Audrey Deprince

Marine Andres

Quentin Throel

Valentine Guinot

Cécilia Bellengier

Artemii Nikitin

Denis Mogilenko

Marion Gimenez

Justine Beauchamp

Lise Ferri

Stephan Delhaye

Yasmin Sebti

Benoit Pourcet

Alicia Mayeuf-Louchart

Laurent L'homme

Emilie Dorchies

Nathalie Hennuyer

Joel Haas

Delphine Eberle

Retinoic acid receptor-related orphan receptor-alpha (RORa) is a transcription factor from the nuclear receptor superfamily expressed by immune and non-immune cells involved in the regulation of obesity, insulin resistance (IR) and non-alcoholic steatohepatitis (NASH). Cholesterol, cholesterol-sulfate, 7oxygenated sterols and oxysterols have been identified as potential endogenous RORa ligands. To better understand the mechanisms of macrophage-expressed RORa regulation in obesity and IR, we generated a macrophage-specific RORa-deficient (MKO) mouse line by using a LysM-Cre and floxed RORa mouse line. We report that RORa deletion in macrophages does not impact on HFD-induced obesity and IR. Surprisingly, we did not confirm an earlier report on the effect of HFD on NASH development upon HFD feeding nor in the more severe and obesity-independent choline-deficient, Lamino acid-defined diet model. We thus, suspected that LysM copy number may play a role in this discrepancy, as the genotype at the LysM locus is a major difference between the two independent lines of work. The LysM-Cre mice carry an insertion of Cre recombinase into the Lyz2 gene, leading to Cre expression under the control of the Lyz2 promoter and enhancers, but abolishing endogenous Lyz2 expression. While we intentionally maintained similar Cre and Lyz2 expression between WT and MKO by using only hemizygous animals for this locus (comparing Rora + / + Lyz2 Cre / + with Rora fl/fl Lyz2 Cre/+ ), floxed mice (Rora fl/fl Lyz2 +/+ ) were used as WT control and compared with MKO mice missing information about the Lyz2 locus (Rora fl/f Lyz2 Cre/? ) in the earlier study. As, we hypothesized that the observed impact of RORa deletion in macrophages on NASH in the earlier study likely did not result from a specific effect of RORa deletion, but rather from a different Lyz2 copy number between WT and MKO mice, we decided to verify this hypothesis experimentally. Surprisingly, our preliminary findings showed that the Lyz2deficient mice exhibit slight protection, rather than a detrimental effect, in HFD-induced obesity and IR, as determined by lower body weight and adipose tissue masses, significantly improved glycemic control and decreased epiAT inflammation. Interestingly, whole body Lyz2 deficiency had no impact on hepatic steatosis (NAFL) in HFD-fed mice. Nonetheless, our preliminary findings even suggest that Lyz2 deficiency might protect against advanced and obesity-independent choline-deficient, L-amino aciddefined diet-induced NASH. Taken together, these preliminary findings indicate that different Lyz2 gene copy number in control mice is unlikely to account for the discrepancy between our work and the earlier study. Overall, our results show that RORa deletion in macrophages does not alter the development of obesity and IR and question its role in NASH. On the other hand, we believe that further investigations are of significant interest in the context of obesity, IR, and advanced NASH, as Lyz2 might possess a therapeutic value.

I am thankful to Barbara GROSS and Christian DUHEM for their effort in the generation of macrophage-specific RORa-deficient mice. Also, I want to thank Olivier MOLENDI-COSTE for the obtained preliminary data from those mice, for cell sorting experiments, and for together with Sandrine QUEMENER to take care of the ROR mice breeding. I am also grateful to Marie-Laure JOSEPH for the genotyping of our mice. Besides, I want to thank Sandrine QUEMENER, Sébastien FLEURY, and Laurent PINEAU for their technical supports during sacrifices. I am much obliged to Sébastien FLEURY for his assistance in our histology applications. I appreciate Mathilde LE MAITRE for the technical supports of her. Last but not least, I want to express my gratitude to Emmanuelle VALLEZ and Anne TAILLEUX for their support in the biochemical analysis by KONELAB.

It was a great pleasure to do some qPCR, RT, RNA extraction, or western blot at the same time as Christian DUHEM that he always made it very entertaining thanks to his sincere personality. I will never forget how much I enjoyed it, in particular when I got very nice results, while he failed. Thank you for being such a magnificent, high-minded person. Special thanks to Bruno DERUDAS for providing me qPCR, RT-PCR,

RÉSUMÉ

RORa (Retinoic acid receptor-related orphan receptor-alpha) est un facteur de transcription de la superfamille des récepteurs nucléaires exprimé par des cellules immunitaires et non immunitaires impliqué dans le contrôle de l'obésité, de l'insulinorésistance (IR) et de la stéatohépatite non alcoolique (NASH). Le cholestérol, le cholestérol-sulfate, les stérols 7-oxygénés et les oxystérols ont été identifiés comme des ligands endogènes potentiels RORa. Pour mieux comprendre le rôle de RORa exprimé par les macrophages dans l'obésité et I'IR, nous avons généré une lignée de souris déficientes en RORa spécifiques aux macrophages (MKO) en utilisant des lignées de souris LysM-Cre et RORa foxée. Nous résultats montrent que l'inactivation de RORa dans les macrophages n'a pas d'impact sur l'obésité et l'insuline-résistance induites par une régime riche en graisses (HFD). Étonnamment, contrairement à des travaux, notre étude ne montre pas d'effet sur le développement de la NASH ni suite à un régime HFD, ni dans le modelé d'alimentation défini par les acides aminés L, plus sévère et indépendant de l'obésité et déficient en choline. Nous avons donc soupçonné que le nombre de copies de LysM pouvait jouer un rôle dans cette divergence, car le génotype des souris au l locus LysM est une différence majeure entre les deux études indépendantes. Les souris LysM-Cre portent une insertion de la recombinase Cre dans le gène Lyz2, ce qui conduit à l'expression de Cre sous le contrôle du promoteur Lyz2 et ses activateurs, mais abolit l'expression endogène de Lyz2. Alors que nous avons intentionnellement maintenu une expression similaire de Cre et de Lyz2 entre WT et MKO en utilisant uniquement des animaux hémizygotes pour ce locus (en comparant Rora +/+ Lyz2 Cre/+ avec Rora fl/fl Lyz2 Cre/+ ), des souris foxées (Rora fl/fl Lyz2 +/+ ) ont été utilisées comme contrôle de WT et comparées avec des souris MKO pour lesquelles il manquait des informations sur le locus Lyz2 (Rora fl/fl Lyz2 Cre/ ? ) dans l'étude antérieure. Aussi, nous avons émis l'hypothèse que l'impact observé de la délétion de RORa dans les macrophages sur la NASH dans l'étude précédente ne résultait probablement pas d'un effet spécifique de la délétion de RORa, mais plutôt d'un nombre de copies Lyz2 différent entre les souris WT et MKO et avons décidé de vérifier cette hypothèse expérimentalement.

De manière surprenante, nos résultats préliminaires ont montré que les souris déficientes en Lyz2 présentent une légère protection, plutôt qu'un effet néfaste, dans l'obésité et l'IR induites par le HFD, comme le montre la diminution du poids corporel et des masses de tissu adipeux, l'amélioration significative du contrôle de la glycémie et la diminution de l'inflammation de l'épiAT. Il est intéressant de noter que la déficience totale en Lyz2 n'a eu aucun impact sur la stéatose hépatique (NAFL) chez les souris nourries au HFD. Néanmoins, nos résultats préliminaires suggèrent même que la carence en Lyz2 pourrait protéger contre la NASH induite par le régime alimentaire, carence en choline. Dans leur ensemble, ces résultats préliminaires indiquent que le nombre différent de copies du gène Lyz2 chez les souris de contrôle n'explique probablement pas la différence entre notre travail et l'étude précédente.

Globalement, nos résultats montrent que la délétion de RORa dans les macrophages ne modifie pas le développement de l'obésité et de l'IR et remettent en question son rôle dans la NASH. D'autre part, nous pensons que des recherches plus approfondies sur le rôle du lysozyme présentent un intérêt significatif dans le contexte de l'obésité, de l'IR et de la NASH avancée, car Lyz2 pourrait avoir un intérêt thérapeutique.

iii ACKNOWLEGMENTS First of all, I am thankful to my thesis advisor Dr. David DOMBROWICZ for the opportunity to welcome me in his team at unit 1011, designing the project and for his supportive as well as tolerant mentoring during those years.

Secondly, I am grateful to Dr. Laurent L'HOMME for his day-to-day supervision as a postdoctoral fellow, which I gained a bunch of experiences from him. I can't thank you enough for the contribution you have been made to this work experimentally and intellectually as well as your effort to help me in administrative procedures. I also appreciated the scientific and nonscientific conversations we had that help me to understand general Belgian, and French culture, especially the culture of the beers. I am so glad to support the ''Belgian Red Devils'' with you in the World Cup 2018 against all our French collogues. What would I do without a bench and project partner like you! Thank you for making the lab such a great place to work every day, literally every day, including almost all the weekends and holidays, with the support of a sheer volume of coffee and the Monster energy drink! Thank you for being a kind, supportive, friendly, and extremely organized role model for me.

I want to declare my appreciation to Prof. Dr. Bart STAELS for the high-level scientific meetings, discussions, and all the helpful advices, which are always making a huge difference in our work.

I am also thankful to the jury members of the international Ph.D. students fellowship competition (2017-2018) for deem me worthy of this fellowship and to the École Doctorale Biologie et Santé de Lille (EDBSL, 446) for funding me as a Ph.D. student. I want to acknowledge my Ph.D. thesis follow-up committee members Prof. Dr. Jean MARIANI and Dr. Stoyan IVANOV for improving the quality of the thesis and scientific discussions.

Importantly, I am much obliged to Dr. Stoyan IVANOV for his support for me to initiate the LysM project.

Importantly, I am very grateful to all the people of unit 1011 for their understanding of how bad I am at speaking in French and their effort to communicate with me in English. Besides, I appreciate their positive attitude and good-humor that constitutes an excellent atmosphere to work in it. I am grateful to have the opportunity to be part of this unit. v I want to thank Corinne COPIN and Jacques FRAMAUX for playing the role of the bad cop in the lab to maintain the order, specifically, to Corinne for her ''gentle'' reminders to the mutual tasks.

Special thanks to Marie-Hélène DERUDAS and Rosamée JAFEU first for their patience with me about French and secondly for their help in administrative works.

I want to express my gratitude to François DECLORIX from the École Doctorale Biologie et Santé de Lille (EDBSL, 446) for his incessant and effective supports in administrative acts throughout my Ph.D.. During those years, I crossed paths with many special people outside the lab, few in France, mostly from Belgium who supported me and reminded me that there is a life next to science, which needs to be lived! My friends, I want to deeply thank you for making me feel part of the big Belgian family.

I have a tremendous appreciation, which inexpressible to my real friends from Turkey, Gülizar AYDOGDU, Kubra KUCUKER, Nuray GULEC, who stayed in contact with me during those years and supported me psychologically against all the trials and tribulations.

The next one goes to my family. Canım annem üç sene içerisinde sadece iki kere Türkiye'ye gelebildiğim ve her birinde ikişer hafta kalabildiğim, özetle üç yılda bir ay yanında olabildiğim için çok üzgünüm. Doğduğun ülkenin dışında, dilini bilmediğin, ailenden, arkadaşlarından, sevdiklerinden uzakta üç yıl geçirmenin bana kazandırdığı iş anlamındaki büyük tecrübelerin yanı sıra, hayatla ilgili de birçok öğretisi oldu. Ben ileride başarılı bir bilim insanı olabilmek için burada neredeyse 7/24 çalışırken hayatın da bir yandan akıp gittiği ve beni beklemediği gerçeğiyle ne yazık ki pamuk prensesim canım anneannemi son bir kez görmeden kaybederek, biricik annişkolatam senin ciddi bir medikal operasyonunda ve canım abişkolatam senin eşinden ayrıldığın dönemde yanınızda size destek olmak için bulunamayarak öğrenmiş oldum. Güçlü olup bana ihtiyacınız olduğu halde ben üzülmeyeyim, etkilenmeyeyim, işlerim aksamasın diye bana tek bir şey yansıtmayan canım annem Gülseren DEMIRBILEK ve abim HILMI ALP SERMIKLI'ye olan vefa borcumu asla ödeyemem. Bir tanecik güzeller güzeli canım annem sen benim bu hayattaki tek gerçek dostumsun. Bu kadar mükemmel bir anne olduğun için en önemlisi dostum olabilen bir anne olduğun için sana çok ama çok minnettarım. Canım abim sana da harika bir abi olduğun için ve benim yokluğumu anneme aratmayacak şekilde ona destek olduğun için ne kadar teşekkür etsem az. Sizleri çok ama çok seviyorum. İyi ki varsınız iyi ki benim ailemsiniz.

LIST OF FIGURES

LIST OF TABLES

INTRODUCTION 1. OBESITY

Obesity is a medical condition characterized by redundant fat accumulation in the body, arising from genetic factors, excessive dietary intake, and sedentary lifestyle (Figure 1). The widely used method to quantify obesity is body mass index (BMI) calculated by dividing the individual's body weight to the individual's height (kg/m²). According to the World Health Organization (WHO), the BMI value over 25 is considered as overweight, and over 30 as obesity in adults 1 . The prevalence of obesity nearly tripled since 1975 worldwide. The latest available data reveal that almost 2 billion world adult population is overweight (39%) among them, 650 million are obese (13%). Furthermore, 340 million children and adolescents aged between 5 and 19 were overweight or obese (10%) in 2016 [START_REF] Ncd-Risc | Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128•9 million children, adolescents, and adults[END_REF] . Obesity is strongly associated with Type 2 Diabetes (T2D), Non-alcoholic Fatty Liver Diseases (NAFLD), and Cardio Vascular Diseases (CVD) 3 . Consequently, overweight and obesity are the 5 th leading risk factor for global mortality in the 21 st century [START_REF] Abdelaal | Morbidity and mortality associated with obesity[END_REF] . Mutation in some key genes that regulate appetite leads to a monogenic form of obesity, including leptin (LEP), leptin receptor (LEPR), melanocortin 4 receptor (MC4R), pro-opiomelanocortin (POMC), and fat mass and obesity associated gene (FTO), which are extremely rare [START_REF] Fairbrother | Genetics of Severe Obesity[END_REF] . Nonetheless, heredity only cannot explain the global increase in the prevalence of obesity over the past decades. Thus, it is essential to identify underlying mechanisms involves in the pathogenesis to identify new therapeutic targets against obesity and associated complications. Diabetes is a cluster of diseases as characterized by increased blood glucose levels resulting from either the defects in insulin secretion, and/or resistance to insulin's action (Table 1). Diagnosis of the diabetes depends on either, the fasting plasma glucose (FPG) value or the 2hplasma glucose (2-h PG) levels through the oral glucose tolerance test (OGTT), and glycated hemoglobulin (HbA1C) criteria (Table 2). Obesity is closely associated with type 2 diabetes (T2D), which is characterized by hyperglycemia and hyperinsulinemia. Overall, 85 % of individuals developing T2D are overweight or obese [START_REF] Bhupathiraju | Epidemiology of Obesity and Diabetes and Their Cardiovascular Complications[END_REF] . The global prevalence of the T2D in adults was 8.5% (422 million) in 2014 [START_REF]Diabetes[END_REF] . T2D is the most frequent type of diabetes accounting for 90-95 % of all types of diabetes worldwide. Individuals with T2D exhibit peripheral insulin resistance in spite of normal insulin secretion, which means cells cannot respond to insulin accurately [START_REF]2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2019[END_REF] . As a result of T2D, insulin resistance occurs at adipose tissue, liver, and skeletal muscle, which is triggered by multiple mechanisms, including genetic factors, lipotoxicity, inflammation, endoplasmic reticulum (ER) stress, mitochondrial dysfunction, and reactive oxygen species (ROS) production [START_REF] Habib Yaribeygi | Biochemical and cellular properties of insulin receptor signalling[END_REF] .

Table 2: Criteria for the diagnosis of diabetes.

Glucocorticoids

Adapted from American Diabetes Association, 2019 .6 Table :2 Criteria for the diagnosis of diabetes FPG ≥126 mg/dL (7.0 mmol/L). Fasting is defined as no caloric intake for at least 8 h.

2-h PG ≥200 mg/dL (11.1 mmol/L) during the OGTT. The test should be performed as described by the WHO.

HbA1C ≥6.5% (48 mmol/mol) The test should be performed in a laboratory using a method that is NGSP certified and standardized to the DCCT assay.

In a patient with classic symptoms of hyperglycemia or hyperglycemic crisis, a random plasma glucose ≥200 mg/dL (11.

b. Insulin Receptor Signaling

Insulin is secreted from the pancreatic beta cells in parallel with the increased blood glucose levels after a meal. Insulin is an anabolic hormone that regulates glucose, lipid, and protein metabolism through the insulin receptor signaling pathway in adipose tissue, liver, and skeletal muscle (Figure 2A). The insulin receptor (IR) is a hetero-tetrameric receptor with tyrosine kinase activity that comprises of two extracellular a subunits and two transmembrane b subunits that are linked by disulfide bonds (Figure 2B). Insulin binds to the extracellular a- Besides mediation of the glucose uptake by glucose transporters, the AKT/PKB is considered as a central regulator of the insulin's distal actions, such as glycogen synthesis by the glycogen synthase kinase three beta (GSK3b), protein and lipid synthesis by mammalian target of rapamycin (mTOR), glucose metabolism by forkhead family box O (FOXO) [START_REF] Manning | AKT/PKB Signaling: Navigating the Network[END_REF] . So far, three AKT isoforms identified in mammalian, which are AKT1 (PKBa), AKT2 (PKBb), and AKT3

subunits
(PKBg). The AKTs possess two key phosphorylation residues to ensure stabilization and become activated, which is the first one a threonine residue (Thr) on the catalytic domain, and the second one is a serine (Ser) residue in the regulatory region of the carboxy-terminal [START_REF] Alessi | Mechanism of activation of protein kinase B by insulin and IGF-1[END_REF] .

Regarding this, the phosphoinositide-dependent kinase one (PDK1) phosphorylates AKT1 at the Thr-308 residue afterward, the mammalian target of rapamycin complex two (mTORC2)

phosphorylates the Ser-473 residue 13 , 14 . Following this, successive phosphorylations also occurs on the corresponding residues of the AKT2 (Thr-309 and Ser-474) and the AKT3 (Thr-305 and Ser-472) [START_REF] Kandel | The Regulation and Activities of the Multifunctional Serine/Threonine Kinase Akt/PKB[END_REF] . It has been reported that activated AKTs be able to phosphorylates several protein substrates with diverse subcellular localizations [START_REF] Manning | AKT/PKB Signaling: Navigating the Network[END_REF] .

Some rare forms of severe insulin resistance have been associated with mutations in the insulin receptor gene, which are leprechaunism, Rabson-Mendenhall syndrome, or the type-A syndrome. Patients with these syndromes have non-sense or missense mutations in the extracellular ligand binding domain (a subunits) or intracellular tyrosine kinase domain (b subunits) of the insulin receptor that hampers insulin signaling pathway 17 , 18 . One of the common polymorphisms is the G972R polymorphism of IRS-1 observed in patients with T2D, leading to decreased insulin signaling through impaired PI3K activity 19 , 20 . Even though it slightly affects the insulin signaling, the M326I polymorphism in the p85a regulatory subunit of the PI3K has been identified as a risk factor for T2D occurrence 21 , 22 . Furthermore, in diabetic patients, a rare missense mutation, which is the R274H in AKT2 has been reported, ruining the kinase activity [START_REF] George | A Family with Severe Insulin Resistance and Diabetes Due to a Mutation in AKT2[END_REF] .

c. Classification of adipose tissue

Adipose tissue is classified on the basis of the major cell type component. White adipose tissue (WAT), which is predominantly composed of large, adipocytes with unilocular lipid droplets and represents the majority of the lipid mass as an energy storage. Brown adipose tissue (BAT)

and beige/brite adipose tissue, which is mainly consist of cells with multilocular lipid droplets and abundant mitochondria that perform thermogenesis via uncoupled mitochondrial respiration, in response to cold or adrenergic stimulation [START_REF] Kahn | Altered adipose tissue and adipocyte function in the pathogenesis of metabolic syndrome[END_REF] . The majority of the WAT is categorized as either visceral (VAT) or subcutaneous (SAT) adipose tissue. VAT depots includes, surroundings of the epicardial/pericardial area and intra-abdominal organs, like mesenteric, omental, perigonadal, perirenal, and retroperitoneal in both humans and rodents.

The main difference between humans and rodents VAT depots is that large omental VAT exist in humans and rather large perigonadal VAT, also known as epididymal WAT (eWAT) is found in rodents (Figure 3). SAT is subdivided into upper (abdominal) and lower (gluteal and femoral) depots in humans, which corresponds to anterior and posterior depots, so-called inguinal WAT (ingWAT) in rodents [START_REF] Luong | Deciphering White Adipose Tissue Heterogeneity[END_REF] .

d. Obesity and Type 2 Diabetes

T2D is known to be related to visceral adiposity. Risk of the T2D can be determined by waist circumference (WC) and waist to hip ratio (WHR) measurements. Thus, if the waist circumference in male equal or more than 102 centimeters, whereas in female equal or more than 88 centimeters, individuals are classified as at high risk. Moreover, the waist / hip ratio should not exceed 1 in men and 0.8 in women [START_REF]Waist circumference and waist-hip ratio: report of a WHO expert consultation[END_REF] . Indeed, in some rare cases, like T2D patients who are not overweight or obese have an increased proportion of body fat distribution mainly, in the visceral depots rather than subcutaneous [START_REF] Lukich | Normal weight diabetic patients versus obese diabetics: relation of overall and abdominal adiposity to vascular health[END_REF] . Interestingly, it has been shown that fat accumulation in the subcutaneous depots rather than visceral depots has a beneficial effect against obesity and associated complications, which is known as metabolically healthy obesity (leptin, adiponectin, resistin, visfatin etc.) and cytokines (TNFa, IL-1b, IL-6, IL-8, IL10, TGFb etc.) that possesses autocrine and paracrine properties [START_REF] Fasshauer | Adipokines in health and disease[END_REF] . For this reason, to be under control, WAT contain several immune cell types within its stromal vascular fraction. Lean and obese WAT immune compartment differ considerably regarding the number and cell type composition (Figure 4), which we will further discuss in detail (see section 1.4). .4). Therefore, dysregulated production of adipokines and pro-inflammatory cytokines, like TNFa, IL-1b, and IL-6 contributes to the chronic low-grade inflammation [START_REF] Ruiz-Fernández | Molecular Relationships among Obesity, Inflammation and Intervertebral Disc Degeneration: Are Adipokines the Common Link?[END_REF] .

In the lean state, some specific subsets of WAT-resident immune cells (see section 1.4) restrict inflammation and insure tissue homeostasis via immuno-regulatory cytokine production 38 , 39 .

In obesity, WAT expands through hypertrophy, due to the lipid accumulation and to some extent, through hyperplasia, due to proliferation and differentiation of the preadipocytes, leading to extracellular matrix disposition [START_REF] Ghaben | Adipogenesis and metabolic health[END_REF] . Obese WAT, secrete increased amount of adipokines that includes several inflammatory mediators, like leptin, MCP-1, RANTES, TNFa, IL-6, IL-1b, promoting infiltration of the pro-inflammatory immune cells (see section 1.4).

