Javiera Villar

Elodie Segura
email: elodie.segura@curie.fr

Recent advances towards deciphering human dendritic cell development

Keywords: Monocyte, Human, Differentiation, mo-mac, mo-DC, Inflammation, ETV3, ETV6 Monocyte, Human, Differentiation, Macrophage, Dendritic cell Dendritic cells Human Development Monocytes, Human, Differentiation, Macrophage, Dendritic cells

Monocytes and monocyte-derived cells are central players in the initiation and resolution of inflammatory responses. In chronic inflammatory diseases, monocyte-derived antigen-presenting cells become major drivers of the physiopathology by stimulating pathogenic T cells. Blocking monocyte differentiation therefore represents an attractive therapeutic strategy. A major hurdle is the paucity of molecular targets, due to a limited knowledge of the molecular regulation of monocyte fate commitment.

The objective of my thesis is to identify new regulators of monocyte differentiation using two complementary approaches:

(1) a candidate-based approach, built on previous work of the group. Comparative transcriptomic analysis revealed several transcription factors differentially expressed between mo-DC and mo-mac. In this project, I focused on ETV3 and ETV6, transcriptional repressors that are highly expressed in mo-DCs. Their role in monocyte differentiation was unknown.

(2) an unbiased approach using single-cell-RNAseq analysis. The molecular pathways of human monocyte differentiation are frequently analyzed from already differentiated cells, either mo-DCs or momac. To analyze the dynamics of monocyte differentiation at earlier stages, I performed scRNAseq experiments at different time points using an in vitro model of differentiation. I then reconstructed the developmental trajectories to discover new molecular pathways that regulate monocyte commitment.

Here we show that the transcriptional repressors ETV3 and ETV6 control human monocyte differentiation into mo-DC. Mechanistically, we find that ETV3 and ETV6 repress mo-Mac development and inhibit the expression of interferon-stimulated genes. Mice deficient for ETV6 in monocytes showed spontaneous expression of interferon-stimulated genes, confirming that ETV6 regulates interferon responses in vivo. Furthermore, these mice display impaired mo-DC differentiation during peritonitis and ameliorated experimental autoimmune encephalomyelitis.

In parallel, I analyzed differentiating monocytes using single cell transcriptomics technology. By unbiased clustering and differential gene expression analysis, I observed that at 3-9h of culture some groups of monocytes are already committed to become mo-DC or mo-Mac. I analyzed the transcription factors showing differential activity or expression between cells committed to mo-DC versus mo-Mac. I validated that IRF1 modulates differentiation into mo-mac, and ZNF366, MAFF and ETS2 into mo-DC.

These analyses revealed new signalling pathways and transcription factors involved in the monocyte commitment process.

My results contribute to a better understanding of the molecular mechanisms regulating monocyte fate.

Résumé

Les monocytes circulent dans le sang et sont recrutés dans les tissus où ils se différencient en macrophages (mo-mac) ou cellules dendritiques (mo-DC). Les mo-DC et les mo-mac participent respectivement à l'initiation et à la résolution des réponses immunitaires inflammatoires. Cependant, dans les maladies chroniques inflammatoires, les mo-DC ont des effets délétères en entretenant le cycle de l'inflammation. Ainsi, manipuler la différenciation des monocytes pourrait contribuer à restaurer l'homéostasie tissulaire. Un obstacle majeur à cette stratégie est notre connaissance limitée des mécanismes moléculaires mis en jeu. L'objectif de ma thèse est d'identifier de nouveaux régulateurs de la différenciation des monocytes en utilisant deux approches complémentaires :

(1) une approche basée sur des candidats, s'appuyant sur les travaux antérieurs du groupe. Une analyse transcriptomique comparative a révélé plusieurs facteurs de transcription différentiellement exprimés entre mo-DC et mo-mac. Dans ce projet, je me suis concentrée sur ETV3 et ETV6, des répresseurs transcriptionnels qui sont fortement exprimés dans les mo-DCs. Leur rôle dans la différenciation des monocytes était inconnu.

(2) une approche non biaisée utilisant l'analyse RNAseq de cellules uniques. Les voies moléculaires de la différenciation des monocytes humains sont fréquemment analysées à partir de cellules déjà différenciées, soit mo-DC ou mo-mac. Des informations essentielles pourraient être obtenues en analysant des stades plus précoces. Pour analyser la dynamique de la différenciation des monocytes, j'ai réalisé des expériences d'RNAseq unicellulaires à différents moments de la différenciation en utilisant un modèle in vitro. J'ai reconstruit ensuite les trajectoires de développement pour découvrir de nouvelles voies moléculaires qui régulent l'engagement des monocytes.

En utilisant un modèle in vitro de différenciation des monocytes humains, j'ai montré que les facteurs de transcription Etv3 et Etv6 contrôlent la différenciation en moDC. Une analyse transcriptomique a révélé que Etv3 et Etv6 répriment les gènes stimulés par l'interféron. J'ai également validé ces résultats in vivo en montrant que Etv6 est impliqué dans la différenciation des mo-DC lors de l'inflammation et identifié Etv6 comme cible thérapeutique dans la sclérose en plaque. Parallèlement, j'ai analysé des monocytes en cours de différenciation en utilisant la technologie de transcriptomique en cellule unique. Par un clustering non biaisé et l'analyse d'expression différentielle des gènes, j'ai observé qu'à 3-9h de culture certains groupes de monocytes sont déjà engagés à devenir mo-DC ou mo-Mac. J'ai analysé les facteurs de transcription présentant une activité ou une expression différentielle entre les cellules engagées en mo-DC versus mo-Mac. J'ai validé que IRF1 module la différenciation en mo-mac, et ZNF366, MAFF et ETS2 en mo-DC. Ces analyses ont révélé de nouvelles voies de signalisation et facteurs de transcription impliqués dans le processus d'engagement des monocytes Mes résultats contribuent à mieux comprendre les mécanismes moléculaires régulant le destin cellulaire des monocytes.

Mots-clés :

Monocytes, différenciation, mo-mac, mo-DC, Inflammation, ETV3, ETV6 Aknowledgments I want to sincerely acknowledge all the people that cooperated and help to have this work done. To the Segura group (Alice, Alba, Adeline and Lamine) for the constant help in experiments and discussions. And especially to Elodie. I feel lucky to have had you as my boss. I learnt a lot from you and I'm really grateful for your support during these four years.

Thanks to all of you! To the U932 for the great environment to work, for the discussions and advice, the last-minute-reagents… and especially for all the parties and beers! As feminist, I need to thanks to all the women that in many ways have allowed me to be here now. I would like to especially thank to my ex-supervisor Maria Ines Becker, a model scientist and person that convince me that the maternity was compatible with science. I want to thank also to all my colleagues and scientist friends during these years. I hope one day we, women, will have the space that we deserve in science. I'm sure we will, and it will happen because of our strength and resilience.

Y finalmente la familia…

Quisiera agradecer a todos los amigos que me regaló París (que no voy a nombrar uno por uno porque no quiero que se me olvide nadie), por que han sido la familia que a veces hace tanta falta. Con quienes hemos compartido asados, miércoles after work, cumpleaños, más asados, covid fiestas, picnics y cazuelas… algunos siguen aquí y otros ya se han ido (traidores!). ¡¡¡A todos los quiero mucho y muchas gracias!!! Y a la familia que está lejos les debo la vida. Gracias mamá, papá y hermana. Y a Lautaro y Pato que aceptaron esta locura… les debo esta tesis.

A todos ustedes; mil veces gracias. Table 1. Monocyte expression of surface markers by species and subpopulations…………17

Table of content

Figures and Tables

Table 2. Expression of surface markers by mo-DC and infDC2 in mice…………………….. [START_REF] Heger | CLEC10A is a specific marker for human CD1c+ dendritic cells and enhances their toll-like receptor 7/8induced cytokine secretion[END_REF] Table 3. Expression of surface marker in human monocytes, mo-DC and and mo-mac….. 28

Results

Chapter 1. ETV3 and ETV6 enable monocyte differentiation into dendritic cells during inflammation by repressing interferon-stimulated genes

Introduction

Introduction is organized in three parts. The chapters describe the different stages of the monocyte life cycle, from their development and exit from the bone marrow to their entry into tissues and differentiation. In the first part, I will focus on the subpopulations of monocytes in humans and mice, their trafficking to tissues and their identification. In a second part, I will detail the different methods to study the ontogeny of monocyte-derived cells and what is known so far in mouse and human, as well as the function of these cells. In the third part, I will focus on studies that have described a deleterious role of mo-mac and mo-DC in tissues during inflammation.

Note: Parts of this introduction are based on two review articles and a method chapter that I wrote with the help of Elodie Segura (see Annexes).

Chapter 1. Definition and development of monocytes

A. Monocyte life cycle

Definition

Monocytes are circulating blood cells that constitute ~10% of blood leukocytes in humans and ~4% in mice. They were first described in 1880 based on various cytological stains and morphological criteria of blood leukocytes and called as Ubergangsformen (Transitional cells).

The term "monocytes" was introduced just in 1910 (Pappenheim). Later, monocytes were shown to derive from a precursor in the bone marrow and to give rise to macrophages in the peritoneum based on in vivo cell tracing by thymidine-3H [START_REF] Van Furth | The origin and kinetics of mononuclear phagocytes[END_REF]). This work is the first mention of monocyte differentiation.

Monocytes are continuously produced in the bone marrow (BM) in a process called hematopoiesis and are then released into the peripheral circulation. Circulating monocytes consist of distinct subsets. Passlick in 1989 classified human monocytes for the first time, based on their expression of CD14 and CD16 [START_REF] Passlick | Identification and Characterization of a Novel Monocyte Subpopulation in Human Peripheral Blood[END_REF]. In mice, monocytes are separated into two subpopulations according to the expression of CCR2 and CX3CR1 [START_REF] Geissmann | Blood Monocytes Consist of Two Principal Subsets with Distinct Migratory Properties[END_REF].

Development of monocytes a. Ontogenic pathway

Hematopoietic stem cells (HSC) are a self-renewing population that generates heterogeneous multipotent progenitors (MPP, [START_REF] Pietras | Functionally Distinct Subsets of Lineage-Biased Multipotent Progenitors Control Blood Production in Normal and Regenerative Conditions[END_REF]. The myeloid and lymphoid fate segregates at this point; MPP further become common myeloid progenitors (CMP, [START_REF] Akashi | A clonogenic common myeloid progenitor that gives rise to all myeloid lineages[END_REF] or common lymphoid progenitors (CLP, [START_REF] Kondo | Identification of clonogenic common lymphoid progenitors in mouse bone marrow[END_REF]. CLP give rise to lymphoid cells including T, B, and natural killer cells. However, dendritic cells (DC) deriving from lymphoid progenitors have also been described [START_REF] Dress | Plasmacytoid dendritic cells develop from Ly6D+ lymphoid progenitors distinct from the myeloid lineage[END_REF]Helft et al., 2017). Human CMP can be divided into two subpopulations with different myeloid potential: a CD131 + subset that expresses the transcription factor Gata1 (CMP-Gata1 + ) and a CD114 + subset (CMP-Gata1 -).

The former is restricted to the megakaryocyte/erythrocyte and mastocyte/basophil/eosinophil lineages, the latter is restricted to monocyte and neutrophil lineages (Drissen et al., 2019).

Recently, it has been proposed that monocytes emerge from two parallel pathways that diverge from the CMP compartment (Figure 1). CMP-Flt3 -transit toward granulocyte and macrophage progenitors (GMP, [START_REF] Akashi | A clonogenic common myeloid progenitor that gives rise to all myeloid lineages[END_REF], while CMP-Flt3 + transit toward macrophage and DC progenitor (MDP, [START_REF] Drissen | Distinct myeloid progenitor differentiation pathways identified through single cell RNA sequencing[END_REF][START_REF] Yáñez | Granulocyte-Monocyte Progenitors and Monocyte-Dendritic Cell Progenitors Independently Produce Functionally Distinct Monocytes[END_REF]. MDP produce classical DCs (cDCs) and plasmacytoid DCs (pDCs) through a common dendritic cell progenitor (CDP) (Lee et al., 2015) and monocytes through a common monocyte progenitor (cMoP) [START_REF] Ginhoux | Monocytes and macrophages: developmental pathways and tissue homeostasis[END_REF][START_REF] Terry | Molecular control of monocyte development[END_REF]. cMoP is found in mice and humans and is a unipotent progenitor with a high proliferative capacity that differentiates into monocytes [START_REF] Hettinger | Origin of monocytes and macrophages in a committed progenitor[END_REF][START_REF] Kawamura | Identification of a Human Clonogenic Progenitor with Strict Monocyte Differentiation Potential: A Counterpart of Mouse cMoPs[END_REF]. GMP also give rise to monocytes through a monocyte progenitor (MP). Of note, MP is phenotypically indistinguishable from cMoP. However, monocytes produced from the "GMP pathway" are transcriptionally different from the MDP-derived monocytes [START_REF] Weinreb | Lineage tracing on transcriptional landscapes links state to fate during differentiation[END_REF][START_REF] Yáñez | Granulocyte-Monocyte Progenitors and Monocyte-Dendritic Cell Progenitors Independently Produce Functionally Distinct Monocytes[END_REF]. The former (termed neutrophil-like monocytes) express higher levels of genes associated with neutrophils such as S100a9, Elane and Mpo, while MDP-derived monocytes (also termed DC-like monocytes) exhibit a DC-related signature including Cd74, Cd209a and MHCII genes [START_REF] Yáñez | Granulocyte-Monocyte Progenitors and Monocyte-Dendritic Cell Progenitors Independently Produce Functionally Distinct Monocytes[END_REF]. It was also proposed based on fate mapping of GMP cells that the MDP compartment actually contains GMP already committed to become monocytes [START_REF] Liu | Fate Mapping via Ms4a3-Expression History Traces Monocyte-Derived Cells[END_REF]. Finally, recent worked showed that Commd10 deficiency in Ly6C high monocytes generates a bias toward "neutrophil-like" monocytes, at the expense of "DC-like" monocytes [START_REF] Cohen | COMMD10 is critical for Kupffer cell survival and controls Ly6Chi monocyte differentiation and inflammation in the injured liver[END_REF]. This differentiation bias is initiated already in the steady-state BM, suggesting that Commd10 regulates monocyte differentiation or heterogeneity.

ScRNA-Seq studies of human blood monocytes support analogous heterogeneity within the classical monocytes (Dutertre et al., 2019;Villani et al., 2017;[START_REF] Weinreb | Lineage tracing on transcriptional landscapes links state to fate during differentiation[END_REF], but Hambleton et al., 2011;[START_REF] Kurotaki | Essential role of the IRF8-KLF4 transcription factor cascade in murine monocyte differentiation[END_REF][START_REF] Mckercher | Targeted disruption of the PU.1 gene results in multiple hematopoietic abnormalities[END_REF]Sichien et al., 2016).

IRF8 restricts neutrophil potential to promote the differentiation of lineage-committed progenitors into monocytes [START_REF] Yáñez | IRF8 acts in lineagecommitted rather than oligopotent progenitors to control neutrophil vs monocyte production[END_REF]. IRF8 also creates a regulatory circuit with KLF4, since overexpression of KLF4 in IRF8 -/-cells partially rescues monocyte differentiation [START_REF] Kurotaki | Essential role of the IRF8-KLF4 transcription factor cascade in murine monocyte differentiation[END_REF]. Consistent with this, patients with an autosomal recessive IRF8 mutation possess reduced numbers of circulating monocytes (Hambleton et al., 2011).

Moreover, human GMP can be divided into subpopulations based on IRF8 expression.

IRF8 high GMP are restricted to pDC, cDC1 and cDC2, while IRF8 low GMP transit to a "monocytic pathway" that gives rise to monocytes and the newly described DC3 (Cytlak et al., 2019) (Figure 2). A comparable IRF8 dose-dependent effect was observed in cDC1, monocyte and neutrophil lineages in mice. The differential doses of Irf8 in progenitors was controlled by lineage-specific enhancers and other TFs [START_REF] Murakami | A RUNX-CBFβ-driven enhancer directs the Irf8 dosedependent lineage choice between DCs and monocytes[END_REF]. These results indicate that the requirement for IRF8 is different in "early" monopoiesis and in the later stages of monocyte differentiation (Figure 2).

The dichotomy of monocyte development reported in mice could also be supported by differential TF requirements. Indeed, high expression of Spi1, encoding PU.1, was shown to induce "DC-like monocytes" based on the expression of Cd209a, Flt3 and MHCII genes [START_REF] Menezes | The Heterogeneity of Ly6Chi Monocytes Controls Their Differentiation into iNOS+ Macrophages or Monocyte-Derived Dendritic Cells[END_REF]. This data supports the concept of bifurcated monocyte ontogeny.

Finally, negative regulators can promote one fate over another. For instance, BACH2 has been shown to contribute as a negative regulator of monopoiesis, as Bach2 knock out mice have increased monocytes [START_REF] Kurotaki | Essential role of the IRF8-KLF4 transcription factor cascade in murine monocyte differentiation[END_REF].

nonclassical monocytes were subsequently labeled and had longer circulating lifespans of ∼4 and ∼7 days, respectively [START_REF] Mildner | Genomic Characterization of Murine Monocytes Reveals C/EBPβ Transcription Factor Dependence of Ly6C-Cells[END_REF][START_REF] Patel | The fate and lifespan of human monocyte subsets in steady state and systemic inflammation[END_REF].

HUMAN MONOCYTES MICE MONOCYTES

MARKER

b. In mice

In mice, two subpopulations of monocytes were reported by the use of the reporter Cx3cr1 +/EGFP mice: classical monocytes Ly6C high CCR2 + CX3CR1 low, also called "inflammatory" monocytes, and non-classical or "patrolling" Ly6C low CCR2 -CX3CR1 high monocytes [START_REF] Geissmann | Blood Monocytes Consist of Two Principal Subsets with Distinct Migratory Properties[END_REF]Palframan et al., 2001). However, the EGFP level in Cx3cr1 EGFP reporter strain does not reflect the actual CX3CR1 expression as would be measured by a specific antibody. Recently CD43 expression was shown to discriminate classical from nonclassical monocytes [START_REF] Meghraoui-Kheddar | Revising CX3CR1 Expression on Murine Classical and Non-classical Monocytes[END_REF].

Ly6C high monocytes are short-lived with an estimated half-life of 0.8 days, while Ly6C low monocytes possess an estimated half-life of 2 days or up to 14 days when Ly6C high monocytes are ablated [START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF]. As in human, CX3CR1 int Ly6C high monocytes are an obligatory intermediate for the generation of CX3CR1 high Ly6C low monocytes in the blood [START_REF] Hettinger | Origin of monocytes and macrophages in a committed progenitor[END_REF][START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF]. Moreover, adoptively transferred cMoP differentiate into Ly6C high and later into Ly6C low monocytes [START_REF] Hettinger | Origin of monocytes and macrophages in a committed progenitor[END_REF].

Comparative transcriptomic studies have established homology between murine Ly6C high classical monocytes and human CD14 + classical monocytes as well as between Ly6C low nonclassical monocytes and CD16 + non-classical monocytes [START_REF] Cros | Human CD14dim Monocytes Patrol and Sense Nucleic Acids and Viruses via TLR7 and TLR8 Receptors[END_REF][START_REF] Haniffa | Human tissues contain CD141hi cross-presenting dendritic cells with functional homology to mouse CD103+ nonlymphoid dendritic cells[END_REF][START_REF] Ingersoll | Comparison of gene expression profiles between human and mouse monocyte subsets[END_REF].

B. Monocyte recruitment into tissues

1. Recruitment

a. Cytokine signals

The egress of monocytes from the BM into the bloodstream is mediated by the interaction of chemokines (Ccl2, Ccl7) with the chemokine receptor Ccr2, which is expressed by monocytes.

At steady state, Ccr2 -/-mice show severe monocytopenia and accumulation of Ly6C high monocytes in the bone marrow [START_REF] Serbina | Monocyte emigration from bone marrow during bacterial infection requires signals mediated by chemokine receptor CCR2[END_REF][START_REF] Tsou | Critical roles for CCR2 and MCP-3 in monocyte mobilization from bone marrow and recruitment to inflammatory sites[END_REF]. Accordingly, monocyte recruitment in tissues is strongly decreased in infection models in mice deficient for Ccr2, Ccl2, or Ccl7, and monocytes are retained in the bone marrow [START_REF] Bosschaerts | Tip-DC Development during Parasitic Infection Is Regulated by IL-10 and Requires CCL2/CCR2, IFN-γ and MyD88 Signaling[END_REF][START_REF] Dunay | Gr1+ Inflammatory Monocytes Are Required for Mucosal Resistance to the Pathogen Toxoplasma gondii[END_REF][START_REF] Jia | Additive Roles for MCP-1 and MCP-3 in CCR2-Mediated Recruitment of Inflammatory Monocytes during Listeria monocytogenes Infection[END_REF][START_REF] Kuziel | Severe reduction in leukocyte adhesion and monocyte extravasation in mice deficient in CC chemokine receptor 2[END_REF]. In addition, Ccl2 expression can be induced upon cytokine or pathogen stimulation in a variety of cells, such as endothelium, smooth muscle, epithelium, tumor cells, among others [START_REF] Gschwandtner | More Than Just Attractive: How CCL2 Influences Myeloid Cell Behavior Beyond Chemotaxis[END_REF][START_REF] Shi | Monocyte recruitment during infection and inflammation[END_REF]. Of note, mice that are double deficient in Ccl8 and Ccl12, which are also Ccr2 ligands, do not show a defect in the recruitment of monocytes [START_REF] Tsou | Critical roles for CCR2 and MCP-3 in monocyte mobilization from bone marrow and recruitment to inflammatory sites[END_REF]. This data indicates that only the interactions between Ccl2 and Ccl7 with Ccr2 are required for monocyte exit from the BM.

Some studies based on adoptive transfer of monocytes have demonstrated that Ccr2 is not required for the passage of monocytes from blood to tissue during inflammation. Indeed, Ccr2 -/-and Ccr2 +/+ monocytes had the same capacity to infiltrate tissues during infection [START_REF] Bosschaerts | Tip-DC Development during Parasitic Infection Is Regulated by IL-10 and Requires CCL2/CCR2, IFN-γ and MyD88 Signaling[END_REF][START_REF] Shi | Monocyte Trafficking to Hepatic Sites of Bacterial Infection Is Chemokine Independent and Directed by Focal Intercellular Adhesion Molecule-1 Expression[END_REF]. Moreover, Ccr2 was not required for early monocyte recruitment in a model of renal nephritis [START_REF] Mysore | Monocytes transition to macrophages within the inflamed vasculature via monocyte CCR2 and endothelial TNFR2[END_REF]. Thus, although Ccr2 is essential for monocyte to egress from the bone marrow, it is not required to traverse blood vessels into other tissues.

a. Adhesion molecules

Extravasation is the passage of immune cells from the bloodstream to the tissues. This phenomenon is mediated by adhesion molecules, such as E-and P-selectin, intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1(VCAM-1) [START_REF] León | Monocyte migration to inflamed skin and lymph nodes is differentially controlled by L-selectin and PSGL-1[END_REF][START_REF] Min | TNF-related activation-induced cytokine enhances leukocyte adhesiveness: induction of ICAM-1 and VCAM-1 via TNF receptor-associated factor and protein kinase C-dependent NF-kappaB activation in endothelial cells[END_REF]. The activated endothelium increases the expression of adhesion molecules that interact with proteins expressed on monocytes. For instance, selectins interact with P-selectin glycoprotein ligand-1 (PSGL-1) [START_REF] León | Monocyte migration to inflamed skin and lymph nodes is differentially controlled by L-selectin and PSGL-1[END_REF] and VCAM-1 interacts with the integrin very late antigen-4 (VLA-4) [START_REF] Schmitz | Increased monocyte adhesion by endothelial expression of VCAM-1 missense variation in vitro[END_REF].

These interactions allow monocytes to roll on the endothelium and then transmigrate into tissues (Figure 3). Interaction with chemokines such as Ccl2 attract monocytes to the endothelium and interaction with adhesion molecules will mediate their capture, rolling, and then transmigration to the tissues.

Chapter 2. Monocyte derived cells: moDC and moMac

Although for many years monocytes were seen as immature siblings of macrophages and DCs, nowadays it is known that monocytes recruited in different tissues give rise to monocytederived cells that are often functionally, phenotypically and transcriptionally distinct from resident macrophages and cDC.

A. Monocyte-derived cells in mice

Mouse models used for the study of monocyte fate

Fate-mapping studies of monocytes have been performed by generating transgenic mouse strains that harbor genes encoding constitutive active Cre or conditional Cre recombinase (CreERT, which depends on tamoxifen for activity) in their Cx3cr1, LysM or Ms4a3 loci, and crossing them with Rosa26 tdTomato reporter strain. In the resulting mice, Cre recombinase will delete the Stop signal adjacent to tdTomato, encoding for a fluorescent protein, resulting in persistent/irreversible tdTomato protein expression in Ms4a3, Cx3cr1 or LysM-expressing cells and their progeny [START_REF] Clausen | Conditional gene targeting in macrophages and granulocytes using LysMcre mice[END_REF][START_REF] Liu | Fate Mapping via Ms4a3-Expression History Traces Monocyte-Derived Cells[END_REF][START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF]. These mouse strains enable tracking cells that normally express these genes and follow them across time and in different tissues.

Fluorescent reporter strains are useful, but some confounding factors should be considered such as specificity. The reporter Cx3cr1 EGFP , created in 2000 by Jung et al helped to establish the definition of classical and non-classical monocytes based on EFGP reporter expression.

The presence of Cx3cr1 was also observed in a portion of NK cells, circulating and skin resident DC and microglia [START_REF] Jung | Analysis of Fractalkine Receptor CX 3 CR1 Function by Targeted Deletion and Green Fluorescent Protein Reporter Gene Insertion[END_REF]. Moreover, it has been shown that Cx3cr1 also targets to a lesser extent the early cDC progenitors [START_REF] Liu | In vivo analysis of dendritic cell development and homeostasis[END_REF]. Ms4a3-based fate mapping helps distinguishing monocytes from cells of cDC lineage, but not from granulocytes.

Ms4a3 TdT targets GMP but not MDP in the bone marrow [START_REF] Liu | Fate Mapping via Ms4a3-Expression History Traces Monocyte-Derived Cells[END_REF], and GMP was shown to give rise to granulocytes (basophils and neutrophils) and monocytes. LysM-based

Identification of mo-Mac in tissues

Tissue-resident macrophages (TRM) were thought to be continuously renewed from adult circulating blood monocytes [START_REF] Van Furth | The mononuclear phagocyte system: a new classification of macrophages, monocytes, and their precursor cells[END_REF]. More recent research has revealed that bona fide TRM arise from embryonic or perinatal precursors and are maintained locally.

Depending on the tissues, the TRM pool can be replenished by monocyte recruitment at homeostasis (Figure 5) [START_REF] Ginhoux | Tissue-Resident Macrophage Ontogeny and Homeostasis[END_REF]. For instance, in vivo lineage tracing with the Cx3cr1 EGFP reporter established that adult microglia in the central nervous system derives from embryonic myeloid progenitors in a process dependent on the MCSF receptor (Csf1r) [START_REF] Ginhoux | Fate Mapping Analysis Reveals That Adult Microglia Derive from Primitive Macrophages[END_REF]. Competitive chimeric mice reconstituted with WT and Ccr2 -/- BM cells showed that alveolar macrophages in lung airspaces develop from fetal monocytes and self-maintain dependently on local GM-CSF (Csf2) production [START_REF] Guilliams | Alveolar macrophages develop from fetal monocytes that differentiate into long-lived cells in the first week of life via GM-CSF[END_REF][START_REF] Hashimoto | Tissue-resident macrophages self-maintain locally throughout adult life with minimal contribution from circulating monocytes[END_REF]. During adulthood, other tissues are replenished by blood monocytes that differentiate into mo-mac and that coexist with the locally maintained TRM at homeostasis, as in the peritoneal macrophage pool [START_REF] Miyanishi | Synergistic effect of Tim4 and MFG-E8 null mutations on the development of autoimmunity[END_REF][START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF] or the liver [START_REF] Sierro | A Liver Capsular Network of Monocyte-Derived Macrophages Restricts Hepatic Dissemination of Intraperitoneal Bacteria by Neutrophil Recruitment[END_REF]. Finally, mo-Mac can completely replace the embryonic TRM such as in the skin dermis [START_REF] Tamoutounour | Origins and functional specialization of macrophages and of conventional and monocyte-derived dendritic cells in mouse skin[END_REF] and intestine [START_REF] Bain | Constant replenishment from circulating monocytes maintains the macrophage pool in the intestine of adult mice[END_REF]. Expression of the apoptotic cell-uptake receptor T-cell membrane protein 4 (Tim-4) can distinguish monocyte-derived from resident (embryonic) macrophages in the small intestine [START_REF] Shaw | Tissue-resident macrophages in the intestine are long lived and defined by Tim-4 and CD4 expression[END_REF]), Peyer's Patches [START_REF] Bonnardel | Innate and Adaptive Immune Functions of Peyer's Patch Monocyte-Derived Cells[END_REF] and peritoneal cavity [START_REF] Miyanishi | Synergistic effect of Tim4 and MFG-E8 null mutations on the development of autoimmunity[END_REF], Rosas et al., 2014;Bain et al., 2016;[START_REF] Kim | MHC II+ resident peritoneal and pleural macrophages rely on IRF4 for development from circulating monocytes[END_REF].

Identification of mo-DC in tissues

Dendritic cells (cDC1, cDC2 and pDCs) are characterized by their ability to present antigens on MHC molecules and to activate naive T cells. They depend on the growth factor Flt3-ligand and develop from CDP progenitor [START_REF] Naik | Development of plasmacytoid and conventional dendritic cell subtypes from single precursor cells derived in vitro and in vivo[END_REF]. However, antigen-presenting cells that originate from monocytes have also been identified at steady state or in inflamatory contexts [START_REF] Bonnardel | Innate and Adaptive Immune Functions of Peyer's Patch Monocyte-Derived Cells[END_REF]Goudot et al., 2017;[START_REF] Kool | Alum adjuvant boosts adaptive immunity by inducing uric acid and activating inflammatory dendritic cells[END_REF][START_REF] León | Monocyte-Derived Dendritic Cells Formed at the Infection Site Control the Induction of Protective T Helper 1 Responses against Leishmania[END_REF][START_REF] Tamoutounour | Origins and functional specialization of macrophages and of conventional and monocyte-derived dendritic cells in mouse skin[END_REF]. These cells have been termed monocyte-derived dendritic cells (mo-DC) and defined by the expression of CD11b, Ly6C, CD11c, MHCII, and/or CD64, CD115, CCR2, CD206.

Recent findings showing that mouse cDC2 upregulate Ly6C and CD64 (classical monocytic markers) upon inflammation have questioned the existence of moDC [START_REF] Bosteels | Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection[END_REF].

