor T cells impacts on their persistence and function. Indeed, in the context of my PhD research, I found that high levels of the glucose transporter GLUT1 was associated with a significantly increased level of IFNγ secretion by both CD4 and CD8 T cells. Furthermore, there was a bias of CD8 over CD4 lymphocytes in the GLUT1 High T cell subset. These data point to the importance of metabolic alterations in the fate and effector function of T lymphocytes and during my PhD, I focused on elucidating the metabolic parameters that regulate effector and regulatory T cells, with the goal of improving the efficacy of anti-tumor T cells. In this context, I contributed to initial studies from our group, revealing a critical role for extracellular nutrient availability in terminal CD4 + T cell differentiation. Activation of naïve CD4 + T cells under conditions of glutamine deprivation caused them to differentiate into induced Treg (iTreg). Moreover, the skewing of glutamine-deprived naïve CD4 + T cells to a FoxP3 + fate occurred even under Th1polarizing conditions, blocking terminal Th1 differentiation. Under glutamine-deprived conditions, we found that alpha-ketoglutarate (αKG), a glutamine-derived metabolite, rescued Th1 differentiation. I then evaluated the impact of αKG under glutamine-replete conditions in the Th1/iTreg differentiation processes. My studies showed that, under Th1polarizing conditions, αKG markedly enhanced naïve CD4 + T cell differentiation into Th1 cells and increased IFNγ secretion. Moreover, under Treg-polarizing conditions, αKG decreased FoxP3 expression and increased the secretion of inflammatory cytokines such as IFNγ, GM-CSF and IL-17. Notably, the αKG-mediated alteration in T cell differentiation was associated with an augmented oxidative phosphorylation (OXPHOS), and inhibiting the citric acid cycle and the mitochondrial complex II with malonate, an inhibitor of succinate dehydrogenase (SDH), alleviated the αKG-mediated block in Treg differentiation. Impressively, these αKGmediated changes in the Th1/Treg balance were maintained in vivo, promoting a Th1-like profile in T cells expressing an anti-tumor chimeric antigen receptor (CAR) in tumor-bearing mice. Thus, our data show that low intracellular αKG content, caused by limited external glutamine availability, imposes a Treg phenotype while high αKG levels shift the balance towards a Th1 phenotype.

Altogether, the data generated during my PhD will promote the development of metabolic strategies aimed at modulating T cell function and foster the design of nutrient transporter-based approaches that can be used to select T lymphocytes with enhanced antitumor effector properties. De plus, nos travaux montrent que la disponibilité en nutriments extracellulaires est un élément clé pour la différenciation terminale des cellules Th1. En effet, l'activation des cellules T CD4 naïves en conditions limitantes en glutamine induit leur différenciation en cellules Treg FoxP3 + . Plus surprenant encore, cette carence induit un blocage de la différenciation Th1 même lors d'une polarisation vers ce lignage. De plus, en conditions de carence en glutamine, nous avons découvert que l'alpha-cétoglutarate (αKG), un métabolite dérivé de la glutamine, rétablit cette différenciation terminale Th1. J'ai ensuite évalué l'impact de l'αKG dans les processus de différenciation Th1/Treg en condition non limitante en glutamine. Mes données montrent que, dans des conditions de polarisation Th1, l'ajout d'αKG améliore la différenciation des cellules T CD4 naïfs en cellules Th1 et augmente la production d'IFNγ. A l'inverse, l'ajout d'αKG s'accompagne d'une diminution des cellules FoxP3 + et d'une augmentation de la sécrétion de cytokines inflammatoires dans des conditions de polarisation Treg. L'altération de la différenciation des cellules T médiée par l'αKG est notamment associée à une phosphorylation oxydative (OXPHOS) accrue ; ainsi, l'ajout d'un inhibiteur du cycle de Krebs et du complexe mitochondrial II /succinate déshydrogénase, atténue le blocage de la différenciation Treg induit par l'αKG. De façon remarquable, ces modifications de l'équilibre Th1/Treg médiées par l'αKG sont maintenues in vivo et impactent le devenir de cellules T exprimant un récepteur chimérique anti-tumoral (CAR) injectées chez des souris porteuses de tumeurs. En résumé, nos données montrent qu'une faible teneur en αKG intracellulaire liée à une disponibilité limitée en glutamine, favorise un phénotype Treg, alors que des niveaux élevés d'αKG modifient l'équilibre vers un phénotype Th1.

Modulation des fonctions effectrices des cellules T en exploitant l'environnement métabolique

En conclusion, les données générées au cours de ma thèse devraient permettre le développement de stratégies permettant de sélectionner des cellules T ayant des propriétés effectrices anti-tumorales améliorées.

Surprisingly, even if I am someone known for my capacity to express my feelings, writing this part was not easy. It was not easy because I could write another thesis manuscript (not right now, or maybe) only to express my gratitude to all those who helped during this journey.

Thus, I will try to be brief and efficient.

First of all, I would like to say to thank you to the thesis jury members who accepted to review my manuscript and be part of this adventure.

I could not start this part without saying thanks to Naomi and Valérie D. Naomi, I was only 21 years old when we first met in Coimbra (a meeting that I will never forget). After assisting to a thesis defense, you came to my faculty and we discussed about the research done in your lab (I could not imagine the amount of things you were able to do in 24 hours). After that, I have been working with you, learning and growing scientifically with you. Thank you very much for the opportunity to work in your lab and thank you for your exigence: the only way to progress is to go beyond ourselves. Valérie, you have been guiding me since the very first moment I was in the lab. The way I work, how I see science, the way that I design and develop my research is a reflect of what I learnt with you. You were always available to help me and to answer my questions no matter how full was your agenda. You also taught me that "life is already too complicated, don't make it more difficult" when I was having my drama queen moments or when I was trying to do experiments with way more conditions that were possibly necessary. For this and much more, thank you.

To my partner and my teammate Yong, I would like to write few special words. We were a fantastic team. Despite how different we are (and how many times we potentially would like "to kill" each other), we became a strong team. We worked hard and we were always moved by the same ambition and objectives. We were complementary and supportive. We were and will always be the Yin and Yong. To Gaspard, or simply "Crenet" (when my French was a catastrophe) I would like to say that it was really a pleasure working with you. Thank you very much for everything you taught me, which will always be one of the foundations of my still little scientific career (I am still waiting for my sock).

Thank you to all the NTL members: Sandrina, (for being my little -or maybe I should say tall-star. Your positive energies were essential to me in this journey), Valérie Z. (for your sense of humor and your incredible capacity of smiling even when you are speaking about serious things), Cédric (for making a lot of noise close to my desk, for making me smile and discuss with me about how good is the Portuguese gastronomy), Patrice (for being Cedric's BFF and making me laugh all the time), Peggy (for all the hugs and your good energies), Daouda (for finding the best car ever, for all your kindness and for being with Mar), Myriam (for your never ending hours in front of the sorter), Manu (for widening my taste for cakes and desserts, especially tiramisu), Anais (always efficient and hard worker), Sarah (for your sense of humor), Vincent (for all the radioactive moments), Little Mehdi and Little Ira (the funniest baby PhD students), Alice (for your funny "fecha a porta"), Anne-So (for your optimism), my Dobbys poisson rouge and PAB (thank you for your help and enthusiasm), Pedro (for defending me all the timeonly the Iberians understand each other), Zoï (discussing about vegetables was never as interesting as it is since I met you. Thank you for your special way to be), Petite Marie (my little sister with whom I can discuss about fashion, coiffure and express my deep feelings. Merci, mon Arc-en-Ciel), Ma Cacahuète (words are not enough. Thank you for being my lab mate, my best friend, my sister and my housemate.

Montpellier is special and it will always be thanks to you).

A big thanks to all the members of the institute for the good environment. A special thank you to my cell culture ladies, Fabi, Rosy and Kata. For all the moments that we shared between beers and glass of wine. You are the best. For Anne I would like also to say thank you for all the support and advices during this important last year. Now, I would like to address some special words to my family, my Portuguese friends, and all the fantastic people that became part of my family during my time in Montpellier. Thanks to them, I now have a family in two different countries. Primeiro de tudo, um grande e enorme obrigada à minha família, especialmente à minha Mãe, ao meu Pai e ao meu Irmão por todo o apoio que me deram ao longo destes anos. Apesar da distância física ser grande, nunca vos senti longe de mim. Estiveram sempre presentes do início ao fim. O que hoje sou, a vôces vos devo e esta conquista é dedicada a vôces. Aos Ferreiritas e aos Matias, obrigada por todo amor durante as tão desejadas férias de Natal e de Verão. À Ben, un énorme merci. Ton support était hors norme. C'est en toi que j'ai trouvé toutes les forces du Monde pour ce grand défi. Obrigada, zangão. Às minhas amigas e irmãs de coração Mariana, Adriana, Soraia e Tati (ordem aleatória e não representativa de quaisquer preferências) gostaria de vos agradecer pela vossa eterna amizade. Por mais anos que passem, nada muda. Obrigada por terem estado sempre presentes neste percurso. Ao Rojões, à Vi, à Filipa, à Su, à Bibiana e à Joana Oliveira um igual especial obrigado. À minha amiga Isabel, gostaria de agredecer todos os momentos de fofoquice e apoio. Há desabafos e dramas que só os Tugas compreendem.

Obrigada por seres a "meilleure Tuga" de Montpellier. À Muriel, Nawel et Pascale et tous les coaches qui nous ont accompagné, merci. Nos moments de cardio à fond ensemble était cruciaux. À la famille Perrin, famille Pouzolles et a famille Molière un grand merci. Quand on est loin de nos origines, être loin de la famille et des amis est le plus difficile à supporter.

Merci de m'avoir adoptée, merci pour tout votre amour. As my PhD project was centered on T lymphocytes and therefore, I will specifically focus on this cell type in the following chapter.

List of Figures/Tables

Results-Chapter 1

Results-Chapter 2

Results-Chapter 3

1) T cells

T cells recognize their cognate antigen and trigger distinct and directional responses through their specific receptor, the TCR. TCR diversity is generated from DNA rearrangements where a randomly somatic recombination of V, D and J segments, mediated by the recombination-activating genes (RAG) 1 and 2, results in the production of several and distinct associations of TCR chains (α, β, γ, δ), giving rise to roughly ~10 18 unique TCRs in humans [START_REF] Murphy | Janeway's Immunology[END_REF]. Based on the TCR rearrangements, T cells are classified in two main group, αβ or γδ T cells (section I 1 A). Although extremely diverse, these TCRs, generated through VDJ recombination, need to be capable to recognize an enormous variety of antigens being at the same time capable to tolerate self-antigens. For that purpose, positive and negative selection takes place in the thymus in order to avoid auto-immunity and maintain self-tolerance (section I 1 B).

A. T cell diversity

αβ T cells are the most represented T cell subpopulation in the periphery and "conventional" αβ T cells are divided into 2 distinct lineages: CD4 + and CD8 + phenotypically and functionally distinct which I will detail below. Within this αβ T cell population, there are also few subtypes classified as "unconventional" like mucosal-associated invariant T (MAIT) cells (Le [START_REF] Bourhis | Antimicrobial activity of mucosal-associated invariant T cells[END_REF][START_REF] Treiner | Selection of evolutionarily conserved mucosal-associated invariant T cells by MR1[END_REF], invariant natural killer T (iNK T) cells and germline-encoded mycolyl-reactive (GEM) T cells which recognize specifically glycolipids presented by MR1, CD1d and CD1b respectively [START_REF] Beckman | Recognition of a lipid antigen by CD1-restricted alpha beta+ T cells[END_REF][START_REF] Van Rhijn | A conserved human T cell population targets mycobacterial antigens presented by CD1b[END_REF].

γδ T cells are also considered as unconventional T cells and they represent between 1%-5% of all T lymphocytes. Even if this population was described for the first time in 1987 [START_REF] Born | Peptide sequences of T-cell receptor delta and gamma chains are identical to predicted X and gamma proteins[END_REF][START_REF] Tonegawa | Diversity, development, ligands, and probable functions of gamma delta T cells[END_REF], the structures to which γδ T cells respond to and how are not well-characterized. Using murine models, it was established that γδ T cells are important for pathogen clearance and tumor surveillance [START_REF] Carding | Gammadelta T cells: functional plasticity and heterogeneity[END_REF]. But the mechanisms underlying these functions are not fully characterized and, in particular, it remains unclear whether or not antigen presentation occurs similarly as for αβ T cells. It has been described so far that γδ T cells are able to bind and get activated by CD1 family members, MHC and CD1 related molecules (such as T10/T22, Qa-1, MICA and EPCR), butyrophilin-like molecules and other surface-bound proteins, soluble proteins, "phosphoantigens", haptens and free peptides [START_REF] Vermijlen | gammadelta T cell responses: How many ligands will it take till we know?[END_REF]. Nevertheless, classical MHC class I and class II molecules have been as well identified as structures involved in antigen presentation [START_REF] Vermijlen | gammadelta T cell responses: How many ligands will it take till we know?[END_REF]. To conclude, further studies are necessary to fully characterize unconventional T cells.

Since all my research work was centered on peripheral conventional αβ T cells, I will therefore develop the rest of the literature review on this cell type.

B. Thymopoiesis

T cell development, also called thymopoiesis, takes place in the thymus, a bilobed primary lymphoid organ. The structure of the thymus is divided in 2 regions, histologically distinct: a peripheral cortex area and a central medullar zone. These two zones of the thymus are composed of different types of thymic epithelial cells (TEC) which play a crucial role in T cell development. T cell development is initiated by the migration into the thymus of bone marrow progenitors. This development could then be characterized by the expression of the CD4 and CD8 markers. Early thymic progenitors enter the thymus as "double negative" (DN) thymocytes as they do not express CD4 or CD8 co-receptors. In the cortex, DN thymocytes will commit into T cell lineage and differentiate into CD4 + CD8 + double positive (DP)

thymocytes. This process is tightly regulated by the interaction with the cortex thymic epithelial cells (cTEC) which allow a positive selection of the CD4 + CD8 + αβ T cells and their further differentiation into CD4 SP (single-positive) or CD8 SP T cells migrating then to the medulla [START_REF] Von Boehmer | The thymus selects the useful, neglects the useless and destroys the harmful[END_REF]. As explained previously, these thymocytes need to be tolerant to self-peptides and, to that end, negative selection takes place in order to eliminate auto-reactive thymocytes. Therefore, in the medulla, the T cell repertoire is shaped by the interaction of the TCR expressed on thymocytes with the tissue-resident antigens (TRA) which are presented by the MHC located on the surface of thymic antigen presenting antigen cells (APC) such as medullar thymic epithelial cells (mTEC) and dendritic cells (DC). TRA expression is controlled by transcriptional regulators such as AIRE (autoimmune regulator) and Fezf2 (Fez family zinc finger protein 2) [START_REF] Anderson | Projection of an immunological self shadow within the thymus by the aire protein[END_REF][START_REF] Takaba | Fezf2 Orchestrates a Thymic Program of Self-Antigen Expression for Immune Tolerance[END_REF]. Thymocytes will then be selected upon TRA presentation based on their TCR affinity. Cells that presented high affinity to self-antigens are negatively selected and eliminated (negative selection) or differentiate into a particular ab T cell population called FoxP3 + T regulatory (Treg) cells [START_REF] Hogquist | Central tolerance: learning selfcontrol in the thymus[END_REF][START_REF] Takaba | The Mechanisms of T Cell Selection in the Thymus[END_REF]) (Figure 1). FoxP3 + Treg cells play an important role in the maintenance of peripheral tolerance. The differentiation, characterization and effector function of this population is discussed in section (I 1 E a 3).

Upon thymic selection, mature SP T cells (also known as recent thymic emigrants (RTE))

exit the thymus and are incorporated into the peripheral pool as naïve T cells. The survival of these cells is notably dependent on signaling induced by MHC-self-peptide complexes/TCR interactions and interleukin (IL) 7 [START_REF] Sprent | Interleukin 7, maestro of the immune system[END_REF][START_REF] Swainson | IL-7-induced proliferation of recent thymic emigrants requires activation of the PI3K pathway[END_REF]. The homeostatic mechanisms involved in the regulation of the peripheral T cell pool will be discussed in detail in section (I 1 C b). Upon recognition of a foreign antigen specific T cell undergo a rapid activation, proliferation and effector differentiation in order to respond to this antigen. The mechanisms involved in this activation are presented in the next section. adhesion molecule and by the absence of CD25 and CD69 activation markers [START_REF] Boyman | Homeostatic proliferation and survival of naive and memory T cells[END_REF]. In humans, the differential expression of the CD45 tyrosine phosphatase isoforms is also required to identify naïve T cells. Therefore, human naïve T cells also express CD45RA and do not express CD45RO which is a memory-associated marker [START_REF] Van Den Broek | The full spectrum of human naive T cells[END_REF]. The different cell surface markers that characterize both murine and human naïve T cells are summarized on Table 1. Naïve T cells are in constant recirculation between the lymphoid organs and the blood via the lymphatic system. This circulation is possible due to the expression of CD62L and CCR7 [START_REF] Boyman | Homeostatic proliferation and survival of naive and memory T cells[END_REF]. Interference with the expression of these 2 molecules either by using mouse CD62L mutant models [START_REF] Arbones | Lymphocyte homing and leukocyte rolling and migration are impaired in L-selectin-deficient mice[END_REF] or genetic deletion of CCR7 ligands [START_REF] Link | Fibroblastic reticular cells in lymph nodes regulate the homeostasis of naive T cells[END_REF], induces a decrease in total CD4 and CD8 naïve T cell counts. These homing receptors are as well important for the recruitment of lymphocytes to the inflammatory site [START_REF] Tedder | L-selectin-deficient mice have impaired leukocyte recruitment into inflammatory sites[END_REF]. Expression of CCR7 and CD62L in naïve T cells are both FoxO1 (forkhead box O1)-and KLF2 (Kruppel-like transcription factor) 2-dependent factor [START_REF] Carlson | Kruppel-like factor 2 regulates thymocyte and T-cell migration[END_REF][START_REF] Kerdiles | Foxo1 links homing and survival of naive T cells by regulating L-selectin, CCR7 and interleukin 7 receptor[END_REF].

Naïve T cell surface markers

Murine CD62L + CCR7 + CD44 low CD25 -CD69 - __ __ Human CD62L + CCR7 + CD44 low CD25 -CD69 -CD45RA + CD45RO -

b) Naïve T cell pull maintenance

The importance of thymic input for the maintenance of the naïve T cell pool seems distinct between mouse and human (Figure 2). Despite the age-associated reduction of the thymus size on both species, the human naïve T cell pool only suffers a small reduction throughout adulthood [START_REF] Douek | Changes in thymic function with age and during the treatment of HIV infection[END_REF][START_REF] Kilpatrick | Homeostasis of the naive CD4+ T cell compartment during aging[END_REF]. Indeed, the absolute number of naïve CD4 + T-cell compartment drops only 2-3 fold with aging [START_REF] Stulnig | Reference intervals for human peripheral blood lymphocyte subpopulations from 'healthy' young and aged subjects[END_REF][START_REF] Utsuyama | Differential age-change in the numbers of CD4+CD45RA+ and CD4+CD29+ T cell subsets in human peripheral blood[END_REF]. For the maintenance of human naïve T cell pool, two mechanisms with distinct relative importance are involved (Figure 2). First of all, it's important to note that despite thymus involution; T cells are still generated in the thymus during adulthood even if the number is reduced as compared to prepubescent children [START_REF] Bertho | Phenotypic and immunohistological analyses of the human adult thymus: evidence for an active thymus during adult life[END_REF][START_REF] Jamieson | Generation of functional thymocytes in the human adult[END_REF][START_REF] Poulin | Direct evidence for thymic function in adult humans[END_REF]. However, the main mechanism regulating the maintenance of the human naïve T cell pool is extrathymic, and is based on the peripheral homeostatic proliferation of generated naïve T cells [START_REF] Harris | Multiparameter evaluation of human thymic function: interpretations and caveats[END_REF][START_REF] Jamieson | Generation of functional thymocytes in the human adult[END_REF][START_REF] Kilpatrick | Homeostasis of the naive CD4+ T cell compartment during aging[END_REF].

Indeed, and despite a 95% decrease of TRECs (TCR excision circles produced during rearrangement; which are a marker of thymus output) between 25 and 65 years of age, the frequency of cycling CD4 + T cells remain steady and their repertoire maintained highlighting the importance of homeostatic proliferation during aging [START_REF] Kilpatrick | Homeostasis of the naive CD4+ T cell compartment during aging[END_REF][START_REF] Naylor | The influence of age on T cell generation and TCR diversity[END_REF]. On the other hand, the naïve T-cell pool in mice is almost fully maintained by thymic output due to a limited role of peripheral homeostatic proliferation [START_REF] Den Braber | Maintenance of peripheral naive T cells is sustained by thymus output in mice but not humans[END_REF] (Figure 2). In contrast to humans, naïve T cell TREC content does not significantly decline in the peripheral T compartment of aging mice [START_REF] Den Braber | Maintenance of peripheral naive T cells is sustained by thymus output in mice but not humans[END_REF].

Regardless of the relative importance of the thymus output, IL-7 signaling is crucial for the survival and homeostatic proliferation of naïve T cells both in mice and humans (Figure 2).

Indeed, when this pathway is deficient, using either murine genetic models or blocking antibodies, the survival of naïve T cells is reduced [START_REF] Vivien | T lymphocytes need IL-7 but not IL-4 or IL-6 to survive in vivo[END_REF]. Mechanistically, IL-7R signaling involves both the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathways in order to target its different downstream partners [START_REF] Jiang | Cell biology of IL-7, a key lymphotrophin[END_REF][START_REF] Rochman | New insights into the regulation of T cells by gamma(c) family cytokines[END_REF]. IL-7 promotes T cell survival by increasing the expression of BCL-2 (B cell lymphoma 2) and the downregulation of pro-apoptotic factors such as BID (BH3interacting domain death agonist), BIM (BCL-2 interacting mediator of cell death) and BAD (BCL-2 antagonist of cell death) [START_REF] Jiang | Cell biology of IL-7, a key lymphotrophin[END_REF][START_REF] Wojciechowski | Bim/Bcl-2 balance is critical for maintaining naive and memory T cell homeostasis[END_REF]. In addition, the contact between TCR and peptide-MHC complexes is also important for the survival of naïve T cells [START_REF] Surh | Homeostasis of naive and memory T cells[END_REF].

D. T cell activation

Upon recognition/interaction with their cognate antigen in an adequate environment, T cells get activated, expand (clonal expansion) and differentiate into effector T cells.

a) Antigen presentation by MHC molecules

As mentioned above, APCs such as B cells, macrophages and DCs are important for antigen presentation and the latter population is considered the most important for T cell activation [START_REF] Sprent | Antigen-presenting cells. Professionals and amateurs[END_REF]. DCs were first described in 1973 [START_REF] Steinman | Identification of a novel cell type in peripheral lymphoid organs of mice. I. Morphology, quantitation, tissue distribution[END_REF] and their increased antigen presentation capacity compare to other cell types was shown later on [START_REF] Steinman | Lymphoid dendritic cells are potent stimulators of the primary mixed leukocyte reaction in mice[END_REF]. Independently of the type of APC, as pointed out above, MHC complexes are required for antigen presentation. The MHC was first characterized in mice Peripheral naïve T cell pool in mice is mainly maintained by thymic input (white cells) while in humans it is essentially maintained by the homeostatic proliferation of naïve T cells present in the periphery (black cells). For both species, both IL-7 and pMHC play a crucial role in naïve T cell survival. IL-7 (interleukin 7), pMHC (peptide-MHC complex)

after the identification of the H-2 locus as encoding for major or strong histocompatibility antigens which turned out to be the major histocompatibility locus in mice. However, over years, several different H-2 loci were identified (H2b, H2d, H2f among others) and the H-2 locus became finally the H-2 complex or the MHC in the mouse (reviewed in [START_REF] Thorsby | A short history of HLA[END_REF]).

In humans, MHC classes are encoded by the human leucocyte antigen gene complex (HLA), and are located on the chromosome 6 which is the most polymorphic gene of the human genome. The classical HLA class I genes described are the HLA-A, HLA-B and HLA-C while the classical genes described for HLA class II are HLA-DR, HLA-DQ and HLA-DP [START_REF] Mosaad | Clinical Role of Human Leukocyte Antigen in Health and Disease[END_REF][START_REF] Shiina | Comparative genomics of the human, macaque and mouse major histocompatibility complex[END_REF].

MHC proteins are divided in two classes: MHC class I and MHC class II. MHC I is expressed on almost all nucleated cells and MHC I complexes are recognized by CD8 + T cells [START_REF] Wieczorek | Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation[END_REF]. MHC I can present notably peptides from defective proteins from cell's own proteome or from invasive virus in order to induce the destruction of the damaged/infected cell. It is important to note that peptides derived from extracellular pathogens can be presented by MHC I-expressing mature DCs by a process named as cross-presentation [START_REF] Joffre | Cross-presentation by dendritic cells[END_REF]. On the other hand, MHC II expression is restricted to specific cells such as B cells, monocytes, macrophages, DCs, endothelial cells and, in humans, also in activated T cells and allows the presentation of peptides to CD4 + T cells [START_REF] Wieczorek | Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation[END_REF] Other signals are however required to obtain an optimal activation. One of them is generated from the engagement of the co-stimulatory molecules, that induce a cascade of reactions known as "signal 2". Indeed, it was shown that lack of co-stimulation upon antigen recognition induces cell anergy [START_REF] Jenkins | Antigen presentation by chemically modified splenocytes induces antigen-specific T cell unresponsiveness in vitro and in vivo[END_REF], demonstrating that antigen presentation itself is not sufficient to induce T cell activation. A well-known and important costimulatory molecule is CD28 that it is constitutively expressed in naïve CD4 and CD8 T cells.

CD28 is recruited at the immunological synapse upon priming by LCK and is able to recognize CD80-86 molecules present on the surface of APC. The cytoplasmic tail of CD28 is composed by two motifs: YMNM and PYAP. Once CD28 is activated, activation signals are transduced by these motifs resulting in the recruitment of the phosphatidylinositol 3-kinase (PI3K), protein kinase Cθ (PKCθ) and RAS guanyl nucleotide-releasing protein (RASGRP) [START_REF] Beyersdorf | CD28 co-stimulation in T-cell homeostasis: a recent perspective[END_REF]. In particular, PI3K is important for AKT (protein kinase B) activation. The CD28-PI3K-AKT pathway contributes to T cell activation, proliferation and survival through the activation of several molecular players such as the IkB kinase (IKK), nuclear factor-κB (NF-κB), nuclear factor of activated T cells (NFAT), BCL-XL and mammalian target of rapamycin (mTOR) among others [START_REF] Chen | Molecular mechanisms of T cell co-stimulation and coinhibition[END_REF][START_REF] Wells | New Insights into the Molecular Basis of T Cell Anergy: Anergy Factors, Avoidance Sensors, and Epigenetic Imprinting[END_REF]. Current evidence suggests that CD28 costimulation-mediated activation of PI3K inducing mTOR and cyclin-dependent kinases (CDKs) allows cell cycle progression and is essential for optimal T cell activation [START_REF] Powell | Inhibition of cell cycle progression by rapamycin induces T cell clonal anergy even in the presence of costimulation[END_REF].

Moreover, CD28 co-stimulation is also important to sustain IL-2-mediated proliferation which is another mechanism crucial for optimal T cell activation. Indeed, the IL-2 gene contains a CD28 responsive element (CD28RE) as well as NFAT, NF-κB and AP-1 (activator protein-1) binding sites, highlighting the importance of the CD28 pathway and its downstream partners on IL-2 secretion [START_REF] Jain | Transcriptional regulation of the IL-2 gene[END_REF][START_REF] Serfling | The architecture of the interleukin-2 promoter: a reflection of T lymphocyte activation[END_REF]. Upon CD28 activation, other co-stimulatory molecules are recruited such as 4-1BB and OX40, as well as co-inhibitory molecules such as cytotoxic T lymphocyte antigen 4 (CTLA-4).

CTLA-4 competes for the same ligands as CD28 and upon T cell activation, its upregulation induces the internalization of CD28 and suppression of T cell responses [START_REF] Rudd | CD28 and CTLA-4 coreceptor expression and signal transduction[END_REF].

CTLA-4 signaling is then a "stop signal" necessary to end contact between T cells and APCs consequently avoiding T cell over-activation and protection against the development of autoproliferation and autoimmune diseases [START_REF] Rudd | CD28 and CTLA-4 coreceptor expression and signal transduction[END_REF]. Indeed, CTLA-4-deficient mice develop a hyperproliferative syndrome and die following massive T cell tissue infiltration and organ destruction [START_REF] Tivol | Loss of CTLA-4 leads to massive lymphoproliferation and fatal multiorgan tissue destruction, revealing a critical negative regulatory role of CTLA-4[END_REF][START_REF] Waterhouse | Lymphoproliferative disorders with early lethality in mice deficient in Ctla-4[END_REF].

d) Cytokine signaling -Signal 3

An efficient T cell activation does not only require TCR engagement (signal 1), costimulation molecules (signal 2), but also cytokine signaling known as signal 3. IL-2 is one of the most important cytokines involved in T cell activation, induced upon TCR/CD28 engagement and acting in an autocrine/paracrine fashion [START_REF] Powell | Molecular regulation of interleukin-2 expression by CD28 co-stimulation and anergy[END_REF]. IL-2 binds to the IL-2 receptor (IL-2R) which can be composed by three different chains: IL-2Rα, IL-2Rβ and γc chain. IL-2 is capable to bind with low affinity to all of them and once these three subunits are together, the receptor affinity increases by a 1000 fold [START_REF] Waldmann | The multi-subunit interleukin-2 receptor[END_REF]) (Figure 4). IL-2βR is constitutively expressed in NK (natural killer), NKT (natural killer T) and memory CD8 + T cells and in naïve T cells upon TCR activation. The γc chain is expressed by all lymphoid cells [START_REF] Malek | Interleukin-2 receptor signaling: at the interface between tolerance and immunity[END_REF]. The combination of the IL-2β and γc chains forms an IL-2R with intermediate affinity that is mainly expressed on NK and memory T cells [START_REF] Liao | IL-2 family cytokines: new insights into the complex roles of IL-2 as a broad regulator of T helper cell differentiation[END_REF].

Finally, high affinity IL-2R (with high CD25 (IL-2Rα) surface expression level) is expressed on Tregs and effector T cells [START_REF] Liao | IL-2 family cytokines: new insights into the complex roles of IL-2 as a broad regulator of T helper cell differentiation[END_REF]) (Figure 4). IL-2 signaling is differently required in vitro and in vivo [START_REF] Malek | Tolerance, not immunity, crucially depends on IL-2[END_REF]. While in vitro IL-2 is essential for T cell activation, expansion and effector cell differentiation, in vivo IL-2 contributes mainly to T cell tolerance [START_REF] Malek | Tolerance, not immunity, crucially depends on IL-2[END_REF].Indeed, it was demonstrated that CD25-deficient mice (in which T cells express an IL-2R with intermediate affinity to IL-2) develop massive enlargement of peripheral lymphoid organs translating an imbalance between clonal expansion and cell death following T cell activation [START_REF] Willerford | Interleukin-2 receptor alpha chain regulates the size and content of the peripheral lymphoid compartment[END_REF]. A similar phenotype was observed in IL-2-deficient mice that developed generalized autoimmune diseases due to uncontrolled activation and proliferation of CD4 + T cells [START_REF] Sadlack | Generalized autoimmune disease in interleukin-2-deficient mice is triggered by an uncontrolled activation and proliferation of CD4+ T cells[END_REF].

Other cytokines can also play a role as signal 3. For instance, Keppler and colleagues demonstrated that, upon TCR stimulation, variable interplays of both IL-12 and IFNγ (interferon-gamma play an important role on CD8 T cell fate decision as well as in cytokine production and cytolytic activity in the context of Indiana vesiculovirus (VSV) and listeria infection [START_REF] Keppler | Signal 3 cytokines as modulators of primary immune responses during infections: the interplay of type I IFN and IL-12 in CD8 T cell responses[END_REF]. Furthermore, cytokine signaling is also important for naïve CD4 T cell differentiation in different effector T cells subsets. The role of cytokines in CD4 and CD8 T cell differentiation is going to be discussed in the next section (I 1 E). IL-2Rβ together with the IL-2γc (IL-2Rγ) forms a receptor with intermediate affinity. The combination of these two chains with the IL-2Rα generates an IL-2R with high affinity that is highly expressed notably on Tregs cell surface. IL-2Rα (CD25) cannot signal but it is able to induce conformational changes to IL-2 and increase its affinity to IL-2Rβ and IL-2 γc chains. IL (interleukin), IL-2R (IL-2 Receptor), γc (gamma common chain). Adapted from: InvivoGen review « IL-2: The Activator and the Controller »

E. Effector T cells

Effector T cells (TEFF) are a short-lived and large population containing several CD4 + and CD8 + T cell subsets. Depending on the antigen type and the surrounding environment, specific TEFF cell subsets are recruited in order to respond and clear the pathogens through the production of specific effector cytokines and mediators. Murine TEFF cells are characterized as CD44 + CD62L -. Even if human TEFF cells are not found in significant proportion at steady-state, a population of terminal effector cells (TEMRA) can be identified as CD45RA + CCR7 - [START_REF] Kumar | Human T Cell Development, Localization, and Function throughout Life[END_REF].

a) CD4 + effector T cells

Within the CD4 + TEFF cell population, several subsets can be identified including T helper 1 (Th1), T helper 2 (Th2), T helper 9 (Th9), T helper 17 (Th17), T helper 22 (Th22) cells as well as regulatory (Treg) T cells and follicular helper T cells (TFH). These subsets can be distinguished based on their cytokine profile and the expression of specific transcription factors [START_REF] Raphael | T cell subsets and their signature cytokines in autoimmune and inflammatory diseases[END_REF]. The several CD4 + TEFF cell subsets and the cytokines required for their polarization are represented on Figure 5.

Each subset previously mentioned has a different immune cell function: Th1 cells are important for immunity against intracellular pathogens while Th2 cells are in the front line against extracellular parasites. As Th2 cells, Th9 are also implicated in host defense against extracellular parasites (primarily nematodes). In their turn, Th17 cells promote protective immunity against extracellular fungi and bacteria, with special emphasis at mucosal surfaces while TFH are important for B cell class switching. Th22 cells were identified in an inflammatory skin disease context, however their role remains unclear. Finally, Treg cells are implicated in the mediation of immunosuppression and tolerogenic responses.

Since all my research work was centered on Th1, Th2 and Treg subsets, I will therefore develop the rest of the literature review on these CD4 + TEFF cell type.

T helper 1 cells

Th1 cells are involved in host defense against intracellular pathogens notably through the activation of macrophages by IFNγ production [START_REF] Szabo | Molecular mechanisms regulating Th1 immune responses[END_REF][START_REF] Zhu | T Helper Cell Differentiation, Heterogeneity, and Plasticity[END_REF]. Th1 cells can produce several types of cytokines including tumor-necrotic factor (TNF), lymphotoxin (TNFβ) and granulocyte-macrophage colony-stimulating factor (GM-CSF). However, this subset is mainly characterized by high levels of IFNγ and IL-2 secretion [START_REF] Raphael | T cell subsets and their signature cytokines in autoimmune and inflammatory diseases[END_REF][START_REF] Szabo | Molecular mechanisms regulating Th1 immune responses[END_REF].

Th1 cell lineage differentiation

Different stimulus where identified to be important for Th1 differentiation, notably TCR strength signal and DCs-mediated IL-12 cytokine signaling, the lasted being the most determinant for effective Th1 cell fate.

On one hand, the strength of the TCR signal influences lineage commitment, notably by controlling the magnitude of the Ca 2+ fluxes. In this context, Th1 cells require a stronger and specific Ca 2+ flux as compared to Th2 cells [START_REF] Sloan-Lancaster | Selective loss of the calcium ion signaling pathway in T cells maturing toward a T helper 2 phenotype[END_REF]. Furthermore, it was demonstrated that Th1 cells have a distinct requirement of lipid-rafts (cholesterol rich pockets), comparing to Th2 cells, that are important for the aggregation of molecules involved in TCR signal initiation, regulation of Ca 2+ signaling. Th1 polarized cells, upon re-activation, recruit rapidly TCR components to lipid rafts domains, resulting in a defined TCR/MHC clusters that have an increased sensitivity to low-affinity stimulation [START_REF] Bailis | Distinct modes of mitochondrial metabolism uncouple T cell differentiation and function[END_REF].

On the other hand, IL-12 cytokine signaling determinates Th1 lineage commitment by initiating a signaling cascade of events crucial for Th1 transcriptional program activation. In mice, CD8α + DCs are a IL-12 producing DC subset which preferentially induce Th1 differentiation [START_REF] Maldonado-Lopez | CD8alpha+ and CD8alpha-subclasses of dendritic cells direct the development of distinct T helper cells in vivo[END_REF][START_REF] Pulendran | Distinct dendritic cell subsets differentially regulate the class of immune response in vivo[END_REF]. Indeed, IL-12-deficient CD8α + DCs are not able to induce Th1 differentiation, underlying the importance of IL-12 secretion for CD8α + DC function [START_REF] Maldonado-Lopez | CD8alpha+ and CD8alpha-subclasses of dendritic cells direct the development of distinct T helper cells in vivo[END_REF]. In humans, a similar subset of DCs was identified. This DC subset, named DC1, does not express CD8 but secretes as well high levels of IL-12 preferentially inducing Th1 differentiation [START_REF] Collin | Human dendritic cell subsets: an update[END_REF][START_REF] Rissoan | Reciprocal control of T helper cell and dendritic cell differentiation[END_REF]. Indeed, in patients presenting a weak Th1 reactivity against melanomaassociated antigens (MAA), a strong Th1 response was restored through the stimulation of patient CD4 T cells with peptide-pulsed DC1 [START_REF] Wesa | Polarized type-1 dendritic cells (DC1) producing high levels of IL-12 family members rescue patient TH1-type antimelanoma CD4+ T cell responses in vitro[END_REF].

As mentioned above IL-12 signaling induces Th1 differentiation: IL-12 receptor is coupled to the JAK-STAT signaling pathway and activates STAT4, between others, [START_REF] Kaplan | Impaired IL-12 responses and enhanced development of Th2 cells in Stat4-deficient mice[END_REF][START_REF] Thierfelder | Requirement for Stat4 in interleukin-12-mediated responses of natural killer and T cells[END_REF] that it is important for the induction of IFNγ secretion (Figure 6). Indeed, IL-12 receptor deficient mice have a defective IL-12-induced IFNγ production [START_REF] Wu | Characterization of IL-12 receptor beta1 chain (IL-12Rbeta1)-deficient mice: IL-12Rbeta1 is an essential component of the functional mouse IL-12 receptor[END_REF]. In mice, STAT4 appeared to be skillfully specific to IL-12 [START_REF] Jacobson | Interleukin 12 signaling in T helper type 1 (Th1) cells involves tyrosine phosphorylation of signal transducer and activator of transcription (Stat)3 and Stat4[END_REF].

However, more recently, IL-23 was identified as well as STAT4 activator, even though the activation induced is substantially weaker as compared to the one induced by IL-12 [START_REF] Parham | A receptor for the heterodimeric cytokine IL-23 is composed of IL-12Rbeta1 and a novel cytokine receptor subunit, IL-23R[END_REF]. In humans, IL-12 and IFNα (interferon alpha) (specificity in human cells) can induce STAT4 activation [START_REF] Bacon | Interleukin 12 induces tyrosine phosphorylation and activation of STAT4 in human lymphocytes[END_REF] [START_REF] Cho | Activation of STAT4 by IL-12 and IFN-alpha: evidence for the involvement of ligand-induced tyrosine and serine phosphorylation[END_REF] whereas IL-23 leads to a weaker activation. [START_REF] Oppmann | Novel p19 protein engages IL-12p40 to form a cytokine, IL-23, with biological activities similar as well as distinct from IL-12[END_REF][START_REF] Parham | A receptor for the heterodimeric cytokine IL-23 is composed of IL-12Rbeta1 and a novel cytokine receptor subunit, IL-23R[END_REF]. Mechanistically, IL-23 is a heterodimeric cytokine which binds to IL-12Rβ1 (IL-12 receptor β1) chain and to the IL-23R, whose downstream signaling activates preferentially STAT3 with weak activation of STAT4.

Furthermore, IL-23 does not utilize the IL-12Rβ2 chain (expressed in IL-12R which is the crucial docking site for efficient STAT4 activation in both murine and human T cells [START_REF] Watford | Signaling by IL-12 and IL-23 and the immunoregulatory roles of STAT4[END_REF]. STAT4-mediated IFNγ secretion induces the activation of STAT1 [START_REF] Meraz | Targeted disruption of the Stat1 gene in mice reveals unexpected physiologic specificity in the JAK-STAT signaling pathway[END_REF].

Both STAT4 and STAT1 phosphorylation by IL-12 and IFNγ signaling respectively, induce the activation of the master regulator of the Th1 transcriptional program, the transcription factor T-bet (T box expressed in T cells) [START_REF] Afkarian | T-bet is a STAT1-induced regulator of IL-12R expression in naive CD4+ T cells[END_REF][START_REF] Lighvani | T-bet is rapidly induced by interferon-gamma in lymphoid and myeloid cells[END_REF][START_REF] Zhu | The transcription factor T-bet is induced by multiple pathways and prevents an endogenous Th2 cell program during Th1 cell responses[END_REF] (Figure 6). T-bet was identified for the first time in 1999 as a key transcription factor of the Th1 lineage commitment, where Szabo and colleagues showed that T-bet was a potent transactivator of the IFNγ gene [START_REF] Szabo | A novel transcription factor, T-bet, directs Th1 lineage commitment[END_REF]. T-bet is not only important for the differentiation of naïve T cell towards a Th1 fate but also plays a crucial role in suppressing the Th2 cell transcription factor, GATA3. Indeed, it was shown that T-bet is able to suppress IL-4 and GATA3 expression during T. gondii infection by promoting H3K27me3 alteration (suppressive histone marker) at the GATA3 (GATA Binding Protein 3 locus and by direct interaction with GATA3 [START_REF] Zhu | The transcription factor T-bet is induced by multiple pathways and prevents an endogenous Th2 cell program during Th1 cell responses[END_REF]. Before this study, other group had already reported that T-bet was able to repress Th2 differentiation by protein-protein interaction with GATA3 interfering with its contact with its target DNA [START_REF] Hwang | T helper cell fate specified by kinase-mediated interaction of T-bet with GATA-3[END_REF].

Th1 cell effector function

IFNγ is a potent pro-inflammatory cytokine involved in many processes. Notably, it increases the expression of toll-like receptors (TLR) by innate immune cells and as a result, their responsiveness [START_REF] Bosisio | Stimulation of toll-like receptor 4 expression in human mononuclear phagocytes by interferon-gamma: a molecular basis for priming and synergism with bacterial lipopolysaccharide[END_REF]. It also promotes MHC I and MHC II transactivation resulting in increased antigen presentation [START_REF] Butticè | Interferon-gamma induces major histocompatibility class II transactivator (CIITA), which mediates collagen repression and major histocompatibility class II activation by human aortic smooth muscle cells[END_REF][START_REF] Giroux | IFN-gamma-induced MHC class II expression: transactivation of class II transactivator promoter IV by IFN regulatory factor-1 is regulated by protein kinase C-alpha[END_REF][START_REF] Martini | IFN-gamma-mediated upmodulation of MHC class I expression activates tumor-specific immune response in a mouse model of prostate cancer[END_REF][START_REF] Vegh | Increased expression of MHC class I molecules on human cells after short time IFN-gamma treatment[END_REF]. Moreover, it induces chemokine signaling such as C-X-C motif chemokine ligand (CXCL) 9, CXCL10 and CXL11 from epithelial cells and it up-regulates the surface expression of CXCR3 (C-X-C motif chemokine receptor 3) on Th1 cells, facilitating their migration to inflammatory sites [START_REF] Rotondi | Role for interferon-gamma inducible chemokines in endocrine autoimmunity: an expanding field[END_REF]. IFNγ also primes macrophage activation and increases phagocytosis [START_REF] Schroder | Interferon-gamma: an overview of signals, mechanisms and functions[END_REF]. Studies done in interferon gamma receptor (IFNγR) -/-mice or using tumor cells expressing dominant-negative IFNγR mutations revealed the importance of IFNγ in tumor rejection [START_REF] Dighe | Enhanced in vivo growth and resistance to rejection of tumor cells expressing dominant negative IFN gamma receptors[END_REF][START_REF] Kaplan | Demonstration of an interferon gamma-dependent tumor surveillance system in immunocompetent mice[END_REF]. Indeed, Th1 cell infiltration in tumors tissue is generally associated with a good prognosis in cancer patients [START_REF] Ling | The infiltration, and prognostic importance, of Th1 lymphocytes vary in molecular subgroups of colorectal cancer[END_REF][START_REF] Tosolini | Clinical impact of different classes of infiltrating T cytotoxic and helper cells (Th1, th2, treg, th17) in patients with colorectal cancer[END_REF][START_REF] Xu | Expression of Th1-Th2-and Th17-associated cytokines in laryngeal carcinoma[END_REF]. Altogether IFNγ appears as a potent weapon in anti-tumor responses [START_REF] Ikeda | The roles of IFN gamma in protection against tumor development and cancer immunoediting[END_REF][START_REF] Schroder | Interferon-gamma: an overview of signals, mechanisms and functions[END_REF][START_REF] Tannenbaum | Immune-inflammatory mechanisms in IFNgamma-mediated anti-tumor activity[END_REF].

Dysregulations of Th1 function can be associated with several autoimmune pathologies including autoimmune type 1 diabetes (T1D), rheumatoid arthritis (RA) and multiple sclerosis (MS) [START_REF] Skurkovich | Anticytokine therapy, especially anti-interferongamma, as a pathogenetic treatment in TH-1 autoimmune diseases[END_REF]. In experimental autoimmune encephalomyelitis (EAE) studies (animal model for multiple sclerosis), it was notably demonstrated that myelinautoreactive T cells were producing high levels of IFNγ, therefore suggesting that EAE was induced because of Th1-aberrant responses [START_REF] Ando | Encephalitogenic T cells in the B10.PL model of experimental allergic encephalomyelitis (EAE) are of the Th-1 lymphokine subtype[END_REF][START_REF] Olsson | Cytokines in neuroinflammatory disease: role of myelin autoreactive T cell production of interferon-gamma[END_REF][START_REF] Renno | Selective enrichment of Th1 CD45RBlow CD4+ T cells in autoimmune infiltrates in experimental allergic encephalomyelitis[END_REF]. This model was however challenged when studies demonstrated that IFNγ-deficient [START_REF] Ferber | Mice with a disrupted IFN-gamma gene are susceptible to the induction of experimental autoimmune encephalomyelitis (EAE)[END_REF], IFNγR deficient [START_REF] Willenborg | IFNgamma plays a critical down-regulatory role in the induction and effector phase of myelin oligodendrocyte glycoprotein-induced autoimmune encephalomyelitis[END_REF], or in IL-12 [START_REF] Becher | Experimental autoimmune encephalitis and inflammation in the absence of interleukin-12[END_REF][START_REF] Gran | IL-12p35-deficient mice are susceptible to experimental autoimmune encephalomyelitis: evidence for redundancy in the IL-12 system in the induction of central nervous system autoimmune demyelination[END_REF] and IL12R deficient [START_REF] Zhang | Induction of experimental autoimmune encephalomyelitis in IL-12 receptor-beta 2-deficient mice: IL-12 responsiveness is not required in the pathogenesis of inflammatory demyelination in the central nervous system[END_REF] mice developed normal or even stronger progression of EAE compared to WT mice. In the early 2000's it was then described by several groups that IL-23 and not IL-12 was the critical cytokine for the development of EAE [START_REF] Becher | IL-23 produced by CNS-resident cells controls T cell encephalitogenicity during the effector phase of experimental autoimmune encephalomyelitis[END_REF][START_REF] Cua | Interleukin-23 rather than interleukin-12 is the critical cytokine for autoimmune inflammation of the brain[END_REF] through the action of CD4 + IL-17-producing T cells [START_REF] Langrish | IL-23 drives a pathogenic T cell population that induces autoimmune inflammation[END_REF]. These CD4 + IL-17 producing T cells were then named Th17 cells [START_REF] Bettelli | Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells[END_REF][START_REF] Harrington | Interleukin 17-producing CD4+ effector T cells develop via a lineage distinct from the T helper type 1 and 2 lineages[END_REF][START_REF] Langrish | IL-23 drives a pathogenic T cell population that induces autoimmune inflammation[END_REF][START_REF] Park | A distinct lineage of CD4 T cells regulates tissue inflammation by producing interleukin 17[END_REF] and consensually accepted as one of the main mediators of EAE.