Consequently, pro-inflammatory immune cells become predominant within the WAT and leads to chronic, low-grade inflammation also, known as metaflammation, as a result, WAT became dysfunctional [START_REF] Unamuno | Adipokine dysregulation and adipose tissue inflammation in human obesity[END_REF] . Dysfunctional WAT will overproduce and secrete FFAs into the circulation due to the uncontrolled lipolysis [START_REF] Sobczak | Changes in Plasma Free Fatty Acids Associated with Type-2 Diabetes[END_REF] . Recently, has been shown that WAT-resident immune cells fundamental mediators of the healthy expansion and tissue remodeling during weight gain [START_REF] Wernstedt Asterholm | Adipocyte Inflammation Is Essential for Healthy Adipose Tissue Expansion and Remodeling[END_REF] .

However, in advanced obesity, adipocytes are no longer being able to expand and undergo a necrosis process due to the decreased oxygen tension [START_REF] Crewe | The ominous triad of adipose tissue dysfunction: inflammation, fibrosis, and impaired angiogenesis[END_REF] . Pro-inflammatory macrophages are recruited around dead cells and form a crown-like structure, supporting NLRP3 inflammasome activation [START_REF] Cinti | Adipocyte death defines macrophage localization and function in adipose tissue of obese mice and humans[END_REF] . Excessive triglycerides and FFAs, which are released by WAT and stored in ectopic tissues, such as liver, heart, pancreas, and kidneys, yielding to lipotoxicity, further contributing to the pro-inflammatory milieu [START_REF] Rosen | What We Talk About When We Talk About Fat[END_REF] . Another sign of lipotoxicity is that increased production of lipid intermediates, like diacylglycerol, ceramide, and fatty acyl-coenzyme A negatively regulates insulin signaling pathway, as we will discuss in the following section [START_REF] Ertunc | Lipid signaling and lipotoxicity in metaflammation: indications for metabolic disease pathogenesis and treatment[END_REF] .

b. Mechanisms of insulin resistance

Pro-inflammatory cytokines, such as TNFa, IL-1b, IL-6, ER stress, and FFAs activate the c-Jun N-terminal kinase (JNK) and the inhibitor of nuclear k-B kinase subunit beta (IKKb) serine/threonine (Ser/Thr) stress kinases 48 , 49 . Activation of the JNK and IKKb, impairs insulin receptor signal transduction by phosphorylation of IRS-1 on inhibitory serine instead of stimulatory tyrosine residues consequently, represses P13K/AKT signal transduction (Figure 5). IKKb also activates the nuclear factor k light chain enhancer of activated B cells (NF-kB)

and translocate to the nucleus where promotes transcription of inflammatory genes that directly influences insulin signaling [START_REF] Catrysse | Inflammation and the Metabolic Syndrome: The Tissue-Specific Functions of NF-κB[END_REF] . The key negative regulator of insulin and leptin sensitivity, protein tyrosine phosphatase 1B (PTP1B) has been shown to be upregulated by NF-kB in the adipose tissue and liver [START_REF] Zabolotny | Protein-tyrosine Phosphatase 1B Expression Is Induced by Inflammation in Vivo[END_REF] . Moreover, saturated fatty acids induce ceramide biosynthesis that interfere with the insulin signaling via toll-like receptor 4 (TLR4) and NF-kB signaling [START_REF] Holland | Lipid-induced insulin resistance mediated by the proinflammatory receptor TLR4 requires saturated fatty acid-induced ceramide biosynthesis in mice[END_REF] . The ribosomal protein S6 kinase (S6K) suppresses insulin signaling by phosphorylation of IRSs on multiple Ser/Thr domains [START_REF] Shah | Inappropriate Activation of the TSC/Rheb/mTOR/S6K Cassette Induces IRS1/2 Depletion, Insulin Resistance, and Cell Survival Deficiencies[END_REF] . Moreover, the pleckstrin homology domain and leucinerich repeat protein phosphatase 1 and 2 (PHLPP1-2) family de-phosphorylates AKT and impairs Akt signaling 54 , 55 . Likewise, S6K-mediated phosphorylation of mTORC2 components rictor and sin1 inhibits phosphorylation of AKT at Ser473 domain 56 , 57 . Additionally, protein kinase C e (PKCe), which is activated via diacylglycerols, interfere insulin signaling by phosphorylating Thr1160 residue in the activation loop of the IR [START_REF] Petersen | Insulin receptor Thr1160 phosphorylation mediates lipid-induced hepatic insulin resistance[END_REF] . Similarly, activation of the protein kinase C z (PKCz) and protein phosphatase 2A (PP2A) by ceramides, alters membrane localization of the AKT consequently, abolishes AKT function 59 , 60 .

Phosphatase and tensin homolog (PTEN) and Src-homology 2-containing inositol phosphatase 2 (SHIP2) are two significant lipid phosphatases that de-phosphorylate lipid messenger PIP3 thereby, attenuate insulin signaling transduction [START_REF] Lazar | Lipid phosphatases as drug discovery targets for type 2 diabetes[END_REF] . PTEN is a 3' phosphatase that turn PIP3 into its precursor PIP2 and disengage insulin signaling [START_REF] Masson | Structural Mechanisms of PTEN Regulation[END_REF] . Moreover, studies showed that tissue-specific deletion of PTEN protects against insulin resistance and associated outcomes in the adipose tissue, liver and muscle 63 , 64 , 65 . SHIP2 is a 5' phosphatase which also converts PIP3 to PIP2 and has been shown to protects against obesity and insulin resistance [START_REF] Lehtonen | SHIPping out diabetes-Metformin, an old friend among new SHIP2 inhibitors[END_REF] .

Growth factor receptor-bound proteins (GRBs), also known as insulin receptor-binding proteins (Grb-IRs) are pseudo-substrates of the IR kinase that has two essential domains. One of them is BPS (between PH and SH2) domains which binds to the substrate-binding slit of the IR. The second domain is an SH2 domain, which binds to the phosphorylated tyrosine residues on the IR. Mice deficient for GRB10 and GRB14, or both displayed better insulin sensitivity, underlying the biological importance of these proteins 67 , 68 , 69 . Furthermore, SNPs located inside or nearby GRB10 gene have been associated with fasting hyperglycemia, and insulin resistance [START_REF]A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance[END_REF] . Similarly, SNPs proximate to the GRB14 gene have been correlated with insulin resistance, adiposity, and body fat disruption [START_REF]A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance[END_REF] .

The Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway is a downstream mediator for various cytokines, growth factors, and hormones. Various receptors upon ligand binding, recruit cell-surface JAK proteins to their intracellular domains that lead to dimerization and activation through autophosphorylation. Thereafter, JAKs, phosphorylate and activate STAT proteins which result in dimerization and translocation to the nucleus where they regulate gene expression [START_REF] Dodington | STAT -Emerging Players in Metabolism[END_REF] . In mammalians, four members of the JAK family (JAK1-3 and TYK2), and seven members of the STAT family (STAT1-4, STAT5A-B, and, STAT6) have been identified [START_REF] Villarino | Mechanisms and consequences of Jak-STAT signaling in the immune system[END_REF] . It has been shown that adipocyte-specific Jak2-deficient mice had impaired lipolysis in response to insulin thereby, displaying insulin resistance, greater body weight and adiposity in basal conditions with ageing [START_REF] Shi | Adipocyte-specific deficiency of Janus kinase (JAK) 2 in mice impairs lipolysis and increases body weight, and leads to insulin resistance with ageing[END_REF] . Furthermore, similar results have been reported

for the adipocyte-specific Stat3 and Stat5-deficient mice resulting in dysregulation of the lipolytic genes in WAT [START_REF] Cernkovich | Adipose-Specific Disruption of Signal Transducer and Activator of Transcription 3 Increases Body Weight and Adiposity[END_REF] , [START_REF] Kaltenecker | Adipocyte STAT5 deficiency promotes adiposity and impairs lipid mobilisation in mice[END_REF] .

The suppressor of cytokine signaling (SOCS) is a family of proteins that regulate JAK/STAT pathway. Thus, modulating various biological processes, like immunity, apoptosis, cell proliferation and differentiation [START_REF] Durham | Targeting SOCS Proteins to Control JAK-STAT Signalling in Disease[END_REF] . Four members of the SOCS (SOCS1, SOCS3, SOCS6, and SOCS7) family attenuate insulin signaling, via their SH2 domain that binds to phospho-tyrosine domain of the IR. A SOCS protein recruits a ubiquitin ligase to target IRS proteins for proteasomal degradation via SOCS box domain [START_REF] Howard | Attenuation of leptin and insulin signaling by SOCS proteins[END_REF] . Among other SOCS, SOCS3 gained special attention since, its expression is increased in various tissues of obese animals [START_REF] Pedroso | SOCS3 as a future target to treat metabolic disorders[END_REF] . Even though, SOCS3 is a key protein reducing the activity of the inflammatory cytokines that has been associated with various inflammatory diseases [START_REF] Rottenberg | SOCS3, a Major Regulator of Infection and Inflammation[END_REF] , additional studies showed that SOCS3 modulates energy metabolism via dampening not only insulin but also leptin signaling in obesity, pregnancy, and refeeding period after fasting 80 , 81 . Brain specific SOCS3-deficient mice displayed reduced weight gain, adiposity in high fat diet (HFD)-induced obesity model [START_REF] Mori | Socs3 deficiency in the brain elevates leptin sensitivity and confers resistance to diet-induced obesity[END_REF] .

Importantly, SOC3-deficient mice only in leptin receptor-expressing cells showed no differences either in weight gain, adiposity or food intake suggesting that the mechanism/s involved in prevent diet-induced obesity depends on specific neuron populations [START_REF] Pedroso | Inactivation of SOCS3 in leptin receptor-expressing cells protects mice from diet-induced insulin resistance but does not prevent obesity[END_REF] .

Role of Gut Microbiota in Obesity

Depletion or alteration of gut microbiota is a prominent contributor to the development of the obesity and insulin resistance in both rodent models and humans 84 , 85 , 86 , 87 . As primarily observed, the germ-free mice are protected from HFD-induced obesity and insulin resistance [START_REF] Backhed | The gut microbiota as an environmental factor that regulates fat storage[END_REF] , whereas fecal microbiota transplantation (FMT) from obese to germ-free mice triggers obesity and insulin resistance [START_REF] Bäckhed | Mechanisms underlying the resistance to diet-induced obesity in germ-free mice[END_REF] . In line, FMT of the lean donors to obese patients improves insulin sensitivity 90 , 91 . Similarly, dyslipidemia, insulin resistance, and inflammation has been associated with low bacterial diversity, determined by low microbial gene count in fecal DNA [START_REF] Metahit Consortium | Richness of human gut microbiome correlates with metabolic markers[END_REF] . Correlatively, it has been shown that compensation of the bacterial richness with dietary intervention in individuals with low microbial gene count lead to improved metabolic outcomes [START_REF]Dietary intervention impact on gut microbial gene richness[END_REF] . In obesity, dysbiosis is associated with increased intestinal permeability due to the reduced expression of epithelial tight junction proteins, causing to leakage of bacteria or bacterial products, like inflammatory lipopolysaccharide (LPS), across the intestinal barrier that triggers intestinal immune system [START_REF] Winer | The Intestinal Immune System in Obesity and Insulin Resistance[END_REF] . Eventually, systemic circulation of the bacterial products has been reported in peripheral tissues, such as WAT, contributing to the pro-inflammatory milieu in obesity [START_REF] Burcelin | Metagenome and metabolism: the tissue microbiota hypothesis: Burcelin et al[END_REF] , 96 , 97 .

Impact of Immune Cells on Health and Obesity in White Adipose

Tissue

As described above, crosstalk between WAT and immune cells is the critical process in the pathophysiology of obesity. Healthy AT harbors type 2 immune cells and communicate with each other via the production of type 2 cytokines that contribute to protective and regulatory response at homeostasis (see below). In contrast, obese AT mostly contains proinflammatory type 1 and 17 immune cells that produces type 1 and type 17 cytokines (Figure 6). CD8a is considered as a marker of lymphoid-resident cDC1 subset 132 , while CD103 expresses in the non-lymphoid tissues (e.g. AT, liver, kidney) and serves as a migratory cDC1 subset 133 .

In addition, the mouse cDC1 subset expresses cell adhesion molecule 1 (CADM1), C-type lectin receptor 9A (Clec9a) and X-C motif chemokine receptor 1 (XCR1), which are also found in human 134 . However, the Clec9a expression is not only restricted to mouse cDC1 subset, but also detectable in the cDC progenitors and pDCs 135 , unlike human 136 . On the other hand, the cDC2 subset can be distinguished by high expression of the MHC-II, CD11b, CD11c, and signal regulatory protein alpha (SIRPa) in both, mice and humans 137 . pDC subset is determined as MHC-II, CD11c-CD123 high CD45A-B220 expressing cells as a mutual surface marker in both mice and humans. Moreover, some additional pDCs markers have been identified, including the blood DC antigen 2 (BDCA2) 138 , BDCA4 139 , CD317, and ILT7 140 , which are specific for humans as well as mice specific the bone-marrow stromal cell antigen 2 (BTS2) 141 , and sialic acid-binding Ig-like lectin H (SiglecH) 142 . The pDC subset has been suggested to originates from the both myeloid and lymphoid lineages 143 . As their secretory cell-like morphology implies, the pDCs are specialized to produce large amount of type-

b. Dendritic cells

The role of the DCs in obesity is not fully understood yet since the lack of specific DC markers, allowing for unambiguous distinction from macrophages. DCs expand in obese AT, promote macrophage infiltration and their increased numbers are positively correlate with HFD-induced metabolic abnormalities 197 . Moreover, the accumulation of DC in obese AT induces Th17 differentiation that promotes obesity-induced inflammation and IR in mice and humans 198 , (197) .

Discrimination of AT-resident DCs from macrophages on the basis of CD64 expression allowed to determine that both cell types are independent contributors to obesity-induced inflammation and IR 199 . In the same study, it was also shown that monocytes, recruited to the AT in a CCR7 and to a lesser extent CCR2-dependent manner, differentiated into DCs in response to HFD feeding 199 In conclusion, even though, obesity and obesity-associated insulin resistance are multifactorial, pathophysiology is characterized by a state of chronic low-grade inflammation driven by different stimulus. Thus, targeting to inflammation hold promise against obesityassociated metabolic diseases. However, the complexity and diversity of inflammatory cells as well as pathways in response to diets, tissue micro-environments, gut microbiota-derived inflammation in obesity is challenging. When obesity is not successfully managed at the stage of SS, immune cells also infiltrate the liver further contributing to a low-grade, but chronic intrahepatic inflammatory process. Lipotoxicity and glucotoxicity

NON-ALCOHOLIC FATTY LIVER DISEASES

Role of gut microbiota in non-alcoholic fatty liver diseases

The portal vein mediates a functional and bidirectional interface that connects the gastrointestinal tract and liver, known as the entero-hepatic axis. Due to the symbiotic association with intestinal gut microbiota, function of the entero-hepatic axis is tightly interconnected with the immune system. As intestinal permeability is altered in obesity, bacteria and bacterium-related product, such as LPS translocation from the intestinal lumen to the circulation, and eventually into the tissues, such as liver via the portal vein, activating the immune system. Indeed, intestinal permeability has been shown to influence the pathogenesis of various chronic liver diseases, including NAFLD, not only by stimulating the immune system but also preventing the arrival of the beneficial microbial metabolites derived from the fermentation of carbohydrates and proteins by intestinal microbiome to the liver in various animal models 296 . Accordingly, early clinical findings indicated that NAFLD patients display increased intestinal permeability with a high prevalence of bacterial overgrowth in small intestine compared to healthy individuals Ksibella pneumonia (HiAlc-Kpn) correlated with NAFLD in up to 60% of individuals in a Chinese cohort. Moreover, the transfer of clinically isolated HiAlc-Kpn from the patients to the mice by oral gavage induced NAFLD, suggesting that a high level of ethanol-producing bacterial strains in the gut microbiota contributes to NAFLD development, even without alcohol consumption 304 . Overall, the NAFLD pathogenesis consisting of multiple factors with a prominent role of local or systemic inflammation mediated by the immune system (Figure 8).

Impact of immune cells on health and non-alcoholic fatty liver diseases in Liver

As reported, the liver is a unique hemodynamic tissue in that around 30% of the total blood in the body is passing from hepatic artery and portal vessels through the liver every minute 306 .

The hepatic portal vein provides to a large extent nutrients that represents nearly 80% of the blood flow to the liver, while the hepatic artery represents about 20% of the flow and supplies oxygen-rich blood 307 . Histologically, the hepatic artery, portal vein, and bile ducts are altogether known as, portal triade (Figure 9). Following its entry, the blood flowing through a honeycomb-like network of liver lobules that comprise of hepatocytes surrounded by the liver sinusoidal endothelial cells (LSECs) to be filtered within the sinusoidal lumen. Hepatic sinusoids, which are capillary-like canals that facilitate the blood filtration by slowing down the blood passage and maximizing the interaction with sinusoid-resident cells, including the LSECs, and several immune subsets, predominantly the Kupffer cells 309 . Indeed, the LSECs are the primary cell type involved in filtering process with the existence of the transcellular pores, named fenestrations. The pore size of the fenestrae is approximately 100nm diameter, many of which assembles into groups, known as sieve plates, allowing for the transition of specific molecules 310 . Due to the lack of basal lamina, the LSECs represent a gap, known as the space of Disse, which contains the hepatic stellate cells (HSCs) and further restrict direct interactions between hepatocytes and blood flow 311 . In fact, has been reported that hepatocytes and T lymphocytes stick out some membrane extensions by way of the fenestrae and reach out to each other in physiological settings 312 .

Consequently, the filtered blood drains off from the liver through the hepatic centrilobular vein.

Regulation of hepatic immune responses relies on the innate recognition of damageassociated molecular patterns (DAMPs) and pathogen-associated molecular patterns (PAMPs) as well as to antigen presentation to the adaptive immune cells and involved multiple interactions between hepatocytes, LSECs, HSCs, and liver-resident immune cells, which expressing cognate pattern recognition receptors (PRRs) and secrete modulator cytokines (Figure 10).

e. Invariant Natural Killer T cells

The invariant natural killer T cells (iNKTs) represents 40% of hepatic lymphocytes in mice, but only 3-5% in humans 345 . Survival and maintenance of hepatic iNKTs depend on the IL-7, IL-5, and some transcription factors that include BLIMP1, HOBIT, ID2, and the intracellular adhesion molecule 1 (ICAM1) 346 , 338 . Among these factors, the chemokine receptor CXCR6 revealed to be the most important 347 . At homeostasis, hepatic iNKTs cells randomly patrol within the sinusoidal lumen by a crawling movement, seeking for a potential threat either in a identical way than in blood flow or the opposite, as shown by intravital imaging 348 .

f. Mucosal-associated invariant T cells

Mucosal-associated invariant T cells (MAIT) are a member of the ab T cells and described with their semi-invariant TCR receptors, which contain the invariant Va7. 3).

Structural and Functional Organization of the Nuclear Receptors

Nuclear receptors possess a common structural organization, which comprises five functional domains in their polypeptide backbone (Figure 11A). The first one is the A/B, or the amino (N)terminal domain (NTD) is variable in size and sequence that contains the ligand-independent activation function 1 (AF-1) region, which cooperates with numerous co-regulator proteins based on the cell types and promoter usage 454 . Moreover, the post-translational modifications and the formation of the multiple isoforms takes place in the NTD upon alternative splicing 455 . center of the receptor 462 . The carboxy (C)-terminal domain of the NRs is the most variable one, and their functional properties have not yet been fully understood. NRs often act on the DNA in the form of homodimers or heterodimers with one of the RXRs (RXRa, RXRb or RXRg), which makes them a unique member of the superfamily (Figure 11B). This binary format constitutes a large interaction surface for co-regulator proteins and post-translational modifications. Also, a pair of LBD enhances the ligand specificity as a regulatory mechanism 463 . Nonetheless, some NRs, like RORa, GCNF, and LRH-1 binds as a monomer to the DNA whit the assistance of a C-terminal extension (CTE) sequence in their DBD, which creates supplemental base-specific DNA contacts within the minor groove as a compensatory mechanism to stabilize monomer binding 464 . NRs binds to the multiple DNA response elements that contain one of the following nucleotide sequences, the direct repeats, palindromic repeats, or extended monomeric sites (Figure 11B) 465 .

Nuclear Receptor Signaling: Mechanism of Action

Mechanistically NRs subdivided into four groups as I to IV (Figure 12). The type I NRs contain the steroid receptors (SRs) that are activated by the cholesterol-derived steroid hormone ligands, like estrogens, androgens, and corticoids 466 . In the inactive state, SRs localize at the In the positive regulation of the transcription, NRs recruits the co-activator scaffold proteins to start building of the large protein complexes that include the histone-modifying enzymes, for instance, histone acetyl-transferases (HATs) or histone methyl-transferases (HMTs) (Figure 13A). The histone modifiers support chromatin accessibility by keeping it open for other regulatory proteins 471 . Eventually, the general transcription machinery and RNA polymerase II lead to the transcription of the target genes. Alternatively, repression of the transcription by NRs is accomplished through two distinct mechanisms (Figure 13B). In the first scenario, like in the case of the inactive type II to IV, NRs keep interacting with the co-repressor proteins, which in turn engage the histone deacetylases (HDACs) that tighten the chromatin by contrast with the HATs, resulting in the prevention of the transcription 472 . In the second scenario, NRs bind to negative DNA response elements on the DNA, altering the conformational structure and favoring use of co-repressor to suppress the transcription 473 . In humans 4 (a1 to a4), in mice 2 (a1 and a4), RORa isoforms have been identified 476 .

RORa4 is the predominant isoform that is widely-expressed, whereas RORa1 and RORa4 are consistently expressed in the cerebellum of the mice 477 . In mice, two RORb isoforms (b1 to b2) have been reported in which RORb1 is exclusively expressed in the central nervous system while RORb2 is expressed in the pineal gland and retina 478 . Two RORg isoforms (g1 to g2)

have been found in both human and mouse in which RORg1 is widely-expressed, whereas the RORg2 (RORgt) is restricted to the thymus 479 . Since RORs binds as a monomer to the DNA 480 at the AT-rich sequences that contain the AGGTCA core motif 481 , known as the ROR response elements (RORE), the DBD is the most profoundly conserved between RORs that DBD of the RORb and RORg are 91% and 88% identical to the DBD of RORa, respectively 482 . Considering the importance of the CTE sequences within the DBD for the binding of monomeric NRs, that estimated similarity of the DBD is attributed to the CTE region 483 . Even though all ROR isoforms bind to similar ROREs, however, they display distinct affinities due to the variable N-terminal domain and promoter assembly 484 . REV-ERBa and REV-ERBb, which are transcriptional repressors of the NR superfamily, recognize a cluster of ROREs that leads to suppression of the RORs-induced transcriptional activation of genes by competing with RORs to bind the identical RORE 485 . Indeed, the competition between REV-ERBs and RORs for the RORE generates a regulatory feedback loop to control several notable physiological events, for instance, by modulation of the brain and muscle ARNT-like 1 (BMAL1 or ARNTL) gene expression Rev-erba and RORa regulates the circadian rhythm 486 . LBD of the RORb and RORg exhibit 63% and 58% analogy, respectively, compared to the LBD of the RORa 482 , containing twelve a-helices (H1 to H12). The AF-2 domain in the H12 comprise a completely conserved PLYKELF sequences among the RORs 487 . As reported, the deletion or mutation within the H12 lead to lack of the ROR transactivation property, prompting a dominant-negative ROR phenotype 488 .