These inflammatory cDC2 (infDC2) were described in lung and lung-draining lymph nodes (LN) only during inflammation and their recruitment in the lung was partially dependent on Ccr2. Consistent with this, CD11b + cDC2 depend on CCR2 in the gut and lungs [START_REF] Nakano | Distinct functions of CXCR4, CCR2, and CX3CR1 direct dendritic cell precursors from the bone marrow to the lung[END_REF][START_REF] Scott | CCR2 + CD103 -Intestinal dendritic cells develop from DC-committed precursors and induce interleukin-17 production by T cells[END_REF]. In contrast to moDC, infDC2 do not express CD115, CD88 nor F4/80 (Table 2). So far, the most reliable marker to distinguish moDC from cDC is CD26 [START_REF] Bosteels | Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection[END_REF][START_REF] Guilliams | Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species[END_REF].

Marker mo-DC infDC2 CD115 + - CD88 + - CD26 - + MAR-1 + + CD64 + + CD11b + + CD11c + + MHCII + +
Table 2. Expression of surface markers by mo-DC and infDC2 in mice.

MoDC have been identified at steady state in mucosal tissues. In peritoneal lavage, moDC have been defined as CD11b + CD115 + CD226 + MHCII + CCR2 + (Goudot et al., 2017). This population has been proposed to be mo-Macs [START_REF] Kim | MHC II+ resident peritoneal and pleural macrophages rely on IRF4 for development from circulating monocytes[END_REF] and called small peritoneal macrophages (SPM) elsewhere. However, they rely on IRF4 for development from circulating monocytes [START_REF] Kim | MHC II+ resident peritoneal and pleural macrophages rely on IRF4 for development from circulating monocytes[END_REF] and are able to present antigens to naïve CD4+ T cells [START_REF] Takenaka | Selective DNAM-1 expression on small peritoneal macrophages contributes to CD4+ T cell costimulation[END_REF]. Moreover, these peritoneal CD226 + cells displayed a typical DC morphology, distinct from that of ICAM2 + macrophages (Goudot et al., 2017). Therefore, we have proposed to identify them as moDC based on their markers, morphology, origin and ability to present antigens (Figure 6).

TFs involved in cDC development [START_REF] Ji | MHC class I-restricted myelin epitopes are crosspresented by Tip-DCs that promote determinant spreading to CD8+ T cells[END_REF]. Mo-DC with the ability to present antigens have been also identified in tumor-draining LN [START_REF] Kuhn | Monocyte-derived dendritic cells are essential for CD8+ T cell activation and antitumor responses after local immunotherapy[END_REF]. Moreover, treatment of tumor-bearing mice with chemotherapy favors the differentiation of CD11b + Ly6C + CCR2 + DCs in the tumor. Adoptive transfer experiments showed that these cells derived from monocytic precursors but not CDP, and were able to stimulate efficiently antigen-specific CD8 + T cells ex vivo [START_REF] Ma | Anticancer Chemotherapy-Induced Intratumoral Recruitment and Differentiation of Antigen-Presenting Cells[END_REF][START_REF] Sharma | Activation of p53 in Immature Myeloid Precursor Cells Controls Differentiation into Ly6c+CD103+ Monocytic Antigen-Presenting Cells in Tumors[END_REF]. These data show that monocyte-derived cells with the ability to present antigens are found at steady state and in inflammatory context in mice.

B. Monocytes and monocyte-derived cells in human

Identification of monocytes in situ at homeostasis

There is fewer evidence of monocyte recruitment in human steady-state tissues. CD14 + extravascular monocytes were observed in lung from healthy donors [START_REF] Desch | Flow Cytometric Analysis of Mononuclear Phagocytes in Nondiseased Human Lung and Lung-Draining Lymph Nodes[END_REF]. In the small intestine, a CD14 + population sharing a large proportion of genes with blood monocytes (such as RXRA, S100A8 and CCR2) has been described. Relying on a mismatch in HLA class I between donors and recipients in duodenum transplantation, the authors showed that this population is almost completely replaced by recipient cells after 3 weeks [START_REF] Bujko | Transcriptional and functional profiling defines human small intestinal macrophage subsets[END_REF]. Moreover, during allogeneic hematopoietic stem cell transplantation, donor CD14 + cells reappeared in blood and in normal skin after 8 and 12 days, respectively.

The sequential detection of donor CD14 + cells strongly suggest that blood monocytes infiltrate the skin and give rise to skin CD14 + macrophages [START_REF] Mcgovern | Human dermal CD14+ cells are a transient population of monocytederived macrophages[END_REF]. The presence of bona fide monocytes has also been shown in human spleen [START_REF] Nagelkerke | Red pulp macrophages in the human spleen are a distinct cell population with a unique expression of Fc-γ receptors[END_REF] by the expression of CD14 and morphology analysis.

Identification of monocytes in situ during inflammation

Several studies have shown monocyte recruitment in the context of acute inflammation.

Phenotyping studies have revealed increased CD14 + monocytes after infection in the peritoneal cavity [START_REF] Liao | Peritoneal macrophage heterogeneity is associated with different peritoneal dialysis outcomes[END_REF]. Similarly, CD14 + cell number increased in the nasal mucosa 12 h after allergen challenge with pollen in patients with allergic rhinitis but not in the nonatopic control group (Eguíluz-Gracia et al., 2016a) and in the bronchoalveolar lavage 8 h following LPS inhalation [START_REF] Jardine | Lipopolysaccharide inhalation recruits monocytes and dendritic cell subsets to the alveolar airspace[END_REF]. Furthermore, CD14 + CD16 -and CD14 + CD16 + cells increased in the heart following acute myocardial infarct compared to heart tissue from donors who died of other causes [START_REF] Van Der Laan | Monocyte subset accumulation in the human heart following acute myocardial infarction and the role of the spleen as monocyte reservoir[END_REF].

Monocytes are also recruited during chronic inflammatory diseases. Following injection of radiolabelled monocytes, infiltrating radioactive CD14 + monocytes have been identified in the colon of patients with Crohn's disease (CD) and ulcerative colitis (UC) [START_REF] Grimm | Direct evidence of monocyte recruitment to inflammatory bowel disease mucosa[END_REF] and in joints of rheumatoid arthritis (RA) patients [START_REF] Thurlings | Monocyte Scintigraphy in Rheumatoid Arthritis: The Dynamics of Monocyte Migration in Immune-Mediated Inflammatory Disease[END_REF]. In multiple sclerosis (MS) patients, monocyte infiltration was observed in brain lesions by in vivo labeling of monocytes with ultra small particle iron oxide [START_REF] Dousset | MR imaging of relapsing multiple sclerosis patients using ultra-small-particle iron oxide and compared with gadolinium[END_REF]. Infiltrating monocytes have been also found in the synovial fluid from gouty arthritis patients [START_REF] Jeong | CD14+ cells with the phenotype of infiltrated monocytes consist of distinct populations characterized by anti-inflammatory as well as pro-inflammatory activity in gouty arthritis[END_REF] by the expression of CD14 + CCR2 + CD16 -MerTK -, and in lung [START_REF] Zilionis | Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species[END_REF] breast tumors [START_REF] Azizi | Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment[END_REF] and brain of MS patients [START_REF] Masuda | Spatial and temporal heterogeneity of mouse and human microglia at single-cell resolution[END_REF] by single-cell RNA sequencing (scRNAseq), among others.

These data summarize ample evidence that, similar to mice, human monocytes are recruited into tissues and mucosa at homeostasis and during acute and chronic inflammation.

Monocytes will further differentiate according to the microenvironment and physiological conditions.

Identification of mo-DC and mo-Mac in human

Identification of mo-Mac and mo-DC based on phenotypic markers is a common method.

However, mo-mac and mo-DC share a lot of markers, such as CD14, which makes their phenotypic identification challenging. Mo-mac express MerTK, CD16, CD163, while mo-DC express CD1a, CD1b, FcεRI, and CD226 (Table 3) (Goudot et al., 2017;[START_REF] Rhodes | Human anogenital monocyte-derived dendritic cells and langerin+cDC2 are major HIV target cells[END_REF]Segura et al., 2013). Morphological analysis is another method to distinguish them. Mo-mac are large cells containing many phagocytic vesicles and mo-DC are smaller and display dendrites on their surface [START_REF] Bajpai | The human heart contains distinct macrophage subsets with divergent origins and functions[END_REF][START_REF] Chapuy | Single-Cell Protein and RNA Expression Analysis of Mononuclear Phagocytes in Intestinal Mucosa and Mesenteric Lymph Nodes of Ulcerative Colitis and Crohn's Disease Patients[END_REF][START_REF] Liao | Peritoneal macrophage heterogeneity is associated with different peritoneal dialysis outcomes[END_REF][START_REF] Rhodes | Human anogenital monocyte-derived dendritic cells and langerin+cDC2 are major HIV target cells[END_REF]Tang-Huau et al., 2018). Moreover, transcriptomic approaches can also be used to distinguish mo-Mac from mo-DC, for instance by comparing specific signatures of each cell type in sorted populations or by unbiased single cell clustering (Richter et al., 2018;Tang-Huau et al., 2018;[START_REF] Watchmaker | Comparative transcriptional and functional profiling defines conserved programs of intestinal DC differentiation in humans and mice[END_REF]. Although it is difficult to prove unequivocally that cells phenotypically defined in vivo in human samples have a monocytic origin, the combination of the methods described here can provide strong evidence. Mo-Mac have been identified at steady state in several tissues such as the small intestine [START_REF] Bujko | Transcriptional and functional profiling defines human small intestinal macrophage subsets[END_REF], the skin [START_REF] Mcgovern | Human dermal CD14+ cells are a transient population of monocytederived macrophages[END_REF] and the peritoneal cavity [START_REF] Liao | Peritoneal macrophage heterogeneity is associated with different peritoneal dialysis outcomes[END_REF]. Monocyte differentiation into mo-Mac also occurs in tissues with lower self-renewal capacities such as in the heart [START_REF] Bajpai | The human heart contains distinct macrophage subsets with divergent origins and functions[END_REF], lung [START_REF] Eguíluz-Gracia | Long-term persistence of human donor alveolar macrophages in lung transplant recipients[END_REF]liver (MacParland et al., 2018). On the other hand, mo-DC at steady state are mainly described in the intestine and peritoneum. Intestinal SIRPa + CD103 -DCs [START_REF] Watchmaker | Comparative transcriptional and functional profiling defines conserved programs of intestinal DC differentiation in humans and mice[END_REF] and (Richter et al., 2018) are transcriptionally related to blood monocytes. CCR2 + CD1c + DC were also evidenced in the peritoneum at steady-state [START_REF] Liao | Peritoneal macrophage heterogeneity is associated with different peritoneal dialysis outcomes[END_REF]. Finally, CD14 + CD1c + cells resembling Mo-DC have been found in the skin [START_REF] Mcgovern | Human dermal CD14+ cells are a transient population of monocytederived macrophages[END_REF][START_REF] Rhodes | Human anogenital monocyte-derived dendritic cells and langerin+cDC2 are major HIV target cells[END_REF]. They were absent in monocyte deficiency states, renewed after hematopoietic transplantation and were similar to monocytes in short-term culture with endothelial cells [START_REF] Mcgovern | Human dermal CD14+ cells are a transient population of monocytederived macrophages[END_REF]. These data demonstrate that monocytederived cells can be found in vivo in steady state tissues.

SIRPa + CD103 -CD14 + S100A8/9 + DCs
Phenotypic and scRNAseq analysis have suggested the presence of mo-DC in several inflammatory contexts. For instance, "inflammatory" DC were found in skin of atopic dermatitis and psoriasis patients expressing CD1a et al., 2018) and in colorectal and breast tumors [START_REF] Laoui | The tumour microenvironment harbours ontogenically distinct dendritic cell populations with opposing effects on tumour immunity[END_REF][START_REF] Michea | Adjustment of dendritic cells to the breast-cancer microenvironment is subset specific[END_REF].

Combined phenotypic and transcriptomic analysis revealed moDC occurring in lung cancer [START_REF] Laoui | The tumour microenvironment harbours ontogenically distinct dendritic cell populations with opposing effects on tumour immunity[END_REF][START_REF] Lavin | Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses[END_REF][START_REF] Zilionis | Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species[END_REF] and peritoneal ascites from ovarian cancer patients, expressing HLA-DR Tang-Huau et al., 2018).

+ CD11c + CD1c + CD16 -(
Moreover, in inflamed gut of CD patients, CD14 + CD163 -MerTK -cells exhibited a typical DC morphology and signatures of monocyte lineage, suggesting they correspond to mo-DC [START_REF] Chapuy | Two distinct colonic CD14+ subsets characterized by single-cell RNA profiling in Crohn's disease[END_REF]. Collectively, these observations relying on phenotypic, morphological and transcriptomic analysis support the notion that human monocytes can differentiate in vivo into both macrophages and DC.

One major weakness of culture systems is the need for an a priori knowledge of the cytokines to use, which potentially influence the outcome of the culture and can bias fate decisions of the progenitors.

While in vitro culture can provide definitive evidence of the differentiation potential of a putative progenitor, it remains unclear which in vitro system better recapitulates the in vivo differentiation of human monocytes. Caution should be taken to evaluate how closely the cells obtained in vitro resemble the in vivo-generated ones. In particular, our lab found by using transcriptomic profiling and functional assays that human mo-DC in peritoneal tumor ascites (Segura et al., 2013;Tang-Huau et al., 2018) do not closely resemble the mo-DC that can be obtained in vitro with GM-CSF and IL-4 (Goudot et al., 2017). In addition, this culture system only yields mo-DC, with some heterogeneity (Sander et al., 2017), but not bona fide macrophages. We use a protocol to simultaneously differentiate monocytes into mo-Mac and mo-DC in the same culture. Mo-DC obtained in this culture system can mimic the mo-DC found in peritoneal ascites from tumor patients and synovial fluid from rheumatoid arthritis patients, in terms of phenotype, transcriptome and functional properties (Goudot et al., 2017).

A strength of in vitro cultures is the fact that it allows the manipulation of the system to address the role/importance of candidate molecules in monocyte differentiation. An example is the silencing of TFs in human progenitors (Goudot et al., 2017;Poulin et al., 2012;Schotte et al., 2004).

b. Transcriptomic analysis

RNA sequencing of bulk samples or single cells allows an unbiased comparison of monocyte subpopulations or different cell states. scRNAseq can be used to identify rare populations in unmanipulated patient samples. When several cellular states are present simultaneously in a sample, scRNAseq data can inform on developmental pathways by analyzing trajectory inference in a pseudo-time. However, results can significantly vary according to the

c. Human immunodeficiencies

Genetic studies of human primary immunodeficiencies allow to define the contribution of specific proteins in the development of immune cells. The main advantage of this approach is that it does not require any manipulation neither a priori knowledge to establish the relationship. Although the identification of patients clearly limits the use of this method, it has been successful in demonstrating the role of several TFs in the differentiation towards cDC, pDC and monocytes (Bigley et al., 2018;Cisse et al., 2008;Cytlak et al., 2018;Dickinson et al., 2011;Hambleton et al., 2011).

Molecular regulators of monocyte differentiation

Monocyte fate is not transcriptionally imprinted (Goudot et al., 2017;[START_REF] Mildner | Genomic Characterization of Murine Monocytes Reveals C/EBPβ Transcription Factor Dependence of Ly6C-Cells[END_REF].

Instead, monocytes respond to micro-environmental cues that can redirect their fate. The expression of a mo-DC differentiation program require IL-4 signalling (Sander et al., 2017;[START_REF] Vento-Tormo | IL-4 orchestrates STAT6-mediated DNA demethylation leading to dendritic cell differentiation[END_REF] and can be fostered by a variety of signals such as nucleotidebinding oligomerization domain (NOD) ligands, TNF-α autocrine secretion (Coillard et al., 2021) and miRNA expression. Both, miR-155 (Coillard et al., 2021) and miR-148a [START_REF] Meng | MicroRNA-148a facilitates inflammatory dendritic cell differentiation and autoimmunity by targeting MAFB[END_REF] have been shown to promote mo-DC by targeting MAFB, a master regulator of human mo-mac differentiation (Goudot et al., 2017). Furthermore, retinoic acid was shown to skew monocyte differentiation in tumors towards mo-mac rather than mo-DC, by regulating the key transcription factor Irf4 [START_REF] Devalaraja | Tumor-Derived Retinoic Acid Regulates Intratumoral Monocyte Differentiation to Promote Immune Suppression[END_REF]. Similarly, toll-like receptor ligands increased mo-mac differentiation via mTORC1 (Coillard et al., 2021).

Transcription factors involved in human mo-DC differentiation include IRF4, aryl hydrocarbon receptor (AhR), BLIMP-1 and the nuclear receptor corepressor 2 (NCOR2) (Goudot et al., 2017;Sander et al., 2017). In mice models, additional molecules have been shown to regulate

Ly6C high monocyte differentiation. For instance, in the peritoneal cavity, Bhlhe40 -/-mice have decreased number of CD226 + mo-DC and Tim4 + resident macrophages, but not Tim4 -mo-mac [START_REF] Jarjour | Bhlhe40 mediates tissue-specific control of macrophage proliferation in homeostasis and type 2 immunity[END_REF]. Nr4a3 was also shown to control mo-DC differentiation, in response to LPS but not at steady-state [START_REF] Boulet | The orphan nuclear receptor NR4A3 controls the differentiation of monocyte-derived dendritic cells following microbial stimulation[END_REF]. In renal inflammation, the acquisition of MHCII and F4/80 expression by monocytes (suggesting differentiation into mo-mac or moDC) was shown to be Ccr2-dependent and occurred already within the inflamed renal vasculature before monocytes extravasated into the tissue [START_REF] Mysore | Monocytes transition to macrophages within the inflamed vasculature via monocyte CCR2 and endothelial TNFR2[END_REF]. Moreover, the differentiation of Ly6C low monocytes from Ly6C high monocytes was shown to be controlled by the survival factor Nr4a1 [START_REF] Hanna | The transcription factor NR4A1 (Nur77) controls bone marrow differentiation and the survival of Ly6C-monocytes[END_REF], which in turn is regulated by C/EBPb [START_REF] Mildner | Genomic Characterization of Murine Monocytes Reveals C/EBPβ Transcription Factor Dependence of Ly6C-Cells[END_REF]. Cell-intrinsic Notch2 and TLR7 signalling was also shown to promote the development of Ly6C low monocytes from Ly6C high monocytes [START_REF] Gamrekelashvili | Notch and TLR signaling coordinate monocyte cell fate and inflammation[END_REF].

All together, these data indicate a transcriptional regulation of monocyte differentiation towards distinct fates. Despite this recent progress, what controls the balance of monocyte differentiation into mo-Mac versus mo-DC remains poorly described.

Chapter 3. Role of monocyte-derived cells

Mo-DC and mo-mac can perform analogue functions to their classical counterparts. Mo-DC are able to present antigens as cDC, while mo-Mac participate in tissue repair after tissue injury (Coillard and Segura, 2019). However, they also possess unique features that I will detail below.

A. Cytokine secretion

Cytokines are essential for the recruitment of immune cells at inflamed sites and for the initiation of immune responses. Both Mo-Mac and mo-DC have been shown to be very efficient at producing pro-inflammatory cytokines such as TNFα and IL-1β. In particular, mo-mac but not TRM secrete high levels of TNFα [START_REF] Bujko | Transcriptional and functional profiling defines human small intestinal macrophage subsets[END_REF][START_REF] González-Domínguez | CD163L1 and CLEC5A discriminate subsets of human resident and inflammatory macrophages in vivo[END_REF][START_REF] Kamada | Unique CD14+ intestinal macrophages contribute to the pathogenesis of Crohn disease via IL-23/IFN-γ axis[END_REF], while mo-DC produce high levels of IL-1β [START_REF] Bajpai | The human heart contains distinct macrophage subsets with divergent origins and functions[END_REF][START_REF] Michea | Adjustment of dendritic cells to the breast-cancer microenvironment is subset specific[END_REF] and IL-23 [START_REF] Chapuy | Two distinct colonic CD14+ subsets characterized by single-cell RNA profiling in Crohn's disease[END_REF]. A few studies have also shown the production of the anti-inflammatory cytokine IL-10 by mo-Mac in inflammation contexts [START_REF] Bajpai | The human heart contains distinct macrophage subsets with divergent origins and functions[END_REF][START_REF] González-Domínguez | CD163L1 and CLEC5A discriminate subsets of human resident and inflammatory macrophages in vivo[END_REF][START_REF] Kamada | Unique CD14+ intestinal macrophages contribute to the pathogenesis of Crohn disease via IL-23/IFN-γ axis[END_REF]. These observations highlight the ability of monocyte-derived cells to facilitate the immune response by secreting key cytokines for T cell activation or for recruitment of other immune cells.

B. T cell polarization

As I previously described, there is ample evidence that monocyte-derived cells are able to present antigen to T cells [START_REF] Estrada-Capetillo | Induction of Th17 lymphocytes and treg cells by monocyte-derived dendritic cells in patients with rheumatoid arthritis and systemic lupus erythematosus[END_REF][START_REF] Ko | GM-CSF-Responsive Monocyte-Derived Dendritic Cells Are Pivotal in Th17 Pathogenesis[END_REF][START_REF] Panea | Intestinal Monocyte-Derived Macrophages Control Commensal-Specific Th17 Responses[END_REF]Segura et al., 2013). Specifically, mo-DC have been shown to promote Th17 polarization in human and mouse models. For instance, in vitro-generated mo-DC from rheumatoid arthritis patients triggered Th17 and Th17/Th1 T cell activation in vitro through the secretion of IL-6 and IL-23 (Estrada-Capetillo et al., 2013). Moreover, in vivo-generated mo-DC from tumor ascites induced Th17 cells from autologous CD4 + T cells (Segura et al., 2013). Th17 cells are critical for mucosal immunity. By genetic ablation of different myeloid cells, [START_REF] Panea | Intestinal Monocyte-Derived Macrophages Control Commensal-Specific Th17 Responses[END_REF] showed that intestinal CD64 + monocyte-derived cells but not cDC are required for Th17 polarization induced by commensal bacteria in the intestine. In addition, human mo-DC found in inflammatory fluids have been shown to induce CD4 + T follicular helper (Tfh) polarization [START_REF] Durand | Human lymphoid organ cDC2 and macrophages play complementary roles in T follicular helper responses[END_REF]. Some studies also indicate that mo-DC are able to perform crosspresentation. Indeed, mouse mo-DC can activate CD8 + T cells in tumor context [START_REF] Ma | Anticancer Chemotherapy-Induced Intratumoral Recruitment and Differentiation of Antigen-Presenting Cells[END_REF]. Furthermore, human mo-DC and mo-mac from tumor ascites are able to cross-present antigens ex vivo (Tang-Huau et al., 2018). In this setting, however, only mo-DC induced effector cytotoxic CD8 + T cells (Tang-Huau et al., 2018). These studies show that monocytederived cells possess distinct T cell polarizing properties, which may be complementary to that of cDCs.

C. Mo-DC as in situ antigen-presenting cells

Contrary to cDCs, monocyte-derived cells have been shown to have a low migratory capacity.

Several studies have failed to detect migratory mo-DC in lymph nodes, even if their setting does not allow to distinguish infDC2 from moDCs [START_REF] Aldridge | TNF/iNOS-producing dendritic cells are the necessary evil of lethal influenza virus infection[END_REF][START_REF] Langlet | CD64 Expression Distinguishes Monocyte-Derived and Conventional Dendritic Cells and Reveals Their Distinct Role during Intramuscular Immunization[END_REF][START_REF] Lim | Circulating CD1c+ myeloid dendritic cells are potential precursors to LCH lesion CD1a+CD207+ cells[END_REF][START_REF] Plantinga | Conventional and Monocyte-Derived CD11b+ Dendritic Cells Initiate and Maintain T Helper 2 Cell-Mediated Immunity to House Dust Mite Allergen[END_REF]. Moreover, in a model of lung infection, only inflammatory cDC2 were found in draining lymph nodes, while monocyte-derived cells did not migrate [START_REF] Bosteels | Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection[END_REF]. Despite this, mo-DC have been observed in lymphoid organs [START_REF] Langlet | CD64 Expression Distinguishes Monocyte-Derived and Conventional Dendritic Cells and Reveals Their Distinct Role during Intramuscular Immunization[END_REF][START_REF] Nakano | Migratory properties of pulmonary dendritic cells are determined by their developmental lineage[END_REF]. These cells were independent of Ccr7, the chemokine receptor expressed in DC required for migration, suggesting that they originated from monocytes recruited from the bloodstream rather than from migratory mo-DC from tissues.

Several lines of evidence support a role for mo-DCs in the activation of effector T cells locally in peripheral tissues. For instance, mo-DCs were identified as the antigen-presenting cells in tumors of chemotherapy-treated mice, where surgical removal of draining lymph nodes did not abolish CD8 + T cells activation [START_REF] Ma | Anticancer Chemotherapy-Induced Intratumoral Recruitment and Differentiation of Antigen-Presenting Cells[END_REF]. In addition, Ccr2-dependent DCs were dispensable for priming CD4 + T cells but were involved in the in situ re-stimulation of effector

Th1 cells in a model of vaginal infection [START_REF] Iijima | Recruited inflammatory monocytes stimulate antiviral Th1 immunity in infected tissue[END_REF]. Mo-DCs can also allow the activation of tissue-resident memory T cells. In experimental herpes virus reactivation, peripheral tissues of a previously infected mouse were transplanted into a naïve mouse. Donor virus-specific CD4 + and CD8 + T cells proliferated locally and were not found recirculating in the host mouse. This phenomenon was dependent on recruited host mo-DCs [START_REF] Wakim | Dendritic cellinduced memory T cell activation in nonlymphoid tissues[END_REF]. In humans, skin CD14 + cells were potent inducers of memory T cell response but poor stimulators of naive T cells, and their spontaneous migration did not occur via lymphatic vessels [START_REF] Mcgovern | Human dermal CD14+ cells are a transient population of monocytederived macrophages[END_REF]. Collectively, these data support a model in which mo-DCs would present antigens in peripheral tissues to strengthen effector and memory functions or to boost already primed T cells.

D. Mo-mac versus TRM

Prenatally developed TRM and monocyte-derived tissue macrophages (that I call mo-mac) play distinct roles in tissue immunity. Mo-mac exhibit a more robust inflammatory response while TRM are in charge of pathogen clearance and niche replenishment [START_REF] Watanabe | The role of macrophages in the resolution of inflammation[END_REF]. In an endometriosis model, peritoneal macrophages were recruited to injury sites.

Ccr2 -/-mice had more lesions than WT mice, suggesting a protective role of mo-mac but not TRM [START_REF] Hogg | Macrophages inhibit and enhance endometriosis depending on their origin[END_REF]. During the resolution phase of EAE, it has been reported that momac possess anti-inflammatory features such as Arg1 expression, unlike resident microglia [START_REF] Giles | Myeloid cell plasticity in the evolution of central nervous system autoimmunity[END_REF][START_REF] Greenhalgh | Arginase-1 is expressed exclusively by infiltrating myeloid cells in CNS injury and disease[END_REF]Locatelli et al., 2018a). In the liver, Sierro et al., 2017 described a population of resident mo-mac located in the hepatic capsule, distinct from Kupffer cells. These cells prevented peritoneal-bacterial infections by recruiting neutrophils.

Furthermore, monocyte-derived alveolar macrophages (AM) were identified in post-influenza mice lungs [START_REF] Aegerter | Influenza-induced monocyte-derived alveolar macrophages confer prolonged antibacterial protection[END_REF]. Although phenotypically undistinguishable from embryonic AM, these cells had a distinct transcriptomic and chromatin profile, and protected mice from subsequent bacterial infections by secreting IL-6 [START_REF] Aegerter | Influenza-induced monocyte-derived alveolar macrophages confer prolonged antibacterial protection[END_REF]. The same phenomenon was described previously with gamma-herpesvirus infection, conferring protection against allergic asthma [START_REF] Machiels | A gammaherpesvirus provides protection against allergic asthma by inducing the replacement of resident alveolar macrophages with regulatory monocytes[END_REF]. Finally, resident CCR2 -and monocyte-derived CCR2 + macrophages have been described in the human heart, analogous to mice [START_REF] Bajpai | The human heart contains distinct macrophage subsets with divergent origins and functions[END_REF]. The former posses reparative functions while mo-mac display pro-inflammatory features [START_REF] Bajpai | The human heart contains distinct macrophage subsets with divergent origins and functions[END_REF]. These data show that mo-mac and TRM play distinct roles in the immune response in several tissues, mo-Mac being more pro-inflammatory or more reparative depending on the context.

E. Deleterious role of monocytes-derived cells

Besides the physiological role of monocyte-derived cells detailed above, they have been involved in some pathological contexts. For instance, uncontrolled or exacerbated cytokine secretion by monocyte-derived cells, and/or stimulation of pathogenic T cells by moDC are major drivers of the physiopathology of diseases such as Crohn's disease [START_REF] Kamada | Unique CD14+ intestinal macrophages contribute to the pathogenesis of Crohn disease via IL-23/IFN-γ axis[END_REF], colitis [START_REF] Arnold | CD11c+ monocyte/macrophages promote chronic Helicobacter hepaticus-induced intestinal inflammation through the production of IL-23[END_REF][START_REF] Zigmond | Ly6Chi Monocytes in the Inflamed Colon Give Rise to Proinflammatory Effector Cells and Migratory Antigen-Presenting Cells[END_REF]), psoriasis (LC et al., 2009), rheumatoid arthritis [START_REF] Evans | In vivo activated monocytes from the site of inflammation in humans specifically promote Th17 responses[END_REF]Segura et al., 2013) and MS. Concerning mo-Mac, their reparative properties become deleterious in cancer. Here, I will focus on the role of mo-mac in tumor immune evasion and of mo-DC in the physiopathology of MS-like disease.

Mo-mac in cancer

Macrophages are an abundant population in the tumor microenvironment. There is ample evidence that they promote tumorigenesis, supported also by clinical data showing inverse correlation between macrophages numbers and prognosis [START_REF] Noy | Tumor-Associated Macrophages: From Mechanisms to Therapy[END_REF]. Pioneer studies showed that these macrophages arise from circulating monocytes [START_REF] Franklin | The cellular and molecular origin of tumor-associated macrophages[END_REF][START_REF] Movahedi | Different tumor microenvironments contain functionally distinct subsets of macrophages derived from Ly6C(high) monocytes[END_REF] and are educated in the tumor to become pro-tumoral mo-mac.

Recent scRNAseq studies of myeloid cells in glioma and carcinoma suggested that the transition of monocytes to mo-mac is dictated by the type of tumor rather than a general behaviour of monocytes [START_REF] Friebel | Single-Cell Mapping of Human Brain Cancer Reveals Tumor-Specific Instruction of Tissue-Invading Leukocytes[END_REF][START_REF] Klemm | Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells[END_REF]. Consistent with this, sarcoma tumor cells have been shown to skew monocyte differentiation toward mo-mac by secreting retinoic acid [START_REF] Devalaraja | Tumor-Derived Retinoic Acid Regulates Intratumoral Monocyte Differentiation to Promote Immune Suppression[END_REF]. Blocking retinoic acid improved antigen presentation and inhibited tumor progression [START_REF] Devalaraja | Tumor-Derived Retinoic Acid Regulates Intratumoral Monocyte Differentiation to Promote Immune Suppression[END_REF]. Mo-mac have been also identified in metastatic sites. Indeed, tumor cells were shown to secrete CCL2 which allowed monocyte recruitment to metastatic sites [START_REF] Qian | CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis[END_REF]. Tumor CCL2 depletion prevented metastatic seeding [START_REF] Qian | CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis[END_REF]. Finally, IL4R expression in monocytes and macrophages was shown to be essential for bone metastasis in a breast cancer model (Ma et al., 2020). Overall, these data indicate that in a tumoral context, mo-mac play a central role in dampening the immune response and promoting metastasis.