T helper 2 cells

Th2 cells are involved in allergic and humoral immunity, with an important role in the mediation of immune responses against extracellular parasites, including helminths [START_REF] Zhu | T Helper Cell Differentiation, Heterogeneity, and Plasticity[END_REF]. This subset can produce several cytokines such as IL-4, IL-5, IL-9 and IL-13 (Walker and McKenzie, 2018) (Figure 5).

Th2 cell lineage differentiation

Th2 differentiation requires the expression of its master transcription factor: GATA 3 [START_REF] Pai | GATA-3 deficiency abrogates the development and maintenance of T helper type 2 cells[END_REF][START_REF] Zhang | Transcription factor GATA-3 is differentially expressed in murine Th1 and Th2 cells and controls Th2-specific expression of the interleukin-5 gene[END_REF][START_REF] Zheng | The transcription factor GATA-3 is necessary and sufficient for Th2 cytokine gene expression in CD4 T cells[END_REF] and its regulation is done by a combination of several and distinct molecular pathways: TCR signaling strength, CD28-co stimulation, priming by other immune cells and cytokine signaling (mainly IL-4 and IL-2).

First of all, strength of the TCR signaling was shown, in vitro, to be important for Th2 differentiation as it was demonstrated that low-dose of peptides (and not the contrary) were able to induce GATA3 [START_REF] Yamane | Independent roles for IL-2 and GATA-3 in stimulating naive CD4+ T cells to generate a Th2-inducing cytokine environment[END_REF]. Moreover, co-stimulatory molecules are also crucial for Th2 differentiation. Indeed, co-stimulation through CD86 is essential for initial IL-4 secretion (a Th2 cell-promoting cytokine) and Th2 development, while another co-stimulation molecule, CD80, seems to be less required [START_REF] De Becker | Regulation of T helper cell differentiation in vivo by soluble and membrane proteins provided by antigen-presenting cells[END_REF][START_REF] Freeman | B7-1 and B7-2 do not deliver identical costimulatory signals, since B7-2 but not B7-1 preferentially costimulates the initial production of IL-4[END_REF][START_REF] Ranger | B7-2 (CD86) is essential for the development of IL-4-producing T cells[END_REF].

Several immune subsets were demonstrated to induce Th2 differentiation through IL-4 secretion. For instance, it was demonstrated that a population of NK cells was able to secrete IL-4 and promotes the development of Th2 cells [START_REF] Yoshimoto | CD4pos, NK1.1pos T cells promptly produce interleukin 4 in response to in vivo challenge with anti-CD3[END_REF]. Moreover, basophils were also shown to be able to secrete IL-4 and induce Th2 differentiation [START_REF] Sokol | A mechanism for the initiation of allergen-induced T helper type 2 responses[END_REF][START_REF] Sokol | Basophils function as antigen-presenting cells for an allergen-induced T helper type 2 response[END_REF]. Finally, other elegant studies demonstrated that CD4 + T cells themselves are able to induce Th2 differentiation through IL-4 secretion [START_REF] Noben-Trauth | IL-4 secreted from individual naive CD4+ T cells acts in an autocrine manner to induce Th2 differentiation[END_REF][START_REF] Yamane | Independent roles for IL-2 and GATA-3 in stimulating naive CD4+ T cells to generate a Th2-inducing cytokine environment[END_REF] In contrast to Th1 cells, the role of DCs in Th2 differentiation is controversial since DCs are not commonly described to produce IL-4 [START_REF] Walker | TH2 cell development and function[END_REF] and therefore it was not consensual that DCs could mediate Th2 differentiation. However, several studies demonstrated that DCs can mediate Th2 differentiation, through IL-4-independent pathways. It was shown that the administration of peritoneal macrophages pulsed with antigen (Keyhole limpet hemocyanin) were capable to induce Th2 differentiation [START_REF] De Becker | Regulation of T helper cell differentiation in vivo by soluble and membrane proteins provided by antigen-presenting cells[END_REF].

Moreover, in humans, it was shown that Th2 differentiation was induced by DC2, using an IL-4-independent mechanism [START_REF] Rissoan | Reciprocal control of T helper cell and dendritic cell differentiation[END_REF]. More recent studies showed that CD301b + dermal dendritic cells were important to drive Th2 immunity [START_REF] Kumamoto | CD301b(+) dermal dendritic cells drive T helper 2 cell-mediated immunity[END_REF] and to prime T cells to IL-4 production upon helminth infection. Finally, other elegant studies demonstrated that DCs that express the transcription factor interferon regulatory factor 4 (IRF4) and KLF4 are crucial for Th2 induction [START_REF] Gao | Control of T helper 2 responses by transcription factor IRF4-dependent dendritic cells[END_REF][START_REF] Tussiwand | Klf4 expression in conventional dendritic cells is required for T helper 2 cell responses[END_REF][START_REF] Williams | Transcription factor IRF4 drives dendritic cells to promote Th2 differentiation[END_REF]. IRF4 targets IL-10 and IL-33 genes which are important for DC-driven Th2 differentiation [START_REF] Williams | Transcription factor IRF4 drives dendritic cells to promote Th2 differentiation[END_REF]. Unlike IRF4, the role of KLF4 is not well understood yet.

However, it remains to clarify whether IRF4-dependent and KLF4-dependent DCs polarize directly or indirectly Th2 cells [START_REF] Walker | TH2 cell development and function[END_REF].

Concerning cytokine signaling, there are two cytokines with an important role for Th2 differentiation: IL-4 and IL-2. Once IL-4 binds to its receptor, JAK-STAT signaling pathway is activated, and STAT6 is phosphorylated resulting in the induction of a set of genes including Gata3 (Kaplan et al., 1996a;[START_REF] Kurata | Ectopic expression of activated Stat6 induces the expression of Th2-specific cytokines and transcription factors in developing Th1 cells[END_REF][START_REF] Zheng | The transcription factor GATA-3 is necessary and sufficient for Th2 cytokine gene expression in CD4 T cells[END_REF]. IL-2 was also demonstrated to be involved in Th2 differentiation [START_REF] Ben-Sasson | IL-4 production by T cells from naive donors. IL-2 is required for IL-4 production[END_REF][START_REF] Gros | Generation of interleukin 4 (IL-4)-producing cells in vivo and in vitro: IL-2 and IL-4 are required for in vitro generation of IL-4-producing cells[END_REF]. Mechanistically, IL-2 is involved in STAT5 activation which consequently contributes to the stabilization of the IL-4 gene transcription [START_REF] Cote-Sierra | Interleukin 2 plays a central role in Th2 differentiation[END_REF]. C-Maf is another key player during Th2 differentiation, as it transactivates the IL-4 promoter and attenuates Th1 differentiation program [START_REF] Ho | c-maf promotes T helper cell type 2 (Th2) and attenuates Th1 differentiation by both interleukin 4-dependent and -independent mechanisms[END_REF][START_REF] Kim | The transcription factor c-Maf controls the production of interleukin-4 but not other Th2 cytokines[END_REF]. GATA3 was also described to have functions in the repression of Th1 cell differentiation program through repression of the IFNγ locus and independently of IL-4 mechanisms [START_REF] Hwang | GATA-binding protein-3 regulates T helper type 2 cytokine and ifng loci through interaction with metastasis-associated protein 2[END_REF][START_REF] Ouyang | Inhibition of Th1 Development Mediated by GATA-3 through an IL-4-Independent Mechanism[END_REF]. IL-25 and IL-33 were also reported as cytokines inducing Th2 responses [START_REF] Fort | IL-25 induces IL-4, IL-5, and IL-13 and Th2-associated pathologies in vivo[END_REF][START_REF] Saenz | Welcome to the neighborhood: epithelial cellderived cytokines license innate and adaptive immune responses at mucosal sites[END_REF][START_REF] Schmitz | IL-33, an interleukin-1-like cytokine that signals via the IL-1 receptor-related protein ST2 and induces T helper type 2-associated cytokines[END_REF].

Th2 cell effector function

Th2 cells secrete several types of cytokines which are involved in distinct functions: 1) IL-4 is important for the induction of other Th2-cytokines such as IL-5, IL-9 and IL-10 and is required for the induction of B-cell immunoglobulin (Ig) switching to IgG1 and IgE [START_REF] Kopf | Disruption of the murine IL-4 gene blocks Th2 cytokine responses[END_REF].

2) IL-5 is involved in the recruitment of eosinophils, an immune subset important to eliminate parasites and certain infections [START_REF] Coffman | Antibody to interleukin-5 inhibits helminth-induced eosinophilia in mice[END_REF].

3) IL-13 allows the induction of smooth muscle's movement and epithelial cell's mucus production [START_REF] Kuperman | Direct effects of interleukin-13 on epithelial cells cause airway hyperreactivity and mucus overproduction in asthma[END_REF][START_REF] Urban | IL-13, IL-4Ralpha, and Stat6 are required for the expulsion of the gastrointestinal nematode parasite Nippostrongylus brasiliensis[END_REF] and it is also important for IgG4 and IgE class switching and upregulation of the MHC II expression by monocytes [START_REF] Mckenzie | Interleukin 13, a T-cell-derived cytokine that regulates human monocyte and B-cell function[END_REF][START_REF] Punnonen | Interleukin 13 induces interleukin 4-independent IgG4 and IgE synthesis and CD23 expression by human B cells[END_REF]. IL-13 in combination with IL-4 can also induce alternatively activated macrophages [START_REF] Gordon | Alternative activation of macrophages[END_REF], which means that both cytokines are a sufficient stimuli and no priming is required.

Initially, Th2 cells were characterized as anti-inflammatory due their capacity to inhibit cell-mediated or Th1 models of disease [START_REF] Berger | Th1 and Th2 responses: what are they?[END_REF]. Indeed, IL-4 is known to powerfully suppress the development of Th1 cells, antagonizing Th1 cells functions [START_REF] Swain | IL-4 directs the development of Th2-like helper effectors[END_REF].

IL-4 is capable to inhibit Th1-activated macrophages and suppress the secretion of several potent pro-inflammatory cytokines [START_REF] Rocken | IL-4-induced immune deviation as antigenspecific therapy for inflammatory autoimmune disease[END_REF].

However, later on, deregulation of Th2 cells was also discovered as mediators in tissue inflammation and some immunopathologies. The pathogenic role of Th2 cells is well documented in antibody-mediated autoimmune diseases such as systemic lupus erythematosus (SLE) [START_REF] Dean | Cytokines and systemic lupus erythematosus[END_REF][START_REF] Luzina | Vasculitis in the Palmerston North mouse model of lupus: phenotype and cytokine production profile of infiltrating cells[END_REF][START_REF] Nakajima | Roles of IL-4 and IL-12 in the development of lupus in NZB/W F1 mice[END_REF]. Th2 cells are also associated with allergic/hypersensitivity immune responses. Allergen-specific Th2 cells are activated by APCs resulting in pathophysiological responses including eosinophilic inflammation, oedema, smooth muscle contraction and increased mucus production [START_REF] Garlisi | T cells are necessary for Th2 cytokine production and eosinophil accumulation in airways of antigen-challenged allergic mice[END_REF][START_REF] Larche | The role of T lymphocytes in the pathogenesis of asthma[END_REF][START_REF] Leigh | Type 2 cytokines in the pathogenesis of sustained airway dysfunction and airway remodeling in mice[END_REF][START_REF] Robinson | Predominant TH2-like bronchoalveolar T-lymphocyte population in atopic asthma[END_REF]. Th2 cytokines such as IL-4, IL-5 and IL-13 have been described as main players in murine models of allergic airway inflammation as well was in human asthma [START_REF] Umetsu | The regulation of allergy and asthma[END_REF]. It was shown that several Th2 transcription factors impact on the regulation of asthma pathology. For instance, STAT6, a downstream signal transducer of IL-4 and IL-13, is implicated in airway inflammation as STAT6-deficient mice displayed reduced eosinophil infiltration and airway hyper responsiveness and decreased mucus production [START_REF] Akimoto | Abrogation of bronchial eosinophilic inflammation and airway hyperreactivity in signal transducers and activators of transcription (STAT)6-deficient mice[END_REF].

The role of Th2 cells in anti-tumor responses is still unclear due to discrepancies in the results demonstrating either a pro-or anti-tumor activity. It was shown that IL-4 has a negative impact on tumor growth as it induces infiltration of granulocytes that are antiangiogenic [START_REF] Modesti | Ultrastructural evidence of the mechanisms responsible for interleukin-4-activated rejection of a spontaneous murine adenocarcinoma[END_REF][START_REF] Pericle | An efficient Th2-type memory follows CD8+ lymphocyte-driven and eosinophil-mediated rejection of a spontaneous mouse mammary adenocarcinoma engineered to release IL-4[END_REF][START_REF] Tepper | An eosinophil-dependent mechanism for the antitumor effect of interleukin-4[END_REF]. Similarly, IL-13 was also described to induce granulocyte-mediated tumor clearance [START_REF] Lebel-Binay | Experimental gene therapy of cancer using tumor cells engineered to secrete interleukin-13[END_REF][START_REF] Ma | Tumor cells secreting IL-13 but not IL-13Ralpha2 fusion protein have reduced tumorigenicity in vivo[END_REF]. However, IL-13-derived NKT cells were able to inhibit cytotoxic T lymphocytes (CTL) through macrophage secretion of TGF-β [START_REF] Terabe | NKT cell-mediated repression of tumor immunosurveillance by IL-13 and the IL-4R-STAT6 pathway[END_REF]. Furthermore, tumor infiltrates composed of high ratios of Th2 cells were associated with a more aggressive cancer and poorer prognosis in pancreatic cancer patients [START_REF] De Monte | Intratumor T helper type 2 cell infiltrate correlates with cancer-associated fibroblast thymic stromal lymphopoietin production and reduced survival in pancreatic cancer[END_REF][START_REF] Tassi | Carcinoembryonic antigen-specific but not antiviral CD4+ T cell immunity is impaired in pancreatic carcinoma patients[END_REF].

CD4 + regulatory T cells

Treg cells participate to the regulation of immunotolerance and control several types of immune responses, including allergy, autoimmunity, inflammation and tumor immunity [START_REF] Zhao | Tregs: Where We Are and What Comes Next?[END_REF]. In 1970, Gherson and Kondo were the first to report the existence of a T cell subset that was able to inhibit immune responses [START_REF] Gershon | Cell interactions in the induction of tolerance: the role of thymic lymphocytes[END_REF] and in 1995, Treg cells were described for the first time as a subset which expresses high levels of CD25 [START_REF] Sakaguchi | Immunologic selftolerance maintained by activated T cells expressing IL-2 receptor alpha-chains (CD25). Breakdown of a single mechanism of self-tolerance causes various autoimmune diseases[END_REF]. Few years later, FoxP3 was identified as the transcription factor controlling Treg cell development [START_REF] Fontenot | Foxp3 programs the development and function of CD4+CD25+ regulatory T cells[END_REF][START_REF] Hori | Control of regulatory T cell development by the transcription factor Foxp3[END_REF]. In the early 90's, a mouse strain, named Scurfy, developing a X-linked recessive autoimmune and inflammatory diseases due to inability to control the expansion and the reactivity of T cells was described [START_REF] Blair | CD4+CD8-T cells are the effector cells in disease pathogenesis in the scurfy (sf) mouse[END_REF][START_REF] Clark | Cellular and molecular characterization of the scurfy mouse mutant[END_REF][START_REF] Godfrey | X-linked lymphoreticular disease in the scurfy (sf) mutant mouse[END_REF]. The origin of the pathology was however not characterized at that time, but few years later, Brunkow and colleagues identified Foxp3 as the defective gene [START_REF] Brunkow | Disruption of a new forkhead/wingedhelix protein, scurfin, results in the fatal lymphoproliferative disorder of the scurfy mouse[END_REF]. Further studies showed that FoxP3 is expressed in naturally arising (thymic) CD4 + Tregs [START_REF] Hori | Control of regulatory T cell development by the transcription factor Foxp3[END_REF] correlating with the Treg deficiency in Scurfy and as well as FoxP3 null mice and explaining the fatal systemic autoimmunity developed in these mouse lines [START_REF] Fontenot | Foxp3 programs the development and function of CD4+CD25+ regulatory T cells[END_REF]. These two publications established the link between uncontrolled T cell reactivity, FoxP3 expression and Treg cells.

In humans, mutations in the Foxp3 gene also generate an impaired development or dysfunction of Treg cells, and result in the development of the immunodysregulation polyendocrinopathy enteropathy X-linked syndrome (IPEX) which is associated with severe autoimmune diseases, inflammatory bowel disease, allergy or even insulin-dependent diabetes mellitus [START_REF] Bennett | The immune dysregulation, polyendocrinopathy, enteropathy, X-linked syndrome (IPEX) is caused by mutations of FOXP3[END_REF][START_REF] Chatila | JM2, encoding a fork head-related protein, is mutated in X-linked autoimmunity-allergic disregulation syndrome[END_REF][START_REF] Gambineri | Immune dysregulation, polyendocrinopathy, enteropathy, and X-linked inheritance (IPEX), a syndrome of systemic autoimmunity caused by mutations of FOXP3, a critical regulator of T-cell homeostasis[END_REF][START_REF] Wildin | X-linked neonatal diabetes mellitus, enteropathy and endocrinopathy syndrome is the human equivalent of mouse scurfy[END_REF]. Interestingly, IPEX identification [START_REF] Powell | An X-linked syndrome of diarrhea, polyendocrinopathy, and fatal infection in infancy[END_REF] as well as FoxP3 mutation were firstly identified/characterized in humans [START_REF] Chatila | JM2, encoding a fork head-related protein, is mutated in X-linked autoimmunity-allergic disregulation syndrome[END_REF] with Bennett et al. and Wildin et al. confirming later that it was the same gene (FoxP3) which was mutated in both IPEX patients and scurfy mice [START_REF] Bennett | The immune dysregulation, polyendocrinopathy, enteropathy, X-linked syndrome (IPEX) is caused by mutations of FOXP3[END_REF][START_REF] Wildin | X-linked neonatal diabetes mellitus, enteropathy and endocrinopathy syndrome is the human equivalent of mouse scurfy[END_REF]. Therefore, the characterization of the scurfy mice brought important clues and allowed to understand this human pathology as well as Treg cell differentiation and function. Since all these discovers, Tregs have been extensively studied and over the years new findings have emerged.

Classification and nomenclature

Until now, three main types of CD4 + Treg cells have been described based on their suppressive functions: Two of them do not express FoxP3 and are IL-10-producing Tr1 (type 1 regulatory T cells) [START_REF] Bacchetta | High levels of interleukin 10 production in vivo are associated with tolerance in SCID patients transplanted with HLA mismatched hematopoietic stem cells[END_REF][START_REF] Cottrez | T regulatory cells 1 inhibit a Th2specific response in vivo[END_REF][START_REF] Groux | A CD4+ T-cell subset inhibits antigen-specific T-cell responses and prevents colitis[END_REF] and TGFβ-producing CD4 + Th3 (T helper 3) [START_REF] Chen | Regulatory T cell clones induced by oral tolerance: suppression of autoimmune encephalomyelitis[END_REF][START_REF] Weiner | Induction and mechanism of action of transforming growth factor-betasecreting Th3 regulatory cells[END_REF]. A third population characterized by CD4 + CD25 + and FoxP3 + expression is the most abundant Treg subset.

Depending on their origin, FoxP3-expressing cells can be classified as: thymus-derived Treg cells (tTreg), previously named as natural Treg cells (nTreg), and peripheral-derived Treg (pTreg) formerly called induced Treg (iTreg). The term iTreg is still used but exclusively for invitro generated Treg cells in order to distinguish them from the ones physiologically generated in vivo in the periphery [START_REF] Abbas | Regulatory T cells: recommendations to simplify the nomenclature[END_REF]. I will center my literature review on FoxP3expressing Treg cells.

Cytokine-induced signaling in Treg differentiation

In order to induce the polarization of naïve T cells to a Treg program, cytokines such as TGF-β [START_REF] Chen | Conversion of peripheral CD4+CD25-naive T cells to CD4+CD25+ regulatory T cells by TGF-beta induction of transcription factor Foxp3[END_REF][START_REF] Marie | TGF-beta1 maintains suppressor function and Foxp3 expression in CD4+CD25+ regulatory T cells[END_REF] and IL-2 are required (Figure 5). TGF-β in combination with TCR signaling results, in vitro, in the induction of Smad3 and NFAT and then FoxP3 expression [START_REF] Tone | Smad3 and NFAT cooperate to induce Foxp3 expression through its enhancer[END_REF]. As discussed above, Treg cells express high levels of cell surface expression of CD25, which means that they express an high affinity IL-2 receptor [START_REF] Sakaguchi | Immunologic selftolerance maintained by activated T cells expressing IL-2 receptor alpha-chains (CD25). Breakdown of a single mechanism of self-tolerance causes various autoimmune diseases[END_REF] indicating the important role of IL-2 in Treg cells [START_REF] Zhu | CD4 T cells: fates, functions, and faults[END_REF]. Indeed, IL-2 is important for Treg cells cycling in vivo [START_REF] Smigiel | CCR7 provides localized access to IL-2 and defines homeostatically distinct regulatory T cell subsets[END_REF]. Moreover, another study demonstrated that IL-2R-dependent activation of STAT5 is important for their suppressive function [START_REF] Chinen | An essential role for the IL-2 receptor in Treg cell function[END_REF]

FoxP3 gene and its regulation

As mentioned above, FoxP3 is a critical transcription factor for the development and function of CD4 + CD25 + Treg cells [START_REF] Fontenot | Foxp3 programs the development and function of CD4+CD25+ regulatory T cells[END_REF][START_REF] Hori | Control of regulatory T cell development by the transcription factor Foxp3[END_REF]; not only contributing to the induction of Treg transcriptional program but it is also important in the lineage stability [START_REF] Gavin | Foxp3-dependent programme of regulatory T-cell differentiation[END_REF]. The foxp3 gene has several conserved noncoding sequences, designated as conserved non-coding DNA sequence (CNS) 0-3 with each of them implicated in different signaling pathways (Figure 7). CNS0, also known as super-enhancer, is upstream of the transcriptional starting site and it is crucial for the expression of FoxP3 in Treg cells. This region is one of the binding sites for Stab1 that allows the modulation of the chromatin and the subsequent activities of the other CNS elements [START_REF] Kitagawa | Guidance of regulatory T cell development by Satb1-dependent super-enhancer establishment[END_REF].

CNS1 is the binding site for NFAT, AP-1, Smads and retinoic acid [START_REF] Tone | Smad3 and NFAT cooperate to induce Foxp3 expression through its enhancer[END_REF] and is required for TGF-β signaling mechanisms, a crucial cytokine involved in the differentiation of naïve T cells to a pTreg/iTreg fate. Indeed, CNS1 KO (knockout) mice showed a reduced differentiation of pTreg/iTreg cells through TGF-β signaling but a normal development of tTreg in the thymus [START_REF] Zheng | Role of conserved non-coding DNA elements in the Foxp3 gene in regulatory T-cell fate[END_REF].

The CNS2 enhancer is activated by TCR expression and IL-2 and contains the binding sites of other transcription factors such as STAT5, runt-related transcription factor (RUNX), CREB and FoxP3 itself [START_REF] Burchill | IL-2 receptor beta-dependent STAT5 activation is required for the development of Foxp3+ regulatory T cells[END_REF][START_REF] Kim | CREB/ATF-dependent T cell receptor-induced FoxP3 gene expression: a role for DNA methylation[END_REF][START_REF] Kitoh | Indispensable role of the Runx1-Cbfbeta transcription complex for in vivo-suppressive function of FoxP3+ regulatory T cells[END_REF][START_REF] Zhao | Tregs: Where We Are and What Comes Next?[END_REF][START_REF] Zheng | Role of conserved non-coding DNA elements in the Foxp3 gene in regulatory T-cell fate[END_REF]. Nevertheless, it was demonstrated that the activation status of this region is considerably different between tTregs and iTregs. Indeed, it was shown that tTreg cells are more stable than iTreg cells. This is in part due to the CpG islands hypomethylation pattern in the CNS2 region of the FoxP3 locus [START_REF] Feng | Control of the Inheritance of Regulatory T Cell Identity by a cis Element in the Foxp3 Locus[END_REF][START_REF] Li | Function of a Foxp3 cis-Element in Protecting Regulatory T Cell Identity[END_REF] that is maintained irrespectively of extracellular conditions, cell proliferation and FoxP3 inducing signals [START_REF] Ohkura | Development and maintenance of regulatory T cells[END_REF]. This demethylation is crucial for the recruitment of several transcription factors mentioned previously. IL-2 signals are essential for the demethylation induction of CNS2 which allows a stable FoxP3 expression and the acquisition of a Treg phenotype for iTreg cells [START_REF] Chen | IL-2 controls the stability of Foxp3 expression in TGF-beta-induced Foxp3+ T cells in vivo[END_REF][START_REF] Freudenberg | Critical Role of TGF-β and IL-2 Receptor Signaling in Foxp3 Induction by an Inhibitor of DNA Methylation[END_REF]. Conversely, in the absence of IL-2 signaling, this region is rarely demethylated in iTreg cells [START_REF] Kanamori | Induced Regulatory T Cells: Their Development, Stability, and Applications[END_REF]. Several elegant studies demonstrated that FoxP3 stability could be increased through augmented CNS2 demethylation by Ten-eleven translocation (TET) dioxygenases [START_REF] Nair | DNA Demethylation of the Foxp3 Enhancer Is Maintained through Modulation of Ten-Eleven-Translocation and DNA Methyltransferases[END_REF][START_REF] Someya | Improvement of Foxp3 stability through CNS2 demethylation by TET enzyme induction and activation[END_REF].

Finally, CNS3 is essential for FoxP3 induction during thymic and induced Treg cell differentiation by enrolling c-Rel and other transcription factors [START_REF] Zheng | Role of conserved non-coding DNA elements in the Foxp3 gene in regulatory T-cell fate[END_REF]. The noncoding regions and its regulation is represented on Figure 7.

Despite the importance of FoxP3, other studies demonstrated that ectopic retroviral transduction of FoxP3 in T conventional (Tconv) cells failed to recapitulate certain Treg cell gene signatures [START_REF] Hill | Retinoic acid enhances Foxp3 induction indirectly by relieving inhibition from CD4+CD44hi Cells[END_REF][START_REF] Sugimoto | Foxp3-dependent and -independent molecules specific for CD25+CD4+ natural regulatory T cells revealed by DNA microarray analysis[END_REF], highlighting that FoxP3 + cells are not always functional Tregs and also, that certain signature molecules can be expressed in absence of FoxP3 expression. Indeed, and even if FoxP3 is a master regulator of Treg development, other findings suggest that FoxP3 expression per se might not be sufficient for lineage maintenance, Treg suppressive functions or even for Treg cell phenotyping. For example, human Tconv cells, unlike murine cells, express FoxP3 transiently and at low levels upon TCR activation, without showing suppressive functions [START_REF] Allan | Activation-induced FOXP3 in human T effector cells does not suppress proliferation or cytokine production[END_REF]. Furthermore, in human blood, three phenotypically and functionally distinct subsets that express FoxP3 TGF-β induces Smad2/3 activation and its recruitment to CNS1 region which is crucial to induce Treg differentiation. TCR activation and IL-2 signaling activate CREB and STAT5, respectively, activating the CNS2 enhancer which is a binding site for RUNX and FoxP3 itself. This region is hypomethylated in tTregs (major TSDR) and heavily methylated in recently generated iTregs causing FoxP3 instability. CNS3 region is activated through TCR/CD28 signaling which induces cREL activity which contributes to FoxP3 induction in nTregs, pTregs and iTregs. AP-1 (activator protein), CREB (C-AMP Response Element-binding protein) JAK (Janus kinase), NFAT (nuclear factor of activated T cells), RUNX (Runtrelated transcription factor), STAT (signal transducer and activator of transcription), TCR (T cell receptor), TGF (transforming growth factor), TSDR (Treg-specific demethylated region) [START_REF] Kanamori | Induced Regulatory T Cells: Their Development, Stability, and Applications[END_REF].

were described and not all of them showed suppressive functions: CD45RA + FoxP3 low (resting Treg cells) and CD45RA -FoxP3 high (activated Treg cells) were proved to be suppressive in vitro while CD45RA -FoxP3 low where non-suppressive T cells [START_REF] Miyara | Functional delineation and differentiation dynamics of human CD4+ T cells expressing the FoxP3 transcription factor[END_REF]. Furthermore, CD45RA -FoxP3 high cells show a fully demethylated CNS2 while FoxP3 low non-Treg cells have been described with only a partially demethylated CNS2 region.

Treg suppressive mechanisms

Treg cells can mediate suppressive functions through different mechanisms including the direct targeting of DCs, through cytolysis and metabolic disruption and also through secretion of suppressive cytokines (Figure 8). The most predominant suppressive mechanism is the inhibition of DCs through CTLA-4. CTLA-4 shares with CD28 two ligands (CD80 and CD86) and it was shown that CTLA-4 binding was able to induce trans-endocytosis of both CD80 and CD86 [START_REF] Qureshi | Trans-endocytosis of CD80 and CD86: a molecular basis for the cell-extrinsic function of CTLA-4[END_REF]. Treg cells express high CTLA-4 surface levels and several studies demonstrated that both in vivo and in vitro Treg suppressive functions could be reversed by blocking CTLA-4 [START_REF] Read | Cytotoxic T lymphocyte-associated antigen 4 plays an essential role in the function of CD25(+)CD4(+) regulatory cells that control intestinal inflammation[END_REF][START_REF] Takahashi | Immunologic self-tolerance maintained by CD25(+)CD4(+) regulatory T cells constitutively expressing cytotoxic T lymphocyte-associated antigen 4[END_REF]. Selective deletion of CTLA-4 results in autoimmune diseases and potent anti-tumor immunity [START_REF] Wing | CTLA-4 control over Foxp3+ regulatory T cell function[END_REF]. CLTA-4 can also stimulate the expression of the enzyme indoleamine 2,3-dyoxyegenase (IDO) by DCs resulting in tryptophan depletion in T cell environment, a known immunoregulator mechanism [START_REF] Grohmann | CTLA-4-Ig regulates tryptophan catabolism in vivo[END_REF][START_REF] Munn | Inhibition of T cell proliferation by macrophage tryptophan catabolism[END_REF]. Furthermore, Treg cells can also deliver negative signals to responder T cells by inducing an up-regulation of intracellular cyclic adenosine mono phosphate (cAMP) [START_REF] Bopp | Cyclic adenosine monophosphate is a key component of regulatory T cell-mediated suppression[END_REF] and through the generation of pericellular adenosine catalyzed by CD39 (ectonucleoside triphosphate diphosphohydrolase 1) and CD73 (ecto-5'-nucleotidase) found on Tregs cell surface. [START_REF] Bopp | Cyclic adenosine monophosphate is a key component of regulatory T cell-mediated suppression[END_REF][START_REF] Grant | Regulatory Tcells in autoimmune diseases: challenges, controversies and--yet--unanswered questions[END_REF]. All these mechanisms can induce a metabolic disruption in Tconv cells. How metabolic changes impact T cell activation, differentiation and effector function will be discussed in detail in section III. Treg cells can as well secrete several types of inhibitory cytokines like TGF-β, IL-10 and IL-35 which are able to inhibit the differentiation, proliferation and activation of TEFF cells in addition to their cytokine secretion [START_REF] Asseman | An essential role for interleukin 10 in the function of regulatory T cells that inhibit intestinal inflammation[END_REF][START_REF] Collison | The inhibitory cytokine IL-35 contributes to regulatory T-cell function[END_REF][START_REF] Fahlen | T cells that cannot respond to TGF-beta escape control by CD4(+)CD25(+) regulatory T cells[END_REF][START_REF] Marie | TGF-beta1 maintains suppressor function and Foxp3 expression in CD4+CD25+ regulatory T cells[END_REF]. Furthermore, TGF-β is likewise able to induce the conversion of naïve cells towards suppressor T cells [START_REF] Chen | Conversion of peripheral CD4+CD25-naive T cells to CD4+CD25+ regulatory T cells by TGF-beta induction of transcription factor Foxp3[END_REF]. In addition, Treg cells suppress polyclonal T cell activation by inhibiting IL-2 production [START_REF] Thornton | CD4+CD25+ immunoregulatory T cells suppress polyclonal T cell activation in vitro by inhibiting interleukin 2 production[END_REF].

Moreover, another study proposed a different mechanism where Treg cells, due to their expression of high affinity IL-2R, 'steal' IL-2 produced by other cells and consequently limits the survival and proliferation of other T cells [START_REF] Pandiyan | CD4+CD25+Foxp3+ regulatory T cells induce cytokine deprivation-mediated apoptosis of effector CD4+ T cells[END_REF]. Therefore, the role of IL-2 in Treg suppression activity is still under debate. Finally, Treg cells can induce T cell cytotoxicity by perforin-dependent or granzyme B-dependent mechanisms [START_REF] Cao | Granzyme B and perforin are important for regulatory T cell-mediated suppression of tumor clearance[END_REF][START_REF] Gondek | Cutting edge: contact-mediated suppression by CD4+CD25+ regulatory cells involves a granzyme Bdependent, perforin-independent mechanism[END_REF].

On one hand, it is widely accepted that defects in Treg function are associated with the pathogenesis of autoimmune diseases in humans [START_REF] Long | CD4+FOXP3+ T regulatory cells in human autoimmunity: more than a numbers game[END_REF]. Autoimmune diseases develop due to reduced frequencies of Treg cells and/or Treg dysfunctions resulting in the lack of control of auto-reactive effector T cells [START_REF] Grant | Regulatory Tcells in autoimmune diseases: challenges, controversies and--yet--unanswered questions[END_REF]. For instance, defective FoxP3 + Treg function can result in T1D development, an autoimmune disease characterized by insulin producing beta cells destruction [START_REF] Hull | Regulatory T cell dysfunction in type 1 diabetes: what's broken and how can we fix it?[END_REF]. On the other hand, given their suppressive properties, Tregs can have a pro-tumor function as demonstrated notably by the poor prognosis associated with the tumor infiltration of this T cell subset [START_REF] Bates | Quantification of regulatory T cells enables the identification of high-risk breast cancer patients and those at risk of late relapse[END_REF][START_REF] Curiel | Specific recruitment of regulatory T cells in ovarian carcinoma fosters immune privilege and predicts reduced survival[END_REF][START_REF] Hiraoka | Prevalence of FOXP3+ regulatory T cells increases during the progression of pancreatic ductal adenocarcinoma and its premalignant lesions[END_REF][START_REF] Hou | Age-related changes in CD4+CD25+FOXP3+ regulatory T cells and their relationship with lung cancer[END_REF][START_REF] Ormandy | Increased populations of regulatory T cells in peripheral blood of patients with hepatocellular carcinoma[END_REF][START_REF] Wolf | Increase of regulatory T cells in the peripheral blood of cancer patients[END_REF]. In this context, the depletion of Treg cells represents therefore an interesting strategy which appeared to be efficient in several studies [START_REF] Kurose | Phase Ia Study of FoxP3+ CD4 Treg Depletion by Infusion of a Humanized Anti-CCR4 Antibody, KW-0761, in Cancer Patients[END_REF][START_REF] Mahne | Dual Roles for Regulatory T-cell Depletion and Costimulatory Signaling in Agonistic GITR Targeting for Tumor Immunotherapy[END_REF][START_REF] Soares | TGF-beta blockade depletes T regulatory cells from metastatic pancreatic tumors in a vaccine dependent manner[END_REF]. Due to the importance of CTLA-4 in the mediation of Treg suppressive functions, it is also important to highlight the contribution of the anti-CTLA-4 immunotherapies (such as ipilimumab) in cancer treatment [START_REF] Seidel | Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations[END_REF] .

b) CD8 + effector T cells

As CD4 + effector T cells, CD8 + effector T cell are divided into several types depending on the profile of the cytokines secreted and the expression of transcription factors: T cytotoxic 1 (Tc1-also known as cytotoxic T cells (CTLs), T cytotoxic 2 (Tc2), T cytotoxic 9 (Tc9), T cytotoxic 17 (Tc17) and CD8 + Treg cells. Each subset contributes specifically to immune responses. Despite this heterogeneity already described, CTLs are the best-characterized subpopulation and I will focus on this CD8 + effector T cell subset.

CTLs play an important role in the clearance of intracellular pathogens and in the killing of malignant cells. Due to their cytotoxic capacity, CTLs are able to kill cells by releasing cytotoxic molecules like granzymes and perforin into the immunological synapse and secrete cytokines such as IFNγ and TNF-α [START_REF] Mittrucker | Heterogeneity in the differentiation and function of CD8(+) T cells[END_REF]. CTLs are well known for their anti-tumor function due to their secretion of IFNγ, TNFα, perforin and granzymes [START_REF] Reiser | Effector, Memory, and Dysfunctional CD8(+) T Cell Fates in the Antitumor Immune Response[END_REF]. Indeed, CD8 + T cells tumor infiltration correlates with good prognosis in many types of cancer such as glioblastoma, lung, breast and colorectal tumors [START_REF] Djenidi | CD8+CD103+ tumor-infiltrating lymphocytes are tumor-specific tissue-resident memory T cells and a prognostic factor for survival in lung cancer patients[END_REF][START_REF] Galon | Type, density, and location of immune cells within human colorectal tumors predict clinical outcome[END_REF][START_REF] Kmiecik | Elevated CD3+ and CD8+ tumor-infiltrating immune cells correlate with prolonged survival in glioblastoma patients despite integrated immunosuppressive mechanisms in the tumor microenvironment and at the systemic level[END_REF]. CTL differentiation requires the combination of several and distinct cellular and molecular pathways such as DC antigen presentation, cytokine and chemokine signaling and transcription factor activation.

Antigen presentation by DCs to CD8 + T cells is important for the acquisition of effector functions. In particular, CD8α + DCs (as mentioned in (section I 1 E a 1.1), the IL-12 secreting DC subset implicated in Th1 differentiation), play a crucial role in the antigen presentation to CD8 + T cells mainly through the receptor pair XCL1-XCR1. XCR1 (X-C motif chemokine receptor 1) is highly expressed on CD8α + DCs while its ligand XCL1 (X-C motif chemokine ligand 1) is produced by activated CD8 + T cells (Figure 9). Upon TCR activation, this interaction plays a role to reach maximal priming and expansion of CD8 + T cells [START_REF] Dorner | Selective expression of the chemokine receptor XCR1 on cross-presenting dendritic cells determines cooperation with CD8+ T cells[END_REF]. Moreover, certain chemokines such as CCL (C-C motif chemokine ligand) 3, CCL4 and CCL17 secreted by DCs upon interaction either with CD4 + or NK cells can attract cognate CCR5 + and CCR4 + naïve CD8 + T cells in a process called cross-priming [START_REF] Castellino | Chemokines enhance immunity by guiding naive CD8+ T cells to sites of CD4+ T celldendritic cell interaction[END_REF][START_REF] Semmling | Alternative cross-priming through CCL17-CCR4-mediated attraction of CTLs toward NKT cell-licensed DCs[END_REF].

Several transcription factors are required for effector differentiation (Figure 9). T-bet is one of the transcription factors required for the effector functions and it's highly expressed in SLEC (short lived effector cells). [START_REF] Intlekofer | Effector and memory CD8+ T cell fate coupled by T-bet and eomesodermin[END_REF][START_REF] Joshi | Inflammation directs memory precursor and short-lived effector CD8(+) T cell fates via the graded expression of T-bet transcription factor[END_REF]. Blimp-1 (also known as PR domain zinc finger protein 1) is another transcription factor required for terminal differentiation, crucial for the repression of central memory properties acquisition [START_REF] Kallies | Blimp-1 transcription factor is required for the differentiation of effector CD8(+) T cells and memory responses[END_REF][START_REF] Rutishauser | Transcriptional repressor Blimp-1 promotes CD8(+) T cell terminal differentiation and represses the acquisition of central memory T cell properties[END_REF]. The IRF4 is another transcription factor required for CTL differentiation. IRF4 is not only indispensable for early activation but also crucial for sustained expansion and effector differentiation as it is involved in the expression and function of T-bet and Blimp-1 [START_REF] Raczkowski | The transcription factor Interferon Regulatory Factor 4 is required for the generation of protective effector CD8+ T cells[END_REF][START_REF] Yao | Interferon regulatory factor 4 sustains CD8(+) T cell expansion and effector differentiation[END_REF]. DNA binding 2 (Id2) is as well upregulated in CD8 + T cells upon infection. Despite the fact that Id2-deficient naïve T cells are able to differentiate into effector cells, these cells are more susceptible to apoptosis which impacts on the accumulation of CD8 + effector T cells [START_REF] Cannarile | Transcriptional regulator Id2 mediates CD8+ T cell immunity[END_REF]. Therefore, Id2 is not necessary for CTL differentiation but instead for the magnitude of the effector responses.

In addition to transcription factors, cytokine signaling is also required for CTL differentiation and function (Figure 9). IL-12 is essential for the terminal effector differentiation of CTLs. Mechanistically, IL-12 induces T-bet expression [START_REF] Curtsinger | Signal 3 determines tolerance versus full activation of naive CD8 T cells: dissociating proliferation and development of effector function[END_REF][START_REF] Joshi | Inflammation directs memory precursor and short-lived effector CD8(+) T cell fates via the graded expression of T-bet transcription factor[END_REF] and can also repress Eomes (a memory T cell transcription factor) [START_REF] Takemoto | Cutting Edge: IL-12 inversely regulates T-bet and eomesodermin expression during pathogen-induced CD8+ T cell differentiation[END_REF]. Signaling mediated by IL-2 is also required for CTL effector function.

IL-2 is mainly produced by CD4 + T cells while activated CD8 + T cells secrete lower amounts [START_REF] Malek | Interleukin-2 receptor signaling: at the interface between tolerance and immunity[END_REF]. Activated CD4 + T cells instruct DCs to produce IL-12 which induces CD25 expression in CD8 T cells, allowing the expression of high affinity IL-2R which increase the responsiveness to IL-2 [START_REF] Obar | CD4+ T cell regulation of CD25 expression controls development of short-lived effector CD8+ T cells in primary and secondary responses[END_REF][START_REF] Wiesel | Th cells act via two synergistic pathways to promote antiviral CD8+ T cell responses[END_REF]. Several elegant studies demonstrated that persistent IL-2 stimulation is needed for promoting terminal-effector differentiation [START_REF] Kalia | Prolonged interleukin-2Ralpha expression on virus-specific CD8+ T cells favors terminaleffector differentiation in vivo[END_REF][START_REF] Pipkin | Interleukin-2 and inflammation induce distinct transcriptional programs that promote the differentiation of effector cytolytic T cells[END_REF].Finally, IL-2 through STAT5 activation regulates as well T-bet and Eomes expression [START_REF] Grange | Active STAT5 regulates T-bet and eomesodermin expression in CD8 T cells and imprints a T-bet-dependent Tc1 program with repressed IL-6/TGF-beta1 signaling[END_REF].

F. Memory T cells

Memory T cells are able to rapidly produce cytokines upon antigen restimulation and respond rapidly to antigens stimulation, which is what make this T cell subset crucial in immediate protection in peripheral tissues and in rapid responses in secondary lymphoid organs. The origin of memory T cells is still a subject of debate with several studies done in CD8 + T cells proposing two different models represented in the figure below (Figure 10) [START_REF] Arsenio | Early specification of CD8+ T lymphocyte fates during adaptive immunity revealed by single-cell gene-expression analyses[END_REF][START_REF] Flossdorf | CD8+ T cell diversification by asymmetric cell division[END_REF][START_REF] Joshi | Effector CD8 T Cell Development: A Balancing Act between Memory Cell Potential and Terminal Differentiation[END_REF][START_REF] Restifo | Lineage relationship of effector and memory T cells[END_REF]. In this literature review I will not detail the discovers done on that matter and I will focus on memory T cell phenotype and functions. The ON-OFF-ON/ OFF-ON-OFF model proposes that memory T cells have always effector T cells as precursors. The developmental model on the other hand, defends that memory cells can be directly generated from naïve T cells [START_REF] Restifo | Lineage relationship of effector and memory T cells[END_REF] Several transcription factors are required for memory T cell differentiation. For instance, B-cell lymphoma 6 protein (BCL-6) in one of the transcription factor involved in the generation and maintenance of memory CD8 + T cells [START_REF] Ichii | Role for Bcl-6 in the generation and maintenance of memory CD8+ T cells[END_REF] as well T cell factor 1 (TCF-1) [START_REF] Zhou | Differentiation and persistence of memory CD8(+) T cells depend on T cell factor 1[END_REF]), FoxO1 (Hess Michelini et al., 2013;[START_REF] Kim | The transcription factor Foxo1 controls central-memory CD8+ T cell responses to infection[END_REF][START_REF] Tejera | FoxO1 controls effector-to-memory transition and maintenance of functional CD8 T cell memory[END_REF] and Id3 [START_REF] Ji | Repression of the DNA-binding inhibitor Id3 by Blimp-1 limits the formation of memory CD8+ T cells[END_REF]. Finally, T-box brain protein 2 or Eomesodermin (Eomes) is also involved for memory differentiation [START_REF] Intlekofer | Effector and memory CD8+ T cell fate coupled by T-bet and eomesodermin[END_REF][START_REF] Pipkin | Interleukin-2 and inflammation induce distinct transcriptional programs that promote the differentiation of effector cytolytic T cells[END_REF].

Memory T cells are highly heterogeneous in regards to their surface-receptor expression, effector function, location and trafficking properties. In 1999, the classification of circulating memory T cells was revisited and gave rise to a division of this vast T cell subset into two distinct groups: T central memory (TCM) and T effector memory (TEM) [START_REF] Sallusto | Two subsets of memory T lymphocytes with distinct homing potentials and effector functions[END_REF].

The TCM and TEM subsets, even if initially described in humans, were rapidly demonstrated to have parallels in mice [START_REF] Huster | Selective expression of IL-7 receptor on memory T cells identifies early CD40Ldependent generation of distinct CD8+ memory T cell subsets[END_REF][START_REF] Masopust | Preferential localization of effector memory cells in nonlymphoid tissue[END_REF][START_REF] Reinhardt | Visualizing the generation of memory CD4 T cells in the whole body[END_REF][START_REF] Wherry | Lineage relationship and protective immunity of memory CD8 T cell subsets[END_REF]. More recently, a population of non-circulating memory T cells known as tissue resident memory T cells (TRM) was also described and will be discussed later on in this section.

Despite their differences, few markers are expressed on both TCM and TEM. On humans, TCM and TEM cells are characterized as CD45RO + CD45RA - [START_REF] Merkenschlager | Evidence for differential expression of CD45 isoforms by precursors for memory-dependent and independent cytotoxic responses: human CD8 memory CTLp selectively express CD45RO (UCHL1)[END_REF][START_REF] Sanders | Human memory T lymphocytes express increased levels of three cell adhesion molecules (LFA-3, CD2, and LFA-1) and three other molecules (UCHL1, CDw29, and Pgp-1) and have enhanced IFN-gamma production[END_REF][START_REF] Smith | Functional subsets of human helper-inducer cells defined by a new monoclonal antibody, UCHL1[END_REF]) (Table 2). Both murine and human TCM and TEM express CD44 that is a carbohydrate-binding type 1 transmembrane protein involved in cell adhesion and migration to inflammatory sites [START_REF] Baaten | Regulation of Antigen-Experienced T Cells: Lessons from the Quintessential Memory Marker CD44[END_REF][START_REF] Camp | CD44 is necessary for optimal contact allergic responses but is not required for normal leukocyte extravasation[END_REF][START_REF] Nandi | Bimolecular complex between rolling and firm adhesion receptors required for cell arrest; CD44 association with VLA-4 in T cell extravasation[END_REF].

Its signaling promotes cytoskeletal changes required for T cell extravasation from blood into tissues and its expression is also associated with T cell activation.