Retinoic Acid Receptor-related Orphan Receptor Alpha and Circadian Rhythm

The circadian clock, (biological clock) is a molecular oscillator that enables organisms to adjust their physiology, including their metabolism, to adapt predictable to periodic changes in the environment in response to the rotation of the Earth within 24 hours, which is known as the According to the available data and the circadian expression profiles databases, RORa gene expression is not circadian but displays very weak oscillation compared to the Bmal1 and Reverbs but, in terms of activity, RORa can exhibit circadian rhythmicity 495 . Indeed, the activation of the Bmal1 by RORa is mediated by the transcriptional co-activator PGC1-a in the liver that oscillate rhythmically and PGC-1a-deficient mice display altered circadian rhythm 496 . It has also been reported that the naturally inactivated RORa staggerer mice (see below) exhibit abnormal circadian rhythm with the decreased expressions of the clock genes, including Clock, NPAS2, and Cry1. Nonetheless, Bmal1, Clock, Cry1, and Per2 expressions continue to oscillate with rhythmicity in the fibroblasts of the staggerer mice, suggesting RORa is not necessary for circadian oscillations of the clock genes but regulates their level of expression 497 . The role of RORa as a metabolic regulator and immune modulator were mostly documented by using staggerer mice. However, as mentioned, due to their pleiotropic immune and metabolic abnormalities, this model is not suitable to determine cell-specific contribution of RORa to pathophysiology. Given the well-established function of several myeloid cell subsets, in particular macrophages in the initiation and progression of the metabolic diseases, such as obesity-driven T2D, or NAFLD and due to the wide cell distributions of RORa within the immune system, its potential contribution to both metabolic homeostasis and immunoregulation can only be studied by a cell-specific RORa-targeting strategy. As we indeed hypothesize that its impact on these pathologies, might in part, mediated by a direct action on macrophages. Therefore, we generated a macrophage-specific RORa-deficient mouse model and evaluated its impact on models of obesity, IR, and NASH.

Retinoic

MATERIALS AND METHODS weeks or maintained under chow diet (SAFE, #A04). To induce a NASH-like disease, tenweek-old RORa WT and MKO mice were fed with a choline-deficient, L-amino acid-defined (CDAA) diet with 35% sucrose, 21% fat and 2% cholesterol (Ssniff, custom diet) for 8 weeks.

In addition to CDAA diet, mice also received monosaccharides in the drinking water (42g/L, fructose: glucose ratio of 55:45). Weight of mice was measured weekly. Before sacrifice, mice were fasted for 5 hrs. Mice were sacrificed at ZT3 (10 am) for HFD and at ZT7 (2 pm) for CDAA experiment.

Insulin and glucose tolerance tests

After 10 weeks of HFD, a Glucose Tolerance Test (GTT) was performed by intraperitoneal injection of glucose (1g/kg). Tail blood sample was collected before glucose injection to measure fasting insulin by ELISA (Mercodia #10-1247-10) according to manufacturer instruction. After 11 weeks of HFD, an Insulin Tolerance Test (ITT) was performed by intraperitoneal injection of human insulin (1IU/kg) (Actrapid, Novo Nordisk). Glycemia was measured from tail before and 15, 30, 60, 90 and 120 min after glucose or insulin injection by using a glucose meter (Accu-Check performa, Roche). Before GTT and ITT, mice were fasted for 5h at ZT2 (9 am) and the tests were performed at ZT7 (2 pm).

Bone marrow-derived macrophages

Bone marrow was isolated from tibia and femur of mice. Bone marrow cells were culture in RPMI 1640 with Hepes and L-glutamine supplemented with 10% fetal bovine serum, 20%

L929-conditioned medium and 25 µg/mL gentamycin for one week. After three days of culture, fresh medium was added. After one week of culture, supernatant was discarded and adherent bone marrow-derived macrophages (BMDMs) were washed two times with PBS. BMDMs were collected by using a cell scraper, counted and plated at a concentration of 10 6 cells/ml.

After 24 hours, BMDMs were treated with 100nM dexamethasone (Sigma, #D1756) for 2 hours to synchronize cells, washed and maintained in complete medium for 32 hours to reach the pic of RORa activity corresponding to ZT0 in vivo.

Cell sorting

Mice were sacrificed at ZT0 (7 am) and tissue kept in PBS on ice until processing. For epididymal adipose tissue, between 3 and 4 mice were pooled. Spleen was gently pressed on a 70 µm cell strainer by using a 1 mL syringe plunger. Adipose tissue, liver and lung were minced with scissors and digested in RPMI containing reach an event rate of maximum 10 000 events/sec. In spleen, cells of interest were selected in the following order: T cells (CD45 + CD3e + TCRb + MHC-II -), B cells (CD45 + CD19 + MHC-II + ), Neutrophils (CD45 + CD3e -TCRb -CD19 -CD11b + Ly6G + ), Macrophages (CD45 + CD3e -TCRb - CD19 -Ly6G -F4/80 + ), monocytes (CD45 + CD3e -TCRb -CD19 -Ly6G -F4/80 -CD11b + CD115 + )

and DCs (CD45 + CD3e -TCRb -CD19 -Ly6G -F4/80 -CD115 -CD11c + MHC-II + ). In liver, cells of interest were selected in the following order: T cells (CD45 + CD3e + TCRb + CD19 -CD20 -), B cells (CD45 + CD19 + CD20 + MHC-II + ), Kupffer cells (CD45 + CD3e -TCRb -CD19 -CD20 -F4/80 + Clec4F + ) and other (CD45 + CD3e -TCRb -CD19 -CD20 -F4/80 -Clec4F -). Adipose tissue macrophages were selected as CD45 + CD3e -TCRb -CD19 -CD20 -F4/80 + CD64 + and lung macrophages as CD45 + CD3e -TCRb -CD19 -F4/80 + CD64 + CD11b low SiglecF + .

For bone marrow (BM) neutrophils, BM was first isolated from tibia and femur of mice. Red blood cells were lysed with ammonium chloride-based buffer and BM cells were blocked by using a combination of anti-CD16/CD32 (clone 2.4G2) (BD Biosciences, #553142) and anti-FcγRIV (clone 9E9) (BioLegend, #149502). Cells were incubated with PE rat anti-mouse Ly-6G (Clone 1A8) (BD Biosciences, #551461) for 30 min and purified by magnetic separation with anti-PE MicroBeads (Miltenyi Biotec, #130-048-801) according to the manufacturer's instructions.

Metabolic parameters

Before sacrifice and after 5 hours of fasting, blood samples were collected from the retro orbital sinus of mice. Plasma alanine aminotransferase (ALAT), aspartate aminotransferase (ASAT), total cholesterol and triglycerides were measured on a Konelab 20 (Thermo Fisher) with reagents from Thermo Scientific for ALAT (#981769) and ASAT (#981771) and reagents from DiaSys for cholesterol (#113009910026) and triglycerides (#157109910026). The plasma ALAT and ASAT measurement under CDAA diet was performed without fasting for the time point T0, 2, 4 and 6 weeks.

Measurement of liver triglycerides

Lipids were extracted from the liver caudate lobe. A weighted piece of tissue was homogenized with T10 Ultra-Turrax (Ika) in PBS 1% Triton. Samples were transferred into glass tubes and mixed with a 2:1 chloroform: methanol mixture. After centrifugation, upper-and inter-phase were discarded. The lower organic phase was evaporated under nitrogen flow and reconstituted in 1% Triton X100. Triglyceride content was measured with Triglycerides FS kit (DiaSys, #157109910026).

Histology

The median lobes of liver were collected and fixed in 4% paraformaldehyde for 48 to 72 hrs.

RT-qPCR

Total RNA was extracted from the snap-frozen tissues or sorted cell pellets by using TRIzol reagent (Ambion, #15596018) according to the manufacturer's instructions. DNase treatment was performed (Thermo Scientific, #EN0521) and RNA was reverse-transcribed to complementary DNA (cDNA) by using the high capacity cDNA reverse transcription kit (Applied Biosystems, #4368813). qPCR was performed by using Brilliant II SYBR Green QPCR Master Mix (Agilent, #600828) and ran on a Mx3000P qPCR system (Agilent). Relative changes in mRNA expression (Fold change, FC) were calculated by the 2 -ΔΔCT method. Absolute changes in mRNA expression were calculated with the formula 2 -ΔCT x 100 and expressed as arbitrary unit (AU). The mean of four housekeeping genes (Rplp0, Ppia, Rpl4 and Rps29) was used to normalize mRNA expression. The primers used for qRT-PCR are listed in table 4.

Western blotting

Tissues were weighted and homogenized with a T10 Ultra-Turrax (Ika) in protect buffer (water with cOmplete protease inhibitor cocktail (Roche, #11836145001) and PhosSTOP (Roche, #04906837001)) (3.75 µL/mg for adipose tissue and 7.5 µL/mg for muscle and liver). Next, total protein lysates were mixed with 4X Laemmli buffer (Tris-HCl 250mM pH 6.8, 40% glycerol, 8% SDS, 12% β-mercaptoethanol and bromophenol blue) and heated at 100 o C for 5 min. Total protein extracts were subjected to SDS-PAGE (10% polyacrylamide gel) and transferred on a 0.22 µm nitrocellulose membrane (Li-Cor, #P/N 926-31092). After blocking in 5% BSA, membranes were probed with mouse anti-Akt (Cell Signaling, #2920) and rabbit anti-phospho-Akt (Ser473) (Cell Signaling, #4058) monoclonal antibodies. The secondary antibodies used for the revelation were Alexa Fluor 680 anti-mouse IgG (Jackson ImmunoResearch, #715-625-150) and Alexa Fluor 790 anti-rabbit IgG (Jackson ImmunoResearch, #711-655-152).

Immunoblots were scanned with an Odyssey CLx Imaging System (LI-COR) and quantified with Image studio software (LI-COR).

Statistical analyses

All statistical analyses were carried out using GraphPad Prism 8 for Windows (GraphPad Software) and presented as means ± SEM. The study was done blinded for genotype. Only one mouse (WT) was excluded from the analysis because it did not reach an appropriate weight gain under HFD feeding (Body weight: 31.2 g; ingAT: 0.165 g; epiAT: 0.348 g). No mice were excluded in CDAA diet group. Data were analyzed with 2-way ANOVA and Sidak's multiple comparisons post-hoc test or Student's t-test. Values with P < 0.05 were considered as significant. All statistical details including statistical test used and exact value of n are described in each figure legend. Each data point represents genuine replication, also called true replicate, and were obtained from a single measurement or multiple measurements illustrated by the mean, such as gene expression by RT-qPCR that was assessed in duplicate or histology quantification made on five random fields per mice. For sake of clarity, results of statistical comparisons between WT and MKO mice upon Chow feeding were not illustrated on the figures but were not significant for all the parameters.

Table 4: List of the primers used in mouse genotype and qPCR.

Forward Reverse

Genotyping

Rora (PCR1) CATGCATACACCCACACACATCACAACC CTTGATGCACTGATGTAATAACATATCC Lyz2 CTTGGGCTGCCAGAATTTCTC TTACAGTCGGCCAGGCTGAC Cre CTTGGGCTGCCAGAATTTCTC CCCAGAAATGCCAGATTACG Excision Rora (PCR2) CATGCATACACCCACACACATCACAACC CAGCCGTGTGAAACTTACGGGAAATACC qPCR Rplp0 GGGAAGGTGTAATCAGTCTCCACAG CATGCTGAACATCTCCCCCTTCTCC Ppia GCATACGGGTCCTGGCATCTTGTCC ATGGTGATCTTCTTGCTGGTCTTGC Rpl4 CTGAACCCTTACGCCAAGAC CCTTCTCGGATTTGGTTGCC Rps29 GATCCGCAAATACGGGCTG CCATTCAAGGTCGCTTAGTCC Rora Exon 3 TTCCATGCAAGATCTGTGGAGAC TGCAGCCTTCACACGTAAT Rorb CCCACACCTACGAGGAAATCAA CATGAAGCCTGTTATCCGCTTG Rorc GGTACCATATGCCTCTCTGA ATCTCCCACATTGACTTCCT Lyz2 CAATGTGCAAAGAGGGTGGTG TAGAGGGGAAATCGAGGGAATG Cre CCTGGAAAATGCTTCTGTCCG CAGGGTCTTATAAGCAATCCC Arntl GGACTTCGCCTCTACCTGTTC ACCCGTATTTCCCCGTTC Ob GGTGTGAAAGAACCTGAGCTGAGG CAGTGGATGCTAATGTGCCCTG Tnf AGCACAGAAAGCATGATCCG CCCGAAGTTCAGTAGACAGAAGAG Il1b GCCACCTTTTGACAGTGATGAG CCTGAAGCTCTTGTTGATGTGC Il6 CCAGTTGCCTTCTTGGGACTG CAGGTCTGTTGGGAGTGGTATCC Il10 AGGCGCTGTCATCGATTTCTC TGGCCTTGTAGACACCTTGGTC Col1a1 AGGCATAAAGGGTCATCGTGG GAGACCGTTGAGTCCGTCTTT Col3a1 TGGCAATGTAAAGAAGTCTC CCCAGTGTGTTTAGTACAGC Acta2 GCCGAGATCTCACCGACTAC CAATCTCACGCTCGGCAGTA Cd19 ACCTGACCATCGAGAGGCACGTG CCTGGCGGGGTCAGTCATTCGCTT Cd3e ACTGGAGCAAGAATAGGAAG GGATGGGCTCATAGTCTG Adgre1 CTTTGGCTATGGGCTTCCAGTC GCAAGGAGGACAGAGTTTATCGTG Clec4f CCCAGGACCCTGCGGCACGTC CCGAAGCAGGAGGGAGGGAGGCTC Ly6g TGATGGATTTTGCGTTGCTCTG GTATTGTCCAGAGTAGTGGGGC Ccr2 ATTCTCCACACCCTGTTTCG CATGGCCTGGTCTAAGTGCT
Table 4: List of the primers used in mouse genotyping and qPCR. To achieve RORa deletion in macrophages, the floxed mice were subsequently crossed with the LysM-Cre mice. Rora fl/fl Lyz2 Cre/+ (MKO) mice and their littermate controls Rora +/+ Lyz2 Cre/+ (WT), exhibiting comparable expression of Lyz2 and Cre (Figure 2A), were further studied. To validate and characterize the RORa deletion in MKO mice, we demonstrated the excision of exon 3 in DNA from sorted splenic macrophages (Figure 2B). Since the LysM-Cre mouse model mainly targets macrophages and neutrophils, but also a fraction of monocytes and DCs, we sorted these populations from spleen and quantified the deletion of exon 3 in Rora mRNA by RT-qPCR (Figure 3A). MKO mice displayed an important deletion of exon 3 in macrophages and to a lesser extent in monocytes and DCs, but surprisingly not in neutrophils. No deletion of exon 3 in Rora mRNA was observed in T cells and B cells. To confirm the absence of deletion in neutrophils, we also analyzed the bone marrow (BM) cells, which mainly contain neutrophils. Neither total BM cells nor purified neutrophils from BM showed a deletion of exon 3, while bone marrow-derived macrophages (BMDM) did (Figure 3B). Collectively, our results show that macrophages, monocytes and DCs, but not neutrophils, exhibit a LysM-Cre-induced deletion of Rora exon 3. Rorc expression was not affected by Rora deletion (Figure 4A) and Rorb was undetectable in both WT and MKO immune cells (data not shown), suggesting no compensatory regulation of other ROR genes. The expression of a key ROR target gene Arntl, encoding for BMAL1, was significantly lower in RORa-deficient splenic macrophages and BMDM (Figure 4B-C). A tendency to a lower Arntl expression was also observed in monocytes, but not in DCs, probably due to the high expression of Rorc (Figure 4A). Thus, despite the significant LysM-Cre-induced deletion of exon 3 in monocytes and DCs, MKO mice foremost displayed a phenotype in macrophages. As macrophages display some tissue-specific characteristics, we sorted ATM (CD45 + CD3e - TCRb -CD19 -CD20 -F4/80 + CD64 + ) from epididymal AT to evaluate the efficiency of Rora deletion in these cells. Similar to the splenic macrophages and BMDM, MKO mice showed a significant deletion of exon 3 and a significant decrease of the ROR target gene Arntl in ATM (Figure 5A). No significant deletion of exon 3 occurred in total epididymal AT, liver nor skeletal muscle (Figure 5B), suggesting the absence of an unwanted recombination in parenchymal cells of metabolic tissues.

B. RORa deletion in macrophages does not affect LPS-induced inflammation in vitro

As previous studies have reported super induction of several cytokines, including TNFa, IL-6, and IL1b in isolated LPS-treated RORa-deficient macrophages by using staggerer mice 545,546,528 . Taking into consideration the impact of gut microbiota-derived LPS on metabolic diseases, we first investigated cytokine response upon LPS treatment in wild-type and RORa-deficient bone marrow-derived macrophages (BMDM). We performed a time course stimulation with 50 ng/mL of LPS and analyzed the mRNA expression and secretion of TNFa and IL-6 in supernatant (SN) and observed no statistical differences at any time points between WT and RORa-deficient BMDM (Figure 6A-B). We also treated BMDM for 8 hours with a lower (10 ng/mL) and a higher (100 ng/mL) LPS concentration and observed no differences between genotypes for TNFa and IL-6 (Figure 7A-B). We also measured Il1b gene expression in time course (Figure 8A) and dose-response (Figure 8B) experiments and observed no differences between WT and RORa-deficient BMDM as well. Because LPS treatment alone did not result in a detectable level of mature IL-1b in SN, we treated BMDM with both LPS and aluminum hydroxide, a well-known inflammasome activator leading to maturation and secretion of IL-1b, and detected no difference in IL-1b release in both genotypes (Figure 8C). We confirmed that deletion of Rora (85%, measured by exon 3 deletion) expectedly decreased expression of Arntl (BMAL1, RORa-target gene) by 50% in untreated conditions (Figure 9A-D). Interestingly, we also observed that LPS downregulates Rora and Arntl expression, abolishing the effect of RORa deletion on Arntl after 2-4 hours (Figure 9A). This observation is in agreement with earlier work showing that LPS decreases circadian genes, including Arntl 547 . Thus, it seems reasonable to conclude that a condition leading to a downregulation of Likewise, plasma cholesterol and triglyceride levels were not different between WT and MKO mice (Figure 11). Overall, these findings suggest that RORa deletion in macrophages has no impact on HFD-induced obesity. Fasting serum glucose and insulin concentrations increased significantly upon HFD feeding although no difference between genotypes was observed (Figure 12A-B). Furthermore, we observed no difference in glucose levels between WT and MKO mice during IPGTT and IPITT (Figure 12C-D). Moreover, insulin signaling in skeletal muscle, epididymal AT and liver was similar in both genotypes (Figure 13). Considering AT inflammation is a central driver for obesity-induced IR, no difference in Tnf, Il1b, Il6, and Il10 expression was observed in epididymal AT between WT and MKO mice (Figure 14). Taken together, our results show that RORa deletion in macrophages has no impact on obesity-induced IR. In interconnection with obesity and IR, HFD feeding also induces liver steatosis. Liver weight, hepatic triglyceride content, and steatosis level determined by histology were increased upon HFD feeding to the same extent in WT and MKO mice (Figure 15). Histology analysis did not reveal cell infiltrates upon HFD feeding despite the significantly increased expression of inflammatory genes such as Tnf, Il1b, Il6 and Il10 (Figure 16A).

Likewise, we did not observe any significant differences in hepatic cytokine expression between WT and MKO mice besides a tendency to a lower Il10 expression in MKO mice (p= 0.07). HFD feeding induced a similar mild increase of plasma transaminase activity in both WT and MKO mice (Figure 16B). Liver fibrosis and expression of collagen genes slightly increased upon HFD feeding for 12

weeks at comparable level between WT and MKO mice (Figure 17). Collectively, our results display that RORa deletion in macrophages has no impact on HFD-induced liver steatosis nor fibrosis.

D. RORa deletion in macrophages does not affect NASH

As a generally accepted fact, HFD feeding efficiently promotes obesity and IR, the liver pathology is mainly characterized by triglyceride accumulation corresponding to the NAFL stage. To investigate whether the deletion of RORa in macrophages might play a role in advanced NAFLD, WT and MKO mice were fed with the choline-deficient, L-amino aciddefined (CDAA) diet supplemented with sucrose and 2% cholesterol for 8 weeks, leading to a pronounced hepatic steatosis, inflammation and fibrosis, but dissociated from obesity and IR, allowing the analysis of liver-centric responses. Thus, unlike HFD, the CDAA diet did not induce obesity, hyperglycemia nor AT inflammation, but led to a 10% weight loss and a drop of glycemia of 30% in both WT and MKO (Figure 18). The CDAA diet produced a massive hepatic steatosis, but RORa deletion in macrophages did not impact on liver weight nor steatosis level (Figure 19). Histological analysis showed evidences of cell infiltrates upon CDAA diet feeding but no manifest difference between WT and MKO mice was observed (Figure 20A). Further analysis of the expression of inflammatory genes revealed no difference in Tnf and Il6 expression whereas Il1b and Il10 mRNA significantly decreased in livers of MKO mice (Figure 20B). Despite this modest decrease in cytokine expression, we did not observe any significant differences in plasma transaminase activity at sacrifice (Figure 21) and in the weekly time course measurements, while a strong effect of the CDAA diet was found on these parameters (Figure 22). Hepatic fibrosis and expression of collagen genes greatly increased upon CDAA diet feeding for 8 weeks at comparable level between WT and MKO mice (Figure 23). These results

indicate that deletion of RORa in macrophages does not affect CDAA-induced NASH. Our sorting results revealed efficient and specific deletion of Rora exon 3 in KC (Figure 26A).

Interestingly, we observed that KC expressed lower levels of Rora than other macrophage populations, with lung macrophages expressing the highest level (Figure 26B), similarly to publicly available transcriptomic data (Figure 26C). Despite a significant Rora exon 3 deletion, expression of the ROR target gene Arntl did not decrease in KC, unlike lung macrophages (Figure 27A), splenic macrophages (Figure 4A), BMDM (Figure 4B) and ATM (Figure 5A). The lack of effect of RORa deletion on Arntl expression in KC suggests a compensatory mechanism by another ROR protein. Rorb was not expressed in KC, similarly to other macrophage populations tested (data not shown), but

Rorc expression was detected (Figure 27B). No compensation of Rorc expression was found in any macrophage subsets from MKO mice compared to littermate controls. However, basal

Rorc expression was between 5-and 10-fold higher in KC compared to other macrophage subsets. The low Rora expression and the high Rorc expression in KC led to a Rorc/Rora ratio 10-to 50-fold higher than in other macrophage populations (Figure 27C). Collectively, these results suggest that RORa deficiency is unlikely to induce major transcriptional effect in KC due to a concomitant high RORg expression.

Gene regulation by RORa in alveolar macrophages

Since RORa expression is the highest in alveolar macrophages and deletion achieved is very high (94%), we reasoned that these cells would be the most appropriate to seek for differential gene expression pattern between RORa-proficient and -deficient macrophages. Therefore, we performed a transcriptomic analysis by microarrays on purified RORa-proficient and -deficient alveolar macrophages (Figure 28). Based on the false discovery rate (FDR), only 2 genes (Coro2b and Arntl) were significantly downregulated in RORa-deficient alveolar macrophages, probably due to the modest fold change observed between the 2 genotypes. Thus, selecting on the basis of a p-value of 0.01 rather than on of a FDR of 0.05 and a log2(FC) of 0.5, we identified 200 differentially expressed genes between the RORa-proficient and -deficient alveolar macrophages in basal conditions (Figure 28A). The complete list of the modulated genes can be found in the annex (Supplementary Table-1). Expectedly, Arntl was among the 10 most downregulated genes in RORa-deficient alveolar macrophages (Figure 28B).