Furthermore, recent studies have reported distinct roles for TRM and mo-Mac in tumor microenvironment. Resident FOLR2 + macrophages were identified interacting with CD8 + T cells in breast tumor samples and their density directly correlated with better patient survival [START_REF] Nalio Ramos | Tissue-resident FOLR2+ macrophages associate with CD8+ T cell infiltration in human breast cancer[END_REF]. By contrast, in glioblastoma, resident tumor microglia was more efficient than mo-mac to suppress T cell proliferation, and was more abundant than mo-mac in newly diagnosed tumors [START_REF] Pombo Antunes | Single-cell profiling of myeloid cells in glioblastoma across species and disease stage reveals macrophage competition and specialization[END_REF]. Moreover, resident macrophages identified in non-small cell lung carcinoma lesions were shown to promote tumour invasiveness and induce regulatory T cells that protected the tumor from adaptive immunity [START_REF] Casanova-Acebes | Tissue-resident macrophages provide a protumorigenic niche to early NSCLC cells[END_REF]. Indeed, their depletion reduced tumor burden and increased T cell infiltration [START_REF] Casanova-Acebes | Tissue-resident macrophages provide a protumorigenic niche to early NSCLC cells[END_REF]. Of note, mo-mac were similarly efficient at promoting regulatory T cells. However, the authors propose that TRM participate in early tumorigenesis when the tumor just seeds. Although it is not clear whether the role of TRM is conserved across tumor types and tissues, these data show that resident macrophages and mo-mac co-exist in the tumor microenvironment and may perform distinct functions during tumorigenesis.

Mo-DCs in experimental autoimmune encephalomyelitis

EAE is a well studied mouse model of the human disease MS. To induce the disease, mice are immunized with a myelin antigen, such as myelin oligodendrocyte glycoprotein (MOG), which results in the priming of myelin-specific CD4 + T cells in peripheral lymphoid organs [START_REF] Shemer | Differential roles of resident microglia and infiltrating monocytes in murine CNS autoimmunity[END_REF]. These myelin-specific T cells are thought to polarize toward Th1

and Th17 cells and home to the brain and spinal cord were they require re-activation by local myeloid cells for full pathogenesis [START_REF] Miller | Antigen presentation in the CNS by myeloid dendritic cells drives progression of relapsing experimental autoimmune encephalomyelitis[END_REF]. These events will further trigger axon demyelination and neuronal loss ultimately resulting in a loss of mobility of the tail and limbs of the mice [START_REF] Shemer | Differential roles of resident microglia and infiltrating monocytes in murine CNS autoimmunity[END_REF].

Monocytes and monocyte-derived cells have been implicated in the disease pathogenesis.

Blockade or genetic deletion of Ccr2 or its ligand prevents severe symptoms or confers resistance to the disease depending on strains, as observed in Figure 9 [START_REF] Ajami | Infiltrating monocytes trigger EAE progression, but do not contribute to the resident microglia pool[END_REF][START_REF] Fife | Cc Chemokine Receptor 2 Is Critical for Induction of Experimental Autoimmune Encephalomyelitis[END_REF][START_REF] Gaupp | Experimental autoimmune encephalomyelitis (EAE) in CCR2(-/-) mice: susceptibility in multiple strains[END_REF][START_REF] Huang | Absence of Monocyte Chemoattractant Protein 1 in Mice Leads to Decreased Local Macrophage Recruitment and Antigen-Specific T Helper Cell Type 1 Immune Response in Experimental Autoimmune Encephalomyelitis[END_REF][START_REF] Izikson | Resistance to Experimental Autoimmune Encephalomyelitis in Mice Lacking the Cc Chemokine Receptor (Ccr2)[END_REF]Mildner et al.,

Monocyte-derived cells as therapeutic targets

Due to the key role of monocyte-derived cells in several pathologies, monocytes have emerged as potential therapeutic targets to prevent the generation of mo-DC in autoimmune disorders such as multiple sclerosis, Crohn's disease or rheumatoid arthritis, or of mo-Mac during cancer therapy or allograph rejection.

A common strategy used in mouse models is to block monocyte recruitment. For instance, pharmacological inhibition of CCL2 synthesis suppresses the development of colitis [START_REF] Bhatia | Treatment with bindarit, an inhibitor of MCP-1 synthesis, protects mice against trinitrobenzene sulfonic acid-induced colitis[END_REF] and the severity of EAE [START_REF] Ge | The CCL2 synthesis inhibitor bindarit targets cells of the neurovascular unit, and suppresses experimental autoimmune encephalomyelitis[END_REF]. M-CSF receptor blockade impairs monocyte survival and differentiation, which reduced inflammation in arthritis [START_REF] Garcia | Colony-stimulating factor (CSF) 1 receptor blockade reduces inflammation in human and murine models of rheumatoid arthritis[END_REF][START_REF] Toh | Bone-and Cartilage-Protective Effects of a Monoclonal Antibody Against Colony-Stimulating Factor 1 Receptor in Experimental Arthritis[END_REF]. Mo-mac have been also shown to induce allograft rejection after transplantation [START_REF] Braza | Inhibiting Inflammation with Myeloid Cell-Specific Nanobiologics Promotes Organ Transplant Acceptance[END_REF]. Treatment with a short-term inhibitor of mTOR prevented the differentiation of monocytes into inflammatory mo-mac, decreasing the activation of CD8 + T cell, promoting regulatory T cell expansion and as consequence, allowing organ transplant acceptance [START_REF] Braza | Inhibiting Inflammation with Myeloid Cell-Specific Nanobiologics Promotes Organ Transplant Acceptance[END_REF]. These findings provide a proof-of-concept for targeting monocytes in immune disorders. However, a major caveat of these approaches is the potential adverse effects due to disrupted differentiation of mo-Mac, which are also involved in the resolution of inflammation. Blockade of the M-CSF receptor was reported to impair cardiac repair [START_REF] Leblond | Systemic and Cardiac Depletion of M2 Macrophage through CSF-1R Signaling Inhibition Alters Cardiac Function Post Myocardial Infarction[END_REF] and skeletal muscle regeneration [START_REF] Segawa | Suppression of macrophage functions impairs skeletal muscle regeneration with severe fibrosis[END_REF].

Manipulating monocyte fate commitment selectively towards mo-DC or mo-Mac would provide an attractive alternative strategy. This was illustrated in the tumor context by [START_REF] Devalaraja | Tumor-Derived Retinoic Acid Regulates Intratumoral Monocyte Differentiation to Promote Immune Suppression[END_REF]. They could skew monocyte differentiation towards mo-DC by intratumoral inhibition of the retinoic acid receptor, which significantly synergized with anti-PD1 treatment for reducing tumor volume. To further develop this strategy in inflammatory diseases, it would require a better understanding of the molecular regulators orchestrating monocyte fate decision.

Chapter 4. Objectives

Monocytes and monocyte-derived cells are central players in the initiation and resolution of inflammatory responses. In chronic inflammatory diseases, monocyte-derived cells become major drivers of the physiopathology by stimulating pathogenic T cells. Blocking monocyte differentiation therefore represents a promising therapeutic strategy. A major hurdle is the paucity of molecular targets, due to limited knowledge of the molecular regulation of monocyte fate commitment. The objective of my thesis is to identify new regulators of monocyte differentiation using two complementary approaches:

1. A candidate-based approach, built on previous work of the group.

Comparative transcriptomic analysis revealed several transcription factors differentially expressed between mo-DC and mo-mac. In this project, I focused on ETV3 and ETV6, transcriptional repressors that are highly expressed in mo-DCs. Their role in monocyte differentiation was unknown.

2. An unbiased approach using single-cell-RNAseq analysis.

The molecular pathways of human monocyte differentiation are frequently analyzed from already differentiated cells, either mo-DC or mo-mac. To analyze the dynamics of monocyte differentiation at earlier stages, I performed scRNAseq experiments at different time points using an in vitro model of differentiation. I then conducted bioinformatics analysis to determine the developmental trajectories of differentiating monocytes and discover new molecular pathways that regulate monocyte commitment.

Results

Chapter 1. ETV3 and ETV6 enable monocyte differentiation into dendritic cells during inflammation by repressing interferonstimulated genes

Javiera Villar

Introduction

Monocytes and monocyte-derived cells are central players in the initiation and resolution of inflammatory responses. In chronic inflammatory diseases, monocyte-derived antigenpresenting cells become major drivers of the physiopathology by stimulating pathogenic T cells. Blocking monocyte differentiation therefore represents an attractive therapeutic strategy.

A major hurdle is the paucity of molecular targets, due to a limited knowledge of the molecular regulation of monocyte fate commitment.

Circulating monocytes infiltrate mucosal or inflamed tissues where they differentiate into macrophages (mo-Mac) or dendritic cells (mo-DC) (Coillard and Segura, 2019;[START_REF] Guilliams | Developmental and Functional Heterogeneity of Monocytes[END_REF][START_REF] Jakubzick | Monocyte differentiation and antigenpresenting functions[END_REF]. Mo-Macs are generally involved in homeostasis and tissue repair, while mo-DC present antigens to T cells directly in tissues. However, in chronic nonresolving inflammation, T cell stimulation by mo-DC becomes deleterious. In Crohn's disease, rheumatoid arthritis and psoriasis, mo-DC secrete high amounts of IL-23 and stimulate Th17 cells, two major drivers of the physiopathology [START_REF] Evans | In vivo activated monocytes from the site of inflammation in humans specifically promote Th17 responses[END_REF][START_REF] Kamada | Unique CD14+ intestinal macrophages contribute to the pathogenesis of Crohn disease via IL-23/IFN-γ axis[END_REF][START_REF] Lc | Psoriasis is characterized by accumulation of immunostimulatory and Th1/Th17 cell-polarizing myeloid dendritic cells[END_REF]Segura et al., 2013). In mouse models, mo-DC induce pathogenic T cells that mediate tissue damage in experimental autoimmune encephalomyelitis (EAE) [START_REF] Croxford | The Cytokine GM-CSF Drives the Inflammatory Signature of CCR2+ Monocytes and Licenses Autoimmunity[END_REF] and colitis [START_REF] Arnold | CD11c+ monocyte/macrophages promote chronic Helicobacter hepaticus-induced intestinal inflammation through the production of IL-23[END_REF][START_REF] Zigmond | Ly6Chi Monocytes in the Inflamed Colon Give Rise to Proinflammatory Effector Cells and Migratory Antigen-Presenting Cells[END_REF]. Blocking monocyte differentiation has therefore emerged as a potential therapeutic strategy for inflammatory disorders. Pharmacological inhibition of monocyte recruitment suppresses the development of colitis [START_REF] Bhatia | Treatment with bindarit, an inhibitor of MCP-1 synthesis, protects mice against trinitrobenzene sulfonic acid-induced colitis[END_REF] and the severity of EAE [START_REF] Ge | The CCL2 synthesis inhibitor bindarit targets cells of the neurovascular unit, and suppresses experimental autoimmune encephalomyelitis[END_REF]. Inducing monocyte apoptosis with nanoparticles reduces inflammation and disease symptoms in colitis, EAE, peritonitis and virus-induced encephalitis [START_REF] Getts | Therapeutic Inflammatory Monocyte Modulation Using Immune-Modifying Microparticles[END_REF]. Finally, impairing monocyte survival and differentiation via M-CSF receptor blockade reduces inflammation in arthritis [START_REF] Garcia | Colony-stimulating factor (CSF) 1 receptor blockade reduces inflammation in human and murine models of rheumatoid arthritis[END_REF][START_REF] Toh | Bone-and Cartilage-Protective Effects of a Monoclonal Antibody Against Colony-Stimulating Factor 1 Receptor in Experimental Arthritis[END_REF]. However, a major caveat of these approaches is the potential adverse effects due to disrupted differentiation of mo-Mac, which are involved in the resolution of inflammation. Blockade of the M-CSF receptor was reported to impair cardiac repair [START_REF] Leblond | Systemic and Cardiac Depletion of M2 Macrophage through CSF-1R Signaling Inhibition Alters Cardiac Function Post Myocardial Infarction[END_REF] and skeletal muscle regeneration [START_REF] Segawa | Suppression of macrophage functions impairs skeletal muscle regeneration with severe fibrosis[END_REF].

Manipulating monocyte fate commitment towards mo-DC versus mo-Mac would therefore provide an attractive alternative strategy. This would require a better understanding of the molecular regulators orchestrating monocyte fate decision.

Monocyte fate is not transcriptionally imprinted (Goudot et al., 2017;[START_REF] Mildner | Genomic Characterization of Murine Monocytes Reveals C/EBPβ Transcription Factor Dependence of Ly6C-Cells[END_REF].

Instead, monocytes respond to micro-environmental cues that can redirect their fate. Using in vitro models of human monocyte differentiation, we and others have shown that IL-4 signaling is essential to induce mo-DC differentiation (Goudot et al., 2017;Sander et al., 2017).

Transcription factors involved in this process include IRF4, aryl hydrocarbon receptor, BLIMP-1 and the nuclear receptor corepressor 2 (NCOR2) (Goudot et al., 2017;Sander et al., 2017).

What controls the balance of monocyte differentiation into mo-Mac versus mo-DC remains unclear.

In this study, we have identified ETV3 and ETV6 as important regulators of mo-DC differentiation and repressors of monocyte differentiation into macrophages. We provide evidence that ETV3 and ETV6 repress interferon stimulated genes (ISG) expression.

Moreover, we show that activation of STAT1 signaling promotes mo-Mac via the inhibition of the IL4-induced mo-DC differentiation program. Finally, we validate the role of ETV6 in monocytes for in vivo ISG repression, by analyzing single-cell transcriptomic data from ETV6 mutated patients and in mice deficient for Etv6 in monocytes. We further show that Etv6 in monocytes is required for mo-DC differentiation in a model of inflammatory peritonitis, and modulates the severity of symptoms in a model of neuro-inflammation. By enabling a better understanding of the molecular ontogeny of monocyte-derived cells, our results provide new opportunities for the therapeutic manipulation of monocyte differentiation.

Results

ETV3 and ETV6 are more expressed in human mo-DCs than mo-Macs in vitro and in vivo

We hypothesized that transcription factors differentially expressed between mo-DC and mo-Mac could be involved in their differentiation from monocytes. Our transcriptomic analysis of monocyte-derived cells from clinical samples identified ETV3 and ETV6 as potential candidates (Goudot et al., 2017). To assess ETV3 and ETV6 expression, we used our transcriptomics data from cells naturally occurring in vivo in peritoneal ascites (Goudot et al., 2017). ETV3 and ETV6 were more expressed in in vivo mo-DC when compared to mo-Mac (Figure 1A). To address their potential role in monocyte differentiation, we employed our previously published in vitro model allowing the simultaneous differentiation of mo-mac and mo-DC (Goudot et al., 2017). In this model, human monocytes cultured for 5-6 days with M-CSF, IL-4 and TNF-α differentiate into mo-mac (CD16+), mo-DC (CD1a+) or remain undifferentiated (double negative cells). To validate the differential expression of ETV3 and ETV6 in in vitro-generated mo-DC and mo-Mac, we measured their expression in sorted mo-DC and mo-Mac after differentiation. Both transcription factors were more expressed in mo-DCs compared to mo-Macs at the mRNA (Figure 1A) and the protein level (Figure 1B).

ETV3 and ETV6 are essential for human mo-DC differentiation

To address the role of ETV3 or ETV6 in monocyte fate commitment, we silenced their expression using a lentivirus expressing a shRNA against ETV3, ETV6 or a scramble sequence. We assessed the effect of silencing on monocyte differentiation after 5 days by staining for phenotypic markers of moDC (CD1a) and moMac (CD16). We used three different

ETV3 and ETV6 repress mo-Mac transcriptional program and differentiation

ETV3 and ETV6 are transcriptional repressors [START_REF] Klappacher | An induced Ets repressor complex regulates growth arrest during terminal macrophage differentiation[END_REF][START_REF] Lopez | TEL is a sequence-specific transcriptional repressor[END_REF], therefore we hypothesized that they may repress genes involved in mo-Mac differentiation. To decipher the transcriptional network of ETV3 and ETV6, we first investigated the kinetics of their nuclear localization using imaging flow cytometry. To increase the resolution of our analysis, we sought to favor mo-DC differentiation in the culture system by using a modified cytokine cocktail (increased TNFa concentration) (Supplemental figure 1A). We performed intracellular staining of ETV3 or ETV6 after 0, 1, 2, 3 or 6 days of culture. To quantify the expression of ETV3 and ETV6, we gated on ETV3 or ETV6 positive cells (Supplemental Fig To identify the target genes of ETV3 and ETV6, we performed transcriptomic analysis by bulk RNA-sequencing on monocytes silenced or not for ETV3 or ETV6, at day 3 of differentiation as above. Then, we performed a differential gene expression analysis using DESeq2 comparing control with silenced samples for ETV3 (Figure 2A) or ETV6 (Figure 2B) separately.

We defined the differentially expressed genes by a |Log2FC| > 0.5 and an adjusted p value < 0.05. Comparison of the differentially expressed genes for each shRNA revealed unique transcriptional networks, as most of the genes are specific of ETV3 or ETV6 silencing (Figure 2C). Using Gene Set Enrichment Analysis (GSEA), we evaluated the enrichment of monocyte, mo-Mac or mo-DC signatures. The mo-Mac signature was enriched in silenced samples, while mo-DC genes were enriched in the control condition (Figure 2D-E). Differentially expressed genes belonging to these signatures include in particular MAFB (Figure 2F), which is essential for mo-Mac differentiation (Goudot et al., 2017). These results suggest that ETV3 and ETV6

ETV3 and ETV6 repress interferon-stimulated genes in human monocytes

To identify the molecular pathways controlled by ETV3 or ETV6, we performed network analysis. We calculated transcription factor activity using DoRoThEa regulons and VIPER (Garcia-Alonso et al., 2019) (Fig 3A). STAT1 and STAT2 were the most active transcription factors in silenced samples. We then calculated the enrichment of gene ontology terms (GO, Biological Process) for upregulated genes (Fig 3B). Type I interferon response gene sets were enriched in silenced samples. This is consistent with the predicted activity of STAT1 and STAT2, which are known to control the expression of ISGs [START_REF] Wang | Transcriptional Regulation of Antiviral Interferon-Stimulated Genes[END_REF]. To confirm this, we filtered the differentially expressed genes matrix for known ISGs. Most of the ISGs were more expressed in silenced compared to control samples (Fig 3C -D). To determine the in vivo relevance of this finding, we re-analyzed single-cell RNA sequencing data from peripheral blood mononuclear cells (PBMCs) of patients carrying a germline mutation of ETV6 (P214L) resulting in loss-of-function [START_REF] Fisher | ETV6 germline mutations cause HDAC3/NCOR2 mislocalization and upregulation of interferon response genes[END_REF]. We first filtered the data to retain only CD14+ and CD16+ monocytes from healthy and ETV6 P214L patients (Supplemental Fig consistent with a previous report [START_REF] Fisher | ETV6 germline mutations cause HDAC3/NCOR2 mislocalization and upregulation of interferon response genes[END_REF]. These results show that ETV3 and ETV6 repress ISG expression in monocytes in vitro and in vivo in humans. This suggests that STAT1

signaling may be involved in the differentiation of monocytes.

Activation of the type I interferon pathway promotes mo-Mac differentiation

Given the impact of ETV3 or ETV6 silencing on moDC differentiation, our findings suggest that STAT1 signaling may be activated in our model despite the absence of exogenous Collectively, these results show that activation of the type I interferon pathway promotes mo-Mac differentiation at the expense of mo-DC. To understand how STAT1 signaling could affect monocyte fate decision, we exposed monocytes to IFNa, in presence or absence of cytokines, and measured the early expression of MAFB and IL4-induced genes PPARG and ZNF366

(Figure 4E). MAFB was rapidly increased upon IFNa exposure, while PPARG and ZNF366 expression upon IL-4 treatment was inhibited by IFNa. These results suggest that STAT1

Etv6 represses interferon-stimulated genes in vivo in mouse

To validate the physiological relevance of our findings, we employed a mouse model that deletes Etv6 in Cx3cr1-expressing cells after induction with tamoxifen (Fig 5A). Cx3cr1 is a canonical marker of patrolling monocytes, thus the deletion of Etv6 in Cx3cr1+ cells would be expected to delete Etv6 in monocytes and their progeny [START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF]. To confirm the cell types targeted by the deletion, we measured a YFP reporter mimicking the endogenous Cx3cr1 expression pattern. As expected, YFP was expressed at the highest level in Ly6c low patrolling monocytes, as well as in certain DC subsets including Esam -splenic cDC2 (Supplemental Fig 4A). To assess the impact of Etv6 deletion in Cx3cr1-expressing cells on ISG expression in vivo, we measured by flow cytometry the expression of Sca-1, an interferoninducible protein [START_REF] Lee | TLR7-dependent and FcγR-independent production of type I interferon in experimental mouse lupus[END_REF][START_REF] Sisirak | Genetic evidence for the role of plasmacytoid dendritic cells in systemic lupus erythematosus[END_REF]. We analyzed immune cells from WT and Cx3cr1-Etv6 Δ bone marrow, blood, and spleen (gating strategies in Supplemental Fig 5A -B). Sca-1 expression was higher in Cx3cr1-Etv6 Δ than WT bone marrow monocytes (Fig 5B

Etv6 controls mo-DC differentiation during in vivo inflammation in mouse

To determine whether Etv6 modulates monocyte differentiation in vivo, we first analyzed monocyte populations in steady-state blood, bone marrow and spleen of Cx3cr1-Etv6 Δ mice.

The numbers of B cells, T cells, neutrophils, or Ly6C high monocytes were not affected by Etv6 deletion (Fig 6A -C). The number of monocyte progenitors was also unchanged (Supplemental Finally, we sought to apply our findings to a physio-pathological setting. Mo-DCs have a deleterious role in EAE [START_REF] Croxford | The Cytokine GM-CSF Drives the Inflammatory Signature of CCR2+ Monocytes and Licenses Autoimmunity[END_REF], an animal model for multiple sclerosis (MS). In addition, IFNb treatment improves disease symptoms and was reported to act primarily on myeloid cells [START_REF] Prinz | Distinct and Nonredundant In Vivo Functions of IFNAR on Myeloid Cells Limit Autoimmunity in the Central Nervous System[END_REF]. Therefore, we hypothesized that Etv6 deletion in monocytes Cx3cr1-cre construct targets not only monocytes, but also Cx3cr1-expressing resident macrophages such as microglia [START_REF] Parkhurst | Microglia promote learning-dependent synapse formation through BDNF[END_REF] . To confirm that this effect was due to a role for Etv6 specifically in monocytes, we performed the same experiment in mice in which Etv6 deletion was induced only in macrophages. To this aim, mice were gavaged with tamoxifen then rested for 4 weeks before MOG injection, allowing short-live monocytes to become WT again while only long-lived resident macrophages remained KO for Etv6. We Collectively, these results confirm that Etv6 controls monocyte differentiation in vivo in mice during inflammation. We also identify Etv6 in monocytes as a therapeutic target for chronic inflammatory disorders such as MS.

Discussion

In this work, we identified ETV3 and ETV6 as molecular regulators of the early stages of monocyte differentiation. We found that ETV3 and ETV6 act as repressors of mo-Mac fate commitment and ISG expression. We validated these observations in vivo, showing that mice deficient for Etv6 in monocytes display elevated type I interferon responses and impaired mo-DC differentiation during inflammation. In addition, we found that Etv6 deletion in monocytes reduces the severity of EAE symptoms. Our findings allow a better understanding of the molecular control of monocyte fate decision and identify ETV6 in monocytes as a therapeutic target in inflammatory disorders.

ETV3 and ETV6 are members of the Ets family of transcription factors. ETV6 is essential for hematopoeitic stem cell survival [START_REF] Hock | Tel/Etv6 is an essential and selective regulator of adult hematopoietic stem cell survival[END_REF] and ETV3 was shown to regulate cell cycle arrest [START_REF] Klappacher | An induced Ets repressor complex regulates growth arrest during terminal macrophage differentiation[END_REF]. However, their role in immune cells remains poorly understood. We previously showed that ETV6 is expressed in DCs and facilitates the functional differentiation of cDC1 [START_REF] Lau | Transcription factor Etv6 regulates functional differentiation of cross-presenting classical dendritic cells[END_REF]. ETV3 was proposed to be a potential antiinflammatory mediator downstream of IL-10 (El Kasmi et al., 2007). Here we identify ETV3 and ETV6 as key transcriptional regulators of mo-DC differentiation. Additional transcriptional repressors are likely involved in this process, as ETV3 or ETV6 transcriptional activity requires their association with co-repressors. In particular, ETV6 has been shown to associate with IRF8 in a murine macrophage-like cell line [START_REF] Kuwata | Gamma Interferon Triggers Interaction between ICSBP (IRF-8) and TEL, Recruiting the Histone Deacetylase HDAC3 to the Interferon-Responsive Element[END_REF], in a human monocyte-like cell line and in mouse CD4 T cells [START_REF] Humblin | IRF8-dependent molecular complexes control the Th9 transcriptional program[END_REF]. While IRF8 is essential for monocyte development from their progenitors [START_REF] Kurotaki | Essential role of the IRF8-KLF4 transcription factor cascade in murine monocyte differentiation[END_REF]Sichien et al., 2016), whether it participates in mo-DC or mo-Mac differentiation is unknown. ETV6 has also been reported to associate in human PBMCs with NCOR2 [START_REF] Fisher | ETV6 germline mutations cause HDAC3/NCOR2 mislocalization and upregulation of interferon response genes[END_REF], which regulates some of the IL-4-induced genes during human mo-DC differentiation (Sander et al., 2017). In a human monocyte-like cell line, ETV3 was shown to associate with the repressor DP103, which interacts with the histone deacetylases HDAC2 and HDAC5 [START_REF] Klappacher | An induced Ets repressor complex regulates growth arrest during terminal macrophage differentiation[END_REF].

Moreover, ETV6 recruits HDAC3 to the repressor complex in murine cell lines and in human PBMCs [START_REF] Fisher | ETV6 germline mutations cause HDAC3/NCOR2 mislocalization and upregulation of interferon response genes[END_REF][START_REF] Kuwata | Gamma Interferon Triggers Interaction between ICSBP (IRF-8) and TEL, Recruiting the Histone Deacetylase HDAC3 to the Interferon-Responsive Element[END_REF][START_REF] Wang | TEL contacts multiple co-repressors and specifically associates with histone deacetylase-3[END_REF]. While a specific role for histone deacetylation in mo-DC fate commitment has not been described, it would be consistent with the fact that remodeling of histone acetylation occurs during monocyte differentiation [START_REF] Nicholas | Quantitative proteomics reveals a role for epigenetic reprogramming during human monocyte differentiation[END_REF]. Further work is needed to unravel the exact mechanism and molecular partners for the repression of ETV3 and ETV6 target genes in monocytes.

We show that ETV3 and ETV6 repress ISG during monocyte differentiation, and that ETV6 deletion in monocytes induces spontaneous ISG expression in vivo in mouse. This is consistent with previous reports showing that ETV6 is involved in ISG repression in human PBMCs [START_REF] Fisher | ETV6 germline mutations cause HDAC3/NCOR2 mislocalization and upregulation of interferon response genes[END_REF] and binds to an IFN-stimulated response element in a reporter assay [START_REF] Kuwata | Gamma Interferon Triggers Interaction between ICSBP (IRF-8) and TEL, Recruiting the Histone Deacetylase HDAC3 to the Interferon-Responsive Element[END_REF]. We also found that genes targeted by ETV3 versus ETV6 were only partially overlapping. This is in line with the observation that ETV7, another member of the Ets transcription repressor family, represses a subset of ISGs, but not all ISGs, in virusexposed cells [START_REF] Froggatt | ETV7 limits antiviral gene expression and control of influenza viruses[END_REF]. These observations suggest the existence of a specific pattern of target ISGs for each member of the ETV family.

We find that activation of the type I interferon pathway promotes mo-Mac differentiation in our culture system, where human monocytes are exposed to M-CSF, IL-4 and TNF-a. This is consistent with the finding that monocytes differentiated with GM-CSF and IL-4 in the presence of IFN-b display altered phenotype and functional features suggesting impaired mo-DC differentiation, although the re-orientation of their fate was not investigated [START_REF] Zang | Regulation of differentiation and functional properties of monocytes and monocyte-derived dendritic cells by interferon beta in multiple sclerosis[END_REF].

In addition, IFN-g and IL-4 have been shown to mutually inhibit each other's program in macrophages, via the cross-repression of STAT1 and STAT6 [START_REF] Piccolo | Opposing macrophage polarization programs show extensive epigenomic and transcriptional cross-talk[END_REF]. In line with this idea, our results indicate that when monocytes are exposed simultaneously to type I interferon and IL-4, the STAT1-induced program dominates over that of STAT6. This suggests that STAT1 signaling needs to be repressed in monocytes to enable the expression of the IL4dependent mo-DC differentiation program.

Monocyte-derived cells have been shown to play a central role in neuro-inflammation. Mice deficient for CCR2 or its ligand, in which monocytes cannot exit the bone marrow, are resistant to EAE or develop milder disease depending on strains [START_REF] Gaupp | Experimental autoimmune encephalomyelitis (EAE) in CCR2(-/-) mice: susceptibility in multiple strains[END_REF][START_REF] Huang | Absence of Monocyte Chemoattractant Protein 1 in Mice Leads to Decreased Local Macrophage Recruitment and Antigen-Specific T Helper Cell Type 1 Immune Response in Experimental Autoimmune Encephalomyelitis[END_REF][START_REF] Izikson | Resistance to Experimental Autoimmune Encephalomyelitis in Mice Lacking the Cc Chemokine Receptor (Ccr2)[END_REF][START_REF] Mildner | CCR2+Ly-6Chi monocytes are crucial for the effector phase of autoimmunity in the central nervous system[END_REF]. In addition, blocking monocyte recruitment using a pharmacological inhibitor diminishes the incidence and severity of EAE [START_REF] Ge | The CCL2 synthesis inhibitor bindarit targets cells of the neurovascular unit, and suppresses experimental autoimmune encephalomyelitis[END_REF]. Monocyte depletion after EAE onset also reduces inflammation and disease symptoms [START_REF] Getts | Therapeutic Inflammatory Monocyte Modulation Using Immune-Modifying Microparticles[END_REF][START_REF] Mildner | CCR2+Ly-6Chi monocytes are crucial for the effector phase of autoimmunity in the central nervous system[END_REF][START_REF] Moreno | Therapeutic depletion of monocyte-derived cells protects from long-term axonal loss in experimental autoimmune encephalomyelitis[END_REF]. Mo-DC and mo-Mac appear to play different roles during EAE. Mo-DC induce pathogenic Th17 cells by secreting IL-23 [START_REF] Croxford | The Cytokine GM-CSF Drives the Inflammatory Signature of CCR2+ Monocytes and Licenses Autoimmunity[END_REF]. By contrast, mo-Mac display specific anti-inflammatory features during the resolution phase of EAE [START_REF] Giles | Myeloid cell plasticity in the evolution of central nervous system autoimmunity[END_REF][START_REF] Greenhalgh | Arginase-1 is expressed exclusively by infiltrating myeloid cells in CNS injury and disease[END_REF]Locatelli et al., 2018b).