To distinguish between TCM and TEM in humans, a combination of surface markers are used: TCM are characterized as CD62L + , CCR7 + CD127 + , CD69 -and CD103 -(αE integrin -) [START_REF] Mueller | Memory T cell subsets, migration patterns, and tissue residence[END_REF]) (Table 2) and they have the ability to rapidly respond to secondary contacts with a cognate antigen. This subset can be found in lymph nodes, spleen, blood and bone marrow mainly because of the expression of lymphoid homing receptor ligands that allows the passage of TCM into the LN through specialized high endothelial venules (HEV) [START_REF] Gowans | The route of re-circulation of lymphocytes in the rat[END_REF]. Endothelial cells express CCL19 and CCL21 which are recognized by CCR7expressing T cells, allowing their extravasation and migration into the T cell zone [START_REF] Okada | CC chemokine receptor 7 contributes to Gi-dependent T cell motility in the lymph node[END_REF][START_REF] Worbs | CCR7 ligands stimulate the intranodal motility of T lymphocytes in vivo[END_REF]. The binding of CD62L to the peripheral lymph node addressin (PNAd) is another mechanism leading to T cell trafficking into LN [START_REF] Butcher | Lymphocyte homing and homeostasis[END_REF]. Despite the fact that they have little/no effector function, TCM cells can proliferate quickly and give origin to an effector response upon antigenic stimulation [START_REF] Sallusto | Central Memory and Effector Memory T Cell Subsets: Function, Generation, and Maintenance[END_REF]. TCM cells can produce high levels of IL-2, but they also can secrete IFNγ and TNFα at moderate levels [START_REF] Farber | Human memory T cells: generation, compartmentalization and homeostasis[END_REF][START_REF] Sallusto | Two subsets of memory T lymphocytes with distinct homing potentials and effector functions[END_REF].

Unlike TCM, TEM are essentially located in peripheral tissues and are dedicated to immediate effector response [START_REF] Sallusto | Central Memory and Effector Memory T Cell Subsets: Function, Generation, and Maintenance[END_REF]. TEM are characterized as CD62L -, CCR7 - CD127 + , CD69 -and CD103 -(Table 2) and they can be found in spleen and blood but also in non-lymphoid organs including liver, lung, intestinal tract, reproductive tract, kidney, adipose tissue and heart [START_REF] Mueller | Memory T cell subsets, migration patterns, and tissue residence[END_REF]. TEM cells can produce high levels of IFNγ and TNFα but they can also secrete IL-2 at moderate levels [START_REF] Farber | Human memory T cells: generation, compartmentalization and homeostasis[END_REF][START_REF] Sallusto | Two subsets of memory T lymphocytes with distinct homing potentials and effector functions[END_REF].

Apart of TCM and TEM, other memory T cell subsets were described. As previously mentioned, TRM define a population of non-circulating memory cells that can permanently reside in peripheral tissues after infection clearance [START_REF] Masopust | Dynamic T cell migration program provides resident memory within intestinal epithelium[END_REF][START_REF] Masopust | Preferential localization of effector memory cells in nonlymphoid tissue[END_REF]. Most TRM are CD103 + CD69 + [START_REF] Schenkel | Tissue-resident memory T cells[END_REF], although in certain tissues such as the lamina propria, brain parenchyma, salivary glands and female reproductive tract they can be CD103 -or/and CD69 - [START_REF] Takamura | Niches for the Long-Term Maintenance of Tissue-Resident Memory T Cells[END_REF][START_REF] Topham | Tissue-Resident Memory CD8(+) T Cells: From Phenotype to Function[END_REF]. TRM cells can also be characterized by the expression of CD49a, an integrin which is an adhesion molecule. Furthermore, as the other memory T cell subsets, TRM express CD44 [START_REF] Amsen | Tissue-resident memory T cells at the center of immunity to solid tumors[END_REF]. The study of human TRM has been more challenging as it requires the study of human tissues and there are no in vitro systems optimized so far for this purpose. Despite the difficulties, several studies contributed already to the description of this memory T cell population in humans, as review in [START_REF] Steinbach | Resident-Memory T Cells in Tissue-Restricted Immune Responses: For Better or Worse[END_REF]. TRM are important in response to infections in nonlymphoid tissues and its presence have been associated to a good prognosis in cancer patients. Dysfunction on TRM responses have been associated with certain chronic inflammatory diseases such as MS [START_REF] Steinbach | Resident-Memory T Cells in Tissue-Restricted Immune Responses: For Better or Worse[END_REF]. TRM cell surface markers are summarized in table 2.

Stem cell memory T cells (TSCM)

. is another memory T cell subset described which, interestingly, shares common markers with naïve T cells (CD45RA, CD62L and CCR7).

However, it can be distinguished from naïve T cells based on the expression of CD95, CD122, CXCR3 and the integrin CD11a (LFA-1) [START_REF] Fuertes Marraco | Long-lasting stem celllike memory CD8+ T cells with a naive-like profile upon yellow fever vaccination[END_REF][START_REF] Gattinoni | A human memory T cell subset with stem cell-like properties[END_REF][START_REF] Gattinoni | T memory stem cells in health and disease[END_REF] They have high proliferative capacity and they can further differentiate into other T cell subsets such as TCM and TEM [START_REF] Gattinoni | A human memory T cell subset with stem cell-like properties[END_REF].

During this section, I reviewed and highlighted the role of antigen presentation, TCR, costimulation and cytokine signaling and also gene regulation on T cell activation, differentiation and effector function. Though, there are other factors that can impact and shape T cell function, notably the metabolic environment which was the main subject of research during my PhD. Therefore, the next sections are going to be centered on the impact of the metabolic environment on T cell activation, differentiation and effector function.

T central memory (TCM) T effector memory (TEM) Tissue Resident memory (TRM)

Mouse Human Mouse Human Mouse Human

CD62L + CD62L + CD62L - CD62L - CD62L - CD62L - CCR7 + CCR7 + CCR7 - CCR7 - CCR7 - CCR7 - CD44 + CD44 + CD44 + CD44 + CD44 + ? CD69 - CD69 - CD69 - CD69 - CD69 + CD69 + - CD45RO + - CD45RO + - ? - CD45RA - - CD45RA - - ? CD103 - CD103 - CD103 - CD103 - CD103 + CD103 + CD49a - CD49a - CD49a - CD49a - CD49a + CD49a +

II. Metabolism

General concepts

Proliferating and differentiating cells have increased requirements of energy and "building blocks". These requirements are essentially fulfilled by the metabolism of essential nutrients like glucose, glutamine, other amino acids and lipids. Energy-sensing mechanisms that allow the detection of nutrient availability as well as energy levels regulate several metabolic pathways. They engage anabolic reactions in nutrient-replete condition whereas catabolic reactions are triggered when nutrients and energy are scarce, in a process called metabolic reprogramming. Amongst several energy sensing pathways, two are particularly implicated in T cell differentiation and function: mTOR and the 5' adenosine monophosphateactivated protein kinase (AMPK).

During my thesis, I studied the role of different metabolic/ energy sensing pathways and their impact on T cell differentiation and effector function. Therefore, in this part II will provide a general overview about the metabolic pathways. In part III, I will discuss in more detail the literature regarding the metabolic pathways implicated in T cell biology.

1) Glycolysis and the pentose phosphate pathway

The glycolytic pathway, commonly referred as glycolysis, starts with the uptake of extracellular glucose. It is essentially mediated by two major families of transporters, GLUT (glucose transporters) and SGLTs (sodium-glucose-linked transporters). Once in the cell, glucose is metabolized by hexokinase (HK) to glucose-6-phosphate (G6P), a metabolite that can be further used either in the pentose phosphate pathway (PPP) or in the glycolytic pathway (Figure 11).

In the first situation, G6P can enter through the oxidative branch of PPP resulting in the production of reduced nicotinamide adenine dinucleotide phosphate (NADPH), crucial for glutathione reduction and fatty acid synthesis. Moreover, the PPP is the only source of Ribose-5-phosphate indispensable for nucleotide formation and amino acid precursors. Glycolysis is also linked with the PPP through its non-oxidative branch. In this case, the PPP is fulfilled through fructose-6-phosphate (F6P) and glyceraldedehyde-3-phospate (G3P) (another intermediates of the glycolysis pathway) resulting also in the generation of Ribose-5phosphate, without production of NADPH (Figure 11).

In the second situation, glucose-6-phosphate, after multistep-reactions, is converted into two molecules of pyruvate along with the production of two molecules of reduced nicotinamide adenine dinucleotide (NADH) and four molecules of adenosine triphosphate (ATP), however two of them are used to restart another round of glycolysis (Figure 11).

Pyruvate can then either be reduced into lactate through the lactate dehydrogenase (LDH)

(to maintain the glycolytic flux by upholding the oxidized nicotinamide adenine dinucleotide (NAD + ) levels) or enter directly into the tricarboxylic acid (TCA) cycle as acetyl coenzyme A (acetyl-coA) (discussed in the next section). Unexpectedly, lactate can be produced as well in aerobic conditions in response to mitogenic or inflammatory signals and this process is called aerobic glycolysis. This phenomenon, initially described in cancer cells, was described by Otto

Warburg and is known as "Warburg effect" [START_REF] Warburg | Metabolism of leukocytes][END_REF][START_REF] Warburg | The transformation of embryonal metabolism in cancer metabolism[END_REF].

Glycolysis is not the most efficient metabolic pathway in terms of ATP production.

However, it can be rapidly activated and quickly produce several intermediates important for a rapid cell growth. These intermediates are not only important to fulfill the PPP and the TCA cycle but they also represent biomass elements for the synthesis of serine, glycine and alanine. Glycolysis can also provide dihydroxyacetone phosphate (DHAP) important for glycerol generation that is important for the cell membrane structure. [START_REF] Gaber | Metabolism of T Lymphocytes in Health and Disease[END_REF][START_REF] O'neill | A guide to immunometabolism for immunologists[END_REF]) (Figure 11).

2) TCA cycle and oxidative phosphorylation

The TCA cycle (also known as citric acid cycle or Krebs cycle) takes place in the matrix of Glucose enters the cell by glucose transporters (GLUTs) and, is metabolized by the hexokinases (HKs) into Glucose-6-P (G6P). G6P is converted into Fructose-6-P (F6P) and then into fructose-1-6-P (F16P) by the phosphofructokinase-1 (PFK1). This process requires 2 ATP molecules. After F16P is metabolized and gives rise to 2 Glyceraldehyde-3-P (G3P) molecules. Each one will be metabolized into 3-phosphoglycerate (3PG). 3GP is then converted into phosphoenolpyruvate and then into pyruvate through the pyruvate kinase isozyme M2 (PKM2). Once pyruvate is produced it can either enter in the mitochondria to fulfill the TCA cycle or be metabolized into lactate by the lactate dehydrogenase (LDH-A). G6P produced during glycolysis can also enter in the oxidative branch of the PPP and be metabolized into ribose-5-phosphate (R5P) by the glucose-6-phosphate dehydrogenase (G6PD). This process results in the generation of 2 NADPH molecules which are important for lipid synthesis. F6P and G3P can also fulfill the PPP through its non-oxidative branch and be metabolized into R5P due the action of transketolase (TKT) and TAL (tyrosine ammonia lyase) respectively. Glycolysis can also provide dihydroxyacetone phosphate (DHAP) from G3P and serine through 3PG. Adapted from [START_REF] Hamanaka | Targeting glucose metabolism for cancer therapy[END_REF] results, the production of 3 molecules of NADH and one molecule of reduced flavin adenine dinucleotide (FADH2) that are crucial for the optimal activity of complexes I and II of the ETC.

The complex I (CI) together with CIII and CIV, export electrons out of the mitochondrial membrane in order to create a proton gradient between the matrix and the intermembrane space of the mitochondria. These electrons located in the intermembrane space, are then used to drive the function of the complex V, also known as ATP synthase. Together, the TCA cycle and ETC, from one single molecule of glucose, produce 36 ATP molecules by a process named oxidative phosphorylation (OXPHOS) (Figure 12). Moreover, TCA cycle also give rise to several metabolites important for fatty acid synthesis and crucial for other cellular and molecular reactions [START_REF] Gaber | Metabolism of T Lymphocytes in Health and Disease[END_REF][START_REF] O'neill | A guide to immunometabolism for immunologists[END_REF].

3) Lipid synthesis and Fatty acid oxidation

Lipid metabolism is a dynamic and a complex process that includes lipid synthesis (anabolic reactions) and oxidation (catabolic reactions). During lipogenesis, lipids, such as fatty acids (de novo fatty acid synthesis pathway) and cholesterol (mevalonate pathway or cholesterol biosynthesis pathway), are synthetized and used as building blocks for cell structures (such as cell membrane). During lipid oxidation, lipids and specific fatty acids (FAs), can be broken down and used as a cell energy source in a process known as β-oxidation or fatty acid oxidation (FAO).

Fatty acid synthesis (FAS) is highly dependent on metabolites produced by other metabolic pathways like glycolysis, PPP and the TCA cycle. As such, the acetyl-coA produced either through TCA cycle-derived citrate, glycolysis-derived pyruvate or from acetate catabolism, is carboxylated into malonyl-CoA by the acetyl CoA carboxylase (ACC) and after into malonyl-ACP (Figure 13). The elongation of the nascent fatty acid starts then with a

Malonyl-ACP molecule acting as a two carbons donor to other acetyl-CoA molecule. After several metabolic reactions, a butyryl-CoA molecule is formed through the enzymatic activity of fatty acid synthase (FASN) in a NADPH-dependent manner (first elongation cycle). This elongation cycle is repeated six more times with another 6 malonyl-CoA molecules (one at each cycle) giving their carbons in a NADPH-dependent manner. This process ends up with a 16-carbon palmitic acid saturated FA straight chain (Figure 13). For the synthesis of alternative-length chain FAs (with more than 16 carbons), palmitic acid is used as a substrate

for elongation and as a substrate for desaturation reactions for the generation of unsaturated fatty acids. The synthesis of other classes of FAs, known as branched chain fatty acids, require specific amino acids like valine, leucine and isoleucine to generate the methyl branches on the carbon chain. [START_REF] Gaber | Metabolism of T Lymphocytes in Health and Disease[END_REF][START_REF] O'neill | A guide to immunometabolism for immunologists[END_REF].

Cholesterol synthesis (also known as mevalonate pathway) requires a distinct metabolic Acetyl-CoA is metabolized into malonyl-CoA by the ACC. Manolyl-CoA is metabolized into Malonyl-ACP which together with another Acetyl-CoA molecule generate Acetoacetyl-ACP (initiation). After, several reactions take place in the FASN protein complex, to produce butyryl-ACP. Once this metabolite is generated, this cycle restarts 6 times up to palmitate synthesis (16:0). Each cycle extends the Acyl Chain by 2 carbons. ACC (acetyl CoA carboxylase), ACP (acyl carrier peptide), FASN (fatty acid synthase). Adapted from [START_REF] Jawed | Engineered Production of Short Chain Fatty Acid in Escherichia coli Using Fatty Acid Synthesis Pathway[END_REF].

The expression of de novo lipid synthesis-related enzymes are regulated by sterol regulatory element binding protein (SREBP). SREBP are a family of transcription factors that regulate both fatty acid and cholesterol synthesis. There are 3 different SREBPs isoforms with distinct physiological roles: SREBP1a (involved in global lipid synthesis), SREBP1c (the most active form in driving expression of genes related to fatty acid synthesis regulation) and SREBP2 (the most active form in the regulation of genes related to cholesterol synthesis) [START_REF] Shimano | SREBP-regulated lipid metabolism: convergent physiology divergent pathophysiology[END_REF][START_REF] Ye | Regulation of cholesterol and fatty acid synthesis[END_REF]. SREBP activation is highly regulated and achieved by a feedback mechanism that senses cholesterol and fatty acids intracellular levels (Figure 15). Mechanistically, SREBP proteins are associated with SCAP (SREBP cleavageactivating protein) in the endoplasmic reticulum (ER) membrane where it is retained due to its binding to the protein INSIG (insulin-induced gene protein). When cholesterol levels are low, INSIG and SCAP are no longer associated; the SREBP-SCAP complex is not retained in the ER and moves to the Golgi. There, SREBP is cleaved by site-1 and 2 proteases (S1P and S2P) giving rise to the SREBP activated form which, after migration to the nucleus, activates genes involved in cholesterol biosynthesis and other lipids. When extracellular levels of cholesterol Acetyl-CoA and Acetoacetyl-CoA through the HMGS enzymatic activity give rise to HMC-CoA, that is then, metabolized into mevalonate through the action of HMGCR. Mevalonate is converted into Mevalonate-5-phosphate by MVK, which through multiple step enzymatic processes, ends up in the generation of isopentenyl pyrophosphate. 6 isopentenyl pyrophosphate molecules are required for the production of one squalene molecule. Squalene is then metabolized into lanosterol and after a 18-steps reaction, cholesterol is generated. Cholesterol can be stored into the cell through the enzymatic activity of ACAT that transforms it into cholesteryl ester. ACAT (Acyl-CoA cholesterol acyltransferase), CYP51 (Lanosterol 14α-demethylase), HMGCR (hydroxymethylglutaryl-coenzyme A reductase), HMGCS (hydroxymethylglutaryl-coenzyme A synthase), MVK (mevalonate kinase).

are high, INSIG and SCAP bind to each other, the SREBP-SCAP complex remains in the ER not allowing the generation of the SREBP mature form and the activation of genes involved in cholesterol and other lipids biosynthesis [START_REF] Bietz | Cholesterol Metabolism in T Cells[END_REF][START_REF] Horton | SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver[END_REF][START_REF] Ye | Regulation of cholesterol and fatty acid synthesis[END_REF]) (Figure 15). However, this regulatory mechanism also applies to other lipids; for example, fatty acid synthesis is controlled by the levels of palmitolyl-CoA; high levels inactivating ACC activity. Furthermore, fatty acids are also able to inhibit proteolytic activation of SREBP1 by increasing the amount of INSIG protein in the ER. However, this inhibition is not independent of sterols, that are crucial for the binding of INSIG and SCAP [START_REF] Ye | Regulation of cholesterol and fatty acid synthesis[END_REF].

Figure 15 -Intracellular Cholesterol levels homeostasis

When intracellular levels of cholesterol are low, INSIG no longer binds to the SREBP-SCAP complex in the ER and allows its migration to the Golgi apparatus. Once in the Golgi, proteases SP1 and SP2 allow the generation of the active form of SREBP that migrates to the nucleus and induces the regulation of cholesterol-synthesis-related genes. When intracellular levels are high, cholesterol binds to SCAP, which results in the increased affinity with INSIG. Once INSIG binds to the SREBP-SCAP complex, it is retained in the ER and cholesterol synthesis is then downregulated. In the same conditions, LXR is activated, increasing the surface expression of ABCA1 and ABCG1 cholesterol efflux transporters. ABCA1/ ABCG1 (ATP binding cassette A1/G1), INSIG (insulin-induced gene protein), ER (endoplasmic reticulum), LDLR (low density lipoprotein receptor), SCAP (SREBP cleavage-activating protein), SREBP (sterol regulatory element binding protein).

Liver X receptor (LXR) plays an opposite role to SREBP as it gets activated under high intracellular cholesterol conditions. Its activation and assembly with the retinoid X receptor (RXR) induces the upregulation of ABCA1 and ABCG1, crucial transporters for cholesterol efflux (Tall and Yvan-Charvet, 2015) (Figure 15). Furthermore, LXR is also involved in the regulation of the SREBP-1c gene. LXR-mediated regulation of the SREBP-1c induces the expression of genes involved in the elongation and unsaturation of fatty acids resulting in an increased synthesis of long-chain polyunsaturated fatty acids (PUFAs) (Tall and Yvan-Charvet, 2015;[START_REF] Ye | Regulation of cholesterol and fatty acid synthesis[END_REF].

The FAs produced or imported into the cells (which is mediated by CD36 and by FATP (fatty acid transport protein) (Howie et al., 2017b)) can also be catabolized in the cell in order to produce energy (ATP). FAs present in the cytosol are first converted to give rise to fatty acid acyl-CoA. Short-fatty acids are able to pass through the mitochondrial membranes without any other mediator. However, medium-chain and long-chain fatty acids need to be conjugated with carnitine by the carnitine palmitoyl transferase (CPT) 1 to be shuttled into the mitochondria. Once in the mitochondria, the carnitine is removed by CPT2 and FAO, also known as β-oxidation, is initiated. Aside of ATP production, from FAO also results the production of NADH and FADH2 that are important for the ETC function. [START_REF] Bietz | Cholesterol Metabolism in T Cells[END_REF][START_REF] Gaber | Metabolism of T Lymphocytes in Health and Disease[END_REF][START_REF] O'neill | A guide to immunometabolism for immunologists[END_REF].

4) Amino acid metabolism

Amino acids (AA) are important precursors for protein synthesis, de novo synthesis of branched-chain fatty acids and de novo purine and pyrimidine synthesis. They can be classified into three different classes: essential, conditionally essential and non-essential.

Essential AA cannot be synthetized by the cell itself or are inadequately synthetized; therefore they need to be provided from the diet. Conditionally essential AA can be synthesized in necessary amounts by the organism. However, when the utilization rate is higher than the synthesis, they need to be provided from the diet. Finally, non-essential AA can be synthetized physiologically in adequate amounts to meet optimal requirements [START_REF] Wu | Amino acids: metabolism, functions, and nutrition[END_REF]. There are several amino acids required for normal cell physiology and function but considering the topics of my PhD work, I will focus on glutamine and arginine.

Glutamine is the most abundant amino acid in the human plasma corresponding to 20% of the total pool and is a non-essential AA [START_REF] Newsholme | Properties of glutamine release from muscle and its importance for the immune system[END_REF][START_REF] Roth | Glutamine: an anabolic effector?[END_REF]. Glutamine is important for cell growth, represents an alternative source for ATP production and can be metabolized into αKG, through a process called glutaminolysis.

Glutamine is first converted into glutamate and ammonia by the glutaminases (GLS) and then glutamate is converted into αKG either through dehydrogenation in the mitochondria by the enzyme glutamate dehydrogenase (GDH) or through a transamination reaction mediated by the glutamate oxaloacetate transaminase (GOT) and the ornithine aminotransferase transaminase (OAT) in the mitochondria or in the cytosol [START_REF] Deberardinis | Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis[END_REF]. αKG can fulfill the TCA cycle through a process called anaplerosis resulting in ATP production through OXPHOS. Furthermore, glutamine-derived αKG can be a precursor for citrate production which can be used for fatty acid synthesis. Moreover, glutamine along with aspartate are important for de novo purine and pyrimidine synthesis [START_REF] Gaber | Metabolism of T Lymphocytes in Health and Disease[END_REF][START_REF] O'neill | A guide to immunometabolism for immunologists[END_REF] (Figure 16).

Arginine is classified as a conditionally essential AA [START_REF] Luiking | Arginine de novo and nitric oxide production in disease states[END_REF] and its imported into the cells by the cationic transporters (CAT) (discussed in section III 2 E). Arginine metabolism results notably in the production of urea and ornithine by the arginase enzymes (ARG) (Figure 17). The urea produced enters in the urea cycle while the ornithine is used for the production of polyamines (putrescine, spermidine and spermine) that are crucial for DNA and RNA stabilization, transcription and translation, cell growth, cell proliferation among others. Arginine can also be metabolized into citrulline by the nitric-oxide-synthase (NOS).

From this reaction results the production of nitric oxide (NO), a well-known signaling molecule involved in many physiological processes (Figure 17). De novo arginine production is dependent on citrulline availability which can therefore give rise to argino-succinate and be metabolized through arginosuccinate lyase (ASL) into arginine which represents 10-15% of whole body arginine production under normal conditions [START_REF] Castillo | Whole body nitric oxide synthesis in healthy men determined from [15N] arginine-to-[15N]citrulline labeling[END_REF][START_REF] Dejong | Renal arginine metabolism in fasted rats with subacute short bowel syndrome[END_REF]) (Figure 17). These metabolic processes take place mainly in the intestinal-renal axis, where citrulline is highly produced in the intestines and arginine in the kidney [START_REF] Ligthart-Melis | Glutamine is an important precursor for de novo synthesis of arginine in humans[END_REF][START_REF] Van De Poll | Interorgan amino acid exchange in humans: consequences for arginine and citrulline metabolism[END_REF][START_REF] Van De Poll | Renal metabolism of amino acids: its role in interorgan amino acid exchange[END_REF][START_REF] Windmueller | Source and fate of circulating citrulline[END_REF][START_REF] Yu | Quantitative aspects of interorgan relationships among arginine and citrulline metabolism[END_REF]. Despite the capacity of the body to produce arginine, about 80% of it results from recycled amino acids released from protein breakdown [START_REF] Szefel | Metabolic pathways of L-arginine and therapeutic consequences in tumors[END_REF] 5) mTOR and AMPK signaling pathways mTOR functions as an energy-sensor pathway that is responsive to several immunological (TCR stimulation, co-stimulation, cytokines) and environmental cues (Pollizzi and Powell, 2015). In environments where nutrient availability is not sufficient to sustain cell growth and expansion, mTOR is inhibited. Signaling from mTOR is mediated through two distinct complexes: mTOR complex (mTORC) 1 and mTORC2 that are associated with several scaffold proteins. Both complexes share the mTOR catalytic subunit, the mammalian lethal with sec-13 protein 8 (mLST8) and the DEP domain containing mTOR-interacting protein (DEPTOR). In contrast, only mTORC1 is associated with the regulatory-associated protein of mammalian target of rapamycin (Raptor) and with proline-rich AKT substrate 40 kDa (PRAs40) while mTORC2 is associated with rapamycin-insensitive companion mTOR (Rictor), with mammalian stress-activated map kinase-interacting protein 1 (mSin1) and protein observed with rictor 1 and 2 (protor 1/2) (Laplante and Sabatini, 2012) (Figure 18). Despite the fact that both complexes share the same catalytic subunit, they have distinct functions. Thus, signaling mediated by mTORC1 promotes protein synthesis, lipogenesis and energy metabolism inhibiting at the same time autophagy and lysosome biogenesis. mTORC1 activation results in the phosphorylation of S6 kinase beta-1 (S6K1) and the eukaryotic translation inhibitor factor 4E-binding protein 1 (4E-BP1). In contrast, mTORC2 signaling regulates cytoskeletal organization and cell survival/metabolism. It also induces a metabolic switch from OXPHOS to glycolysis [START_REF] Laplante | mTOR signaling in growth control and disease[END_REF]Pollizzi and Powell, 2015). mTORC2 activation results in the phosphorylation of the AKT kinase at serine 473 and the glucocorticoid-regulated kinase 1 (SGK1) (Figure 18). AMPK complex is another metabolic regulator, highly conserved, that senses intracellular adenosine nucleotide levels. AMPK is constituted by 3 subunits: the catalytic subunit α and two other regulatory subunits, β and γ (Figure 19). When the AMP (adenosine mono phosphate )/ATP ratio decreases, AMPK activation is induced through the phosphorylation of the Thr172 present in the α subunit by liver kinase B1 (LKB1) [START_REF] Shaw | The tumor suppressor LKB1 kinase directly activates AMP-activated kinase and regulates apoptosis in response to energy stress[END_REF][START_REF] Woods | LKB1 is the upstream kinase in the AMPactivated protein kinase cascade[END_REF]. Furthermore, AMP is able to directly bind to the γ regulatory subunits, inducing a conformational change protecting AMPK against dephosphorylation, and thus, its inactivation [START_REF] Xiao | Structure of mammalian AMPK and its regulation by ADP[END_REF]. Activation of AMPK due to AMP increased levels can also happen through mTOR pathway via two different complexes: mTORC1 and mTORC2. mTORC1 that contains the adaptor protein RAPTOR while mTORC2 contains RICTOR. Activation of mTORC1 and mTORC2 leads to the phosphorylation of different targets as illustrated in this figure. AKT (mechanistic target of rapamycin), mTOR (), mLST8 (mammalian lethal with sec-13 protein 8), mSIN1 (map kinase-interacting protein 1), PRAs40 (proline-rich AKT substrate 40 kDa), RAPTOR (regulatory-associated protein of mammalian target of rapamycin), RICTOR (rapamycin-insensitive companion mTOR), SGK1 (), S6K (S6 kinase), 4E-BP1 (4E-binding protein 1). Adapted from (Pollizzi and Powell, 2015) allosteric activation of the phosphorylated enzyme [START_REF] Suter | Dissecting the role of 5'-AMP for allosteric stimulation, activation, and deactivation of AMPactivated protein kinase[END_REF]. Once activated, AMPK triggers several metabolic pathways to generate ATP while inhibiting cell growth, biosynthesis and other ATP-dependent/consuming processes. Importantly, AMPK activity inhibits mTORdependent pathways, promoting catabolism and inhibiting biosynthesis and cell growth [START_REF] Hardie | AMP-activated protein kinase-development of the energy sensor concept[END_REF].

Several metabolic pathways are engaged upon TCR stimulation. However, the energy and the metabolic requirements of each T cell subset are distinct. In section III, the metabolic changes that occur throughout T cell lifecycle are dissected in order to specifically highlight the importance of metabolism on T cell activation, differentiation, effector function and survival.

III. T cell metabolism 1) Naïve T cells

In the periphery, naïve T cells are continuously migrating through the secondary lymphoid organs, surveying for antigens. For example, cytoskeletal rearrangements, sustained by ATP production, occur constantly and energetic resources are needed in order to fulfill their energetic demands. It has been shown that naïve T cell metabolism relies mainly on OXPHOS [START_REF] Verbist | T cell metabolism and the immune response[END_REF]. Therefore, naïve T cells have a metabolic balance that favors energy production over biosynthesis of new cellular compounds [START_REF] Maciver | Metabolic regulation of T lymphocytes[END_REF]. Thus, and despite the classification of naïve T cells as quiescent T cells, they are metabolically active. It will be tempting to believe that the maintenance of a quiescent metabolic state that characterizes naïve T cells is a "by-default" program in the absence of activation signals. On the contrary, several studies suggest that naïve T cells metabolic state is a process actively maintained. For naïve T cell survival and homeostatic proliferation, cytokine signaling (IL -7) and weak TCR interactions with self-peptides presented by MHC molecules are required [START_REF] Geltink | Unraveling the Complex Interplay Between T Cell Metabolism and Function[END_REF]. Indeed, IL-7 and TCR stimulation are important for the maintenance of naïve T cell state and are associated with GLUT1 transporter upregulation at the cell surface and increased glucose uptake. Furthermore, this process recruits the PI3K /Akt /mTOR pathway with constitutively active Akt promoting the trafficking of GLUT1 to cell surface [START_REF] Barata | Activation of PI3K is indispensable for interleukin 7-mediated viability, proliferation, glucose use, and growth of T cell acute lymphoblastic leukemia cells[END_REF][START_REF] Jacobs | IL-7 is essential for homeostatic control of T cell metabolism in vivo[END_REF][START_REF] Rathmell | IL-7 enhances the survival and maintains the size of naive T cells[END_REF][START_REF] Swainson | IL-7-induced proliferation of recent thymic emigrants requires activation of the PI3K pathway[END_REF][START_REF] Swainson | IL-7R alpha gene expression is inversely correlated with cell cycle progression in IL-7-stimulated T lymphocytes[END_REF][START_REF] Tan | IL-7 is critical for homeostatic proliferation and survival of naive T cells[END_REF][START_REF] Verhoeyen | IL-7 surface-engineered lentiviral vectors promote survival and efficient gene transfer in resting primary T lymphocytes[END_REF][START_REF] Wofford | IL-7 promotes Glut1 trafficking and glucose uptake via STAT5-mediated activation of Akt to support T-cell survival[END_REF]. Contradictory, full mTOR signaling can impact naïve T cells homeostasis since the loss of TSC1 (tumor suppressor tuberous sclerosis complex 1) function (which inhibits mTOR activation) results in loss of quiescence state, increased glycolytic metabolism and cell growth disrupting naïve T cell homeostasis [START_REF] Yang | The tumor suppressor Tsc1 enforces quiescence of naive T cells to promote immune homeostasis and function[END_REF]. All together, these data suggest that naïve T cell metabolic profile requires mTOR activation but at low level comparing to activated T cells [START_REF] Geltink | Unraveling the Complex Interplay Between T Cell Metabolism and Function[END_REF].

2) Metabolic requirements and reprograming upon TCR activation

Upon TCR stimulation, naïve T cells get activated. In order to sustain their rapid proliferation, a "metabolic switch" from OXPHOS to aerobic glycolysis occurs, even if the oxygen supply is not limiting. This phenomenon is not specific to T cells and, as mentioned earlier, was initially described in cancer cells as Warburg effect [START_REF] Warburg | Metabolism of leukocytes][END_REF][START_REF] Warburg | The transformation of embryonal metabolism in cancer metabolism[END_REF] (previously discussed in the section II 1). As previously discussed, the Warburg effect can appear at first glance as counterproductive since the ATP production is lower compared to OXPHOS (2 ATP molecules instead of 36). However, this metabolic pathway is faster to engage notably because of the fast upregulation of glycolytic enzymes expression as compared to the ones involved in OXPHOS (mitochondrial biogenesis is consequently relatively slow).

Moreover, it allows the generation of several "building blocks" important, for instance, for the PPP or the FAS pathways [START_REF] Donnelly | Glucose, glycolysis and lymphocyte responses[END_REF]. It is important to keep in mind that upon activation, even if the glycolytic rate is increased [START_REF] Chang | Posttranscriptional control of T cell effector function by aerobic glycolysis[END_REF]Michalek et al., 2011), the TCA cycle and OXPHOS remain essential to fulfill T cell energetic requirements [START_REF] Carr | Glutamine uptake and metabolism are coordinately regulated by ERK/MAPK during T lymphocyte activation[END_REF][START_REF] Dimeloe | T-cell metabolism governing activation, proliferation and differentiation; a modular view[END_REF][START_REF] Sena | Mitochondria are required for antigenspecific T cell activation through reactive oxygen species signaling[END_REF]Wang et al., 2011). Altogether, it would be more accurate to describe this "metabolic switch" as a change in the ratio between glycolysis/OXPHOS: biosynthetic intermediates for new cellular components (which result mainly from glycolysis) are a priority when compared to ATP production (more efficiently produced by OXPHOS) [START_REF] Gaber | Metabolism of T Lymphocytes in Health and Disease[END_REF]. How nutrients and the metabolic pathways are used upon T cell activation will be further discussed in the next parts of this section.

A. mTOR and AMPK signaling

As mentioned previously in the section II 5, mTOR is a central regulator of cell growth and metabolism (Pollizzi et al., 2015). Mechanistically, TCR engagement induces the activation of the PI3K-Akt axis which in turn, activates mTOR [START_REF] Bantug | The spectrum of T cell metabolism in health and disease[END_REF]. Furthermore, recruitment of the CD28 co-stimulation signaling, is also crucial to reach an optimal mTORC1 activation [START_REF] Zheng | A Role for Mammalian Target of Rapamycin in Regulating T Cell Activation versus Anergy[END_REF]. mTOR activation will then induces the up-regulation of two important transcription factor: inducible impact factor 1α (HIF-1α) and c-Myc. HIF-1α alters the range of glycolytic-associated genes resulting in increased glycolysis rate and enhances IFNγ secretion [START_REF] Roman | T-cell activation under hypoxic conditions enhances IFN-gamma secretion[END_REF][START_REF] Semenza | Transcriptional regulation of genes encoding glycolytic enzymes by hypoxia-inducible factor 1[END_REF]. c-Myc is tightly involved in the increase of the glycolysis and glutaminolysis rates, and as consequence of the PPP pathway and TCA cycle, respectively (Wang et al., 2011). mTOR activity is also crucial for the activation of SREBP and PPAR (peroxisome proliferator-activated receptors) which are two crucial transcription factors involved in lipid production [START_REF] Angela | Fatty acid metabolic reprogramming via mTOR-mediated inductions of PPARgamma directs early activation of T cells[END_REF][START_REF] Kidani | Sterol regulatory element-binding proteins are essential for the metabolic programming of effector T cells and adaptive immunity[END_REF].

PPARs are transcription factors that are part of the nuclear hormone receptors family. They are activated by lipophilic molecules and mostly control genes involved in lipid metabolism [START_REF] Sonoda | Nuclear receptors: decoding metabolic disease[END_REF]. The role of mTOR in T cell activation and metabolic reprogramming is represented on Figure 20.

AMPK is also activated by TCR signaling and it is important for T cell activation [START_REF] Tamás | Regulation of the energy sensor AMP-activated protein kinase by antigen receptor and Ca<sup>2+</sup> in T lymphocytes[END_REF]. AMPKα deficient T cell demonstrated defects in T cell activation, metabolism and inflammatory cytokine production. In the same line, LKB1-deficient T cells exhibited defects in cell proliferation, viability and altered glycolytic and lipid metabolism [START_REF] Maciver | The liver kinase B1 is a central regulator of T cell development, activation, and metabolism[END_REF].

Activated AMPK induced FAO and inhibited fatty acid synthesis [START_REF] Davies | Location and function of three sites phosphorylated on rat acetyl-CoA carboxylase by the AMP-activated protein kinase[END_REF][START_REF] Merrill | AICA riboside increases AMPactivated protein kinase, fatty acid oxidation, and glucose uptake in rat muscle[END_REF] and its activation also downregulated mTORC1 activity under nutrient deprived conditions [START_REF] Blagih | The Energy Sensor AMPK Regulates T Cell Metabolic Adaptation and Effector Responses In Vivo[END_REF]. These AMPK functions seem to be count productive considering the metabolic requirements of activated T cells. Thought, AMPK activation by TCR is transient, decreasing over the time to low levels in proliferating T effector cells (Kishton et al., 2016;[START_REF] Tamás | Regulation of the energy sensor AMP-activated protein kinase by antigen receptor and Ca<sup>2+</sup> in T lymphocytes[END_REF].

B. Glycolysis

Upon activation, increased glycolysis is crucial to sustain T cell activation and proliferation [START_REF] Gerriets | Metabolic pathways in T cell fate and function[END_REF]. Glucose can enter in the cells either through the SGLTs or through the facilitative glucose transporters, a family of transporters named GLUTs [START_REF] Navale | Glucose transporters: physiological and pathological roles[END_REF]. SGLTs are glucose transporters which transport glucose together with Upon TCR/CD28 activation, mTORC1 is activated and several transcription factors recruited. These transcription factors allow the engagement of several metabolic pathways necessary for the reprograming required to sustain T cell activation. Akt (protein kinase B), AMPK (AMP-activated protein kinase), HIF1α (Hypoxia-inducible factor 1-alpha), mTOR (mechanistic target of rapamycin), PI3K (Phosphoinositide 3-kinases), PGC1α (Peroxisome proliferator-activated receptor gamma coactivator 1-alpha). Adapted from: [START_REF] Bantug | The spectrum of T cell metabolism in health and disease[END_REF] sodium ions (in the same direction) and they are mainly expressed in intestinal cells. The GLUTs family is composed of 13 isoforms in mice and 14 in humans [START_REF] Uldry | The SLC2 family of facilitated hexose and polyol transporters[END_REF][START_REF] Zhao | Functional properties and genomics of glucose transporters[END_REF]. All Gluts are highly glycosylated proteins harboring a N-linked glycosylation site and, based on their localization, they can be divided into three classes.

GLUT1 is the main glucose transporter in T lymphocytes. However, it also important to mention that upon TCR activation, GLUT3, GLUT6 and GLUT8 were also detected at mRNA level even if it was at lower levels as compared to GLUT1 (Macintyre et al., 2014;[START_REF] Vaeth | Store-Operated Ca(2+) Entry Controls Clonal Expansion of T Cells through Metabolic Reprogramming[END_REF]. T cell activation is associated with an increased glucose uptake and an upregulation of GLUT1 cell surface expression [START_REF] Gerriets | Metabolic pathways in T cell fate and function[END_REF][START_REF] Kinet | Isolated receptor binding domains of HTLV-1 and HTLV-2 envelopes bind Glut-1 on activated CD4+ and CD8+ T cells[END_REF][START_REF] Maciver | Metabolic regulation of T lymphocytes[END_REF]Manel et al., 2003b). GLUT1 can be detected at the cell surface as early as 4 hours following TCR stimulation (Manel et al., 2003b) and it is expressed in both CD4 + and CD8 + T cells [START_REF] Kinet | Isolated receptor binding domains of HTLV-1 and HTLV-2 envelopes bind Glut-1 on activated CD4+ and CD8+ T cells[END_REF]. Despite the fact that the precise mechanism by which T cells control GLUT1 expression and trafficking has not been yet fully characterized, it is known that PI3K signaling through Akt is essential for this process [START_REF] Wieman | Cytokine stimulation promotes glucose uptake via phosphatidylinositol-3 kinase/Akt regulation of Glut1 activity and trafficking[END_REF] and CD28 signaling is crucial for Akt regulation of GLUT1 trafficking [START_REF] Frauwirth | The CD28 signaling pathway regulates glucose metabolism[END_REF][START_REF] Jacobs | Glucose uptake is limiting in T cell activation and requires CD28mediated Akt-dependent and independent pathways[END_REF]. Also, another recent study demonstrated that store-operated Ca 2+ was involved in the regulation of glucose transporters, glycolytic enzymes through the activation of NFAT (nuclear factor of activated T cells) [START_REF] Vaeth | Store-Operated Ca(2+) Entry Controls Clonal Expansion of T Cells through Metabolic Reprogramming[END_REF]. Interestingly, over-expression of GLUT1 did not impact T cell development or homeostasis but was associated with increased cell size, glucose uptake, proliferation rate and IFNγ and IL-2 secretion and lead to inflammatory diseases [START_REF] Cretenet | Cell surface Glut1 levels distinguish human CD4 and CD8 T lymphocyte subsets with distinct effector functions[END_REF][START_REF] Jacobs | Glucose uptake is limiting in T cell activation and requires CD28mediated Akt-dependent and independent pathways[END_REF]Michalek et al., 2011). Additionally, under glucosedeprived conditions, proliferating T cells undergo apoptosis [START_REF] Jacobs | Glucose uptake is limiting in T cell activation and requires CD28mediated Akt-dependent and independent pathways[END_REF][START_REF] Rathmell | In the absence of extrinsic signals, nutrient utilization by lymphocytes is insufficient to maintain either cell size or viability[END_REF].

C. Glutamine metabolism

Glutamine is also crucial for T cells as low extracellular concentrations decrease human leukocyte proliferation [START_REF] Parry-Billings | Does glutamine contribute to immunosuppression after major burns?[END_REF]) whereas a glutamine-rich diet is associated with an increased lymphocyte proliferation and increased cytokine secretion [START_REF] Kew | Dietary glutamine enhances murine T-lymphocyte responsiveness[END_REF]. As observed for glucose, activation of the TCR signaling resulted in increased glutamine import, notably through upregulation of the cell surface expression of neutral amino acid transporters [START_REF] Sena | Mitochondria are required for antigenspecific T cell activation through reactive oxygen species signaling[END_REF]. Several transporters can uptake glutamine including the sodium-dependent neutral amino acid transporter 1/2 (SNAT1/SNAT2) and the system ASC amino acid transporter-2 (ASCT2 or SLC (solute carrier family) 1A5) [START_REF] Carr | Glutamine uptake and metabolism are coordinately regulated by ERK/MAPK during T lymphocyte activation[END_REF]Nakaya et al., 2014;[START_REF] Ren | Amino-acid transporters in T-cell activation and differentiation[END_REF]. Glutamine is a rate limiting step for mTOR activation and its entry in Hela cells through the transporter ASCT2 regulates mTOR activation [START_REF] Nicklin | Bidirectional Transport of Amino Acids Regulates mTOR and Autophagy[END_REF]. Mechanistically, glutamine entry through ASCT2 allows the functioning of the SLC7A5/SLC3A2 heterodimer, a bidirectional transporter which controls the import of extracellular leucine in exchange with intracellular glutamine export. This process activates mTORC1 and highlights the role of glutamine flux in mTOR activation. [START_REF] Nicklin | Bidirectional Transport of Amino Acids Regulates mTOR and Autophagy[END_REF]. In addition, another elegant study demonstrated that activated ASCT2 -/-T cells displayed defective phosphorylation of mTOR targets S6K1 and 4EBP1, highlighting again the importance of ASCT2 in the activation/recruitment of mTOR signaling pathway (Nakaya et al., 2014).

D. Lipid metabolism

The induction of the lipid biosynthetic pathway is also engaged upon TCR activation program [START_REF] Lochner | Fatty acid metabolism in the regulation of T cell function[END_REF]. Thus cholesterol as well as FA synthesis has been shown to be highly upregulated upon T cell activation [START_REF] Bietz | Cholesterol Metabolism in T Cells[END_REF]. Indeed, Wang and colleagues demonstrated that 24-30 hours following T cell activation, an increase of metabolites from the FAS pathway was detected (Wang et al., 2011). The FAS pathway is induced by SREBP processing and LXR signaling inhibition (Bensinger et al., 2008). Mechanistically, TCRstimulated de novo lipid synthesis, is dependent on mTORC1 which activates SREBP and mediates the process [START_REF] Kidani | Sterol regulatory element-binding proteins are essential for the metabolic programming of effector T cells and adaptive immunity[END_REF][START_REF] Yang | T cell exit from quiescence and differentiation into Th2 cells depend on Raptor-mTORC1-mediated metabolic reprogramming[END_REF]. C-myc also contributes to lipid biosynthesis in T cells through its implication in glucose catabolism (from which result important intermediates to sustain lipid synthesis) (Wang et al., 2011).

Cholesterol can also modulate T cell activation due to its contribution on lipid rafts formation, which are structures where lipid-lipid and lipid-protein interactions occur and contribute to the optimal clustering of signaling proteins at the membrane to facilitate signal transduction [START_REF] Hou | Omega-3 fatty acids, lipid rafts, and T cell signaling[END_REF]. In T cells, it was demonstrated that cholesterol present in the lipid rafts was important for the formation of TCR dimers which determined the sensitivity of the TCR to external stimuli [START_REF] Molnar | Cholesterol and sphingomyelin drive ligandindependent T-cell antigen receptor nanoclustering[END_REF]. Lipids, and in particular cholesterol, can modulate TCR signaling through the promotion of different conformational state of the CD3 chain [START_REF] Guo | Lipid-dependent conformational dynamics underlie the functional versatility of T-cell receptor[END_REF]. Furthermore, cholesterol can directly bind to the TCR and modify it via allosteric regulation of TCR phosphorylation [START_REF] Swamy | A Cholesterol-Based Allostery Model of T Cell Receptor Phosphorylation[END_REF]. Moreover, membrane fluidity and spatial control of the receptors is also important to maintain the immunological synapse [START_REF] Dustin | The immunological synapse[END_REF]. Finally, cholesterol efflux also plays an important role on T cells being LXR-dependent ABCG1 expression regulation (section II 3) important for T cell proliferation regulation (Bensinger et al., 2008).

E. Arginine metabolism

Arginine availability is essential for optimal immune responses and more specifically for T cell proliferation and function [START_REF] Bronte | Regulation of immune responses by L-arginine metabolism[END_REF]. However, another study revealed that arginine was not equally important for both CD4 + and CD8 + T cell showing that CD4 + T cell proliferation was not dependent on arginine, whereas CD8 + T cell proliferation appeared to be arginine concentration-dependent [START_REF] Ochoa | Effects of L-arginine on the proliferation of T lymphocyte subpopulations[END_REF]. However, this study goes against other works mentioned in this section, where total T cell proliferation was impacted either by arginine deprivation either by reduced arginine uptake [START_REF] Werner | Induced arginine transport via cationic amino acid transporter-1 is necessary for human T-cell proliferation[END_REF][START_REF] Werner | Reconstitution of T Cell Proliferation under Arginine Limitation: Activated Human T Cells Take Up Citrulline via L-Type Amino Acid Transporter 1 and Use It to Regenerate Arginine after Induction of Argininosuccinate Synthase Expression[END_REF]. In human cells, arginine is mostly transported by members of the SLC7 [START_REF] Closs | Structure and function of cationic amino acid transporters (CATs)[END_REF][START_REF] Fotiadis | The SLC3 and SLC7 families of amino acid transporters[END_REF] comprising three CATs known as SLC7A1-3 or CAT1-3 and three other subfamilies transporting not only cationic amino acids but also neutral amino acids which are y + L-type amino acid transporter 1 (y + LAT1 or SLC7A7), y + LAT2 or SLC7A6 and b 0,+ AT or SLC7A9 [START_REF] Fotiadis | The SLC3 and SLC7 families of amino acid transporters[END_REF]. On one hand, CAT transporters can mediate arginine import [START_REF] Closs | Structure and function of cationic amino acid transporters (CATs)[END_REF][START_REF] Fotiadis | The SLC3 and SLC7 families of amino acid transporters[END_REF] in most eukaryotic cells fueling argininedependent metabolic pathways and protein synthesis, while, on the other hand, y + LAT proteins mediate arginine export in exchange for neutral amino acids import [START_REF] Closs | Structure and function of cationic amino acid transporters (CATs)[END_REF][START_REF] Fotiadis | The SLC3 and SLC7 families of amino acid transporters[END_REF]. From all these arginine transporters, CAT-1 appears as the most expressed on T cells. Recently it was shown that human CAT-1 mRNA is the most upregulated upon T cell activation and also that CAT-1 is necessary for activation-induced arginine uptake and human T cell proliferation [START_REF] Werner | Induced arginine transport via cationic amino acid transporter-1 is necessary for human T-cell proliferation[END_REF].