Moreover, pathway analysis using Database for Annotation, Visualization, and Integrated Discovery (DAVID) revealed that pathways related to circadian rhythm were significantly Thus, we investigated whether or not Lyz2 copy number affects metabolic parameters independently of RORa expression. Indeed, lysozyme expression and activity is affected in various liver diseases 549,550,551 , but, to our knowledge, the role of Lyz2 in NASH was never investigated. Besides, impact of lysozyme on obesity and obesity-associated IR is unknown.

Presented results are preliminary and need to be confirmed.

A. Generation and validation of Lyz2-deficient mice

We crossed wild-type mice with homozygous Lyz2-Cre mice (wild-type at the RORa locus) to obtain heterozygous (Lyz2 WT/Cre ) mice. Subsequently, we crossed heterozygous Lyz2 WT/Cre mice with each other to obtain wild-type (Lyz2 WT/WT ), heterozygous (Lyz2 WT/Cre ), and Lyz2deficient (Lyz2 Cre/Cre ) littermates. We validated genotypes of the mice by using single PCR reaction with three primers on extracted DNA and agarose gel electrophoresis (Figure 29A-B). Similarly, KO mice displayed lower inguinal and epididymal adipose tissue masses under HFD compared to WT and Het mice (Figure 31). Furthermore, HFD-fed KO mice exhibited significantly better glycemic control during intraperitoneal glucose tolerance (IPGTT) test compared to WT and Het mice. Nevertheless, we observed no significant difference between genotypes in fasting glucose levels at sacrifice (Figure 32). Regarding AT inflammation as a causative factor for obesity-induced IR, expression of Tnf and Adreg1 genes was significantly lower, whereas Il1b expression tended to decrease, and Il6 expression remained unchanged (data not shown) in epididymal AT of KO mice compared to WT and Het mice upon HFD-feeding (Figure 33). Altogether, our results suggest that Lyz2 deficiency has a slightly protective effect against HFD-induced obesity and IR. Considering HFD-induced NAFL development, liver weight, steatosis level determined by histology were increased upon HFD feeding to the same extent regardless of the genotype of the mice (Figure 34). Furthermore, we did not observe any significant differences in hepatic cytokine expression levels but tended to increase in HFD-fed KO mice compared to WT and Het mice (data not shown). Overall, our findings suggest that Lyz2 deficiency has no impact on HFD-induced hepatic steatosis development. B. Lyz2 deficiency might protects against obesity-independent NASH Given the fact that 12 weeks of HFD feeding only induces NAFL, we further investigated the impact of Lyz2 deficiency on an advanced NASH model that is independent from obesity and IR. Thus, wild-type (Lyz2 WT/WT ), heterozygous (Lyz2 WT/Cre ), and Lyz2-deficient (Lyz2 Cre/Cre ) littermates were fed with the choline-deficient, L-amino acid-defined (CDAA) diet supplemented with sucrose and 2% cholesterol for 4 weeks. In contrast to HFD, as expected, CDDA diet feeding induced neither obesity nor hyperglycemia. Instead, as expected, the CDAA diet feeding resulted in a 15% weight loss and a decrease of nearly 40% of fasting glycemia at a similar rate in WT, Het, and KO mice (Figure 35). Accordingly, we also observed a lower subcutaneous and epididymal adipose tissue masses upon the CDDA diet at a comparable level between each genotype (data not shown). Interestingly, our preliminary findings revealed that Lyz2-deficient mice exhibit significantly lower liver weight in comparison with Het mice and almost significantly than WT mice in response to CDAA diet feeding, despite the steatotic appearance of the liver (Figure 36). These results suggest that whole-body Lyz2 deficiency might have a protective effect against NASH development. the susceptibility to HFD-induced NASH 548 , even though both studies adopted the same HFD reference and duration of the procedure. As feeding a HFD for 12 weeks is not per se leading to NASH, but rather to NAFL 552 , only a more pronounced steatosis (higher liver weight and triglyceride content) was reported in MKO mice in the earlier study 548 . Indicators of increased hepatic lipotoxicity, such as higher plasma transaminase activity, increased expression of proinflammatory cytokines (Tnf, Il1b and Il6) and decreased expression of Il10 in liver were also observed 548 . It was proposed that RORa directly regulates M2 polarization of KCs leading to increased IL-10 production which would protect hepatocytes against lipid accumulation 548 .

While we also observed a tendency to lower Il10 expression in livers from MKO mice upon HFD feeding (Figure 16A) and a significant decrease upon CDAA diet feeding (Figure 20B), we did not observe any exacerbation of steatosis or NASH. As the putative protective role for IL-10 was only based on in vitro findings, we believe that the reduced Il10 expression in liver of MKO mice upon HFD is unlikely to contribute to aggravated steatosis. Further supporting this finding, IL-10-deficient mice fed with a HFD for 12 weeks developed increased liver inflammation, but decreased steatosis and transaminase activity 553 , suggesting that beyond its well described anti-inflammatory function, endogenous IL-10 is not protective against HFDinduced steatosis.

Several other factors might account for the discrepancy between our results and these earlier findings 548 . The microbiological status of the animal facility and housing conditions are two underestimated factors that might account for major differences in experimental outcome and it is not uncommon for this information to be missing. Specific pathogen free (SPF) status indicates that mice are free of defined pathogens including the mouse hepatitis virus and

Helicobacter hepaticus, which may interfere with liver function. As we discussed with the sheer volume of evidence, gut microbiota also influences NAFLD development. The microbiota composition is highly variable between animal facilities, mouse lines and even between cages, especially when two genotypes are bred separately. Generation of littermate animals is critical to ensure that both deficient and control mice harbor identical gut microbiota while postweaning cohousing is ineffective 554 . Our mice were housed in SPF facility and bred to obtain WT and MKO littermate animals. Nevertheless, no information was provided in the earlier study about the animal facility and littermate status.

Additionally, used floxed mice strategy may also account for the observed discrepancies between studies. We generated mice with floxed Rora exon 3 while exon 4 was targeted in the earlier study 548 . Deletion of exon may still result in the translation of a truncated protein containing a portion of the DBD that includes the exon 3-encoded zinc finger motif (Figure 1C).

This difference in deletion strategy is however unlikely to account for the observed phenotypic differences, considering the absence of C-terminal extension (CTE) sequence within the DBD domain, that stabilize DNA contact for monomeric nuclear receptors 464 .

By using a 12-week HFD that induces liver steatosis (NAFL) or an 8-week CDAA diet that leads to NASH, we observed no differences between WT and MKO mice for any tested hepatic parameters including liver weight, triglyceride content, inflammatory and fibrosis gene expression, histology and transaminase activity. We also found no impact on obesity and glucose homeostasis. Investigations on KC showed that, despite an effective deletion of to study the specific contribution of macrophage-expressed genes in a specific tissue. Use of dual recombinase Dre-rox system 559 might be useful to further refine cell specificity. In conclusion, RORa deletion in macrophages by using the LysM-Cre system has no impact on the development of obesity, IR and NASH.

Gene regulation by RORa in alveolar macrophages

Our microarray data revealed that coronin 2b (Coro2b) and aryl hydrocarbon nuclear receptor (Arntl) are significantly (p=0.000001 and p=0.000002, respectively) downregulated in RORadeficient alveolar macrophages (Figure 28). Coronins are an evolutionarily conserved family of actin-binding proteins that regulate the actin cytoskeleton dynamics and turnover 560 . The actin cytoskeleton mediates various critical cellular processes, such as cell migration, endocytosis, vesicular trafficking, and cytokinesis therefore, is required for cell survival 561 , 562 .

So far, seven mammalian coronin genes have been identified and classified by the Human

Impact of Lyz2 deficiency on metabolic diseases

As mentioned, we hypothesized that the observed impact of RORa deletion in macrophages on NASH in the earlier study 548 likely did not result from a specific effect of RORa deletion, but rather from a different Lyz2 copy number between WT and MKO mice and decided to verify this hypothesis experimentally. Surprisingly, our preliminary findings showed that the Lyz2deficient mice exhibit slight protection, rather than a detrimental effect, in HFD-induced obesity and IR, as determined by lower body weight and adipose tissue masses, significantly improved glycemic control and decreased epiAT inflammation (Figures 30-33). Interestingly, whole body

Lyz2 deficiency had no impact on hepatic steatosis (NAFL) in HFD-fed mice (Figure 34).

Nonetheless our preliminary findings even suggest that Lyz2 deficiency might protect against advanced NASH (Figure 36). Taken together, these preliminary findings indicate that different Lyz2 gene copy number in control mice is unlikely to account for the discrepancy between our work and the earlier study 548 .

Despite the fact that our preliminary findings in Lyz2-deficient mice do not clarify the discrepancy between our work and the earlier study 548 , we believe that further investigations Subsequently, they identified that ILC2-derived IL13 promotes goblet and Tuft cell differentiation through ILC2-IL13-IL4Ra-Stat6 axis, and accounts for anti-colitogenic protection in Lyz1-deficient 609 . Moreover, authors by using broad-spectrum antibiotic treatment, showed that gut microbiota of Lyz1-deficient mice is required for the type 2 immune phenotype and anti-colitogenic effect 609 . Importantly, authors found no change in luminal bacterial load in cecum or mucosa-associated bacteria in ileum and colon 609 . In line, 16S rRNA amplicon profiling of fecal and ileal content showed unchanged a-diversity (the mean species diversity in habitats at a local scale) between the 2 genotypes 609 . However, by using unweighted UniFrac analysis, which reflects b-diversity (the ratio between regional and local species diversity), they found significant differences between the 2 genotypes in fecal and ileal bacterial composition 609 . They identified that for ileal luminal bacteria an expansion of Ruminococcus gnavus, Blautia gnavus, and Dorea formicigenerans and a reduction of Candidatus Arthromitus in Lyz1-deficient mice 609 . Similarly, for fecal and ileal mucosal bacteria, relative expansion of Dorea formicigenerans and reduction of Candidatus Arthromitus was found, indicating that Lyz1 deficiency alters gut bacterial landscape 609 . Authors next performed fecal microbiota transfer (FMT) using germ-free wild-type recipients to test the anti-inflammatory activity of Lyz1-deficient microbiota in DSS-induced colitis whether transferable or not 609 . Interestingly, they found that Lyz1-deficient-FMT mice exhibit an exacerbated colitis, loss of 20% of body weight, and a 20% mortality at the end of the study 609 . The authors suggested that transfer of Lyz1-deficient microbiota to lysozyme-sufficient recipients exacerbated colitis likely through enhanced bacterial processing by host lysozyme 609 . Thus, they concluded that transfer of Lyz1-deficient microbiota to lysozyme-sufficient recipients did not transfer the protection 609 .

Taken together, authors concluded that Paneth cells possibly monitor and regulate the intestinal type 1 immunity via lysozyme, while goblet and Tuft cells are regulated by type 2 immunity 609 . Thus, the Th1-Paneth cell axis is balanced by goblet-tuft-Th2 circuit to maintain gut homeostasis 609 . The authors also proposed that such interplay between host lysozyme and microbiota might also exist in Lyz2-deficient mice 609 . In agreement with earlier published report that compare muramidase and bacterial killing activity of the lysozyme M and lysozyme P 596 , the authors suggested that myeloid lysozyme M might mediate direct bacterial killing to prevent infection spreading, while luminal lysozyme P, with an intact barrier, might primarily process bacterial cell-wall to alert the immune system 609 .

Moreover, lysozyme improves the anti-oxidant capacity of hepatocytes in vitro and in vivo, leading to a protection against oxidative stress in liver 608 . Given the impact of intestinal permeability and dysbiosis on metabolic diseases and the anti-microbial activity of the lysozyme M, we suspected that its potential protection upon HFD, might in part, be mediated by a direct action on intestinal microbiota and/or permeability-derived local and distal inflammation. Thus, we will measure plasmatic endotoxin levels by ELISA of chow diet and HFD-fed wild-type (Lyz2

Introduction

Growth differentiation factor-15 (GDF-15) is a cytokine from the transforming growth factor-beta (TGF-b) superfamily. GDF-15 is positively associated with the development of several diseases including obesity (Dostálová et al., 2009; Vila et al., 2011), type 2 diabetes (T2D) (Bao et al., 2019; Kempf et al., 2012), non-alcoholic steatohepatitis (NASH) (Koo et al., 2018), cardiovascular diseases (Brown et al., 2002) and various cancers (Brown et al., 2003; Koopmann et al., 2004). In the past decades, GDF-15 has been extensively studied in cancer where it is mainly regulated by the transcription factor p53 and plays roles in apoptosis, proliferation, invasion, angiogenesis, metastasis, drug resistance and anorexia/cachexia (Johnen et al., 2007; Osada et al., 2007; Tsai et al., 2018). More recently, a growing interest about its role in metabolic diseases has emerged, particularly in obesity and T2D. Indeed, similar to its role on cancer-induced anorexia (Johnen et al., 2007), GDF-15 also regulates food intake in obesity models. Transgenic mice overexpressing Gdf15 or mice injected with recombinant GDF-15 are protected against obesity and insulin resistance (IR) (Chrysovergis et al., 2014; Chung et al., 2017; Emmerson et al., 2017; Jung et al., 2018; Macia et al., 2012; Mullican et al., 2017). On the contrary, Gdf15-deficient mice are prone to obesity and IR (Tran et al., 2018).

Glial-derived neurotrophic factor receptor alpha-like (GFRAL) was recently identified as the GDF-15 receptor (Emmerson et al., 2017; Hsu et al., 2017; Mullican et al., 2017; Yang et al., 2017). The discovery of GFRAL and its highly restricted expression within the brainstem area postrema and the nucleus tractus solitaries (Emmerson et al., 2017; Hsu et al., 2017; Mullican et al., 2017; Yang et al., 2017) confirm earlier findings showing that GDF-15 activates neurons in these regions controlling food intake (Johnen et al., 2007; Tsai et al., 2014). Similar to Gdf15 deficient mice, mice lacking 15 in obesity and T2D, little is known about the regulation of GDF15 in macrophages in metabolic diseases.

One major regulator of GDF-15 in myocytes, hepatocytes and cancer cells is the endoplasmic reticulum (ER) stress (Chung et al., 2017; Li et al., 2018; Patel et al., 2019; Yang et al., 2010). Importantly, ER stress is also involved in the development of obesity and T2D and occurs in liver, pancreas and adipose tissue (Boden et al., 2008; Laybutt et al., 2007; Ozcan et al., 2004). Accumulation of misfolded proteins in ER lumen, referred as ER stress, occurs when the protein-folding machinery is overwhelmed (Walter and Ron, 2011). It may result from an increase of protein synthesis, a defect in post-translational modification, an impairment of protein degradation, an alteration in ER calcium concentration or a lipid bilayer stress. ER stress triggers a cellular response, called the unfolded protein response (UPR), to restore ER homeostasis or to induce cell death if the stress is chronic or substantial.

Initiation of the UPR arises from the detection of misfolded proteins accumulation through three sensor proteins, inositol-requiring enzyme 1a (IRE1a), PKR-like ER kinase (PERK) and activating transcription factor 6 (ATF6), that ultimately activate signaling cascades (Walter and Ron, 2011). Among the signaling pathways activated by the UPR, the integrated stress response (ISR) is highly important in ER stress resolution. ISR is initiated following the phosphorylation of the eukaryotic initiation factor 2 alpha (eIF2α) by PERK. Phosphorylation of eIF2α regulates eIF2 complex activity and leads to a global decrease of mRNAs translation. Paradoxically, ISR increases the translation and expression of some mRNAs such as those encoding the transcription factors ATF4, ATF3 and CHOP. Together, these transcription factors regulate the expression of various genes critical to resolve ER stress. Interestingly, ISR and the transcription factor CHOP contribute to obesity and IR (Han et al., 2013;

Materials and Methods

Preparation of FFA solutions

FFA solutions were prepared as previously described (L'homme et al., 2013). In summary, C16:0 (Sigma, #P0500), C16:1 (Sigma, #P9417), C18:0 (Sigma, #S4751), C18:1 (Sigma, #O1008) and C18:2 (Sigma, #L1376) were first dissolved in NaOH and then complexed with fatty acid free, low endotoxin BSA (Sigma, #A8806) at a FFA:BSA molar ratio of 3.4:1.

Cell culture and treatments

Peripheral blood mononuclear cells (PBMCs) were purified by single step density gradient centrifugation with Ficoll-Paque PLUS (GE Healthcare) from buffy coat obtained from healthy donors after informed consent (Croix Rouge de Belgique and Etablissement Francais du Sang). Monocytes were isolated from PBMCs using CD14 MicroBeads (Miltenyi Biotec) according to the manufacturer's instructions. Monocytederived macrophages (MDMs) were generated by culturing freshly isolated monocytes in RPMI 1640 (Lonza) with 20% heat-inactivated FBS (Gibco), 100 IU/mL penicillin (Lonza), 100 IU/mL streptomycin (Lonza) and 100 ng/mL of human M-CSF premium grade (Miltenyi Biotec) for 7 days at 37°C under 5% CO2 atmosphere before stimulation.

The THP-1 monocytic cell line (ATCC) were maintained between 0.5 and 2.0 × 10 6 cells/ml in RPMI 1640 (Lonza) supplemented with 10% heat-inactivated FBS (Gibco) and 25 µg/mL gentamycin (Gibco) at 37°C under 5% CO2 atmosphere. THP-1 cells were differentiated into macrophage-like cells with 100 ng/ml of PMA (Sigma, #P8139)

for 24 h, washed with PBS, and kept resting for one night in fresh supplemented medium before stimulation. CHOP and ATF3 siRNAs were transfected in PMA-differentiated THP-1 cells for 8 hours before FFAs treatment.

Cell viability assay

Cell proliferation reagent WST-1 (Roche Applied Science #05015944001) was used to assess cell proliferation, viability and toxicity according to the manufacturer's instructions. 1.5 x 10 5 THP-1 cells were differentiated with PMA in 96-well plate followed by treatment for 16 hours before addition of WST-1 reagent.

Luminex assay

GDF-15 was measured in culture supernatants from MDMs by Luminex assay (R&D Systems) according to manufacturer's instructions. Beads were read on a Bio-Plex 200 system (Bio-Rad) or on a Bio-Plex MAGPIX system (Bio-Rad).

RT-qPCR

Total RNAs were extracted with high pure RNA isolation kit (Roche Applied Science)

or TRIzol reagent (Ambion) according to the manufacturer's recommendations. DNase treatment was performed on column for RNA isolation kit or after resuspension of RNA pellet for TRIzol extraction by using DNase I (Thermo Scientific, #EN0521). Purified

RNAs were reverse-transcribed to complementary DNA (cDNA) by using the high capacity cDNA reverse transcription kit (Applied Biosystems, #4368813). qPCR was performed by using Brilliant II SYBR Green QPCR Master Mix (Agilent, #600828) and ran on a Mx3000P qPCR system (Agilent) or on a LightCycler 480 (Roche Applied Science). Gene expressions were calculated using the 2 -DDCT method. OAZ1, a highly stable gene in human (de Jonge et al., 2007), was chosen as housekeeping gene.

Primer sequences are provided in supplementary table 1.

Western blot

Cells were lysed in total phospho lysis buffer (62.5 mM Tris-HCl at pH 6.8, 10% glycerol, 2% SDS, 3% β-mercaptoethanol, 0.03% bromophenol blue, 1 mM DTT, 1 mM sodium orthovanadate, 25 mM β-glycerophosphate, 15 mM sodium fluoride, 1 mM PMSF, and complete protease inhibitor cocktail) and subjected to SDS-PAGE. The following primary antibodies were used: anti-phospho-eIF2a (Cell Signaling #9721), anti-eIF2a (Cell Signaling #9722), anti-CHOP (Santa Cruz #sc-575), anti-HSP90

  INTRODUCTION .............................................................................................................................................. 1 1. OBESITY ..................................................................................................................................................... 1 Obesity and Type 2 Diabetes ........................................................................................................... 2 a. Classification of diabetes and type 2 diabetes ............................................................................... 2 b. Insulin Receptor Signaling .............................................................................................................. 3 c. Classification of adipose tissue ....................................................................................................... 4 d. Obesity and Type 2 Diabetes ......................................................................................................... 6 1.2 Obesity, Metaflammation and Insulin Resistance ............................................................................................ 6 a. Crosstalk between white adipose tissue and resident immune cells in obesity ............................ 6 b. Mechanisms of insulin resistance .................................................................................................. 8 1.3 Role of Gut Microbiota in Obesity ............................................................................................................. 10 1.4 Impact of Immune Cells on Health and Obesity in White Adipose Tissue ............................................ 11 1.4.1 Immune cells at homeostasis in white adipose tissue ................................................................. 12 a. Monocytes ................................................................................................................................... 12 b. Macrophages ............................................................................................................................... 12 c. Dendritic cells ............................................................................................................................... 14 d. Eosinophils ................................................................................................................................... 15 e. Type 2 Innate Lymphoid Cells ...................................................................................................... 16 f. CD4 + T cells .................................................................................................................................... 16 g. Regulatory T cells ......................................................................................................................... 17 h. gdT cells ........................................................................................................................................ 17 i. Natural Killer T cells ....................................................................................................................... 18 j. B cells ............................................................................................................................................ 18 Immune drivers of inflammation in obese white adipose tissue ............................................ 19 a. Adipose tissue macrophages, recruited monocytes and macrophages ....................................... 19 b. Dendritic cells ............................................................................................................................... 21 c. Neutrophils ................................................................................................................................... 21 d. Mast cells ..................................................................................................................................... 23 e. Type 1 Innate Lymphoid Cells and Natural Killer Cells ................................................................ 23 f. Invariant Natural Killer T cells ....................................................................................................... 24 g. CD4 + T cells ................................................................................................................................... 24 h. CD8 + T cells ................................................................................................................................... 25 i. B cells ............................................................................................................................................ 25 2. NON-ALCOHOLIC FATTY LIVER DISEASES ................................................................................................ 26 Pathogenesis of obesity-dependent non-alcoholic fatty liver diseases ......................................... 27 2.2 Pathogenesis of obesity-independent non-alcoholic fatty liver diseases ....................................................... 29 2.3 Role of gut microbiota in non-alcoholic fatty liver diseases ...................................................................... 30 2.4 Impact of immune cells on health and non-alcoholic fatty liver diseases in Liver ............................... 33 2.4.1 Immune guardians of homeostasis in liver ................................................................................... 35 a. Kupffer cells .................................................................................................................................. 35 b. Dendritic Cells .............................................................................................................................. 36 c. Natural Killer Cells ........................................................................................................................ 37 d. gdT cells ........................................................................................................................................ 37 e. Invariant Natural Killer T cells ...................................................................................................... 37 f. Mucosal-associated invariant T cells ............................................................................................. 38 g. Regulatory T cells ......................................................................................................................... 38 h. CD8 + Memory T cells .................................................................................................................... 39 i. B cells ............................................................................................................................................ 39 Immune drivers of inflammation in Non-Alcoholic Fatty Liver Diseases ................................ 39 a. Kupffer Cells, recruited monocytes, and macrophages ............................................................... 39 vii b. Dendritic Cells .............................................................................................................................. 42 c. Neutrophils ................................................................................................................................... 44 d. Natural Killer Cells ........................................................................................................................ 44 e. Natural Killer T cells ...................................................................................................................... 45 f. CD4 + T cells .................................................................................................................................... 45 g. CD8 + cytotoxic T cells ................................................................................................................... 46 h. B cells ........................................................................................................................................... 47 3.