In MS patients, monocyte recruitment is particularly increased in demyelinated areas [START_REF] Lagumersindez-Denis | Differential contribution of immune effector mechanisms to cortical demyelination in multiple sclerosis[END_REF]. Histological analysis also evidenced the presence around active MS lesions of myeloid cells that have a phenotype consistent with mo-DC and that are found interacting with numerous lymphocytes in situ [START_REF] Henderson | Multiple sclerosis: Distribution of inflammatory cells in newly forming lesions[END_REF]. Specifically blocking monocyte differentiation into mo-DC, while preserving mo-Mac development, could therefore provide clinical benefits in neuro-inflammation. Our results identify ETV6 as a candidate target to re-orient monocyte fate decision for therapeutic strategies.

Collectively, our findings suggest that active repression of mo-Mac differentiation is required to allow monocytes to commit to the mo-DC fate, when exposed to the appropriate external cues. Given the central role of mo-DC in fueling pathogenic inflammation in numerous chronic inflammatory diseases, our work should have important implications for the therapeutic manipulation of monocyte differentiation.

Material and Methods

Human samples

Buffy coats from healthy donors (both male and female donors) were obtained from Etablissement Français du Sang (Paris) in accordance with INSERM ethical guidelines.

According to French Public Health Law (art L 1121-1-1, art L 1121-1-2), written consent and IRB approval are not required for human non-interventional studies.

Mouse strains

Cx3Cr1-CreER were obtained from Jackson Laboratories (Stock # 021160). Cx3Cr1-CreER express the enhanced yellow fluorescent protein (EYFP) from endogenous Cx3cr1

promoter/enhancer elements. Etv6 flox/flox mice were obtained from H.Hock [START_REF] Hock | Tel/Etv6 is an essential and selective regulator of adult hematopoietic stem cell survival[END_REF].

Cx3cr1-Etv6 D were generated by crossing Cx3Cr1-CreER +/-mice with Etv6 flox/flox mice. For Cx3cr1-Etv6 D mice, Cx3Cr1-CreER -/-Etv6 flox/flox littermates were used as WT controls. CD11c-Etv6 D have been previously described [START_REF] Lau | Transcription factor Etv6 regulates functional differentiation of cross-presenting classical dendritic cells[END_REF]. All mice were on C57BL/6 background. Mice were maintained under specific pathogen-free conditions at the animal facility of Institut Curie or New York University School of Medicine, in accordance with institutional guidelines. Both male and female mice were used at age 7-9 weeks. All animal procedures were in accordance with the guidelines and regulations of the French Veterinary Department or Institutional animal Care and Use Committee of New York University School of Medicine and approved by the local ethics committee.

Monocyte isolation and culture

Peripheral Blood Mononuclear Cells (PBMC) were prepared by centrifugation on a Ficoll gradient (Lymphoprep, StemCell). Blood CD14+ monocytes were isolated from healthy donors' PBMC by positive selection using magnetic beads (Miltenyi). Monocytes were 95%-98% CD14 + CD16 -as assessed by flow cytometry. Monocytes (2x10 6 cells/mL) were cultured for 5 days in RPMI-Glutamax medium (GIBCO) supplemented with antibiotics (penicillin and streptomicin) and 10% Fetal Calf Serum in the presence or absence of 100 ng/mL M-CSF (Miltenyi), 5 ng/mL IL-4 (Miltenyi) and 5 ng/mL TNF-a (R&D Biotechne). Cytokines were added only at the start of the culture, and medium was not refreshed during the course of the culture.

CD16 + or CD1a + cell populations were isolated by cell sorting on a FACSAria instrument (BD Biosciences). In some experiments, monocytes were cultured in the presence of 100 ng/mL M-CSF (Miltenyi), 5 ng/mL IL-4 (Miltenyi) and 20 ng/mL TNF-a (R&D Biotechne), or in presence of IFNa (rh Interferon-alpha 1b, Immunotools, #11343596) or IFNb (generated inhouse by the platform of recombinant proteins of Institut Curie).

Flow cytometry of human cells

Human cells were stained in PBS containing 0.5% human AB serum and 2mM EDTA with

Analysis of mouse tissues

For phenotypic analysis, Cx3cr1-Etv6 D mice and WT (Etv6 flox/flox ) littermates were treated with 5 mg of tamoxifen (Sigma) resuspended in corn oil (Sigma) by oral gavage for 3 consecutive days and sacrificed 5 days after the last treatment.

Bone marrows were flushed from one leg and filtered using 40µm cell strainers. 50 µL of blood was used and incubated twice with red blood cells lysis buffer (Sigma) for 5 min at room temperature. Spleens were cut in small pieces and incubated for 30 minutes at 37°C in digestion mix (RPMI containing 0.4mg/mL DNAse I (Sigma) and 0.5mg/mL collagenase D (Roche). Spleen suspensions were then incubated with red blood cells lysis buffer for 5 min and then filtered using 40µm cell strainers. Peritoneal lavage was recovered by intraperitoneal injection of 5 mL of PBS. Lymph nodes closed to the immunization site lymph nodes were cut into small pieces and incubated for 30 minutes at 37°C in digestion mix: RPMI containing 0.4mg/mL DNAse I (Sigma) and 0.5mg/mL collagenase D (Roche). Cell suspensions were then filtered using 40µm cell strainers.

Cells were stained in PBS containing BSA 0.5% and 2mM EDTA for 30-45 min on ice. Streptavidin BV421 (Invitrogen). Antibody panels for the different tissues can be found in Supplemental Table 1. After washing, cells were resuspended in staining buffer containing DAPI (Fischer Scientific, 100ng/mL). Cells were acquired on a ZE5 flow cytometer (Bio-Rad).

Supervised analysis was performed using FlowJo software.

Tetramer staining

Lymph nodes were collected and dissociated by forcing through a 40µm cell strainer. Cells

Immuno blot

Cells were lysed in RIPA buffer (Thermo Scientific) supplemented with complete Mini EDTAfree protease inhibitor cocktail (Roche), at 1x10 6 cells in 100 µL of lysis buffer. Post-nuclear lysates were resolved by SDS-PAGE using 4%-15% BisTris NuPAGE gels (Invitrogen) and proteins were transferred to membranes (Immunoblot PVDF membranes, Bio-Rad).

Membranes were stained with primary antibodies against ETV6/Tel (Novus Biologicals, NBP1-80695), ETV3 (Atlas Antibodies, HPA004794), GP96 (Novus Biologicals, clone 9G10), or actin (Millipore, clone C4), followed by HRP-conjugated secondary antibodies (Jackson Immunoresearch). Some membranes were incubated with ''Re-blot Plus'' buffer (Millipore).

RNA-seq library preparation

Total RNA was extracted using the RNAeasy minikit (Qiagen) including on-column DNase digestion according to the manufacturer's protocol. The integrity of the RNA was confirmed in

RNA-seq data analysis

Genome assembly was based on the Genome Reference Consortium (hg38). Quality of RNAseq data was assessed using FastQC [START_REF] Andrews | FastQC. A quality control tool for high throughput sequence data[END_REF]. Reads were aligned to the transcriptome using STAR [START_REF] Dobin | STAR: ultrafast universal RNA-seq aligner[END_REF]. Differential gene expression analysis was performed using DESeq2 using the design 'donor + group' [START_REF] Love | Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2[END_REF]. Genes with low number of counts (<10) were filtered out. Differentially expressed genes were identified based on adjusted p-value < 0.05 and absolute Log2 FoldChange > 0.5. Volcano plots were generated with EnhancedVolcano [START_REF] Blighe | EnhancedVolcano: Publication-ready volcano plots with enhanced colouring and labeling[END_REF]. Transcription factor activity was calculated using Dorothea regulons and VIPER [START_REF] Garcia-Alonso | Benchmark and integration of resources for the estimation of human transcription factor activities[END_REF].

Gene Set Enrichment Analysis

GSEA [START_REF] Subramanian | Gene set enrichment analysis: A knowledgebased approach for interpreting genome-wide expression profiles[END_REF] was performed using the GSEA software (version 4.0.3) with the default parameters, except for the number of permutations that we fixed at n=1000.

Count matrix from RNA-seq studies were first normalized using DESeq2. Gene signatures of blood monocytes, mo-DC and mo-mac were designed from microarray data (Goudot et al., 2017).

Analysis of public scRNAseq data

Single-cell RNA-Seq data from healthy controls and patients with the ETV6 P214L mutation [START_REF] Fisher | ETV6 germline mutations cause HDAC3/NCOR2 mislocalization and upregulation of interferon response genes[END_REF] was downloaded from BioProject PRJNA657295 and was processed with Cell Ranger (v2.1.0) using the human reference genome (hg38). Count matrices were then integrated and analyzed using Seurat v4. Cells with less than 200 genes detected or percentage of mitochondrial genes over 15%, as well as genes detected in less than 3 cells, were excluded from analysis.

We used a reference-mapping approach to annotate cell labels in the query dataset using the MapQuery function of Seurat v4. We first projected each query cell onto a previously computed UMAP visualization of the reference data set [START_REF] Hao | Integrated analysis of multimodal single-cell data[END_REF]

Experimental Peritonitis

Cx3cr1-Etv6 D mice and WT (Etv6 flox/flox ) littermates were treated with 5 mg of tamoxifen (Sigma) resuspended in Corn oil (Sigma) by oral gavage for 3 consecutive days (day 0-2). On day 5, mice received a fourth gavage of tamoxifen and were injected intra-peritonally with 1 mL of 3.8% brewer's thioglycollate medium (Sigma). Mice were analyzed 3 days after thioglycollate injection.

Experimental Autoimmune Encephalomyelitis

Cx3cr1-Etv6

Statistical analysis

Wilcoxon matched paired test, Mann-Whitney test and unpaired t test were performed using Prism (GraphPad Software). Statistical details for each experiment can be found in the corresponding figure legend. N corresponds to the number of individual donors or the number of individual mice analyzed.

Chapter 2. Monocytes differentiate into macrophages or dendritic cells along two alternative paths controlled by distinct regulatory networks

Javiera Villar 1 and Elodie Segura

Introduction

Monocytes are key actors in the maintenance of tissue homeostasis and in inflammatory responses. After exiting the bone marrow, they circulate in the blood and can migrate to peripheral tissues where they rapidly differentiate into macrophages or dendritic cells (DC) (Coillard and Segura, 2019;[START_REF] Guilliams | Developmental and Functional Heterogeneity of Monocytes[END_REF][START_REF] Jakubzick | Monocyte differentiation and antigenpresenting functions[END_REF]. The factors orchestrating monocyte fate decision remain poorly understood. In particular, whether these two cellular identities represent alternative differentiation pathways or different stages along a continuum is controversial.

Monocyte-derived macrophages (mo-Mac) and DC (mo-DC) have been evidenced in multiple tissues during acute and chronic inflammation, in both mouse and human (Coillard and Segura, 2019;[START_REF] Guilliams | Developmental and Functional Heterogeneity of Monocytes[END_REF][START_REF] Zigmond | Ly6Chi Monocytes in the Inflamed Colon Give Rise to Proinflammatory Effector Cells and Migratory Antigen-Presenting Cells[END_REF]. Mo-Mac and mo-DC are also present in the steady-state in skin and peritoneum (Goudot et al., 2017;[START_REF] Tamoutounour | Origins and functional specialization of macrophages and of conventional and monocyte-derived dendritic cells in mouse skin[END_REF]. In other tissues at homeostasis, monocytes replenish the pool of macrophages over time, in particular in heart [START_REF] Epelman | Embryonic and Adult-Derived Resident Cardiac Macrophages Are Maintained through Distinct Mechanisms at Steady State and during Inflammation[END_REF][START_REF] Molawi | Progressive replacement of embryo-derived cardiac macrophages with age[END_REF], intestine [START_REF] Bain | Constant replenishment from circulating monocytes maintains the macrophage pool in the intestine of adult mice[END_REF][START_REF] Shaw | Tissue-resident macrophages in the intestine are long lived and defined by Tim-4 and CD4 expression[END_REF] and pancreas [START_REF] Calderon | The pancreas anatomy conditions the origin and properties of resident macrophages[END_REF], but do not seem to differentiate into mo-DC in this context [START_REF] Liu | Fate Mapping via Ms4a3-Expression History Traces Monocyte-Derived Cells[END_REF]. Monocytes were initially proposed to be precommitted to become mo-Mac or mo-DC [START_REF] Menezes | The Heterogeneity of Ly6Chi Monocytes Controls Their Differentiation into iNOS+ Macrophages or Monocyte-Derived Dendritic Cells[END_REF]. Subsequently, we and others have shown that monocyte differentiation is not transcriptionally imprinted but can be oriented by external signals including cytokines, retinoic acid and pathogen-derived products (Coillard et al., 2021;[START_REF] Devalaraja | Tumor-Derived Retinoic Acid Regulates Intratumoral Monocyte Differentiation to Promote Immune Suppression[END_REF]Goudot et al., 2017;[START_REF] Mildner | Genomic Characterization of Murine Monocytes Reveals C/EBPβ Transcription Factor Dependence of Ly6C-Cells[END_REF]Sander et al., 2017;[START_REF] Vento-Tormo | IL-4 orchestrates STAT6-mediated DNA demethylation leading to dendritic cell differentiation[END_REF].

Several molecular regulators involved in mo-DC development have been identified using in vitro models and include IRF4, aryl hydrocarbon receptor, BLIMP-1, NCOR2 and miR-155 [START_REF] Briseño | Distinct Transcriptional Programs Control Cross-Priming in Classical and Monocyte-Derived Dendritic Cells[END_REF]Coillard et al., 2021;Goudot et al., 2017;[START_REF] Mendes | The epigenetic pioneer EGR2 initiates DNA demethylation in differentiating monocytes at both stable and transient binding sites[END_REF]Sander et al., 2017). The role of IRF4 and aryl hydrocarbon receptor was confirmed in vivo in genetically deficient mice in homeostatic conditions (Goudot et al., 2017;[START_REF] Kim | MHC II+ resident peritoneal and pleural macrophages rely on IRF4 for development from circulating monocytes[END_REF].

The orphan nuclear receptor NR4A3 was also shown to participate in mo-DC differentiation, acting downstream of IRF4, but only during inflammation in vivo [START_REF] Boulet | The orphan nuclear receptor NR4A3 controls the differentiation of monocyte-derived dendritic cells following microbial stimulation[END_REF]. While the transcriptional regulation of macrophage identity in tissues is well characterized [START_REF] Blériot | Determinants of Resident Tissue Macrophage Identity and Function[END_REF], transcription factors driving the monocyte-to-macrophage program remain poorly characterized, beside our finding that MAFB is required for human mo-Mac differentiation (Goudot et al., 2017).

Based on the requirement for distinct transcription factors for their differentiation, we have proposed that mo-Mac and mo-DC constitute two distinct lineages stemming from monocytes (Goudot et al., 2017). Recently, single-cell analyses and trajectory reconstruction in a model of neuro-inflammation have suggested that mo-DC could represent an intermediate state of monocyte differentiation, with mo-Mac being the end stage [START_REF] Amorim | IFNγ and GM-CSF control complementary differentiation programs in the monocyte-to-phagocyte transition during neuroinflammation[END_REF]. The transcriptional control of these transitions was not explored. More work is needed to better understand the molecular regulation of the monocyte differentiation program.

In this study, we used temporal single-cell RNA sequencing (scRNA-seq) to analyze human monocyte differentiation trajectories in an in vitro system. We evidenced divergent differentiation paths towards mo-Mac versus mo-DC, with a fate decision occurring within the first 24 hours. Using computational approaches, we identified candidate transcription factors involved in monocyte differentiation. We further showed that IRF1 is required for mo-Mac differentiation, and that MAFF, ETS2, MXD1 and ZNF366 are involved in mo-DC differentiation. Our results support a model in which mo-Mac and mo-DC derive from alternative differentiation pathways, controlled by distinct regulatory networks.

Results

Temporal scRNA-seq analysis reveals early divergent paths of human monocyte differentiation

To dissect monocyte fate decision mechanisms, we used our previously established in vitro differentiation model, in which human monocytes are cultured with a cocktail of M-CSF, IL4

and TNF-α and differentiate in the same culture into mo-DC and mo-Mac resembling the ones found in clinical samples (Goudot et al., 2017). To address whether monocytes followed a binary fate decision or differentiated along a continuum of states, we sought to reconstruct monocyte differentiation trajectories using single-cell transcriptomes. We profiled monocyte cultures from two individual donors by scRNAseq using a droplet-based method, and focused on early time points: 3h, 9h, 24h and 48h after the start of the culture (fig1A). We integrated the different datasets using STACAS [START_REF] Andreatta | STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data[END_REF] and performed unsupervised clustering using a graph-based approach with the Seurat package [START_REF] Hao | Integrated analysis of multimodal single-cell data[END_REF]. This unsupervised analysis grouped cells according to time points (fig1A) and cells from both donors were distributed homogenously (figS1A). We identified 14 different clusters in the dataset, most of them with mixed sample origins (fig1D). Of note, clusters 1 and 2 contained almost exclusively cells captured at 3h, cluster 5 contained cells captured at 9h, while clusters 11, 12, 13 and 14 displayed a majority of cells from the 48h time point (fig1D).

To decipher cluster identity, we analyzed the expression of canonical genes of monocytes (S100A9, S100A8, VCAN, CD14), mo-Mac (MAFB, CXCL8, THBS1, APOE) and mo-DC (IRF4, PRDM1, CD1B, CD1A) (fig1E) and the top differentially expressed genes between clusters (fig1F). Clusters 1, 2, 3 and 4 had the highest expression of monocyte genes.

Consistent with this, clusters 1, 2, 3, 4, 5 and 6 were enriched for the monocyte signature compared to other clusters (fig1G). Macrophage genes were predominantly expressed in clusters 4, 5, 6, 13 and 14, including APOC1, sterol 27-hydroxylase (CYP27A1), fatty acid binding proteins FABP4 and FABP5, and chemokine CCL22. DC genes were found in clusters 3, 7, 8, 11 and 12, including CD1E and CST3. Of note, cluster 10 contained cells from all time points and expressed genes consistent with a contaminating population of intermediate CD14+CD16+ monocytes, including FCGR3A (encoding CD16) and AIF1 (Villani et al., 2017).

We have previously shown in this model that IRF4 and MAFB are necessary for mo-DC and mo-Mac differentiation respectively (Goudot et al., 2017). Their expression appeared largely exclusive, with IRF4 expression highest in cluster 3 while MAFB was mainly expressed in clusters 1, 4, 5 and 6 (fig1E). These results suggest clusters 1 and 2 correspond to undifferentiated monocytes, while cells from other clusters express either a DC-or a macrophage-oriented transcriptional program starting after 3-9h.

To study differentiation trajectories, we analyzed RNA velocity using scVelo [START_REF] Bergen | Generalizing RNA velocity to transient cell states through dynamical modeling[END_REF]. This method estimates the kinetics of mRNA splicing in single-cell transcriptomes, in order to reconstruct cellular dynamics. Inference of the velocity pseudotime using scVelo was able to reconstruct independently the temporal sequence of the dataset (figS1B), confirming the robustness of this approach. RNA velocity projection indicated two main dynamics (fig1H).

Clusters 1 and 2 showed a strong activity directed towards clusters 3 and 4, suggesting early transcriptional changes consecutive to fate decision. At later time points, two parallel differentiation trajectories were evident, with velocities from clusters 7 and 11 directed towards clusters 8 and 12 on one hand (DC path), and velocities from cluster 13 directed towards cluster 14 on the other hand (macrophage path). Collectively, these results reveal two divergent and alternative differentiation pathways (fig1G), with fate commitment occurring in the first few hours after monocytes are exposed to cytokines.

Identification of candidate transcription factors involved in monocyte differentiation

To identify transcriptional regulators of the early steps of monocyte differentiation, we analyzed differentially expressed genes between clusters with a commitment towards mo-DC versus mo-Mac, and extracted genes annotated as transcription factors. We focused on the comparison between clusters 3 and 4 (fig2A), clusters 6 and 7 (fig2B), clusters 6 and 8 (fig2C)

and clusters 12 and 14 (fig2D). To infer transcriptional activity, we also performed network analysis using DoRoThEa [START_REF] Garcia-Alonso | Benchmark and integration of resources for the estimation of human transcription factor activities[END_REF][START_REF] Holland | Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data[END_REF]. Based on these analyses, we selected for further study IRF1, which is more expressed in macrophageengaged clusters 4 (fig2A) and 6 (fig2B-C) and shows high transcriptional activity in the clusters 5 and 6 (fig2D). We also identified as candidates ZNF366, which is more expressed in DC-committed clusters 3 (fig2A) and 8 (fig2C), ETS2, which is more expressed in clusters 4 and 6 (fig2A-C), and MAFF, which is more expressed in clusters 6 (fig2B) and 14 (fig2D).

Finally, we selected MXD1, a factor more expressed in cluster 4 (fig2A) and 14 (fig2D), and known to antagonize the transcriptional activity of MYC [START_REF] Ayer | Mad: A heterodimeric partner for Max that antagonizes Myc transcriptional activity[END_REF], which is expression of interferon-stimulated genes (ISG) in macrophages [START_REF] Langlais | The macrophage IRF8/IRF1 regulome is required for protection against infections and is associated with chronic inflammation[END_REF][START_REF]Requirement for Transcription Factor IRF-1 in NO Synthase Induction in Macrophages[END_REF][START_REF] Song | IRF1 governs the differential interferon-stimulated gene responses in human monocytes and macrophages by regulating chromatin accessibility[END_REF]. Of note, cluster 5 showed high expression of ISG such as MX1 and ISG15, and was enriched for the ISG signature (fig3C). In addition, network analysis suggested that IRF1 controlled the expression of several ISG expressed in our dataset (fig3D).

Therefore, we hypothesized that IRF1 may impact mo-Mac differentiation through the regulation of ISG expression. To confirm the expression of ISG during monocyte differentiation in vitro, we measured by RT-qPCR the expression of MX1, IFIT3 and CXCL10 after 9h of culture with different cytokine combinations (fig3E). We found that ISG expression were significantly induced upon exposure to M-CSF, with TNF-α decreasing ISG expression. To address the effect of ISG on monocyte differentiation, we used a soluble type I interferon receptor (B18R) which acts as an inhibitor of interferon signaling [START_REF] Colamonici | Vaccinia Virus B18R Gene Encodes a Type I Interferon-binding Protein That Blocks Interferon α Transmembrane Signaling (&#x2217[END_REF]. We validated the inhibitory effect of B18R on the expression of MX1, IFIT3 and CXCL10 (fig3E).

However, we did not observe any impact of B18R on mo-Mac differentiation, whether using M-CSF alone, M-CSF and IL4, or the cocktail M-CSF, IL4 and TNF-α (fig3F-G). Taken together, these results suggest that IRF1 controls mo-Mac differentiation independently of its role in ISG expression.

Discussion

In this work, we used temporal scRNA-seq analysis to reveal differentiation paths of human monocytes. We identified IRF1, MAFF, ETS2, MXD1 and ZNF366 as molecular regulators of the early stages of monocyte differentiation. We found that IRF1 is required for mo-Mac development, independently of the control of ISG expression. In addition, we evidenced a role for MAFF, ETS2, MXD1 and ZNF366 in mo-DC development. Our findings support the idea that mo-DC and mo-Mac constitute divergent and alternative cell fates, rather than stages along a differentiation trajectory.

IRF1 is known to be involved in myelopoiesis. Irf1-deficient mice display reduced granulocyte numbers, but normal monocyte numbers in circulation with reduced expression of PU.1 [START_REF] Testa | Impaired myelopoiesis in mice devoid of interferon regulatory factor 1[END_REF]. A role for IRF1 in the function and differentiation of osteoclasts (a bone-resident population of the monocyte lineage [START_REF] Arai | Commitment and Differentiation of Osteoclast Precursor Cells by the Sequential Expression of C-Fms and Receptor Activator of Nuclear Factor κb (Rank) Receptors[END_REF] was also proposed [START_REF] Place | Osteoclast fusion and bone loss are restricted by interferon inducible guanylate binding proteins[END_REF][START_REF] Salem | A novel role for interferon regulatory factor 1 (IRF1) in regulation of bone metabolism[END_REF]. In macrophages, IRF1 regulates the transcriptional response to IFN- [START_REF] Langlais | The macrophage IRF8/IRF1 regulome is required for protection against infections and is associated with chronic inflammation[END_REF][START_REF]Requirement for Transcription Factor IRF-1 in NO Synthase Induction in Macrophages[END_REF] and to type I interferon [START_REF] Song | IRF1 governs the differential interferon-stimulated gene responses in human monocytes and macrophages by regulating chromatin accessibility[END_REF]. In particular, IRF1 was shown to modulate in human macrophages, but not in monocytes, the expression of ISG by controlling chromatin accessibility upon stimulation [START_REF] Song | IRF1 governs the differential interferon-stimulated gene responses in human monocytes and macrophages by regulating chromatin accessibility[END_REF]. This finding together with our results suggest that the role of IRF1 in monocytes may be different from that observed in macrophages.

DC-SCRIPT and MXD1 were previously shown to participate in cDC development and maturation in mouse. DC-SCRIPT is highly expressed in human DC, either derived in vitro or isolated from tissues [START_REF] Triantis | Identification and Characterization of DC-SCRIPT, a Novel Dendritic Cell-Expressed Member of the Zinc Finger Family of Transcriptional Regulators[END_REF], and in murine cDC [START_REF] Shengbo | Type 1 conventional dendritic cell fate and function are controlled by DC-SCRIPT[END_REF]. Mouse DC-SCRIPT (encoded by Zfp366) is required specifically for cDC1 development, and maintains their transcriptional identity [START_REF] Chopin | Transcription Factor PU.1 Promotes Conventional Dendritic Cell Identity and Function via Induction of Transcriptional Regulator DC-SCRIPT[END_REF][START_REF] Shengbo | Type 1 conventional dendritic cell fate and function are controlled by DC-SCRIPT[END_REF]. In particular, DC-SCRIPT controls in mouse cDC1 the production of IL-12, a cytokine expressed specifically by human mo-DC from clinical samples compared to mo-Mac (Tang-Huau et al., 2018). MXD1

participates in the terminal differentiation of granulocytes [START_REF] Foley | Targeted disruption of the MYC antagonist MAD1 inhibits cell cycle exit during granulocyte differentiation[END_REF]. In DC, MXD1

regulates the maturation program of cDC1 via the repression of Mycl (A. et al., 2020). What ETS2 is an ETS-domain transcription factor. It was reported to cooperates with PU.1 for inducing the expression of Csf1r (encoding the M-CSF receptor) in mouse and human cell lines [START_REF] Reddy | Opposing actions of c-ets/PU.1 and c-myb protooncogene products in regulating the macrophage-specific promoters of the human and mouse colony-stimulating factor-1 receptor (c-fms) genes[END_REF]. ETS2 is dispensable for inducing macrophage differentiation from embryonic stem cells [START_REF] Henkel | PU.1 But Not Ets-2 Is Essential for Macrophage Development From Embryonic Stem Cells[END_REF], but overexpression of ETS2 promotes a macrophage phenotype in a murine myeloblast cell line [START_REF] Aperlo | Constitutive c-ets2 expression in M1D+ myeloblast leukemic cells induces their differentiation to macrophages[END_REF]. Peritoneal macrophages from Ets2-deficient mice were found to display abnormal morphological features but were not analyzed further [START_REF] Jin | Alterations in differentiation and behavior of monocytic phagocytes in transgenic mice that express dominant suppressors of ras signaling[END_REF]. Here, we evidenced a role for ETS2 in human monocyte differentiation into DC, but not into macrophages. A possible target of ETS2 in differentiating monocytes is miR-155, which promotes mo-DC differentiation (Coillard et al., 2021) and whose expression is induced by ETS2, as shown in mouse macrophages [START_REF] Quinn | The Role of Ets2 Transcription Factor in the Induction of MicroRNA-155 (miR-155) by Lipopolysaccharide and Its Targeting by Interleukin-10*[END_REF]. Further work is needed to better characterize the transcriptional network of ETS2 in monocytes.

Our results contribute to the evidence supporting a model of divergent pathways leading to mo-DC versus mo-Mac differentiation. Recently, it was proposed in a model of neuroinflammation that monocytes differentiate along a single path, with mo-DC being an intermediate and mo-Mac the end stage [START_REF] Amorim | IFNγ and GM-CSF control complementary differentiation programs in the monocyte-to-phagocyte transition during neuroinflammation[END_REF]. This discrepancy might be due

Material and Methods

Human samples

Buffy coats from healthy donors (both male and female donors) were obtained from Etablissement Français du Sang (Paris) in accordance with INSERM ethical guidelines.

According to French Public Health Law (art L 1121-1-1, art L 1121-1-2), written consent and IRB approval are not required for human non-interventional studies.

Monocyte isolation and culture

Peripheral Blood Mononuclear Cells (PBMC) were prepared by centrifugation on a Ficoll gradient (Lymphoprep, StemCell). Blood CD14+ monocytes were isolated from healthy donors' PBMC by positive selection using magnetic beads (Miltenyi). Monocytes (2x10 6 cells/mL) were cultured for indicated times in RPMI-Glutamax medium (GIBCO) supplemented with antibiotics (penicillin and streptomicin) and 10% Fetal Calf Serum in the presence or absence of 100 ng/mL M-CSF (Miltenyi), 5 ng/mL IL-4 (Miltenyi) and 5 ng/mL TNF-a (R&D Biotechne). Cytokines were added only at the start of the culture, and medium was not refreshed during the course of the culture. In some experiments, monocytes were cultured in the presence of 1 ug/ml of recombinant B18R (StemCell).

Single-cell RNA seq in 10x Genomics platform

For each time point, monocytes were detached from the plate and dead cells were removed with Dead Cell Removal Kit (Miltenyi) according to manufacturer's instructions. Cells were barcoded per donor (Donor A and B) using TotalSeq™-anti-human Hashtag antibody (A0251, A02052, respectively; Biolegend) according to manufacturer's instruction. Barcoded cells were counted and mixed in a 1:1 ratio. Finally, barcoded single-cell suspension was loaded into 10x

Genomics Chromium (CA, USA). Libraries were prepared as per manufacturer's protocol (Chromium Single Cell 3' Reagent Kits v3 protocol) and sequenced on an Illumina NovaSeq sequencer according with 10x Genomics recommendations (paired-end reads, R1= XX, R2 = XX ) to a depth of approximately 50,000 reads per cell.

Single-cell RNA-sequencing analysis

Initial processing was done using CellRanger (v3.1.0). Starting from the filtered gene-cell count matrix produced by CellRanger's, we proceeded with the Seurat v4.0 workflow for demultiplex cells based on hashtag barcode and quality control (QC) processing. Briefly, we filtered out cells with mitochondrial genes < 20%, as well as genes expressed in less than 3 cells. Hashtag demultiplexing was performed with the function HTODemux() and positive.quantile = 0.99. Integration of the 8 samples (2 donors, 4 time-points) was subsequently done with STACAS workflow [START_REF] Andreatta | STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data[END_REF]. Briefly, normalization and identification of variable features was performed with standard Seurat pipelines and then anchors were identified with FindAnchors.STACAS(…, dims=1:30, anchor.features= 5000) and filter with FilterAnchors.STACAS (…, dist.thr = 0.8). The order for integration was calculated with SampleTree.STACAS(). Finally, integration was performed with the filtered anchors using the function IntegrateData().