It was shown that, in low-arginine environments, CD3ζ expression is down-regulated, most likely because of a decreased synthesis of the chain [START_REF] Taheri | L-Arginine regulates the expression of the T-cell receptor zeta chain (CD3zeta) in Jurkat cells[END_REF][START_REF] Zea | L-Arginine modulates CD3zeta expression and T cell function in activated human T lymphocytes[END_REF].

Moreover, these cells also demonstrated lower IFNγ, IL-5, IL-10 but not IL-2 production [START_REF] Zea | L-Arginine modulates CD3zeta expression and T cell function in activated human T lymphocytes[END_REF]. Furthermore, T cells stimulated in the absence of arginine failed to progress through cell cycle and remained in G0-G1 phase [START_REF] Rodriguez | L-arginine availability regulates Tlymphocyte cell-cycle progression[END_REF]. Besides, in absence of arginine, T cells undergo autophagy to get arginine intra-cellularly to preserve cell viability [START_REF] Garcia-Navas | Depletion of L-arginine induces autophagy as a cytoprotective response to endoplasmic reticulum stress in human T lymphocytes[END_REF]). An alternative strategy in arginine-deprived environments relies on citrulline catabolism through ASS and ASL into arginine [START_REF] Husson | Argininosuccinate synthetase from the urea cycle to the citrulline-NO cycle[END_REF]. Macrophages can take up citrulline from the extracellular environment and therefore produce arginine [START_REF] Baydoun | Discrimination between citrulline and arginine transport in activated murine macrophages: inefficient synthesis of NO from recycling of citrulline to arginine[END_REF], demonstrating the importance of citrulline-arginine pathway in this immune cell type. Similar mechanisms were recently demonstrated in human T cells, where it was showed that citrulline could be transported by LAT1 transporter as siRNA-mediated LAT1 knockdown in activated T cells resulted in reduced citrulline import [START_REF] Werner | Reconstitution of T Cell Proliferation under Arginine Limitation: Activated Human T Cells Take Up Citrulline via L-Type Amino Acid Transporter 1 and Use It to Regenerate Arginine after Induction of Argininosuccinate Synthase Expression[END_REF]. Furthermore, citrulline supplementation was able to restore CD4 + and CD8 + proliferation under arginine-deprived concentrations being this process correlated with ASS induction. However, in the complete absence of arginine, citrulline was not able to restore T cell proliferation to the levels observed in conditions where arginine was available [START_REF] Werner | Reconstitution of T Cell Proliferation under Arginine Limitation: Activated Human T Cells Take Up Citrulline via L-Type Amino Acid Transporter 1 and Use It to Regenerate Arginine after Induction of Argininosuccinate Synthase Expression[END_REF]. Another elegant study highlighted the importance of ASS as they demonstrated that ASS1 deficiency resulted in reduced spleen size, reduced T cell numbers and abnormal T cell differentiation and function [START_REF] Tarasenko | Impaired T cell function in argininosuccinate synthetase deficiency[END_REF].

The global T cells metabolic feautures before and after TCR stimulation are described in Figure 21.

3) Metabolic requirement and control during T cell differentiation -Effector and regulatory functions.

A. Glycolysis

Glucose not only plays a crucial role in T cell activation but also in T cell differentiation and acquisition of effector functions. Besides the general importance of glucose in T cell biology several elegant studies demonstrated that glycolysis is not equally required for all T cell subsets and can differentially impact their fate. Indeed, and despite the fact that both human CD4 + and CD8 + T cells increased their glycolytic flux upon stimulation, CD4 + T cells had increased HKII expression and were more dependent on aerobic glycolysis comparing to CD8 + T cells [START_REF] Jones | Metabolic Adaptation of Human CD4+ and CD8+ T-Cells to T-Cell Receptor-Mediated Stimulation[END_REF]. It has also been shown that upon TCR activation, murine CD4 + and Naïve T cells use glucose, amino acids and fatty acids to produce energy through OXPHOS. Nutrient uptake occurs at low levels (comparing to TEFF cells), enough to maintain naïve T cell homeostasis and cell quiescence. Upon TCR activation, nutrient uptake is increased followed by augmented protein, lipid and nucleotide synthesis to sustain T cell growth and proliferation. Glucose is used as a main energy source through aerobic glycolysis, a faster pathway to engage and from which results several metabolic intermediates important to sustain the increased biosynthetic demands. mTOR (mechanistic target of rapamycin), OXPHOS (oxidative phosphorylation), PI3K (Phosphoinositide 3kinases). Adapted from: (Palmer et al., 2016b) CD8 + T cells rely highly on glycolysis. However, in contrast to the previous study, the authors describe that CD4 + murine T cells had a higher ratio OXPHOS/glycolysis than CD8 + T cells.

These discrepancies can probably be explained by the differences on the time points chosen to measure these parameters and by the fact that the studies were done in the distinct systems (human vs murine). Moreover, glucose requirements among the different CD4 + T cell subsets appear to be different as well. Indeed, naïve CD4 + T cell differentiation into Th1 and Th17 cells was highly dependent on glycolysis, though these two different subsets exhibited clear difference in the activation of HIF-1α for their glycolytic engagement [START_REF] Dang | Control of T(H)17/T(reg) balance by hypoxia-inducible factor 1[END_REF]Michalek et al., 2011;[START_REF] Shehade | Cutting Edge: Hypoxia-Inducible Factor 1 Negatively Regulates Th1 Function[END_REF]Shi et al., 2011). Differentiated Th2 cells were also highly dependent on glycolysis (Michalek et al., 2011), although the role of glucose in the polarization of this lineage is less understood [START_REF] Bantug | The spectrum of T cell metabolism in health and disease[END_REF]. Due to the importance of glycolysis in Th1, Th2 and Th17 cells, it was not surprising that GLUT1 deletion, as well as glucose deprivation, altered Th1, Th2 and Th17 differentiation (Macintyre et al., 2014;Michalek et al., 2011). In the context of my thesis, we also demonstrated that GLUT1 cell surface levels could be used to select human CD4 + and CD8 + T cells subsets with distinct effector functions. Cells that express high levels of GLUT1 were more proliferative, secreted more IL-2 and IFNγ and had more effector-like phenotype [START_REF] Cretenet | Cell surface Glut1 levels distinguish human CD4 and CD8 T lymphocyte subsets with distinct effector functions[END_REF]. Other elegant studies showed as well that increased glycolysis enhanced effector functions. For instance, in GLUT1 transgenic mice, it was observed a selective increase in TEFF cells and in IFNγ, IL-4 and IL-17 secretion (Michalek et al., 2011). Moreover, other two studies demonstrated that reduced T effector function in tumor bearing mice could be overcome by increased T cell glycolytic activity (Chang et al., 2015;[START_REF] Ho | Phosphoenolpyruvate Is a Metabolic Checkpoint of Anti-tumor T Cell Responses[END_REF]. Controversially, in a study were T cells were segregated based on glucose uptake level (based on the uptake of a fluorescent 2-NBDG glucose analogue), high glucose uptake was associated with a terminal differentiated effector state and decreased in vivo effector function (Sukumar et al., 2013a).

Glycolytic enzymes activity can also impact on T cell polarization. For instance, PDH activity seems to be important for Treg cell but not for Th17 cell differentiation [START_REF] Gerriets | Metabolic programming and PDHK1 control CD4+ T cell subsets and inflammation[END_REF]. Furthermore, LDH-A (another enzyme from the glycolytic pathway) was demonstrated to be important in promoting an efficient Th1 polarization through a direct role on the epigenetic regulation of IFNγ expression [START_REF] Peng | Aerobic glycolysis promotes T helper 1 cell differentiation through an epigenetic mechanism[END_REF]. Finally, Chang and colleagues showed that the glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was important to control effector cytokine production, notably IFNγ due the regulation of its locus [START_REF] Chang | Posttranscriptional control of T cell effector function by aerobic glycolysis[END_REF].

B. Glutaminolysis

Despite its role in T cell activation, glutamine is also involved during T cell differentiation and acquisition of effector functions. ASTC2 knockout revealed an important role of glutamine and its transporter in the induction of signaling pathways required for T cell polarization and effector function. Indeed, our lab among others demonstrated that ASCT2 knockout as well as glutamine deprivation in vitro (on both murine and human cells) impaired the induction of both Th1 and Th17 cells (Klysz et al., 2015;[START_REF] Metzler | Restricting Glutamine or Glutamine-Dependent Purine and Pyrimidine Syntheses Promotes Human T Cells with High FOXP3 Expression and Regulatory Properties[END_REF]Nakaya et al., 2014) via a suboptimal activation of mTORC1. However, glutamine deprivation or glutaminolysis inhibition did not alter Th2 and Treg differentiation on both murine and human T cells (Klysz et al., 2015;[START_REF] Metzler | Restricting Glutamine or Glutamine-Dependent Purine and Pyrimidine Syntheses Promotes Human T Cells with High FOXP3 Expression and Regulatory Properties[END_REF]. Furthermore, work from our lab showed that, in glutamine-deprived conditions, naïve T cells failed to differentiate to a Th1 fate and resulted instead with a Treg phenotype, highlighting the role of glutamine availability in the differentiation of CD4 + T cells into different Th subsets (Klysz et al., 2015).

C. TCA cycle metabolites

As already described in section II 2, TCA-cycle metabolic intermediates can derive from the catabolism of glucose, glutamine and fatty acids. These metabolites are important for T cell activation and acquisition of effector functions by activating different metabolic pathways. For instance, citrate and acetyl-coA are not only fulfilling the TCA cycle, but also have an interconnection with lipid synthesis and gene expression. TCA cycle-produced citrate can be transported into cytosol by the citrate carrier (CIC) and then used for lipid and cholesterol synthesis [START_REF] Palmieri | The mitochondrial transporter family (SLC25): physiological and pathological implications[END_REF]. In the same line, acetyl-coA is important for FA and cholesterol synthesis. How these metabolites are used in the fatty acid and cholesterol metabolism is explained in the section II 3. Importantly, citrate and acetyl-coA are also main players on epigenetic regulation (Figure 22) (section III 3 C b). a) Alpha-ketoglutarate αKG is involved in many processes besides its role in fueling the TCA cycle. Thus, it was demonstrated that αKG contributes to lipid metabolism. For instance, it was demonstrated that αKG supplementation, was able to decrease through unknown mechanisms the serum content in total cholesterol, LDL and triglycerides, and increase HDL concentration [START_REF] Radzki | Effect of dietary alpha-ketoglutarate on blood lipid profile during hypercholesterolaemia in rats[END_REF]. Moreover, αKG was demonstrated to have also a role as regulator of gene expression and cell signaling pathways. For instance, αKG was identified as a ligand of a G protein-coupled receptor (GPR99 also known as 2-oxoglutarate receptor 1) which, once activated, is able to modulate cell metabolism and signaling resulting in increased cell proliferation [START_REF] He | Citric acid cycle intermediates as ligands for orphan G-protein-coupled receptors[END_REF]. Another better-described role of αKG consists in its capacity to repress HIF-1α stabilization by fostering the activity of the metabolic sensor prolyl hydroxylases (PHDs) [START_REF] Pan | Multiple factors affecting cellular redox status and energy metabolism modulate hypoxia-inducible factor prolyl hydroxylase activity in vivo and in vitro[END_REF]. Indeed, when amino acids are depleted, reduced αKG levels lead to PHDs inactivation and HIF-1α stabilization [START_REF] Durán | HIF-independent role of prolyl hydroxylases in the cellular response to amino acids[END_REF]. Furthermore, HIF-1α has many functions in the regulation of T cell cellular metabolism and function. An elegant study revealed that HIF-1α was important to sustain glycolysis during T cell response, but not required during early T cell activation (Wang et al., 2011). The role of HIF-1α in T cell differentiation and notably on the Th17/iTreg balance is however not fully characterized [START_REF] Dang | Control of T(H)17/T(reg) balance by hypoxia-inducible factor 1[END_REF]Shi et al., 2011). While Shi and colleagues demonstrated that HIF-1α deficiency inhibited Th17 differentiation and promoted iTreg differentiation due a reduction of the glycolytic metabolism (Shi et al., 2011), Dang and colleagues revealed that Th17 differentiation was altered due to the inhibition of RORγT expression and, on the contrary, iTreg differentiation was promoted because of the absence of HIF-1α-dependent inhibition of FoxP3 expression [START_REF] Dang | Control of T(H)17/T(reg) balance by hypoxia-inducible factor 1[END_REF]. Contradictory, another study demonstrated that HIF-1α was required for FoxP3 expression and optimal Treg function [START_REF] Clambey | Hypoxia-inducible factor-1 alpha-dependent induction of FoxP3 drives regulatory T-cell abundance and function during inflammatory hypoxia of the mucosa[END_REF]. However, this study was performed in a hypoxia context and in iTreg polarizing conditions while the previous ones were done in normoxia conditions (Shi et al., 2011) and in a Th17 polarizing context [START_REF] Dang | Control of T(H)17/T(reg) balance by hypoxia-inducible factor 1[END_REF]Shi et al., 2011), which can potentially explain the differences observed. In CD8 T cells, it was shown that HIF-1α increased the expression of effector molecules (such as IFNγ and TNF) and the cytolytic activity [START_REF] Doedens | Hypoxia-inducible factors enhance the effector responses of CD8(+) T cells to persistent antigen[END_REF][START_REF] Finlay | PDK1 regulation of mTOR and hypoxia-inducible factor 1 integrate metabolism and migration of CD8+ T cells[END_REF]. αKG also promotes mTOR signaling through PHDs activation, blocks autophagy and induces cell growth and proliferation [START_REF] Duran | Glutaminolysis activates Rag-mTORC1 signaling[END_REF][START_REF] Durán | HIF-independent role of prolyl hydroxylases in the cellular response to amino acids[END_REF]. αKG has also an important role as a nitrogen-acting scavenger to protect cells from ammonia exposure [START_REF] Nilsang | Three-dimensional culture for monoclonal antibody production by hybridoma cells immobilized in macroporous gel particles[END_REF].

αKG plays also an important role in gene regulation through its implication in epigenetic regulation. Indeed, αKG is a co-factor for 2 families of dioxygenases that mediate demethylation and hydroxylation reactions of DNA and histones: the TET proteins family of 5-methylcytosine (5mc) hydroxylases and the Jumonji C (JmjC) domain containing histone demethylases (HDM)(JHDM) [START_REF] Kaelin | Influence of metabolism on epigenetics and disease[END_REF][START_REF] Loenarz | Physiological and biochemical aspects of hydroxylations and demethylations catalyzed by human 2-oxoglutarate oxygenases[END_REF]. These dioxygenases not only required αKG as a co-factor, but also oxygen and iron [START_REF] Kaelin | Influence of metabolism on epigenetics and disease[END_REF]) (Figure 22). TET proteins are able to oxidize 5mC to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-hydroxymethylcytosine (5caC) [START_REF] He | Tet-mediated formation of 5-carboxylcytosine and its excision by TDG in mammalian DNA[END_REF]Ito et al., 2011;[START_REF] Tahiliani | Conversion of 5-methylcytosine to 5hydroxymethylcytosine in mammalian DNA by MLL partner TET1[END_REF]) leading to demethylation.

Several studies have recently demonstrated that TET proteins are important for T cell differentiation. Indeed, mice deficient in TET2 were unable to produce Th1 and Th17 cytokines, although Th2 differentiation was not impacted. Therefore, different Th subsets exhibit a differential dependence on TET2-mediated 5hmc and H3K4me3 epigenetic modifications [START_REF] Ichiyama | The methylcytosine dioxygenase Tet2 promotes DNA demethylation and activation of cytokine gene expression in T cells[END_REF]. Furthermore, several studies have shown a distinct epigenetic regulation of Treg differentiation as compared to other Th subsets [START_REF] Morikawa | Differential roles of epigenetic changes and Foxp3 expression in regulatory T cell-specific transcriptional regulation[END_REF]. FoxP3 expression has been demonstrated to be regulated by epigenetic mechanisms, particularly through the methylation of an element located in the 5'untranslated region of the FoxP3 locus known as TSDR (Treg-specific demethylated region) [START_REF] Polansky | DNA methylation controls Foxp3 gene expression[END_REF]. TET1, 2 and 3 have also been shown to be important for FoxP3 stability in Treg cells through epigenetic regulation mechanism [START_REF] Someya | Improvement of Foxp3 stability through CNS2 demethylation by TET enzyme induction and activation[END_REF][START_REF] Yang | Hydrogen Sulfide Promotes Tet1-and Tet2-Mediated Foxp3 Demethylation to Drive Regulatory T Cell Differentiation and Maintain Immune Homeostasis[END_REF][START_REF] Yue | Control of Foxp3 stability through modulation of TET activity[END_REF]. Mechanistically, Yang and colleagues demonstrated that IL-2 and TGF-β signaling, through SMAD3 and STAT5a phosphorylation, activate TET1 and 2 facilitating the demethylation of CNS1 and CNS2 regions and consequently allowing FoxP3 stability (Yang et al., 2015). In the absence of IL-2, TSDR remained methylated and FoxP3 expression was transient and unstable [START_REF] Nair | DNA Demethylation of the Foxp3 Enhancer Is Maintained through Modulation of Ten-Eleven-Translocation and DNA Methyltransferases[END_REF]. Furthermore, it was recently discovered that αKG was able to regulate certain CTCF (CCCTC-binding factor is a DNA-binding zinc-finger transcription factor) binding sites inducing CTCF association and impacting the Th1 program in a TET-dependent manner (Chisolm et al., 2017).

Alteration of αKG availability and dysregulation of associated enzymes can interfere with T cell differentiation and it is often associated with oncogenicity. Mutations in a single allele of the isocitrate dehydrogenase (IDH) 1 and 2 can create a neomorphic enzyme with increased affinity to αKG. Mutant IDH1/2 enzymes result in diminished αKG/ isocitrate inter-conversion and the generation of the 2-hydroxyglutarate (2HG) oncometabolite: D-(R)-2hydroxyglutarate ((R)-2HG or D-2HG) [START_REF] Dang | Cancer-associated IDH1 mutations produce 2hydroxyglutarate[END_REF][START_REF] Rendina | Mutant IDH1 enhances the production of 2hydroxyglutarate due to its kinetic mechanism[END_REF][START_REF] Ward | Identification of additional IDH mutations associated with oncometabolite R(-)-2-hydroxyglutarate production[END_REF]. As such, elevated levels of D-2HG have been detected in patients with myeloid leukemias (AML), gliomas and angio-immunoblastic T-cell lymphoma (AITL) [START_REF] Dang | Cancer-associated IDH1 mutations produce 2hydroxyglutarate[END_REF][START_REF] Lemonnier | The IDH2 R172K mutation associated with angioimmunoblastic T-cell lymphoma produces 2HG in T cells and impacts lymphoid development[END_REF][START_REF] Ward | The common feature of leukemia-associated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha-ketoglutarate to 2-hydroxyglutarate[END_REF]. αKG can also be converted into a different 2HG enantiomer known as L-(S)-2-hydroxyglutarate (S-2HG or L-2HG). Interestingly, this enantiomer does not result from a mutation in IDH enzymes and can be generated either from LDH-A and malate dehydrogenase (MDH)1 activity in cytosol , either from MDH2 activity in the mitochondria under conditions such as hypoxia, mitochondrial impairment or specific pH conditions [START_REF] Intlekofer | Hypoxia Induces Production of L-2-Hydroxyglutarate[END_REF][START_REF] Intlekofer | L-2-Hydroxyglutarate production arises from noncanonical enzyme function at acidic pH[END_REF][START_REF] Oldham | Hypoxia-Mediated Increases in L-2-hydroxyglutarate Coordinate the Metabolic Response to Reductive Stress[END_REF].

While D-2HG has been commonly detected in different cancers, both D-2HG and L-2HG enantiomers are competitive inhibitors of αKG due their capability to bind to αKG-dependent dioxygenases. As a result, increased levels of 2HG can inhibit the TET2 and JmjC mediateddemethylation [START_REF] Chowdhury | The oncometabolite 2-hydroxyglutarate inhibits histone lysine demethylases[END_REF][START_REF] Lu | IDH mutation impairs histone demethylation and results in a block to cell differentiation[END_REF][START_REF] Xu | Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alphaketoglutarate-dependent dioxygenases[END_REF]. Moreover, mutations in TET2 have also been reported in myeloid cancer patients, strongly suggesting that epigenetic deregulation and histone modifications can promote an oncogenic phenotype [START_REF] Delhommeau | Mutation in TET2 in myeloid cancers[END_REF][START_REF] Langemeijer | Acquired mutations in TET2 are common in myelodysplastic syndromes[END_REF].

b) Other TCA cycle metabolites

As discussed on the section III 3 C a, αKG is a TCA intermediate with a preponderant role in epigenetic regulation. However, other TCA cycle metabolites are also crucial. Succinate and fumarate are two metabolites that can directly compete with αKG, inhibiting αKG-dependent dioxygenases and PHDs activation [START_REF] Vatrinet | The alpha-ketoglutarate dehydrogenase complex in cancer metabolic plasticity[END_REF]) (Figure 22). Indeed, in succinate dehydrogenase-(SDH) and fumarate hydratase (FH) (two enzymes classified as tumor suppressors) deficient tumors, an increased stability of HIF1-α was observed even in normoxic conditions [START_REF] Pollard | Accumulation of Krebs cycle intermediates and overexpression of HIF1alpha in tumours which result from germline FH and SDH mutations[END_REF]. Furthermore, it was also shown that ectopic expression of tumor-derived SDH and FH mutants inhibited histone demethylation and hydroxylation of 5mC [START_REF] Xiao | Inhibition of alpha-KG-dependent histone and DNA demethylases by fumarate and succinate that are accumulated in mutations of FH and SDH tumor suppressors[END_REF]. However, the precise impact of SDH and FDH mutations in T cell differentiation and function remain unclear.

Epigenetic control not only requires methylation/demethylation events, but also involves acetylation consisting in post-transcriptional modifications mediated by histone acetyltransferases. These enzymes use Acetyl-CoA as substrate which can be originated from the citrate, another TCA cycle metabolite [START_REF] Gaber | Metabolism of T Lymphocytes in Health and Disease[END_REF]. Actually, acetyl-CoA-mediated histone acetylation (Figure 22) was already demonstrated to be important to regulate the transcription of Ifng , thus promoting Th1 cell differentiation [START_REF] Peng | Aerobic glycolysis promotes T helper 1 cell differentiation through an epigenetic mechanism[END_REF].

D. Lipid metabolism

Depending on the T cell subset, FAS and FAO are more or less engaged. The role of fatty acids in CD8 + T cells is mainly associated with the generation of murine memory cells [START_REF] Pearce | Enhancing CD8 T-cell memory by modulating fatty acid metabolism[END_REF] since CD8 + effector cells rely mainly on glycolysis (discussed in section III 4).

Within murine CD4 + T cell compartment, Treg cells as compared to Th cells, were less glycolytic and rely mainly on FAO (Michalek et al., 2011). However, another study done in human T cells showed that freshly isolated Treg cells were highly glycolytic comparing to Tconv cells and that FAO was upregulated only upon activation and during proliferation [START_REF] Procaccini | The Proteomic Landscape of Human Ex Vivo Regulatory and Conventional T Cells Reveals Specific Metabolic Requirements[END_REF]. Furthermore, Cluxton and colleagues demonstrated that human Treg cells not only exhibited increased FAO but also increased glycolysis upon TCR stimulation [START_REF] Cluxton | Differential Regulation of Human Treg and Th17 Cells by Fatty Acid Synthesis and Glycolysis[END_REF].The recruitment of FAO metabolic program in Treg cells could explain the capacity of these cells to adapt to environments rich in FAs as it was demonstrated FoxP3 expression is sufficient to upregulate FAO and OXPHOS related proteins and therefore favors the survival of Treg cells (Howie et al., 2017a). Moreover, it was demonstrated that FoxP3 induces OXPHOS and increases the NAD/NADH ratio to overcome lactate-mediated inhibition of proliferation [START_REF] Angelin | Foxp3 Reprograms T Cell Metabolism to Function in Low-Glucose, High-Lactate Environments[END_REF]. These mechanisms could justify the capacity of Treg cells to adapt to environments rich in FAs, lactate and poor in glucose. Another study demonstrated that FAO is required for Treg differentiation by using etomoxir (FAO inhibitor through CPT1) (Michalek et al., 2011). However, two studies demonstrated recently that, when used at high concentrations (as in the study by Michalek and colleagues), etomoxir induces CPT1a-independent off-targets resulting in severe oxidative stress and decreased OXPHOS instead of long-chain fatty acid oxidation inhibition per se [START_REF] O'connor | The CPT1a inhibitor, etomoxir induces severe oxidative stress at commonly used concentrations[END_REF]Raud et al., 2018). Furthermore, using CPT1 -/-mice or etomoxir at non-toxic concentrations, it was shown that FAO inhibition did not impact Treg differentiation (Raud et al., 2018).

Finally, another study showed that pharmalogical/genetic inhibition of FAS did not impact Treg development since Treg cells used mainly exogenous FAs from the surrounding environment (Berod et al., 2014). Though, other study indicated that intratumoral Treg cells displayed an intracellular lipid accumulation due and increased rate on FAS that complement glycolysis to sustain Treg cell expansion [START_REF] Pacella | Fatty acid metabolism complements glycolysis in the selective regulatory T cell expansion during tumor growth[END_REF]. Therefore, the overall picture of FAS/FAO role in Treg differentiation/function remains a controversy subject of ongoing investigation.

Th17 cells were described as a T cell subset that favors a lipogenic mode of metabolism for their development where ACC1 is highly required (Berod et al., 2014). In this study, they showed that Th17 cells depend on fatty acid synthesis to produce cellular membrane phospholipids which were important for their metabolic program (Berod et al., 2014).

Another very recent study done in human T cells went in the same direction highlighting the importance of FAS for Th17 cell function [START_REF] Cluxton | Differential Regulation of Human Treg and Th17 Cells by Fatty Acid Synthesis and Glycolysis[END_REF]. Furthermore, an elegant study also established that the balance between saturated and polyunsaturated FAs, which is controlled by CD5L expression, can determine the pathogenic vs non-pathogenic profile of Th17 cells [START_REF] Wang | CD5L/AIM Regulates Lipid Biosynthesis and Restrains Th17 Cell Pathogenicity[END_REF]. Down-regulation of CD5L promoted pathogenic Th17 cells by changing the fatty acid composition and increasing cholesterol synthesis [START_REF] Wang | CD5L/AIM Regulates Lipid Biosynthesis and Restrains Th17 Cell Pathogenicity[END_REF] which was previously demonstrated to be important for Th17 function since is a precursor of RORγT ligands [START_REF] Santori | Identification of natural RORgamma ligands that regulate the development of lymphoid cells[END_REF][START_REF] Soroosh | Oxysterols are agonist ligands of RORgammat and drive Th17 cell differentiation[END_REF].

The role of cholesterol in T cell activation is well described, however, its role on T cell differentiation and its importance among the different T cell subsets have been so far less addressed. It is known that levels of cholesterol in the microenvironment can impact T cell differentiation. For instance, it was demonstrated by different studies that hypercholesterolemia promoted inflammation and enhanced TCR stimulation, T cell proliferation and Treg cell development [START_REF] Maganto-Garcia | Hypercholesterolemia-induced regulatory T cell responses detected in FOXP3-GFP x LDLR-/-mice[END_REF]Mailer et al., 2017a;Mailer et al., 2017b).

T cell differentiation and effector function can also be impacted by the cholesterol biosynthesis pathway (discussed on section II 3). Several studies pointed out that statinsmediated inhibition of cholesterol synthesis was associated with enhanced Treg differentiation [START_REF] Forero-Pena | Statins as modulators of regulatory T-cell biology[END_REF]. However, another study showed that the inhibition of the cholesterol pathway blocked Treg suppressive capacity (Zeng et al., 2013).

Therefore, the role of cholesterol biosynthesis on Treg differentiation is not fully understood.

Nevertheless, it was shown that cholesterol esterification in CD8 T cells through the inhibition of the enzyme ACAT1 potentiated antiviral functions (Yang et al., 2016b).

Finally, LXR also have a role in T cell differentiation. Indeed, in EAE model, the treatment with a LXR decreased Th17 differentiation resulting in decrease disease severity [START_REF] Xu | Liver X receptor agonist regulation of Th17 lymphocyte function in autoimmunity[END_REF]. Furthermore, it was shown that the use of LXR agonists enhances Treg differentiation [START_REF] Herold | Liver X receptor activation promotes differentiation of regulatory T cells[END_REF].

More indirectly, ABCA1/G1 deficient-dendritic cells resulted in enhanced T cell activation, increased T cell numbers on lymph nodes and enhanced Th1 and Th17 polarizations due to inflammasome activation, GMCSF and inflammatory cytokines secretion, highlighting the importance of cholesterol efflux transporters in maintaining immune tolerance. (Westerterp et al., 2017).

The metabolic signatures of Teff and Treg cells is summarized on Figure 23.

E. Arginine metabolism

A recent study demonstrated extracellular concentrations of arginine could impact on the T cell phenotype and effector function. Geiger and colleagues showed, in mice, that high extracellular arginine levels modulated the regulation of several metabolic programs, downregulating glycolysis and upregulating OXPHOS [START_REF] Geiger | L-Arginine Modulates T Cell Metabolism and Enhances Survival and Anti-tumor Activity[END_REF]. Furthermore, high extracellular arginine levels limited T cell differentiation and maintain cells in a centralmemory-like state with great anti-tumor properties [START_REF] Geiger | L-Arginine Modulates T Cell Metabolism and Enhances Survival and Anti-tumor Activity[END_REF]. Finally, another recent study performed in infantile rats reveals that arginine supplementation enhances Th1 response following activation by concanavalin A (Con A) or lipopolysaccharide (LPS) (Lee et Th1, Th2, Th17 cells depend mainly on carbon substrates such as glucose and glutamine in order to fulfill their biosynthetic demands and to produce energy through aerobic glycolysis and OXPHOS. Additionally, Th17 cells rely also on de novo fatty acid synthesis for their differentiation. Despite the fact that Treg cells engage glycolysis, this subset depends on FAO for suppressive function. FAS (fatty acid synthesis), GLYC (glycolysis), OXPHOS (oxidative phosphorylation), Th (T helper), TEFF (T effector), Treg (T regulatory), Adapted from: [START_REF] Geltink | Unraveling the Complex Interplay Between T Cell Metabolism and Function[END_REF][START_REF] Newton | Immunometabolism of regulatory T cells[END_REF] al., 2018). Moreover, both arginine and citrulline based-therapies in infantile rats could modulate Treg immune effects by increasing IL-10 levels [START_REF] Lee | L-Arginine and L-Citrulline Supplementation Have Different Programming Effect on Regulatory T-Cells Function of Infantile Rats[END_REF].

F. mTOR and AMPK signaling pathway

Despite its role in metabolic regulation and T cell activation, mTOR has also a crucial implication in T cell differentiation. The conditional deletion of mTOR altered Th1, Th2 and Th17 differentiation while promoted Treg differentiation [START_REF] Delgoffe | The mTOR kinase differentially regulates effector and regulatory T cell lineage commitment[END_REF]. Furthermore, as mTOR can be part of 2 different complexes (mTORC1 and mTORC2), Delgoffe and colleagues further demonstrated that mTORC1 was required for Th1 and Th17 differentiations, while Rictor and therefore mTORC2 was required specifically for the Th2 development (Delgoffe et al., 2011). Controversially, further studies demonstrated that deletion of Raptor (as discussed in section II, a mTORC1-associated protein) was important for Th17 differentiation but not for Th1 development [START_REF] Kurebayashi | PI3K-Akt-mTORC1-S6K1/2 axis controls Th17 differentiation by regulating Gfi1 expression and nuclear translocation of RORgamma[END_REF]. Moreover, Raptor deletion showed as well an important mTORC1 role in Th2 development [START_REF] Yang | T cell exit from quiescence and differentiation into Th2 cells depend on Raptor-mTORC1-mediated metabolic reprogramming[END_REF]. Interestingly, and despite the studies from Delgoffe and colleagues showing that the absence of mTOR resulted in T cells with a Treg phenotype (Delgoffe et al., 2011), the role of mTOR in Treg cells is still debated. Indeed, few other studies demonstrated that deletion of mTOR signaling pathway components induced Treg generation [START_REF] Battaglia | Expanding human T regulatory cells with the mTOR-inhibitor rapamycin[END_REF][START_REF] Chang | Sin1 regulates Treg-cell development but is not required for T-cell growth and proliferation[END_REF][START_REF] Haxhinasto | The AKT-mTOR axis regulates de novo differentiation of CD4+Foxp3+ cells[END_REF]. However, other groups showed that mTOR activity was important to support Treg proliferation and it was increased in human Treg cells [START_REF] Battaglia | Rapamycin promotes expansion of functional CD4+CD25+FOXP3+ regulatory T cells of both healthy subjects and type 1 diabetic patients[END_REF][START_REF] Procaccini | An oscillatory switch in mTOR kinase activity sets regulatory T cell responsiveness[END_REF][START_REF] Valmori | Rapamycin-mediated enrichment of T cells with regulatory activity in stimulated CD4+ T cell cultures is not due to the selective expansion of naturally occurring regulatory T cells but to the induction of regulatory functions in conventional CD4+ T cells[END_REF]. Another elegant study demonstrated that mTORC1 was a pivotal determinant of Treg suppressive activity while it did not directly affect Foxp3 expression (Zeng et al., 2013). Finally, another recent study done in mice revealed that mTOR inhibition promoted generation of long-lived central Tregs with a memory-like phenotype while mTOR function was required for the generation of effector Treg cells [START_REF] Sun | mTOR Complex 1 Signaling Regulates the Generation and Function of Central and Effector Foxp3(+) Regulatory T Cells[END_REF]. Thus, a balanced mTOR activity is required to maintain Treg cells stability and function [START_REF] Zeng | mTOR signaling in the differentiation and function of regulatory and effector T cells[END_REF]. The roles of mTOR complexes during T cells differentiation are depicted in Figure 24.

AMPK, as mentioned in the section II 5 is another energy sensor involved in the regulation of cell metabolism. Activation of AMPK inhibits mTOR signaling, favoring catabolism. Therefore, it was not surprising that AMPK activation could impact Th/Treg cell differentiation. Indeed, studies performed in CD4 + T cells showed that AMPK activation by metformin prevented the efficient polarization of Th1 and Th17 cells [START_REF] Kang | Metformin downregulates Th17 cells differentiation and attenuates murine autoimmune arthritis[END_REF][START_REF] Zhao | Metformin decreases IL-22 secretion to suppress tumor growth in an orthotopic mouse model of hepatocellular carcinoma[END_REF], suggesting a role of AMPK as negative regulator in Th1 and Th17 differentiation.

However, the role of AMPK on Treg cells appears to be different. TFG-β signals that were important for iTreg differentiation [START_REF] Marie | TGF-beta1 maintains suppressor function and Foxp3 expression in CD4+CD25+ regulatory T cells[END_REF] are also required for AMPK activation [START_REF] Xie | A pivotal role for endogenous TGF-beta-activated kinase-1 in the LKB1/AMP-activated protein kinase energy-sensor pathway[END_REF]. Indeed, AMPK activation was required to promote FAO which promotes Treg differentiation [START_REF] Gualdoni | The AMP analog AICAR modulates the Treg/Th17 axis through enhancement of fatty acid oxidation[END_REF]Michalek et al., 2011). Furthermore, under Th17 polarizing conditions, AMPK activation dampened Th17 induction and induced FoxP3 expression [START_REF] Gualdoni | The AMP analog AICAR modulates the Treg/Th17 axis through enhancement of fatty acid oxidation[END_REF]. Moreover, Treg-specific LKB1 deletion (one of the activators of AMPK, discussed on section II 5) impacted Treg function and survival due to defective mitochondria, compromised OXPHOS, altered cellular metabolism and decreased ATP levels (He et al., 2017).

4) Memory T cells

At steady state, memory T cells share some common features with naïve T cells, illustrated by 95% similarity in gene expression [START_REF] Weng | The molecular basis of the memory T cell response: differential gene expression and its epigenetic regulation[END_REF]. Thus, it is not surprising that memory T cells present a metabolism similar to that of naïve T cells relying mainly on OXPHOS and FAO [START_REF] Almeida | Metabolic pathways in T cell activation and lineage differentiation[END_REF][START_REF] Verbist | T cell metabolism and the immune response[END_REF]. However, upon TCR activation, memory T metabolic response is faster and more intense as compared to naïve T cells [START_REF] Gubser | Rapid effector function of memory CD8+ T cells requires an immediate-early glycolytic switch[END_REF][START_REF] Van Der Windt | CD8 memory T cells have a bioenergetic advantage that underlies their rapid recall ability[END_REF]. Furthermore, because of increased mitochondrial biogenesis, CD8 + memory T cell also have a greater mitochondrial mass than naïve T cells displaying an increased spare respiratory capacity (SRC) [START_REF] Dimeloe | The Immune-Metabolic Basis of Effector Memory CD4+ T Cell Function under Hypoxic Conditions[END_REF][START_REF] Van Der Windt | Mitochondrial respiratory capacity is a critical regulator of CD8+ T cell memory development[END_REF][START_REF] Van Der Windt | CD8 memory T cells have a bioenergetic advantage that underlies their rapid recall ability[END_REF]. In line with this result, another study revealed that CD8 + T cells with low glucose uptake (based on the uptake of a fluorescent 2-NBDG glucose analogue) correlated with memory T cell phenotype [START_REF] Sukumar | Inhibiting glycolytic metabolism enhances CD8+ T cell memory and antitumor function[END_REF], highlighting the low glycolytic profile of memory T cells.

Several factors are involved in the regulation of memory T cell metabolism, among which is IL-15. In CD8 + T cells, IL-15-mediated signaling increases mitochondrial biogenesis and expression of CPT1 resulting in an increased SRC and FAO, respectively (van der [START_REF] Van Der Windt | Mitochondrial respiratory capacity is a critical regulator of CD8+ T cell memory development[END_REF]. However, the concentrations of etomoxir used in this study were further demonstrated to have CPT1a-independent off-targets, as discussed in the section III 3 D, which makes complicated the interpretation of the results (O' Connor et al., 2018;Raud et al., 2018). Mitochondrial dynamics is also important for memory T cell generation as it was demonstrated, in mice, that the differentiation of memory cells required the expression of Opa1 (optic atrophy 1), a molecule involved in mitochondrial fusion and promoting efficient ETC activity [START_REF] Cogliati | Mitochondrial cristae shape determines respiratory chain supercomplexes assembly and respiratory efficiency[END_REF]. Indeed when mitochondrial fusion is enforced in effector cells, they acquire memory T cell characteristics [START_REF] Buck | Mitochondrial Dynamics Controls T Cell Fate through Metabolic Programming[END_REF].

Energy-sensing pathways were also shown to have a preponderant role in memory T cell differentiation. Contrary to its role in CD8 + effector T cells, mTOR was shown to be a negative regulator in memory T cell generation. In a mice, mTOR inhibition through rapamycin treatment induced CD8 + T cell differentiation to a memory phenotype [START_REF] Araki | mTOR regulates memory CD8 T-cell differentiation[END_REF]. Furthermore, siRNA-mediated reduction of mTORC1 signaling as well as inhibition of mTORC2 in CD8 + T cell was also resulting in memory T cell generation [START_REF] Berezhnoy | Aptamer-targeted inhibition of mTOR in T cells enhances antitumor immunity[END_REF].

Moreover, it was demonstrated that AMPK promoted memory T cell formation [START_REF] Rolf | AMPKalpha1: a glucose sensor that controls CD8 T-cell memory[END_REF] and TRAF-6 (TNF receptor associated factor 6) was important for effective AMPK activation and consequent increase on FAO [START_REF] Pearce | Enhancing CD8 T-cell memory by modulating fatty acid metabolism[END_REF]. Also, the activation of AMPK by metformin in activated T cell resulted in increased FAO and CD8 + memory T cell differentiation [START_REF] Pearce | Enhancing CD8 T-cell memory by modulating fatty acid metabolism[END_REF]. Further, AMPK activity on memory CD8 + T cells (at the expense of mTOR activation) increased CPT1 activity and supported the mitochondrial uptake of fatty acids. These mechanisms resulted in a decreased dependence on glucose metabolism [START_REF] Buzzai | The glucose dependence of Akt-transformed cells can be reversed by pharmacologic activation of fatty acid beta-oxidation[END_REF].

IV. The tumor metabolic environment and Chimeric antigen receptor (CAR) T cell immunotherapies 1) Immunity shapes the tumorcancer immunoediting

The role of the immune system in controlling cancer was not always a subject of debate.

In early 1900s, Paul Ehrlich had the theory that without the immune system, cancer would be probably a pathology with a higher incident rate [START_REF] Ehrlich | Ueber den jetzigen stand der Karzinomforschung Nederlandsch Tijdschrift voor Geneeskunde[END_REF]. However, since little was known about the immune system at that time it was difficult to prove this theory. For a long time, the contribution of the immune system to tumor surveillance was under debate and it was only in late 1950s that Burnet and Thomas proposed, for the first time, a major implication in cancer immunosurveillance and that immune cells play an important role in preventing cancer development in immunocompetent hosts [START_REF] Burnet | Cancer; a biological approach. I. The processes of control[END_REF][START_REF] Thomas | Cellular and Humoral Aspects of the Hypersensitive States[END_REF].

Since then, many scientific discoveries supported the role of immune cells in anti-tumor responses. However, in 2001, another discovery led to the revision of the cancer immunosurveillance hypothesis proposed by Burnet and Thomas [START_REF] Shankaran | IFNgamma and lymphocytes prevent primary tumour development and shape tumour immunogenicity[END_REF].

Indeed, when intracellular tumor suppressor mechanisms fail, upon cellular transformation, several immune mechanisms are involved in the recognition and elimination of these transformed cells. Despite the pressure of the immune system, an equilibrium phase establishes and tumor cells with reduced immunogenicity escape immunosurveillance and, as a result, pursue transformation by genetic and epigenetic changes. In the final phase, these alterations will allow escape from immune detection and elimination, resulting in the expansion of the cell clones transformed at the equilibrium phase and generation of a tumor.

All these different phases (elimination, equilibrium, escape) demonstrate that the immune system not only protects the host from tumor generation but also shapes tumor immunogenicity in a process called cancer immunoediting [START_REF] Schreiber | Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion[END_REF]. This gap in the host's immune system can lead to alterations in tumor cells that can notably affect tumor recognition (downregulation of MHC molecules) or induce T cell apoptosis and condition the TME (tumor microenvironment) [START_REF] Dunn | The three Es of cancer immunoediting[END_REF]. The TME is a really complex environment, composed of different actors in which tumor cells take part. The explanation of how the TME is composed and how it can impact T cell anti-tumor function is described in the next section.

2) Tumor microenvironment

Solid tumors are not only composed of clones of cancer cells but they also include several other cell types such as endothelial cells, stromal fibroblasts, adipocytes, extracellular matrix molecules and immune cells in a highly disorganized version of what we would find in normal organs [START_REF] Egeblad | Tumors as organs: complex tissues that interface with the entire organism[END_REF]. This structure favors the development of hypoxic environments that represents an adverse prognostic factor for patient outcome [START_REF] Vaupel | Hypoxia in cancer: significance and impact on clinical outcome[END_REF].

Furthermore, these structures vary between tumors, which add to the complexity of solid tumors.

In 2000, an iconic review came out describing the six hallmarks of cancer. In this review, the authors discussed about the remarkable diversity of neoplastic diseases due the capacity of tumor cells to sustain proliferative signaling, to evade growth suppressor genes, to activate invasion and metastasis, to enable replicative immortality, to induce angiogenesis and finally to resist cell death [START_REF] Hanahan | The hallmarks of cancer[END_REF]. Eleven years later, the same authors pursued their initial discussion to integrate new raised questions and to highlight new mechanistic concepts and notably the following two hallmarks: Dysregulation of cellular energetics and mechanisms to avoid immune destruction [START_REF] Hanahan | Hallmarks of cancer: the next generation[END_REF].

Therefore, not only the capacity of tumor cells to evade immunological destruction by B and T cells was discussed but also the capacity of cancer cells to modify and reprogram cellular metabolism was pointed out as a crucial factor to support neoplastic proliferation [START_REF] Hanahan | Hallmarks of cancer: the next generation[END_REF]. As a result, in the past years, the concept that tumors are more than an assembly of tumorigenic cells but instead a complex system where the TME should be taken into account was consolidated [START_REF] Hanahan | Hallmarks of cancer: the next generation[END_REF]. How the TME impacts on T cell anti-tumor functions, in particular through nutrient availability and hypoxia, will be discussed in the next two sections (section IV 2 A and IV 2 B).

A. Nutrient competition

As explained in the section III, several metabolic pathways are crucial for T cells and their engagement plays then an important role to sustain T cell activation, differentiation and effector functions. Tumors are poorly vascularized and highly glycolytic resulting in the generation of a surrounding environment with reduced glucose and amino acid levels [START_REF] Johnson | Nutrients and the microenvironment to feed a T cell army[END_REF] and high levels of waste products such as lactate [START_REF] Romero-Garcia | Lactate Contribution to the Tumor Microenvironment: Mechanisms, Effects on Immune Cells and Therapeutic Relevance[END_REF]. Once tumor-infiltrating T cells (TILs) infiltrate the tumor, they face an adverse TME that not only can impact their activation and differentiation, but also their anti-tumor function.

a) Glucose deprivation

Tumor cells are highly glycolytic [START_REF] Warburg | The Metabolism of Carcinoma Cells[END_REF] and several recent studies have demonstrated the importance of metabolic pathways coordinating glucose and lactate metabolisms in several cancer types [START_REF] Doherty | Targeting lactate metabolism for cancer therapeutics[END_REF][START_REF] Draoui | Lactate shuttles at a glance: from physiological paradigms to anti-cancer treatments[END_REF][START_REF] Hensley | Metabolic Heterogeneity in Human Lung Tumors[END_REF][START_REF] Kennedy | Catabolism of exogenous lactate reveals it as a legitimate metabolic substrate in breast cancer[END_REF][START_REF] Ruan | Lactate engages receptor tyrosine kinases Axl, Tie2, and vascular endothelial growth factor receptor 2 to activate phosphoinositide 3-kinase/Akt and promote angiogenesis[END_REF]. Cancer cells and endothelial cells in the TME are able to regulate lactate transport via the monocarboxylate transporter (MCT) 1 which is released by glycolytic cancer cells mainly through MCT4 [START_REF] Sonveaux | Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice[END_REF][START_REF] Vegran | Lactate influx through the endothelial cell monocarboxylate transporter MCT1 supports an NF-kappaB/IL-8 pathway that drives tumor angiogenesis[END_REF]. Inhibition of MCT1 can impact the metabolic preferences of cancer cells forcing them to use glucose, reducing the availability of lactate for tumor cells in hypoxic environments and thereby impacting their survival [START_REF] Sonveaux | Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice[END_REF]. Moreover, the inhibition of MCT4 directly targets tumor cells in hypoxic environments and promotes cell death through the intracellular accumulation of lactate [START_REF] Draoui | Lactate shuttles at a glance: from physiological paradigms to anti-cancer treatments[END_REF]. These works highlight the importance of lactate as a cell metabolic fuel. However, cancer cells are not the only ones requiring high amount of glucose in the TME. A study performed in prostate cancer showed that cancer associated fibroblasts (CAFs) present high GLUT1 expression, glucose uptake, MCT4 expression and lactate release [START_REF] Fiaschi | Reciprocal metabolic reprogramming through lactate shuttle coordinately influences tumor-stroma interplay[END_REF].

In presence of CAFs, the surrounding cancer cells increase their lactate intake highlighting the importance of the tumor-stromal interplay [START_REF] Fiaschi | Reciprocal metabolic reprogramming through lactate shuttle coordinately influences tumor-stroma interplay[END_REF][START_REF] Rattigan | Lactate is a mediator of metabolic cooperation between stromal carcinoma associated fibroblasts and glycolytic tumor cells in the tumor microenvironment[END_REF].