FIGURE 1 :

 1 FIGURE 1: IMPAIRED ENERGY BALANCE IN OBESITY. ............................................................................................. FIGURE 2: INSULIN'S ACTION IN METABOLIC TISSUES AND INSULIN SIGNALING PATHWAY .................................... FIGURE 3: COMPARISON BETWEEN HUMAN AND RODENT WHITE ADIPOSE TISSUE (WAT) DEPOTS. .................... FIGURE 4: WAT-RESIDENT IMMUNE CELLS IN LEAN AND OBESE INDIVIDUALS. ..................................................... FIGURE 5:INSULIN SIGNALING PATHWAY IN INSULIN RESISTANCE. ....................................................................... FIGURE 6: SIGNALING CROSSTALK IN HEALTHY AND OBESE WAT BY IMMUNE CELLS. ....................................... FIGURE 7: WAT-LIVER CROSSTALK IN THE PATHOGENESIS OF OBESITY-DEPENDENT NAFLD. ........................ FIGURE 8: OVERVIEW OF THE NAFLD PATHOGENESIS. ...................................................................................... FIGURE 9: HEPATIC IMMUNE AND STROMAL CELLS. ............................................................................................. FIGURE 10: CROSSTALK BETWEEN HEPATIC STROMAL AND IMMUNE CELLS IN NAFLD. .................................... FIGURE 11: SCHEMATIC REPRESENTATION OF THE NUCLEAR RECEPTOR DOMAIN ORGANIZATION, OLIGOMERIC COMPLEXES OF THE NUCLEAR RECEPTORS AND DNA RESPONSE ELEMEN REPERTOIRES. ...................... FIGURE 12: SCHEMATIC OF THE NUCLEAR RECEPTOR SIGNALING MECHANISMS. ............................................... FIGURE 13: MODULATION OF THE GENE EXPRESSION BY NUCLEAR RECEPTORS. .............................................. FIGURE 14: SCHEMATIC REPRESENTATION OF THE ROR FAMILY MEMBERS. ..................................................... FIGURE 15: REGULATION OF THE CIRCADIAN RHYTHM AT MOLECULAR LEVEL. ...................................................

TABLE 1 :

 1 CLASSIFICATION OF THE DIABETES. ........................................................................................................ TABLE 2: CRITERIA FOR THE DIAGNOSIS OF DIABETES. ......................................................................................... TABLE 3: CLASSIFICATION OF HUMAN NUCLEAR RECEPTOR SUPER FAMILY. ...................................................... TABLE 4: LIST OF THE PRIMERS USED IN MOUSE GENOTYPE AND QPCR. ........................................................... TABLE 5: LIST OF THE ANTIBODIES USED IN CELL SORTING. ................................................................................ SUPPLEMENTARY TABLE 1: LIST OF THE MODULATED GENES FROM MICROARRAYS PERFORMED ON ALVEOLAR MACROPHAGES ...................................................................................................................................................

Figure 1 :

 1 Figure 1: Impaired energy balance in obesity. Negative energy balance in obesity arising from genetic factors, high calorie intake and sedentary lifestyle. Management of the energy balance one of the best strategies to prevent obesity and associated complications.

Figure 1 :

 1 Figure 1: Impaired energy balance in obesity.

  of the IR in the target tissue that include adipose tissue, liver, and skeletal muscle, stimulating tyrosine kinase activity. Tyrosine phosphorylation leads to the recruitment of the downstream members of insulin receptor substrate family (IRS, referred to as IRS-1 through IRS-6). This results in recruitment and activation of the phosphoinositide-3-kinase (PI3K), which rapidly phosphorylates phosphatidylinositol-4,5-biphosphate (PIP2) to generate second lipid messenger phosphatidylinositol-3,4,5-triphosphate (PIP3) on the plasma membrane, that activate and translocate the cytosolic serine/threonine kinase AKT, also known as the protein kinase B (PKB) to the plasma membrane, triggering glucose import into the adipose tissue and skeletal muscle or liver by Glucose Transporter Type 4 (GLUT4) or GLUT2, respectively 10 .

Figure 2 :

 2 Figure 2: Insulin's action in metabolic tissues and Insulin Signaling Pathway

Figure 2 :

 2 Figure 2: Insulin's action and Insulin Signaling Pathway. (A) Insulin's action on the white adipose tissue, liver, and skeletal muscle metabolism. (B) The insulin receptor signaling pathway. IRS, Insulin receptor substrate; PI3K, Phosphoinositide 3-kinase; PIP2, Phosptidylinositol-4,5-biphosphate; PIP3, Phosphotidylinositol-3,4,5-triphosphate; AKT/PKB, Protein kinase B; PDK1, Phosphoinositidedependent kinase 1; mTORC1, mammalian target of rapamycin complex 1; mTORC2, mammalian

Figure 3 :

 3 Figure 3: Comparison between human and rodent white adipose tissue depots. White Adipose Tissues (WAT) are mostly visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Major visceral depots common in both humans and rodents include epicardial/pericardial (not shown), perirenal (prWAT), retroperitoneal (rWAT), and mesenteric WAT (mWAT). While humans have large omental (oWAT) fat, mice have large perigonadal (pgWAT) fat. SAT in humans can be divided into upper (abdominal) and lower (gluteofemoral). Abdominal fat in human can be further divided into superficialand deep, which are separated anatomically by Scarpa's Fascia. In mice, SAT is divided into anterior and posterior. Dermal WAT (dWAT) is another fat depot that exists in both humans and mice. dWAT is located in the dermis and above the SAT (note: this separation is visible by the presence of striated muscular layer known as panniculus carnosus only found in mice). Bone marrow adipose tissue (BMAT or MAT) is also another adipose depot common in both species. Cephalad and caudad are also referred to as anterior and posterior in mice, respectively[START_REF] Luong | Deciphering White Adipose Tissue Heterogeneity[END_REF] .

Figure 3 :

 3 Figure 3: Comparison between human and rodent white adipose tissue (WAT) depots.

Figure 4 :

 4 Figure 4: WAT-resident immune cells in lean and obese individuals. In lean adipose tissue, the crosstalk between adipocytes and resident immune cells maintains tissue homeostasis that include M2-like macrophages, eosinophils, Tregs, Th2 cells (see section 1.4). Obesity leads to the expansion of WAT, resulting secretion of chemoattractants and infiltration of pro-inflammatory immune cells (see section 1.4). Therefore, dysregulated production of adipokines and pro-inflammatory cytokines, like TNFa, IL-

Figure 4 :

 4 Figure 4: WAT-resident immune cells in lean and obese individuals.

Figure 5 :

 5 Figure 5:Insulin Signaling Pathway in insulin resistance.

Figure 5 :

 5 Figure 5: Insulin Signaling Pathway in insulin resistance. (A) Underlying mechanisms of the insulin resistance. (B) Representative suppressors of the insulin signaling pathway that causing insulin resistance. IRS: Insulin receptor substrate, PI3K: Phosphoinositide 3-kinase, PIP2: Phosptidylinositol-4,5-biphosphate, PIP3: Phosphotidylinositol-3,4,5-triphosphate, PTEN: Phosphatase and tensin homolog, SHIP2: Src-homology 2-containing inositol phosphatase 2, PKCe: protein kinase C epsilon, JNK: c-Jun N-terminal kinase, IKKb: inhibitor of nuclear kappa-B kinase subunit beta, AKT/PKB: Protein kinase B, mTORC2: mammalian target of rapamycin complex 2, S6K: Ribosomal protein S6 kinase, NF-kB: nuclear factor kappa light chain enhancer of activated B cells, PTP1B: protein tyrosine phosphatase 1B, PP2A: protein phosphatase 2A, PKCz: protein kinase C zetta, PHLPP: pleckstrin homology domain and leucine-rich repeat protein phosphatase.

Figure 6 :

 6 Figure 6: Signaling crosstalk in healthy and obese WAT by immune cells. In lean conditions (left part), AT-resident type 2 immune cells insure tissue homeostasis by secreting type 2 cytokines. gdT cells by immune modulator IL17A and TNFa secretion stimulate preadipocytes/stromal cells to produce IL-33, which activates Tregs and ILC-2. Preadipocytes/stromal cells and ILC-2 directly interact with each other by ICAM-1 and LFA-1, similarly Tregs and ILC-2 interact via ICOS and ICOSL. In turn, Tregs secrete IL-10 and ILC-2 cells IL-4, and IL-13 to support M2-like phenotype of ATM and IL-5 to induce eosinophils.Eosinophils also contribute to IL-4 secretion, supporting M2-like phenotype for ATM. iNKT cells also produce IL-4 and IL-10 type 2 cytokines to sustain M2-like phenotype for ATM. Th2 cells contribute as well to that process by secreting IL-5 and IL-4 cytokines. In obesity (right part), enlarged adipocytes secrete pro-inflammatory cytokines, like TNFa, IL-1b as well as chemokines, such as RANTES and MCP-1 and DAMPs not only to induce phenotypic switch of the resident ATM toward M1-like phenotype but also to recruit neutrophils, monocytes, monocyte-derived macrophages, mast cells, Th1 cells, cytotoxic CD8 + T cells, B cells, ILC-1, and NK cells to the AT, promoting type 1 inflammation. Th1 cells and CD8 + T cells secrete IFNg, IL12, and IL-18, supporting M1-like phenotype of ATM. Mast cells, iNKT

Figure 6 :

 6 Figure 6: Signaling crosstalk in healthy and obese WAT by immune cells.

  . In a recent study,Ghosh et al. evidenced that the chemerin adipokine recruits circulating pDCs into VAT by chemokine-like receptor 1 (CMKLR1), in obese individuals. Moreover, adipose tissue-derived high-mobility group 1 (HMGB1) protein activates TLR9 in the recruited pDCs by transporting extracellular DNA via the receptor for advanced glycation end products (RAGE) and induces production of type 1 interferons (IFNs), further contributing to the pro-inflammatory milieu200 . In line, mice, lacking the receptor for IFNa and deficient in pDCs has been shown to prevent diet-induced obesity and IR 201 .c. NeutrophilsNeutrophils are dominant granulocyte subset in the circulation and the first innate immune cells that respond against pathogens or injury 202 . Initially, half-life of the circulating neutrophils is defined as less than 1 day, however a recent study in humans revealed a lifespan of up to 5.4 days203 . Moreover, lifespan of tissue neutrophils reported to be twice or three times longer than circulating ones204 . Neutrophils originate from HSCs and differentiate into mature neutrophils through CXCL12-CXCR4 signaling in the bone marrow, where approximately 10 7 neutrophils in mice and 10 11 in humans are produced every day205 . Indeed, a recent study by using multi-parametric analysis (lineage commitment, and transcriptional profile) evidenced three distinct neutrophil subsets in the bone marrow, the pre-neutrophil subset, which is a proliferative precursor, differentiating into the non-proliferative immature and the mature neutrophils, in mice and humans206 . Following the maturation, neutrophils exit from the bone marrow and, under homeostasis, mobilize into the circulation via CXCR2, patrolling the organism for any sings of infection or injury 207 . Upon infection, neutrophils anti-microbial activity relies on four main mechanisms, which are phagocytosis, release of reactive oxygen species as well as cytotoxic granule components, like myeloperoxidase, cathepsins, bdefensins lysozyme M, and nuclear material in the form of neutrophil extracellular traps (NET)208 . The granules of the neutrophils classified as azurophilic (primary), specific (secondary), and gelatinase (tertiary) granule, facilitating pathogen destruction209 . NET are the neutrophilspecific structures that contains chromatin, mitochondrial DNA, granule-derived anti-microbial peptides, and enzymes, ejecting it into the extracellular space to trap and kill pathogens, as well as prime other immune cells to induce inflammatory immune response 210 .Neutrophils have been reported to infiltrate into the AT early, roughly a week later, and further increase over the course of HFD feeding 211 . One of the key regulators of inflammation, cytosolic phospholipase A2a, is required for such a fast neutrophil recruitment (roughly a week after HFD feeding)212 . Moreover, the deletion of neutrophil elastase in mice prevent HFDinduced obesity and IR by decreasing macrophage and neutrophil content of AT and limiting tissue inflammation 213 . On the other hand, neutrophil myeloperoxidase regulates HFD-induced obesity and IR in mice by modulating macrophage infiltration 214 . Furthermore, Kawanishi et al. described that exercise training attenuates neutrophil infiltration and elastase expression in AT of HFD-induced obese mice 215 . Interestingly, chemical inhibition of NET release by the peptidyl arginine deiminase 4 inhibitor Cl-amidine in HFD-fed obese mice fails to reduce AT inflammation 216 . On the other hand, Revelo et al. show that HFD feeding in mice stimulates the release of NET and autoantibody formation against nucleic acid-related antigens in VAT, and decrease systemic clearance of NET. In line, they also show that TLR7 and TLR9-deficient HFD-fed obese mice display reduced metabolic inflammation and improved glucose homeostasis. Moreover, inhibitors of the NET formation or a TLR7/9 antagonist decrease HFD-induced obesity in mice 217 . Clinical trials have also shown that the numbers of activated neutrophils is increased in obese individuals, as determined by increased ROS production 218 , 219 . Interestingly, Hagman et al. reported that following bariatric surgery in humans, metabolic improvements occur without significant reduction of AT inflammation neutrophils, and macrophages numbers were even increased 220 . A recent study indicated that severe obesity is associated with increased production of NET, in humans. Furthermore, they also showed that weight loss after bariatric surgery is not restore dysregulated NET generation, suggesting that patients with persistent NET accumulation following bariatric surgery are at the highest risk of cardiovascular events 221 . d. Mast cells Even though the role of mast cells mainly associated with allergic responses, Liu et al. reported that mast cell numbers in WAT increased with obesity in both mice and humans 222 . Moreover, genetic or pharmacological depletion of mast cells improves metabolic outcomes of Western style-diet feeding in mice. Mast cells contribute to WAT and muscle angiogenesis, angiogenesis-related cell apoptosis, and cathepsin activity by producing IL-6 and IFNg in mice, thereby promoting diet-induced obesity and glucose intolerance 222 . Takana et al. showed that mast cell-derived 15-deoxy-delta-12,14-prostaglandin-J2 is an alternative modulator of the adipogenesis through PPARg activation 223 . It has also been shown that mast cells regulate preadipocyte to adipocyte differentiation in both obese and non-obese mice 224 . Moreover, Hirai et al. showed that immature mast cells infiltrate into lean AT and gradually mature with the progression of obesity. Following maturation, mast cells secrete mast-cell protease-6 (MCP-6) that induces AT fibrosis through stimulation of collagen-V expression, leading to the acceleration of IR by the suppression of preadipocyte differentiation in genetically obese and diabetic db/db mice 225 . These findings further confirmed in C57Bl/6 mice by using pharmacological mast cell stabilizers the sodium cromoglicate sodium liposomes (DSCGs) 226 . 227 . In line, Zhou et al. reported that WAT-resident mast cells in lean humans as well as mice are leptin-deficient which promote M2-like macrophage polarization, while WAT-resident mast cells in obese conditions are leptin sufficient, thus reconstitution of leptin-deficient mast cells mitigates obesity and IR in mice 228 e. Type 1 Innate Lymphoid Cells and Natural Killer Cells Murine T-bet + , NK1.1 + , and NKp46 + type 1 innate lymphoid cell (ILC1) population that produce high amounts of the immunoregulatory cytokine IFNg upon activation. ILC1s are divided into three subsets, which are immature natural killer cells (iNKs), mature natural killer cells (mNKs), and mixed/heterogenous ILC1s 229 . A recent study revealed that mNKs are circulating, while mixed ILC1s and iNKs are AT-resident in both mice and humans, furthermore a subset of AT-resident ILC1s has ATM-killing activity and maintain ATM homeostasis at steady-state 230 . Furthermore, circulating ILC1s infiltrate into AT, promoting pro-inflammatory macrophages, and the AT-resident ILC1 subset loses the ability to kill ATMs 230 . O-Sullivan et al. discovered that diet-induced obesity drive early production of IL-12 in AT, leading to the selective proliferation and accumulation of T-bet + Nfil3 + AT-resident ILC1s in an IL-12R and STAT4dependent manner 231 . Furthermore, they also indicated that ILC1s-derived IFNg mediates proinflammatory macrophage polarization to promote obesity-associated IR 231 . In earlier study, NKp46-deficient mice, considered as lacking NK cells, displayed reduced recruitment of macrophages into AT and improved systemic insulin sensitivity 232 . Wensveen et al. found that obesity stimulates the ligands of the NK cell-activating receptor (NCR1) in adipocytes and leads to the proliferation of NK cells. In turn, increased NK cell numbers triggered the recruitment of pro-inflammatory macrophages and prompted IR. Eventually, NK cell ablation by using the NCR1-deficient mouse model prevented the accumulation of pro-inflammatory macrophages in VAT and improved glucose homeostasis 233 . Recently, Theurich et al. identified an IL-6/STAT3-dependent distinct, obesity-associated NK cell subpopulation, which defined as myeloid-signature NK cells by the authors that regulate energy and glucose homeostasis in mice 234 . f. Invariant Natural Killer T cells As mentioned, iNKTs mediate AT homeostasis at steady-state, Lynch et al. reported that their quantities significantly decrease in WAT of obese mice and the omentum of obese individuals 173 . The depletion of iNKTs via CD1d-deficient and Ja18-deficient mice models does not protect against metabolic abnormalities induced by either HFD feeding or choline-deficient diet feeding on two independent studies 235 , 236 . On the other hand, Schipper et al. revealed that CD1ddeficient mice fed a low-fat diet exhibit a distinctive insulin resistance phenotype without overt AT inflammation 237 . Moreover, Ji et al. stimulated iNKTs by a-galactosyl ceramide in HFDinduced obese CD1d-deficient mice and showed that iNKTs enhanced alternative macrophage polarization in AT and improves glucose homeostasis by IL-4/STAT6 signaling axis at different stages of HFD feeding, precisely at 4 days, 8 and 24 weeks 238 . g. CD4 + T cells CD4 + T cell populations increase in WAT of mice as well as humans in response to adiposederived chemokine, RANTES or CCL5, which also contribute to macrophage recruitment 239 . Th1 subpopulation and one of the pro-inflammatory Th1 cytokine IFNg reported to enriched in WAT of obese mice. Accordingly, IFNg-deficient obese mice displayed improved metabolic phenotype, suggesting IFNg regulates AT inflammation 240 . Another study showed that reducing the number of the Th1 cell subset reversed the IR phenotype even if HFD feeding maintained in mice 160 . Furthermore, McGillicuddy et al. revealed that IFNg attenuates insulin signaling, lipid storage, and differentiation in human adipocytes by stimulating JAK/STAT pathway 241 . Th17 cells produce IL-17 are involve in the several pathophysiology of inflammatory diseases and are regulated by the transcription factor RORgt 242 . Nevertheless, the role of Th17 cells in obese AT and related outcomes has not been extensively studied. IL-17 seems to have opposite effects on various cell types. According to Winer et al., in mice HFD induces Th17 accumulation within SAT and spleen in an IL-6-dependent manner, whereas their numbers in VAT decreases 243 . Moreover, Shin et al. reported that IL-17 inhibits adipocyte differentiation in human mesenchymal stem cells and regulates pro-inflammatory responses in adipocytes 244 . Similarly, IL-17 suppressed adipocyte differentiation of mouse 3T3-L1 preadipocytes and impaired glucose homeostasis in differentiated mature 3T3-L1 adipocytes 245 . In the same study, IL-17-deficient mice also displayed enhanced fat mass, upon HFD feeding and even upon feeding a low-fat diet result in altered glucose homeostasis 245 . h. CD8 + T cells CD8 + T cell number increases in eWAT of HFD-fed mice and these cells are infiltrating into AT before macrophages, likewise contributing to macrophage recruitment. In line, CD8 + T cell depletion decreases macrophage infiltration, AT inflammation, and glucose sensitivity 246 . Moreover, CD11a, so-called integrin alpha L or ITGAL, participates in AT inflammation by facilitating CD8 + T cell infiltration and activation 247 . i. B cells B cells accumulate in VAT of diet-induced obese mice and impair glucose metabolism by the activation of pro-inflammatory macrophages, T cells, and production of pathogenic IgG antibodies (253), 249 . Furthermore, Winer et al. showed that B cell depletion via anti-CD20 antibody treatment attenuates obesity-associated complications, while IgG transfer from obese mice to lean mice rapidly induce insulin resistance and glucose intolerance 248 . Additionally, they found that insulin resistance in obese individuals associated with a unique profile of IgG autoantibodies 248 . Moreover, Kim et al. revealed that the adipocyte-derived B-cell-activating factor (BAFF) is a pro-inflammatory adipokine and regulates adipose tissue distribution and systemic inflammation in obesity 250 .Furthermore, B2 subset within the AT promotes obesity-induced IR through leukotriene LBT4/LBT4R1 signaling in mice 251 . In addition, activation of the IgG receptor FcgRIIB in endothelium by hypo-sialylated IgG has been reported to stimulate obesity-induced insulin resistance in mice 252 . Subsequently, Frasca et al. identified and characterized AT-derived IgG antibodies with self-specificity in the plasma of obese individuals 253 .