Downstream analysis, graph-based clustering, visualization and differential gene expression

analyses of the scRNA-seq data were performed using Seurat v4.0. For clustering analysis, FindNeighbors() and FindClusters() functions of the Seurat package were used with the first 50 significant PCs and a resolution of 1.3, respectively. For signatures enrichment we used the function AddModuleScore(). For identification of DEGs, we used the FindMarkers or DEGs with adjusted P values of >0.05 were filtered out.

RNA velocity

Annotations of unspliced/spliced reads were obtained using velocyto CLI with default parameters. Next, unspliced counts were merged with the preprocessed, normalized, integrated and annotated spliced count matrix (Seurat v4.0) and the RNA velocity analysis was performed using scVelo (v0.2.4) workflow. Briefly, we computed moments for velocity estimation and then the stochastic model to learn the transcriptional dynamics of splicing kinetics, transcriptional state and velocity pseudo-time across the complete dataset.

Flow cytometry

Human cells were stained in PBS containing 0.5% human AB serum and 2mM EDTA with APC anti-CD1a (Biolegend, clone HI149) and FITC anti-CD16 (Biolegend, clone 3G8). DAPI (Fischer Scientific, 100ng/mL) was added immediately prior to acquisition on a FacsVerse instrument (BD Biosciences). Data was analyzed with FlowJo (FlowJo LLC).

Immuno blot

Cells were lysed in RIPA buffer (Thermo Scientific) supplemented with complete Mini EDTAfree protease inhibitor cocktail (Roche), at 1x10 6 cells in 100 µL of lysis buffer. Post-nuclear lysates were resolved by SDS-PAGE using 4%-15% BisTris NuPAGE gels (Invitrogen) and proteins were transferred to membranes (Immunoblot PVDF membranes, Bio-Rad).

Membranes were stained with primary antibodies against IRF1 (Cell Signaling, clone D5E4), GP96 (Novus Biologicals, clone 9G10), or actin (Millipore, clone C4), followed by HRPconjugated secondary antibodies (Jackson Immunoresearch). Some membranes were incubated with ''Re-blot Plus'' buffer (Millipore).

Statistical analysis

Statistical tests were performed using Prism v9 (GraphPad Software). Statistical details for each experiment can be found in the corresponding figure legend. N corresponds to the number of individual donors analyzed.

Discussion

A. Experimental approaches and their limitations

In vitro differentiation of human monocytes

Due to limitations inherent to working with human samples, human monocyte differentiation is commonly studied in vitro. Pioneer work has shown that human monocytes can differentiate into DC when cultured with GM-CSF and IL4 (Sallusto and Lanzavecchi, 1994). These cells display phenotypic markers of human DC such as CD1a and CD1c, and typical DC functions such as stimulation of naïve T cells. In addition, mo-mac can be obtained by culturing human monocytes with M-CSF [START_REF] Akagawa | Functional heterogeneity of colony-stimulating factor-induced human monocyte-derived macrophages[END_REF]. In vivo, monocytes are exposed to several signals (such as cytokines) that will modulate their commitment into either mo-mac or mo-DC.

A limitation of these culture systems is that they do not allow the analysis of alternative fates of monocytes (mo-DC versus mo-mac). In my project, I used a protocol to simultaneously differentiate monocytes into mo-mac and mo-DC in the same culture, using a cocktail of cytokines consisting in M-CSF, IL-4 and TNF-a. In addition, the mo-DC and mo-mac obtained in this culture system resemble the mo-DC and mo-Mac found in clinical samples (peritoneal ascites from tumor patients and synovial fluid from rheumatoid arthritis patients), in terms of phenotype, transcriptome and functional properties (Goudot et al., 2017;Tang-Huau et al., 2018).

Our model itself has some limitations. Several intrinsic and extrinsic factors can influence the differentiation balance of monocytes. Intrinsic factors include cytokine concentration and cell density. For instance, higher proportions of mo-DC can be obtained by increasing the concentration of TNF-a (Figure 11A), while high cell densities increase mo-Mac differentiation (Figure 11B). Therefore, these factors are carefully controlled in our experiments so that they do not contribute to variability. Extrinsic factors lie with the variability of individual blood donors.

We observed that mo-DC/mo-Mac ratios vary between donors, even if monocytes are isolated

Unbiased analysis by single cell transcriptomic a. Regulon analysis versus transcription factor expression

Regulation of gene expression is fundamental during differentiation. Transcription factors (TF)

are key proteins in this regulation and thus, they are a focus when studying molecular pathways of differentiation. However, the sole expression of a TF is not informative enough to build a regulatory gene network, as changes in TF expression could be imperceptible or do not necessarily reflect the activity of that TF on gene expression. By contrast, expression analysis of the genes controlled by a TF serves as a readout for activity. In the past few years, algorithms to measure TF activity in transcriptomic data have emerged such as SCENIC [START_REF] Aibar | SCENIC: Single-cell regulatory network inference and clustering[END_REF], Dorothea/Viper [START_REF] Garcia-Alonso | Benchmark and integration of resources for the estimation of human transcription factor activities[END_REF], Aracne [START_REF] Margolin | ARACNE: An algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context[END_REF], among others. They allow to calculate the activity of a regulon, i.e. the expression of a set of genes controlled by a specific TF. In my project, I used the Dorothea/Viper described by [START_REF] Garcia-Alonso | Benchmark and integration of resources for the estimation of human transcription factor activities[END_REF], which is based on TF-target interactions obtained through manually curated repositories, interactions derived from ChIP-seq binding data, in silico prediction of TF binding on gene promoters, and inference from large gene expression data sets. I chose this method because it is based on empiric TF-target interactions and allows filtering the regulons by the level of confidence of the information used to build the regulon.

Using this approach, I was able to identify IRF1 as a candidate that could modulate mo-mac differentiation. Its expression was decreasing during monocyte differentiation but we found a cluster of cells where IRF1 TF activity was highly active. This observation was validated with silencing experiments in differentiating monocytes.

A limitation of these approaches it that they rely on repositories of TF-target interactions that may not be comprehensive enough. Indeed, ETV6 targets have not been widely studied and this lack of information makes ETV6 regulon unreliable. Therefore, ETV6 did not appear as a candidate based on this method, although we validated its role in monocyte differentiation.

b. Integration methods of several data sets

In scRNAseq analysis, batch effect refers to changes in gene expression due to technical variability such as sample processing at different times or sequencing in different lanes of the chip. To overcome the batch effect, normalization and integrations toolkits have been developed to align several data sets. The integration of data sets is performed to allow the identification of shared subpopulations across datasets, and under the assumption that there is a correspondence between datasets. In this thesis, I used two methods for different situations; ( 1) "MapQuery" to re-analyze a public data set of human PBMCs from patients with a mutation in ETV6, and ( 2) "STACAS" to analyze my own kinetic data sets of differentiating monocytes.

First, I used the MapQuery function of Seurat [START_REF] Hao | Integrated analysis of multimodal single-cell data[END_REF]. This algorithm will project the query cells (PBMC from healthy donors and patients) into a the reference UMAP (obtained from [START_REF] Hao | Integrated analysis of multimodal single-cell data[END_REF]) and cells will be annotated accordingly. This method is useful when we analyze well-characterized samples such as PBMC, and when we do not expect to find "new" populations.

Second, I chose STACAS, which allows to filter the anchors used for the aligment of the different data sets. The anchors are cross-dataset pairs of cells that correspond to the same state across samples. According to its developers, STACAS can accurately align scRNA-seq datasets composed of only partially overlapping cell populations [START_REF] Andreatta | STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data[END_REF], especially when Seurat aligment overcorrects the batch effect and overlays samples with little genes in common. This was the case in my datasets, as it has been reported that there is a time-dependent effect of IL-4 on monocytes (Sander et al., 2017). Thus, I assumed that monocytes from 3 hours culture could not be in the same cell state as monocytes after 24 hours of culture. A proof that the cells are not "forcedly separated" is that contaminating "intermediate" monocytes (CD14 + CD16 + cells) clustered together independently of the time point. Nevertheless, our scRNAseq kinetics experiment could be improved with more time points, especially one after 5 days in culture. This could make the integration of all the data sets easier, as there would be more "anchors" between the time points and facilitate the identification of "mo-DC" and "mo-mac" paths.

c. RNA velocity

In my project, I used ScVelo as a method to perform RNA velocity inferences. ScVelo is a widely used toolkit for the analysis of RNA velocity in single cells [START_REF] Bergen | Generalizing RNA velocity to transient cell states through dynamical modeling[END_REF]. It estimates RNA velocities by three methods; stochastic, deterministic, or dynamical. The stochastic model has been proposed for cell-specific dynamics [START_REF] Bergen | Generalizing RNA velocity to transient cell states through dynamical modeling[END_REF] and was the model I used to infer RNA velocity directions. Expression kinetics are inherently stochastic, due to random biomolecular interactions in the activity of the RNA synthesis and stochastic rates of transcription [START_REF] Bergen | RNA velocity-current challenges and future perspectives[END_REF]. It has been proposed that these sources of randomness can have important implications and be informative during cell fate decisions, when epigenetic priming or environmental signals guide different cellular decisions of transcriptionally similar cells [START_REF] Soldatov | Spatiotemporal structure of cell fate decisions in murine neural crest[END_REF], for example cytokine-driven differentiation of non-precommitted monocytes. The deterministic model, which describes the kinetics by differential equations, does not allow the identification of other sources of heterogeneity in kinetic rates, such as those imposed by external factors [START_REF] Bergen | RNA velocity-current challenges and future perspectives[END_REF]. Indeed, when analyzing my data, I observed that only the stochastic model resulted in directions that correlated with the biological process. Thus, when choosing a method to calculate RNA velocity, the nature of the data must be considered. Another important point is the need for previous and biased knowledge of the process being studied.

Several limitations of studying cellular dynamics using RNA velocity modelling approaches have been described. For instance, [START_REF] Bergen | RNA velocity-current challenges and future perspectives[END_REF] detailed that changes in transcription rate can induce a boost in gene expression, which would incorrectly yield negative velocity estimates interpreted as down-regulation (as seen in Figure 12 upper box). Another common example of incomplete scope is the analysis of populations exclusively at steady-state, such as PBMCs. Such analysis would show cell dynamics that could be explained by genes with high noise

In vivo validation using the Cx3cr1 CreER model

We performed in vivo validation of the role of Etv6 in monocyte differentiation using the Cx3cr1 CreER model. A limitation of our study is that Cx3cr1 creER also target cDCs [START_REF] Liu | In vivo analysis of dendritic cell development and homeostasis[END_REF]) and thus we cannot unequivocally prove that the effect on EAE progression is due to a deletion of Etv6 in monocytes and not in cDCs. However, some evidence supports our hypothesis. It has been reported that Batf3 -/-mice, which have defective cDC1 development, are susceptible to EAE [START_REF] Edelson | Batf3-Dependent CD11blow/-Peripheral Dendritic Cells Are GM-CSF-Independent and Are Not Required for Th Cell Priming after Subcutaneous Immunization[END_REF], suggesting that cDC1 are not involved in EAE induction. In addition, antigen presentation of MOG by mo-DC, but not cDC, is required for EAE induction [START_REF] Amorim | IFNγ and GM-CSF control complementary differentiation programs in the monocyte-to-phagocyte transition during neuroinflammation[END_REF]. This data suggests that it is unlikely that the decrease in EAE severity in Cx3cr1 creER Etv6 fl/fl is due to Etv6 deletion in cDCs. However, the ideal control wound be to induce EAE in CD11c cre Etv6 fl/fl mice and evaluate the progression of the disease as well as the mo-DC numbers in the subcutaneous LN. I would expect no difference between CD11c cre Etv6 fl/fl and Etv6 fl/fl mice in terms of severity of EAE symptoms.

On the other hand, IFNb treatment improves EAE symptoms [START_REF] Axtell | T helper type 1 and 17 cells determine efficacy of interferon-Β in multiple sclerosis and experimental encephalomyelitis[END_REF][START_REF] Prinz | Distinct and Nonredundant In Vivo Functions of IFNAR on Myeloid Cells Limit Autoimmunity in the Central Nervous System[END_REF][START_REF] Rasouli | IFN-β Acts on Monocytes to Ameliorate CNS Autoimmunity by Inhibiting Proinflammatory Cross-Talk Between Monocytes and Th Cells[END_REF]. After Etv6 deletion in monocytes, we observed increased type I IFN activation in all immune cells analysed in bone marrow, blood and spleen. So, we cannot discard a role for type I IFN activation in the better EAE outcome in Cx3cr1 creER Etv6 fl/fl mice.

To address this question, we could induce EAE in IFNAR -/-mice crossed with

Cx3cr1 creER Etv6 fl/fl , and analyse mo-DC numbers and MOG tetramers in subcutaneous LN.

However, the analysis of EAE progression would be confounded by the fact that IFNAR -/-mice develop more severe symptoms after disease onset [START_REF] Prinz | Distinct and Nonredundant In Vivo Functions of IFNAR on Myeloid Cells Limit Autoimmunity in the Central Nervous System[END_REF]. Thus, this experiment could clarify the role of type I IFN activation in the effect of Etv6 deletion on monocyte skewed differentiation but not in EAE progression.

Inflammatory models

In this work I used two models of inflammation to study the role of Etv6 in monocyte commitment. Although the concept of inflammation is generally related to the response to a pathogenic stimulus, sterile inflammation commonly occurs in situations such as trauma, ischemia-reperfusion injury, atherosclerosis, stroke, myocardial infarction, or transplantation.

Here, we used thioglycolate-induced sterile inflammation, which induces into the peritoneal cavity a strong recruitment of monocytes [START_REF] Kool | Alum adjuvant boosts adaptive immunity by inducing uric acid and activating inflammatory dendritic cells[END_REF] that will further differentiate to mo-DC and mo-mac. Our lab recently showed that toll-like receptors ligands favor monocyte differentiation into mo-mac (Coillard et al., 2021). Therefore, we decided to use a model of sterile inflammation to avoid confounding effects due to exposure to pathogen-derived products. In addition, monocyte-derived cells are well characterized in the peritoneal cavity.

Thus, it was a suitable model to study a potential shift in monocyte differentiation.

On the other hand, EAE is a good model for studying neuro-inflammation. However, an important difference between EAE and MS is that the former requires an immunization step for induction. By contrast, in humans the priming with myelin antigens is not artificial, and multiple antigens are involved. Therefore, the mechanism of induction of EAE in mice and MS in human might differ significantly.

B. Discussion of results and proposed model

Repressing mo-Mac differentiation

Monocytes are not pre-committed to one cell fate. I observed a transcriptomic heterogeneity in scRNAseq data of CD14 + monocytes, consistent with the "neutrophil-like" and "DC-like" monocytes previously reported [START_REF] Weinreb | Lineage tracing on transcriptional landscapes links state to fate during differentiation[END_REF][START_REF] Yáñez | Granulocyte-Monocyte Progenitors and Monocyte-Dendritic Cell Progenitors Independently Produce Functionally Distinct Monocytes[END_REF]. However, environmental cues, such as agonists of Aryl Hydrocarbon receptor or pathogen-derived products, can drastically direct monocyte differentiation, as our lab has previously shown (Coillard et al., 2021;Goudot et al., 2017). These observations led us to the hypothesis that

IFN type I stimulation: promoting mo-Mac

Here I showed that in conditions where monocytes can differentiate into both mo-mac and mo-DC, IFNa and b skew monocyte differetiation towards mo-mac. Although I did not characterize the molecular mechanism behind the IFN-I effect on monocyte differentiation, we propose that IFN-I signalling could antagonize the mo-DC program driven by IL-4, via the cross-talk of STAT1 and STAT6 [START_REF] Dickensheets | Inhibition of IL-4-inducible gene expression in human monocytes by type I and type II interferons[END_REF][START_REF] Ohmori | IL-4-induced STAT6 suppresses IFN-gamma-stimulated STAT1-dependent transcription in mouse macrophages[END_REF]. Type I IFN is an important inflammatory signal and its expression is increased in some pathological conditions. For instance, systemic lupus erythematosus (SLE) is an autoimmune disease characterized by an increase in interferon type I signature [START_REF] Zhuang | Animal models of interferon signature positive lupus[END_REF]. COVID-19 is also characterized by an increase in type I IFN [START_REF] Knoll | Monocytes and Macrophages in COVID-19[END_REF]. Thus, it would be interesting to better understand the effect of IFN-I on monocyte differentiation in these pathological conditions and the potential relationship to the pathogenesis.

ISG + monocytes: alternative fate for monocytes or a transitional state?

We have shown that monocytes culture triggers a wave of ISGs expression after around 9 hours. By scRNAseq, we observed that ISGs expression is restricted to one cluster of cells.

Monocytes expressing interferon related genes have also been described by scRNAseq data ex vivo. In a model of injured liver, clustering of Ly6C high monocytes sorted from LysM DCommd10 and Commd10 fl/fl at 24h showed a cluster of cells representing around 1% of the cells, expressing ISGs such as Ifit1, Ifit2, Ifit3 [START_REF] Cohen | COMMD10 is critical for Kupffer cell survival and controls Ly6Chi monocyte differentiation and inflammation in the injured liver[END_REF]. During the acute and the chronic phase of EAE, sorted CD11b + Ly6G -cells (excluding CX3CR1 high CD44 low microglia) from CNS were analysed by scRNAseq. It revealed a cluster of Ifit2 + monocytes expressing Ifit2, Rsad2, Ifit1, Irf7, among others [START_REF] Giladi | Cxcl10 + monocytes define a pathogenic subset in the central nervous system during autoimmune neuroinflammation[END_REF]. Moreover, transcriptomic analysis of CNS monocytes in the early phase of EAE showed two clusters enriched in the type I IFN signature [START_REF] Amorim | IFNγ and GM-CSF control complementary differentiation programs in the monocyte-to-phagocyte transition during neuroinflammation[END_REF]. In addition, a recent meta-analysis integrating 41 studies of scRNAseq datasets of human mononuclear phagocytes also identified a cluster present in health and disease expressing ISG including ISG15, ISG20, IFIT1, IFIT2 and IFIT3 [START_REF] Mulder | Cross-tissue single-cell landscape of human monocytes and macrophages in health and disease[END_REF].

Together, these data suggest that ISG + monocytes exist at steady state and in pathological conditions in human and mouse.

It has been proposed that ISG + monocytes could be a final state of monocyte differentiation [START_REF] Amorim | IFNγ and GM-CSF control complementary differentiation programs in the monocyte-to-phagocyte transition during neuroinflammation[END_REF][START_REF] Giladi | Cxcl10 + monocytes define a pathogenic subset in the central nervous system during autoimmune neuroinflammation[END_REF]. This is based on scRNAseq data where ISG + monocytes cluster separately from other cells or seem to have a different dynamic. However, ISG expression could superimpose on the core transcriptional program and dominate detected mRNA, as it occurs with cycling genes (Luecken and Theis, 2019) or the migratory program of DCs [START_REF] Maier | A conserved dendritic-cell regulatory program limits antitumour immunity[END_REF]. This phenomenon could bias the interpretation of the data. Our own data suggests that ISGs could be early markers of differentiating monocytes rather of a final fate, because the ISG + cluster does not persist at latter time points. By contrast, contaminating CD16 + intermediate monocytes cluster together across different time points.

Therefore, I propose that ISG + monocytes represent a transitional state of differentiating monocytes.

These observations raise the question of whether ISG + monocytes would give rise exclusively to mo-mac. To answer this, it would be necessary to build a "reporter" monocyte for the expression of ISG and then follow their progeny. Alternatively, ISG + monocytes could be sorted and re-cultured to evaluate their outcome. However, this would require identifying a surface marker for this population, which will be challenging.

Other TFs that modulate monocyte differentiation

The temporal scRNAseq analysis revealed several transcription factors that could modulate monocyte differentiation. For instance, IRF1 is needed for mo-mac differentiation. IRF1 is known to control the expression of ISG in macrophages [START_REF] Langlais | The macrophage IRF8/IRF1 regulome is required for protection against infections and is associated with chronic inflammation[END_REF][START_REF] Piccolo | Opposing macrophage polarization programs show extensive epigenomic and transcriptional cross-talk[END_REF][START_REF] Song | IRF1 governs the differential interferon-stimulated gene responses in human monocytes and macrophages by regulating chromatin accessibility[END_REF]. In addition, we detected the spontaneous expression of ISG in culture, suggesting that differentiating monocytes secrete type I interferon (which we failed to detect using several techniques). However, blocking ISG expression with the IFN! blocker B18R did not have any effect on monocyte differentiation. Therefore, the activity of IRF1 might be controlling other pathways involved in monocyte differentiation, independently of the type I IFN pathway. This question will require further investigation. We could perform transcriptomic analysis in conditions were IRF1 is silenced to identify the genes controlled by IRF1, or perform chromatin immunoprecipitation (ChIP) of IRF1 followed by sequencing to identify the direct target genes in monocytes.

My work also revealed a role for ETS2, MXD1 and MAFF in mo-mac differentiation, while ZNF366 is involved in mo-DC differentiation. More work is needed to understand what aspects of monocyte differentiation they control and how they may be important in a physiological situation.

C. Conclusions

This thesis work provides new insight into the molecular regulators orchestrating monocyte fate decision. I showed that ETV3 and ETV6 repress mo-mac differentiation enabling mo-DC commitment. Furthermore, we reported a role for type I IFN signaling in monocyte fate decision, although there are molecular aspects that remain to be clarified. Additionally, this work provides evidence that monocyte commitment occurs during the first hours of monocyte exposure to cytokines.

ETV6 role in mo-DC differentiation was validated in two in vivo models of inflammation. Etv6 deletion on monocytes resulted in decreased mo-DC numbers in inflamed peritoneal cavity and in the draining lymph nodes of mice immunized for EAE induction. Moreover, Etv6 deficient mice had decreased EAE symptoms. Thus, we provide a proof-of-concept that Etv6 inhibition in monocytes could be used as a therapeutic strategy in MS-like disease. I also evidenced a role for other transcription factors in monocyte differentiation: IRF1, ETS2, MXD1

MAFF and ZNF366. The identification of new transcription factors as regulators of monocyte differentiation should offer new therapeutic opportunities in chronic inflammatory diseases.

Opinion

Decoding the Heterogeneity of Human Dendritic Cell Subsets Javiera Villar 1 and Elodie Segura 1, * Dendritic cells (DCs) have been classified into distinct subsets based on phenotype and ontogeny. In the past few years, high throughput single-cell approaches have revealed further heterogeneity of human DCs, in particular at the transcriptomic level. Herein examined, are recent studies describing new human DC populations based on single-cell RNA-seq analysis, and a unified view of these emerging DC populations is presented. Also assessed are the features that define bona fide DC lineages, as opposed to cell states of the same lineage. Finally, where these newly described DC populations fit in the ontogeny-based classification of human DCs is examined.

Key Features Defining DC Subsets

DCs (see Glossary) are recognized as the most efficient antigen-presenting cells, and are present throughout the mammalian body in both lymphoid organs and peripheral tissues. Since the initial identification of DCs in mouse spleen by Ralph Steinman [1], methodological advances have gradually revealed the complexity of DC populations. Multi-color flow cytometry has shown the existence of several subpopulations of DCs displaying distinct surface phenotypes [2]. Transgenic mouse models have revealed the transcriptional control of DC lineages and specific functions of DC subsets [3]. Transcriptomic analyses have also evidenced a conserved gene expression profile for each DC subset across tissues and species [4,5]. The current classification of DC subsets is based on their cellular and molecular ontogeny: (i) plasmacytoid DCs (pDC);

(ii) type 1 classical DCs (cDC1); (iii) type 2 classical DCs (cDC2); and (iv) monocyte-derived DCs (mo-DC) [6](Table 1).

To better understand the biology of human immune cells, an increasing number of groups are analyzing immune cells, including DCs, directly purified from human tissues using high-dimensional single-cell approaches. These single-cell analyses have revealed further heterogeneity within human DC subsets, especially at the transcriptional level (Table 2). However, in this rapidly evolving field, there is still little consensus on the identification and naming of new DC populations. In this Opinion article, the aim is to provide a unified view of the newly described human DC populations, and to discuss the limitations of single-cell RNA sequencing (scRNA-seq) for identifying DC subsets. It is argued, that differential gene expression profiles are not sufficient to distinguish bona fide DC lineages from cell states of the same lineage. Finally examined, are the place of these newly described DC populations in the widely used ontogeny-based DC classification.

Transcriptional Heterogeneity of Human DCs Revealed by Single-Cell Approaches

DCs orchestrate immune responses, and manipulating their properties holds great promise for therapeutic strategies to treat chronic inflammatory diseases, cancers, graft rejection, or to improve vaccine efficiency [7][8][9]. DC dysfunction may also play acrucialpartinautoimmune diseases. Because each DC subset displays unique functions [3], it is vital to understand the Highlights ScRNA-seq analyses of human DC subsets have revealed unexpected heterogeneity within cDC2 and pDC subsets, leading to the identification of new populations.

AXL + SIGLEC6 + DCs display a mixed pDC/cDC transcriptional profile and can differentiate into cDC2 when placed in culture.

DC3 have a mixed cDC2/monocyte gene expression profile and develop from precursors distinct from other DC lineages and monocytes.

All human DC subsets express a convergent transcriptional program when they mature in vivo, in lymphoid organs or peripheral tissues.

In the ontogeny-based classification of human DCs, DC3 may represent a new DC subset, along with pDC, cDC1, cDC2, and mo-DC.

complexity of human DC subsets to decipher their specificproperties.Recentstudiesusing scRNA-seq have revisited this issue with unprecedented resolution. However, results from this body of work can be confusing, when different groups propose contradictory interpretations or different terminologies for apparently similar populations.

One important result from a recent series of human scRNA-seq studies, is that unbiased clustering based on differential gene expression, confirms the earlier classification of DCs into three main groups (pDC, cDC1, and cDC2). Another striking observation is that cDC1 display remarkable homogeneity as a subset in all tissues and pathological situations analyzed. While previous work suggested some level of heterogeneity in pDC and cDC2, scRNA-seq analyses have provided irrefutable evidence of the existence of different populations within these DC subsets.

AXL + SIGLEC6 + DCs: pDC-Related Cells or cDCs Precursors?

Human pDC do not express CD11c, and are usually defined by their expression of CD123/IL3R, CD303/BDCA2, and CD304/BDCA4 [START_REF]Resuspend the cells in 30 ul of antibody cocktail and incubate for 20 min at 4 °C in the dark to minimize exposure to light. 11. Wash the cells by adding 200 ul of staining buffer per well and centrifuge[END_REF]. Two studies have proposed the existence of subsets of pDC based on the differential expression of CD2 [11] or CD5 [12]. scRNA-seq analysis has shed new light on this question, showing the presence in human blood of a CD123 + population with a mixed pDC/cDC gene expression profile, best characterized by high expression of AXL and SIGLEC6, which encode two surface molecules that can be used to distinguish this population [13,[START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF]. This finding was consistent with previous observations of preferential AXL expression in blood CD2 + pDC [11] and CD2 + CD5 + pDC [12]. High-dimensional cytometry further confirmed the phenotype of this population as being AXL + SIGLEC6 + CD123 + CD2 + CD5 + [START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF][15][START_REF] Leylek | Integrated cross-species analysis identifies a conserved transitional dendritic cell population[END_REF]. These AXL + SIGLEC6 + DCs do not secrete IFNa (a defining functional feature of pDC) but are efficient for T cell stimulation (a property classically associated with cDCs) [12][13][START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF][15][START_REF] Leylek | Integrated cross-species analysis identifies a conserved transitional dendritic cell population[END_REF]. They also display the typical morphology of cDC [13,[START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF]. The identity of these cellsr e m a i n su n c l e a r ,a st h e y show themselves some level of heterogeneity, in particular with a spectrum of expression for CD123, CD5, or CD11c [13][START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF][15]. AXL + SIGLEC6 + DCs are able to differentiate into cDCs (predominantly cDC2) when placed in in vitro culture systems [13,[START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF][START_REF] Cytlak | Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans[END_REF], and therefore, were proposed to be DC precursors [START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF]. Putative mouse counterparts of AXL + SIGLEC6 + DCs were later identified, but these do not express either AXL or SIGLEC6 [START_REF] Leylek | Integrated cross-species analysis identifies a conserved transitional dendritic cell population[END_REF]. Because this population

Glossary

Ascites: abnormal infiltration of fluid in the abdomen.

Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq): next generation sequencing method providing the DNA sequences of open chromatin regions; this allows the inference of regions that are accessible for transcription factor binding.

Dendritic cell (DC): immune cell specialized for antigen presentation and T cell stimulation; can migrate from peripheral tissues to lymphoid organs.

Fate-mapping: method to trace cell lineages, for instance by transferring purified precursor cells or inserting a genetic mark such as a fluorochrome in precursor cells.

Lamina propria: mucosal connective tissue that lies between the epithelium and underlying tissues.

Macrophage: antigen presenting immune cell residing in peripheral and lymphoid tissues, and specialized in ingesting pathogens and dying cells. Maturation: process by which dendritic cells modify their morphology and expression of molecules (including surface), rendering the cells more efficient in their interaction with T cells. Monocyte: immune cell that circulates in the blood and massively infiltrates tissues upon inflammation.

Pitt-Hopkins syndrome: rare genetic disorder due to the loss of function of the transcription factor 4 (TCF4), characterized by a moderate to severe intellectual disability. Patients show an impairment of the pDC compartment in terms of number, phenotype, and

Trends in Immunology

displays an intermediate phenotype between pDC and cDCs, both at the level of their transcriptome and surface markers, the term 'transitional DCs' was also proposed [START_REF] Leylek | Integrated cross-species analysis identifies a conserved transitional dendritic cell population[END_REF].