As discussed in the section III 3 we, among others, demonstrated that glucose is important for IFNγ secretion and for pro-inflammatory functions [START_REF] Cham | Glucose deprivation inhibits multiple key gene expression events and effector functions in CD8+ T cells[END_REF][START_REF] Cretenet | Cell surface Glut1 levels distinguish human CD4 and CD8 T lymphocyte subsets with distinct effector functions[END_REF]Macintyre et al., 2014). Thus, it is expected that the low glucose availability generated in the TME could negatively impact on T cell anti-tumor function. For instance, in a mouse sarcoma model, Chang and colleagues demonstrated that glucose restriction on the TME reduced the glycolytic capacity, mTOR activity and IFNγ secretion of tumor-infiltrating T cells, therefore favoring tumor progression (Chang et al., 2015). Another elegant study demonstrated that reduction of glycolysis resulted in a decrease in phosphoenolpyruvate (PEP), a glucose-derived metabolite, impacting calcium signaling and therefore anti-tumor responses [START_REF] Ho | Phosphoenolpyruvate Is a Metabolic Checkpoint of Anti-tumor T Cell Responses[END_REF]. Also, using an human ovarian cancer chimeric model in a tumorimposed glucose restriction context, microRNAs miR-101 and miR-26a were induced limiting the expression of the methyltransferase EZH2 which therefore is important for Notch pathway activation and consequently T cell cytokine production induction [START_REF] Zhao | Cancer mediates effector T cell dysfunction by targeting microRNAs and EZH2 via glycolysis restriction[END_REF].

The lactate that results from cancer glycolytic activity also impairs T cell effector capacity [START_REF] Romero-Garcia | Lactate Contribution to the Tumor Microenvironment: Mechanisms, Effects on Immune Cells and Therapeutic Relevance[END_REF], with several studies demonstrating that lactate contributes to T cell suppressive functions [START_REF] Calcinotto | Modulation of microenvironment acidity reverses anergy in human and murine tumor-infiltrating T lymphocytes[END_REF][START_REF] Fischer | Inhibitory effect of tumor cell-derived lactic acid on human T cells[END_REF]. High lactate concentration exposure impairs NFAT activation as well as IFNγ secretion [START_REF] Brand | LDHA-Associated Lactic Acid Production Blunts Tumor Immunosurveillance by T and NK Cells[END_REF] and in addition, T cell mobility and cytolytic functions were impacted as well. However, even if low-glucose/high-lactate environments impact negatively T cell function, FoxP3-expressing

Treg cells seem to have the metabolic capacity to overcome this negative TME environment [START_REF] Angelin | Foxp3 Reprograms T Cell Metabolism to Function in Low-Glucose, High-Lactate Environments[END_REF]. Indeed, Treg cells have been associated with pro-tumor activity in several cancer types [START_REF] Curiel | Specific recruitment of regulatory T cells in ovarian carcinoma fosters immune privilege and predicts reduced survival[END_REF][START_REF] Jiang | FOXP3+ lymphocyte density in pancreatic cancer correlates with lymph node metastasis[END_REF][START_REF] Sayour | Increased proportion of FoxP3+ regulatory T cells in tumor infiltrating lymphocytes is associated with tumor recurrence and reduced survival in patients with glioblastoma[END_REF][START_REF] Tang | An increased abundance of tumor-infiltrating regulatory T cells is correlated with the progression and prognosis of pancreatic ductal adenocarcinoma[END_REF][START_REF] Tao | Prognostic potential of FOXP3 expression in non-small cell lung cancer cells combined with tumor-infiltrating regulatory T cells[END_REF][START_REF] Yang | Intratumoral CD4+CD25+ regulatory T-cell-mediated suppression of infiltrating CD4+ T cells in B-cell non-Hodgkin lymphoma[END_REF] and bad prognosis.

b) Glutamine deprivation

Glutaminolysis is also a crucial metabolic pathway for some cancer cells types [START_REF] Medina | Relevance of glutamine metabolism to tumor cell growth[END_REF][START_REF] Souba | Glutamine and cancer[END_REF]. Several studies revealed that cancer cells such as non-small cell lung cancer (NSCLC), breast, brain and liver tumor cells are highly dependent on glutamine for their growth and survival [START_REF] Choi | Targeting Glutamine Metabolism for Cancer Treatment[END_REF]. It was demonstrated that glutamine synthase (GS)

is an important enzyme for fueling nucleotide biosynthesis and to support the growth of glutamine-restricted glioblastoma [START_REF] Tardito | Glutamine synthetase activity fuels nucleotide biosynthesis and supports growth of glutamine-restricted glioblastoma[END_REF]. Furthermore, another study showed that both GS activity in CAFs and glutaminases in cancer cells are two important enzymes for tumor growth and metastasis (Yang et al., 2016a). Thus, it is not surprising that in some cases, TILs will find a glutamine-depleted TME. As detailed in the section section III 3 B, glutamine is also essential during naïve T cells activation/differentiation to a Th1 fate. Furthermore, glutamine deprivation pushes naïve T cells to differentiate into Tregs which, as mentioned before, are important pro-tumor players (Klysz et al., 2015;[START_REF] Metzler | Restricting Glutamine or Glutamine-Dependent Purine and Pyrimidine Syntheses Promotes Human T Cells with High FOXP3 Expression and Regulatory Properties[END_REF].

c) Arginine deprivation and byproducts

In the TME, myeloid-derived suppressor cells (MDSC), tumor-associated macrophages (TAM) and DC are immune cells that also play a crucial role in the maintenance of an hostile environment for anti-tumor effector T cells [START_REF] Marigo | Tumor-induced tolerance and immune suppression by myeloid derived suppressor cells[END_REF]. It is well known that one of the metabolic features of both MDSC and TAMs is their capacity to rapidly degrade arginine [START_REF] Lyssiotis | Metabolic Interactions in the Tumor Microenvironment[END_REF][START_REF] Marigo | Tumor-induced tolerance and immune suppression by myeloid derived suppressor cells[END_REF] which is either catabolized by Arg1 or NOS2 and results in urea and ornithine production or in citrulline and NO production respectively [START_REF] Bronte | L-arginine metabolism in myeloid cells controls T-lymphocyte functions[END_REF]. As a consequence, arginine catabolization results in reduced arginine availability (which is crucial for T cells as discussed in the section III 2 E) and also in the generation of byproducts (such as NO) that can impact T cell function. In a murine lung carcinoma model, the production of Arg1 in the TME by myeloid cells was already shown to inhibit T cell receptor CD3ζ chain surface expression and antigen-specific T cell proliferation [START_REF] Rodriguez | Arginase I production in the tumor microenvironment by mature myeloid cells inhibits T-cell receptor expression and antigenspecific T-cell responses[END_REF]. Another study in renal cell carcinoma patients demonstrated that these patients had low levels of arginine and high levels of ornithine in the plasma due myeloid cells activity, highlighting the role of Arg1 in tumor progression [START_REF] Zea | Arginase-producing myeloid suppressor cells in renal cell carcinoma patients: a mechanism of tumor evasion[END_REF].

Moreover, NO released from these heterogeneous groups of MDSC was able to inhibit T cell responses due to an impairment of the IL-2R signaling pathway (defects in the phosphorylation of janus kinase JAKs, STAT5, ERK and AKT) [START_REF] Bingisser | Macrophage-derived nitric oxide regulates T cell activation via reversible disruption of the Jak3/STAT5 signaling pathway[END_REF][START_REF] Mazzoni | Myeloid suppressor lines inhibit T cell responses by an NO-dependent mechanism[END_REF].

d) Tryptophan degradation and IDO activity

Another important player in the TME are IDO (indoleamine 2,3 deoxygenase)-expressing cells that can be found in both murine and human tumor contexts [START_REF] Munn | Indoleamine 2,3-dioxygenase and tumor-induced tolerance[END_REF].

IDO is an enzyme which catabolizes tryptophan and in response to TGF-β, acts as signal transducer important for plasmocytoid DCs tolerogenic phenotype [START_REF] Chen | IDO: more than an enzyme[END_REF]. IDO enzymatic activity is important for the creation of a suppressive TME which, through the reduction of tryptophan availability, suppresses T cell responses and enhances Treg-mediated suppression [START_REF] Munn | Indoleamine 2,3-dioxygenase and tumor-induced tolerance[END_REF]). An elegant study demonstrated that most human tumors constitutively express IDO and the tumors that express IDO are resistant to immune rejection [START_REF] Uyttenhove | Evidence for a tumoral immune resistance mechanism based on tryptophan degradation by indoleamine 2,3-dioxygenase[END_REF]. IDO activity can also affect T cell priming: the presence of a small population of IDO-expressing plasmacytoid DCs in tumor-draining lymph nodes was described to create a suppressive microenvironment impacting anti-tumor T cell responses [START_REF] Munn | Expression of indoleamine 2,3-dioxygenase by plasmacytoid dendritic cells in tumor-draining lymph nodes[END_REF]. Moreover, this same IDO-expressing DC population could directly activate mature Treg cell in tumor-draining lymph nodes [START_REF] Sharma | Plasmacytoid dendritic cells from mouse tumor-draining lymph nodes directly activate mature Tregs via indoleamine 2,3-dioxygenase[END_REF]. Blocking IDO activity is considered as a potential strategy to enhance anti-tumor immunity [START_REF] Munn | Blocking IDO activity to enhance anti-tumor immunity[END_REF].

As discussed above, the metabolic activity of myeloid cells can have a negative impact on anti-tumor functions. Nevertheless, it is essential to take in consideration that the TME can impact myeloid cell functions. Immune responses are characterized as transient going through "on" (cytotoxic activity and cytokine release) and "off" (immunosuppression) phases [START_REF] Bercovici | Revisiting the role of T cells in tumor regression[END_REF]). Both T cells and myeloid cells go through these phases that are not necessarily synchronized between them [START_REF] Bercovici | Revisiting the role of T cells in tumor regression[END_REF]. One possible model is that when T cells infiltrate the TME, myeloid cells (which are recruited first) are already in this long "off" phase conditioned by the surrounding environment. The cooperation between T -myeloid cells occurs at the tumor site [START_REF] Bercovici | Analysis and characterization of antitumor Tcell response after administration of dendritic cells loaded with allogeneic tumor lysate to metastatic melanoma patients[END_REF][START_REF] Thoreau | Vaccine-induced tumor regression requires a dynamic cooperation between T cells and myeloid cells at the tumor site[END_REF] where the TME can interfere with it, pushing myeloid cells to have a pro-tumor role. Therefore, the role of the TME on myeloid and its cooperation with T cells should be also taken in consideration to improve anti-tumor responses.

e) Lipid metabolism

Another feature associated with cancer cells is the increased lipid biosynthesis [START_REF] Zaidi | Lipogenesis and lipolysis: the pathways exploited by the cancer cells to acquire fatty acids[END_REF]. De novo FAS contributes to generate lipids and phospholipids required for the plasma membrane as well as lipid droplets in proliferating cancer cells [START_REF] Zaidi | Lipogenesis and lipolysis: the pathways exploited by the cancer cells to acquire fatty acids[END_REF]. This high lipid synthesis is associated with a membrane composed mainly by high saturated/ mono-unsaturated fatty acids that allow cancer cells to be more resistant to oxidative stress [START_REF] Rysman | novo</em> Lipogenesis Protects Cancer Cells from Free Radicals and Chemotherapeutics by Promoting Membrane Lipid Saturation[END_REF]. Fatty acids can also represent a source of energy for tumors that are less glycolytic such as prostate tumors [START_REF] Effert | Metabolic imaging of untreated prostate cancer by positron emission tomography with 18fluorine-labeled deoxyglucose[END_REF][START_REF] Liu | Dominant uptake of fatty acid over glucose by prostate cells: a potential new diagnostic and therapeutic approach[END_REF] and human leukemia cells [START_REF] Samudio | Pharmacologic inhibition of fatty acid oxidation sensitizes human leukemia cells to apoptosis induction[END_REF]. Increased level of FASN expression and activity are detected in cancer cells and correlate with cancer progression [START_REF] Menendez | Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis[END_REF].

However, cancer cells also uptake exogenous fatty acids to fulfill their energetic demands [START_REF] Kuemmerle | Lipoprotein lipase links dietary fat to solid tumor cell proliferation[END_REF]. Several studies demonstrated that targeting several lipid synthesis pathway-related enzymes could result in tumor regression [START_REF] Chajes | Acetyl-CoA carboxylase alpha is essential to breast cancer cell survival[END_REF][START_REF] Hanai | Inhibition of lung cancer growth: ATP citrate lyase knockdown and statin treatment leads to dual blockade of mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-kinase (PI3K)/AKT pathways[END_REF][START_REF] Kridel | Orlistat is a novel inhibitor of fatty acid synthase with antitumor activity[END_REF][START_REF] Mashima | De novo fatty-acid synthesis and related pathways as molecular targets for cancer therapy[END_REF][START_REF] Menendez | Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis[END_REF]. Lipid availability is important for T cell activation, differentiation and function, as summarized in the sections III 2 D and III 3 D, and this should be taken in consideration considering the high demand on lipids by tumor cells. Indeed, lipid and cholesterol intra-tumoral metabolism can impact antitumor function. It was shown that TILs have an abnormal lipid metabolism when compared to non-tumor infiltrated T cells that can be reversed by inhibiting programmed cell death-1 (PD-1) which was initially induced by TME [START_REF] Yin | Tumor infiltrating T cells have abnormal lipid metabolism that can be modulated by PD-L1 blockade[END_REF]. It was also demonstrated that lipid metabolism is also impacted in tumor-associated DCs from the tumor-bearing host, resulting in the accumulation of lipid bodies that impair proper MHCI trafficking and antigen presentation to CD8 + T cells [START_REF] Ramakrishnan | Oxidized lipids block antigen cross-presentation by dendritic cells in cancer[END_REF][START_REF] Veglia | Lipid bodies containing oxidatively truncated lipids block antigen cross-presentation by dendritic cells in cancer[END_REF]. As a result, targeting immune cells lipid metabolism could also represent a strategy in cancer treatment.

Indeed, it was recently revealed that CD8 + anti-tumor responses could be potentiated by modulating cholesterol metabolism (Yang et al., 2016b), highlighting the importance of lipids on anti-tumor function. A summary of the principal points concerning nutrient competition in the TME is described in Figure 25.

B. Hypoxia

Hypoxia is a well-known characteristic of solid tumors associated with a wide range of malignancies [START_REF] Vaupel | Hypoxia in cancer: significance and impact on clinical outcome[END_REF]) (Figure 25). It is also known that hypoxia levels among different solid tumors is distinct [START_REF] Brown | Exploiting tumour hypoxia in cancer treatment[END_REF][START_REF] Byrne | Methods to study the tumor microenvironment under controlled oxygen conditions[END_REF] and that within a tumor tissue, hypoxia levels vary as well notably between the periphery and center of the tumor. In the periphery, tumor cells are better irrigated when compared to the central parts of the tumor tissue, which therefore modulates differently the TME and tumorigenesis [START_REF] Campillo | Differential Oxygenation in Tumor Microenvironment Modulates Macrophage and Cancer Cell Crosstalk: Novel Experimental Setting and Proof of Concept[END_REF][START_REF] Herman | A quantitative theory of solid tumor growth, metabolic rate and vascularization[END_REF][START_REF] Lewis | Intratumoral oxygen gradients mediate sarcoma cell invasion[END_REF][START_REF] Quail | Microenvironmental regulation of tumor progression and metastasis[END_REF][START_REF] Rofstad | Tumor interstitial fluid pressure-a link between tumor hypoxia, microvascular density, and lymph node metastasis[END_REF]. It is commonly accepted that the levels of oxygen (O2) within the tumor tissues are low (between 1% and 2%) when compared to the respective healthy organs [START_REF] Muz | The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy[END_REF]. In human organs, oxygen concentration will vary between 9.5% in the renal cortex [START_REF] Muller | Renocortical tissue oxygen pressure measurements in patients undergoing living donor kidney transplantation[END_REF]) and 4.6% in the brain [START_REF] Dings | Clinical experience with 118 brain tissue oxygen partial pressure catheter probes[END_REF][START_REF] Hoffman | Brain tissue oxygen, carbon dioxide, and pH in neurosurgical patients at risk for ischemia[END_REF]. In murine lymphoid organs, the oxygen tension range between 0.5% and 4.5% [START_REF] Caldwell | Differential effects of physiologically relevant hypoxic conditions on T lymphocyte development and effector functions[END_REF].

Thus, when TILs arrive into the TME, they will most likely encounter an environment lower in O2 availability comparing to their initial location. Hypoxia is an environmental factor impacting cell signaling through activation of the HIF pathway, of which HIF (a transcription factor) is important for cellular adaptation to low oxygen environments [START_REF] Muz | The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy[END_REF][START_REF] Semenza | A nuclear factor induced by hypoxia via de novo protein synthesis binds to the human erythropoietin gene enhancer at a site required for transcriptional activation[END_REF]. Hypoxia is linked to several signaling pathways such as PI3K/AKT/mTOR [START_REF] Agani | Oxygen-independent regulation of HIF-1: novel involvement of PI3K/AKT/mTOR pathway in cancer[END_REF][START_REF] Courtnay | Cancer metabolism and the Warburg effect: the role of HIF-1 and PI3K[END_REF], MAPK/ERK [START_REF] Minet | ERK activation upon hypoxia: involvement in HIF-1 activation[END_REF][START_REF] Sanchez | p38 MAPK: a mediator of hypoxia-induced cerebrovascular inflammation[END_REF] and NFκB pathways [START_REF] Koong | Hypoxia causes the activation of nuclear factor kappa B through the phosphorylation of I kappa B alpha on tyrosine residues[END_REF]) that, once activated, are able to induce the HIF pathway. HIFs mediate through gene regulation several physiological processes that are crucial for tumor development [START_REF] Semenza | Hypoxia-inducible factors: mediators of cancer progression and targets for cancer therapy[END_REF]. For instance, it is involved in the promotion of angiogenesis through induction of vascular endothelial growth factor (VEGF) expression [START_REF] Ahluwalia | Critical role of hypoxia sensor--HIF-1alpha in VEGF gene activation. Implications for angiogenesis and tissue injury healing[END_REF][START_REF] Lin | Hypoxia induces HIF-1alpha and VEGF expression in chondrosarcoma cells and chondrocytes[END_REF] and stromal cell-derived factor 1 (SDF-1) [START_REF] Zagzag | Stromal cell-derived factor-1alpha and CXCR4 expression in hemangioblastoma and clear cell-renal cell carcinoma: von Hippel-Lindau loss-of-function induces expression of a ligand and its receptor[END_REF]. Furthermore, the HIF pathway is important for cell apoptosis regulation and cell survival via the induction of BNIP-3 [START_REF] Guo | Hypoxia induces the expression of the pro-apoptotic gene BNIP3[END_REF], the stabilization of p53 (An et al., 1998), and activation of TGF-β and bFGF [START_REF] Muz | The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy[END_REF]. Hypoxia also inhibits the expression of genes related to cell-surface integrins, thus promoting tumor cell detachment and potential metastasis [START_REF] Hasan | Hypoxia facilitates tumour cell detachment by reducing expression of surface adhesion molecules and adhesion to extracellular matrices without loss of cell viability[END_REF]. Moreover, HIF pathway is important for the regulation of GLUT1, GLUT3 and other glycolytic enzymes [START_REF] Iliopoulos | Negative regulation of hypoxia-inducible genes by the von Hippel-Lindau protein[END_REF][START_REF] Iyer | Cellular and developmental control of O2 homeostasis by hypoxia-inducible factor 1 alpha[END_REF][START_REF] Semenza | HIF-1 mediates metabolic responses to intratumoral hypoxia and oncogenic mutations[END_REF]. Indeed, the induction of HIF-1α increased tumor cell utilization of glucose and lactate release [START_REF] Eales | Hypoxia and metabolic adaptation of cancer cells[END_REF]. Using a glucose tracing in healthy lung tissue and in tumor tissue of non-small lung cell carcinoma patients, an elegant study demonstrated that, even within the same type of tumor, heterogeneity of glucose utilization was observed when compared to benign tumor [START_REF] Hensley | Metabolic Heterogeneity in Human Lung Tumors[END_REF]. Combining a glucose tracing approach and dynamic contrast-enhanced magnetic resonance imaging, Hensley and colleagues demonstrated that in less-perfused regions, glucose was the main source of energy. However, in more-perfused regions, lactate was used as an alternative fuel [START_REF] Hensley | Metabolic Heterogeneity in Human Lung Tumors[END_REF]) that, as described in the beginning of this section, can be transported into cancer cells by MCT1 and used as carbon source. This highlights how oxygen availability in the TME impacts metabolites utilization by tumor cells.

Hypoxia, indeed, impacts T cell metabolism, proliferation and effector function. During my PhD, we showed that, in hypoxic conditions, GLUT1 surface expression was higher as compared to normoxic conditions, and in contrast proliferation and cytokine secretion was diminished [START_REF] Cretenet | Cell surface Glut1 levels distinguish human CD4 and CD8 T lymphocyte subsets with distinct effector functions[END_REF]. Furthermore, and as explained in the section III 2 A, HIF-1α plays many roles in T cell metabolism and function, notably in the regulation of cellular metabolism [START_REF] Kim | HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia[END_REF] and T cell differentiation. However, the role of HIF-1α in Treg cells is still under debate [START_REF] Clambey | Hypoxia-inducible factor-1 alpha-dependent induction of FoxP3 drives regulatory T-cell abundance and function during inflammatory hypoxia of the mucosa[END_REF][START_REF] Dang | Control of T(H)17/T(reg) balance by hypoxia-inducible factor 1[END_REF]Shi et al., 2011) and in CD8

T cells it was demonstrated that HIF-1α increased effector molecules expression and the cytolytic activity [START_REF] Doedens | Hypoxia-inducible factors enhance the effector responses of CD8(+) T cells to persistent antigen[END_REF][START_REF] Finlay | PDK1 regulation of mTOR and hypoxia-inducible factor 1 integrate metabolism and migration of CD8+ T cells[END_REF]. Therefore, it was expected that the hypoxic environment in the TME could modulate HIF1-α activation and, as a result, potentiate T cell anti-tumor responses. This is actually not the case [START_REF] Buck | Metabolic Instruction of Immunity[END_REF] and several reasons could explain this result. One of those is related to the induction of programmed cell death ligand 1 (PD-L1) on tumor cells, TAMs and MDSCs by HIF-1α [START_REF] Noman | PD-L1 is a novel direct target of HIF-1alpha, and its blockade under hypoxia enhanced MDSC-mediated T cell activation[END_REF]. PD-L1 is the ligand of PD-1 expressed on T cell surface following activation which is maintained upon chronic activation mediated for instance by tumor cells. [START_REF] Simon | PD-1 expression on tumor-specific T cells: Friend or foe for immunotherapy?[END_REF]. When PD1 binds to its ligand, the TCR signaling and CD28-costimulation are impaired [START_REF] Hui | T cell costimulatory receptor CD28 is a primary target for PD-1-mediated inhibition[END_REF][START_REF] Yokosuka | Programmed cell death 1 forms negative costimulatory microclusters that directly inhibit T cell receptor signaling by recruiting phosphatase SHP2[END_REF] resulting in reduced proliferation, cytokine secretion and effector function. PD1 + TILs upon binding to PD-L1 expressed by tumor cells or other immune cells have an impaired anti-tumor function, known as checkpoint inhibition [START_REF] Simon | PD-1 expression on tumor-specific T cells: Friend or foe for immunotherapy?[END_REF]. Another parameter to take in consideration is the difficulty to perform experiments in hypoxic conditions, making it hard to mimic the actual physiological conditions found in the TME, which could explain the discrepancies of the previous studies mentioned before.

All these findings highlight hypoxia as an important determinant in the TME microenvironment which should be taken in consideration for the design of new therapies.

Further studies are necessary to understand the impact of hypoxia in T cell differentiation and effector function, notably on Treg cells.

3) Chimeric Antigen Receptor (CAR) T cell Immunotherapies

The tight relation between cancer cells and the immune system described in section IV 1 opened the doors to the development of immunotherapies. The idea that immune cells could be directly targeted and manipulated ex vivo to overcome immune tolerance resulted in the development of several therapies. Since T cells are the main players in immunosurveillance, the first attempts at immunotherapy were centered on T cell manipulation [START_REF] Kantoff | Sipuleucel-T immunotherapy for castrationresistant prostate cancer[END_REF][START_REF] Rosenberg | Durable complete responses in heavily pretreated patients with metastatic melanoma using T-cell transfer immunotherapy[END_REF]. Ever since, adoptive T-cell therapies (ACT) have been in continuous development.

ACT consists on the re-infusion of autologous tumor-antigen-specific T cells that were previously collected from the patient, expanded ex vivo and thus re-injected in order to generate an anti-tumor response. The current T-cell therapies are centered in two general approaches: the use of T cells isolated from tumor zones called TILs and redirected T cells [START_REF] Cheadle | CAR T cells: driving the road from the laboratory to the clinic[END_REF]. This latter category results from advances in genetic engineering leading to recombinant T cell receptors (TCR) or to chimeric antigen receptors (CAR). Both approaches result in the generation of T cells with increased specificity to specific tumor antigens [START_REF] Miliotou | CAR T-cell Therapy: A New Era in Cancer Immunotherapy[END_REF]. In this section, I will particularly focus on CAR T cells.

TILs are isolated from tumor biopsies and can be activated ex vivo (free from a potentially suppressive tumor environment) and demonstrate in vitro tumor killing [START_REF] Rosenberg | A new approach to the adoptive immunotherapy of cancer with tumor-infiltrating lymphocytes[END_REF]. These cells are then cultured in presence of IL-2 in order to get the largest number possible. After testing their reactivity, TILs are re-infused into the patient. Despite the interesting therapeutic results from TILs treatment, this approach presents some disadvantages. This method is laborious, patient-specific, time-consuming and highly dependent on the antigen levels expressed on the tumor. Furthermore, not all the TILs isolated are tumor-specific which obliges the use of enrichment strategies that increases time spent in culture which may alter their phenotype or induce anergy [START_REF] Geukes Foppen | Tumor-infiltrating lymphocytes for the treatment of metastatic cancer[END_REF]. However, the studies and the clinical trials that have been performed with TILs not only highlighted the therapeutic potential of T cell-based immunotherapies but also have been extremely important and crucial to understand, evaluate and improve the conditioning regimens used prior to TILs injection (chemotherapy and radiotherapy) as well as the optimal IL-2 doses to administrate to the patients [START_REF] Andersen | Long-Lasting Complete Responses in Patients with Metastatic Melanoma after Adoptive Cell Therapy with Tumor-Infiltrating Lymphocytes and an Attenuated IL2 Regimen[END_REF][START_REF] Dudley | Adoptive cell transfer therapy following non-myeloablative but lymphodepleting chemotherapy for the treatment of patients with refractory metastatic melanoma[END_REF][START_REF] Dudley | Adoptive cell therapy for patients with metastatic melanoma: evaluation of intensive myeloablative chemoradiation preparative regimens[END_REF][START_REF] Goff | Randomized, Prospective Evaluation Comparing Intensity of Lymphodepletion Before Adoptive Transfer of Tumor-Infiltrating Lymphocytes for Patients With Metastatic Melanoma[END_REF][START_REF] Rosenberg | Durable complete responses in heavily pretreated patients with metastatic melanoma using T-cell transfer immunotherapy[END_REF][START_REF] Tseng | Thrombotic microangiopathy in metastatic melanoma patients treated with adoptive cell therapy and total body irradiation[END_REF].

The approach using a modified TCR results from the ectopic expression of α and β chains to T cells to redirect their antigen specificity. These α and β chains are associated with constant regions by disulphide bonds and also with the γ, δ, ε and ζ chains of the CD3 complex [START_REF] Uttenthal | Challenges in T cell receptor gene therapy[END_REF]. The advantage of this gene-modified T cells is that the antigen recognition mechanisms are equal to non-modified TCRs. However, with this approach the responses against tumor antigens depend on MHC presentation, which is therefore not compatible with the treatment of patients expressing a different MHC haplotype [START_REF] Cheadle | CAR T cells: driving the road from the laboratory to the clinic[END_REF]. Furthermore, it also represents an important downside for the treatment of tumors with low or no MHC expression [START_REF] Garrido | MHC antigens and tumor escape from immune surveillance[END_REF][START_REF] Seliger | Antigen-processing machinery breakdown and tumor growth[END_REF]. These problems promoted scientific investigations on approaches to provide antigen specificity to T cells and to overcome disadvantages related to modified TCRs.

CARs, or T-bodies, are generated by joining as a single chain variable fragment (scFv) molecule, the light and heavy chains of variable regions of a monoclonal antibody. The construct contains a hinge domain, transmembrane domain, and cytoplasmic signaling domains derived from the CD3ζ chain or Fc receptor γ chains [START_REF] Sadelain | T-cell engineering for cancer immunotherapy[END_REF]. A specificity of the CAR approach is that MHC antigen presentation is not required, since the antigens can bind directly to the CARs and trigger T cell responses. This approach therefore overcomes the problems discussed earlier associated with the lack of MHC recognition in some tumor environments. However, contrary to TCRs, CARs cannot recognize antigens that are not localized on tumor cells surface which, therefore, need to be processed, presented by APCs and recognized through the MHC molecules. [START_REF] Uttenthal | Challenges in T cell receptor gene therapy[END_REF].

The development of the CAR strategy led to the generation of several generations of CAR constructs. Until now, 4 different CAR constructions were developed and they can be distinguished based on their intracellular tail composition which results in distinct features:

first generation, second generation, third generation and fourth generation; also called TRUCK (T cell redirected universal cytokine killing) [START_REF] Cheadle | CAR T cells: driving the road from the laboratory to the clinic[END_REF][START_REF] Wilkins | CAR T-Cell Therapy: Progress and Prospects[END_REF].

The first generation, initially designed by Zelig Eshhar, includes only the CD3ζ as intracellular domain [START_REF] Eshhar | Specific activation and targeting of cytotoxic lymphocytes through chimeric single chains consisting of antibody-binding domains and the gamma or zeta subunits of the immunoglobulin and T-cell receptors[END_REF][START_REF] Gross | Expression of immunoglobulin-T-cell receptor chimeric molecules as functional receptors with antibody-type specificity[END_REF]. The second generation also expresses one costimulatory domain (provided from endodomains of co-stimulatory molecules) and therefore the intracellular tail contains two signaling domains. The idea of adding a co-stimulatory molecule in this second generation CAR construct was to have a co-stimulatory signal which could promote IL-2 synthesis in order to complete T cell activation and to improve the CAR T cell proliferation, cytotoxicity and to prolong the lifespan of CAR T cells by avoiding apoptosis [START_REF] Zhang | Engineering CAR-T cells[END_REF]. The intracellular domain of the third generation is composed of the CD3ζ and two co-stimulatory domains. These domains could be, for instance, CD28, CD137 (also named 4-1BB) or CD134 (also known as OX40) [START_REF] Finney | Activation of resting human primary T cells with chimeric receptors: costimulation from CD28, inducible costimulator, CD134, and CD137 in series with signals from the TCR zeta chain[END_REF]. The presence of two costimulatory domains was combined with the intention of increasing cytokine production, killing ability and to respond better to recurrent exposition to tumor antigen [START_REF] Miliotou | CAR T-cell Therapy: A New Era in Cancer Immunotherapy[END_REF][START_REF] Zhang | Engineering CAR-T cells[END_REF]. The fourth generation is distinct as the vector encoding the CAR construct also includes a cytokine cassette that is expressed upon engagement of the CAR. The expression of these cytokines leads to the activation of a CARresponsive promoter that could be a nuclear factor of activated T cells that potentiate antitumor immune responses [START_REF] Chmielewski | IL-12 release by engineered T cells expressing chimeric antigen receptors can effectively Muster an antigenindependent macrophage response on tumor cells that have shut down tumor antigen expression[END_REF][START_REF] Pegram | Tumor-targeted T cells modified to secrete IL-12 eradicate systemic tumors without need for prior conditioning[END_REF]. The structure of the different CAR constructs is represented in Figure 26. CAR T cell therapies represent a very promising approach for the treatment of hematologic malignancies. These malignancies express high levels of surface antigens and T cells have a tendency to migrate to hematologic organs like blood, bone marrow and lymph nodes, which facilitates contacts between CAR T cell and malignant cells [START_REF] Maus | Antibody-modified T cells: CARs take the front seat for hematologic malignancies[END_REF].

The most successful CAR therapies so far are directed against CD19. The expression of lineage specific antigens like CD19 (which is expressed at all B cell stages and also in B-cell malignancies) ensure that CAR T cells can target cancer cells in the absence of antigen heterogeneity [START_REF] Maus | Making Better Chimeric Antigen Receptors for Adoptive Tcell Therapy[END_REF]. Moreover, CD19 is not expressed in hematopoietic stem cells which reduces the risk of autoimmunity and bone marrow toxicity [START_REF] Brentjens | Safety and persistence of adoptively transferred autologous CD19-targeted T cells in patients with relapsed or chemotherapy refractory B-cell leukemias[END_REF]. However, it is important to point out that as normal B cells also express CD19, this approach depletes normal B cells [START_REF] Grupp | Chimeric antigen receptor-modified T cells for acute lymphoid leukemia[END_REF][START_REF] Kochenderfer | Eradication of B-lineage cells and regression of lymphoma in a patient treated with autologous T cells genetically engineered to recognize CD19[END_REF][START_REF] Wilkins | CAR T-Cell Therapy: Progress and Prospects[END_REF]. Therefore, to overcome this problem, patients are provided with gamma globulins which compensates for the lack of B cells [START_REF] Savoldo | Chimeric antigen receptors (CARs) from bench-to-bedside[END_REF]. However, the CAR T cell approach in hematologic malignancies is not always efficient and successful. For example, studies demonstrate that engineered T cells are more efficient in acute lymphocytic leukemia (ALL) than in chronic lymphocytic leukemia (CLL) or indolent lymphomas [START_REF] Maude | Chimeric antigen receptor T cells for sustained remissions in leukemia[END_REF][START_REF] Porter | Chimeric antigen receptor T cells persist and induce sustained remissions in relapsed refractory chronic lymphocytic leukemia[END_REF]. Several factors could modulate the efficiency of the response: host T cell defects, inhibitory impact of the tumor microenvironment, pre-conditioning treatments, age of the patients, number and/or effector capacity of transduced T cells and loss or downregulation of the target antigen in tumor cells [START_REF] Majzner | Tumor Antigen Escape from CAR T-cell Therapy[END_REF][START_REF] Maus | Antibody-modified T cells: CARs take the front seat for hematologic malignancies[END_REF]. For instance, it was recently demonstrated that CAR T cell can provoke reversible antigen loss through trogocytosis, resulting in decreased density of antigen on tumor cells and impacting T cell anti-tumor function [START_REF] Hamieh | CAR T cell trogocytosis and cooperative killing regulate tumour antigen escape[END_REF]. Moreover, intravital imaging in B-cell lymphoma bearing mice revealed that CAR T cell activity was higher in bone marrow than in lymph nodes, which suggests anatomical heterogeneity in CAR T cell function [START_REF] Cazaux | Single-cell imaging of CAR T cell activity in vivo reveals extensive functional and anatomical heterogeneity[END_REF]. Also, in this study they demonstrated that exists a functional heterogeneity as not all CAR T cell contacts resulted in tumor cell killing [START_REF] Cazaux | Single-cell imaging of CAR T cell activity in vivo reveals extensive functional and anatomical heterogeneity[END_REF]. All these issues can vary from one type of tumor to another and as a result, impact the overall efficiency of the therapy. Moreover, despite the impressive success of CD19 CAR T therapies, it is necessary to reduce the variables and understand the differences between clinical approaches. Moreover, the research in B malignancies is very complex and there is not a single standardized optimized CD19-specific CAR construct. Nevertheless, most clinical trials are based on second generation of CARs like CD19-CD28-ζ or CD19-4-1BB-ζ [START_REF] Cheadle | CAR T cells: driving the road from the laboratory to the clinic[END_REF].

A study performed by Savoldo et al. demonstrated that the presence of co-stimulatory molecule CD28 improves in vivo expansion and persistence of CAR-modified T cells when compared with T cells with only one signaling domain (first generation CAR) [START_REF] Savoldo | CD28 costimulation improves expansion and persistence of chimeric antigen receptor-modified T cells in lymphoma patients[END_REF]. Additionally, the levels of CAR CD19-CD28-ζ detected in tumor biopsies suggested a better efficient tumor infiltration [START_REF] Savoldo | CD28 costimulation improves expansion and persistence of chimeric antigen receptor-modified T cells in lymphoma patients[END_REF]. In another study, Brentjens et al. tried to evaluate the putative role of the cytoplasmic signaling co-stimulatory domain in the increased efficiency of second generation CARs. They observed that the presence of CD28 in the CAR structure was associated with an enhanced T-cell proliferation and cytokine secretion. However, this was not the case with other signaling domains, such as 4-1BB, DAP-10 or OX40 [START_REF] Brentjens | Genetically targeted T cells eradicate systemic acute lymphoblastic leukemia xenografts[END_REF]. On the other hand, other studies demonstrated that 4-1BB and OX40 co-signaling domains contribute to an enhanced co-stimulation in secondgeneration CARs by increasing cytokine secretion upon antigen stimulation and specific cytotoxicity [START_REF] Finney | Activation of resting human primary T cells with chimeric receptors: costimulation from CD28, inducible costimulator, CD134, and CD137 in series with signals from the TCR zeta chain[END_REF][START_REF] Imai | Chimeric receptors with 4-1BB signaling capacity provoke potent cytotoxicity against acute lymphoblastic leukemia[END_REF]. These discrepancies could be notably related to the type of antigen targeted and/or the CAR construct.

Furthermore, it is described that the co-stimulatory domain CD28 is important to promote IL-2 secretion [START_REF] Hombach | A recombinant anti-carcinoembryonic antigen immunoreceptor with combined CD3zeta-CD28 signalling targets T cells from colorectal cancer patients against their tumour cells[END_REF]Hombach et al., 2001a;[START_REF] Hombach | Tumor-specific T cell activation by recombinant immunoreceptors: CD3 zeta signaling and CD28 costimulation are simultaneously required for efficient IL-2 secretion and can be integrated into one combined CD28/CD3 zeta signaling receptor molecule[END_REF]) by CAR T cells, a feature not observed in second generation CAR constructs containing 4-1BB and OX40 co-stimulatory domains [START_REF] Koehler | Engineered T cells for the adoptive therapy of B-cell chronic lymphocytic leukaemia[END_REF]. 4-1BB and OX40 are not associated with an increase of IL-2 production, but both domains can lead to enhanced IFNγ production.

Nevertheless, OX40 and 4-1BB are better for preventing induced cell death mechanisms and promoting T cell survival [START_REF] Koehler | Engineered T cells for the adoptive therapy of B-cell chronic lymphocytic leukaemia[END_REF]. With these results, we can conclude that CD28, constructions and showed that the third generation CAR demonstrated higher NFκB activity, IL-2 secretion, continuous proliferation and enhanced anti-tumor activity [START_REF] Pule | A chimeric T cell antigen receptor that augments cytokine release and supports clonal expansion of primary human T cells[END_REF].

Furthermore, other studies showed that the combination of 4-1BB and CD28 improved persistence, survival, anti-tumor efficiency and induced multifunctional cytokine secretion as compared to second generation CARs [START_REF] Carpenito | Control of large, established tumor xenografts with genetically retargeted human T cells containing CD28 and CD137 domains[END_REF][START_REF] Tammana | 4-1BB and CD28 signaling plays a synergistic role in redirecting umbilical cord blood T cells against B-cell malignancies[END_REF]Wang et al., 2007;[START_REF] Zhong | Chimeric antigen receptors combining 4-1BB and CD28 signaling domains augment PI3kinase/AKT/Bcl-XL activation and CD8+ T cell-mediated tumor eradication[END_REF].

Despite the huge success of CAR T cell approaches in hematological malignancies, up to 90% clinical response rates in the case of ALL [START_REF] Maude | Chimeric antigen receptor T cells for sustained remissions in leukemia[END_REF], the overall clinical efficiency to treat solid cancer has been much less rewarding (Yong et al., 2017). Several cases describing a lack of therapeutic response or toxic side effects have been reported when using CAR T cells for solid tumors treatment [START_REF] Kershaw | A phase I study on adoptive immunotherapy using gene-modified T cells for ovarian cancer[END_REF][START_REF] Lamers | Treatment of metastatic renal cell carcinoma with autologous T-lymphocytes genetically retargeted against carbonic anhydrase IX: first clinical experience[END_REF][START_REF] Maus | T cells expressing chimeric antigen receptors can cause anaphylaxis in humans[END_REF][START_REF] Morgan | Case report of a serious adverse event following the administration of T cells transduced with a chimeric antigen receptor recognizing ERBB2[END_REF]. One potential issue in this case is the nature of the surrounding TME microenvironment which is more complex in solid tumors. This TME not only restricts the CAR T cells infiltration into the solid tumor mass due to the presence of stromal and epithelial cells, but also alters nutrient availability, which transforms the TME into a metabolic barrier (discussed in the section IV 2 A). Finally, the low levels of O2 availability and immune checkpoint ligands such as PD-L1 can also dampen effector T cell responses (discussed in the section IV 2 B).

The importance of the TME and the metabolic reprograming on CAR T cell treatment and other T cell based immunotherapies has been recently addressed and highlighted (Le [START_REF] Bourgeois | Targeting T Cell Metabolism for Improvement of Cancer Immunotherapy[END_REF]. Kawalekar and colleagues demonstrated that depending on the costimulatory domain expressed in the CAR construct, the redirected T cells recruit distinct metabolic programs and are engaged into different differentiating programs [START_REF] Kawalekar | Distinct Signaling of Coreceptors Regulates Specific Metabolism Pathways and Impacts Memory Development in CAR T Cells[END_REF]. In this study, they demonstrated that 4-1BBζ CAR T cells have better persistence, high SRC, higher mitochondrial biogenesis, higher oxidative metabolism and increased frequency of TCM as compared to 28ζ CAR T cells. These latter ones, on the other hand, showed reduced persistence, higher glycolytic metabolism and an increased frequency of TEM cells [START_REF] Kawalekar | Distinct Signaling of Coreceptors Regulates Specific Metabolism Pathways and Impacts Memory Development in CAR T Cells[END_REF]. These findings demonstrate that the CAR construct itself could impact the metabolism of the redirected-T cells and suggesting that this parameter should be considered for the design of CAR therapies. Recently, another group developed a CAR T cell construct based on another feature of the TME: hypoxia. This CAR express an oxygen sensitive domain of HIF1-α which is fused to a CAR scaffold, allowing the CAR-expressing T cells to better respond to hypoxic environments. Furthermore, another team demonstrated that metabolic modulation of CAR T cell could already be performed before CAR T cell injection with a positive impact for anti-tumor functions. Through the combination of IL-7 and IL-15 with CD3 and CD28 stimulation, TSCM and TCM phenotypes were promoted which were described to have better persistence and anti-tumor immunity [START_REF] Alizadeh | IL15 Enhances CAR-T Cell Antitumor Activity by Reducing mTORC1 Activity and Preserving Their Stem Cell Memory Phenotype[END_REF][START_REF] Gargett | Different cytokine and stimulation conditions influence the expansion and immune phenotype of third-generation chimeric antigen receptor T cells specific for tumor antigen GD2[END_REF][START_REF] Gomez-Eerland | Manufacture of genemodified human T-cells with a memory stem/central memory phenotype[END_REF]. A study performed by Sukumar and colleagues highlighted the importance of metabolic reprograming and the TME in T-cell based immunotherapies. They show that T cell activation in the presence of a glycolysis inhibitor resulted in an increased generation of memory like cells with increased anti-tumor function comparing to the non-treated T cells with a higher glycolytic flux [START_REF] Sukumar | Inhibiting glycolytic metabolism enhances CD8+ T cell memory and antitumor function[END_REF]. These results clearly demonstrate that T cell metabolic reprogramming can be used to select T cells for ACT therapies. Moreover, Chang et al demonstrated that within the tumor, there is a competition for glucose between tumor cells and T cells which impacts negatively anti-tumor function. They showed that this could be overcome by PD-L1 blockade, which dampened the glycolytic rate of tumor cells and improved consequently anti-tumor functions (Chang et al., 2015). In an evident manipulation of the TME, this study highpoint the impact of the metabolic competition between T cells and tumor cells and why it is important to take it into consideration.

As described in this literature review, modulation of T cell metabolism can impact their activation, differentiation and effector function. Moreover, nutrients availability required to fulfill cell function is decreased in the TME, which as a consequence, impacts on anti-tumor responses. Therefore, it becomes crucial to further understand how CAR T cell metabolism is regulated and to develop new strategies to overcome the metabolic barriers imposed by the TME and to optimize CAR T cell efficiency.

Introduction

Irrespective of the T cell subset utilized in an adoptive therapy, the metabolic needs of T cells have begun to be appreciated as a key factor in their anti-tumor activity. The activation, proliferation and effector functions of T cells are energy-"hungry" processes and recent studies have shown the importance of metabolic pathways in optimizing immune functions.

When activated, lymphocytes upregulate their energetic state, increasing both oxidative phosphorylation and aerobic glycolysis but in general the latter increases to a greater level than the former [START_REF] Buck | Metabolic Instruction of Immunity[END_REF][START_REF] Clerc | Entry of glucose-and glutamine-derived carbons into the citric acid cycle supports early steps of HIV-1 infection in CD4 T cells[END_REF][START_REF] Geltink | Unraveling the Complex Interplay Between T Cell Metabolism and Function[END_REF] . This metabolic programming results in an increase in the input and use of nutrients. Indeed, the optimal activation of T cells and their effector activity requires, in particular, an increase in the surface expression of glucose (GLUT1) and arginine (CAT-1)transporters, resulting in an augmented use of these nutrients by lymphocytes [START_REF] Jacobs | Glucose uptake is limiting in T cell activation and requires CD28mediated Akt-dependent and independent pathways[END_REF][START_REF] Loisel-Meyer | Glut1-mediated glucose transport regulates HIV infection[END_REF]Macintyre et al., 2014;Wang et al., 2011;[START_REF] Werner | Induced arginine transport via cationic amino acid transporter-1 is necessary for human T-cell proliferation[END_REF]. In addition, recent studies have shown that distinct subpopulations of T lymphocytes have disparate metabolic profiles;

effector T cells are highly glycolytic but also lipogenic, while regulatory T cells present a heterogeneous metabolism with an increase in the level of lipid oxidation (Michalek et al., 2011). From this point of view, it is interesting to note that Treg, but not effector T cells, can be generated in the absence of glucose, glutamine or leucine transporters (Macintyre et al., 2014). Similarly, the restriction of glucose or glutamine in the cellular environment limits the development of effector cells but not Tregs [START_REF] Cham | Glucose deprivation inhibits multiple key gene expression events and effector functions in CD8+ T cells[END_REF][START_REF] Chang | Posttranscriptional control of T cell effector function by aerobic glycolysis[END_REF]Klysz et al., 2015;Macintyre et al., 2014;[START_REF] Metzler | Restricting Glutamine or Glutamine-Dependent Purine and Pyrimidine Syntheses Promotes Human T Cells with High FOXP3 Expression and Regulatory Properties[END_REF]Nakaya et al., 2014). This is of particular interest as the metabolism generated in the tumor microenvironment, wherein nutrient availability may be limiting, would then contribute to prevent effective anti-tumor responses against a solid tumor. Indeed, the dysregulated growth of cancer cells can directly influence the extracellular environment and multiple studies now strongly suggest that the metabolic phenotype of the tumor governs the ensuing immune response (reviewed in [START_REF] Ackerman | Hypoxia, lipids, and cancer: surviving the harsh tumor microenvironment[END_REF][START_REF] Mayers | Nature and Nurture: What Determines Tumor Metabolic Phenotypes?[END_REF]). Thus, the metabolic fitness of an effector T cell in a tumor environment is likely to differ from its fitness in healthy lymphoid tissue.

It is interesting to note that within an activated T cell population, cells that are capable of transporting higher levels of glucose or exhibiting higher mitochondrial activity have an enhanced effector phenotype (as monitored by higher IFNγ secretion levels), while populations with low glucose incorporation or low mitochondrial activity have a memory phenotype. Furthermore, arginine metabolism also activates mitochondrial respiration [START_REF] Geiger | L-Arginine Modulates T Cell Metabolism and Enhances Survival and Anti-tumor Activity[END_REF]. Thus, metabolic parameters can be used to distinguish T cells with different characteristics [START_REF] Sukumar | Inhibiting glycolytic metabolism enhances CD8+ T cell memory and antitumor function[END_REF][START_REF] Sukumar | Nutrient Competition: A New Axis of Tumor Immunosuppression[END_REF].

Based on the importance of glucose and arginine metabolism in T cell function, we initiated studies to assess whether the levels of these nutrient transporters (focusing on the GLUT1 glucose transporter and CAT-1 arginine transporter) on activated T lymphocytes can be used to select for T cells with distinct anti-tumor effector functions. Using GLUT1 and CAT-1 surface expression, we were able to select T cells expressing distinct GLUT1 and CAT-1 surface levels.