  Non-alcoholic fatty liver diseases (NAFLD) comprise a spectrum of liver complications in individuals exclusive of significant alcohol consumption ranging from non or benign inflammatory, isolated, simple steatosis, also called Non-alcoholic fatty liver (NAFL) to inflammatory non-alcoholic steatohepatitis (NASH). According to the American Gastroenterological Association's clinical practice guideline, the diagnosis of NAFLD based on histology with steatosis that identified by triglyceride accumulation inside the hepatocytes, being the first stage254 . NAFL further evolve into NASH that is characterized by lobular inflammation, hepatocyte ballooning, and potentially accompanied by some degree of fibrosis255 . The predisposition of the fibrosis in NASH might ultimately progress into cirrhosis, which is a leading risk factor for the development of hepatocellular carcinoma (HCC)256 . Pathogenesis of NAFLD is strongly associated with visceral obesity, T2D, and to some features of metabolic syndrome, including insulin resistance, dyslipidemia, and hypertension that are independent from the grade of obesity 257 . The global prevalence of NAFLD is rising dramatically in parallel to obesity, and frequently depending on the ethnicity of the population 258 . Highest prevalence rates are found in the Middle East (32%) and South America (31%), median proportions in Asia (27%), USA (24%), and Europe (23%), whereas the lowest ratio is in Africa (14%)259 .Given the fact that no established pharmacological treatment exists for NAFLD, finding potential candidates to cure or prediction markers for the diagnosis that are the centers of interest by scientists.Pathogenesis of obesity-dependent non-alcoholic fatty liver diseasesCrosstalk between AT and liver is the primary step in the development of obesity-induced NAFLD. As mentioned earlier, in advanced obesity, saturation of WAT storing capacity and enhanced lipolysis leads to excess FFAs load into the circulation. Since the liver is the central tissue for FA metabolism, the elevation of circulating FFA levels leads to excessive influx into the liver through uptake in hepatocytes via several transporters, including fatty acid transport protein 2 (FATP2), FATP5, FA-binding protein (FABP), FA-translocase (CD36), and caveolins260 . FFAs are then esterified into triglyceride (TG) in the liver. Indeed, hepatic TG synthesis is considered as a protective mechanism to prevent lipotoxicity. Besides conversion into hepatic TG, FAs follow several fates in the liver, in which most circumstances they are the primary oxidative fuel that undergoes b-oxidation. Acetyl coenzyme-A (Acetyl-CoA) is the end product of the b-oxidation that support different purposes in the liver261 . First of all, Acetyl-CoA can enter Krebs cycle and produce energy by oxidative phosphorylation (OXPHOS). Secondly, Acetyl-CoA is a substrate for cholesterol biosynthesis that is an active molecule for membrane, steroid hormones, and bile acid synthesis. Lastly, the liver converts unnecessary Acetyl-CoA into ketone bodies released into the circulation to supply energy to extra-hepatic tissues, such as brain, and heart, mainly during prolonged fasting 261 . At homeostasis, daily, the liver regulates substantial amounts of FAs, in response to dietary fat and simple carbohydrate sources, like fructose intake. However, it stores very-low quantities in the form of TG thanks to balanced FAs uptake from the plasma and hepatic de novo synthesis as well as the ratio of FA oxidation and excretion into the circulation by TG-rich very-low-density lipoprotein (VLDL)262 . Nevertheless, this equilibrium is impaired in obesity-driven NAFLD, as a result of the increased hepatic de novo TG synthesis (lipogenesis) due to WAT lipolysis-induced FAs uptake, leading to the initiation of NAFL 263 . Hepatic de novo TG synthesis is catalyzed mainly by two enzymes: Acetyl-CoA carboxylase (ACC) and fatty acid synthase (FAS). These two enzymes are regulated by insulin-dependent sterol regulatory element-binding protein 1C (SREBP-1C) and glucose-dependent carbohydrate-responsive element-binding protein (ChREB) under the control of the Liver X receptor (LXR) 264 . Hyperinsulinemia and hyperglycemia, which are the characteristic symptoms of obesity-associated IR, possibly overstimulate hepatic lipogenesis by the induction of the SREB1c and ChREB regulator enzymes, further contributing to the progression of NAFL. Indeed, an earlier study, using labeled isotypes, revealed that FA composition of the hepatic TG in NAFLD patients, were originating for 60% from WAT lipolysis-induced plasmatic FA uptake, for 25% from de novo TG synthesis, and for 15% from dietary intakes 265 . Recently,Roumans et al. showed that hepatic saturated FA fraction is associated with de novo lipogenesis and hamper hepatic insulin sensitivity in a cross-sectional study 266 . The beta-oxidation of the long-chain fatty acids (LCFAs) takes place in the hepatic mitochondria following the transport and catalysis by carnitine-palmitoyl transferase-1 (CPT1), which is suppressed through insulin and malonyl-CoA, one of the intermediate products of lipogenesis 267 . Moreover, it has been shown that excessive FFAs in the liver are processed by omega-oxidation in a cytochrome P450 4A (CP4A)-dependent manner within the endoplasmic reticulum, which leads to hepatic IR, and apoptosis, contributing to NAFLD 268 . Eventually, the over-accumulation of TGs due to the imbalanced hepatic FA metabolism, stimulates lipotoxicity-induced hepatocellular injury and cell death 269 .Hepatocellular injury accompanied by mitochondrial dysfunction, oxidative and endoplasmic reticulum stresses activates the liver-resident macrophages, known as Kupffer cells (KCs) that stimulates the infiltration of other inflammatory immune cells into the liver by the release of cytokines and chemokines, triggering the transition from NAFL to NASH 270 . Furthermore, the persistence of inflammation and hepatocellular injury activates hepatic stellate cells (HSCs) that produce extracellular matrix (ECM) proteins in response to the transforming growth factor beta (TGF-b) and induce abnormal wound healing response, contributing to hepatic fibrosis (Figure7).

Figure 7 :

 7 Figure 7: WAT-Liver crosstalk in the pathogenesis of obesity-dependent NAFLD. The expansion of adipose tissue in obesity diminishes its ability to store excess energy. Adipocyte dysfunction and IR are increased, leading to lipolysis. Consequently, circulating FFAs and leptin increase, and adiponectin decreases, resulting in intrahepatic fat accumulation (SS), which is further amplified by the high dietary fat and carbohydrates (commonly observed in obesity), the latter increasing de novo lipogenesis. Upon the expansion of adipose tissue, it is also infiltrated by immune cells that produce cytokines and ILs.

Figure 7 :

 7 Figure 7: WAT-Liver crosstalk in the pathogenesis of obesity-dependent NAFLD.

Figure 8 :

 8 Figure 8: Overview of the NAFLD pathogenesis. The main components for the development and progression of the disease are diet, genetics, obesity with adipose tissue expansion and enhanced lipolysis due to IR, resulting in lipotoxicity, mitochondrial dysfunction, production of ROS, ER stress, autophagy, apoptosis, inflammasome activation, release of EVs, and ultimately HSC activation and fibrogenesis. Abbreviations: CCL2/CCL5, C-C motif chemokine ligand 2/5; DAMPs, damage-associated molecular patterns; ER, endoplasmic reticulum; EtOH, ethanol; EVs, extracellular vesicles; FFAs, free fatty acids; FXR, farnesoid X receptor; HCC, hepatocellular carcinoma; HSC, hepatic stellate cell; IL-6, interleukin 6; IR, insulin resistance; JNK, c-Jun N-terminal kinase; LPS, lipopolysaccharide; NAFLD, nonalcoholic fatty liver disease; NF-kB, nuclear factor kappa B; PAMPs, pathogen-associated molecular patterns; PDGF, platelet-derived growth factor; PPAR, peroxisome proliferator-activated receptors; ROS, reactive oxygen species; TGF-b, transforming growth factor beta; TLR4, Toll-like receptor 4; TNFa, tumor necrosis factor a 305 .

Figure 8 :

 8 Figure 8: Overview of the NAFLD pathogenesis.

Figure 9 :

 9 Figure 9: Hepatic immune and stromal cells.

Figure 9 :

 9 Figure 9: Hepatic immune and stromal cells. Schematic representation showing hepatic cells and their location. The liver harbors a large population of immune cells. Dendritic cells (CX3CR1+ cells) can be found in the subcapsular space and surround large vessels, as the centrilobular vein and the portal triade vessels (portal vein and hepatic artery). Kupffer cells are the liver resident macrophages and constitute the largest population of hepatic immune cells. They can be found within sinusoids, in contact with endothelial cells. Neutrophils, B lymphocytes, T lymphocytes, and NK cells eventually circulate in the sinusoids. 308 .

Figure 10 :

 10 Figure 10: Crosstalk between hepatic stromal and immune cells in NAFLD.

  2 chain in general rearranging by either with Ja12, 20, or 33 fragment together with the variable b-chains 349 .Predominantly, MAIT found in the gut lamina propria, but also in liver where they account for 20-50% of the hepatic innate-like T lymphocyte population350 . Activation of the MAIT relies on the antigen presentation, in which bacteria-produced vitamin B metabolites, such as 6hydroxymethyl-8-D-ribityllumazine, acetyl-6-formyl-pterin, 6-formyl-pterin by the MHC-Irelated gene protein MR1 in mice as well as in humans351 . Upon activation, the MAIT cells produce a vast amount of pro-inflammatory cytokines, including IFNg, TNFa, IL17, IL22, and are also able to lysis bacteria-infected cells by granzyme B and perforin secretion352 . In line, MAIT are lack within the germ-free mice, and a recent study,Legoux et al. reported that microbial metabolites, such as 5-(2-oxopropylideneamino)-6-D-ribityl-amino-ouracil (5-OP-RU) control the thymic development of the MAIT 353 . Of note, MAIT are reported to be also activated by the MR1/TCR-independent manner in response to anti-viral cytokines, such as IL-12, IL-18, IL-15, and IFNa/b in viral infections, including HIV, hepatitis B, and C by mainly producing IFNg 354 , 355 , 356 .g. Regulatory T cellsAt steady state hepatic CD4 + T cell population is less abundant than CD8 + T cell population respectively, which reflects approximately 40% and %60 of total TCRa/b + T cell population.CD25 hi CD127 int FoxP3 + Tregs are prevalent among the CD4 + T cell fraction 357 . At homeostasis, two crucial functions of the Tregs are that to restrict hepatic inflammation by mainly secreting the IL-10 and TGF-b cytokines, also maintaining self-tolerance through regulating autoreactive T cells within the sinusoidal lumen and nearby portal tract358 . Indeed, in a recent study,Li et al. revealed that hepatic neonatal Tregs are critical to ensure self-tolerance and liver maturation at steady-state359 . Tregs are highly sensitive to IL-2 in connection with the high expression of CD25, which is the receptor for IL-2 cytokine. Production of IL-2 from other T cells activates IL-2 signaling in Tregs that leads to phosphorylation of the STAT5, regulating their differentiation, proliferation, and survival 360 . Moreover, human hepatic Tregs have also been shown to require IL-2 cytokine from the effector cells for survival361 . h. CD8 + Memory T cells At homeostasis, liver contain a specific CD8 + T cell subset, characterized as T-bet lo Eomes lo Blimp-1 hi Hobit lo CD69 + CD103 + CXCR3 + CXCR6 + liver-resident memory T cells (TRM) that patrol the space of Disse close to the hepatic veins, supplying quick and powerful responses against invasive pathogens 362 . The liver-resident CD8 + TRM are strongly associated with malaria infection in mice and required for long-term protection363 . In a recent study,Olsen et al. proposed a combined prime-and-trap strategy to fight against pre-erythrocytic malaria infection by which priming the protective liver-resident CD8 + TRM 364 . Moreover, the inflammatory and antigenic signals dictate the development of a high amount of liver-resident CD8 + TRM subsets, requiring IL-15, with a half-life of 36 days in mice 365 . Furthermore,Feau et al. showed that the IL-2, necessary for the expansion CD8 + TRM population, is mainly provided by CD8 + T cells, rather than CD4 + T cells in mice 366 . In line, IL-2-expressing liver-resident CD8 + TRM, are considered as sentinels for hepatotropic infection in the human liver 367 .i. B cellsIn mouse, hepatic B cell subsets include small numbers of B220 + IgM + CD23 -CD43 + B1 subset and large quantities of bone marrow-derived mature B220 + IgM + CD23 + CD43 -B2 subset at steady-state 368 . Functionally, B2 cells need T helper cells for proliferation and isotype switch that result in the production of highly antigen-specific antibodies 369 . Nonetheless, the maturation of B1 cells occurs independently from the T cells, which are the principal sources of natural, poly-specific (cross-reactive) IgM antibodies against both self and microbial antigens 370 . Therefore, together with their cross-reactive natural antibody production ability, IL-10-producing regulatory B cells (Bregs), maintaining hepatic homeostasis 371 .Immune drivers of inflammation in Non-Alcoholic Fatty Liver Diseases a. Kupffer Cells, recruited monocytes, and macrophages Since KCs express several receptors, such as the scavenger, complement, and PRRs, they sense and are quickly activated by pathogens or metabolic abnormalities. Activated KCs, initiate the hepatic immune response through expanding their number, the release of the immune modulators (cytokines i.e. TNFa, IL-1b, IL6 and chemokines i.e. CCL2/CCL5), the recruitment of other immune subsets to the liver, such as monocytes, pro-inflammatory macrophages, and, based on the state of the damage, exacerbate or resolve the injury by coordinating the tissue-repair process. Besides infection, KCs are also at the center of the initiation, progression, and regression of NAFLD, as revealed by several experimental settings.One of the robust evidence in that the depletion of KCs, by gadolinium chloride or clodronate liposome techniques, protects against diet-induced hepatic steatosis and insulin resistance in rodents 372 ,373 . In the pathophysiology of the NAFLD, KCs are activated by diverse stimuli.Lipotoxicity-induced hepatocellular injury, characterized by oxidative stress, endoplasmic reticulum stress, mitochondrial dysfunction, and cell death causes the secretion of DAMPs, such as the high mobility group protein 1 (HMGB1), which believed to be the primary inducer of KCs 374 . Besides, cholangiocytes, which are the epithelial cells of the bile duct, LSECs, and HSCs contribute to the KCs activation by secreting DAMPs 375 . On the other hand, as a result of the intestinal permeability altered in NAFLD, the gut-derived PAMPs, including LPS, flagellin, bacterial-derived products that bind to TLR4, and activate KCs, leading to release of a massive amount of pro-inflammatory cytokines, including TNFa, and IL-1b 376 . The excessive LDL is mostly in its oxidized form (ox-LDL), due to the lipotoxicity-induced oxidative stress in NAFLD. KCs capture the toxic ox-LDL by the two principal scavenger receptors, which are the SR-A and CD36, that leads to the formation of foamy KCs with cholesterol crystals, prompting hepatic inflammation 377 , 378 . Moreover, activated KCs stimulate fat accumulation within the hepatocytes in part due to IL1-b-dependent suppression of the PPARa activity, which in turn down-regulate fatty acid oxidation related genes, favoring hepatic steatosis 379 . Interestingly, Wan et al. observed an M2-like alternatively polarized KC subset that promotes M1-like proinflammatory KC apoptosis in morbidly obese patients with minimal hepatic injury and steatosis compared to patients with severe liver problems. These findings were also confirmed in animal models by the authors, suggesting the balance between anti-inflammatory and inflammatory milieu shaping the KC identity in NAFLD 380 . Indeed, the persistence of the hepatic inflammatory environment stimulates KCs to recruit pro-inflammatory immune cell infiltration into the liver, progressing from NAFL to NASH phenotype. During the inflammatory phase, KCs promotes hepatic monocyte infiltration mainly by producing the monocyte chemoattractant protein 1 (MCP-1/CCL2) through activation of CCR2, which is expressed by monocytes 381 . Indeed, a strategy to target pharmacological inhibition of CCL2 decreases macrophage infiltration and steatohepatitis 382 . Alternate chemokine signaling pathways, such as the, CXCR3/CXCL10, CCR1/CCL5 (RANTES), and CCR8/CCL1, contribute hepatic monocyte recruitment, favoring a NASH phenotype 383 , 384 , 385 . Idrissova et al. determined that the deletion of the TNF related apoptosis-inducing ligand (TRAIL) receptor in mice reverse metabolic outcomes in response to high saturated fat, cholesterol, and fructose feeding, implying that the TRAIL involved in bone marrow-derived monocyte/macrophage recruitment 386 . Circulating monocytes are considered to give rise to the hepatic monocyte-derived macrophage subset in NASH 387 . Indeed, Beattie et al. revealed that the bone marrow-derived macrophages and KCs exhibit distinct transcriptomic signatures, nevertheless comparable biological functions 388 . In a recent study, Seidman et al. by performing single-cell RNA sequencing (scRNA-seq) on liver non-parenchymal cells from standard or NASH diet fed mice identified five major hepatic macrophage populations, which are healthy KC (KC-H), NASH KC (KC-N), recruited macrophages occupying the KC-N niche (KN-RM), Ly6C hi -RM, and Ly6C low -RM 389 . Authors revealed that the KC-H, KC-N, and KN-RM mutually express high levels of Adgre1 (F4/80) and low levels of Cd11b as well as KC lineage-determining Mafb and Maf genes, coding for BZIP transcription factors, while Ly6C hi -RMexpress Ly6c2, Chil3, F13a1,Fn1 and Ly6C low -RM express Cd2091, CD7, and Itgax 389. They also performed fate-mapping analysis and found that KC-N cells are long-lived and originate from embryonic KCs, while KN-RM, Ly6C hi -RM, and Ly6C low -RM are short-lived and derive from HSCs 389 . Moreover, authors employed diphtheria toxin (DTR)-driven KC ablation (Clec4f-creR26-iDTR) and showed that KN-RM are able to re-populate KC niche and contribute to NASH pathogenesis, as similar to the embryonically derived KCs 389 . Furthermore, they also showed that NASH microenvironments induce apoptosis of KC-H cells and impair their regulatory transcriptomic landscape, which result in acquisition of KC-N phenotype through reprogramming the transcriptomic landscape of liver-X receptor (LXR)-mediated KC-signature 389 . Authors also identified by analyzing LXR ChIP-seq and gene expression data obtained from KC-N and KN-RM fate-map strategy, several potential NASH-dependent LXR binding partners that are responsible for LXR-dependent transcriptomic landscape remodeling, for example, ATF3 as a gain of function partner and Spic as a loss of function partner 389 . More recently, two independent studies using different NASH models also confirmed that embryonic KCs (EmKCs) are dying in the course of NASH pathogenesis and are replaced by monocytederived macrophages (MoKCs)390,391 . Tran et al. by using BM chimerism and parabiosis strategies, identified that TIM4 + Clec2 + (Clec2 was used as a KC marker instead of Clec4f) EmKCs were gradually replaced by TIM4 -Ly6C hi MoKCs with the progression of MCD-induced NASH development in mice390 . Authors showed that NASH alters EmKCs self-renewal by causing their death, while MoKCs acquire self-renewal capacity, evidenced by long-term survival and proliferation 390 . Importantly, they found MoKCs store less lipid droplets than EmKCs and exhibit higher pro-inflammatory markers under NASH diet, suggesting that MoKCs are more prone to lipid-induced stress and inflammation 390 . They also showed that DTRmediated EmKC depletion leads to enrichment of MoKCs and severe liver damage as well as hepatic fibrosis development in response to NASH-inducing diet 390 . Remmerie et al. by combining CITE-seq technology and BM chimerism approach, found a similar gradual loss of Clec4f + TIM4 + EmKC and their replacement with monocyte-derived Clec4f + TIM -MoKCs with the progression of Western diet-induced NASH development in mice391 . In line with the findings ofTran et al. 390 , authors also discovered MoKCs contain less lipid droplet than EmKCs 391 . Interestingly, they identified a distinct monocyte-derived macrophage population, characterized as Ly6C hi Clec4f -Spp1 + Trem2 + CD9 + cells that resemble to recently described lipid-associated macrophages (LAMs) in obese WAT 194 thus, named hepatic LAMs 391 . Authors revealed that LAMs exhibit an altered transcriptome compared to MoKCs and EmKCs with the highest lipid metabolization rate in response NASH, however function of these osteopontinexpressing cells has not been explored in detail 391 . Pro-inflammatory milieu found during NASH stimulates hepatocytes to produce a large number of complement proteins. Following the binding to their target antigens, the complement proteins cleaved to create active fragments and complement-opsonized particles, which are efficiently phagocytosed by KCs via the complement receptors that include CR1, CR3, CR4, CR5aR, and CRIg 313 , contributing to the pathogenesis as also reported in NASH patients392 . Additionally, KCs are involved in hepatic fibrosis development as they activate the HSCs by releasing pro-fibrotic cytokines TGF-b and platelet-derived growth factor (PDGF). Conversely, HSCs produce the tissue inhibitors of metalloproteinases (TIMPs) and extracellular matrix components (ECM)393 . KCs trigger extracellular matrix degradation being the primary source of the various matrix metalloproteinases, including MMP9, -12, and -13, thus leading to resolve the fibrosis394, 395, 396 . Recruited Ly6C hi monocyte-derived proinflammatory macrophages also directly communicate and activate HSCs by TGF-b to promote hepatic fibrosis 397 . Recently, the stimulator of interferon genes (STING) in monocyte-derived macrophages was found to correlate with the progression of liver inflammation and fibrosis in individuals with NAFLD 398 . Moreover, recruited Ly6c low monocyte-derived macrophages have also been linked to the resolution phase of the hepatic fibrosis by secreting MMPs 399 . Selective deficiency of infiltrating macrophages by using the CD11b-diphtheria toxin receptor transgenic mice, decreases fibrosis development, but by contrast, during the state of resolution, aggravates hepatic fibrosis 400 . These findings highlights the significance of phenotypic flexibility of the KCs, recruited monocyte, and macrophage entity in response to environmental and metabolic signals 400 . b. Dendritic Cells Given the fact that lack of specific markers to target hepatic DCs and diversity in the employed animal models, i.e., diets, duration, genetic background, the role of DC in NASH remains unclear. In this regard, Henning et al. showed in mice with CD11c-DTR-mediated depleted DCs, intrahepatic inflammation is exacerbated in response to MCD-feeding, suggesting hepatic DCs are protective against NASH by ignoring the absence of DC specifity 401 . On the other hand, Suitti et al. claimed that the inflammatory hepatic CX3CR1 + DCs, which arises from the bone marrow, contribute to NASH progression in MCD-fed mice 402 . Besides, Ibrahim et al. suggested that the hepatic environment and cellular lipid content determines the phenotype of DCs, as they found that hepatic lipid-rich DCs are immunogenic, activating T, NKT, and NK cells. Nonetheless, the hepatic lipid-poor DCs are tolerogenic, which induce activation of the Tregs, in both mice and humans, facilitating DC discrimination 403 . Moreover, Heier et al. identified that CD103 + cDC1 subset protects against the metabolic challenges upon highsucrose and MCD diets in mice 404 . Interestingly, in a recent study, Aarts et al. revealed that DC-CD40-deficient mice obtained by crossing CD40 floxed mice with CD11c Cre mice, displayed severe obesity and liver steatosis with a considerable reduction of the Tregs number compared to control group in response to the HFD-feeding. Nevertheless, under a NASHinducing diet, hepatic inflammation decreased without affecting hepatic lipid content in DC-CD40-deficient mice, suggesting CD40 + CD11c + DC subset acts as a double-edged sword by contributing inflammation in NASH and protecting against metabolic syndrome 405 . Likewise, Connolly et al. reported that hepatic DCs display a pro-inflammatory phenotype, which induces inflammation and progression of fibrosis, as they have been shown improved phenotype by using CD11c-DTR mice to deplete DCs in a fibrotic model 406 . It has also been reported that CD11c-DTR mice, which have depleted DCs, subjected to the carbon tetrachloride-induced liver fibrosis, manifests prolonged regression of fibrosis 407 . Our group recently demonstrated that increased extracellular free fatty acids (FFAs) profoundly affect DC immune function, primarily via modification of DC intracellular metabolism 408 . Compared to stimulation with TLR ligands alone, BM-derived DCs, which differentiated into mostly cDC2-like phenotype displayed a distinct cytokine and metabolic response when treated with TLR ligands in the presence ofFFAs with synergistic IL-23A production as a hallmark 408 . Our group, also performed a comprehensive blood immunophenotyping combined with hepatic transcriptomic analysis of a large cohort of NAFLD patients 409 . It was found that in the blood, cDC1 cells were inversely correlated with histological features of NASH (especially lobular inflammation), while cDC2 were positively correlated with hepatic lesions409 . In parallel, the hepatic transcriptome of patients with NASH was enriched in genes closely associated with cDC functions, especially with antigen presentation and specific cytokines and chemokine, such as IL18, CXCL10, and IL23A that are also synergistically upregulated by TLR and FFAs 409 . Moreover, intrahepatic immunophenotyping of a diet-induced murine model of NASH revealed changes in a number of immune cell populations that paralleled those observed in blood from NAFLD patients, notably decreased cDC1 and increased cDC2 in NASH 409 . These data highlights importance of considering the metabolic environment for the understanding the hepatic immune system activation in NAFLD 409 . Collectively, this paper clearly implicates hepatic cDC in the development and resolution of NASH in mice as well as in humans 409 .c. NeutrophilsUpon activation, KCs early on mainly recruit neutrophils into the inflamed liver by the CXCR1/CXCR2 chemokine signaling ligands that include CXCL1, CXCL2, and CXCL8 410 .There is a positive correlation between NAFLD and hepatic neutrophil infiltration, thus neutrophil myeloperoxidases (MPOs) is a good predictive marker of the severity of the disease progression 411 . Indeed, overproduction of neutrophil MPOs aggravates NASH in mice while, MPO-deficient mice have an opposite phenotype 412 . Pulli et al. revealed, by using the MCDfed mice model, the underlying mechanism in that MPO leads to oxidative stress that directly kills hepatocytes and macrophages, increases mitochondrial permeability through pore formation and it furthermore activates the HSCs, contributing to NASH pathogenesis 413 . Moreover, neutrophil elastases have also been shown to mediate insulin resistance, thereby enhancing inflammation 213 . Consequently, the antibody-based depletion of neutrophils ameliorates diet-induced NAFLD in mice 414 . Besides, neutrophil extracellular trap (NET) formation upon activation by DAMPs favors the hepatic sterile inflammatory injury 415 . In addition, hepatocyte and neutrophil crosstalk regulates the NET formation upon bacterial antigen exposure, which might be counteract increased gut permeability associated to NASH 416 . d. Natural Killer Cells Even though hepatic NK cells are essential to homeostasis, NK cells polarize KCs towards M1-like inflammatory phenotype in response to MCD-feeding in mice 417 . Moreover, a spontaneous NASH development is observed in the principal methyl donor, the glycinemethyltransferase (GMNT)-deficient mice, is NK cell-dependent, through increasing the hepatic proinflammatory milieu 418 . Since the proinflammatory cytokine IL-15 is necessary for NK cell maturation and function 419 , IL-15-driven NASH development is also mediated by NK cells 419 . The metabolic checkpoint kinase mTOR is the master regulator of the IL-15 signaling during the NK cell development and activation 420 . Likewise, osteopontin (OPN) has also been shown to regulates the development and function of the NK cells 421 , 422 . Consequently, alteration of NK cell function in response to PPARg-mediated suppression of mTOR signaling has been linked to NAFLD in obese patients 423 , 424 . Furthermore, in a recent study, Assman et al. revealed that the Srebp-1 transcription factor regulates glucose and lipid metabolism in NK cells and leads to cytokine-induced metabolic reprogramming of NK cells from antiinflammatory phenotype to pro-inflammatory phenotype, determining their effector function 425 . e. Natural Killer T cells The hepatic number of the NKT cells increases dramatically with NASH. Their recruitment mediated by hedgehog signaling-dependent production of the CXCL16 and the vascular cell adhesion molecule 1 (VCAM-1) leading to induction of OPN synthesis by NKT cells that drive fibrinogenesis in mice and humans 426 . Recently, Maricic et al. showed that hepatic IL-17 + IL22 + iNKT cells switch to an IFNg + IL-4 + IL-13 + iNKT phenotype during the progression in the cholinedeficient L-amino acid-defined (CDAA) diet-induced mouse NASH model. Furthermore, steatosis and fibrosis development in this model is mediated by IFNg + IL-4 + IL-13 + iNKT cells throughout the recruitment of the inflammatory macrophages, CD8 + T cell, and activation of the HSCs 427 . Moreover, NKT cells induce hepatocyte FA-uptake by the lymphotoxin beta receptor (LTbR)-ligand LIGHT, also known as tumor necrosis factor superfamily member 14 (TNFSF14) and together with CD8 + T cells, lead to liver damage and HCC development in response to the choline-deficient high-fat diet 428 . Regarding that, in a recent study, a Spanish group confirmed that the genetic deficiency of the LIGHT exhibits improved glucose homeostasis and hepatic steatosis in the high-fat high-sucrose diet-fed mice 429 . f. CD4 + T cells The secretion of increased pro-inflammatory cytokines, like TNFa and immunoregulatory cytokine IFNg by various hepatic immune cell types not only recruits T-bet + STAT2 + STAT4 + CD4 + Th1 cells but also induces polarization of the hepatic naïve CD4 + T cell population into CD4 + Th1 subset, increasing total CD4 + T cell quantity in the liver of mice and humans with NASH 430 . The Th1 cells further contributes to the hepatic inflammation by IFNg, TNFa, and IL-2 production and stimulating pro-inflammatory macrophage polarization. Furthermore, hepatic, and circulating IFNg-producing Th1 cells are enriched in NASH patients and mouse models 431 , 432 . Relatedly, IFNg-deficient mice displayed alleviated hepatic inflammation and fibrosis, by restricting the inflammatory phenotype of macrophages in animals fed with a NASH-inducing diet 433 . Hepatic Th17 are also increased in mice fed with HFD, as well as in NASH patients compared to healthy control groups and neutralization of IL-17 attenuate hepatic steatosis and inflammation, thus Th17 cells facilitate the progression from simple steatosis to NASH 434 . Similarly, Harley et al. showed that IL-17RA-deficient mice exhibit decreased hepatocellular damage and steatosis in response to HFD feeding. Moreover, alteration of IL-17 production by modulation to the colonization of mice with segmented filamentous bacteria suggested that the IL-17 axis is central to the development and progression of NAFL to NASH 435 . Besides, Rau et al. confirmed that NAFL to NASH progression characterized by an increase in IL-17 + T cells among the intrahepatic CD4 + T cells and peripheral blood ratio of Th17/Tregs as compared to lean individuals with NAFL and NASH patients 436 . It has also been reported that IL-17 directly activates the HSCs to produce TGF-b, alpha-smooth muscle actin (a-SMA), collagen type-I by inducing the STAT3 signaling pathway, contributing to hepatic fibrosis formation 437 , 438 . g. CD8 + cytotoxic T cells Hepatic CD8 + cytotoxic T cells expand during NAFL to NASH transition. CD8 + T cells recognizes damaged or infected cells via MHC-I receptor, which are killed through the release of various cytokines and cytotoxic molecules that include perforin and granzymes in mice and humans 439 , 428, 409 . Recently, Ghazarian et al. showed that the accumulation of CD8 + cytotoxic T cells within the liver is mediated by the hepatic type-I interferon (IFN-I) responses, as suggested by increased interferon regulatory factors (IRFs), interferon stimulatory genes (ISGs), and IFNa protein expressions in HFD-fed mice. Furthermore, whole-body IFNaR1deficient or CD8-specific IFNaR1-deficient chimeric mice are protected from HFD-induced liver complications, which results improved hepatic insulin sensitivity and gluconeogenesis 440 . Relatedly, CD8 + T cell-deficient mice fed a high-fat high sucrose (HFHS) supplemented with high cholesterol diet, which is a progressive murine NASH model, exhibited alleviation of the hepatic steatosis and fibrosis together with the decreased number of activated KCs and immune cell infiltration compared to wild-type mice as well as in humans with NASH 441 . Moreover, Breuer et al. showed that hepatic CD8 + T cells increased in obese and hyperlipidemic NASH mice, upon feeding a western diet and are positively correlated to HSCs activation, while the CD8 and LDLR (low-density lipoprotein receptor) double-deficient mice displayed a significant reduction in hepatic inflammation upon feeding with a Western diet.Furthermore, depletion of the CD8 + T cells in a lean NASH model obtained by MCD diet feeding, neither affected hepatic inflammation nor HSCs activation 442 . Interestingly, genetic ablation of the CD8 + cytotoxic T cell protein perforin in mice leads to excessive hepatic fat accumulation and lobular inflammation in response to MCD diet or HFD feeding by causing inflammatory polarization of the recruited bone marrow-derived monocytes and macrophages, pointing towards immunoregulatory role of the CD8 + T cells. Moreover, perforin-deficient mice also display an increase in accumulation, survival, activation, and proinflammatory cytokine production of CD8 + T cells but neither NK cells or CD4 + T cells, presumably as compensatory mechanism, which confirmed by their transcriptome by RNA-sequencing data. In line, elevated plasmatic perforin levels and hepatic perforin expression were observed in individuals with NASH443 . In accordance, our group also evidenced an increased in blood perforin-expressing CD8 + T cells as well as in hepatic perforin and granzyme A-expressing CD8 + T subset that positively correlate with the severity of disease in a large NAFLD patients cohort 409 . h. B cells Hepatic B cell populations expand strikingly in NASH. The B cell-activating factor (BAFF) is the stimulator of the B cell differentiation and expansion accounts for increased serum immunoglobulin levels and is associated with the histological severity of NAFLD 444 . Surprisingly, Kawasaki et al. revealed that the BAFF receptor-deficient mice fed with HFD worsen the hepatic steatosis development by stimulating expression of the steatogenic genes compared to wild-type mice, implying the protective role of the BAFF signaling 445 . Nevertheless, Sutti et al. reported that MCD diet-fed mice when vaccinated with BAFFneutralizing antibody, were protected from the NASH development leading to improved hepatic steatosis, and lobular inflammation. They identified that 40% of decreased in the circulating and hepatic B cell number and decreased CD4 + Th1 activation, as evaluated by IFNg production. The authors also found similar findings in mice over-expressing the soluble form of the BAFF/APRIL receptor in mice fed a CDAA diet 446 . Compatibly, in a recent study, HFDfed BAFF-deficient mice displayed significantly improved insulin sensitivity accompanied by attenuated inflammation and marked decreased CD11c + ATMs and fibrosis of epiAT, suggested to contribute to healthy AT expansion. Attenuated hepatic steatosis was also observed in BAFF-deficient mice, suggesting a therapeutic interest for BAFF neutralization in obesity-induced diabetes and NAFLD 447 .In conclusion, diverse mechanisms and microenvironmental changes together with the heterogenous and evolving cell populations are involved in the onset and progression of NAFLD. Therefore, identifying reliable molecular players against multifactorial NASH development is difficult.3. NUCLEAR RECEPTORSNuclear receptors (NRs) are a superfamily of transcription factors that include 48 members in humans, 49 members in mice, and 47 in rats. NRs regulate activity of the target genes mostly, in a ligand-dependent manner, involving various biological processes, such as development, metabolism, inflammation, and circadian rhythm 448 , 449 . Due to the capability to control such essential physiological processes and to the nature of their ligands (small and often stable molecules), NRs have long been represented a valuable therapeutic targets in several pathologies that include breast cancer, T2D, fertility, NASH, and atherosclerosis 450 . Ligands of the NRs comprise of small lipophilic molecules and hormones, like phospholipids, steroids, retinoids, and vitamin D that induce NRs to bind specific DNA sequences, known as DNA response elements, formerly named as hormone response elements (HRE), all along the genome 450 . Upon activation NRs are recruited to the DNA with co-regulator proteins, chromatin remodelers, and the principal transcriptional machinery, which in turn activate or repress the target gene expression 451 . Nevertheless, ligands for some of the NRs have not yet been determined and the receptors are thus considered as the ''orphans'' 452 . NRs are categorized into seven subfamilies from subfamily 0 to 6 based on the origin and evolutionary diversification (Table