The Expanding cDC2 Family

In humans, cDC2 are usually characterized by their expression of CD1c/BDCA1. Based on their phenotypic characterization by flow cytometry, two studies have proposed the existence in blood

Trends in Immunology

Trends in Immunology, Month 2020, Vol. xx, No. xx 3

and skin of two subsets of cDC2, CD5 + ,a n dC D 5 - [START_REF] Yin | Human blood cd1c+ dendritic cells encompass cd5high and cd5low subsets that differ significantly in phenotype, gene expression, and functions[END_REF][START_REF] Korenfeld | A type of human skin dendritic cell marked by CD5 is associated with the development of inflammatory skin disease[END_REF]. In addition, a population of CD1c + CD14 + cDC was reported in blood [START_REF] Bakdash | Expansion of a BDCA1+CD14+ myeloid cell population in melanoma patients may attenuate the efficacy of dendritic cell vaccines[END_REF]. In these studies, CD1c + CD5 -DCs and CD1c + CD14 + cDCs, both expressed genes classically associated with monocytes (such as VCAN, FCN1, S100A8, and S100A9) [START_REF] Yin | Human blood cd1c+ dendritic cells encompass cd5high and cd5low subsets that differ significantly in phenotype, gene expression, and functions[END_REF][START_REF] Bakdash | Expansion of a BDCA1+CD14+ myeloid cell population in melanoma patients may attenuate the efficacy of dendritic cell vaccines[END_REF]. These observations suggested the existence of a new DC subset displaying hybrid cDC/monocyte features, but could also be explained by the co-isolation of a mixed population of cDC2 and monocytes that were analyzed together by bulk transcriptomics. ScRNA-seq analysis confirmed the existence of a population of CD1c + DCs expressing at the same time cDC2 classical marker genes (such as CD1c, FCER1A, and CLEC10A)a n dm o n o c y t e -r e l a t e dg e n e s( s u c ha sVCAN, FCN1, S100A8, S100A9, CD14, and CD163) [13]. These DCs were best defined as CD1c + CD163 + ,andweretermed'DC3'. Subsequent studies, using high-dimensional cytometry, refined the phenotypic definition of blood cDC2 as CD1c + BTLA + with low to high expression of CD5, and DC3 as CD88 -CD1c + CD163 + with low to high expression of CD14 [START_REF] Cytlak | Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans[END_REF][START_REF] Dutertre | Single-cell analysis of human mononuclear phagocytes reveals subset-defining markers and identifies circulating inflammatory dendritic cells[END_REF][START_REF] Bourdely | Transcriptional and functional analysis of cd1c+ human dendritic cells identifies a CD163+ subset priming CD8+CD103+ T cells[END_REF]. Of note, DC3 were also described in human cord blood [START_REF] Jin | Characterization of dendritic cell subtypes in human cord blood by single-cell sequencing[END_REF].

A recent scRNA-seq study has added another layer of complexity to the cDC2 family. Clec10A is considered a phenotypic marker of human cDC2 [START_REF] Heger | CLEC10A is a specific marker for human CD1c+ dendritic cells and enhances their toll-like receptor 7/8induced cytokine secretion[END_REF]. A population of Clec10A -cDC2 was described in human spleen but absent from blood. In this study, CD1c + Clec10A -were termed 'DC2A' and CD1c + Clec10A + 'DC2B',a n dw e r ec h a r a c t e r i z e dm o s t l yb yt h e i rs i m i l a r i t yt o their mouse putative counterparts, Tbet + 'DC2A' and Tbet -'DC2B' [START_REF] Brown | Transcriptional basis of mouse and human dendritic cell heterogeneity[END_REF]. Based on their higher expression of cDC2 markers Clec10A and CD1c, DC2B were proposed to correspond to the well-characterized classical cDC2 subset, while DC2A were thought to be a new population of cDC2-related DCs [START_REF] Brown | Transcriptional basis of mouse and human dendritic cell heterogeneity[END_REF]. However, this population has not been reported by others so far. In a scRNA-seq analysis of human tonsil antigen-presenting cells [START_REF] Durand | Human lymphoid organ cDC2 and macrophages play complementary roles in T follicular helper responses[END_REF], a population of CD14 -cells were observed, which did not correspond to cDC1 nor cDC2, and which exhibited high expression of LTB and RUNX3 -two genes enriched in the described DC2A population. It was proposed that these LTB + cells were precursor cells, because a proportion of them were mitotic. Of note, AREG, another proposed DC2A marker gene, was more expressed in Clec10A + cDC2 in the dataset, compared with LTB + cells [START_REF] Durand | Human lymphoid organ cDC2 and macrophages play complementary roles in T follicular helper responses[END_REF]. Nevertheless, the gene profile of this putative human 'DC2A' remains ill defined.

A Thin Line between mo-DC and DC3

Fate-mapping techniques in mice have demonstrated that monocytes can differentiate into DC-like cells in mucosal or inflamed tissues [START_REF] Tamoutounour | Origins and functional specialization of macrophages and of conventional and monocyte-derived dendritic cells in mouse skin[END_REF][START_REF] Hohl | Inflammatory monocytes facilitate adaptive CD4 T cell responses during respiratory fungal infection[END_REF][START_REF] Kool | Alum adjuvant boosts adaptive immunity by inducing uric acid and activating inflammatory dendritic cells[END_REF][START_REF] León | Monocyte-derived dendritic cells formed at the infection site control the induction of protective T helper 1 responses against Leishmania[END_REF]. Despite obvious methodological limitations, there is also accumulating evidence that this phenomenon can occur in vivo in humans [START_REF] Coillard | In vivo differentiation of human monocytes[END_REF]. Bulk transcriptomic analysis was initially used to identify human in vivo-generated mo-DC, and a transcriptomic similarity with blood monocytes or in vitro-derived mo-DC [START_REF] Segura | Human inflammatory dendritic cells induce Th17 cell differentiation[END_REF][START_REF] Watchmaker | Comparative transcriptional and functional profiling defines conserved programs of intestinal DC differentiation in humans and mice[END_REF] was observed.

ScRNA-seq studies have confirmed the presence of a human DC population, displaying a mixed cDC2/monocyte transcriptional profile (CD1c, FCER1A, CLEC10A, VCAN, S100A8, S100A9, and CD14) in peritoneal tumor ascites [START_REF] Tang-Huau | Human in vivo-generated monocyte-derived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway[END_REF], inflamed and uninflamed intestinal lamina propria [START_REF] Martin | Single-cell analysis of Crohn's disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy[END_REF], non-small cell lung cancer [START_REF] Zilionis | Single-cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species[END_REF], and melanoma-draining lymph nodes [START_REF] Binnewies | Unleashing type-2 dendritic cells to drive protective antitumor CD4+ T cell immunity[END_REF]. Given that blood DC3 show an overall similar profile, DC3 and 'mo-DC' have been proposed as being the same DC subset [START_REF] Dutertre | Single-cell analysis of human mononuclear phagocytes reveals subset-defining markers and identifies circulating inflammatory dendritic cells[END_REF]. A closer look at the gene expression patterns of the two populations suggests that expression of other genes such as CD207 and DAB2 might help to distinguish them. CD207 is expressed by both mo-DC and cDC2 [START_REF] Martin | Single-cell analysis of Crohn's disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy[END_REF], but not by DC3 [START_REF] Dutertre | Single-cell analysis of human mononuclear phagocytes reveals subset-defining markers and identifies circulating inflammatory dendritic cells[END_REF]. DAB2 has comparable expression to mo-DC and macrophage clusters [START_REF] Tang-Huau | Human in vivo-generated monocyte-derived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway[END_REF][START_REF] Martin | Single-cell analysis of Crohn's disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy[END_REF], and is detected in blood pDC but not DC3 [13]. A side-by-side comparison of blood DC3 and tissue mo-DC in the same scRNA-seq study, would be needed to better define their respective gene signatures.

Combining gene expression profiling with analysis of surface molecules might also be necessary to discriminate these. DC3 express CD163 [13,[START_REF] Dutertre | Single-cell analysis of human mononuclear phagocytes reveals subset-defining markers and identifies circulating inflammatory dendritic cells[END_REF][START_REF] Bourdely | Transcriptional and functional analysis of cd1c+ human dendritic cells identifies a CD163+ subset priming CD8+CD103+ T cells[END_REF]b u tn o ta s c i t e sm o -D C [START_REF] Goudot | Aryl hydrocarbon receptor controls monocyte differentiation into dendritic cells versus macrophages[END_REF]. Of note,

Trends in Immunology

surface LSP1 has also been recently identified as a marker for ascites and in vitro-generated mo-DC, and not expressed by blood DC3 [START_REF] Moutel | Surface LSP-1 is a phenotypic marker distinguishing human classical versus monocyte-derived dendritic cells[END_REF]. However, the possibility that differential surface expression results from differential localization (blood versus tissue) cannot be completely ruled out. More in vivo evidence is needed to clarify whether DC3 and 'mo-DC' represent distinct subsets, ultimately displaying a similar phenotype, or variations of the same subset (for instance a blood state for DC3 versus a tissue state for the described mo-DC).

CCR7 + DCs: The Rediscovery of a Well-Known Phenomenon

ScRNA-seq analysis of DCs, isolated from human tissues other than blood, has revealed another previously unnoticed group of DCs, expressing high amounts of genes associated with DC maturation and migration (such as LAMP3, CCR7, FSCN1, CD83, and CCL22) [START_REF] Tang-Huau | Human in vivo-generated monocyte-derived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway[END_REF]. CCR7 + DCs, also referred to as 'activated DCs' or 'mature DCs enriched in immunoregulatory molecules' (mregDCs), were reported in liver tumors [START_REF] Zhang | Landscape and dynamics of single immune cells in hepatocellular carcinoma[END_REF], non-small lung cancer [START_REF] Zilionis | Single-cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species[END_REF][START_REF] Maier | A conserved dendritic-cell regulatory program limits antitumour immunity[END_REF], colon cancer [START_REF] Zhang | Single-cell analyses inform mechanisms of myeloid-targeted therapies in colon cancer[END_REF], melanoma-draining lymph nodes [START_REF] Binnewies | Unleashing type-2 dendritic cells to drive protective antitumor CD4+ T cell immunity[END_REF], inflamed colon of Crohn's disease patients [START_REF] Martin | Single-cell analysis of Crohn's disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy[END_REF] and ulcerative colitis [START_REF] Zhang | Single-cell analyses inform mechanisms of myeloid-targeted therapies in colon cancer[END_REF], skin of atopic dermatitis patients [START_REF] He | Single-cell transcriptome analysis of human skin identifies novel fibroblast subpopulation and enrichment of immune subsets in atopic dermatitis[END_REF], as well as in inflammatory peritoneal ascites of cancer patients [START_REF] Tang-Huau | Human in vivo-generated monocyte-derived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway[END_REF], and in the fluid of experimental skin blisters [START_REF] Chen | Re-evaluation of human BDCA-2+ DC during acute sterile skin inflammation[END_REF]. A similar population was also present in steady-state tonsils [START_REF] Durand | Human lymphoid organ cDC2 and macrophages play complementary roles in T follicular helper responses[END_REF], spleen [START_REF] Brown | Transcriptional basis of mouse and human dendritic cell heterogeneity[END_REF], thymus [START_REF] Park | A cell atlas of human thymic development defines T cell repertoire formation[END_REF], and skin [START_REF] He | Single-cell transcriptome analysis of human skin identifies novel fibroblast subpopulation and enrichment of immune subsets in atopic dermatitis[END_REF][START_REF] Xue | Transcriptome landscape of myeloid cells in human skin reveals diversity, rare populations and putative DC progenitors[END_REF], indicating that this population was not specific to inflamed tissues. The fact that this population was detected in inflammatory fluids [START_REF] Tang-Huau | Human in vivo-generated monocyte-derived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway[END_REF][START_REF] Chen | Re-evaluation of human BDCA-2+ DC during acute sterile skin inflammation[END_REF], which do not require dissociation prior to analysis, and by in situ staining [START_REF] Martin | Single-cell analysis of Crohn's disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy[END_REF][START_REF] Park | A cell atlas of human thymic development defines T cell repertoire formation[END_REF][START_REF] Xue | Transcriptome landscape of myeloid cells in human skin reveals diversity, rare populations and putative DC progenitors[END_REF] also shows that the expression of activation genes is not an artefact induced by tissue digestion.

While these cells all expressed a common gene signature of DC activation and maturation, a more detailed analysis showed that depending on context, this population also expressed genes associated with the transcriptional profile of cDCs [START_REF] Tang-Huau | Human in vivo-generated monocyte-derived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway[END_REF], cDC1 [START_REF] Zhang | Single-cell analyses inform mechanisms of myeloid-targeted therapies in colon cancer[END_REF], pDC [START_REF] Chen | Re-evaluation of human BDCA-2+ DC during acute sterile skin inflammation[END_REF], mo-DC [START_REF] Tang-Huau | Human in vivo-generated monocyte-derived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway[END_REF], AXL + SIGLEC6 + DCs [START_REF] Chen | Re-evaluation of human BDCA-2+ DC during acute sterile skin inflammation[END_REF], or those comprising both cDC1 and cDC2 [START_REF] Maier | A conserved dendritic-cell regulatory program limits antitumour immunity[END_REF][START_REF] Park | A cell atlas of human thymic development defines T cell repertoire formation[END_REF]. Collectively, these results suggest that all human DC types may express the same transcriptional module upon activation in vivo. This is consistent with mouse studies showing that DCs of any subset undergoing maturation, either homeostatic or upon exposure to a danger signal, converge towards a common transcriptional program [5,[START_REF] Manh | Plasmacytoid, conventional, and monocyte-derived dendritic cells undergo a profound and convergent genetic reprogramming during their maturation[END_REF]48].

Distinguishing Human DC Lineages Versus Cell States

ScRNA-seq analysis represents a snapshot of transcriptional states, which can be dynamic for myeloid cells, such as DCs that are constantly surveying their environment. Using scRNA-seq data to identify DC subsets purely based on differential gene expression can therefore be misleading, as illustrated by the CCR7 + DC population which has been observed in many recent studies. In this case, a superficial description of cell clusters might conclude in the identification of a new putative DC subset. However, a more detailed analysisby combining scRNA-seq with surface staining of phenotypic markers [START_REF] Maier | A conserved dendritic-cell regulatory program limits antitumour immunity[END_REF], or by applying gene signatures analysis [START_REF] Park | A cell atlas of human thymic development defines T cell repertoire formation[END_REF] has revealed that legacy markers of subset identity can also be detected, suggesting that CCR7 + DCs may correspond to DCs undergoing maturation.

Another important consideration when studying human DCs is the potential variability between individuals, as exemplified by the diversity in CD1c + DC phenotypes observed from different donors, using high-dimensional flow cytometry [15]. From a practical standpoint, if several donor samples cannot be analyzed via scRNA-seq analysis for practical reasons, identified populations may need to be validated in additional donors using other techniques.

What are the key features that define a bona fide DC subset (or lineage) as opposed to a transitory cell state? While distinct transcriptional programs might constitute a prerequisite for discriminating

Trends in Immunology

distinct subsets, this criterion is not sufficient, as outlined in the previous text. Therefore, scRNAseq analysis may provide a basis for DC subset identification, but it also needs to be complemented by other approaches (Box 1). Numerous studies in mice have evidenced functional specialization of DC subsets. However, functional properties do not necessarily correlate with lineage identity. For example, immature or mature populations from the same cDC lineage will display a differential ability in activating T cells via co-stimulatory signals as shown in vitro for human DCs or in vivo in mice [48][START_REF] Sallusto | Efficient presentation of soluble antigen by cultured human dendritic cells is maintained by granulocyte/macrophage colony-stimulating factor plus interleukin 4 and downregulated by tumor necrosis factor alpha[END_REF][START_REF] Wilson | Most lymphoid organ dendritic cell types are phenotypically and functionally immature[END_REF]. Therefore, distinct functional abilities might not necessarily define the attributes of DC subset identity. In line with the current DC classification based on ontogeny, it is argued that DC populations might only be considered distinct subsets if they possess distinct ontogeny, that is, separate developmental pathways controlled by specific transcription factors.

The methodological difficulties and available strategies for addressing the ontogeny of human DCs experimentally, have been reviewed previously [START_REF] Villar | Recent advances towards deciphering human dendritic cell development[END_REF]. With these technical limitations in mind, which of the new DC populations fulfill this criterion? AXL + SIGLEC6 + DCs seem to be related to pDC in their ontogeny. They depend on E2-2/TCF4 for their development, as pDC do; this has been shown by the partial decrease in AXL + SIGLEC6 + DC and pDC populations in the blood of Pitt-Hopkins syndrome patients, bearing a loss-of-function mutation for TCF4 [START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF]. In addition to TCF4, these cells express high amounts of BCL11A, RUNX2, and SPIB, all of which are transcription factors involved in pDC development [START_REF] Leylek | Integrated cross-species analysis identifies a conserved transitional dendritic cell population[END_REF]. Analysis of chromatin accessibility by Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) also suggests that TCF4 and RUNX2 are active in AXL + SIGLEC6 + DCs [START_REF] Leylek | Chromatin landscape underpinning human dendritic cell heterogeneity[END_REF]. Moreover, transitional DCs, (the mouse counterpart of AXL + SIGLEC6 + DCs) are severely decreased in CD11C cre Tcf4 fl/fl deficient mice, but unaffected by Irf8 deficiency in CD11C cre Irf8 fl/fl mice, similar to pDC [START_REF] Leylek | Integrated cross-species analysis identifies a conserved transitional dendritic cell population[END_REF]. The transcription factor KLF12 is preferentially expressed in AXL + SIGLEC6 + DCs, Box 1. Challenges in the Interpretation of Single-Cell RNA Sequencing Data to Identify New Dendritic Cell Populations

While single-cell RNA sequencing (scRNA-seq) analysis is usually considered unsupervised, there are several analysis biases. Algorithms have been developed for the automated identification of cell types in scRNA-seq data [START_REF] Abdelaal | A comparison of automatic cell identification methods for single-cell RNA sequencing data[END_REF]. However, automated identification is not suitable for cell types that closely resemble each other, such as dendritic cell (DC) subsets, and cell clusters are generally manually annotated. Prior knowledge therefore necessarily influences the identification of DC clusters, based on the presence of canonical markers among differentially expressed genes (see Table 1 in main text). A major challenge is to decide on how many clusters are present in the dataset. There is no consensus on how to predict the number of clusters, so it is left to the user to determine the number of clusters that are considered biologically relevant [START_REF] Luecken | Current best practices in single-cell RNA-seq analysis: a tutorial[END_REF]. Under-clustering can hide a rare but biologically relevant population. By contrast, over-clustering can result in partitioning a population into several clusters that simply represent stochastic variations instead of biological states. A possibility for mitigating this problem might be to re-cluster a specific population of interest, as performed for cDC2 clusters [13,[START_REF] Binnewies | Unleashing type-2 dendritic cells to drive protective antitumor CD4+ T cell immunity[END_REF], but such analysis will almost certainly reveal further heterogeneity that might be difficult to interpret.

Cluster annotation is usually based on the most differentially expressed genes. The output of such analysis is highly dependent on the populations being compared to one another. This can introduce some bias regarding the identification of marker genes for putative new populations. This difficulty is illustrated by the divergent interpretations of the level of expression of monocyte-related genes by DC3 [13,[START_REF] Dutertre | Single-cell analysis of human mononuclear phagocytes reveals subset-defining markers and identifies circulating inflammatory dendritic cells[END_REF]. One way to overcome this issue may be to assess the enrichment for transcriptomic signatures derived from independent datasets. This can be achieved by calculating an enrichment score for each individual cell [START_REF] Tang-Huau | Human in vivo-generated monocyte-derived dendritic cells and macrophages crosspresent antigens through a vacuolar pathway[END_REF][START_REF] Tirosh | Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq[END_REF], or by using gene set enrichment analysis (GSEA)-based methods [START_REF] Subramanian | Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles[END_REF] such as connectivity MAP (cMAP) which compares clusters to one another [START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF][START_REF] Balan | Large-scale human dendritic cell differentiation revealing Notch-dependent lineage bifurcation and heterogeneity[END_REF]. By considering the entire gene expression profile instead of the most differentially expressed genes, these approaches provide valuable complementary information.

Finally, another challenge lies in the interpretation of cellular changes that can superimpose on the core transcriptional program and dominate detected mRNA. This is particularly true for cell cycle genes, which are often regressed out to limit their weight in the analysis [START_REF] Luecken | Current best practices in single-cell RNA-seq analysis: a tutorial[END_REF]. Recent scRNA-seq studies on human DCs have shown that this is also the case for DC maturation genes. Such transcriptional changes can be dynamic for DC exposed to signals from their microenvironment, and can become a confounding factor for scRNA-seq data interpretation. New methods coupling surface protein staining to scRNA-seq detection, such as cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) [START_REF] Stoeckius | Simultaneous epitope and transcriptome measurement in single cells[END_REF], are useful to circumvent this issue [START_REF] Maier | A conserved dendritic-cell regulatory program limits antitumour immunity[END_REF].

Trends in Immunology

and their mouse counterparts compared to other DC subsets, but whether it is involved in their differentiation remains unknown [START_REF] Leylek | Chromatin landscape underpinning human dendritic cell heterogeneity[END_REF]. Evidence for a unique transcriptional regulation of AXL + SIGLEC6 + DCs, distinct from pDC, is still lacking.

Regarding DC3, two recent studies shed lightontheirdevelopmentalpathwayusingin vitro culture models, in which human hematopoietic progenitors could give rise simultaneously to cDC2, DC3, and monocytes [START_REF] Cytlak | Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans[END_REF][START_REF] Bourdely | Transcriptional and functional analysis of cd1c+ human dendritic cells identifies a CD163+ subset priming CD8+CD103+ T cells[END_REF]. In these cultures, purified monocytes or monocytecommitted precursors did not differentiate into DC3, but the IRF8 low fraction of granulocytemonocyte and DC progenitors gave rise to DC3 and monocytes along separate pathways, while pDC, AXL + SIGLEC6 + DCs, cDC1, and cDC2 derived from IRF8 high progenitors [START_REF] Cytlak | Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans[END_REF][START_REF] Bourdely | Transcriptional and functional analysis of cd1c+ human dendritic cells identifies a CD163+ subset priming CD8+CD103+ T cells[END_REF].

Observations from patients with IRF8 deficiencies also support this model. Specifically, patients with a total loss of IRF8 activity exhibit a complete absence of DC and monocyte development [START_REF] Cytlak | Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans[END_REF]. However, patients harboring a heterozygous or dominant negative mutation in IRF8 that results in reduced IRF8 activity, display decreased numbers of pDC, cDC1, and cDC2, but increased DC3 in blood [START_REF] Cytlak | Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans[END_REF], consistent with the idea that DC3 development is largely independent of IRF8. As shown in Batf3 -/-mice in which related transcription factors Batf and Batf2 can induce an alternative cDC1 development program [START_REF] Tussiwand | Compensatory dendritic cell development mediated by BATF-IRF interactions[END_REF], such genetic deficiencies may result in compensatory phenomena, where the activitieso fo t h e rt r a n s c r i p t i o nf a c t o r sw i t hs h a r e d properties can compensate for the deficient molecule at the molecular level. Therefore, these observations should be interpreted with caution. Nevertheless, these data suggest that two distinct developmental pathways might exist for cDC2 and DC3 in vivo.O fn o t e ,b o t h CD1c + BTLA + ??CD5 + and CD1c + BTLA + CD5 -DCs populations, were reported as reduced in the blood of patients with reduced IRF8 activity, while CD1c + CD163 + CD14 + and CD1c + CD163 + CD14 -DCs were expanded [START_REF] Cytlak | Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans[END_REF], validating their classification as cDC2 or DC3 populations, respectively.

The case of DC2A and DC2B populations is less clear. While there is evidence for differential expression of some transcription factors between mouse DC2A and DC2B, the requirement for distinct transcriptional regulators for their development, to our knowledge, has not been demonstrated [START_REF] Brown | Transcriptional basis of mouse and human dendritic cell heterogeneity[END_REF]. In mouse, in vivo lineage tracing has shown that pre-DCs give rise to both DC2A and DC2B, and DC2A appears to be enriched at mucosal sites, while their numbers are decreased upon microbiota depletion, by broad-spectrum antibiotics treatment; this suggested that signals from the tissue microenvironment could drive the expression of the DC2A phenotype in cDC2 [START_REF] Brown | Transcriptional basis of mouse and human dendritic cell heterogeneity[END_REF]. Therefore, DC2A and DC2B might represent variations of the same subset rather than distinct lineages, although this remains to be further tested. This is also consistent with the heterogeneity of cDC2 expression profiles between tissues reported in mouse [5,[START_REF] Guilliams | Unsupervised high-dimensional analysis aligns dendritic cells across tissues and species[END_REF]a n d human [15,[START_REF] Heidkamp | Human lymphoid organ dendritic cell identity is predominantly dictated by ontogeny, not tissue microenvironment[END_REF], suggesting tissue adaptation in response to microenvironmental signals. More work is needed to better characterize the putative DC2A and DC2B populations, particularly in humans. While mouse models can be useful for understanding DC biology, caution should be exercised in extrapolating murine findings and conclusions to humans. In particular, marker genes are not always directly translatable, as in the case of AXL + SIGLEC6 + DCs and their mouse counterparts [START_REF] Leylek | Integrated cross-species analysis identifies a conserved transitional dendritic cell population[END_REF].

Finally, by definition, mo-DC possess specific ontogeny. While monocytes differentiate into mo-DC in vitro (in human cultures and different models [START_REF] Goudot | Aryl hydrocarbon receptor controls monocyte differentiation into dendritic cells versus macrophages[END_REF][START_REF] Sallusto | Efficient presentation of soluble antigen by cultured human dendritic cells is maintained by granulocyte/macrophage colony-stimulating factor plus interleukin 4 and downregulated by tumor necrosis factor alpha[END_REF]) as well as in vivo in mice [START_REF] Tamoutounour | Origins and functional specialization of macrophages and of conventional and monocyte-derived dendritic cells in mouse skin[END_REF][START_REF] Hohl | Inflammatory monocytes facilitate adaptive CD4 T cell responses during respiratory fungal infection[END_REF][START_REF] Kool | Alum adjuvant boosts adaptive immunity by inducing uric acid and activating inflammatory dendritic cells[END_REF][START_REF] León | Monocyte-derived dendritic cells formed at the infection site control the induction of protective T helper 1 responses against Leishmania[END_REF], it remains unclear whether the same phenomena occur in vivo in humans. Indeed, in an in vitro model, the developmental pathway of mo-DC is distinct from that of monocyte-derived macrophages, and silencing experiments have shown that it is dependent on IRF4, BLIMP1, and AHR [START_REF] Goudot | Aryl hydrocarbon receptor controls monocyte differentiation into dendritic cells versus macrophages[END_REF]. While these findings have been corroborated in Ahr -/-mice [START_REF] Goudot | Aryl hydrocarbon receptor controls monocyte differentiation into dendritic cells versus macrophages[END_REF], it remains to be formally demonstrated whether monocytes differentiate into DCs along a specific developmental pathway in vivo in humans.

Trends in Immunology

Trends in Immunology

Concluding Remarks

In Emerging observations that AXL + SIGLEC6 + DCs or DC3 are enriched in inflamed tissues, or in the blood of patients with chronic diseases, suggest that these previously overlooked DC populations may be important for certain immunopathologies. ScRNA-seq studies have brought new DC populations into the spotlight, but it is now necessary to go beyond the description of transcriptomic profiles to address their functional properties. Identifying specific and unique cell surface markers for each DC subset will be a prerequisite, allowing their isolation for functional assays, as well as a better profiling of the DC landscape in patients samples (when scRNA-seq analysis is not feasible for practical reasons). This work will be essential for understanding the respective roles of these subsets in the initiation and progression of human diseases, and ultimately for manipulating these cells in an endeavor to improve therapeutic treatments for specific patient populations.

Outstanding Questions Is there a mouse equivalent of DC3? So far, mouse and human counterparts have been discovered for all DC subsets except for DC3. One potential candidate is the Notch2-independent Esam low cDC2-like population, described in mouse spleen [START_REF] Lewis | Notch2 receptor signaling controls functional differentiation of dendritic cells in the spleen and intestine[END_REF]. However, it remains unclear whether DC3 are present in human lymphoid organs.

Studying mouse equivalents of DC3 might provide some clues about their dynamics and possible functions in vivo.

Are there specificmarkersofDC3versus mo-DC that would distinguish them unambiguously? Identifying unique surface markers for these two populations will be essential for better understanding their relationship and respective roles.

Can DC3 differentiate into mo-DC-like cells? While monocytes can differentiate in vitro into cells resembling 'mo-DC' populations found in human samples, could some of these 'mo-DC' actually derive in vivo from DC3 instead of monocytes, along a convergent differentiation program?

What transcription factors govern the differentiation of DC3 from IRF8 low precursors? In particular, do they depend on IRF4 and AHR, similar to mo-DC? Perturbations of in vitro culture systems should provide a first line of evidence for this question.

Trends in Immunology

Introduction

Dendritic cell (DC) biology, classification and development have been primarily described in mice due to historical and practical reasons. DCs have been divided into several subsets based on their ontogeny: plasmacytoid DCs (pDCs) and classical DCs (cDCs) derive from hematopoïetic progenitors, while monocyte-derived DCs (mo-DCs) arise from monocytes. Langerhans Cells, which derive from embryonic selfrenewing precursors, have been re-classified as belonging to the macrophage family, and will not be covered in this review.

In the past ten years, analyzing human DCs directly extracted from tissues, and establishing correlations with mouse DCs, has gained considerable attention. Pioneer comparative transcriptomic studies have demonstrated the homology between mouse and human DC subsets [START_REF] Crozat | The XC chemokine receptor 1 is a conserved selective marker of mammalian cells homologous to mouse CD8α+ dendritic cells[END_REF][START_REF] Robbins | Novel insights into the relationships between dendritic cell subsets in human and mouse revealed by genome-wide expression profiling[END_REF]. Human DC comprise pDCs (expressing CD123/IL-3RA and CD303/BDCA2/CLEC4C), cDC1 (expressing CD141/BDCA3/THBD, CLEC9A/DNGR1 and XCR1), cDC2 (expressing CD1b, CD1c/BDCA1, and FcεRI) and mo-DCs (expressing CD1a, CD1c and CD14). Moreover, recent high-resolution analyses have evidenced heterogeneity in human cDC2, with the identification of a previously overlooked DC3 subset (expressing CD1c, CD14 and CD163) in blood and bone marrow (Cytlak et al., 2019;[START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF]Villani et al., 2017).

DC development from hematopoietic stem cells (HSC) requires the coordinated action of cytokines and transcription factors (TFs). Mouse models have enabled major conceptual advances in our understanding of these processes. Efforts have also been made to translate these findings to the human situation. Here we review the experimental strategies employed to analyze DC development in humans, and summarize findings regarding human DC development, including the imprinting of DC lineage bias in early hematopoietic progenitors and the developmental pathway of the DC3 population.

Methods used to analyze human DC development

Genetic fate mapping and lineage tracing experiments have considerably advanced our understanding of mouse DC ontogeny. For obvious reasons, these experimental approaches are not transferable to human settings. In this context, alternative strategies have been developed to study the development of DCs in humans.

In vitro culture systems

In vitro culture is a powerful tool to assess the developmental potential of hematopoietic progenitors. Several culture systems supporting the simultaneous differentiation of all DC subsets have been developed (Table 1). They have been used to differentiate in vitro a variety of human progenitors: stem cells (HSC, in general defined as CD34 + CD38 -CD45RA -and ideally CD90 + CD49f + ), multi-lymphoid progenitors (MLP), pre-DCs or monocytes. Culture models differ in cytokine cocktails and/or co-culture with stromal cell lines. DC differentiation can be obtained by culturing progenitors with combinations of cytokines, mainly Flt3L but also stem cell factor (SCF), interleukin 7 (IL-7), thrombopoietin (TPO), granulocyte/macrophage colony-stimulating factor (GM-CSF) and/or interleukin 4 (IL-4) [START_REF] Breton | Circulating precursors of human CD1c+ and CD141+ dendritic cells[END_REF]Goudot et al., 2017;[START_REF] Harada | Flt3 ligand promotes myeloid dendritic cell differentiation of human hematopoietic progenitor cells: possible application for cancer immunotherapy[END_REF][START_REF] Proietto | The equivalents of human blood and spleen dendritic cell subtypes can be generated in vitro from human CD34 stem cells in the presence of fms-like tyrosine kinase 3 ligand and thrombopoietin[END_REF]. One major weakness of this method is the need for an a priori knowledge of the cytokines to use. Cytokine cocktails potentially influence the

Table 1

In vitro culture models for the differentiation of human hematopoietic progenitors into dendritic cells. Some models include a step for "progenitor expansion" without stromal cell lines. outcome of the culture, and can bias fate decisions of the progenitors.