These sorted cells were then studied and their phenotype as well as their effector function was evaluated. The data resulting from these studies are discussed in this chapter.

p

Results and Discussion

Selection of TCR-stimulated human T cells on the basis of surface CAT-1 expression

Based on our previous work, demonstrating that the cytokine secretion potential of human TCR-stimulated T cells can be distinguished on the basis of GLUT1 levels, we assessed whether human T cells selected on the basis of the surface expression of an independent nutrient transporter would exhibit distinct characteristics. We focused on the arginine transporter, CAT-1/SLC7A1. Briefly, arginine uptake in T cells is dependent on CAT-1 and its expression is important for T cell proliferation [START_REF] Werner | Induced arginine transport via cationic amino acid transporter-1 is necessary for human T-cell proliferation[END_REF]. Indeed, upon TCR stimulation, CAT-1 surface expression is highly upregulated, to a higher level even than GLUT1 expression (CAT-1 deltaMFI 20467 compared to GLUT1 deltaMFI 4703 at day 2 and CAT-1 deltaMFI 24974 compared to GLUT1 deltaMFI 7748 at day 4 (Figure 1).

To address this question, CD3 + T cells were isolated from the blood of healthy donors and TCR-stimulated using anti-CD3/anti-CD28 mAbs. Following 48h of TCR activation, T cells were stained with a CAT-1 ligand (CAT-1-RBD) in order to detect CAT-1 surface expression. CD3 + T cells expressing the lowest and highest levels of CAT-1 (~15%) were FACS-sorted and distinguished as CAT-1 Low and CAT-1 High , respectively. Since CAT-1 was not detected on quiescent T cells and was induced following TCR stimulation, we hypothesized that the CAT-1 High subset would have a higher metabolic activity. In agreement with this hypothesis, the forward/side scatters of CAT-1 High cells were higher than those of CAT-1 Low cells (Figure 2).

Increased percentages of CD8 T cells in the CAT-1 High as compared to the CAT-1 Low subset following TCR stimulation

We next assessed whether there was a difference in the CD4/CD8 ratios within the CAT-1 High vs. CAT-1 Low T cell subset. Notably, the relative percentages of CD4 + T cells were significantly higher in the CAT-1 Low than the CAT-1 High T cell subset (81% versus 50%) at day 2 post stimulation and this correlated with a lower percentage of CD8 + T cells (17% versus 47% in a representative experiment, Figure 3A). Thus, while the total T cell population (CAT-1 Total , all cells were sorted) exhibited a CD4:CD8 ratio of approximately 3:1 following 2 days of TCR stimulation, the ratio in the CAT-1 Low subset was >4:1 and the ratio in the CAT-1 High subset was approximately 1:1 (Figure 3A). Thus, we detected a striking bias towards CD8 + T cells in lymphocytes with a high induction of CAT-1. Interestingly, the ex vivo culture of sorted CAT-1 Low and CAT-1 High T cells in the presence of IL-2 resulted in an increased proportion of CD8 T cells in both subsets (day 8) but the relative percentages of CD8 T cells remained higher in the latter, resulting in a CD4:CD8 ratio of approximately 0.7 in the former and 0.3 in the latter (Figure 3A). The bias towards CD8 + T cells was likely due to their faster proliferation as compared to CD4 + T cells (Figure 3B). Furthermore, as monitored by VPD dilution in Figure 2B, the percentages of CD4 + T cells that underwent extensive proliferation in the CAT-1 Low subset was substantially lower than in the CAT-1 High subset (80% as compared to 54%). Within the CD8 subset, 64% of CAT-1 Low cells had undergone >4 divisions whereas 72% of CAT-1 High cells had already reached this level (Figure 3B). Notably, this alteration in cell division was not due to a defect in activation as both CAT-1 Low and CAT-1 High cells exhibited an equivalent upregulation of activation markers such as CD69 and CD25 (data not shown).

Altogether, these data show that CAT-1 High cells exhibit a higher level of proliferation than CAT-1 Low cells in response to TCR stimulation and moreover, that the high induction of CAT-1 is biased to the highly proliferating CD8 T cell subset.

CAT-1 High CD4 + T cells exhibit higher effector function than CAT-1 Low CD4 + T cells

To assess whether the selection of human T cells on the basis of CAT-1 expression Is associated with the enrichment of naïve versus memory T cells, we monitored expression of the CD45RA and CD45RO markers which are generally expressed on naïve and memory cells, respectively. As expected, the percentages of CD45RA + T cells decreased between days 2 and 8 of stimulation, consistent with the loss of naïve cells following TCR stimulation, with a more pronounced loss in the CD4 + subset. Notably though, there were no striking alterations in the percentages of CD45RA + and CD45RO + cells within the CAT-1 Low as compared to CAT-1 High sorted subsets, at either time point (Figure 4). These data suggest that CAT-1 surface expression does not distinguish CD4 or CD8 T cell subsets on the basis of their naïve/ memory phenotype. Interestingly, these data differ from our previous results based on Glut-1 We next assessed whether there were differences in the effector potential of CAT-1 Low and CAT-1 High T cells by evaluating their cytokine secretion capacity. While the percentages of CD4 and CD8 T cells secreting IL-2 was high in both the CAT-1 Low and CAT-1 High subsets (mean of >50%), it is notable that IL-17 secretion was substantially higher in the CD4 + CAT-1 High subset (6% as compare to <2% in the CAT-1 Low subset). Furthermore, IFN-γ secretion was slightly increased in CAT-1 High as compared to CAT-1 Low CD4 + T cells and total CD4 T cells (29 vs 23%).

Interestingly, these percentages were not altered in the CD8 T cell compartment, potentially due to the high level proliferation of CD8 T cells in both the CAT-1 Low and CAT-1 High subsets (Figure 5). Purified human CD3 + T cells were TCR-activated and sorted on the basis of CAT-1 expression at day 2 as indicated. Production of IL-2, IL-17, and IFN-γ was assessed in the CAT-1 Low , CAT-1 High and total CD4 and CD8 T cell subsets by intracellular staining at day 5/6, following restimulation with PMA/ionomycin in the presence of Brefeldin A for 4h. Means ± SEM of 2 independent experiments are presented.

Considering our previous work on the characterization of T cells selected based on Glut1

surface expression and the proliferation level of CD4 + CAT-1 High cells, it was quite surprising not to detect a higher percentage of IFNγ + cells or memory phenotype associated to this subset. As a result, the cytokine/phenotype pattern associated to each subset appears as distinct and the major characteristic at this point seems that IL-17-producing cells are enriched in CD4 + CAT-1 High cells as compared to CD4 + CAT-1 low . It is important to keep in mind that these results are representative of two independent experiments and further experiments are therefore required. However, and even if these results are preliminary, selection based on GLUT1 and CAT-1 surface expression does not seem to select/enrich similar T cell subsets. Therefore, these data open new perspectives regarding the use of distinct nutrient transporters to select T cells with different phenotype and effector functions.

Material and Methods

Human T cell isolation and culture. CD3 + T cells were isolated from healthy adult donors. All experiments using primary human cells were conducted in accordance with the Declaration min at RT. For intracellular cytokine staining, lymphocytes were re-activated with PMA (Sigma-Aldrich; 100 ng/ml) and ionomycin (Sigma-Aldrich; 1 μg/ml) in the presence of brefeldin A (Sigma-Aldrich; 10 ug/ml) for 3.5-4h at 37 °C. Intracellular staining for IL-2, IFN-γ and IL-17 was performed following fixation/ permeabilization using the eBioscience kit (Thermo-scientific) or using the BD kit (BD Biosciences). Cells were analyzed on LSRII-Fortessa (BD Biosciences) and data was analyzed using FlowJo (Tree Star) software.

Nutrient transporters surface expression detection. GLUT1 and CAT-1 expression at cell surface was monitored using RBD (receptor binding domain) ligands fused to rFc tail or eGFP [START_REF] Kim | HTLV-1 and -2 envelope SU subdomains and critical determinants in receptor binding[END_REF][START_REF] Kinet | Isolated receptor binding domains of HTLV-1 and HTLV-2 envelopes bind Glut-1 on activated CD4+ and CD8+ T cells[END_REF]Manel et al., 2003a). RBDs were incubated during 30 min at 37 °C. If required, after RBD incubation, an anti-rFc secondary antibody coupled to AF647 (life technology) was incubated during 30 min at 4 °C. The surface expression level was monitored by flow cytometry and was calculated as a function of the difference in average fluorescence intensity (ΔMFI) between the sample and its control condition (non-stained cells or cells incubated only with anti-rFc secondary antibody coupled to AF647).

Cell sorting based on surface CAT-1 expression. CD3 + T cells maintained in Nutr+ medium and VPD450-labeled were stained at day 2 post TCR stimulation and the 15-16% of lymphocytes expressing the highest (CAT-1 High ) and lowest levels of CAT-1 (CAT-1 Low) were sorted on a FACSAria (BD Biosciences). Lymphocytes were cultured in RPMI medium 1640 supplemented with 10% FCS and 1% penicillin/streptomycin (Gibco-Life technologies) in the presence of rIL-2.

Introduction

In the previous chapter we demonstrated that GLUT1 and CAT-1 surface expression could be used to select T cells with distinct phenotypes and effector functions. Altogether, our data suggest that nutrient transporters can be used to select T cells with increased anti-tumor function and a potentially better metabolic fitness. However, and despite of the advantages of injecting specific T cell subsets in cancer patients, it remains important to evaluate the impact of nutrient availability on T cell differentiation and effector function. T cell-based therapies have had much more success in the treatment of hematological malignancies than in the treatment of solid malignancies. One challenge in the latter context is that the ability of immune cells to maintain an effective response is often negatively modulated by the metabolic environment of the tumor. This environment is conditioned by nutrient composition, "waste" products, oxygen concentration, pH and physical forces, amongst others. The dysregulated growth of cancer cells can directly influence the extracellular environment and multiple studies now strongly suggest that the metabolic phenotype of the tumor governs the ensuing immune response (reviewed in [START_REF] Ackerman | Hypoxia, lipids, and cancer: surviving the harsh tumor microenvironment[END_REF][START_REF] Mayers | Nature and Nurture: What Determines Tumor Metabolic Phenotypes?[END_REF]. Furthermore, recent data suggest that several metabolites, generated by distinct cells within the tumoral microenvironment (TME), may represent a form of intercellular communication modulating both tumor cell growth and response to therapy [START_REF] Xu | A Metabolism Toolbox for CAR T Therapy[END_REF]. One feature associated with the tumoral metabolic environment and directly linked to the proliferation of the tumor cells, is the depletion of nutrients in the TME. Indeed, in the context of several solid tumors, including hepatocellular carcinomas, stomach/colon tumors, and pancreatic tumors, quantitative metabolite profiling has revealed decreased intra-tumoral concentrations of glucose as well as glutamine [START_REF] Bode | Glutamine transport and human hepatocellular transformation[END_REF][START_REF] Hirayama | Quantitative metabolome profiling of colon and stomach cancer microenvironment by capillary electrophoresis time-of-flight mass spectrometry[END_REF][START_REF] Kamphorst | Human pancreatic cancer tumors are nutrient poor and tumor cells actively scavenge extracellular protein[END_REF]. In this context, our group as well as others have shown that the competition of T cells and tumor cells for limiting amounts of nutrients has a negative impact on the former, inhibiting T cell cytolytic and effector functions [START_REF] Cham | Glucose deprivation inhibits multiple key gene expression events and effector functions in CD8+ T cells[END_REF][START_REF] Chang | Posttranscriptional control of T cell effector function by aerobic glycolysis[END_REF]Klysz et al., 2015;Macintyre et al., 2014;[START_REF] Metzler | Restricting Glutamine or Glutamine-Dependent Purine and Pyrimidine Syntheses Promotes Human T Cells with High FOXP3 Expression and Regulatory Properties[END_REF]Nakaya et al., 2014). Glucose and glutamine represent essential carbon/nitrogen sources, sustaining the proliferation and activity of T effector cells [START_REF] Carr | Glutamine uptake and metabolism are coordinately regulated by ERK/MAPK during T lymphocyte activation[END_REF][START_REF] Gerriets | Metabolic pathways in T cell fate and function[END_REF]. This is illustrated by the upregulation of glucose and glutamine transporters following TCR stimulation as well as the associated increase in glucose and glutamine metabolism [START_REF] Carr | Glutamine uptake and metabolism are coordinately regulated by ERK/MAPK during T lymphocyte activation[END_REF][START_REF] Gerriets | Metabolic pathways in T cell fate and function[END_REF][START_REF] Kinet | Isolated receptor binding domains of HTLV-1 and HTLV-2 envelopes bind Glut-1 on activated CD4+ and CD8+ T cells[END_REF][START_REF] Maciver | Metabolic regulation of T lymphocytes[END_REF]Manel et al., 2003b;Nakaya et al., 2014;[START_REF] Ren | Amino-acid transporters in T-cell activation and differentiation[END_REF]. However, T cells also strongly rely on others amino acids. Indeed, the presence of arginine-degrading enzymes, arginases, in the TME can result in arginine depletion and T cell anergy [START_REF] Rodriguez | L-arginine availability regulates Tlymphocyte cell-cycle progression[END_REF]. Furthermore, arginine supplementation was described to contribute to the production of pro-inflammatory cytokines and to the survival of central memory T cells in an in vitro setting [START_REF] Geiger | L-Arginine Modulates T Cell Metabolism and Enhances Survival and Anti-tumor Activity[END_REF][START_REF] Rodriguez | L-arginine availability regulates Tlymphocyte cell-cycle progression[END_REF]. Thus, the metabolic fitness of an effector T cell in a nutrient-deprived tumor environment is likely to differ from its fitness in healthy lymphoid tissue. Finally, considering the divergent metabolic requirements of different T cell subsets (reviewed in [START_REF] Buck | Metabolic Instruction of Immunity[END_REF], the TME may differentially promote the survival and/or proliferation of one subtype as compared to another.

It is therefore of critical importance to determine how metabolic modulation of antitumor T cells impact on their persistence and function, especially in the context of "hostile"

tumor tissue with high nutrient consumption. As a result, part of my PhD research focused on advancing our understanding of how T cell responses are modulated by their metabolic environment and more specifically to elucidate the impact of glutamine and arginine deprivation, which represent some hallmarks of the TME on T cell function.

Addendum II Impact of arginine availability on human T cell function

Results and Discussion

Arginine deprivation impairs T cell activation and proliferation. Arginine concentrations can be significantly modulated within the tumor environment [START_REF] Kim | Impact of l-Arginine Metabolism on Immune Response and Anticancer Immunotherapy[END_REF][START_REF] Lyssiotis | Metabolic Interactions in the Tumor Microenvironment[END_REF][START_REF] Marigo | Tumor-induced tolerance and immune suppression by myeloid derived suppressor cells[END_REF][START_REF] Szefel | Metabolic pathways of L-arginine and therapeutic consequences in tumors[END_REF] with important consequences on T cell function. Moreover, the arginine transporter CAT-1 is significantly upregulated upon TCR stimulation (presented in Chapter I, Addendum I, Figure1), suggesting a dependence of activated T cells on arginine uptake to sustain their new metabolic requirements.

To evaluate the impact of arginine deprivation on human T cell activation, CD3 + T cells were isolated from the blood of healthy donors and TCR-stimulated using anti-CD3/anti-CD28 mAbs in the absence (-Arg) or presence (Nutr+) of arginine at 200 µg/ml which represents the « classical » concentration used in RPMI media). At day 4 following TCR-stimulation, T cells activated in arginine-deprived conditions exhibited high viability but were significantly smaller as compared to T cells activated in nutrient replete media, as assessed by microscopy and forward/side scatters parameters (data not shown and Figure 1A). Indeed, expression of the CD25 and CD71 activation markers, encoding the IL-2Rα chain and the transferrin receptor, respectively, were strongly reduced in conditions of arginine depletion (Figure 1B).

Interestingly, CD69, an early activation marker whose cell surface upregulation is independent of transcription (Manel et al., 2003b), was upregulated even in arginine-depleted conditions and its downregulation was delayed as compared to control Nutr+ conditions (>45fold higher MFI at day 4 for both CD4 and CD8 T cells, Figure 1B). Consistent with the suboptimal upregulation of T cell activation markers, there was a massive reduction of T cell proliferation in arginine-depleted conditions. T cells stimulated in -Arg conditions only initiated a first round of division at day 7 post stimulation whereas the vast majority of both CD4 and CD8 T cells activated in Nutr+ conditions had divided by day 3 (Figure 1C). Lower concentrations of arginine (decreasing from 200µg/ml to 50 µg/ml) did not appear to significantly impact CD4 T cell proliferation but CD8 T cell proliferation was delayed (14% of undivided cells at day 3 as compared to 8% of undivided cells in 50 µg/ml vs 200ug/ml arginine, respectively, Figure 1C). Notably though, the concentration of 50 µg/ml is higher than plasma arginine levels (14 µg/ml; 82µM) suggesting that arginine levels in the T cell microenvironment may limit optimal T cell responsiveness in vivo.

Arginine deprivation does not inhibit the acquisition of a memory phenotype or the cytokine secretion potential of TCR-stimulated T lymphocytes. To determine whether arginine deprivation alters the proportion of CD4/CD8 T cells or the acquisition of a memory phenotype, we monitored T cell phenotype at day 4 post-stimulation in the presence or absence of arginine. Interestingly, neither the CD4/CD8 ratio (Figure 2A) nor the CD45RA/RO ratio (Figure 2B) was altered by activation in the absence of arginine. The percentages of CD4 and CD8 T cells producing IL-2, IL-17 and IFNg were also not significantly modulated in the absence of arginine (Figure 2C). While these data differ from reported decreases in T cellmediated IFNg secretion in the absence of arginine [START_REF] Feldmeyer | Arginine deficiency leads to impaired cofilin dephosphorylation in activated human T lymphocytes[END_REF], it is notable that the previous study assessed the levels of secreted cytokines whereas our experiments evaluated the potential of individual cells to produce cytokines following PMA/ ionomycin restimulation. Indeed, Geiger and colleagues found that even though high extracellular arginine levels resulted in a lower secretion of IFNg from TCR-stimulated human CD8 T cells, PMA/ionomycin stimulation of the same cells resulted in the opposite effect, with an observed increase in IFNg stimulation [START_REF] Feldmeyer | Arginine deficiency leads to impaired cofilin dephosphorylation in activated human T lymphocytes[END_REF][START_REF] Geiger | L-Arginine Modulates T Cell Metabolism and Enhances Survival and Anti-tumor Activity[END_REF][START_REF] Munder | Suppression of T-cell functions by human granulocyte arginase[END_REF][START_REF] Rodriguez | L-arginine availability regulates Tlymphocyte cell-cycle progression[END_REF]. Collectively, these data indicate that while both arginine deprivation and excess can decrease the level of cytokine secretion by TCR-stimulated T cells, they do not diminish the PMA/ionomycin-induced potential of these cells to secrete effector cytokines.

Downregulation of the CAT-1 arginine transporter decreases TCR-mediated CD4 and CD8 T cell proliferation.

The CAT-1/SLC7A1 arginine transporter has been shown to be important for T cell proliferation [START_REF] Werner | Induced arginine transport via cationic amino acid transporter-1 is necessary for human T-cell proliferation[END_REF] and indeed, we found that it is highly upregulated following TCR stimulation as shown in (Chapter I, Addendum I, Figure1). In an attempt to modulate arginine availability in CD4/CD8 T cells, we employed a CAT-1-mediated shRNA strategy. T cells were simultaneously activated with anti-CD3/anti-CD28 mAbs and transduced with a lentiviral vector harboring an shCAT-1 or control scramble (shCTRL)

sequence. The transduction efficiency for both constructs, evaluated at day 3 by GFP expression, reached approximately 50% (Figure 3A, left panel). As expected, CAT-1 surface expression was not decreased in either CD4 or CD8 T cells following transduction with the shCTRL vector but notably, the mean florescence intensity of CAT-1 expression in shCAT1transduced lymphocytes was decreased by approximately 50% (Figure 3A, right panels).

shRNA-mediated knockdown of CAT-1 did not alter either the CD4/CD8 ratio (Figure 3B) nor the upregulation of CD25 or CD71 following stimulation (Figure 3C) and cytokine secretion was not impacted (Figure 3D). Furthermore, the proliferation of CD4 as well as CD8 T cells transduced with the shCAT-1 vector did not differ from cells transduced with the shCTRL vector. Interestingly though, those T cells that were susceptible to lentiviral transduction, irrespective of the shRNA construct, proliferated to a greater extent than non-transduced cells, suggesting that lymphocytes that had progressed further into the cell cycle were more susceptible to lentiviral transduction. It is likely that the absence of a detectable impact of CAT-1 downregulation on CD4/CD8 proliferation is due to the experimental setup wherein lymphocytes were already in an activated state when transporter levels were decreased.

Importantly, CD4 T cells with downregulated CAT-1 expression, but not cells with a control shRNA, were negatively selected during the expansion period, as monitored by a loss of GFP (Figure 3E). Moreover, when T cells transduced with a CAT-1-specific shRNA were restimulated (12-14 days post initial TCR stimulation), cells with downregulated CAT-1 exhibited a significantly lower level of proliferation, as monitored by >50% of undivided cells as compared to <20% in control conditions. Conversely, <5% of CAT-1-downregulated T cells underwent 2 divisions whereas >20% of control T cells underwent division (Figure 3E). Thus, CAT-1 upregulation is required for optimal cell cycle entry of human T cells and its continued expression is required for the expansion of these lymphocytes.

Arginine-mediated polyamine synthesis, but not NO production, is required for optimal T cell activation and proliferation. Arginine is used in different metabolic pathways, contributing to the production of iNOS, creatine, agmantine, polyamines, as well as the hypusine modification on the eIF5A translation factor (Figure 4A). To determine the potential contributions of these different pathways to T cell activation and proliferation, the following inhibitors were used: DL-α-(Difluoromethyl)ornithine (DFMO), an inhibitor of putrescine synthesis; asymmetric dimethylarginine (ADMA), a methyl derivate of arginine that impairs nitric oxide (NO) synthesis; and N1-monoguanyl 1,7-diaminoheptane (GC7), a spermidine analogue that inhibits the hypusination (conjugation of the aminobutyl moiety of spermidine to lysine) of the eIF5A translation factor (Figure 4A). Neither the absence of arginine nor any of the tested inhibitors negatively impacted on T cell viability (Figure 4B) but inhibiting polyamine synthesis markedly decreased, in a dose-dependent manner, T cell proliferation (Figure 4C). Interestingly, inhibiting the production of NO (with ADMA) or eIF5A hypusination did not attenuate T cell proliferation (Figure 4C) nor the upregulation of activation markers (Figure 4D). The potential importance of NO production (and NOS activity) in the relative survival/proliferation of CD4 and CD8 T cells will be further evaluated but given the significant decrease in T cell proliferation following inhibition of polyamine biosynthesis, we further investigated its impact on the induction of T cell activation markers. Notably, the upregulation of CD25 was similarly decreased in the absence of arginine as compared to the presence of DFMO, at levels approximately 2-fold lower than control activated T cells (days 3 and 5 of activation, Figure 4D,4E). Consistent with a decreased activation state of DFMO-treated T cells, there was a delay in CD69 downregulation, similarly to that detected in the absence of arginine; 80% vs 60% and 50% vs 10% compared to control cells, at days 3 and 5, respectively (Figure 4D,4E).

T cell activation results in the upregulation of genes involved in polyamine biosynthesis, including ODC and S-adenosylmethionine decarboxylase [START_REF] Fidelus | The role of mitogens and lymphokines in the induction of ornithine decarboxylase (ODC) in T lymphocytes[END_REF][START_REF] Hesterberg | Role of Polyamines in Immune Cell Functions[END_REF][START_REF] Hunt | Effects of anti-oxidants on ornithine decar☐ylase in mitogenically-activated T lymphocytes[END_REF][START_REF] Kay | Control of ornithine decarboxylase activity in stimulated human lymphocytes by putrescine and spermidine[END_REF][START_REF] Kay | Effect of inhibition of spermidine formation on protein and nucleic acid synthesis during lymphocyte activation[END_REF][START_REF] Puleston | Ancillary Activity: Beyond Core Metabolism in Immune Cells[END_REF][START_REF] Scott | Rapid activation of ornithine decarboxylase by mitogenic (but not by nonmitogenic) ligands in human T lymphocytes[END_REF] and polyamine levels increase upon T cell activation (Wang et al., 2011). While the specific role of polyamines as well as the genes regulating their biosynthesis (i.e. ODC) have not been evaluated in T cell development and activation, Myc, a critical transcription factor in both of these processes, regulates polyamine biosynthesis [START_REF] Hesterberg | Role of Polyamines in Immune Cell Functions[END_REF]. The ensemble of these data point to the importance of the arginine-polyamine pathway and future studies will specifically evaluate the role of this axis in regulating T cell activation and effector function.

Materials and Methods

Human T cell isolation and culture. CD3 + and CD4 + T cells were isolated from healthy adult donors. All experiments using primary human cells were conducted in accordance with the Declaration of Helsinki and IRB approval to the French Blood Bank (Etablissement Francais du Sang). T lymphocytes were purified by negative-selection using Rosette tetramers (StemCell Technologies) and purity was monitored by flow cytometry. Lymphocytes were cultured in nutrient-replete (Nutr+) RPMI SILAC medium 1640 supplemented with lysine (0.2mM) and arginine (1.15mM) or in the absence of arginine (-Arg). Both Nutr+ and -Arg medium were supplemented with 10% FCS and 1% penicillin/streptomycin (Gibco-Life technologies). In some experiments, alpha-difluoromethylornithine (DFMO, 0,25 mM or 1mM), asymmetric dimethylarginine (ADMA, 120mM) or GC7 (0,5 µM) were added as indicated.

T cell activation was performed using plate-bound anti-CD3 (clone OKT3, Biolegend) and anti-CD28 (clone 9.3, kindly provided by Carl June) mAbs at a concentration of 1 μg/ml. rIL-2 (100 U/ml) was added every other day starting either at day 2-3 post-activation. Cells were maintained in a standard tissue culture incubator containing atmospheric (20%) O2 and 5% CO2.

Flow cytometry analyses. Immunophenotyping of cells was performed using fluorochromeconjugated mAbs (BD Bioscience or eBioscience) against CD4, CD8, CD45RA and CD45RO and cell activation was monitored using fluorochrome-conjugated mAbs against CD25, CD69 and CD71 (BD Bioscience, Beckman Coulter or eBioscience). CAT-1 (SLC7A1) cell surface expression was monitored by binding to its Fc-coupled receptor binding domain (RBD) ligand (Ivanova et al, manuscript in preparation; patent WO2017085271A1) for 30 min at 37°C

following by a secondary AF647-coupled anti-rFc secondary antibody (Life Technologies).

Proliferation was monitored by labeling cells with VPD450 (BD Biosciences; 1 μM) for 3 min at RT. For intracellular cytokine staining, lymphocytes were re-activated with PMA (Sigma-Aldrich; 100 ng/ml) and ionomycin (Sigma-Aldrich; 1 μg/ml) in the presence of brefeldin A (Sigma-Aldrich; 10 ug/ml) for 3.5-4h at 37 °C. Intracellular staining for IL-2, IFNγ and IL-17 was performed following fixation/ permeabilization using the eBioscience kit (Thermo-scientific)

or using the BD kit (BD Biosciences). Cells were analyzed on an LSRII-Fortessa (BD Biosciences)

and data was analyzed using FlowJo (Tree Star) software.

shRNA-mediated inhibition of CAT-1 mRNA expression in T lymphocytes.

shRNA-encoding lentiviral vectors were generated by transient transfection of 293T cells as described previously [START_REF] Verhoeyen | IL-7 surface-engineered lentiviral vectors promote survival and efficient gene transfer in resting primary T lymphocytes[END_REF]. Briefly, co-transfection was performed with For T cell transductions, 1×10 6 lymphocytes were transduced with shRNA-encoding lentiviral particles (MOI 5) and activated on anti-CD3 /CD28-coated plates in RPMI media. Transduction was evaluated at day 3 as a percentage of GFP + cells on an LSRII Fortessa (BD Biosciences).

Introduction

In the previous chapter, I described our work showing that glutamine deprivation had a pronounced effect, abrogating the differentiation of naïve T cells to a Th1 effector fate and skewing them towards a regulatory suppressive T cell function.

As naïve CD4 + T cells are unable to differentiate to an IFNγ-secreting Th1 fate in glutaminedeprived conditions and rather, generate FoxP3-expressing suppressive T cells, it was important to determine the mechanism(s) responsible for this alteration. We found that this defect is specifically due to a deficiency in intracellular α-ketoglutarate, an intermediate that feeds the tricarboxylic acid cycle (TCA). We further demonstrated that an exogenous cell permeable form rescued Th polarization in these conditions. In the past years, several studies have demonstrated an important role of αKG-dependent hydroxylases and demethylases during T cell differentiation and effector function through epigenetic regulation (Chisolm et al., 2017;[START_REF] Polansky | DNA methylation controls Foxp3 gene expression[END_REF][START_REF] Someya | Improvement of Foxp3 stability through CNS2 demethylation by TET enzyme induction and activation[END_REF][START_REF] Xu | Metabolic control of TH17 and induced Treg cell balance by an epigenetic mechanism[END_REF][START_REF] Yang | Hydrogen Sulfide Promotes Tet1-and Tet2-Mediated Foxp3 Demethylation to Drive Regulatory T Cell Differentiation and Maintain Immune Homeostasis[END_REF].

However, this is clearly not the only mechanism via which aKG (or the ratio between aKG and other TCA metabolites) can impact on T cell functions and it becomes therefore crucial to decipher them. In this context, the major aspect of my PhD project has focused on the role of

Results and Discussion

αKG enhances Th1 differentiation while conversely, inhibiting Treg polarization. To assess whether high αKG levels modulate Th1 differentiation potential, naïve murine CD4 T lymphocytes were TCR-stimulated under Th1 conditions in the absence or presence of exogenous αKG. Notably, αKG significantly augmented the percentage of CD4 T cells secreting IFNg, increasing the mean level from 24% to 52% (p<0.0001, Figure 1A). This increase was regulated at the transcriptional level with a >10-fold augmentation in Ifng mRNA levels (p<0.01) and a markedly altered visualization of RNASeq reads mapped to the Ifng gene (Figure 1B). Thus, high levels of αKG augment the potential of CD4 T cells to produce IFNg following stimulation in Th1-polarizing conditions.

As the potential of a CD4 T cell to generate an effector Th1 phenotype is often inversely related to its potential to adopt a suppressive Treg phenotype (1-3), we assessed whether αKG attenuates Treg polarization. Indeed, while the majority of naïve T cells stimulated under

Treg polarization conditions exhibited an upregulation of the master transcription factor FoxP3, the percentage of FoxP3 + T cells differentiated in the presence of exogenous αKG was approximately 3-fold lower (decreasing from a mean of 60% to 28%, p<0.0001; Figure 1C).

This decrease in Treg polarization efficiency/potential was associated with 3-fold lower levels of FoxP3 mRNA levels and an attenuation of RNAseq reads in the Foxp3 gene (Figure 1D).

Moreover, Treg differentiation was attenuated even when T cells were initially stimulated in control Treg polarization conditions and αKG was added only 24h post-activation (Supplementary Figure 1). Importantly though, the αKG-mediated inhibition of FoxP3 upregulation was specific to Treg polarizing conditions because the activation of natural Treg (nTreg), expressing FoxP3 in a quiescent state, was not altered by αKG (Figure 1E). Together, these data reveal the importance of αKG in regulating the balance in the polarization of naïve The data presented above suggested that αKG might alter the phenotype and persistence of anti-tumor T cells in an in vivo setting. This is especially critical in the "hostile" environment of a solid tumor that consumes high levels of nutrients and is often anaerobic [START_REF] Yong | CAR T-cell therapy of solid tumors[END_REF]. To test this hypothesis, we evaluated the effector function of murine T cells harboring a CAR directed against the ErbB2/HER2 tumor antigen in immunodeficient RAG2 -/-mice bearing the 24JK fibrosarcoma, engineered to express ErbB2 (24JK-ERB) (Figure 3A) [START_REF] Yong | A role for multiple chimeric antigen receptor-expressing leukocytes in antigen-specific responses to cancer[END_REF]. We first assessed

whether αKG altered the differentiation potential of ErbB2-CAR CD4 T cells similarly to that of polyclonal T cells. αKG treatment resulted in a >2-fold increase in IFNg-secreting cells following activation in Th1 conditions and a decrease in FoxP3 + cells, irrespective of whether the T cells were polyclonal or harboring the ErbB2-CAR construct (Supplemental Figure 2).

ErbB2-CAR T cells were then activated under Th1 or Treg polarizing conditions in the absence or presence of αKG for 4 days and adoptively transferred into 24JK-ERB tumor-bearing mice.

At day 20 of tumor growth, the percentages of ErbB2-CAR CD4 T cells within lymph nodes (LN)

were not significantly different in an of the groups (Figure 3B). Notably though, within the tumor, the percentages of ErbB2-CAR CD4 T cells were significantly higher following In association with the data presented above, we found that genes involved in cholesterol biosynthesis were significantly downregulated by αKG treatment (Figure 5A). Cholesterol is an integral part of the lipid membrane and its incorporation is coordinated with efflux via the ATP-binding cassette transporters ABCA1 and ABCG1 [START_REF] Yvan-Charvet | ABCA1 and ABCG1 protect against oxidative stress-induced macrophage apoptosis during efferocytosis[END_REF][START_REF] Yvan-Charvet | Role of HDL, ABCA1, and ABCG1 transporters in cholesterol efflux and immune responses[END_REF]. Notably, loss of these transporters in dendritic cells and macrophages resulted in increased inflammatory responses [START_REF] Westerterp | Cholesterol Accumulation in Dendritic Cells Links the Inflammasome to Acquired Immunity[END_REF][START_REF] Tall | Cholesterol, inflammation and innate immunity[END_REF][START_REF] Westerterp | Deficiency of ATPbinding cassette transporters A1 and G1 in macrophages increases inflammation and accelerates atherosclerosis in mice[END_REF] and the loss of ABCG1 in T cells has been associated with an increased responsiveness to antigen and altered lipid raft formation [START_REF] Bensinger | LXR signaling couples sterol metabolism to proliferation in the acquired immune response[END_REF][START_REF] Armstrong | ATP-binding cassette transporter G1 negatively regulates thymocyte and peripheral lymphocyte proliferation[END_REF]. Conversely, the knockout of ABCG1 has also been associated with an increase in the differentiation of natural Tregs ( 17), but its impact on Treg polarization is not known.

Importantly, we find that αKG significantly decreased mRNA levels of both ABCA1 and ABCG1 in CD4 T cells activated in Treg polarization conditions (p<0.0001, Figure 5B and Supplementary Figure 3). While αKG did not impact on these transporters in Th1 conditions, it is important to note that the levels of both ABCA1 and ABCG1 were significantly higher in Treg-than Th1-polarized cells (Figure 5B).

As the low cholesterol biosynthesis in αKG-treated CD4 T cells activated under Treg conditions was potentially compensated by decreased levels of ABCA1 and ABCG1 efflux transporters, it was not apparent as to whether cholesterol levels were altered. Using a quantitative lipidomics approach ( 18), we found that while total lipids were substantially increased by αKG treatment, the percentage of cholesterol as well as other lipid classes were unchanged (Figure 5C). Consistent with these data, cholesterol supplementation did not augment Treg differentiation, either in the presence or absence of αKG (Figure 5D).

While cholesterol supplementation did not impact on Treg differentiation, despite the massive alterations in the expression of cholesterol biosynthesis genes and ATP-binding cassette transporters, the physical parameters of a membrane are also regulated by changes in the packing of saturated and polyunsaturated fatty acids, altering lateral organization, membrane permeability, tension, bilayer thickness and fluidity, amongst others [START_REF] Ernst | Cellular mechanisms of physicochemical membrane homeostasis[END_REF][START_REF] Sezgin | The mystery of membrane organization: composition, regulation and roles of lipid rafts[END_REF][START_REF] Sezgin | Adaptive lipid packing and bioactivity in membrane domains[END_REF][START_REF] Levental | Polyunsaturated Lipids Regulate Membrane Domain Stability by Tuning Membrane Order[END_REF]. The incorporation of polyunsaturated fatty acids into phospholipids can alter the order of microdomains and the proximity of signaling proteins, thereby impacting on signaling pathways. Indeed, one of the lipid species whose percentage was increased in αKG-treated

Tregs was triacylglycerol (TAG) and cellular stores of TAG in lipid droplets release fatty acids that undergo β-oxidation and regulate gene transcription through different signaling pathways [START_REF] Coleman | Mammalian triacylglycerol metabolism: synthesis, lipolysis, and signaling[END_REF]. Importantly, a comparison of the number of double bonds in phosphatidylcholine (PC) and phosphatidylethanolamine (PE), the most abundant phospholipids in mammalian membranes [START_REF] Van Der Veen | The critical role of phosphatidylcholine and phosphatidylethanolamine metabolism in health and disease[END_REF] revealed a significant increase in unsaturation in response to αKG treatment (p<0.0001,p<0.05; Figure 5E). While polyunsaturated phospholipids are generally associated with a higher disorder, it has been shown that polyunsaturated PE can exert a differential structural effect, increasing molecular order through cholesterol redistribution [START_REF] Shaikh | How polyunsaturated fatty acids modify molecular organization in membranes: insight from NMR studies of model systems[END_REF]. Using the polarity sensitive C-Laurdan probe and a fluorescence correlation spectroscopy (FCS) combined with super-resolution stimulated emission depletion (STED) microscopy [START_REF] Sezgin | Adaptive lipid packing and bioactivity in membrane domains[END_REF][START_REF] Sezgin | Measuring nanoscale diffusion dynamics in cellular membranes with super-resolution STED-FCS[END_REF], we determined that αKG treatment results in an increased generalized polarization (GP). Thus, the αKG-mediated decrease in CD4 T cell polarization to a Treg fate is accompanied by significant changes in membrane composition, with increased TAG and membrane ordering likely regulating the behavior of membrane receptor signaling pathways.

Augmented αKG-dependent TCA cycling and oxidative phosphorylation negatively regulates Treg differentiation

The metabolism of CD4 T cell subsets is distinct; T effector cells exhibit a highly glycolytic metabolism [START_REF] O'sullivan | Fatty acid synthesis tips the TH17-Treg cell balance[END_REF][START_REF] Michalek | Cutting edge: distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+ T cell subsets[END_REF] and suppressive regulatory T cells (Tregs) display a mixed metabolism with augmented lipid oxidation [START_REF] Berod | De novo fatty acid synthesis controls the fate between regulatory T and T helper 17 cells[END_REF][START_REF] Michalek | Cutting edge: Distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+ T cell subsets[END_REF][START_REF] Shi | HIF1{alpha}-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells[END_REF][START_REF] Wang | The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation[END_REF]. However, while mitochondrial metabolism is critical for Treg differentiation and function [START_REF] Layman | Ndfip1 restricts mTORC1 signalling and glycolysis in regulatory T cells to prevent autoinflammatory disease[END_REF][START_REF] He | Metabolic control of regulatory T cell (Treg) survival and function by Lkb1[END_REF][START_REF] Howie | Foxp3 drives oxidative phosphorylation and protection from lipotoxicity[END_REF][START_REF] Chapman | mTOR coordinates transcriptional programs and mitochondrial metabolism of activated Treg subsets to protect tissue homeostasis[END_REF][START_REF] Weinberg | Mitochondrial complex III is essential for suppressive function of regulatory T cells[END_REF], long chain fatty acid oxidation does not appear to be required [START_REF] Raud | Etomoxir Actions on Regulatory and Memory T Cells Are Independent of Cpt1a-Mediated Fatty Acid Oxidation[END_REF] and the precise role of the TCA cycle in fueling oxidative phosphorylation in Tregs is not known. Interestingly, the level of basal oxygen consumption (correlating with oxidative phosphorylation, OXPHOS) as well as spare respiratory capacity was higher in CD4

T cells polarized to a Th1 as compared to a Treg fate (Figure 6A). These data are in accord with a recent study that reported a lower OXPHOS and glycolysis in activated nTreg as well as iTreg as compared to Th0 and Th1 polarized cells [START_REF] Priyadharshini | Cutting Edge: TGF-beta and Phosphatidylinositol 3-Kinase Signals Modulate Distinct Metabolism of Regulatory T Cell Subsets[END_REF]. The higher OXPHOS in Th1 cells (as compared to Treg) was associated with an augmented glycolysis (measured as a function of the extracellular acidification rate, ECAR); as such, the OCR/ECAR ratios in Th1 and Tregs were equivalent (data not shown). Thus, CD4 T cells polarized to a Treg fate exhibit a lower energetic profile than cells polarized to a Th1 fate.

αKG directly affected the metabolism of Treg-polarized cells because its injection into the flux analyzer immediately increased oxygen consumption (Figure 6A, middle) and 2 days later, both the basal and spare respiratory capacity were markedly elevated (Figure 6A, right). This increase in OXPHOS resulted in an elevated OCR/ECAR ratio (data not shown) and in accord with the enhanced ATP production from oxidative phosphorylation as compared to aerobic glycolysis, the ratio of ATP/ADP was significantly higher in αKG-treated cells (p<0.05; Figure 6B). These data strongly suggested an increased level of cycling of TCA intermediates (Supplemental Figure 4A) and indeed, while αKG levels were markedly elevated (p<0.0001),

as expected from the ectopic addition of mM quantities, it was surprising that MS metabolite analysis did not reveal significant increases in either succinate or malate (Figure 6C).

Accordingly, we detected a substantial utilization of ectopic αKG in the TCA cycle, monitored by the tracing of glutamine and glucose uniformly labelled with heavy carbon ( 13 C5 and 13 C6, respectively), as shown by an increased level of utilization of non-labelled (C0) in the generation of the different intermediates (Supplemental Figure 4B). The enhanced level of TCA cycling was also associated with a decreased generation of intracellular lactate (Supplemental Figure 4C), in agreement with the increased OCR/ECAR ratio in the presence of αKG.

To assess whether increased αKG levels and the associated augmentation in the αKG/succinate ratio regulated Treg polarization, we monitored the impact of ectopic succinate. While the addition of succinate did not significantly alter Treg polarization, it significantly attenuated the negative impact of αKG (Figure 6D). Succinate, which often accumulates due to mutations in the succinate dehydrogenase (SDH) gene, can function by inhibiting prolyl hydroxylase (PHD), thereby leading to stabilization of the HIF-1α transcription factor and decreased TCA flux through the αKG dehydrogenase complex [START_REF] Selak | Succinate links TCA cycle dysfunction to oncogenesis by inhibiting HIF-alpha prolyl hydroxylase[END_REF][START_REF] King | Succinate dehydrogenase and fumarate hydratase: linking mitochondrial dysfunction and cancer[END_REF][START_REF] Koivunen | Inhibition of hypoxiainducible factor (HIF) hydroxylases by citric acid cycle intermediates: possible links between cell metabolism and stabilization of HIF[END_REF]. To distinguish between potential cytosolic and mitochondrial effects of succinate, we inhibited succinate oxidation with malonate, using a cell-permeable dimethyl malonate (DMM) molecule, impairing the oxidation of succinate to fumarate without altering PHD activity in the cytoplasm [START_REF] Mills | Succinate Dehydrogenase Supports Metabolic Repurposing of Mitochondria to Drive Inflammatory Macrophages[END_REF]. Malonate directly decreased oxygen consumption in the presence of αKG, as shown by a diminished spare respiratory capacity following its injection into the Seahorse machine (Figure 6E). Notably, under these conditions, malonate not only restored the induction of FoxP3 + T cells in the presence of αKG (p<0.0001) but increased FoxP3 levels under control conditions (mean of 63% to 75% FoxP3 + cells, p<0.01; Figure 6F). Furthermore, malonate massively reduced the generation of inflammatory cytokines including IFN-g, IL-17, IL-2, TNFa and GM-CSF (p<0.005, Figure 6G). Similarly, malonate was recently found to decrease IFN-g secretion in Th1-polarized cells [START_REF] Bailis | Distinct modes of mitochondrial metabolism uncouple T cell differentiation and function[END_REF]. Together, these data show that maintaining a low level of TCA flux is central to Treg differentiation. Indeed, TCA flux is inversely proportional to Treg polarization; conditions that increase TCA flux inhibit Treg polarization while decreased flux augments Treg polarization.

The ensemble of these data provide a mechanistic explanation for the observation by several groups, including our own, that Treg, but not TEFF, generation is maintained under conditions where glucose and amino acid transport are limiting [START_REF] Klysz | Glutamine-dependent alphaketoglutarate production regulates the balance between T helper 1 cell and regulatory T cell generation[END_REF][START_REF] Macintyre | The glucose transporter Glut1 is selectively essential for CD4 T cell activation and effector function[END_REF][START_REF] Nakaya | Inflammatory T Cell Responses Rely on Amino Acid Transporter ASCT2 Facilitation of Glutamine Uptake and mTORC1 Kinase Activation[END_REF][START_REF] Sinclair | Control of amino-acid transport by antigen receptors coordinates the metabolic reprogramming essential for T cell differentiation[END_REF][START_REF] Sundrud | Halofuginone inhibits TH17 cell differentiation by activating the amino acid starvation response[END_REF]. Furthermore, together with the finding that Th1 differentiation is augmented under conditions of complement-mediated increases in OCR and ECAR [START_REF] Kolev | Complement Regulates Nutrient Influx and Metabolic Reprogramming during Th1 Cell Responses[END_REF], our results support a mechanism whereby IFN-g secretion by CD4 + T cells is positively regulated by an increased energetic state and an elevated OCR/ECAR ratio. These results have important implications for the modulation of anti-tumor effector function by αKG. Indeed, we found that the negative impact of αKG on Treg polarization was also observed in human CD4 T cells (Supplementary Figure 5). And finally, our data showing that the intratumoral migration of effector CAR-T cells is significantly augmented by pretreatment with αKG suggests that this TCA cycle intermediate may promote the persistence and efficacy of anti-tumor CAR T cells.

Materials and Methods

Mice

Ly5.1 or Ly5.2 C57BL/6 mice were crossed with Foxp3-GFP reporter mice and mice harboring an ErbB2-CAR (Yong et al., 2015) were crossed with C57BL/6 FOXP3GFP mice. Mice were housed in a conventional, pathogen-free facility at the Institut de Génétique Moléculaire de

Montpellier. Animal care and experiments All experiments were approved by the local animal facility institutional review board in accordance with French national guidelines.

T cell isolation, activation and culture

Murine CD4 + T cells from the indicated mice strains were purified using the MACS CD4 + T cell negative selection kit (Miltenyi Biotec) and naïve CD4 + T cells were then sorted on the basis of a CD4 + CD8 -CD62L hi CD44 -GFP -expression profile on a FACSAria flow cytometer (BD Biosciences). Natural Tregs were sorted as CD4 + CD8 -CD62L hi CD44 -CD25 + GFP + . T cell activation was performed using plate-bound a-CD3 (clone 145-2C11, 1 mg/ml) and a-CD28

(clone PV-1, 1 mg/ml) monoclonal antibodies in RPMI 1640 medium (Life Technologies) supplemented with 10% FCS, 1% penicillin/streptomycin (Gibco-Life technologies). For Th1 and iTreg-polarizing conditions, IL-12 (15 ng/ml) and aIL-4 antibody (5 ug/ml) or hTGF-b (3 ng/ml) and hIL-2 (100 U/ml), respectively, were added to the cultures. When indicated, cell permeable αKG (dimethyl ketoglutarate, 3.5 mm; Sigma), malonate (dimethyl malonate, 10mM; Sigma), succinate (diethyl succinate, 10mM; Sigma) and water soluble cholesterol (50mM, C4951, Sigma) were added. Cells were maintained in a standard tissue culture incubator containing atmospheric (20%) O2 and 5% CO2.

Human CD4 + T cells were isolated from healthy adult donors. All experiments using primary human cells were conducted in accordance with the Declaration of Helsinki and IRB approval to the French Blood Bank (Etablissement Francais du Sang). T lymphocytes were purified by negative-selection using Rosette tetramers (StemCell Technologies) and the purity was monitored by flow cytometry. For sorting of Human CD4 + Naïve T cells, CD4 + T cells were sorted on the basis of CD4 + CD8 -CD45RA + CD45RO -CCR7 + CD62L + CD127 low and CD25 -on a BD FACSAria flow cytometer. For Th1 and iTreg-polarizing conditions, IL-12 (10 ng/ml) and a-IL-added to the cultures. T cell activation was performed using plate-bound a-CD3 (clone OKT3, Biolegend) and a-CD28 (clone 9.3, kindly provided by Carl June) mAbs at a concentration of 1 μg/ml in RPMI medium 1640 (Life Technologies) supplemented with 10% FCS and 1% penicillin/streptomycin (Gibco-Life technologies).