Figure 11 :

 11 Figure 11: Schematic representation of the (A) NRs domain organization. NR polypeptides have an Nterminal domain (NTD) that is variable in size and sequence, a conserved DBD, a variable hinge region, and a 12-helical LBD. Several NRs also contain a variable F-domain positioned at their C-termini. (B) Oligomeric complexes of NRs and DNA response element repertoires. Receptors can be organized into distinct oligomeric states such as heterodimers with the common partner retinoid X receptor (RXR), homodimers, or monomers. The non-steroid receptor heterodimers and many homodimers bind to direct repeat response elements with various inter-half-site spacings. Steroid receptor homodimers mainly use palindromic DNA elements, where the two half sites are in an inverted repeat arrangement. Other receptors use monomeric sites extended at their 5'-end with short sequences used for selectivity. Several examples of receptors falling into each of these four categories are shown 456 .

Figure 11 :

 11 Figure 11: Schematic representation of the nuclear receptor domain organization, oligomeric complexes of the nuclear receptors and DNA response elemen repertoires.

  cytoplasm and are coupled with the chaperone proteins to keep open steroid-binding cleft, leading to accessibility for a steroidal ligand. Following the ligand-dependent activation, chaperones facilitate migration of the SRs throughout the microtubular paths to the nucleus 467 . Then, the SRs binds to the DNA response element, as a homodimer, containing palindromic repeats 468 . During that time, chaperone machinery still in contact with the receptor and interacts with transcriptional regulatory complexes to terminate transcriptional activation when it is necessary 467 . The type II NRs reside in the nucleus even in the absence of a cognate ligand bound to the co-repressor protein complexes that include, for example, the RAR and LXR. Upon ligand-binding, co-repressors are displaced by co-activators and the transcriptional machinery complexes, forming heterodimers with one of the RXRs on the direct repeat DNA response sequences 469 . Type III and type IV NRs share the same mechanism of action with type II NRs except upon activation, they binds to the DNA as a homodimers on direct repeat sequences, and as a monomers on extended single half-site, respectively 470 .

Figure 12 :

 12 Figure 12: Schematic of NR signaling mechanisms. (A) Type I receptors reside in the cytoplasm (C) in complex with chaperone proteins. Upon ligand binding (hexagon), the receptor is released from this complex and is trafficked into the nucleus (N) where they typically bind to palindromic hormone response elements (HREs) as a homodimer to regulate transcription. (B) Type II receptors are localized in the nucleus. In their unliganded state, they interact with co-repressor proteins, but upon ligand binding are exchanged for co-activators. NRs in this group generally form heterodimeric complexes with RXR. (C) Similar to Type II receptors, Type III receptors reside in the nucleus and exchange bound co-repressors and co-activators. These receptors bind to direct repeat HREs as homodimers. (D) Type IV receptors are almost identical to Type III except they bind HREs that are extended half sites as monomers 453 .

Figure 12 :

 12 Figure 12: Schematic of the nuclear receptor signaling mechanisms.

Figure 13 :

 13 Figure 13: Modulation of the gene expression by NRs. NRs both activate and repress transcription. (A) To activate gene expression, NRs (blue) interact with their DNA response elements. DNA-bound NRs recruit co-activator proteins (magenta), which in turn recruit histone-modifying enzymes. These histonemodifying enzymes are commonly histone acetylases (green), which acetylate histone tails. This modification is a mark of active chromatin. Ultimately, the general transcriptional machinery and RNA Polymerase Pol II (gray) are recruited to drive gene expression. (B) To repress transcription, NRs recruit co-repressor proteins (orange). These proteins recruit other histone deacetylases (red) that reverse histone acetylation and restrict chromatin accessibility. This condensation prevents the transcriptional machinery from accessing the DNA, thus repressing gene expression 453 .

Figure 13 :

 13 Figure 13: Modulation of the gene expression by nuclear receptors.

Figure 14 :

 14 Figure 14: Schematic representation of ROR family members. Schematic structure of the various human (h) and mouse (m) ROR isoforms. The DNA binding domain (DBD) and ligand binding domain (LBD), and activation function 2 (AF2) are indicated. The variable regions at the N-terminus of each ROR generated by alternative promoter usage and/or alternative slicing are indicated by patterned boxes on the left. The numbers on the right refer to the total number of amino acids in RORs. The different ROR isoforms identified in human and mouse are shown on the right (+/-) 475 .

Figure 14 :

 14 Figure 14: Schematic representation of the ROR family members.

circadian rhythm 489 .

 489 photoreceptor cells and synchronizes peripheral clocks wherein theoretically every cell in the body is entertained to the circadian rhythm in a coordinated manner490 . Synchronization of the peripheral clock by the master clock incorporates the neuronal outputs and hormonal signals, like melatonin and glucocorticoids in return, the daily oscillations, including dark/light exposure, feeding/fasting, and activity/rest cycles modulate body temperature, blood pressure, metabolism, and immune function. In addition, tissue specific circadian rhythm is regulated by local/environmental cues independent from the central clock 491 . Regulation of the circadian rhythm is governed by complex transcriptional/translational negative and positive feedback loops at the molecular level (Figure15). The positive loop is under the control of the basic helix-loop-helix-PAS (bHLH-PAS) transcription factors, which are the brain and muscle ARNTlike protein-1 (Bmal1) and the circadian locomotor output cycles kaput protein (Clock) or its paralogue the neuronal PAS domain protein-2 (NPAS2)492 . The Bmal1 constitutes a heterodimer with the Clock or NPAS2 to activate the expression of the Period (Per1, Per2, and Per3) and the Cryptochrome (Cry1 and Cry2) genes by binding to the E-box DNA response elements in their promoter region. Afterward, the Per and Cry proteins forms heterodimers and suppresses the activity of Bmal1/Clock (or NPAS2) by negative feedback loop 493 . Furthermore, the repressor Rev-erba and activator RORa creates an additional regulatory feedback loop that controls Bmal1 expression by binding to the mutual response element

Figure 15 :

 15 Figure 15: Regulation of the circadian rhythm at molecular level. Circadian rhythms are biological processes that display endogenous oscillations of approximately 24 hours and are regulated by a core circadian clock. The master circadian clock is located in the suprachiasmatic nucleus (SCN) of the hypothalamus. There are several interconnected transcriptional auto-regulatory feedback loops controlling the circadian cycle. Heterodimers of BMAL1 and CLOCK activate the expression of CRY and PER genes. Once the CRY/PER heterodimers reach a critical threshold, they enter the nucleus and repress BMAL/CLOCK transactivation. RORa and REV-ERBa have been demonstrated to positively or negatively regulate the expression of BMAL1, respectively. RORa competes with REV-ERBa for binding of their shared DNA response element in the BMAL1 promoter. The oscillating pattern of RORa and REVERBa in the SCN dictates the circadian pattern of BMAL1 expression. This RORa/REV-ERBa feedback loops interconnects the positive and negative arms of the core circadian clock 494 .

Figure 15 :

 15 Figure 15: Regulation of the circadian rhythm at molecular level.

3. 3 . 3

 33 Retinoic Acid Receptor-related Orphan Receptor Alpha as an immune regulator Initial data about the role of RORa as an immune regulator arose from observation of the staggerer mice that display limited thymus development, swollen lymph nodes, and decreased spleen mass 518 . Moreover, in the same study, it was also surprisingly shown that staggerer mice generated normal proportions of the T helper cells and antibody-producing B cells following the SRBC immunization. However, they exhibited prolonged immune response and delay in the generation of suppressor T-cells following the challenge, suggesting impaired regulatory feedback mechanisms 518 . In response to LPS-induced inflammation, staggerer mice found to be highly sensitive, causing hyper activation of macrophages leading to increased production of the pro-inflammatory cytokines, like IL-1 and TNFa, suggested a reduced regulator activity of RORa in inflammation 528 . Relatedly, Dzhagalov et al. revealed that RORa indirectly governs the development of T and B cells by supplying the necessary environment and controls immune responses through limiting cytokine production in innate immune cells and lymphocytes by using staggerer and Rag-2 -/-ROR sg/sg bone marrow chimeric mice 529 . Furthermore, Delerive et al. reported that over-expression of RORa in smooth muscle cells activates IkBa that represses the NF-kB signaling pathway by reducing the p65 translocation and suppresses TNFa-induced cytokine production, confirming RORa is a negative regulator of the inflammatory response 530 . Additionally, human aortic smooth muscle cells have been shown to predominantly express RORa1, while in atherosclerotic plaques, it was decreased significantly, supporting the absence of protective RORa in staggerer mice provokes atherosclerosis development 531 . By contrast, Sun et al. demonstrated that RORa drives the oxygen-induced retinopathy by repressing the suppressors of cytokine signaling 3 (SOCS3) expression, which is a negative regulator of the inflammation, implying immune regulator activity of the RORa depends on the pathology 532 . It has also been reported that staggerer mice are protected from ovalbumin-induced allergic airway inflammation, evidenced by decreased mucus cell hyperplasia, Th2 cytokine responses, like IL-4, IL-5, and IL-13, infiltration of the neutrophils, eosinophils, and lymphocytes into the lung and bronchoalveolar fluids 533 . Similarly, Stapleton et al. found that staggerer mice heightened susceptibility tointratracheal LPS-induced Th17 and neutrophilia-dependent lung inflammation 534 . Importantly, they also identified that the engagement of the attenuated IkBa-dependent mechanism was not responsible for this protection, as previously shown in smooth muscle cells, highlighting that RORa possibly affects various inflammatory pathways as a negative immune modulator534 . These findings suggest that RORa plays a significant role in the development of Th2-driven allergic lung inflammation in mice as a potential asthma target. Indeed, in a recent study, the RORA gene has been identified as a high risk for asthma in a large-scale genome-wide association study535 , 536 . Besides, RORa is widely-expressed within the immune system and play key roles in the development and function of various immune cell types. Friesenhagen et al. by using genome-wide microarray analysis revealed that monocytes display reduced immune response against a highly pathogenic avian influenza virus (HPAIV), H5N1 compared to human influenza A virus 537 . They showed that RORa is activated in monocytes upon H5N1 infection and inhibited NF-kB signaling, suggesting that RORa regulate immune function of monocytes in response to viral infection 537 . In a recent study, Saini et al. reported that RORa expression is increased in murine macrophages and DCs as well as in human PBMCs upon Mycobacterium tuberculosis infection without providing a functional mechanism 538 . It has been shown that RORa regulate development of group 2 innate lymphoid cells (ILC2) 539 , which are crucial cell types in allergic asthma as well as to maintain metabolic homeostasis in AT 540 . Moreover, Yang et al. revealed that Th17 lineage differentiation is programmed by RORa and RORg nuclear receptors 541 . Furthermore, RORa regulate differentiation of T follicular helper (TFH) cells 542 , which are specialized to stimulate B cell growth, differentiation, immunoglobulin isotype switching, and affinity maturation. In line, RORa control survival of IgG2a-producing memory B cells 543 . Recently, Malhotra et al. showed that RORa expression in Tregs control allergic skin inflammation through TNF ligand-related molecule 1 (TL1A) and death receptor 3 (DR3)-mediated suppression of ILC2 and eosinophil infiltration 544 .

3 .

 3 Mouse studiesMice were kept on a 12-hours light/dark cycle in the SPF animal facility from the Institute Pasteur de Lille with ad libitum access to food and water. Littermate WT and MKO mice were maintained all along the experiment procedures in 904 cm² cages (Green line GR900, Tecniplast) with 6-12 mice per cage and a ratio WT:MKO tending to 1:1. Only male mice were used for the experiments. All animal procedures were approved by the ethical committee for animal experimentation of the Nord-Pas-de-Calais Region (CEEA75) (APAFIS#7160-2017040313471173) in accordance with European guidelines on the protection of animals used for scientific purposes (2010/63/UE). Ten-week-old RORa WT and their littermates RORa MKO mice were fed with a 60% high-fat diet (HFD, Research Diet, D12492) for 12

  Tissues were embedded in paraffin by using a STP 120 Spin Tissue Processor (Microm Microtech) and an EG1160 Tissue Embedding Station (Leica). Paraffin-embedded samples were cut at a thickness of 3μm and sections were transferred on a gelatin-coated slide for hematoxylin and eosin (H&E) staining and on a Superfrost Plus slides (Thermo Scientific, # J1800AMNZ) for Sirius Red staining. Staining was performed with a Leica autostainer XL and the following steps for H&E staining: xylene (2 min), xylene (2 min), 100% ethanol (2 min), tap water (2 min), hematoxylin (Sigma, #HHS128) (3 min), tap water (2 min), 70% ethanol 0.25% HCl (6 s), tap water (2 min), 90% ethanol (2 min), eosin (Sigma, #HT1101128) (2 min), 90% ethanol (6 s), 100% ethanol (1 min) and finished in xylene before mounting with Mercoglas (Merck, # 103973). For Sirius red staining, the process was the following: xylene (2 min), xylene (2 min), 100% ethanol (2 min), tap water (2 min), 0.1% Direct Red 80(Sigma, #365548) in saturated picric aqueous solution (60 min), tap water (8 min), 100% ethanol (1 min) and finished in xylene before mounting with Mercoglas. Images were acquired on an Eclipse Ti-U microscope (Nikon) and quantified with Image J software.