The addition of stromal cells can significantly improve the output of these cultures. In addition, it allows single-cell clonal cultures of progenitors to address their differentiation potential. OP9 is a mouse stromal cell line that has been used to facilitate differentiation of human pDCs (Schotte et al., 2004), while the stromal cell line MS5 supports other hematopoietic lineages in addition to DCs (Lee et al., 2015a). For instance, MS5 with Flt3L + SCF + GM-CSF supports the development of cord blood CD34 + HSC into granulocytes, monocytes, lymphoid cells and bona fide DCs (Lee et al., 2015a). In addition, the combination of OP9 and MS5 together with Flt3L + SCF + GM-CSF allows the differentiation of DCs, granulocytes, monocytes, megakaryocytes, erythrocytes, NK and B cells [START_REF] Lee | Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors[END_REF]. Although stromal cell lines are widely used, the molecular mechanism by which OP9 or MS5 monolayers support the development of DCs remains unclear.

Another strength of in vitro cultures is the fact that it allows the manipulation of the system in order to address the role/importance of candidate molecules in DC development. An example is the silencing of TFs in human progenitors (Goudot et al., 2017;Poulin et al., 2012;Schotte et al., 2004). Manipulation of OP9 stromal cells [START_REF] Dontje | Delta-like1-induced Notch1 signaling regulates the human plasmacytoid dendritic cell versus T-cell lineage decision through control of GATA-3 and Spi-B[END_REF] has also revealed the role of Notch ligands in cDC1 differentiation [START_REF] Balan | Large-scale human dendritic cell differentiation revealing notch-dependent lineage bifurcation and heterogeneity[END_REF][START_REF] Kirkling | Notch signaling facilitates in vitro generation of cross-presenting classical dendritic cells[END_REF].

While in vitro culture can provide definitive evidence of the differentiation potential of a putative progenitor, it remains unclear which in vitro system better recapitulates the in vivo development of human DCs. Caution should be taken to evaluate how closely the cells obtained in vitro resemble the in vivo-generated ones. Researchers have used comparative transcriptomics and functional assays to address this question [START_REF] Balan | Large-scale human dendritic cell differentiation revealing notch-dependent lineage bifurcation and heterogeneity[END_REF][START_REF] Balan | Human XCR1+ dendritic cells derived in vitro from CD34+ progenitors closely resemble blood dendritic cells, including their adjuvant responsiveness, contrary to monocyte-derived dendritic cells[END_REF]Goudot et al., 2017;Lee et al., 2015b;Villani et al., 2017).

Humanized mice

Humanized mice can be used to address the developmental potential of human hematopoietic progenitors in an in vivo context. Human progenitors are injected into mice with severe immunodeficiency that limits the rejection of human cells. To achieve efficient engraftment, host murine NK cells are particularly limiting. A solution to this has been the injection of antibodies against IL2Rβ (anti-CD122) to deplete murine NK cells [START_REF] Ding | FLT3ligand treatment of humanized mice results in the generation of large numbers of CD141 + and CD1c + dendritic cells in vivo[END_REF] or the use of mice lacking NK cells by knockout of IL2Rγ (CD132), such as the nonobese diabetic-severe combined immunodeficiency (NOD-SCID)/IL2rγ null (NSG mice) [START_REF] Ishikawa | The developmental program of human dendritic cells is operated independently of conventional myeloid and lymphoid pathways[END_REF]Poulin et al., 2012) or the RAG-2 -/ -γ c -/ -mice (Schotte et al., 2004) that also lack T and B lymphocytes. For example, sublethally irradiated NSG newborn mice are efficiently reconstituted by human CD34 + HSCs [START_REF] Ishikawa | The developmental program of human dendritic cells is operated independently of conventional myeloid and lymphoid pathways[END_REF]Poulin et al., 2012). The different models of humanized mice are extensively reviewed elsewhere [START_REF] Legrand | Experimental models to study development and function of the human immune system in vivo[END_REF][START_REF] Li | Modeling infectious diseases in mice with a "Humanized" immune system[END_REF][START_REF] Theocharides | Humanized hemato-lymphoid system mice[END_REF]. One major limitation is the lack of complete cross-reactivity between human and mouse cytokines, making it necessary to supplement mice with human cytokines. In particular, human HSC differentiation towards the monocyte/macrophage and DC lineages in these models is inefficient unless human cytokines are provided. For example, administration of human Flt3L enhances the differentiation of cDC subsets from CD34 + progenitors [START_REF] Ding | FLT3ligand treatment of humanized mice results in the generation of large numbers of CD141 + and CD1c + dendritic cells in vivo[END_REF]. To circumvent this issue, NSG-SGM3 mice have been developed (NOD.Cg-Prkdcscid-IL2rg tmlWjl Tg(CMV-IL3,CSF2,KITLG)1Eav/MloySzJ), which constitutively express human IL-3, GM-CSF and SCF [START_REF] Lee | Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors[END_REF]. One caveat of this approach remains the choice of specific cytokines and their doses, which may not be physiological and could bias progenitor differentiation towards one lineage at the expense of others.

Hematopoietic stem cell transplantation

Transplantation of bone marrow cells in humans represents an opportunity for the in vivo study of the replacement kinetics of DCs. Recipient and donor cells can be distinguished based on mismatch, for instance HLA mismatch or gender mismatch by using fluorescent in situ hybridization (FISH) with X/Y probes [START_REF] Haniffa | Differential rates of replacement of human dermal dendritic cells and macrophages during hematopoietic stem cell transplantation[END_REF]Richter et al., 2018). Patients undergoing HSC grafts are biopsied at different intervals, allowing the analysis of the replacement of short-lived recipient cells by donor cells while long-lived cells remain of recipient origin. Observations from these experiments remain very limited due to difficult access to patient samples. However, they provide valuable information on the life span of DCs in different tissues.

Human immunodeficiencies

Genetic studies of human primary immunodeficiencies allow defining the contribution of specific proteins in the development of immune cells. The main advantage of this approach is that it does not require any manipulation nor a priori knowledge to establish the relationship. Although the identification of patients clearly limits the use of this method, it has been successful in demonstrating the role of several TFs in the differentiation towards cDC, pDC and monocytes (Bigley et al., 2018;Cisse et al., 2008;Cytlak et al., 2018;Dickinson et al., 2011;[START_REF] Hambleton | IRF8 mutations and human dendritic-cell immunodeficiency[END_REF][START_REF] Kong | Disruption of an antimycobacterial circuit between dendritic and helper T cells in human SPPL2a deficiency[END_REF].

Injection of cytokines to healthy volunteers

The injection of cytokines to human volunteers enables the in vivo study of the importance of certain cytokines [START_REF] Breton | Circulating precursors of human CD1c+ and CD141+ dendritic cells[END_REF]Dutertre et al., 2019;[START_REF] Maraskovsky | In vivo generation of human dendritic cell subsets by Flt3 ligand[END_REF][START_REF] Pulendran | Flt3-ligand and granulocyte colony-stimulating factor mobilize distinct human dendritic cell subsets in vivo[END_REF]. Volunteers receive daily subcutaneous injections of Flt3L for 5-14 days, and cell numbers are assessed in peripheral blood. These studies have confirmed the major role of Flt3L in sustaining cDC development. However, a major limitation of these experiments is that the injection of high cytokine concentrations does not resemble physiological conditions, which may induce artifacts that are difficult to control for.

Transcriptomic analysis

RNA sequencing of bulk samples or single cells allows an unbiased comparison of DC subsets or progenitors in different states. Transcriptomic analysis should be systematically used to compare in vitro-differentiated DC subsets with their in vivo or mouse counterparts [START_REF] Balan | Human XCR1+ dendritic cells derived in vitro from CD34+ progenitors closely resemble blood dendritic cells, including their adjuvant responsiveness, contrary to monocyte-derived dendritic cells[END_REF]Goudot et al., 2017;Lee et al., 2015b;Villani et al., 2017). scRNAseq can be used to identify rare populations in unmanipulated patient samples. When several cellular states are present simultaneously in a sample, scRNAseq data can inform on developmental pathways by analyzing trajectory inference in a pseudo-time. However, results can significantly vary according to the computational method used. To solve this problem, experts advise to compare several algorithms, depending on the topology of the expected trajectory, in order to get robust results and choose the most accurate methods (Saelens et al., 2019). Certainly, the main advantage of scRNAseq is that unbiased analysis of biological processes may lead to unexpected findings.

DC development

Human DCs have been described in lymphoid organs as well as in numerous peripheral tissues. Transcriptomic analysis has shown that DC subset identity is strongly imprinted by their ontogeny [START_REF] Heidkamp | Human lymphoid organ dendritic cell identity is predominantly dictated by ontogeny, not tissue microenvironment[END_REF]. However, mucosal tissue DCs possess specific transcriptomic signatures, which likely result from the influence of microenvironmental signals on the final steps of their differentiation.

Life cycle of human DCs

DCs have a very limited life span and are constantly replenished in the periphery by hematopoietic progenitors. Study of skin antigen presenting cells after bone marrow transplantation showed that dermal recipient DCs are almost completely replaced after 40 days, while recipient macrophages persist in the dermis 1 year after transplantation [START_REF] Haniffa | Differential rates of replacement of human dermal dendritic cells and macrophages during hematopoietic stem cell transplantation[END_REF]. Similarly, intestinal recipient DCs are completely replaced 6 weeks after bone marrow transplantation (Richter et al., 2018). The homeostasis of DC subsets therefore relies on the migration and in situ differentiation of hematopoietic precursors. Of note, DCs have been identified in several fetal tissues [START_REF] Mcgovern | Human fetal dendritic cells promote prenatal T-cell immune suppression through arginase-2[END_REF][START_REF] Park | A cell atlas of human thymic development defines T cell repertoire formation[END_REF][START_REF] Popescu | Decoding the development of the blood and immune systems during human fetal liver haematopoiesis[END_REF] after the development of HSCs and the onset of definitive hematopoiesis (in contrast to yolk-sac derived tissue macrophages or Langerhans Cells), suggesting that DC development starts early in life.

DC precursors

The classical view of an ontogenic tree with a series of dichotomous fate decisions has been challenged in the past few years. Accumulating evidence shows that hematopoietic progenitors possess a developmental bias, observed already at early stages.

The classical model proposed that DCs arise from the common myeloid progenitor (CMP) that was thought to co-segregate with the lymphoid multipotent progenitor (LMPP) from the HSC multipotent progenitors (MPP). However, lymphoid progenitors are not lymphoidrestricted but also give rise to pDC, cDC1 and cDC2 in vitro and in vivo when transplanted to NGS mice [START_REF] Doulatov | Revised map of the human progenitor hierarchy shows the origin of macrophages and dendritic cells in early lymphoid development[END_REF]Helft et al., 2017;[START_REF] Ishikawa | The developmental program of human dendritic cells is operated independently of conventional myeloid and lymphoid pathways[END_REF][START_REF] Lee | Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors[END_REF]. DCs derived from "myeloid" and "lymphoid" progenitors are transcriptionally identical (Helft et al., 2017;[START_REF] Ishikawa | The developmental program of human dendritic cells is operated independently of conventional myeloid and lymphoid pathways[END_REF], suggesting either that there are two DC developmental pathways or, more likely, that when defined by a restricted number of surface markers, DC-primed progenitors can phenotypically resemble both myeloid and lymphoid progenitors (Fig. 1).

On the other hand, it was recently shown that the common myeloid progenitor (CMP) is divided into two subpopulations with different myeloid potential: a CD131 + subset that expresses the TF Gata1 (CMP-Gata1 + ) and a CD114 + subset (CMP-Gata1 -). The former is restricted to the megakaryocyte/erythrocyte and mastocyte/basophil/eosinophil lineages, the latter is restricted to monocyte and neutrophil lineages (Drissen et al., 2019), while DC potential was not addressed. Human granulocyte-monocyte-DC progenitors (GMDP) transit towards monocyte-DC progenitors (MDP) and finally towards committed DC progenitors (CDP) that produce cDCs and pDCs (Lee et al., 2015b). In healthy individuals, CDP are found in cord blood and in the bone marrow (Lee et al., 2015b).

The DC lineage bias is observed from HSC-MPP, through LMPP, CMP and GMDP, and correlates with TF expression (Fig. 1). For example, cDC1-lineage specification in HSC-MPP is enforced by IRF8/ PU.1 ratio [START_REF] Lee | Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors[END_REF]. Recent work shows that GMDP can be divided into subpopulations based on IRF8 expression. IRF8 high GMDP are restricted to pDC, cDC1 and cDC2, while IRF8 low GMDP transit to a "monocytic" pathway that also gives rise to DC3 (Cytlak et al., 2019). Therefore, phenotypically defined progenitors are not considered anymore as homogeneous multipotent populations, but rather a mixture of pre-primed cells that share the same temporary phenotype.

Pre-cDCs are the immediate precursors of cDCs [START_REF] Breton | Circulating precursors of human CD1c+ and CD141+ dendritic cells[END_REF]. These cells are found in diverse lymphoid tissues, such as blood, bone marrow, spleen and tonsils, but not in skin [START_REF] Alcántara-Hernández | High-dimensional phenotypic mapping of human dendritic cells reveals interindividual variation and tissue specialization[END_REF]. Initially they were described by direct comparison to their mouse counterpart. Pre-cDCs have also been identified by unbiased single cell transcriptomics of blood cells [START_REF] See | Mapping the human DC lineage through the integration of high-dimensional techniques[END_REF]Villani et al., 2017) and high-dimensional flow cytometry approaches [START_REF] Alcántara-Hernández | High-dimensional phenotypic mapping of human dendritic cells reveals interindividual variation and tissue specialization[END_REF]Dutertre et al., 2019). Clonal analysis of hematopoietic progenitors shows that pre-cDCs derive from the CDP. Moreover, pre-cDCs are transcriptionally pre-committed to become cDC1 or cDC2 [START_REF] Breton | Human dendritic cells (DCs) are derived from distinct circulating precursors that are precommitted to become CD1c+ or CD141+ DCs[END_REF][START_REF] Ma | Single cell RNA-Seq reveals pre-cDCs fate determined by transcription factor combinatorial dose[END_REF].

Monocytes can also be direct precursors of DCs, referred to as mo-DCs (Sallusto and Lanzavecchi, 1994). Mo-DCs arise in vitro in different culture conditions (detailed in Table 1) and have been identified in vivo in mucosal or inflamed tissues (reviewed in Coillard and Segura, 2019). In contrast to pre-cDCs, monocytes are not transcriptionally pre-committed to become DCs versus macrophages (Goudot et al., 2017).

Regulation of DC development

Cytokine requirements

Flt3L is the most important cytokine in DC development and expansion. Initial observations in healthy volunteers injected with Flt3L showed a dramatic increase in the number of cDCs (Lin -HLA + CD11c + ) and pDCs (Lin -HLA + CD11c -CD123 + ) in peripheral blood [START_REF] Pulendran | Flt3-ligand and granulocyte colony-stimulating factor mobilize distinct human dendritic cell subsets in vivo[END_REF], as well as CD14 + monocytes [START_REF] Maraskovsky | In vivo generation of human dendritic cell subsets by Flt3 ligand[END_REF]. In addition, injection of Flt3L also increases pre-cDC population [START_REF] Breton | Circulating precursors of human CD1c+ and CD141+ dendritic cells[END_REF] and circulating DC3 (Dutertre et al., 2019). In mice reconstituted with cord blood CD34 + cells and injected with human Flt3L, cDC1 and cDC2 are expanded to a similar degree in blood and spleen, but in bone marrow mainly cDC2 are increased [START_REF] Ding | FLT3ligand treatment of humanized mice results in the generation of large numbers of CD141 + and CD1c + dendritic cells in vivo[END_REF]. Of note, patients with HSC and DC deficiency have 100-fold increased levels of circulating Flt3L (Bigley et al., 2011). This could happen because Flt3L is not consumed by DC or their progenitors and accumulates in the blood. However, the effect of DC versus HSC consumption cannot be separated in this study. Consistent with these observations, Flt3L expands DC progenitors in vitro better than SCF [START_REF] Harada | Flt3 ligand promotes myeloid dendritic cell differentiation of human hematopoietic progenitor cells: possible application for cancer immunotherapy[END_REF] and induces the differentiation of HSC into pDCs, unlike G-CSF [START_REF] Blom | Generation of interferon α-producing predendritic cell (pre-DC)2 from human CD34 + hematopoietic stem cells[END_REF]. These observations demonstrate that Flt3L is essential in cDC and pDC development.

Other cytokines such as SCF, GM-CSF, IL-3 and IL-7 are widely used for in vitro culture systems that sustain DC development. Although the precise mechanisms are not well understood, these requirements have been used to define subpopulations within progenitor cells, using cytokine receptors as phenotypic markers. For example, the phenotype of human GMDP, MDP and CDP was refined based on the expression of the receptors for M-CSF, GM-CSF, and IL-3 [START_REF] Lee | Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors[END_REF], and Gata1 - CMP was described based on the upregulation of the G-CSF receptor (Drissen et al., 2019).

Regarding mo-DCs, it is now clear that IL-4 drives their differentiation program in vitro (Goudot et al., 2017;Sander et al., 2017). However, the role of IL-4 in vivo for monocyte differentiation into DCs, and the requirement for M-CSF versus GM-CSF, remains to be characterized.

Transcription factors

A combination of in vitro studies in culture systems and ex vivo analysis of genetically deficient patients has provided insight into the TFs involved in human DC development.

IRF8 is an essential TF for DC development. Patients with IRF8 deficiency have reduced or null numbers of blood cDC1, cDC2 and pDC, and dermal cDC2 and CD14 + DC (Bigley et al., 2018(Bigley et al., , 2011;;[START_REF] Hambleton | IRF8 mutations and human dendritic-cell immunodeficiency[END_REF][START_REF] Kong | Disruption of an antimycobacterial circuit between dendritic and helper T cells in human SPPL2a deficiency[END_REF]. Consistent with this, early expression of IRF8 in HSC-MPP imprints a bias towards the cDC1 lineage [START_REF] Lee | Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors[END_REF]. CMP and GMDP are also heterogeneous for IRF8 expression. IRF8 high progenitors give rise to pDC, cDC1 and cDC2, and IRF8 low progenitors contain the monocytic, neutrophil and DC3 potential (Cytlak et al., 2019). A role for Flt3L in the development of DC3 has also been proposed (Dutertre et al., 2019). As GMDPs express CD135/Flt3 [START_REF] Doulatov | Revised map of the human progenitor hierarchy shows the origin of macrophages and dendritic cells in early lymphoid development[END_REF], an hypothesis to reconcile these observations would be that Flt3 expression is down-regulated in pre-monocytes but maintained in pre-DC3. Finally, while in pre-cDCs the expression of IRF8 or IRF4 is not mutually exclusive between pre-cDC1 and pre-cDC2, the IRF8/IRF4 ratio correlates with pre-cDC commitment to cDC1 (higher IRF8) or cDC2 (higher IRF4) [START_REF] Ma | Single cell RNA-Seq reveals pre-cDCs fate determined by transcription factor combinatorial dose[END_REF].

Other important TFs for cDC development are NOTCH, BATF3 and GATA2. NOTCH activation through DL1 promotes cDC1 differentiation (and less strikingly cDC2) from bone marrow and cord blood precursors [START_REF] Balan | Large-scale human dendritic cell differentiation revealing notch-dependent lineage bifurcation and heterogeneity[END_REF][START_REF] Kirkling | Notch signaling facilitates in vitro generation of cross-presenting classical dendritic cells[END_REF], and refines the phenotype and function of in vitro-differentiated cDC1 compared to their blood counterpart [START_REF] Kirkling | Notch signaling facilitates in vitro generation of cross-presenting classical dendritic cells[END_REF]. Silencing of BATF3 in HSC impairs cDC1 differentiation in vitro, but not in humanized mice (Poulin et al., 2012). Finally, patients possessing a non-functional mutation of GATA2 lack DCs, monocytes, B cells and NK cells (DCML deficiency patients) (Dickinson et al., 2011). These data indicate that GATA2 is important for maintenance/differentiation of hematopoietic progenitors with different potentials (DC, monocytic and lymphocyte), while NOTCH and BATF3 participate in later differentiation events of the DC lineage.

The development of pDCs is positively regulated by Ikaros, E2-2, SpiB, and negatively regulated by NOTCH. Patients with IKZF1 (Ikaros) deficiency have reduced numbers of pDCs and decreased IFNα production (Cytlak et al., 2018). By contrast, patients bearing monoallelic loss-of-function mutations or deletions of E2-2 (Pitt-Hopkins syndrome patients) have normal pDC numbers in the blood, but displaying an altered phenotype and function (Cisse et al., 2008). Forced expression of E2-2 in thymic CD34 + progenitors enhances the development of pDC in vitro, while silencing E2-2 decreases pDC output [START_REF] Nagasawa | Development of human plasmacytoid dendritic cells depends on the combined action of the basic helix-loop-helix factor E2-2 and the Ets factor Spi-B[END_REF]. In addition, co-expression of E2-2 and SpiB is necessary to promote pDC development in this system [START_REF] Nagasawa | Development of human plasmacytoid dendritic cells depends on the combined action of the basic helix-loop-helix factor E2-2 and the Ets factor Spi-B[END_REF]. Silencing SpiB completely blocks pDC development in vitro and in vivo in humanized mice (Schotte et al., 2004). Actually, Spi-B expression is downregulated by NOTCH1 signaling [START_REF] Dontje | Delta-like1-induced Notch1 signaling regulates the human plasmacytoid dendritic cell versus T-cell lineage decision through control of GATA-3 and Spi-B[END_REF], which inhibits pDC development in vitro [START_REF] Balan | Large-scale human dendritic cell differentiation revealing notch-dependent lineage bifurcation and heterogeneity[END_REF].

Finally, the differentiation of monocytes toward mo-DCs involves IRF4, BLIMP1 and Aryl Hydrocarbon Receptor (AHR), as demonstrated by gene silencing in an in vitro culture model (Goudot et al., 2017). The nuclear receptor corepressor 2 (NCOR2) was also proposed as an orchestrator of mo-DC differentiation in a different culture model (Sander et al., 2017).

Conclusion and perspectives

Despite inherent limitations to working with human samples, successful experimental approaches have been developed to study human DC ontogeny. This work has confirmed that the same principles apply to mouse and human DC development. Human DCs have a short life span and are constantly replenished from circulating precursors originating from the bone marrow. Lineage bias is imprinted early in human hematopoietic progenitors, and correlates with TF expression.

Differences between mouse and human may lie in the molecular regulators involved. Although Flt3L is the key DC-promoting cytokine in both mouse and human, it is not sufficient to generate human DCs in vitro from BM progenitors without additional cytokines, contrary to the mouse. The precise role of some TF could also differ, such as IRF8. IRF8 deficiency in humans affects all cDC and pDC populations (Hambleton et al., 2011;[START_REF] Kong | Disruption of an antimycobacterial circuit between dendritic and helper T cells in human SPPL2a deficiency[END_REF], while cDC2 development is independent of IRF8 in the mouse (Sichien et al., 2016).

Methodological developments are needed to refine our understanding of human DC development in vivo. Such methods will undoubtedly include clonal genetic tracing, either using artificial barcoding of single hematopoietic stem cells [START_REF] Naik | Diverse and heritable lineage imprinting of early haematopoietic progenitors[END_REF][START_REF] Perié | Determining lineage pathways from cellular barcoding experiments[END_REF] or using spontaneous somatic mutations as genetic labels for progenitors [START_REF] Lee-Six | Population dynamics of normal human blood inferred from somatic mutations[END_REF][START_REF] Woodworth | Building a lineage from single cells: genetic techniques for cell lineage tracking[END_REF].

Open questions to be addressed in humans include the ontogeny of DC3. More work is also needed to better understand the final steps of DC differentiation and the role of tissue-derived signals.

Introduction

Human dendritic cells (DC) can be classified into 4 main groups based on their ontogeny: classical DC (cDC1 and cDC2), plasmacytoid DC (pDC), DC3 and monocyte-derived DC (mo-DC) [1]. Monocytes circulate in the blood and have been shown to differentiate after entering tissues into either macrophages or dendritic cells. In human, mo-DC have been described in clinical samples at steady-state in intestine and lung, as well as in several inflamed tissues in the context of acute inflammation or chronic disease [2].

Due to limitations inherent to working with human samples, mo-DC are commonly studied in vitro. Pioneer work has shown that human monocytes can differentiate into DC when cultured with GM-CSF and IL4 [3]. These cells display phenotypic markers of human DC such as CD1a and CD1c, and typical DC functions such as stimulation of naïve T cells. However, recent studies have revealed a number of differences with naturally occuring mo-DC that can be isolated from clinical samples. In particular we have identified human mo-DC in peritoneal tumor ascites [4,5], and found using transcriptomic profiling and functional assays that they do not closely resemble the mo-DC that can be obtained in vitro with GM-CSF and IL4 [6].

In addition, this culture system only yields mo-DC, with some heterogeneity [7], but not bona fide macrophages. By contrast, monocyte-derived macrophages (mo-Mac) can be obtained by culturing human monocytes with M-CSF. In vivo, monocytes are exposed to several signals (such as cytokines) that will modulate their commitment into either mo-Mac or mo-DC. A limitation of these culture systems is that it does not allow the analysis of alternative fates of monocytes (mo-DC versus mo-Mac). Here, we describe a protocol to simultaneously differentiate monocytes into mo-Mac and mo-DC in the same culture, using a cocktail of cytokines consisting of M-CSF, IL-4 and TNF-α. In addition, the mo-DC obtained in this culture system can mimic the mo-DC found in peritoneal ascites from tumor patients and synovial fluid from rheumatoid arthritis patients, in terms of phenotype, transcriptome and functional properties [6].

Materials

Blood monocyte isolation

1 CNS

 1 Abbreviations ......................................................................................................................... Figures and Tables ................................................................................................................

Figure 1 . 14 Figure 2 . 16 Figure 3 . 19 Figure 4 . 21 Figure 5 . 23 Figure 6 . 25 Figure 7 . 30 Figure 8 . 32 Figure 9 . 40 Figure 10 .

 11421631942152362573083294010 Figure 1. Bifurcated development of mouse monocytes from CMP. ..................................... 14 Figure 2. Human monocytes and DC3 share a common IRF8 low progenitor. ........................ 16 Figure 3. Representation of different steps of the extravasation cascade of monocytes (from Gerhardt and Ley, 2015). ...................................................................................................... 19 Figure 4. Illustration of main strains used to study monocyte development and fate. ........... 21 Figure 5. Tissue-resident macrophages ontogeny dynamics from Ginhoux and Guilliams, 2016. ...................................................................................................................................... 23 Figure 6. Schematic representation of peritoneal monocyte-derived cells. ........................... 25 Figure 7. Mo-mac appear as elongated and adherent cells, while mo-DC look round and semiadherent, from Villar et al., 2022. .......................................................................................... 30 Figure 8. RNA velocity inference (Modified from Bergen et al., 2021). ................................. 32 Figure 9. GM-CSF signalling in Ccr2 + cells after EAE induction is key for the development of the disease. ........................................................................................................................... 40 Figure 10. Dual role of mo-DC in pathogenesis of EAE. ....................................................... 41

Figure 1 .Figure 2 .Figure 3 . 54 Figure 4 . 56 Figure 5 . 58 Figure 6 . 80 Supplemental Figure 6 .Chapter 2 .Figure 1 .Figure 2 .Figure 3 .Figure 4 .Figure 5 .Figure Complementary 1 .DiscussionFigure 11 .Figure 12 .Figure 13 .

 1235445655868062123451111213 Figure 1. Etv3 and Etv6 are essential for mo-DC differentiation. ………………………………49 Figure 2. Etv3 and Etv6 repress mo-Mac differentiation…………………………………………52 Figure 3. Etv3 and Etv6 repress interferon-stimulated genes…………………………………..54 Figure 4. Activation of the type I interferon pathway promotes mo-Mac differentiation……….56 Figure 5. Etv6 represses interferon-stimulated genes in vivo in mouse……………………….58 Figure 6. Etv6 controls mo-DC differentiation during in vivo inflammation in mouse…………60 Supplemental Figure 1. Etv3 and Etv6 exert their function at an early stage of monocyte differentiation………………………………………………………………………………………...76 Supplemental Figure 2. Analysis of bulk RNAseq of ETV3 and ETV6 silenced monocytes and a public scRNAseq data of PBMCs from healthy and Etv6 P214L patients……………………….77 Supplemental Figure 3. IFNa increases mo-Mac differentiation. ……………………………….78

Figure 3 .

 3 Figure 3. Representation of different steps of the extravasation cascade of monocytes (from Gerhardt and Ley, 2015).

Figure 5 .

 5 Figure 5. Tissue-resident macrophages ontogeny dynamics from Ginhoux and Guilliams, 2016. "Closed tissues" contain only prenatally derived macrophages. "Open tissues" are rapidly replenished by blood monocytes with a kinetics specific to each tissue, heart and pancreas being slower than gut and dermis.

  shRNA for each molecule, and their efficiency was evaluated by measuring protein expression by Western Blot. These shRNAs all significantly decreased ETV3 or ETV6 expression with an efficiency of 40-90% (Figure1C and E). Silencing of ETV3 or ETV6 decreased mo-DC and increased mo-Mac differentiation (Figure1Dand Figure1F, respectively). These results show that ETV3 and ETV6 play a key role in mo-DC differentiation. To characterize their expression kinetics during monocyte differentiation, we measured their expression by RTqPCR at different time points. ETV3 and ETV6 mRNA increased during the first hours in culture with a peak at 3 or 6 hours for ETV3 and ETV6, respectively (Figure1G). To determine the physiological signals that trigger their expression by monocytes, we measured ETV3 and ETV6 mRNA in monocytes upon exposure to M-CSF, in presence or absence of IL-4 and TNFα (Figure1H). ETV3 expression was induced by TNF-α. ETV6 expression was induced by IL-4, with TNF-α sustaining its expression at later time points. These results show that ETV3 and ETV6 are expressed upon exposure to inflammatory signals at an early stage of monocyte differentiation, suggesting they could play a role in their lineage commitment towards mo-DC.

  figure 1E). We observed that ETV3 and ETV6 are located in the nucleus until day 3 in around 90% of the cells (Supplemental Fig1F-G). By contrast, at day 6, ETV3 and ETV6 are located in the cytosol in around 50% of the cells. Because the transcriptional activity of ETV3 and

  repress the mo-Mac transcriptional program. To confirm this, we sought to overexpress ETV6 during monocyte differentiation. To avoid spontaneous expression of ETV6, we cultured monocytes with M-CSF only, condition in which monocytes differentiate exclusively into mo-Macs. We validated the forced expression of ETV6 by Western blot (Fig 2G). ETV6 overexpression decreased mo-Mac differentiation (Fig 2H-I). Taken together, these results indicate that ETV3 and ETV6 repress mo-Mac differentiation.