Immunophenotyping and flow cytometric analysis

Immunophenotyping of cells was performed with fluorochrome-conjugated antibodies, and intracellular staining was performed after the fixation and permeabilization of the cells (intracellular staining kit from ThermoFisher or BD Bioscience). Analysis of cells collected from in vivo experiments were performed following Fc block treatment (2.4G2, BioXcell) for 10 minutes prior to incubation with conjugated antibodies for FACS analysis. For intracellular cytokine staining, cells were stimulated with phorbol 12-myristate 13-acetate (PMA) (100 ng/ml) and ionomycin (1 μg/ml) in the presence of brefeldin A (10 ug/ml; all from Sigma) for 3.5-4h at 37 °C. Cells were labeled with fixable viability dye prior to fixation, followed by at least 3 hours of intracellular staining with the following antibodies; Foxp3-PeCy7, T-Bet-Pe and IFNg-APC. Cytokine production (IFNg, TNFα, IL-2, IL-17 and IL-10) was also assessed by Cytometric Bead Array (CBA) Kit (BD Biosciences) using supernatants at day 3 of polarization.

For human cells; immunophenotyping was performed using fluorochrome-conjugated mAbs against CD4, CD8, CD45RA, CD45RO, CCR7 and CD62L (BD Bioscience, Beckman Coulter or eBioscience). Cells were analyzed on a FACSCanto or LSRII-Fortessa flow cytometer (BD Biosciences). Data analysis was performed using FlowJo (Tree Star software) and FCAPArray Software (CBA analysis). Antibodies are presented in Table 1.

Tumour model and adoptive T cell transfer

The murine 24JK fibrosarcoma cell line expressing the human ErbB2/Her2 antigen was generated as described Yong, 2016 #3110}. 24JK-ErbB2 (1 x 10 6 ) were subcutaneously injected into RAG2 -/-mice and allowed to establish over a 7 days period. On day 7, 3-5 x 10 6 in vitro

ErbB2-CAR T cells, activated as indicated, were injected retroorbitally into tumor-bearing mice. For endpoint analyses,: tumors were excised, mechanically digested in T cell culture media (as above) using collagenase IV (1 mg/ml, Sigma) and DNASE I (500mg/ml, Roche), incubated for 25 minutes at 37°C and processed into single cell suspensions for FACS analysis.

Lymph nodes and spleens of tumor bearing mice were isolated and dissociated into single cell suspensions in PBS + 2% FCS and analyzed by flow cytometry.

RNA-seq analysis

T cells (5x 10 6 ) were lysed in triplicates in TRIzol (Thermofisher). Total RNA was isolated using the mirVana (Applied Biosystems) isolation kit. RNA-seq libraries were prepared from 4 μg of total RNA using the TruSeq RNA sample preparation kit following manufacturer's protocol (Illumina). Briefly, oligo-dT purified mRNA was fragmented and subjected to first and second strand cDNA synthesis. cDNA fragments were blunt-ended, ligated to Illumina adaptors, and PCR amplified to enrich for the fragments ligated to adaptors. The resulting cDNA libraries were verified and quantified on Agilent Bioanalyzer and RNA-seq was conducted using the GAIIx Genome Analyzer (Illumina). Reads from RNA-seq were mapped to the human genome (GRCh37, hg19) using the splice-aware aligner TopHat with optionmate-inner-dist 160coverage-searchmicroexon-searchmax-multi hits. Aligned reads were then visualized on a local mirror of the UCSC Genome Browser. Quantification of gene expression was performed by counting aligned reads on each gene, for each condition. DEGseq was then applied to identify differentially expressed genes with p value ⩽ 1e -5 .

Gene expression analysis

RNA was isolated from T cells as indicated using the RNeasy Micro Kit and then reversetranscribed to produce cDNA using oligonucleotide priming with the QuantiTect Reverse Transcription Kit (both Qiagen). Quantitative PCR was performed using the Quantitect SYBR green PCR Master mix (Roche) with 10 ng of DNA and 0.5 µM primers in a final volume of 10 µl. Amplification of DNAs was performed using the LightCycler 480 (Roche). Each sample was amplified in triplicate. Relative expression was calculated by normalization to HPRT and primer sequences are presented in Table 2.

Lipid analyses

Mass spectrometry-based lipid analysis was performed at Lipotype GmbH (Dresden, Germany) as previously described (Sampaio et al., 2011). Lipids were extracted using a twostep chloroform/methanol procedure (Ejsing et al., 2009). Samples were analyzed by direct infusion on a QExactive mass spectrometer (Thermo Scientific) equipped with a TriVersa NanoMate ion source (Advion Biosciences) as described (Mitroulis et al., 2018). Phospholipids were analyzed by electrospray ionization tandem mass spectrometry (ESI-MS/MS) on a hybrid quadrupole linear ion trap mass spectrometer (4000 QTRAP system, AB SCIEX) equipped with a TriVersa NanoMate robotic nanosource (Advion Biosciences) as previously described (Talebi et al., 2018).

Generalized polarization (GP) was calculated to determine molecular order of the plasma membrane. Cells were stained with Laurdan (ThermoFisher) and fixed with 4% paraformadehyde before super-resolution STED microscopy with scanning fluorescence correlation spectroscopy (scanning STED-FCS, sSTED-FCS) to characterize the spatial and temporal heterogeneity of lipid interactions as previously described (Sezgin et al., 2019).

Quantification of fluorescence intensity was performed using NIH ImageJ.

Mass spectrometry (LC-MS)

For profiling of intracellular metabolites, cells (1x10 6 ) were treated as previously described (Oburoglu et al., 2014). Briefly, cells were incubated in RPMI medium without glucose or glutamine and supplemented with uniformly labeled [U-13 C6]glucose or [U-13 C5- [START_REF] Collaborators | Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015[END_REF]. Radiotherapy and chemotherapy have been extensively used, however the limited efficiency on refractory and metastatic cancers as well as the off-side target effects revealed the necessity to develop other therapies.

In the last decades, cancer immunotherapy has demonstrated to be a new promising solution:

In 2013, it was acknowledged as the breakthrough of the year by Science due to the concept of targeting directly the immune system (and not the tumor itself) and to the fantastic success in the treatment of certain cancers such as leukemia and melanomas [START_REF] Couzin-Frankel | Breakthrough of the year 2013. Cancer immunotherapy[END_REF][START_REF] Sambi | Current Challenges in Cancer Immunotherapy: Multimodal Approaches to Improve Efficacy and Patient Response Rates[END_REF]. Manipulating and improving anti-tumor immune responses, instead of using pharmacological/chemical anti-tumor treatments, was indeed an ingenious approach.

One of the major innovations on cancer immunotherapy is CAR T Cells. Until now, CAR T cell therapies have been associated with high success rate for the treatment of hematological malignancies [START_REF] Cao | Potent anti-leukemia activities of humanized CD19-targeted Chimeric antigen receptor T (CAR-T) cells in patients with relapsed/refractory acute lymphoblastic leukemia[END_REF][START_REF] Wei | Advances of CD19-directed chimeric antigen receptor-modified T cells in refractory/relapsed acute lymphoblastic leukemia[END_REF]. CAR T cells were accepted for clinical use in the European Union for the first time last year. The two first CAR constructs (Kymriah and Yescarta) were approved to treat several cancers such as ALL, CLL, DLBCL (diffuse large B-cell lymphoma), SLL (small lymphocytic lymphoma), PMBCL (primary mediastinal large B-cell lymphoma) and FL (follicular lymphoma) (European Medicines Agency.2018). Despite the high success of CAR T cells in blood cancers, the treatment of solid tumors has been less fruitful (Yong et al., 2017) and one of the reasons is the TME. Firstly, the existence of physical barriers (stromal cells) which negatively impact T cell infiltration [START_REF] Newick | CAR T Cell Therapy for Solid Tumors[END_REF]Yong et al., 2017). Secondly, the existence of an adverse metabolic environment that can impact T cell anti-tumor functions [START_REF] Anderson | Obstacles Posed by the Tumor Microenvironment to T cell Activity: A Case for Synergistic Therapies[END_REF][START_REF] Buck | Metabolic Instruction of Immunity[END_REF]. As described in the section IV of this thesis literature review, the metabolic activity of tumor cells as well as myeloid and stromal cells resident in the TME can induce a deprivation of nutrients and as a result a competition for resources with T cells. Furthermore, from these metabolic reactions, byproducts such as lactate are produced as well, creating a hostile T cell surrounding environment. Thus, it becomes important to evaluate the impact of these metabolic conditions on T cell differentiation and effector function in order to optimize CAR T cell immunotherapies. To that purpose, during my PhD, I evaluated how the metabolic environment can impact T cell functions.

Nutrient deprivation and T cell function

One of the approaches used during my thesis to assess the potential impact of the TME on T cells, was to stimulate T cells in nutrient depleted conditions. Glutamine, the most abundant amino acid in the human plasma [START_REF] Roth | Nonnutritive effects of glutamine[END_REF], was one of the nutrients I focused on during my thesis. The study of glutamine metabolism on T cell functions is particularly relevant in this context as is was demonstrated that some malignant cells highly consume and metabolize glutamine to sustain their grow and survival [START_REF] Choi | Targeting Glutamine Metabolism for Cancer Treatment[END_REF][START_REF] Kovacevic | The role of glutamine in the oxidative metabolism of malignant cells[END_REF]. More specifically, it has been demonstrated that cancers as NSCLC, breast and brain are particularly dependent on glutamine and upregulate the transporter ASCT2 in order to enhance glutamine uptake [START_REF] Marquez | Glutamine Addiction In Gliomas[END_REF][START_REF] Mohamed | Altered glutamine metabolism and therapeutic opportunities for lung cancer[END_REF].

In our lab, we demonstrated that glutamine availability is important for the differentiation of naïve CD4 + T cells towards a Th1 fate (Chapter 2, Article II) (Klysz et al., 2015). In glutaminedeprived conditions, naïve T cells stimulated under Th1 polarizing conditions were not able to differentiate into Th1 cells and consequently to secrete IFNγ. However, Th2 and iTreg differentiations were not impacted, showing the glutamine is not required for Th2 and iTreg differentiation program. Furthermore, lower glutamine availability pushed naïve CD4 + T cells toward a Treg phenotype even under Th1 polarizing conditions in a TFG-β dependent manner.

Thus, absence of glutamine favored iTreg and blocked Th1 differentiation. To understand what was the rate limiting step, we decided to look specifically at the glutamine metabolic pathway. As described in section II of this thesis literature review, αKG is one of the crucial metabolites that results from glutamine catabolism. Based on this knowledge, we decided to evaluate if αKG levels were a rate-limiting step. Indeed, when extracellular αKG was added in glutamine deprived conditions, naïve CD4 + T cells were able to differentiate towards a Th1 fate and T-bet expression as well as IFNγ secretion was restored. These results were translational to the humans. Metzler and colleagues showed that glutamine restriction induce high level of FoxP3 expression as well in human T cells [START_REF] Metzler | Restricting Glutamine or Glutamine-Dependent Purine and Pyrimidine Syntheses Promotes Human T Cells with High FOXP3 Expression and Regulatory Properties[END_REF]. Also, similar results were obtain when glutamine-dependent purine and pyrimidine synthesis was blocked [START_REF] Metzler | Restricting Glutamine or Glutamine-Dependent Purine and Pyrimidine Syntheses Promotes Human T Cells with High FOXP3 Expression and Regulatory Properties[END_REF]. However, in this study exogenous αKG was not able to restore Th1 differentiation, demonstrating the existence of differences between murine and human T cells.

These data brought important clues about Th1 and Treg metabolic requirements. The fact that glutamine is not equally required for pro-inflammatory Th1 cells and anti-inflammatory iTreg cells indicates that the metabolic requirements of both subsets are not the same.

Indeed, it was demonstrated that TEFF rely more in aerobic glycolysis while Treg cells are more dependent on fatty acid metabolism [START_REF] Geltink | Unraveling the Complex Interplay Between T Cell Metabolism and Function[END_REF]Michalek et al., 2011;Shi et al., 2011).

Another elegant study goes in line with the results from our lab as they demonstrated that ASCT2 knockout impeached the differentiation of Th1 and Th17 cells without affecting the differentiation of Th2 and Treg cells (Nakaya et al., 2014). Our results together with other groups data allow to conclude that Treg cells do not require glutamine, contrary to Th1 cells.

Indeed, it has been demonstrated that Treg cells metabolic program is not dependent on amino acid metabolism. For instance, degradation of tryptophan in the cell environment by DCs (which can negatively impact T cell metabolism) results in a byproduct product formation (kynurenine) which was shown to promote iTreg differentiation [START_REF] Mezrich | An interaction between kynurenine and the aryl hydrocarbon receptor can generate regulatory T cells[END_REF].

Deficiency in the neutral amino acid transporter LAT1 was demonstrated as well to impair CD4 and CD8 effector function without impacting Treg differentiation [START_REF] Hayashi | LAT1 is a critical transporter of essential amino acids for immune reactions in activated human T cells[END_REF]Sinclair et al., 2013). Interestingly, it was as well shown that Treg cells induce, in skin grafts and dendritic cells, the expression of at least 5 enzymes that consume different essential amino acids [START_REF] Cobbold | Infectious tolerance via the consumption of essential amino acids and mTOR signaling[END_REF] presence on the TME is associated with a poor prognosis [START_REF] Bates | Quantification of regulatory T cells enables the identification of high-risk breast cancer patients and those at risk of late relapse[END_REF][START_REF] Curiel | Specific recruitment of regulatory T cells in ovarian carcinoma fosters immune privilege and predicts reduced survival[END_REF][START_REF] Hiraoka | Prevalence of FOXP3+ regulatory T cells increases during the progression of pancreatic ductal adenocarcinoma and its premalignant lesions[END_REF][START_REF] Hou | Age-related changes in CD4+CD25+FOXP3+ regulatory T cells and their relationship with lung cancer[END_REF][START_REF] Ormandy | Increased populations of regulatory T cells in peripheral blood of patients with hepatocellular carcinoma[END_REF][START_REF] Wolf | Increase of regulatory T cells in the peripheral blood of cancer patients[END_REF]. Our group has found that glutamine-deprive environments, such as the TME, benefit to iTreg differentiation.

The fact that Tregs seem to be less dependent of amino acids to sustain their metabolic chain surface expression inhibition and antigen-specific T cell proliferation impairment [START_REF] Rodriguez | Arginase I production in the tumor microenvironment by mature myeloid cells inhibits T-cell receptor expression and antigenspecific T-cell responses[END_REF]. As such, studying how reduced arginine availability impact on T cell functions becomes highly relevant. During my PhD, I evaluated the role of arginine on human T cell function using 3 different angles: by reducing arginine availability in the medium, by using drugs inhibiting different arginine metabolic pathways and finally through CAT-1 surface expression downregulation by a Sh-RNA approach. Our results demonstrated that arginine deprivation impacted T cell activation and proliferation (Chapter 2, Addendum II, Figure 1).

These effects on T cell activation and proliferation were as well documented in few other publications [START_REF] Rodriguez | L-arginine availability regulates Tlymphocyte cell-cycle progression[END_REF][START_REF] Taheri | L-Arginine regulates the expression of the T-cell receptor zeta chain (CD3zeta) in Jurkat cells[END_REF][START_REF] Zea | L-Arginine modulates CD3zeta expression and T cell function in activated human T lymphocytes[END_REF]. However, the CD4:CD8 ratio and CD45RA vs CD45RO percentages (naïve versus memory/effector cells) seemed not to be affected (Chapter 2, Addendum II, Figure 2A and2B). Regarding the effector function of those cells, we observed a diminished IFNγ secretion from CD4 + T cells, however it was not significant based on our statistical analysis (Chapter 2, Addendum II, Figure 2C). Only one group demonstrated a link between arginine availability, T cell phenotype and anti-tumor function, although using an opposite strategy. Geiger and colleagues showed that increased arginine extracellular levels enhanced the survival and antitumor activity by promoting a generation of a memory-like T cells [START_REF] Geiger | L-Arginine Modulates T Cell Metabolism and Enhances Survival and Anti-tumor Activity[END_REF]. Based on this study, we would expect to see a decrease in the percentage of RO + (memory) cells in deprived arginine conditions, as increased arginine availability induced the generation of memory T cells. However, we observed no significant differences. As T cell memory differentiation is highly dependent on T cell metabolic program and memory T cells rely mainly on OXPHOS and FAO [START_REF] Almeida | Metabolic pathways in T cell activation and lineage differentiation[END_REF][START_REF] Verbist | T cell metabolism and the immune response[END_REF], to evaluate how T cell metabolism is impacted in arginine deprived conditions could be interesting approach angle to understand the T cell phenotype observed in arginine-deprived conditions. At which extend are OXPHOS and glycolysis impacted in the absence of arginine? Therefore, it would be interesting to pursue with this project and investigate the impact of arginine deprivation on CD4 + T cell phenotype and differentiation. Notably, the impact of arginine availability on memory T cells as well as on iTregs and Th1 cells.

Arginine can fuel different metabolic axis of its own pathway (Figure 17), what makes complex to analyze which is indeed important for T cell metabolic fitness. From arginine catabolism can result the production of citrulline and ornithine. Citrulline is an important precursor related with the TCA cycle while ornithine is an important precursor for polyamines synthesis. Thus, arginine deprivation conditions can have several and different implications on T cell metabolism. In order to understand more in detail for what for is arginine required in a CD4 + T cell context, we used in culture three different drugs able to block different reactions (Chapter 2, Addendum II, Figure 4A). Preliminary data, indicates that while blocking citrulline synthesis (ADMA) or hyposination (GC7) does not impact T cell activation and proliferation, DFMO treatment, which block ornithine and polyamine synthesis, has a negative impact (Chapter 2, Addendum II, Figure 4C and4D). It was described that in human naïve T cells the activity levels of polyamine synthesis enzymes are low [START_REF] Kay | Control of ornithine decarboxylase activity in stimulated human lymphocytes by putrescine and spermidine[END_REF][START_REF] Kay | Effect of inhibition of spermidine formation on protein and nucleic acid synthesis during lymphocyte activation[END_REF] and increase upon TCR activation (notably ODC and Sadenosylmethionine decarboxylase) [START_REF] Fidelus | The role of mitogens and lymphokines in the induction of ornithine decarboxylase (ODC) in T lymphocytes[END_REF][START_REF] Kay | Control of ornithine decarboxylase activity in stimulated human lymphocytes by putrescine and spermidine[END_REF][START_REF] Kay | Effect of inhibition of spermidine formation on protein and nucleic acid synthesis during lymphocyte activation[END_REF][START_REF] Scott | Rapid activation of ornithine decarboxylase by mitogenic (but not by nonmitogenic) ligands in human T lymphocytes[END_REF]. A more recent study demonstrates now, that polyamine levels in T cells are highly increased upon activation (Wang et al., 2011). Moreover, and in line with our data, they demonstrated as well that DFMO treatment inhibited activation-induced T cell proliferation (Wang et al., 2011). Interestingly, DFMO has been tested (phase II) to treat high risk neoblastoma [START_REF] Sholler | Maintenance DFMO Increases Survival in High Risk Neuroblastoma[END_REF]. Several studies demonstrated that some tumors have a high content on polyamines and the treatment with DFMO reduces tumor proliferation in vitro and in xenograft models [START_REF] Hixson | Ornithine decarboxylase and polyamines in colorectal neoplasia and mucosa[END_REF][START_REF] Hogarty | ODC1 is a critical determinant of MYCN oncogenesis and a therapeutic target in neuroblastoma[END_REF][START_REF] Koomoa | Ornithine decarboxylase inhibition by alpha-difluoromethylornithine activates opposing signaling pathways via phosphorylation of both Akt/protein kinase B and p27Kip1 in neuroblastoma[END_REF][START_REF] Rounbehler | Targeting Ornithine Decarboxylase Impairs Development of <em>MYCN</em>-Amplified Neuroblastoma[END_REF][START_REF] Samal | AMXT-1501, a novel polyamine transport inhibitor, synergizes with DFMO in inhibiting neuroblastoma cell proliferation by targeting both ornithine decarboxylase and polyamine transport[END_REF]. However, based on our and others data, we could hypothesize that DFMO treatment could have an impact in TILs proliferation and, consequently, in anti-tumor function. Therefore, it would be interesting to evaluate the effect of DFMO on TILs in order to weight the impact of DFMO treatment in the immune system.

Furthermore, it would be of interest to assess the impact on CD4 + T cell differentiation in order to evaluate if DFMO treatment affects differently for instance Th1 and Treg cells and consequently creates a disequilibrium in T cell effector responses.

Finally, I also evaluated the potential impact of CAT-1 surface expression downregulation (an essential arginine transporter) (Chapter 2, Addendum II, Figure 3) during T cell activation.

Decreased CAT-1 surface expression did not significantly impact CD4: CD8 ratio, T cell activation and proliferation. These results were surprising considering than in arginine deprived conditions T cell proliferation and activation were highly impacted. Therefore, by downregulating CAT-1 surface expression, in theory we should have reduced entry of arginine into the cell and therefore to have similar results as in arginine deprived culture conditions.

However, the results did not go in the same direction. These results can be potentially explained by a compensatory mechanism. Apart of CAT-1, other nutrient transporters can mediate arginine entry into the cells such as CAT-2 and CAT-3 [START_REF] Closs | Structure and function of cationic amino acid transporters (CATs)[END_REF][START_REF] Fotiadis | The SLC3 and SLC7 families of amino acid transporters[END_REF]. Regardless the fact that CAT-1 mRNA is selectively upregulated upon T cell activation, we could hypothesize that T cells can upregulate CAT2 and CAT3 in response to CAT-1 downregulation. Looking at the mRNA levels of these three transporters simultaneity in Sh transduced cells could give us important clues about this hypothesis. Moreover, it would be important to look at the arginine uptake level in Sh transduced cells (sh control vs shCAT-1) to measure the impact of CAT-1 downregulation in arginine entry into the cells.

Altogether, these data highlight the impact of nutrient deprivation on T cell activation, an increased acquisition of an effector phenotype and secrete higher amounts of IFNγ [START_REF] Cretenet | Cell surface Glut1 levels distinguish human CD4 and CD8 T lymphocyte subsets with distinct effector functions[END_REF]. Previous studies demonstrated that increased T cell glycolysis boosted anti-tumor effector functions, notably by promoting IFNγ secretion [START_REF] Cham | Glucose deprivation inhibits multiple key gene expression events and effector functions in CD8+ T cells[END_REF][START_REF] Ho | Phosphoenolpyruvate Is a Metabolic Checkpoint of Anti-tumor T Cell Responses[END_REF]. Thus, our work together with others, demonstrate that GLUT1 surface expression and as well as increased glycolysis are highly linked to T cell effector function. Furthermore, our investigation shows that GLUT1 High cells also have increased effector function in hypoxia conditions. These results are particularly relevant in a context of anti-tumor therapy, as the TME is highly hypoxic [START_REF] Vaupel | Hypoxia in cancer: significance and impact on clinical outcome[END_REF]. Therefore, it would be interesting to evaluate in vivo the efficacy/fate of T cells sorted based on nutrient transporter expression, to address notably which subset has a better anti-tumor function. As GLUT1 High cells have an increased percentage of effector memory cells and secrete higher amounts of IFNγ it would be tempting to speculate that these cells will have a better anti-tumor function. Indeed, several studies demonstrated that TEFF/ TEM and consequent cytokine secretion induce tumor regression and maintain long-term tumor protection in preclinical models [START_REF] Perret | Effector CD8+ T cells activated in vitro confer immediate and long-term tumor protection in vivo[END_REF][START_REF] Powell | Transition of latestage effector T cells to CD27+ CD28+ tumor-reactive effector memory T cells in humans after adoptive cell transfer therapy[END_REF][START_REF] Rosenberg | Cancer regression in patients with metastatic melanoma after the transfer of autologous antitumor lymphocytes[END_REF]. Nonetheless, other studies showed that these cells persist poorly in vivo, which is not optimal for anti-tumor responses [START_REF] Dudley | A phase I study of nonmyeloablative chemotherapy and adoptive transfer of autologous tumor antigen-specific T lymphocytes in patients with metastatic melanoma[END_REF][START_REF] Gattinoni | Acquisition of full effector function in vitro paradoxically impairs the in vivo antitumor efficacy of adoptively transferred CD8+ T cells[END_REF][START_REF] Yee | Adoptive T cell therapy using antigen-specific CD8+ T cell clones for the treatment of patients with metastatic melanoma: in vivo persistence, migration, and antitumor effect of transferred T cells[END_REF]. Additionally, other works demonstrated that TCM have also an effective tumor function changing the paradigm that only TEFF/ TEM are effective and should be used in anti-tumor immunotherapies [START_REF] Beckhove | Specifically activated memory T cell subsets from cancer patients recognize and reject xenotransplanted autologous tumors[END_REF][START_REF] Busch | Role of memory T cell subsets for adoptive immunotherapy[END_REF][START_REF] Klebanoff | Central memory self/tumor-reactive CD8+ T cells confer superior antitumor immunity compared with effector memory T cells[END_REF]. Therefore, and even if GLUT1 High subset is enriched in effector T cell with higher proliferative capacity and effector function, it remains to prove that GLUT1 High cells offers in vivo a better and persistent anti-tumor response than GLUT1 Low cells. With this propose, in vivo experiments on tumor-bearing mice are ongoing to evaluate the fate and anti-tumor function of these sorted subsets.

During my PhD I also had the opportunity to initiate studies evaluating the potential of CAT-1 nutrient transporter as a T cell selection tool. Preliminary data demonstrates that, as GLUT1 High cells, CAT-1 High cells proliferate faster and have a decreased CD4:CD8 ratio (Chapter I, addendum I, Figure 3). However, the cytokine prolife appeared to be slightly different between these two T cell subsets. CD8 + GLUT1 High cells secrete more IFNy than CD8 + GLUT1 Low .

However, these differences are not observed between CD8 + CAT-1 high and CD8 + CAT-1 Low subsets (Chapter I, addendum I, Figure 5). Moreover, one major difference between these different subsets is that CD4 + GLUT1 High and CD4 + GLUT1 Low produce different levels of IFNγ whereas CD4 + CAT-1 High differ mainly from CD4 + CAT-1 Low on IL-17 secretion levels with IFNγ secretion only slightly affected (Chapter I, addendum I, Figure 5). Therefore, these preliminary results suggest that the level of GLUT1 and CAT-1 surface expression allow the selection of T cell subsets with distinct effector functions, notably characterized by different IFNy and IL-17 secretion levels. As a result, it would be interesting to further evaluate and characterize T cells selected based on CAT-1 surface expression to confirm this preliminary result. Moreover, it would be interesting to evaluate and compare the fate and function of these subsets in tumor-bearing mice. The fact that CD4 + CAT-1 High cells are associated with an increased IL-17 production and minimal differences on IFNγ secretion would be interesting to explore. The role of IL-17 on tumor development has been controversial so far and its pro-or anti-tumor functions remain under debate. For instance, in ovarian cancer, IL-17 secretion was demonstrated to be associated with a good prognosis, whereas in cancers such as colon and pancreatic cancer, IL-17 secretion was identified as a bad prognosis as reviewed in [START_REF] Bailey | Th17 cells in cancer: the ultimate identity crisis[END_REF]. Therefore, the role of IL-17 on tumor growth remains to be elucidated and in this context, it would be important to address and compare the anti-tumor efficiency of T Our data shows that when exogenous αKG is added, a higher IFNγ secretion in Th1polarizing conditions is observed, which goes in line with our previous study which demonstrates that exogenous αKG restores IFNγ secretion in glutamine-deprived conditions.

Moreover, in iTreg-polarizing conditions, FoxP3 expression decreases. This decrease in FoxP3 expression is associated by an increase in T-bet expression as well as IFNγ secretion and other inflammatory cytokines such IL-17, TNF-α and GM-CSF. Thus, αKG is able to enhance Th1 differentiation and significantly attenuate iTreg differentiation, shifting these cells towards an inflammatory phenotype (Chapter 3, Article III, Figure 1). Interestingly, αKG treatment increased iTreg OXPHOS levels compared to the control condition (Chapter 3, Article III, Figure 6). Furthermore, we also noticed an increase in the αKG/succinate ratio (Chapter 3, Article III, Figure 6). As succinate is highly linked and required to mitochondrial complex II function, we selectively inhibited this complex by using malonate, a SDH competitive inhibitor, which leads to decrease OXPHOS capacity. Malonate treatment restored iTreg differentiation, which highlights the potential impact of OXPHOS modulation in iTreg differentiation and the possible role of the αKG/succinate ratio (Chapter 3, Article III, Figure 6).

In order to evaluate if the phenotype observed upon αKG treatment was due an imbalance between αKG and succinate levels, we used two strategies to alter the αKG/succinate ratio: by adding exogenous succinate or by inhibiting SDH with malonate treatment (which should decrease the αKG/succinate ratio). Adding succinate to αKG -treated iTreg polarization rescued at least partially, the percentage of FoxP3 expressing cells as compared to control, however not statistically significant (Chapter 3, Article III, Figure 6). On the other hand, adding malonate rescued significantly the generation of FoxP3-expressing cells. Thus, we can hypothesize that balancing the αKG/succinate ratio might be important to rescue the percentage of FoxP3 expressing cells but we also need to take in consideration that SDH functioning itself might as well have an important role in iTreg differentiation (Discussion, Figure 1). Importantly, SDH is the only enzyme that participates in both TCA cycle and ETC as part integrant of the mitochondrial complex II. Therefore, an increase in the TCA cycle metabolic rate mediated by αKG treatment could potentially lead to an increase of OXPHOS, notably through SDH enzymatic activity. Recently, a study demonstrated that mitochondrial complex II (SDH) could dictate T cell differentiation (Bailis et al., 2019). More specifically, they revealed that, upon malonate treatment or in the absence of SDH function (SDH KO mice), complex II was important for Th1 differentiation and IFNγ secretion in Th1 polarized conditions (Bailis et al., 2019). These results are in line with our data. Upon malonate treatment, we not only restore the percentage of FoxP3-expressing cells but we also decrease IFNγ secretion. In this work they also revealed that the ETC is differentially recruited in the different CD4 + Th subsets. For instance, blocking separately each one of the five mitochondrial complexes had minimal effect on Th2 effector cells. Moreover, selective and individual blocking of both complex I and complex II impaired Th17 function (Bailis et al., 2019). Furthermore, the role of mitochondrial complexes on Treg cells was recently addressed by another group (Weinberg et al., 2019). In this study, using a murine model lacking specifically the mitochondrial complex III in Treg cells, they demonstrate the importance of this complex for Treg suppressive function. Nonetheless, Treg cell numbers, T cell maintenance and FoxP3 expression were not altered (Weinberg et al., 2019). Yet, the role of mitochondrial complex II on Treg cells remain to be elucidated. Based on these works and our data, we could therefore hypothesize that not all mitochondrial complexes, notably the complex II, function would be required for iTreg cells differentiation and probably complex II works as regulator of the Th1/iTreg cell differentiation. Increased SDH activity would therefore push the cells towards a Th1 phenotype whereas blocking it would favor iTreg cell differentiation.

Additional experiments would be required to test these hypotheses. It would be important to assess the TCA cycle metabolite levels in succinate-and malonate-treated conditions to evaluate its impact on TCA cycle metabolism and function. Also, it would be relevant to look at OCR levels in succinate-treated conditions to measure the impact of this treatment on OXPHOS. Does exogenous succinate significantly impact OXPHOS as observed upon malonate treatment? Moreover, it would be as well important to further evaluate the potential role of SDH in iTreg differentiation. For instance, it was demonstrated that oxaloacetate (another TCA cycle metabolite) is a potent inhibitor of SDH activity [START_REF] Gutman | The steady state activity of succinate dehydrogenase in the presence of opposing effectors.II. Reductive activation of succinate dehydrogenase in presence of oxaloacetate[END_REF][START_REF] Rutter | Succinate dehydrogenase -Assembly, regulation and role in human disease[END_REF]. Therefore, adding exogenous oxaloacetate to αKG-treated cells could be a complementary approach to evaluate the role of the mitochondrial complex II. Moreover, as described in (Bailis et al., 2019), we could use an SDH knockout mice model to further evaluate the role of this complex in iTreg differentiation. Finally, it would be essential to look at SDH enzymatic activity: first, to see if there are differences between Th1 and iTreg cells (as these two types of cells rely on distinct OXPHOS levels); secondly, to see if αKG is able to directly impact SDH activity (which could explain the increase in OXPHOS).

Finally, it would be as well essential to address SDH protein levels in both Th1, iTreg and iTreg αKG -treated cells.

Consequences of αKG treatment on epigenetic regulation

Notwithstanding the hypothesis discussed above, it is also important to take into account the important role of αKG in epigenetic regulation. Changes in the αKG/succinate ratio have been already demonstrated to have an impact in stem cell differentiation by epigenetic regulation, notably through TET proteins (Koivunen et al., 2007). As reviewed in the literature review of this thesis (section II 3 C a), TET proteins require αKG as a co-factor [START_REF] Kaelin | Influence of metabolism on epigenetics and disease[END_REF]. Furthermore, it is also known that succinate and fumarate are competitive inhibitors of αKG, which ultimately can block TET demethylation activity [START_REF] Vatrinet | The alpha-ketoglutarate dehydrogenase complex in cancer metabolic plasticity[END_REF].

Thus, another hypothesis is that modulation of the αKG/succinate ratio could impact on T cell differentiation through epigenetic mechanisms. It is known that FoxP3 and IFNγ can be epigenetically regulated [START_REF] Aune | Epigenetic Activation and Silencing of the Gene that Encodes IFN-gamma[END_REF][START_REF] Kitagawa | Transcriptional and Epigenetic Control of Regulatory T Cell Development[END_REF][START_REF] Peng | Aerobic glycolysis promotes T helper 1 cell differentiation through an epigenetic mechanism[END_REF][START_REF] Polansky | DNA methylation controls Foxp3 gene expression[END_REF][START_REF] Sekiya | Roles of transcription factors and epigenetic modifications in differentiation and maintenance of regulatory T cells[END_REF]. Moreover, several recent studies highlighted the role of TET activity in the regulation of T cell effector function and differentiation. It was demonstrated that TET2-mediated epigenetic modifications where important for the production of Th1

(IFNγ) and Th17 (IL-17) cytokines but not for Th2 differentiation [START_REF] Ichiyama | The methylcytosine dioxygenase Tet2 promotes DNA demethylation and activation of cytokine gene expression in T cells[END_REF].

Furthermore, TET1, TET2 and TET3 were shown to be important for FoxP3 stability trough epigenetic regulation of the CNS promoter [START_REF] Nair | DNA Demethylation of the Foxp3 Enhancer Is Maintained through Modulation of Ten-Eleven-Translocation and DNA Methyltransferases[END_REF][START_REF] Yue | Control of Foxp3 stability through modulation of TET activity[END_REF]. Though, based on the literature previously mentioned, we could expect to detect an increased FoxP3 stability in αKG-treated conditions, as αKG is directly related with TET proteins function. Nonetheless, and considering that we have a decreased percentage of FoxP3 expressing cells, we could hypothesize that, in our conditions, αKG is not promoting FoxP3 stability. However, it is important to take in consideration that 2HG levels are as well increased by 4 fold in iTreg αKG conditions (Chapter 3, Article III, Figure 6). As reviewed in the introduction (section II 3 C a),

IDH mutations or LDH/MDH activity in specific conditions result in the conversion of αKG into D-2HG and L-2HG respectively. Furthermore, increased levels of 2HG (both enantiomers) can inhibit demethylation by blocking TET and JmjC activity (Discussion, Figure 1) [START_REF] Chowdhury | The oncometabolite 2-hydroxyglutarate inhibits histone lysine demethylases[END_REF][START_REF] Lu | IDH mutation impairs histone demethylation and results in a block to cell differentiation[END_REF][START_REF] Xu | Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alphaketoglutarate-dependent dioxygenases[END_REF]. Indeed, a recent study done in Th17-polarizing conditions demonstrated that increased levels of 2HG leaded in hypermethylation of the FoxP3 gene, consequently inhibiting FoxP3 transcription and increasing IL-17 secretion (Xu et al., 2017). Furthermore, by blocking conversion of glutamate to αKG, they demonstrated that FoxP3 expression increased and IL-17 secretion diminished due a reduction of 2HG production [START_REF] Xu | Metabolic control of TH17 and induced Treg cell balance by an epigenetic mechanism[END_REF]. Thus, αKG and 2HG levels are important for the balance between Th17 and iTreg cells and are important for FoxP3 gene regulation. In our work, in iTreg-polarized conditions in the presence of αKG, we observed as well an increase of IL-17 secretion, which goes along with this cited work. However, and despite the similarities between our data, the potential mechanisms involved could be distinct: In their study, the regulation appears to be dependent on GOT1 transamination activity and, at least at mRNA level (our RNA-sequencing data), we did not detect any significant difference generated by αKG treatment for this enzyme (data not shown). Therefore, our data demonstrates that αKG treatment in iTreg conditions induce an increase of both αKG and 2HG intracellular levels (Discussion, Figure 1).

Both metabolites have a crucial role in TET proteins-mediated epigenetic regulation and several studies previously mentioned highlight and describe the role of TET protein specifically on FoxP3, IFNγ and IL-17 regulation (Discussion, Figure 1). Therefore, it would be interesting to address if TET activity is increased or decreased in αKG treated iTreg cells and check the methylation levels of FoxP3, IFNγ and IL-17.

Impact of cholesterol metabolism and polyunsaturated fatty acid in iTreg differentiation

During our investigation, and using the RNA-seq approach, we observed that one of the most impacted metabolic pathways in αKG-treated iTreg cells was the cholesterol biosynthesis pathway which was highly downregulated (Chapter 3, Article III, Figure 5A). In order to understand if this was directly impacting FoxP3 expression, we used two different strategies: one, using inhibitor drugs of the cholesterol biosynthesis pathway (for instance, lovastatin); another adding exogenous cholesterol (Chapter 3, Article III, Figure 5B). As a result, when cholesterol pathway was blocked, the percentage of FoxP3 + cells was maintained at equal levels as the control condition. Furthermore, when exogenous cholesterol was added in αKG treated conditions, we did not witness a rescue of the percentage of FoxP3 expressing cells (Chapter 3, Article III, Figure 5B). These results did not go in the direction that we were expecting. First of all, several studies reported that blocking cholesterol synthesis by statins treatment induces increase of FoxP3 expression and increase Treg cell numbers in mice [START_REF] Forero-Pena | Statins as modulators of regulatory T-cell biology[END_REF]. Second of all, it would be logical that, if cholesterol synthesis is downregulated and consequently intracellular cholesterol levels are possibly reduced, adding exogenous cholesterol could be possibly a way to rescue iTreg differentiation. Then, as this was not observed and based on the literature, we hypothesize that the downregulation of cholesterol biosynthesis related genes could be due to an increase of intracellular cholesterol content as it was already shown that high cholesterol intracellular levels block cholesterol biosynthesis [START_REF] Bietz | Cholesterol Metabolism in T Cells[END_REF][START_REF] Horton | SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver[END_REF][START_REF] Ye | Regulation of cholesterol and fatty acid synthesis[END_REF]. Furthermore, RNA-sequencing data also revealed that cholesterol efflux transporters ABCG1 and ABCA1 were downregulated, which could have as consequence an increase in intracellular cholesterol levels (data not shown). However, and despite the overall increased lipids levels in αKG -treated iTreg, the intracellular cholesterol levels were equal on both conditions (Chapter 3, Article III, Figure 5C) and we did not detect differences in cholesterol efflux (data not shown). Moreover, upregulation of ABCG1 and ABCA1 through LXR activation did not impact the percentage of FoxP3 expressing cells (data not shown). As a conclusion, we did not observe any evidences that the cholesterol biosynthesis pathway was directly involved in FoxP3 regulation. However, it is important to highlight that the levels of PUFAs were increased in αKG-treated iTregs (Chapter 3, Article III, Figure 5D). This is particularly interesting in this context as it was already shown that polyunsaturated fatty acids can inhibit SREBP1 function [START_REF] Hannah | Unsaturated fatty acids down-regulate srebp isoforms 1a and 1c by two mechanisms in HEK-293 cells[END_REF][START_REF] Takeuchi | Polyunsaturated fatty acids selectively suppress sterol regulatory element-binding protein-1 through proteolytic processing and autoloop regulatory circuit[END_REF][START_REF] Xu | Sterol regulatory element binding protein-1 expression is suppressed by dietary polyunsaturated fatty acids. A mechanism for the coordinate suppression of lipogenic genes by polyunsaturated fats[END_REF][START_REF] Xu | Polyunsaturated fatty acids suppress hepatic sterol regulatory element-binding protein-1 expression by accelerating transcript decay[END_REF] and, therefore, negatively impact cholesterol biosynthesis. Thus, downregulation of cholesterol synthesis observed by RNA-seq analysis could be directly linked with the increased PUFAs intracellular levels in αKG treated conditions (Discussion, Figure 1). Moreover, it is important to take in consideration the potential role of PUFAs on T cell membrane. So far, it has been described that treatment of human T cells with PUFAs diminished TCR/CD3-induced calcium response and proliferation [START_REF] Rossetti | Oral administration of unsaturated fatty acids: effects on human peripheral blood T lymphocyte proliferation[END_REF][START_REF] Stulnig | Polyunsaturated fatty acids inhibit T cell signal transduction by modification of detergent-insoluble membrane domains[END_REF][START_REF] Zeyda | LAT displacement from lipid rafts as a molecular mechanism for the inhibition of T cell signaling by polyunsaturated fatty acids[END_REF][START_REF] Zurier | Human peripheral blood T lymphocyte proliferation after activation of the T cell receptor: effects of unsaturated fatty acids[END_REF]. This is particularly interesting in this context, as several studies reported a role of TCR signaling in the regulation of Th and Treg cell differentiation [START_REF] Li | T cell receptor signalling in the control of regulatory T cell differentiation and function[END_REF][START_REF] Van Panhuys | TCR Signal Strength Alters T-DC Activation and Interaction Times and Directs the Outcome of Differentiation[END_REF]. The role of TCR signaling in tTreg cell differentiation is well known [START_REF] Li | T cell receptor signalling in the control of regulatory T cell differentiation and function[END_REF] (discussed in section I). The role of TCR signaling in iTreg differentiation was as well described in several studies: while IKK and calcium signaling promotes iTreg cell differentiation [START_REF] Long | Nuclear factor-kappaB modulates regulatory T cell development by directly regulating expression of Foxp3 transcription factor[END_REF][START_REF] Ruan | Development of Foxp3(+) regulatory t cells is driven by the c-Rel enhanceosome[END_REF][START_REF] Vaeth | Dependence on nuclear factor of activated T-cells (NFAT) levels discriminates conventional T cells from Foxp3+ regulatory T cells[END_REF], strong AKT activation negatively impacts FoxP3 expression [START_REF] Haxhinasto | The AKT-mTOR axis regulates de novo differentiation of CD4+Foxp3+ cells[END_REF][START_REF] Sauer | T cell receptor signaling controls Foxp3 expression via PI3K, Akt, and mTOR[END_REF]. These results are not surprising because, as discussed in the introduction of this manuscript, AKT activation is crucial for mTOR (energy sensor pathway) function (Figure 18)

and balanced mTOR activity (Figure 24) is required to maintained Treg stability and function.

Therefore, it would be interesting to evaluate the potential role of polyunsaturated fatty acids in membrane structure and TCR signaling and consequently in T cell differentiation (treated or not by αKG) (Discussion, Figure 1).

Translation from the lab to a clinical application

To assess whether αKG effects were potentially translatable to the clinic, we assessed as well the impact of exogenous αKG in human iTreg conditions. Interestingly, we observed, as in murine Treg cells, that FoxP3 levels decreased upon αKG treatment (Chapter 3, Article III, Supplemental Figure 5). However, in the same conditions we did not observe an increase in IFNγ secretion. These results suggest that even if FoxP3 regulation by αKG seems to be similar between species, IFNγ gene regulation might be different. It is important to note that an increase of other inflammatory cytokines such as TNF-α and GM-CSF was detected in αKGtreated human iTreg cells as well as an increase of granzyme B secretion (data not shown).

Therefore, it would be interesting to evaluate the effector function of αKG-treated human iTreg cells in a humanized mice model in order to study their potential anti-tumor function and to compare with the results already obtained in our murine model. Moreover, it would be interesting to study whether malonate treatment is able to restore FoxP3 expression in human iTreg cells generated in presence of αKG and assess if αKG treatment has the same in IDH1 and IDH2 mutant cells can be rescued by the addition of exogenous αKG [START_REF] Xu | Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alphaketoglutarate-dependent dioxygenases[END_REF]. αKG has also been studied as treatment for certain cancers, principally in hypoxic conditions. Indeed, in pre-clinical models, αKG was able to restrict angiogenesis and to reduce expression of VEGF, resulting in tumor regression [START_REF] Matsumoto | Antitumor effects of 2-oxoglutarate through inhibition of angiogenesis in a murine tumor model[END_REF]. In another elegant study it was proved that αKG role in epigenetic modulation of tumor cells was important to facilitate anti-tumor treatments [START_REF] Pan | Regional glutamine deficiency in tumours promotes dedifferentiation through inhibition of histone demethylation[END_REF]. Hence, these studies demonstrate that the use of αKG in a clinical context is possible and associated with high antitumor efficiency.

During my thesis I also demonstrated that GLUT1 and potentially CAT-1 surface expression could be used to select T cells with different phenotypes, proliferation capacity and effector functions. These studies have been performed in human T cells opening therefore a direct path towards a translational application. However, these experiments were performed in non-engineered T cells from healthy donors. As a first step (and already on going for GLUT1)

it is important to assess whether CAR T cells can be selected based on the nutrient transporter surface expression. Furthermore, we will then evaluate their anti-tumor function in a tumor-

Conclusion

For the last years, anti-tumor immunotherapies, notably CAR T cells, have been advancing at a rapid rate. However, there are still many challenges to overcome in order to make CAR T cell therapy efficient not only in blood malignancies, but also in solid tumors. During my thesis I demonstrated that we can target T cell metabolism to modulate T cell effector function. Preselecting CAR T cells based on their nutrient transporters surface expression and "priming" CAR T cell differentiation and function in vitro under certain metabolic conditions could be interesting approaches to overcome the metabolic environment found in the tumor tissue.

Moreover, we demonstrated that metabolic changes imposed in vitro can be maintained in vivo, therefore showing that the T cell metabolism modulation could be a potential strategy to adopt in clinical trials. Altogether, we consider that T cell metabolism modulation can be used as tool to improve CAR T cells anti-tumor function and overcome the low successful rate in solid tumor treatment.

RésuméL

  'activation des cellules T est initiée suite à la rencontre avec un antigène spécifique. Les études réalisées pour mieux comprendre ce processus d'activation se sont principalement focalisées sur le rôle des cellules présentatrices d'antigènes et des cytokines. Toutefois, des données récentes soulignent également l'importance du microenvironnement métabolique pour soutenir l'augmentation des besoins énergétiques et biosynthétiques liés à la stimulation antigénique. Cette reprogrammation métabolique est conditionnée par la disponibilité en nutriments et la teneur en oxygène qui peuvent être altérés en conditions pathologiques, comme dans des tumeurs. En effet, plusieurs groupes dont le nôtre ont montré qu'en cas de faible disponibilité en nutriments, une compétition peut se créer entre les cellules tumorales et les cellules T, impactant de ce fait négativement leurs fonctions antitumorales. Cet effet est dû, du moins en partie, aux profils métaboliques distincts des souspopulations de cellules T ; alors que les cellules T effectrices (dont les cellules Th1) sont fortement glycolytiques, les cellules T régulatrices suppressives (Treg) présentent un métabolisme plus mixte avec des niveaux accrus d'oxydation lipidique. Il est donc important de déterminer comment les changements métaboliques des cellules T anti-tumorales affectent leur persistance et leur fonctionnalité. Ainsi, j'ai entrepris des travaux afin d'évaluer si le niveau d'expression du transporteur de glucose GLUT1 permettait d'identifier et de sélectionner des cellules T ayant des fonctions effectrices distinctes. Nous avons confirmé cette hypothèse et notamment montré que les cellules T exprimant un niveau élevé de GLUT1 possèdent un potentiel de sécrétion d'IFNγ accru.

Figure 1 -

 1 Figure 1 -αβT cell selection mechanisms in the thymus .................................................................... Table 1 -Naïve T cell surface markers in both mouse and human species ........................................

Figure 2 -

 2 Figure 2 -Comparison of the maintenance of the naïve T cell pool in aging mice and humans .......

Figure 3 -

 3 Figure 3 -TCR signaling cascade upon antigen presentation .............................................................

Figure 4 -

 4 Figure 4 -IL-2 receptor affinity and STAT5 activation ........................................................................

Figure 5 -

 5 Figure 5 -Polarization of CD4 + naïve T cells towards distinct subsets ................................................

Figure 6 -

 6 Figure 6-IL-12 and IFNγ signaling pathways during Th1 ....................................................................

Figure 7 -

 7 Figure 7 -Scheme of non-coding regions, signals and transcription factors involved in FoxP3 induction and stabilization ..................................................................................................................................

Figure 8 -

 8 Figure 8 -Treg-mediated suppression mechanisms/pathways .........................................................

Figure 9 -

 9 Figure 9 -Cytotoxic T cell differentiation and phenotype .................................................................

Figure 10 -

 10 Figure 10 -Two models proposed for T cell differentiation ............................................................... Table 2 -TCM and TEM surface markers in both mouse and human species ........................................

Figure 11 -

 11 Figure 11 -Glycolysis and the pentose phosphate pathway (PPP) .....................................................

Figure 12 -

 12 Figure 12 -The tricarboxylic acid (TCA) cycle and its connection with the electron transport chain and OXPHOS ...............................................................................................................................................

Figure 13 -

 13 Figure 13 -Fatty acid synthesis ..........................................................................................................

Figure 14 -

 14 Figure 14 -The Mevalonate pathway ................................................................................................

Figure 15 -

 15 Figure 15 -Intracellular Cholesterol levels homeostasis ...................................................................

Figure 16 -

 16 Figure 16 -Glutaminolysis ..................................................................................................................

Figure 17 -

 17 Figure 17 -Arginine metabolism ........................................................................................................

Figure 18 -

 18 Figure 18 -mTOR complexes and its targets ......................................................................................

Figure 19 -

 19 Figure 19 -The AMPK pathway ..........................................................................................................

Figure 20 -

 20 Figure 20 -Role of mTOR activation in metabolic reprogramming ...................................................

Figure 21 -

 21 Figure 21-Metabolic reprogramming of T cell upon TCR activation ..................................................

Figure 22 -

 22 Figure 22 -Epigenetic regulation mediated by TCA cycle metabolites ..............................................

Figure 23 -

 23 Figure 23-Metabolic signatures of TEFF (Th1/Th2/Th17) and Treg cells ............................................

Figure 24 -

 24 Figure 24-mTOR signaling function in T cell differentiation ..............................................................

Figure 25 -

 25 Figure 25 -The tumor microenvironment ..........................................................................................

Figure 26 -

 26 Figure 26 -The four generations of CAR T cell constructs ..................................................................

Figure 1 -

 1 Figure 1 -Upregulation of CAT-1 surface expression upon TCR stimulation ....................................

Figure 2 -

 2 Figure 2 -Selection of TCR-stimulated human T cells on the basis of CAT-1 surface expression .....

Figure 3 -

 3 Figure 3 -CAT-1 is highly upregulated on CD8 T cells and is associated with an increased proliferation of CD8 as compared to CD4 T cells ...............................................................................

Figure 4 -

 4 Figure 4 -CD45RA and CD45RO expression on CAT-1 Low and CAT-1 High sorted cells .........................

Figure 5 -

 5 Figure 5 -High CAT-1 expression is associated with high IL-17 and IFN-γ expression in the CD4 T cell subset .................................................................................................................................................

Figure 1 -

 1 Figure 1 -Arginine deprivation inhibits T cell activation and proliferation ......................................

Figure 2 -

 2 Figure 2 -T cell phenotype is not significantly altered under conditions of arginine deprivation .

Figure 3 -

 3 Figure 3 -Downregulation of CAT-1 expression by lentiviral-mediated shRNA based approach inhibits T cell proliferation following restimulation...........................................................................

Figure 4 -

 4 Figure 4 -Arginine-based generation of polyamines is required for optimal T cell activation and proliferation .......................................................................................................................................

Figure 1 -

 1 Figure 1 -Exogenous aKG augments Th1 polarization and inhibits the polarization potential of naïve CD4 T cells towards a Treg fate .........................................................................................................

Figure 2 -

 2 Figure 2 -aKG induces an inflammatory profile in Treg-polarized CD4 T cells...............................

Figure 3 -

 3 Figure 3 -ErbB2-CAR + T cells polarized ex vivo in the presence of aKG maintain an in vivo inflammatory profile following adoptive transfer into tumor-bearing mice ...........................................................

Figure 4 -

 4 Figure 4 -Genes affecting membrane-related processes are strongly impacted by aKG in Treg polarizing conditions .........................................................................................................................

Figure 5 -

 5 Figure 5 -Lipid saturation and membrane order is altered by aKG under Treg polarization conditions ............................................................................................................................................................

Figure 6 -DiscussionFigure 1 -

 61 Figure 6 -Treg differentiation is enhanced by blocking the aKG-induced augmentation in oxidative phosphorylation ................................................................................................................................ Supplemental Figure 1-Treg polarization is attenuated by aKG following TCR stimulation .......... Supplemental Figure 2-ErbB2-CAR T cells exhibit an attenuated Treg polarization in the presence of aKG ................................................................................................................................................... Supplemental Figure 3-Abca1 and Abcg1 levels are decreased by aKG treatment in Treg-polarizing conditions..........................................................................................................................................

Figure 1 -

 1 Figure 1 -αβT cell selection mechanisms in the thymus.DN thymocytes arrive to the cortex and give rise to DP cells. DP cells are positively selected by cTEC cells and differentiate ultimately in SP CD4 or CD8 that migrate to the medulla. In the medulla, mTEC cells and DC present TRA antigens through AIRE and Fezf2 regulation. TRA presentation allows the negative selection of autoreactive T cell cells through apoptosis. AIRE (Autoimmune regulator), DN (double negative), DP (double positive), Fezf2 (Fez family zinc finger protein 2), SP (single positive) TRA (tissue-resident antigens). From[START_REF] Takaba | The Mechanisms of T Cell Selection in the Thymus[END_REF]

  3 different signals are necessary for an efficient T cell activation: TCR signaling cascade, co-stimulation and cytokine signaling. All these mechanisms are described in detail in the following paragraphs.

Figure 2 -

 2 Figure 2 -Comparison of the maintenance of the naïve T cell pool in aging mice and humans.

  . MHC II molecules, unlike MHC I, generally present peptides from extracellular sources upon phagocytosis of the antigen. b) TCR signaling cascade -Signal 1 Upon TCR recognition of a cognate peptide (presented by a MHC molecule), a signaling cascade is induced, leading to T cell activation, proliferation, differentiation and effector function. CD4 and CD8 co-receptors help assisting antigen recognition through a close association with a kinase named lymphocyte cell-specific protein-tyrosine kinase (LCK). Upon activation, an immunologic synapse is formed at the site of interaction between the peptide-MHC complex (pMHC) and the TCR ab chains associated with CD3 γε, CD3 δε and CD3 ζζ dimers that contain immunoreceptor tyrosine-based activation motifs (ITAMs) in their individual cytoplasmic segments. One of the three ITAM domains present on the CD3 ζζ pairs is phosphorylated upon TCR activation by LCK proteins, inducing the recruitment and activation of ZAP-70 (Zeta-chain-associated protein kinase 70) that phosphorylates then another molecule named linker for activation of T cells (LAT) allowing signal diversification and amplification (Malissen and Bongrand, 2015). This intracellular cascade is the first signal required to induce T cell activation and is known as "signal 1" and is represented in Figure 3. c) Co-stimulation signaling -Signal 2

Figure 3 -

 3 Figure 3 -TCR signaling cascade upon antigen presentation Upon TCR-pMHC pair, single CD3γε, CD3 δε and CD3 ζζ pairs associate with TCRαβ heterodimer. The ITAM (white dots) are then phosphorylated (red dots) by LCK which induces the recruitment and activation of ZAP-70. ZAP-70 in its turn phosphorylates LAT adaptor, which allows signal diversification and amplification. ITAM (immunoreceptor tyrosine-based activation motifs), LAT (linker for activation of T cells), pMHC (peptide-MHC), ZAP-70 (Zeta-chainassociated protein kinase 70). Adapted from (Malissen and Bongrand, 2015).

Figure 4 -

 4 Figure 4 -IL-2 receptor affinity and STAT5 activation.

Figure 5 -

 5 Figure 5 -Polarization of CD4 + naïve T cells towards distinct subsets Upon encounter with their cognate antigen, naïve T cells differentiate into distinct T helper subsets depending on the cytokine environment and the nature of the antigen. The different subsets are characterized based on their cytokine profile and the master transcription factors expressed. AHR (aryl hydrocarbon receptor), BCL6 (B-cell lymphoma 6), FoxP3 (Forkhead box P3), GATA3 (GATA Binding Protein 3), IL (interleukin), IRF4 (Interferon regulatory factor 4), IFN (Interferon), RORγT (retinoic acid receptor-related orphan nuclear receptor gamma), TGF-β (transforming growth factorb), T-bet (T-box expressed in T cells).

Figure 6 -

 6 Figure 6-IL-12 and IFNγ signaling pathways during Th1 IL-12 induces STAT4 activation which will then induce IFNγ secretion and T-bet transcription. T-bet once expressed induces Th1 cell-specific genes and contributes to the repression of the Th2 program. IFNγ and T-bet work synergistically. T-bet induces IFNγ secretion while IFNγ activates STAT1 which together with STAT4, induces and maintains T-bet expression[START_REF] Zhu | The transcription factor T-bet is induced by multiple pathways and prevents an endogenous Th2 cell program during Th1 cell responses[END_REF]

Figure 7 -

 7 Figure 7 -Scheme of non-coding regions, signals and transcription factors involved in FoxP3 induction and stabilization.

Figure 8 -

 8 Figure 8 -Treg-mediated suppression mechanisms/pathways. Treg cells can suppress TEFF cells through different mechanisms: 1) inhibition of DCs through cytotoxic T-lymphocyte-associated protein 4 (CTLA-4); 2) metabolic disruption due to adenosine production; 3) through inhibitory cytokine secretion such as IL-10, IL-35 and TGF-β; 4) competing with TEFF cells for IL-2; 5) cytolysis due to GzmB and perforin secretion. Ad (adenosine), A2AR (adenosine A2A receptor), CTLA-4 (cytotoxic T-lymphocyte-associated protein), DC (dendritic cell), GzmB (granzyme B) IL (interleukin), IDO (indoleamine 2,3-dioxygenase), STAT5 (signal transducers and activators of transcription 5), Treg (T regulatory), Teff (T effector).

Figure 9 -

 9 Figure 9 -Cytotoxic T cell differentiation and phenotype. The phenotype of CTL (TF and surface cell markers) as well as the mechanisms involved in CTL differentiation are represented. IRF4 (interferon regulatory factor 4), Id2 (DNA binding 2), T-bet (T box transcription factor), XCR1 (X-C motif chemokine receptor 1), XCL1 (X-C motif chemokine ligand 1).

Figure 10 -

 10 Figure 10 -Two models proposed for T cell differentiation.

  mitochondria and is closely associated with the electron transporter chain (ETC). The TCA cycle can be fed from different metabolites generated in distinct metabolic pathways through: (I) acetyl-CoA produced either from: (I) pyruvate catabolism by the pyruvate dehydrogenase (PDH) or from fatty acid oxidation (FAO); (II) α-ketoglutarate (αKG) that is an end product of the glutaminolysis pathway (discussed on section II 4). From the TCA cycle

Figure 11 -

 11 Figure 11 -Glycolysis and the pentose phosphate pathway (PPP)

Figure 12 -

 12 Figure 12 -The tricarboxylic acid (TCA) cycle and its connection with the electron transport chain and OXPHOSPyruvate is converted into Acetyl-CoA by PDH and enters in the TCA cycle. Once in the TCA cycle, a cascade of metabolic reactions occurs with the generation of several metabolites. From this cycle results the formation of NADH and FADH2 which are proton (H + ) donors crucial for CI and CII activity of the electron transport chain and initiation of the OXPHOS pathway. While H + are pumped out to the IMS space and create a transmembrane proton electrochemical gradient, electrons are transported from the CI and CII to the CIII and CIV until they reach the terminal electron acceptor (O2). This process ends up with the entry of the H + pumped out from the first 4 complexes through the CV which generates ATP. αKGDH (α-Ketoglutarate dehydrogenase), CS (citrate synthase), CI (complex I), CII (complex II), CIII (complex III), CIV (complex IV), CV (complex V), FH (fumarate hydratase), FADH2 (reduced flavin adenine dinucleotide), IDH (isocitrate hydrogenase), NADH (reduced nicotinamide adenine dinucleotide), MDH (malate dehydrogenase), PDH (pyruvate dydrogenase), SDH (succinate dehydrogenase), SCS (succinyl-CoA synthetase), TCA (tricarboxylic acid). Adapted from:[START_REF] Osellame | Cellular and molecular mechanisms of mitochondrial function[END_REF]

  pathway. Acetyl-CoA is one of the essential precursors that is metabolized into acetoacetyl-CoA by the thiolases. After, this acetoacetyl-CoA molecule in combination with another Acetyl-CoA molecule is converted in hydroxymethylglutaryl-coenzyme A (HMC-CoA) by the hydroxymethylglutaryl-coenzyme A synthase (HGMCS). Then, HMC-CoA is reduced by the hydroxymethylglutaryl-coenzyme A reductase (HGMCR) and mevalonate is generated. After, through a multistep enzymatic reaction, several intermediates are produced such as squalene and lanosterol until the end product: cholesterol (Figure14). Cholesterol is transported as a lipoprotein either in the form of HDL (high-density lipoprotein) or LDL (low-density lipoprotein)[START_REF] Bietz | Cholesterol Metabolism in T Cells[END_REF] and its influx and efflux are regulated by several transporters: cholesterol enters in the cells through CD36 and/or through the LDL receptor and exit the cell through ATP binding cassette (ABC) A1 and ABCG1 (Figure15).

Figure 13 -

 13 Figure 13 -Fatty acid synthesis.

Figure 14 -

 14 Figure 14 -The Mevalonate pathway.

Figure 16 -

 16 Figure 16 -GlutaminolysisGlutamine is converted into glutamate via actions of glutaminases. Glutamate is then converted to αKG, which enters and fuels OXPHOS through the TCA cycle. αKG (αketoglutarate), GLS (glutaminase), GDH (glutamate dehydrogenase), TCA (tricarboxylic acid).

Figure 17 -

 17 Figure 17 -Arginine metabolism Arginine can be converted into two major metabolites: Ornithine through the action of ARG and Citrulline by NOS. From ARG enzymatic activity, it results the production of Urea and from NOS action, NO generation. Ornithine can be metabolized into polyamines by ODC while Citrulline can give rise to fumarate creating a link with the TCA cycle. ADC (arginine decarboxylase), AGAT (arginine: glycine amidinotransferase), ARG (arginase), ASL (argininosuccinate lyase), OAT (ornithine aminotransferase), ODC (ornithine decarboxylase), OTC (Ornithine transcarbamylase), NO (nitric oxide), NOS (nitric oxide synthase), P5C (pyrroline-5-carboxylate), TCA (tricarboxylic acid).

Figure 18 -

 18 Figure 18 -mTOR complexes and its targets.

Figure 19 -

 19 Figure 19 -The AMPK pathwayAMPKα can be activated by phosphorylation on Thr172 by LKB1 kinase. LKB1 promotes AMPK phosphorylation under high AMP: ATP ratio. High AMP levels also induce allosteric activation of the phosphorylated enzyme. One biological outcome of AMPK activity is the inhibition of mRNA translation under low-energy conditions through inhibition of mTORC1 activity. AMPK (AMP-activated protein kinase), AMPK-P (AMPK phosphorylated) AMP (Adenosine monophosphate), ATP (Adenosine triphosphate), mTOR (mechanistic target of rapamycin).

Figure 20 -

 20 Figure 20 -Role of mTOR activation in metabolic reprogramming.

Figure 21 -

 21 Figure 21-Metabolic reprogramming of T cell upon TCR activation

Figure 22 -

 22 Figure 22 -Epigenetic regulation mediated by TCA cycle metabolitesDemethylation can be mediated by TET enzymes and KDM which require αKG, O2 and Fe as co-factors. High levels of succinate, fumarate and 2HG inhibit TET and KDM demethylation activity. Acetylation is mediated by HAT which requires the utilization of the acetyl group from the acetyl-CoA. Acetyl-CoA can derive from nuclear/cytosolic citrate and pyruvate, which are the substrates for ACL and PDH, respectively. HDAC can generate acetate as a product that can be used by ACSS2 to regenerate acetyl-CoA. 2HG (2-hydroxyglutarate), αKG (Alpha-Ketoglutarate), ACL (acetyl-CoA-generating enzymes), ACSS2 (Acyl-CoA Synthetase Short Chain Family Member 2), HAT (Histone acetyltransferases), HDAC (histone deacetylase), KDM (Lysine demethylases), PDH (Pyruvate dehydrogenase), TET (ten-eleven translocation hydroxylases). Adapted from:[START_REF] Intlekofer | Metabolic signatures of cancer cells and stem cells[END_REF]

Figure 23 -

 23 Figure 23-Metabolic signatures of TEFF (Th1/Th2/Th17) and Treg cells

Figure 24 -

 24 Figure 24-mTOR signaling function in T cell differentiation mTORC1 and mTORC2 play a role in T cell differentiation.In this figure it is detailed the role of mTOR complexes in Th/Treg cell differentiation. mTOR (mechanistic target of rapamycin), mTORC (mTOR complex). Adapted from:[START_REF] Zeng | mTOR signaling in the differentiation and function of regulatory and effector T cells[END_REF]

Figure 25 -

 25 Figure 25 -The tumor microenvironment Tumor cells consume high levels of glucose, amino acids and fatty acids resulting in a deprived environment in nutrients crucial for T cell anti-tumor function. As a consequence of high glycolytic tumor activity, tumor cells secrete high levels of lactate, which is a toxic for T cells. Despite that, tumor cells are able to use lactate as an energy source exporting it by the MCT1. In the TME, other immune cells are present, favored by the surrounding environment and able to impact negatively T cell antitumor function. TAM and MDSC metabolic activity deprive the TME from arginine (through the action of Agr1) while DCs are well known for their capacity to deplete the TME in tryptophan through the activity of IDO. Furthermore, Tregs present in the TME downregulate T cell effector function. Finally, PD-1 expression by T cells, as a result of cell exhaustion, results in the downregulation of T cell antitumor function through the binding with PD-L1 present on the tumor cells surface. Hypoxia levels in the tumor site are also a negative factor in the TME which impact T cell function.Arg1 (arginase 1), DC (dendritic cell), EAA (essential amino acids), IDO (indoleamine 2,3-dioxygenase), MDSC (myeloid derived suppressor cells), MCT1 (monocarboxylate transporter 1), PD1 (programmed cell death-1), PD-L1 (PD ligand 1), TAM (tumor-associated macrophages), TME (tumor microenvironment), Treg (T regulatory T cells). From:[START_REF] Buck | Metabolic Instruction of Immunity[END_REF]

Figure 26 -

 26 Figure 26 -The four generations of CAR T cell constructs.All CAR generations contains a scFv domain derived from a monoclonal antibody. This extracellular part is specific to a desired tumor-antigen and does not require MHC presentation. The different CAR T cell generations are characterized by different cytoplasmic tails. The first generation only contains a CD3ζ domain in its cytoplasmic tail, while the second generation contains two domains: a CD3ζ and co-stimulatory domain (here represented by CD28 or 4-1BB). The third generation, as the other generations, contains three cytoplasmic domains being two of them two different co-stimulatory molecules. Structurally, the fourth generation (TRUCK) is similar to the third generation, with the capacity to induce the secretion of pro-inflammatory cytokines. From:[START_REF] Miliotou | CAR T-cell Therapy: A New Era in Cancer Immunotherapy[END_REF]

4 -

 4 1BB and OX40 can bring distinct advantages to potentiate the function of CAR T cells. As a result, the third CAR generation was initiated by combining two different co-stimulatory domains. In this regard, an elegant study compared CD28-ζ, OX40-ζ and CD28-OX40-ζ CAR

Figure 1 -

 1 Figure 1 -Upregulation of CAT-1 surface expression upon TCR stimulation Purified human CD3 + T cells were TCR-activated with anti-CD3/CD28 mAbs. At day 2 and 4 post stimulation, T cells were stained for GLUT1, CAT-1 as well as the activation markers CD25, CD69 and CD71. Data are representative of 2 independent experiments.

Figure 2 -

 2 Figure 2 -Selection of TCR-stimulated human T cells on the basis of CAT-1 surface expressionPurified human CD3 + T cells were TCR-activated with anti-CD3/CD28 mAbs. Two days post-stimulation, T cells were stained for CAT-1 expression and cells with the lowest and highest levels of surface CAT-1 (appr. 15%) were sorted on a FACSAria cell sorter as shown and are hereby designated as CAT-1 Low and CAT-1 High , respectively. The forward (FSC) and side (SSC) scatter profiles of the sorted CAT-1 Low and CAT-1 High subsets are presented. Data are representative of 4 independent experiments.

Figure 3 -

 3 Figure 3-CAT-1 is highly upregulated on CD8 T cells and is associated with an increased proliferation of CD8 as compared to CD4 T cells. (A) Purified human CD3 + T cells were VPD450-labeled and TCR-activated using anti CD3/CD28 mAbs and FACS-sorted on the basis of CAT-1 expression as described in Figure 1. The repartition of CD4 and CD8 T cells within each subset was assessed immediately after sorting (day 2) and at day 8 post-TCR activation and representative dot plots of 2 independent experiments are shown. (B) The proliferation of sorted CAT-1 Low and CAT-1 High CD4 and CD8 subsets, as well as control total sorted T cells (CAT-1 Total ) were monitored at day 7 post-stimulation as a function of VPD450 fluorescence and representative histograms

Figure 4 -

 4 Figure 4 -CD45RA and CD45RO expression on CAT-1 Low and CAT-1 High sorted cells Purified human CD3 + T cells were TCR-activated, sorted on the basis of CAT-1 expression at day 2 as indicated and then cultured ex vivo in the presence of IL-2. The CD45RA/CD45RO phenotype of CD4 + and CD8 + T cells is shown at days 2 and 8 and the percentages of cells in each gate are presented. Representative plots from 1 of 2 independent experiments are shown.

Figure 5 -

 5 Figure 5 -High CAT-1 expression is associated with high IL-17 and IFN-γ expression in the CD4 T cell subset.

of

  Helsinki and IRB approval to the French Blood Bank (Etablissement Francais du Sang). T lymphocytes were purified by negative-selection using Rosette tetramers (StemCell Technologies) and the purity was monitored by flow cytometry. Lymphocytes were cultured in RPMI supplemented with 10% FCS and 1% penicillin/streptomycin (Gibco-Life technologies). T cell activation was performed using plate-bound anti-CD3 (clone OKT3, Biolegend) and anti-CD28 (clone 9.3, kindly provided by Carl June) mAbs at a concentration of 1 μg/ml. rIL-2 (100 U/ml) was added every other day starting either at day 2 or day 3 postactivation. Cells were maintained in a standard tissue culture incubator containing atmospheric (20%) O2 and 5% CO2. Flow cytometry analyses. Immunophenotyping of cells was performed using fluorochromeconjugated mAbs (BD Bioscience, Beckman Coulter or eBioscience) against CD4, CD8, CD45RA, CD45RO, CCR7 and CD62L and cell activation monitored using fluorochromeconjugated mAbs BD Bioscience, Beckman Coulter or eBioscience) against CD25, CD69 and CD71. Proliferation was monitored by labeling cells with VPD450 (BD Biosciences; 1 μM) for 3

Figure 1 -

 1 Figure 1-Arginine deprivation inhibits T cell activation and proliferation

Figure 2 -

 2 Figure 2-T cell phenotype is not significantly altered under conditions of arginine deprivation (A) The repartition of CD4 and CD8 T cells was assessed at day 4 post-TCR activation in nutrient-replete (Nutr+) and arginine-deprived (-Arg) conditions by flow cytometry and representative dot plots are shown (1 of 5 independent experiments). (B) The CD45RA/CD45RO phenotype of CD4 + and CD8 + T cells is shown at day 4 and the percentages of cells in each gate are presented. Representative plots from 1 of 5 independent experiments are shown. (C) Production of IL-17, IL-2, and IFNγ was assessed in the T cells activated in the presence or absence of arginine at day 4 of TCR engagement following restimulation with PMA/ionomycin in the presence of Brefeldin A for 4h. Cytokine production was monitored by intracellular staining with the indicated fluorochrome-conjugated antibodies and representative plots are shown (left). Quantification of means ± SEM of 5 independent experiments are presented as historgrams; ns=non-significant.

Figure 3 -

 3 Figure 3-Downregulation of CAT-1 expression by lentiviral-mediated shRNA based approach inhibits T cell proliferation following restimulation (A) Purified human CD3+ T cells were activated with anti-CD3/CD28 mAbs and simultaneously transduced with a lentiviral-based vector harboring a scrambled (CTL) or CAT-1-specific shRNA and encoding GFP as a marker protein. Transduction efficiency was monitored as a function of GFP expression at day 3 and means ± SEM of 3 independent experiments are presented (left panel). Surface CAT-1 expression was monitored in non-transduced (GFP-/sh-, grey histograms) as compared to transduced (GFP+/sh+, green histograms) CD4+ and CD8+ T cells and representative histograms with indicated mean fluorescence intensities (MFI) are presented (middle panels). Quantification of MFI in non-transduced and transduced CD4 and CD8 T cell subsets are presented as means ± SEM of 3 independent experiments (right panels). *NS=non-significant; *, p<0.05; **, p<0.01; ***, P<0.001. (B) The repartition of CD4 and CD8 T cells within non-transduced (sh-) and transduced T cell subsets was assessed at day 3 post-TCR activation and representative dot plots with the indicated percentages are shown (left panels). Quantification of CD4/CD8 subsets in 3 independent experiments are shown as means ± SEM (right). (C) Induction of the CD25 and CD71 activation markers was monitored in non-transduced (sh-) and transduced (sh+) CD4 and CD8 subsets at day 3 of activation and representative histograms with the corresponding MFIs are shown (left). Proliferation was monitored by VPD450 fluorescence dilution and day 3 profiles of sh-and sh+ subsets are overlaid in representative histograms in 1 of 3 independent experiments. (D) Production of IL-17, IL-2, and IFNγ was assessed in shand sh+ CD4 and CD8 T cell subsets at day 5 by intracellular staining following restimulation with PMA/ionomycin in the presence of Brefeldin A for 4h. Representative plots are shown (left) and means ± SEM of 3 independent experiments are presented (right). (E) The percentages of T cells transduced with shCTL and shCAT-1 vectors were followed over time (day 6 to 16) as a function of GFP fluorescence and normalized to "1" (representing 40-60% transduction at day 3). (F) Cell division of non-transduced (sh-) and transduced (sh+) T cells was evaluated following CD3/CD28 restimulation of T cells at day 14. Representative proliferation profiles are shown as a function of VPD450 fluorescence and the mean percentages ± SEM of undivided cells (P0) and cells that divided twice (P2) within the sh-and sh+ subsets are presented.

Figure 4 .

 4 Figure 4.-Arginine-based generation of polyamines is required for optimal T cell activation and proliferation

  PsPax2, encoding Gag, Pol, Rev and tat, the VSV-G pseudotyping envelope, pCMV-VSV-G and the HIV-1 derived shRNA-encoding vectors (pLKO.1, ShRNA mission, Sh-CAT-1 ref# TRCN0000042967 and Sh-scramble ref# shC002 (non mammalian sh-scr)). Viral supernatant was harvested 48 hours post-transfection, and concentrated by centrifugation (3000 RPM O/N, 4°C). Titers were assessed on Jurkat cells to determine transducing units (TU/ml) and transduction was determined as the percentage of GFP + cells by flow cytometry.

αKG

  in controlling T cell differentiation and the data resulting from these studies are presented in this section. Briefly, these data have revealed a critical role of αKG, positively regulating IFNγ effector function in CD4 + T cells activated under Th1-polarizing conditions. Interestingly, αKG markedly upregulated IFNγ secretion in naive T cells activated under Treg polarizing conditions and inhibited the induction of FoxP3. Our work unrevealed a new role of αKG on Th1 and iTreg differentiation. The balance between Th1 and Treg differentiation is regulated by a-ketoglutarate-mediated alterations in TCA cycle flux mediated attenuation of FoxP3 transcription resulted in the differentiation of CD4 T cells with an enhanced inflammatory profile. Under these conditions, aKG promoted the effector activity of chimeric antigen receptor (CAR)-engineered T cells against the ErbB2 tumor antigen in tumor-bearing mice, increasing IFNg secretion by >10-fold under conditions of Treg polarization. Mechanistically, aKG altered the transcription of genes in the cholesterol biosynthesis pathway and significantly increased membrane concentrations of polyunsaturated fatty acid species. Furthermore, an aKG-mediated augmentation in TCA cycle metabolism and downstream oxidative phosphorylation was identified as a critical component of CD4 T cell differentiation. Inhibition of succinate oxidation and decreasing the aKG/succinate ratio resulted in a significantly augmented Treg polarization and decreased levels of IFNg. Thus, manipulation of TCA cycle intermediates may promote the development of novel strategies aimed at enhancing anti-tumor CAR T cell effector functions.

  Figure2A) and this correlated with an upregulation of the master Th1 transcription factor, Tbet, at both the protein and mRNA level (Figure2B, 2C). Furthermore, these CD4 T cells exhibit an upregulation of granzyme B (Figure2C), a marker of CD4 T cells with CTL activity[START_REF] Takeuchi | CD4 CTL, a Cytotoxic Subset of CD4(+) T Cells, Their Differentiation and Function[END_REF]. While this αKG-induced CD4 T cell phenotype was not associated with an increase in TNFα or GM-CSF at the mRNA level, the secretion of these two cytokines as well as that of IFNg, IL-17 and IL-2 were remarkably elevated by αKG following stimulation of naïve CD4 T cells in Tregpolarizing conditions (Figure2D, 2E). The increase in IL-2 levels is in agreement with previous work showing that αKG regulates the association of CCTC-binding factor (CTCF) with select loci including that of the IL-2 gene, specifically increasing IL-2 expression[START_REF] Chisolm | CCCTC-Binding Factor Translates Interleukin 2-and alpha-Ketoglutarate-Sensitive Metabolic Changes in T Cells into Context-Dependent Gene Programs[END_REF].

  stimulation in either Th1 or Treg+αKG polarizing conditions as compared to control Treg polarizing conditions (***, p<0.005; Figure3C). Furthermore, the percentages of FoxP3 + ErbB2-CAR T cells in both LNs and tumors were significantly decreased by the initial ex vivo polarization in the presence of αKG (p<0.005) and the IFNg potential of ErbB2-CAR cells in LN, but not in tumors, was significantly augmented (p<0.01; Figures3B and 3C). While these data point to the critical role of the metabolic tumor environment in diminishing the effector function of anti-tumor T cells[START_REF] Chang | Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression[END_REF], they strongly indicate that an ex vivo modification of intracellular metabolite levels can alter the migration and/or persistence of anti-tumor T cells.Furthermore, αKG treatment significantly decreased the percentage of intratumoral FoxP3 + cells. This is particularly important in the solid tumor setting where recruitment of Tregs negatively impacts on the potential of effector T cells to eradicate the tumor[START_REF] Darrasse-Jeze | Tumor emergence is sensed by self-specific CD44hi memory Tregs that create a dominant tolerogenic environment for tumors in mice[END_REF].The transcriptional landscape of CD4 T cells polarized to a Treg fate is significantly impactedby αKG. To gain insights into the mechanisms via which αKG negatively impacts on Treg differentiation but not on Th1 differentiation, RNASeq analyses were performed. In accord with the alteration in T cell fate under Treg but not Th1 conditions, αKG-mediated changes in gene expression were more marked in the former as assessed by volcano plot representations (Figure4A). This corresponded to substantially more upregulated and downregulated genes in Treg as compared to Th1 conditions (Figure4B). Upregulation of transcription factors such as T-bet (p<1x10 -20 ) were expected based on our initial qRT-PCR analyses (Figure2) but other factors such as Irf1, Irf8 and Stat1 were also highly upregulated, suggesting increased signaling in these cells (Figure4C). Interestingly though, other factors were markedly downregulated by αKG (i.e. Fos, Klf4, Sox4) whereas others were unaffected (Rpl11, Ube3c; Figure4C). Most importantly, gene ontogeny analysis revealed the importance of membrane proteins, glycoproteins, which are often present at the cell membrane, and signal peptides, which result in the translocation of proteins to organelles and the cell membrane (Figure4D). These data highlight the importance of cell surface proteins in the αKG-mediated inhibition of CD4 T cell polarization to a Treg fate. αKG alters cholesterol metabolism and incorporation of poly-unsaturated fatty acids in the membrane of Treg-polarized lymphocytes.

Figure 1 -

 1 Figure 1-Exogenous aKG augments Th1 polarization and inhibits the polarization potential of naïve CD4 T cells towards a Treg fate

Figure 2 -

 2 Figure 2-aKG induces an inflammatory profile in Treg-polarized CD4 T cells

Figure 3 -

 3 Figure 3-ErbB2-CAR + T cells polarized ex vivo in the presence of aKG maintain an in vivo inflammatory profile following adoptive transfer into tumor-bearing mice

Figure 4 -

 4 Figure 4-Genes affecting membrane-related processes are strongly impacted by aKG in Treg polarizing conditions Murine naïve CD4 T cells were stimulated with plate-bound aCD3/aCD28 and polarized to Th1 or iTreg conditions in the presence or absence of exogenous aKG. On day 4 following polarization, cells were collected and transcript analysed by RNAseq. (A). Volcano plot representations of the differential expression analyses of genes expressed in T cells activated in Th1 (left) and Treg (right) polarization conditions in the absence versus presence of aKG. The x-axis shows log2 fold-changes in expression and the y-axis presents the log odds of a gene being differentially expressed. Downregulated (left) and upregulated (right) genes with a 3-fold change threshold are shown as dotted lines. (B) Venn diagram representation of the RNAseq data showing the number of genes upregulated (left) and downregulated (right) in Th1-(dark grey) and Treg-(light grey) polarizing cells (as based on a 3-fold change), with the intersection of common genes. (C) Genes identified in the transcription factor term in Treg-polarizing conditions, in the absence or presence of aKG, are presented. Statistical significance is indicated in the color scheme. (D) Gene ontology analysis (DAVID 6.7) of RNA-seq data. Significantly enriched terms associated to differentially expressed transcripts that were either upregulated (left) or downregulated (right) in Treg polarizing conditions in the presence of aKG versus control Tregpolarizing conditions are presented. The percentages of hits identified in each pathway are depicted, with the highest percentages of genes clustered in membrane-related pathways.

Figure 5 -

 5 Figure 5-Lipid saturation and membrane order is altered by aKG under Treg polarization conditions

Figure 6 -

 6 Figure 6-Treg differentiation is enhanced by blocking the aKG-induced augmentation in oxidative phosphorylation (A) Oxygen consumption (OCR), a measure of oxidative phosphorylation, was monitored on a Seahorse XFe96 analyzer at day 2 of polarization of naïve CD4 T cells to a Th1 versus Treg fate; means ± SEM of data from 9 independent experiments are shown (left panel). The impact of injecting αKG directly into the XFe96 flux analyzer at day 2 of Treg polarization was evaluated (middle panel; data are representative of 1 of 2 independent experiments). OCR of CD4 T cells polarized to a Treg fate at day 4 of stimulation, in the absence or presence of αKG, is presented (means ± SEM of 9 independent experiments). (B) The ATP/AMP ratio of CD4 T cells polarized to a Treg fate in control conditions or in the presence of αKG were evaluated by mass spectrometry and means ± SEM of triplicate technical replicates from 2 independent experiments are presented and statistical difference determined by an unpaired 2-tailed t-test. (C) The levels of αKG, succinate, malate, citrate and 2-hydroxyglutarate (2HG) were evaluated by mass spectrometry and the ratio of these metabolites in αKG-treated to control conditions are presented as means ± SEM of triplicate technical replicates from 2 independent experiments. Statistical significance was evaluated by an unpaired 2-tailed t-test. (D) To assess the impact of the αKG/succinate ratio on Treg differentiation, naïve CD4 T cells were stimulated in Treg polarization conditions in the presence or absence of aKG and succinate (7 mM). FoxP3 expression was evaluated a day 4 and representative plots are shown (left). Quantification of FoxP3 levels are presented as means ± SEM from 3 independent experiments and significance was evaluated by a oneway ANOVA and Tukey multiple comparison test (*, p<0.05; NS, not significant). (E) Oxygen consumption (OCR) was monitored in CD4 T cells stimulated in Treg-polarizing conditions in the presence of aKG and the impact of dimethyl malonate (DMM) was evaluated. Data are representative of means of 6 samples in 2 independent experiments. (F) The impact of malonate (10 mM) on Treg polarization was evaluated in the absence of presence of aKG. Representative FACS plots of FoxP3 expression are presented at day 4 (left) and quantifications of the means ± SEM of 19 independent experiments are presented (right). Significance was determined by a one-way ANOVA and Tukey multiple comparison test (**, p<0.01; ****, p<0.0001; NS, not significant). (G) IFNg, IL-17, IL-2, TNFa, and GM-CSF secretion by CD4 T cells polarized to a Treg fate in the absence of presence of aKG and/or malonate was evaluated at day 4 and means ± SEM are presented (n=10 independent experiments for aKG conditions and n=5 for malonate conditions). Significance was determined by a one-way ANOVA and Tukey multiple comparison test (*, p<0.05; **, p<0.01; ***, p<0.005; ****, p<0.0001; NS, not significant).

  activity, highlight the importance to study the potential impact of other amino acids deprivation on TEFF and Treg cell functions. As such, during my PhD I addressed the role of another amino acid important to T cells: arginine. Arginine availability is also reduced in the TME as it is reviewed in the section IV 2 A c. The direct link between arginine deprivation on the TME and T cell function was already described. Rodriguez and colleagues revealed that reduced arginine availability by myeloid cells activity in the TME induced T cell receptor CD3ζ

  differentiation and effector function. As previous discussed, the TME is characterized by low nutrient-availability, notably glutamine and arginine. Therefore, when CAR T cell therapies are designed it would be important to evaluate the impact of the nutrient availability on CAR T cell anti-tumor function. Analyze CAR T cell differentiation and cytokine secretion in a nutrient deprived context could help to predict CAR T cell anti-tumor efficiency and help in the selection of T cell subsets with a better survival and/or enhanced functions in a hostile environment. Moreover, understanding how nutrient availability impacts on CAR T cell differentiation and function, could help in the development of new tools to regulate and modulate CAR T cells metabolic program to fit them to the TME.Selection of T cells based on nutrient transportersIn addition of using pharmacological treatments to enhance and modulate T cell antitumor function, we could think about select CAR T cells based on their nutrient transporters surface expression and on their metabolic characteristics, before inject them into the patients. During my PhD, I showed that sorting T cells based on GLUT1 surface expression allows the selection of T cells with different phenotypes and effector functions[START_REF] Cretenet | Cell surface Glut1 levels distinguish human CD4 and CD8 T lymphocyte subsets with distinct effector functions[END_REF] (Chapter 1, Article I ). GLUT1 High cells have an increased percentage of CD8 + T cells,

  cells selected based on nutrient transporter expression characterized by distinct IL-17 vs IFNγ secretion pattern. Finally, it could be of interest to evaluate CAT-1 expression in hypoxia conditions and assess the phenotype and effector of T cells selected based on CAT-1 surface expression of T cell maintained in hypoxia. αKG as a metabolic regulator of the Th1/iTreg differentiation. As previously discussed, adding exogenous αKG in glutamine deprived conditions restored Th1 differentiation by rescuing T-bet expression and IFNγ secretion and by reducing FoxP3 expression (Chapter 2, Article II). Nevertheless, the mechanisms by which αKG modulates Th1/Treg differentiation were not characterized. To answer this question, during my PhD I studied the impact of exogenous αKG added in nutrient replete conditions during both Th1 and iTreg polarizations.

Figure 1 -

 1 Figure 1 -Potential mechanisms involved in the α-KG-dependent inhibition of iTreg polarizationαKG is a glutamine-derived metabolite that can fulfill the TCA cycle and therefore increase its metabolic functioning rate. Therefore, we hypothesize that the high amount of extracellular αKG and changes in the αKG/succinate ratio might impact the SDH activity, resulting in increased OXPHOS levels, reduced percentage of FoxP3 expressing cells and increased IFNγ secretion. Furthermore, high αKG intracellular levels is also associated with an augmentation of 2HG intracellular levels which could lead to an altered αKG/2HG ratio and as a result could impact TET-mediated epigenetic control of the FoxP3 and IFNγ gene. It would be also interesting to evaluate the potential impact of PUFAs increased levels in T cell membrane and TCR signaling.2HG(2-hydroxyglutarate), αKG (α-ketoglutarate), FoxP3 (forkhead box P3), IFNγ (interferon γ), SDH (succinate dehydrogenase), Succi (succinate), PUFAs (polyunsaturated fatty acids), TCA (tricarboxylic acid cycle), TCR (T cell receptor). Created with Biorender.com

  metabolic impact. Therefore, to pursue the experiments on human iTreg cells is crucial and necessary to evaluate the translational potential of our work. During my PhD I demonstrated that adding exogenous αKG in culture can impact T cell fate and effector function, potentiating Th1 differentiation and negatively impacting Treg differentiation. Therefore, it could be of interest to add αKG during the ex vivo generation of CAR T cells and before adoptive transfer to the patient. CAR T cells with increased IFNγ and TNFα secretory potential and reduced FoxP3 expression, would be interesting in a TME context. Moreover, manipulation of αKG levels in the TME could be as well an interesting strategy for the reduction of Treg cell numbers in the TME. The utilization of αKG in the clinic has been already done with other different proposes. For instance, the accumulation of 2HG

  bearing humanized mouse model. If the results on murine models are encouraging, it would become exciting to evaluate the feasibility to include this strategy to on-going clinical protocols. CAR T cell manufacture protocols used in clinic are quite standardized with wellestablished procedures. Sorting T cells based on nutrient transporters surface expression would add an extra procedure to include. Thus, it would be interesting to evaluate the efficiency of the CAR T cell selection based on nutrient transporters surface expression and the stability/phenotype of sorted CAR T cells during the expansion phase and before injection into the patient.

Table 1 -Naïve T cell surface markers in both mouse and human species

 1

Table 2 -TCM, TEM and TRM surface markers in both mouse and human species

 2

Table 1 : Antibody List

 1

	15 N2]glutamine, respectively, for 24 hours. Cells were rapidly washed in ice-cold PBS and
	metabolites were extracted in a 50% methanol / 30% acetonitrile/ 20% water solution. The
	volume of extraction solution was adjusted to 2 x 10 6 cells / ml for all samples and were
	normalized to the number of cells obtained at the end of the 24-hour incubation period. All
	cultures were performed in triplicate. Both cell extracts and media were centrifuged at
	16,000g for 10min at 4°C and supernatants were analyzed by HPLC-MS. Samples were
	separated on a Thermo Scientific Accela liquid chromatography system coupled with a guard
	column (Hichrom) and a ZIC-pHILIC column (Merck). The separation was performed using a
	gradient elution in a solution of 20mM ammonium carbonate, with 0.1% ammonium
	hydroxide and acetonitrile. Metabolites were detected using a Thermo Scientific Exactive
	Orbitrap mass spectrometer with electrospray ionization, operating in a polarity switching
	mode. Raw data were analyzed with Xcalibur 2.2 and LCquan 2.7 Thermo scientific software.

Table 2 : Primer Sequences

 2 Pathology of the Century"[START_REF] Falzone | Evolution of Cancer Pharmacological Treatments at the Turn of the Third Millennium[END_REF]. Despite the improvement in cancer treatment, in 2015 it was estimated that over 8.7 million of people died from cancer neoplasia and near 17.5 million of new cases were detected (GBD Mortality and Causes of Death

	Gene	Forward 5'-3'	Reverse 5'-3'
	FOXP3	GGCCCTTCTCCAGGACAGA	GCTGATCATGGCTGGGTTGT
	IFNg	TGGCTCTGCAGGATTTTCATG	TCAAGTGGCATAGATGTGGAAGAA
	TBET	CAACAACCCCTTTGCCAAAG (S)	TCCCCCAAGCAGTTGACAGT
	GMCSF	TTTACTTTTCCTGGGCATTG	TAGCTGGCTGTCATGTTCAA
	IL10	ACCTGCTCCACTGCCTTGCT	GGTTGCCAAGCCTTATCGGA
	TNFa	CATCTTCTCAAAATTCGAGTGACAA	GGGAGTAGACAAGGTACAACCC
	HPRT	CTGGTGAAAAGGACCTCTCG	TGAAGTACTCATTATAGTCAAGGGCA
	ACTIN	CAATAGTGATGACCTGGCCGT	AGAGGGAAATCGTGCGTGAC
	GRZB	TGCTGACCTTGTCTCTGGCC	TAGTCTGGGTGGGGAATGCA
	ABCA1	AAAACCGCAGACATCCTTCAG	CATACCGAAACTCGTTCACCC
	ABCG1	CTTTCCTACTCTGTACCCGAGG	CGGGGCATTCCATTGATAAGG
	ACAT1	GAAACCGGCTGTCAAAATCTGG	TGTGACCATTTCTGTATGTGTCC
	CPT1	TTGGGCCGGTTGCTGAT	GTCTCAGGGCTAGAGAACTTGGAA
	LSS	CGACATCACTGCTCAGGAGA	TGGCACAGGACTTGTTGAAG
	CYP51	TCTCCAATTCCATTCCTTGG	GCCCACCATGGTAAAGCTAA
	LDLR	TGACTCAGACGAACAAGGCTG	ATCTAGGCAATCTCGGTCTCC
	HMGCR	AGCTTGCCCGAATTGTATGTG	TCTGTTGTGAACCATGTGACTTC
	HMGCS	AACTGGTGCAGAAATCTCTAGC	GGTTGAATAGCTCAGAACTAGCC
	SREBP1	GCAGCCACCATCTAGCCTG	CAGCAGTGAGTCTGCCTTGAT
	SREBP2	GCAGCAACGGGACCATTCT	CCCCATGACTAAGTCCTTCAACT
	IRF1	CAGAGGAAAGAGAGAAAGTCC	CACACGGTGACAGTGCTGG
	IRF8	GGGCTGATCTGGGAAAATGATGAGA	CCCAGGCCTTGAAGATGGAAGCA
	ACACA	CATCACCATCAGCCTGGTTACA	ACTGTGTACGCTCTTCGGCAT
	LXRA	AGGAGTGTCGACTTCGCAAA	CTCTTCTTGCCGCTTCAGTTT

  . This work is curious as it highlights the capacity of Treg cells to induce amino acid depletion in the surrounding environment and it would be interesting to see if similar mechanisms take place in the TME. The fact the amino acid metabolism is not crucial for Treg cells, give to this subset a selective advantage in amino acid-Treg cells metabolic activity is able to shape the environment, impacting other cells function and, at the same time, contributes to its own differentiation program in hostile environments. Indeed, Treg metabolic characteristics can clearly favor their cell development and function in a TME that is characterized by low amino acids and glucose availability as well as high levels of lactate and FAs. It is known that Treg cells have a pro-tumor function and its

	deprived environments. However, Treg cells have other mechanisms to survive in hostile
	metabolic environments. For instance, it was shown that FoxP3 reprograms Treg cell
	metabolism to function in high-lactate and low-glucose environments, suppressing glycolysis,
	enhancing OXPHOS and increasing NAD oxidation (Angelin et al., 2017). Moreover, another

elegant study demonstrated that FoxP3 induces FAO, which gives a selective advantage to Treg cells in FA-rich environments and protect them from lipotoxicity

(Howie et al., 2017a)

.Thus,

Acknowledgments

Abstract

The proliferation and differentiation of T lymphocytes is regulated by antigen and cytokine signals but the induction of metabolic pathways is also required, resulting in an integration of environmental cues in cell fate decisions. Indeed, T lymphocyte activation is regulated by the metabolism of glucose, fatty acids and amino acids, allowing the cell to meet increased energetic and biosynthetic demands. Notably, we recently found that glutamine availability is a key determinant of T cell differentiation; CD4 lymphocytes undergo differentiation to IFNg-secreting Th1 effectors under conditions of optimal glutaminolysis but are converted to FoxP3 + regulatory T cells (Tregs) when glutamine catabolism is abrogated.

Here, we show that the glutamine-derived metabolite, a-ketoglutarate (aKG), significantly augmented IFNg secretion while dramatically attenuating Treg generation. Specifically, aKG-

Results

Article

Discussion

Bibliography Annexes