  2A-B). We then interrogated the single-cell data of ETV6 P214L and WT monocytes with different gene sets. Genes upregulated upon ETV6 silencing in our in vitro system were enriched in ETV6 P214L monocytes compared to WT monocytes(Fig 3E, Supplemental Fig 2C). Moreover, ETV6 P214L monocytes had a higher enrichment for ISGs than WT monocytes (Fig 3F-G),

  interferon in the culture system. To analyze the spontaneous expression of ISGs during monocyte differentiation in vitro, we measured MX1, CXCL10 and IFIT3 expression by RTqPCR during the first hours of culture(Fig 4A). ISG expression peaked at 9 hours. To address whether this phenomenon was specific to our cytokine cocktail, we also cultured monocytes with M-CSF only, conditions in which monocytes differentiate exclusively into mo-Macs(Fig 4A). ISG expression was even greater in this setting. To confirm our observations, we quantified by flow cytometry STAT1 phosphorylation, which is required for its transcriptional activity. We detected STAT1 phosphorylation after 24 hours of culture (Fig4B).The percentage of pSTAT1 + cells was higher with M-CSF than with the three-cytokines cocktail, and similar to that induced by exogenous IFNa. However, we could not detect type I interferon secretion in the culture supernatant in any condition. To directly assess the effect of STAT1 activation on monocyte differentiation, we cultured monocytes in the presence of IFNa or IFNb. Type I interferon increased mo-Mac and decreased mo-DC differentiation in a dosedependent manner(Fig 4C and Supplemental Fig 3A). Neither IFNa nor IFNb affected monocyte-derived cells viability(Supplemental Fig 3B). In addition, type I interferon increased the expression of CD163, an early mo-Mac marker, and decreased the expression of CD1b, an early mo-DC marker, on the double negative cells(Fig 4D and Supplemental Fig 3C).

Fig

  Fig 4D). The numbers of CD11b + CD115 + Ly6C int and CD11b + CD115 + Ly6C neg monocytes decreased in Cx3cr1-Etv6 Δ mice compared to WT. Moreover, the spleens of Cx3cr1-Etv6 Δ mice harbored decreased numbers of cDC2, particularly of the Esam -subset that is transcriptionally and functionally related to monocytes (Fig6C)[START_REF] Lewis | Notch2 receptor signaling controls functional differentiation of dendritic cells in the spleen and intestine[END_REF]. We have

  would ameliorate EAE outcome. We induced EAE in WT and Cx3cr1-Etv6 Δ mice by injection of Myelin Oligodendrocyte Glycoprotein (MOG) (Fig 6G). Cx3cr1-Etv6 Δ mice showed less severe symptoms during the course of EAE (Fig 6G-H) and reduced incidence (Fig 6H). The

  found that Etv6 deletion only in long-live macrophages did not decrease EAE symptoms or incidence (Supplemental Fig 6B-C), indicating that Etv6 expression in monocytes regulates the severity of EAE. To address the cellular mechanisms involved, we analyzed the presence of mo-DC in the lymph nodes draining the site of MOG injection (Supplemental Fig 6D).Cx3cr1-Etv6 Δ mice showed significantly decreased numbers of mo-DC in the draining lymph nodes, while other inflammatory immune cells (monocytes and neutrophils) and DC populations (cDC1, cDC2, Langerhans cells) remained unchanged (Fig 6J-K). This result confirms that mo-DC differentiation is impaired during inflammation in Cx3cr1-Etv6 Δ mice. Mo-DC are the main antigen-presenting cells inducing pathogenic CD4 T cells in the lymph nodes in the EAE model[START_REF] Amorim | IFNγ and GM-CSF control complementary differentiation programs in the monocyte-to-phagocyte transition during neuroinflammation[END_REF]. To analyze the induction of MOG-specific CD4 T cells, we performed tetramer staining in the lymph nodes 7 days after MOG injection (Fig6I). We found reduced numbers of MOG-specific CD4 T cells in Cx3cr1-Etv6 Δ mice, suggesting that reduced EAE symptoms were due to decerased induction of autoreactive CD4 T cells by mo-DC.

  APC anti-CD1a (Biolegend, clone HI149), FITC anti-CD16 (Biolegend, clone 3G8), PE-Cy7 anti-CD163 (Biolegend, clone GHI/61), PE anti-CD1b (eBioscience, clone eBioSN13). DAPI (Fischer Scientific, 100ng/mL) was added immediately prior to acquisition on a FacsVerse instrument (BD Biosciences) or MACSQuant (Miltenyi) instrument. Data was analyzed with FlowJo (FlowJo LLC).For intracellular staining of phosphorylated STAT1, cells were first incubated with Live/Dead Aqua (Thermofisher) in PBS for 10 min on ice. Cells were then fixed with PFA 4% in PBS for 20 min at room temperature followed by a permeabilization with pre-chilled True-Phos™ Perm Buffer (Biolegend) at -20ºC for 1 hour. Cells were stained with anti-STAT1 Phospho (Tyr701) PE (Biolegend, clone A17012A) for 30 min on ice and then washed twice. Samples were acquired on a FacsVerse instrument (BD Biosciences). Data was analyzed with FlowJo (FlowJo LLC).Imaging flow cytometryCells were first stained with Live/Dead Aqua (Thermofisher) in PBS for 10 min at 4°C. Then, cells were stained in PBS containing 0.5% human AB serum and 2mM EDTA with anti-CD1a APC and anti-CD16 FITC for 30 min on ice. After washing, cells were fixed with PFA 4% in PBS for 20 min at room temperature and permeabilized with Permeabilization Buffer (Fixation/Permeablization Kit, BD Biosciences) containing Fc block (Human TruStain FcX, Biolegend) and mouse serum (Biolegend) for 30 min on ice. Cells were then incubated with the primary antibody in permeabilization buffer, rabbit anti-ETV6/Tel (Novus Biologicals, NBP1-80695) or rabbit anti-ETV3 (Atlas Antibodies, HPA004794), at 4 ug/ml for 1 hour at room temperature. Finally, cells were incubated with the secondary antibody anti-Rabbit IgG (H+L) Alexa 594 (Molecular Probes, #A-11037) for 1 hour at room temperature and then resuspended in staining buffer containing DAPI (Fischer Scientific, 50ng/mL). Samples were acquired in an Amnis ImageStream instrument (Luminex). Data was analyzed using the IDEAS software to obtain the similarity score between DAPI and Alexa 594 channels. Finally, data was exported to FlowJo for quantification and visualization.

  Antibodies used were anti-CD115 BUV 395 (BD Bioscience, clone AFS98), anti-TCRb BUV737 (BD Bioscience, clone H57-597), anti-Sca1 BV421 (Biolegend, clone D7), anti-CD19 BV480 (BD Bioscience clone 1D3), anti-TCRb BV480 (BD Bioscience, clone H57-597), anti-NK1.1 BV480 (BD Bioscience, clone PK136), anti-SiglecF BV480 (BD Bioscience, clone E50-2440), anti-XCR1 BV510 (Biolegend, clone ZET), anti-Ly6G BV605 (Biolegend, clone 1A8), anti-CCR2 BV711 (BD Bioscience, clone 475301), anti-CD11c BV785 (Biolegend, clone N418), anti-CD45.2 PE (BD Bioscience, clone 104), anti-CD26 PE (Biolegend, clone H194-112), anti-CD226 PE (Biolegend, clone 10E5), anti-CD11b PE da594 (BD Bioscience, clone M1/70), anti-F4/80 PECy7 (Biolegend, clone BM8), anti-ESAM APC (Biolegend, clone 1G8/ESAM), anti-CD115 APC (BD Bioscience, clone AFS98), anti-TIM4 APC (Biolegend, clone RMT4-54), anti-Ly6C Alexa 700 (Biolegend, clone HK1.4), anti-MHC II APC Cy7 (Biolegend, clone M5/114.15.2) and anti-ICAM2 Biotin (Biolegend, clone 3C4) followed by

  were incubated for 3h at 37°C in RPMI containing 10% FCS in the presence of PE-conjugated MOG tetramer (I-A(b) GWYRSPFSRVVH, 2.7 µg/mL) or control tetramer (I-A(b) PVSKMRMATPLLMQA, 2.7 µg/mL) (both obtained from the NIH tetramer core facility). After washing, cells were stained with anti-CD8 BUV395, anti-TCRb BUV737 (BD Bioscience, clone H57-597), anti-CD19 BV480 (BD Bioscience clone 1D3), anti-CD4 PerCPCy5.5 and anti-CD11b PeCy7 (BD Bioscience, clone M1/70).shRNA interferenceshRNA (all from Sigma) against ETV3 (sh1: NM_005240-TRCN0000013930, sh2: NM_005240-TRCN0000013931, sh3: NM_005240-TRCN0000013932), ETV6 (sh1: NM_001987-TRCN0000003853, sh2: NM_001987-TRCN0000003854, sh3: NM_001987-TRCN0000003855), or nontargeting control shRNA (MISSION shRNA SHC002) were in the LKO.. Viral particles were produced by transfection of 293FT cells in 6-well plates with 3 mg DNA and 8 uL TransIT-293 (Mirus Bio) per well: for VSV-G pseudotyped SIVmac VLPs, 0.4 mg CMV-VSVG and 2.6 mg pSIV3+; for shRNA vectors, 0.4 mg CMV-VSV-G, 1 mg psPAX2 and 1.6 mg LKO1puro-derived shRNA vector. One day after 293FT cells transfection, medium was replaced by fresh culture medium. Viral supernatants were harvested 1 day later and filtered through 0.45 µm filters. Freshly isolated CD14+ monocytes were infected with viral particles containing the control vector or individual shRNA vectors, and cultured as above. Puromycin (InvivoGen) was added 2 days later (2 mg/mL). At day 5, cells were harvested for analysis.OverexpressionETV6 cDNA was cloned in a pTRIP-SFFV-BFP-P2A vector. Viral particles were produced by transfection of 293FT cells in 6-well plates with 3 mg DNA and 8 uL TransIT-293 (Mirus Bio) per well: for VSV-G pseudotyped SIVmac VLPs, 0.4 mg CMV-VSVG and 2.6 mg pSIV3+; for ETV6 vectors, 0.4 mg CMV-VSV-G, 1 mg psPAX2 and 1.6 mg pTRIP-SFFV-BFP-P2A-derived vector. One day after 293FT cells transfection, medium was replaced by fresh culture medium.Viral supernatants were harvested 1 day later and filtered through 0.45 µm filters. Freshly isolated CD14+ monocytes were infected with viral particles containing the control pTRIP-SFFV-BFP-P2A or pTRIP-SFFV-BFP-P2A-ETV6 vector. At day 5, cells were harvested for Western Blot or FACS analysis. qPCR Cells were harvested and lysed in RLT buffer(QIAGEN). RNA extraction was carried out using the RNAeasy micro kit (QIAGEN) according to manufacturer's instructions. Total RNA was retro-transcribed using the superscript II polymerase (Invitrogen), in combination with random hexamers, oligo dT and dNTPs (Promega). Transcripts were quantified by real time PCR on a 480 LightCycler instrument (Roche). Reactions were carried out in 10 µL, using a master mix (Eurogentec), with the following Taqman Assays primers (Merk), for human samples: , Ly6a (Mm00726565_s1), Ifna1-Ifna5-Ifna6 (Mm03030145_gH), Ifnb1 (Mm00439552_s1), Ifng (Mm01168134_m1), Ifnl2-Ifnl3 (Mm04204158_gH). The second derivative method was used to determine each Cp and the expression of genes of interest relative to the housekeeping genes was quantified: B2M (HS00187842_m1), HPRT (Hs02800695_m1), RPL34 (Hs00241560_m1) for human, Gapdh (Mm99999915_g1), B2M (Mm00437762_m1) and Polr2a (Mm00839502_m1) for mouse.

  kit (Agilent Technologies)(8.8 < RIN < 10). Libraries were prepared according to Illumina's instructions accompanying the TruSeq Stranded mRNA Library Prep Kit (Illumina). 500 ng of RNA was used for each sample. Library length profiles were controlled with the LabChip GXTouchHT system (Perkin Elmer). Sequencing was performed in 4 sequencing unit of NovaSeq 6000 (Illumina) (100-nt593 length reads, paired end) with an average depth of 40 millions clusters per sample. The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus(Edgar et al., 2002) and are accessible through GEO Series accession number (to be provided).

   and then, we subset the CD14+ and CD16+ monocytes. The dimensionality reduction, PCA, and UMAP projection were performed in this subset(Supplemental Fig 2C). Differential signature enrichment was calculated by a t-test comparing the signature score in WT versus P214L patients.

  D mice and WT (Etv6 flox/flox ) littermates were treated with 5 mg of tamoxifen (Sigma) resuspended in Corn oil (Sigma) by oral gavage twice a week, starting one week prior to immunization. Mice were immunized subcutaneously in the back with 100 µg myelin oligodendrocyte glycoprotein (MOG)35-55 peptide (sb-PEPTIDE) emulsified in Incomplete Freud's Adjuvant (Invivogen) supplemented with 4 mg/mL desiccated Mycobacterium Tuberculosis (H37RA, Sigma). Mice were injected intra-peritonally with 200 ng of pertussis toxin from Bordetella Pertussis (Calbiochem) at day 0 and 2 after immunization. Mice were examined daily for clinical signs. In agreement with the local ethics committee, mice were scored as follows: 0 healthy; 0.5 tail weakness; 1 limp tail; 1.5 tail paralysis and hindlimb weakness; 2 tail paralysis and limping of one hindlimb; 2.5 tail paralysis and limping of both hindlimbs; 3 paralysis of tail and both hindlimbs; 3.5 paralysis of tail and both hindlimbs, and weakness in forelimbs. Score 3 was predefined as the humane endpoint of the experiment.

  using a lentivirus containing shRNA. Mo-mac and mo-DC differentiation after 5 days. One representative donor is shown (n=8). DN = double negative. Proportion of mo-DC, mo-Mac and DN cells after 5 days. Median is shown (n=8 in 3 independent experiments). Paired one-way Anova. *P < 0.05, **P < 0.01, ***P < 0.001. (E) Irf4 expression in wild type and Mxd1-deficient spleen DC (GSE141492).

  gene programs are controlled by DC-SCRIPT and MXD1 during monocyte differentiation remains open for future investigation.

FindAllMarkers

  function (test.use = 't', logfc.threshold = log[0.25]) based on normalized data.

  sh1: TRCN0000017570, sh2: TRCN0000017570) or nontargeting control shRNA (MISSION shRNA SHC002) were in the LKO.. Viral particles were produced by transfection of 293FT cells in 6-well plates with 3 mg DNA and 8 uL TransIT-293 (Mirus Bio) per well: for VSV-G pseudotyped SIVmac VLPs, 0.4 mg CMV-VSVG and 2.6 mg pSIV3+; for shRNA vectors, 0.4 mg CMV-VSV-G, 1 mg psPAX2 and 1.6 mg LKO1puro-derived shRNA vector. One day after 293FT cells transfection, medium was replaced by fresh culture medium. Viral supernatants were harvested 1 day later and filtered through 0.45 µm filters. Freshly isolated CD14+ monocytes were infected with viral particles containing the control vector or individual shRNA vectors, and cultured as above. Puromycin (InvivoGen) was added 2 days later (2 mg/mL). At day 5, cells were harvested for analysis.qPCRCells were harvested and lysed in RLT buffer(QIAGEN). RNA extraction was carried out using the RNAeasy micro kit (QIAGEN) according to manufacturer's instructions. Total RNA was retro-transcribed using the superscript II polymerase (Invitrogen), in combination with random hexamers, oligo dT and dNTPs (Promega). Transcripts were quantified by real time PCR on a 480 LightCycler instrument (Roche). Reactions were carried out in 10 µL, using a master mix (Eurogentec), with the following Taqman Assays primers (Merk), for human samples: . The second derivative method was used to determine each Cp and the expression of genes of interest relative to the housekeeping genes (B2M, HPRT, RPL34) was quantified.

  the ontogeny-based human DC classification and based on the work discussed here, it is proposed that DC3 represent a new human DCs u b s e t ,a l o n gw i t hp D C ,c D C 1 ,c D C 2 ,a n d mo-DC (Figure 1, Key Figure). All these DC subsets express a similar transcriptional program upon activation, which dominates the gene expression profile of activated cells and corresponds to the recently described CCR7 + DC populations. Evidently, further work is needed to classify AXL + SIGLEC6 + DCs and the proposed DC2A and DC2B populations (see Outstanding Questions).

Fig. 1 .

 1 Fig. 1. Unified model of human dendritic cell development. Hematopoietic stem cells (HSCs) give rise to dendritic cells (DCs) by a sequential diversification of increasingly restricted progenitors. Lymphoid multipotent progenitors (LMPPs), deriving from the HSCs, give rise to a Gata1 -CD114 + common myeloid progenitor (CMP). Monocytes and DC3 arise from the IRF8 low fraction of the granulocyte-monocyte-DC progenitors (GMDP or GMP), while conventional DC1 and DC2 and pDC differentiate from committed DC progenitors (CDP). Colors represent lineage potential observed in each progenitor. Proportions of each lineage in a given progenitor are arbitrary.

Table 1 . Monocyte expression of surface markers by species and subpopulations.

 1

		Classical	Intermediate	Non-classical	Classical	Non-classical
	CD14	+	+	-	/	/
	CD16	-	+	+	/	/
	LY6C	/	/	/	high	low
	CX3CR1	-	+	+	low	high
	CD11B	+	+	+	+	+
	CD115	+	+	+	+	+
	CD43	?	?	?	low	high
	HLA-DR/MHCII	+	++	++	-	-
	S100A8/9	+	low	low	+	+

Table 3 . Expression of surface marker in human monocytes, mo-DC and and mo-mac.

 3

	Marker	CD14+ monocytes	mo-DC	mo-mac
	CD14	++	+	+
	HLA-DR	+	+	+
	CD11B	+	+	+
	CD11C	+	+	+
	CD226	-	+	-
	CD1A/B/C	-	+	-
	FcεRI	-	+	-
	CD209	-	+	+
	CD88	+	+	+
	CD16	-	-	+
	CD163	-	-	+
	MERTK	-	-	+

  of one representative donor are shown (n=8). Percentage of CD163+ or CD1b+ cells among DN cells. Median is shown (n=8 in 3 independent experiments). Paired-one way Anova. (E) Monocytes were cultured with medium only, or combinations of MCSF, IL4 and TNF , in presence or absence of 1000 U/mL IFN . MX1 and MAFB expression measured by RTqPCR after 3 hours, and PPARG and ZNF366

	after 6 hours. Median is shown (n=5 in 2 independent experiments). Paired-two way Anova. Asterisks
	represent tests against the same condition without IFN . For all panels: *P < 0.05, **P < 0.01, ***P <
	0.001, ****P < 0.0001.

  ).

	Sca-1 was also more expressed in Cx3cr1-Etv6 Δ mice in B cells, T cells and neutrophils in
	bone marrow, blood, and spleen, and in spleen cDC1, cDC2 and pDC (Fig 5C-E). By contrast,
	deletion of Etv6 in CD11c-expressing cells did not affect Sca-1 expression in bone marrow
	and spleen B cells (Supplemental Fig 4B). These results indicate that the increased ISG
	expression in Cx3cr1-Etv6 Δ mice is due to Etv6 deletion in monocytes. Although we were
	unable to detect circulating IFNb (Supplemental Fig 4C), this result suggests that Etv6

Δ

monocytes spontaneously secrete type I interferon. To confirm our observations, we analyzed the expression of additional ISGs and interferon genes by RTqPCR in bone marrow

  1* 1 Institut Curie, PSL Research University, INSERM, U932, 26 rue d'Ulm, Paris, France

* Corresponding Author: Elodie Segura elodie.segura@curie.fr

Table 1 .

 1 Known human Dendritic Cell (DC) Subsets

	function.
	Single-cell RNA sequencing
	(scRNA-seq): next generation
	sequencing method, providing RNA
	expression profiles from individual cells.
	Transitional DCs: population of DCs
	displaying an intermediate phenotype
	between cDC and pDC.
	Unbiased clustering: (in single-cell
	RNAseq) grouping of a set of cells that
	are more similar to each other than to
	other groups of cells, based on their
	expression data. Unbiased clustering
	(also termed unsupervised clustering) is
	performed without consideration of prior
	knowledge about the cell attributes.
	Common clustering methods include
	hierarchical clustering, graph-based
	clustering, and k-means clustering.

a Abbreviations: pDC, plasmacytoid DCs; cDC1, type 1 classical DCs; cDC2, type 2 classical DCs; mo-DC, monocytederived DCs.

Table 2 .

 2 Newly Described Human Dendritic Cell (DC) Populations

		AXL + SIGLEC6 + DC	DC3 a	DC2A a	DC2B a	CCR7 + DC a	Refs
	Presence in	Cord blood	Cord blood	No	Corresponds to	No	[23]
	blood	Peripheral blood	Peripheral blood		classical cDC2		[11-15,21]
							[23]
							[13,17-22]
	Presence in	Spleen	Bone marrow	Spleen	Spleen	Tonsil (cDC)	[14,15,25]
	lymphoid	Tonsil				Thymus (cDC1 and cDC2)	[12,13,15]
	organs	Bone marrow				Spleen	[12,14]
						Melanoma-draining lymph	[17]
						node	[25]
							[25]
							[26]
							[45]
							[25]
							[37]
	Presence in	Absent from uninflamed skin	Skin?	?	?	Ascites (mo-DC)	[15]
	peripheral					Skin blisters (AXL + SIGLEC6 +	[19,20]
	tissues					DC and pDC)	[34]
						Liver tumor	[44]
						Lung tumor	[40]
						Lung tumor (cDC1 and cDC2)	[36]
						Colon tumor (cDC1)	[41]
						Skin	[42]
							[43]
	Pathological	Recruited to inflamed skin	Increased in blood of			Increased in skin lesions of	[44]
	situation	blisters and inflamed lung	SLE patients and			atopic dermatitis patients	[63]
			melanoma patients				[21]
							[20]
							[43]
	Marker genes	AXL	CD1C	CLEC4A	CD1C	LAMP3
		SIGLEC6	FCER1A	AREG	FCER1A	CCR7
		CD123	CD14	LTB	CLEC10A	CD83
		SIGLEC1	VCAN	CD3E		CCL22
		LYZ	S100A8			BIRC3
		BCL11A	S100A9			FSCN1
		TCF4	FCN1			IDO1
		KLF12	CLEC4E
			CD36
			CD163
	Surface	CD5 +	CD1c +	CD1c low	CD1c +	CCR7 +
	markers	CD2 +	CD5 -	CLEC10A -	CLEC10A +
		CX3CR1 +	BTLA -
		CD11c +/-	CD26 -
		CD123+/ low	CD14 low/+
			CD163 +
	Development	E2-2/TCF4 dependent	Derived from IRF8 low	?	?	Cell state induced by
		Differentiate into cDC2	precursor			maturation
		in vitro
	a Abbreviations: cDC, classical DCs; pDC, plasmacytoid DCs; DC3, type 3 DCs; cDC1, type 1 classical DCs; cDC2, type 2 classical DCs; mo-DC, monocyte-derived DCs;
	SLE, systemic lupus erythematosus.

  Trends in Immunology, Month 2020, Vol. xx, No. xx 7 Pre-pDC differentiate in the bone marrow into pDC. The developmental pathway of AXL + SIGLEC6 + DCs remains to be confirmed; they may derive from pre-pDC or directly from differentiated pDC in the periphery. Monocytes, cDC1, cDC2, pDC, and AXL + SIGLEC6 + DCs, circulate in the blood and can migrate to peripheral tissues and lymphoid organs. Whether blood DC3 can migrate to tissues is unclear. In mucosal tissues or upon inflammation, monocytes can differentiate in situ into mo-DCs. AXL + SIGLEC6

	Key Figure
	Proposed Updated Ontogeny-Based Classification of Human Dendritic
	Cell (DC) Subsets
	Bone marrow	IRF8 low precursor	pre-DC		pre-pDC
	precursors
				?	pDC
	DC3	Mono	preDC1	preDC2
	Blood			AXL + SIGLEC6 + DC	?
	DC3	Mono	cDC1	cDC2		pDC
	?
				??
		moDC
	Peripheral	Peripheral tissues and	Lymphoid
	tissues	lymphoid organs	organs
	Differentiation Migration	Maturation	Activated DC
					Trends Trends in in Immunology Immunology
	Figure 1. Plasmacytoid DCs (pDC), type 1 classical DCs (cDC1), type 2 classical DCs (cDC2), type 3 DCs (DC3), and
	monocyte-derived DCs (mo-DC), represent distinct human DC subsets. CD14 + monocytes (Mono) and DC3 derive from
	IRF8 low bone marrow precursors along distinct pathways. Bone marrow pre-DC give rise to preDC1 and preDC2, which
	differentiate into cDC1 and cDC2 in the periphery.

+ DCs may differentiate into cDC2 directly in tissues. Upon homeostatic or inflammation-induced maturation, all DC subsets express a convergent activation program.

  Trends in Immunology, Month 2020, Vol. xx, No. xx 9

	Are AXL + SIGLEC6 + DCs a subpopulation
	of pDC, or a distinct DC subset that
	stems from pre-pDC? A side-by-side
	comparison of the gene regulatory
	network of pDC and AXL + SIGLEC6 +
	DCs, might help to identify unique puta-
	tive transcription factors regulating
	separate developmental pathways.
	Can AXL + SIGLEC6 + DCs differentiate
	in vivo into cDC, and if so, in which
	contexts? Do they differentiate
	spontaneously or in response to
	specific signals? AXL + SIGLEC6 + DCs
	can differentiate in vitro into cDC2-like
	cells when placed in culture with cyto-
	kines. They are detected in inflamed tis-
	sues, but whether they can differentiate
	in situ after their recruitment is unclear.

Trends in Immunology, Month 2020, Vol. xx, No. xx

Trends in Immunology, Month 2020, Vol. xx, No. xx

Trends in Immunology, Month 2020, Vol. xx, No. xx 5

Trends in Immunology, Month 2020, Vol. xx, No. xx

Trends in Immunology, Month 2020, Vol. xx, No. xx

J.Villar and E. Segura

Acknowledgements

This work was funded by INSERM, Institut Curie (CIC IGR-Curie 1428), the Agence Nationale de la Recherche (ANR-10-LABX-0043, ANR-10-IDEX-0001-02 PSL and ANR-17-CE15-0011-01), the « Fondation pour l'aide à la recherche sur la sclérose en plaques », NIH grants AI128730 and AI100853. JV is a fellow of the IC-3i PhD program supported by the ERC Horizon 2020-Marie Sklodowska-Curie Actions (grant #666003) and of the Fondation pour la Recherche Médicale (FDT202106013025). IT is supported by the Bernard Levine Postdoctoral Fellowship in Immunology. The authors wish to thank the Flow Cytometry Platform of Institut Curie, the Next Generation Sequencing Platform of Institut Curie and the In vivo Experiments Platform of Institut Curie. The authors wish to thank S.Heurtebise and A.Coillard for technical assistance and J.Waterfall for helpful discussions.

to different methods for identifying monocyte-derived populations, or may reflect context-or tissue-dependent phenomenon. Mo-DC and mo-mac possess distinct functional properties.

Mo-DC can stimulate T cells in lymphoid organs or directly in tissues (Amorim et al., 2022; Coillard and Segura, 2021), while mo-mac are involved in resolution of inflammation and tissue repair (Gieseck et al., 2018;Guilliams et al., 2018). Determining the differentiation trajectories of monocytes, and their transcriptional control, will be essential in the therapeutic manipulation of their fate during pathogenic inflammation.

Acknowledgements

This work was funded by INSERM, Institut Curie (CIC IGR-Curie 1428), the Agence Nationale de la Recherche (ANR-10-LABX-0043, ANR-10-IDEX-0001-02 PSL and ANR-17-CE15-0011-01). JV is a fellow of the IC-3i PhD program supported by the ERC Horizon 2020-Marie Sklodowska-Curie Actions (grant #666003) and of the Fondation pour la Recherche Médicale (FDT202106013025). The authors wish to thank the Next Generation Sequencing Platform of Institut Curie. The authors wish to thank J.Waterfall for helpful discussions. Acknowledgments This work was funded by INSERM and Agence Nationale de la Recherche (ANR-10-LABX-0043 and ANR-17-CE15-0011-01). J.V. is a fellow of the IC-3i PhD program supported by the ERC Horizon 2020-Marie Sklodowska-Curie Actions (grant #666003).

The authors wish to thank A. Coillard for critical reading of the manuscript and M. Durand for graphic designing.

Acknowledgements

This work was funded by INSERM and Agence Nationale de la Recherche (ANR-10-LABX-0043 and ANR-17-CE15-0011-01). JV is a fellow of the IC-3i PhD program supported by the ERC Horizon 2020-Marie Sklodowska-Curie Actions (grant #666003).

Author Contributions

Conceptualization: JV, BR and ES. Methodology: JV, AC, CML, IT, BR, ES. Formal analysis: JV and PEB. Investigation: JV, AC, AdJ, CML, IT, ES. Writing -original draft: JV and ES.

Writing -review and editing: all authors. Supervision: ES.

Competing interests

The authors declare no competing interests.

Author Contributions

Conceptualization: JV and ES. Methodology: JV, ES. Formal analysis: JV. Investigation: JV.

Writing -original draft: JV and ES. Writing -review and editing: all authors. Supervision: ES.

Competing interests

The authors declare no competing interests.

Author Contributions

J.V. and E.S. wrote the manuscript.

Author contributions

JV and ES wrote the manuscript.

Declaration of Competing Interest

The authors declare no competing interests. Javiera Villar 1 , Alice Coillard 1 , Corné van Roessel 1 andElodie Segura 1

Culture system allowing the simultaneous differentiation of human monocytes into dendritic cells and macrophages using M-CSF, IL-4 and TNF-α

2.

Monocytes usually make up around 5-15% of PBMC. This can vary between donors.

3. CD14+ monocytes will be retained on the magnet while other PBMC will be eluted in the flow through. You can use the flow through to isolate other cell populations, otherwise you can discard the flow through.

4.

TNF-α enhances mo-DC differentiation in a dose-response manner. If only mo-DC are desired, the concentration of TNF-α can be increased to inhibit mo-Mac differentiation.

5.

We have noticed that cell density is critical in obtaining a balanced mo-Mac/mo-DC ratio (see Fig 4). High cell densities will increase mo-Mac differentiation. Each user should carefully calculate the expected density according to the culture plate or flask to be used.

6.

To test the impact of a given compound on monocyte differentiation, the tested molecule can be added at the beginning of the culture, or at later time points.

7.

In this culture system, the medium is not refreshed. The culture can be kept until day 6. After day 6, viability will decrease.

8.

The cells can be recovered in Eppendorf tubes, falcon tubes or 96-deep-well plates depending on the volume.

9.

To detach adherent cells from the wells, we recommend avoiding enzymatic treatments, such as trypsin. Instead, we incubate the cells in staining buffer (containing EDTA) on ice. This will allow detaching them by flushing, without damaging them.

10.

Other viability dyes can be used.