Table 5 :

 5 List of the antibodies used in cell sorting. antibody was coupled with PE/Cy7 by using PE/Cy7 Conjugation Kit -Lightning-Link (Abcam, #ab102903).

RESULTS 1 .

 1 Impact of macrophage-specific RORa deletion on HFD-induced obesity, IR, NAFL and obesity-independent NASH development A. Generation and characterization of the macrophage-specific RORadeficient mice We generated Rora floxed mice by introducing loxP sites flanking exon 3 (Figure 1A). Exon 3, the first common exon of isoforms 1 and 4, encodes for the DBD and includes the first zinc finger motif. Deletion of exon 3 leads to a frameshift, resulting in a premature stop codon and the absence of functional domains (Figure 1B-C).

Figure 1 :

 1 Figure 1: Generation of macrophage-specific RORa-deficient (MKO) mice. (A) Schematic representation of the strategy to target exon 3 of Rora. (B) mRNA structures of RORa1 and RORa4 and the resulting proteins in both WT and MKO (∆Ex3) mice. Exons are represented in black. Protein predictions are illustrated below mRNA and functional domains are indicated with colors. (C) Comparison of Rora exon 3 and exon 4 deletion on protein translation. Zinc finger motifs are indicated in red. Protein predictions were generated with Translate tool from ExPASy (https://web.expasy.org/translate) by using GenBank sequences for RORa1 (NM_013646.2) and RORa4 (NM_001289916.1).

Figure 2 :

 2 Figure 2: Characterization of RORa MKO mice. (A) mRNA expression levels measured by RT-qPCR for Lyz2 and Cre genes in spleen from WT (Rora +/+ Lyz2 Cre/+ ) and MKO (Rora fl/fl Lyz2 Cre/+ ) mice. (B) PCR analysis of genomic DNA extracted from sorted splenic macrophages of WT and MKO mice. Locations of primer hybridization are represented with ♦. Data are shown as mean ± SEM. * p < 0.05; ** p < 0.01; *** p < 0.001 by 2-way ANOVA followed by Sidak's multiple comparisons test or unpaired t test. n= 8-10 mice per genotype for A. NS: Not significant; AU: Arbitrary unit; FC: Fold change.

Figure 3 :

 3 Figure 3: Characterization of RORa MKO mice. (A) mRNA expression levels measured by RT-qPCR for the exon 3 of Rora in B cells, T cells, neutrophils, macrophages, monocytes, and dendritic cells (DCs) sorted from the spleen of WT and MKO mice. (B) mRNA expression levels measured by RT-qPCR for the exon 3 of Rora in total bone marrow (BM) cells, in neutrophils purified from BM and in BM-derived macrophages (BMDM) from WT and MKO mice. Data are shown as mean ± SEM. * p < 0.05; ** p < 0.01; *** p < 0.001 by 2-way ANOVA followed by Sidak's multiple comparisons test or unpaired t test n= 5 mice per genotype for A and n= 3 mice per genotype for B. NS: Not significant; AU: Arbitrary unit; FC: Fold change.

Figure 4 :

 4 Figure 4: Characterization of RORa MKO mice.(A-B) mRNA expression levels measured by RT-qPCR for Rorc (A) and Arntl (B) genes in B cells, T cells, neutrophils, macrophages, monocytes, and DCs sorted from the spleen of WT and MKO mice. (C) mRNA expression levels measured by RT-qPCR for Arntl in BMDM. Data are shown as mean ± SEM. * p < 0.05; ** p < 0.01; *** p < 0.001 by 2-way ANOVA followed by Sidak's multiple comparisons test or unpaired t test n= 5 mice per genotype for A & B, n= 3 mice per genotype for C. NS: Not significant; AU: Arbitrary unit; FC: Fold change.

Figure 5 :

 5 Figure 5: Characterization of RORa MKO mice. (A) mRNA expression levels measured by RT-qPCR for the exon 3 of Rora, Arntl, Rorc and Adgre1 in adipose tissue macrophages (ATM) sorted from epididymal adipose tissue of WT and MKO mice. (B) mRNA expression levels measured by RT-qPCR for the exon 3 of Rora in liver, epididymal adipose tissue (epiAT) and skeletal muscle from WT and MKO mice. Data are shown as mean ± SEM. * p < 0.05; ** p < 0.01; *** p < 0.001 by 2-way ANOVA followed by Sidak's multiple comparisons test or unpaired t test. n= each dot represents a pool of 3-4 mice for A, and n= 8-10 mice per genotype for B. NS: Not significant; AU: Arbitrary unit; FC: Fold change.

Figure 6 :

 6 Figure 6: Impact of RORa deletion on cytokine response upon LPS treatment in BMDM. BMDM from WT and MKO mice were treated with 50 ng/mL of LPS before analysis of (A) cytokine release in supernatant (SN) by ELISA and (B) gene expression by RT-qPCR. Data are shown as mean ± SEM. 2way ANOVA followed by Sidak's multiple comparisons test n= 4-5 mice per genotype. AU: Arbitrary unit.

Figure 7 :

 7 Figure 7: Impact of RORa deletion on cytokine response upon LPS treatment in BMDM. BMDM from WT and MKO mice were treated with 10 or 100 ng/mL of LPS for 8 hours before analysis of (A) cytokine release in SN by ELISA and (B) gene expression by RT-qPCR. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test n= 4-5 mice per genotype. AU: Arbitrary unit.

Figure 8 :

 8 Figure 8: Impact of RORa deletion on cytokine response upon LPS treatment in BMDM. BMDM from WT and MKO mice were treated with either 50 ng/mL or 10 ng/mL or 100 ng/mL of LPS for 8 hours before analysis of (A-B) gene expression by RT-qPCR. (C) ELISA for IL-1b in SN of BMDM treated with 10 ng/mL of LPS for 8 hours. 400µg/mL of aluminum hydroxide was added 2 hours after LPS stimulation. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test n= 4-5 mice per genotype. NS: Not significant, AU: Arbitrary unit.

Figure 10 :

 10 Figure 10: Effect of RORa deletion in macrophages on HFD-induced obesity. Ten weeks old WT and MKO mice were fed with either a chow or a HFD for 12 weeks. (A) Body weight gain. (B) Weight of inguinal (IngAT) and epidydimal (epiAT) adipose tissues. (C) mRNA expression levels measured by RT-qPCR for the Ob gene in both IngAT and epiAT. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-15 mice per group. NS: Not significant; FC: Fold Change.

Figure 11 :

 11 Figure 11: Effect of RORa deletion in macrophages on HFD-induced obesity and IR. Ten weeks old WT and MKO mice were fed with either a chow or a HFD for 12 weeks. (A) Plasma triglyceride (TG). (B) Plasma cholesterol. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-15 mice per group. NS: Not significant; AU: Arbitrary unit.

Figure 12 :

 12 Figure 12: Effect of RORa deletion in macrophages on HFD-induced obesity and IR. Ten weeks old WT and MKO mice were fed with either a chow or a HFD for 12 weeks. After 10 weeks of diet, mice were fasted for 5 hours and glycemia (A) and insulinemia (B) were measured, (C) then intraperitoneally injected with 1g/kg glucose for a glucose tolerance test (IPGTT). (D) Intraperitoneal insulin tolerance test (IPITT) was performed by injecting 1 IU/kg insulin after 11 weeks of diet and 5 hours of fasting. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-15 mice per group. NS: Not significant; FC: Fold Change.

Figure 13 :

 13 Figure 13: Effect of RORa deletion in macrophages on HFD-induced obesity and IR. Ten weeks old WT and MKO mice were fed with either a chow or a HFD for 12 weeks. (A) Western blot of phospho-AKT Ser473 in skeletal muscle, epiAT and liver. Mice were injected with either PBS or 1 IU of insulin 15 min before sacrifice. Images were cropped for sake of clarity. (B) Quantification of western blot for phospho-Akt in skeletal muscle, epididymal adipose tissue (epiAT) and liver. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-15 mice per group. NS: Not significant; FC: Fold Change.

Figure 14 :

 14 Figure 14: Effect of RORa deletion in macrophages on HFD-induced obesity and IR. Ten weeks old WT and MKO mice were fed with either a chow or a HFD for 12 weeks. (A) mRNA expression levels measured by RT-qPCR for Tnf, Il1b, Il6, and Il10 genes in epiAT. Data are shown as mean ± SEM. 2way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-15 mice per group. NS: Not significant; FC: Fold Change.

Figure 15 :

 15 Figure 15: Effect of RORa deletion in macrophages on liver upon HFD feeding. Ten weeks old WT and MKO mice were fed with either a chow or a HFD for 12 weeks. (A) Representative liver gross morphology. (B) Liver weight. (C) Hepatic triglycerides (TG) content. (D) Hematoxylin & Eosin staining of liver sections and (E) quantification of lipid droplets. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-15 mice per group. NS: Not significant; FC: Fold Change.

Figure 16 :

 16 Figure 16: Effect of RORa deletion in macrophages on liver upon HFD feeding. Ten weeks old WT and MKO mice were fed with either a chow or a HFD for 12 weeks. (A) mRNA expression levels measured by RT-qPCR for Tnf, Il1b, Il6, and Il10 genes in liver. (B) Plasma transaminases activity. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-15 mice per group. NS: Not significant; FC: Fold Change.

Figure 17 :

 17 Figure 17: Effect of RORa deletion in macrophages on liver upon HFD feeding. Ten weeks old WT and MKO mice were fed with either a chow or a HFD for 12 weeks. (A) Sirius red staining of liver sections and (B) quantification of fibrosis. (C) mRNA expression levels measured by RT-qPCR for Col1a1, Col3a1, and Acta2 genes in the liver. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-15 mice per group. NS: Not significant; FC: Fold Change.

Figure 18 :

 18 Figure 18: Effect of RORa deletion in macrophages upon CDAA diet feeding. Ten weeks old WT and MKO mice were fed with either a chow or a CDAA diet for 8 weeks. (A) Body weight gain. (B) Fasting glycemia. (C) mRNA expression levels measured by RT-qPCR for Tnf, Il1b, Il6, and Il10 genes in epiAT. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-17 mice per group. NS: Not significant; FC: Fold Change.

Figure 19 :

 19 Figure 19: Effect of RORa deletion in macrophages upon CDAA diet feeding. Ten weeks old WT and MKO mice were fed with either a chow or a CDAA diet for 8 weeks. (A) Representative liver gross morphology. (B) Liver weight. (C) Hepatic triglycerides (TG) content (D) Hematoxylin & Eosin staining of liver sections and (E) quantification of lipid droplets. Data are shown as mean ± SEM. * p < 0.05 by 2-way ANOVA followed by Sidak's multiple comparisons test. n= 10-17 mice per group. NS: Not significant; FC: Fold Change.

Figure 20 :

 20 Figure 20: Effect of RORa deletion in macrophages upon CDAA diet feeding. Ten weeks old WT and MKO mice were fed with either a chow or a CDAA diet for 8 weeks. (A) Hematoxylin & Eosin staining of liver sections. (B) mRNA expression levels measured by RT-qPCR for Tnf, Il1b, Il6, and Il10 genes in liver. Data are shown as mean ± SEM. * p < 0.05; ** p < 0.01 by 2-way ANOVA followed by Sidak's multiple comparisons test. n= 10-17 mice per group. NS: Not significant; FC: Fold Change.

Figure 21 :

 21 Figure 21: Effect of RORa deletion in macrophages upon CDAA diet feeding. Ten weeks old WT and MKO mice were fed with either a chow or a CDAA diet for 8 weeks. (A) Plasma transaminases activity. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-17 mice per group. NS: Not significant; FC: Fold Change.

Figure 22 :

 22 Figure 22: Effect of RORa deletion in macrophages upon CDAA diet feeding. Ten weeks old WT and MKO mice were fed with either a chow or a CDAA diet for 8 weeks. (A & B) Kinetics of plasma transaminases activity. Data are shown as mean ± SEM. 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-17 mice per group. NS: Not significant; FC: Fold Change.

Figure 23 :

 23 Figure 23: Effect of RORa deletion in macrophages upon CDAA diet feeding. Ten weeks old WT and MKO mice were fed with either a chow or a CDAA diet for 8 weeks. (A) Sirius red staining of liver sections and (B) quantification of fibrosis. (C) mRNA expression levels measured by RT-qPCR for Col1a1, Col3a1, and Acta2 genes in the liver. Data are shown as mean ± SEM. * p < 0.05 by 2-way ANOVA followed by Sidak's multiple comparisons test. n= 10-17 mice per group. NS: Not significant; FC: Fold Change.

Figure 25 :

 25 Figure 25: Quality control of Kupffer Cells (KCs) sorting. (A-F) mRNA expression levels measured by RT-qPCR for the Cd19 (A), Cd3e (B), Adgre1 (C), Clec4f (D), Ly6g (E) and Ccr2 (F) genes in B cells, T cells, KCs and Others sorted from the liver of WT and MKO mice. Data are shown as mean ± SEM. n=5 mice per genotype. AU: Arbitrary unit.

Figure 26 :

 26 Figure 26: Impact of RORa deletion on Kupffer Cells (KCs). (A-B) mRNA expression levels measured by RT-qPCR for the exon 3 of Rora gene in B cells, T cells, KCs, and CD45 + non-T, B or KC (others) sorted from liver (A) and in different macrophage populations (B) from WT and MKO mice. (C) Heatmap

Figure 27 :

 27 Figure 27: Impact of RORa deletion on Kupffer Cells (KCs). (A-C) mRNA expression levels measured by RT-qPCR for Arntl (A) and Rorc (B) genes in different macrophage populations. (C) Rorc/Rora in different macrophage populations from WT mice. Data are shown as mean ± SEM. * p < 0.05 by 2-way ANOVA followed by Sidak's multiple comparisons test. n= 3-6 mice per genotype except for ATM where each dot represents a pool of 3-4 mice. NS: Not significant; AU: Arbitrary unit.

(

  p=0.0367) dysregulated in RORa-deficient alveolar macrophages, in line with earlier results on the role of RORa in other cell types. Taken together, these data indicate that RORa regulate a restricted subset of genes of the alveolar macrophages in basal conditions, despite the high expression level and efficiency of deletion. Impact of RORa deletion in activated lung macrophages and/or pathophysiological conditions remains to be investigated.

Figure 28 :

 28 Figure 28: Transcriptomic analysis of RORa-deficient alveolar macrophages.(A) Volcanoplot and (B) top 10 modulated genes from microarrays performed on alveolar macrophages from lung of 14 weeks old naïve WT and MKO mice. n=6 mice per genotype.

3 .

 3 Impact of Lyz2 deletion on HFD-induced obesity, IR, NAFL and obesity-independent NASH development We found no impact of LysM-Cre-mediated RORa deletion neither on HFD-induced obesity, IR and steatosis nor on CDAA diet-induced NASH. These finding contrast with an earlier report showing that LysM-Cre-mediated RORa deletion increases the susceptibility to HFD-induced NASH 548 , while both studies used the same HFD reference and duration of treatment.Therefore, we suspected that LysM copy number may play a role in this discrepancy, as the only difference between the two independent lines of work is the mouse genotype regarding the LysM locus. The LysM-Cre mice carry an insertion of Cre recombinase into the Lyz2 gene, leading to Cre expression under the control of the Lyz2 promoter and enhancers, but abolishing endogenous Lyz2 expression. While we intentionally maintained similar Cre and Lyz2 expression between WT and MKO by using only hemizygous animals for this locus (comparing Rora + / + Lyz2 Cre / + with Rora fl/fl Lyz2 Cre/+ ), floxed mice (Rora fl/fl Lyz2 +/+ ) were used as WT control and compared with MKO mice missing information about the Lyz2 locus (Rora fl/f Lyz2 Cre/? ) in the earlier study 548 . This latter strategy results in differential Cre and Lyz2 expression between the WT, expressing no Cre, and the MKO mice expressing less or no Lyz2. Thus, MKO mice generation strategy in the earlier study, possess at least one inactivated Lyz2 allele and possibly a homozygous (whole body) Lyz2 deletion. Indeed, based on the described genotyping strategy using a single PCR reaction to analyze Cre gene, it is highly likely that MKO mice 548 were actually also Lyz2-deficient in this earlier study.

Figure 30 :

 30 Figure 30: Effect of Lyz2 deficiency on HFD-induced obesity. Eight weeks old WT, Het, and KO mice were fed with either a chow or a HFD for 12 weeks. (A) Body weight gain. (B) Weight of mice at sacrifice. Data are shown as mean ± SEM. **** p < 0.0001 by 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-12 mice per group.

Figure 31 :

 31 Figure 31: Effect of Lyz2 deficiency on HFD-induced obesity. Eight weeks old WT, Het, and KO mice were fed with either a chow or a HFD for 12 weeks. (A) Weight of subcutaneous/inguinal (IngAT) and (B) epidydimal (epiAT) adipose tissues. Data are shown as mean ± SEM. **** p < 0.0001 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-12 mice per group.

Figure 32 :

 32 Figure 32: Effect of Lyz2 deficiency on HFD-induced IR. Eight weeks old WT, Het, and KO mice were fed with either a chow or a HFD for 12 weeks. After 10 weeks of diet, mice were fasted for 5 hours (A) thereafter, intraperitoneally injected with 1g/kg glucose for a glucose tolerance test (IPGTT). (B) fasting glycemia of the mice at sacrifice. Data are shown as mean ± SEM. ** p < 0.01; **** p < 0.0001 by 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-12 mice per group.

Figure 33 :

 33 Figure 33: Effect of Lyz2 deficiency on HFD-induced IR. Eight weeks old WT, Het, and KO mice were fed with either a chow or a HFD for 12 weeks. mRNA expression levels measured by RT-qPCR for (A) Tnf, (B) Adreg1 (encoding for F4/80), (C) Il1b in epiAT. Data are shown as mean ± SEM. * p < 0.05; ** p < 0.01 by 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-12 mice per group for WT and KO mice. n= 1 that represents a pool of 10-12 mice for heterozygous mice. AU: Arbitrary unit.

Figure 34 :

 34 Figure 34: Effect of Lyz2 deficiency on HFD-induced IR. Eight weeks old WT, Het, and KO mice were fed with either a chow or a HFD for 12 weeks (A) Representative liver gross morphology. (B) Liver weight. (C) Hematoxylin & Eosin staining of liver sections and (D) quantification of lipid droplets. Data are shown as mean ± SEM. *** p < 0.001; **** p < 0.0001 by 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=10-12 mice per group.

Figure 35 :

 35 Figure 35: Effect of Lyz2 deficiency on CDAA diet-induced NASH. WT, Het, and KO mice were fed with either a chow or a CDAA diet for 4 weeks. (A) Body weight gain. (B) Weight of mice at sacrifice. (C) Fasting glycemia of the mice at sacrifice. Data are shown as mean ± SEM. **** p < 0.0001 by 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=5-6 mice per group.

Figure 36 :

 36 Figure 36: Effect of Lyz2 deficiency on CDAA diet-induced NASH. WT, Het, and KO mice were fed with either a chow or a CDAA diet for 4 weeks. (A) Representative liver gross morphology. (B) Liver weight. Data are shown as mean ± SEM. **** p < 0.0001 by 2-way ANOVA followed by Sidak's multiple comparisons test was performed. n=5-6 mice per group.

  are of significant interest in the context of obesity, IR, and advanced NASH, as Lyz2 might possess a therapeutic value. Lysozyme is a b-1,4-N-acetyl-muromoyl-hydrolase, an antimicrobial protein that catalyzes the hydrolysis of the peptidoglycan between Nacetylglucosamine (NAG) and N-acetylmuramic acid (NAM), contributing to the degradation of the both Gram-positive and Gram-negative bacterial cell walls. Hydrolysis of the peptidoglycan by lysozyme leads to release of muramyl dipeptide (MDP) that stimulate Pattern Recognition Receptor (PRR), specifically NOD2, modulating intestinal epithelia and microbiota interactions

  MDMs and PMA-differentiated THP-1 cells were treated with 100 to 200 µM FFAs or 5 µg/mL tunicamycin (Sigma #T7765) for 2 to 16 hours. Inhibitors, including pifithrin-a (Enzo Life Sciences #BML-GR325 ; 20 µM), 4-phenylbutyric acid (PBA) (Sigma #P21005 ; 1 mM), GSK2606414 (Sigma #516535 ; 2 µM), GSK2656157 (Santa Cruz #sc-490341 ; 2 µM), trans-ISRIB (Tocris #5284 ; 1 µM) and salubrinal (Tocris #2347 ; 50 µM), were added 15 minutes before FFAs stimulation and maintained through the experiment. Cell viability for ER stress inhibitors and FFAs was assessed and nontoxic concentrations were selected (Fig.S1A-B). siRNA transfection 2.5 x 10 5 THP-1 cells were transfected by using the HiPerFect Transfection reagent (Qiagen #301705) according to manufacturer's instructions (protocol for suspension cell lines). Predesigned siRNA targeting human IRE1a, PERK, ATF6, CHOP and ATF3 were purchased from Integrated DNA Technologies (TriFECTa DsiRNA Kit). For IRE1a and PERK, THP-1 cells were transfected before PMA differentiation and the treatment with FFAs performed 80 hours post-transfection. For ATF6, PMAdifferentiated THP-1 cells were transfected for 32 hours before FFAs stimulation.

Figure 1 .

 1 Figure 1. SFAs promote GDF15 expression and secretion in macrophages.

Figure 3 .

 3 Figure 3. Role of ISR in SFAs-induced GDF15 expression.

Figure 4 .

 4 Figure 4. Role of CHOP in SFAs-induced GDF15 expression.

Figure 6 .

 6 Figure 6. UFAs prevent SFA-induced GDF15 expression.

Table 1 :

 1 Classification of the diabetes.

  cells, ILC-1 and NK cells contribute type 1 inflammatory milieu by being additional sources of IFNg and IL-12, respectively. Adipocytes and macrophages directly interact with Th1 cells for MHC-II-restricted antigen presentation and TCR-mediated activation. Similarly, B cells directly interact with Th1 cells in a MHC-II-restricted manner to stimulate TCR-mediated activation. In addition, CD8 + T cells directly interact with B cells through TCR and MHC-I-mediated interactions, which stimulate B cells to produce antigen-

	professional antigen presenting cells (APCs) that capture, process, and present antigens to release of the free fatty acids (FFAs), which are caught by the ATMs to be recycled 118 . High
	the adaptive immune cells. Strategically, macrophages are located at diverse anatomic lipid-buffering capacities of the ATMs also capture lipids by the fatty acid transporter CD36 and
	locations, such as body cavities, mucosal surfaces, and in tissues where they are the lipid scavenger receptor MSR1, during the some physiological processes, such as weight-
	transcriptionally programmed to perform diverse tissue-specific functions 107 , such as adipose loss, and fasting 119 . Thus, ATMs restrain ectopic lipid accumulation and peripheral lipotoxicity
	tissue macrophages (ATMs) in the adipose tissue, Kupffer cells (KCs) in the liver, osteoclast through their high lipid-buffering ability to maintain an anti-inflammatory environment. In
	specific IgG that contribute M1-like phenotypic switch of ATM. Neutrophil elastase, MPO, IL1b in the bone, and microglia in the central nervous system. Macrophages are dived into two addition, it has been shown that ATMs recruits preadipocytes by secretion of high-level of
	secreteion by neutrophils and TNFa secretion by gdT cells, supporting M1-like phenotypes of the ATM. subtypes that classically polarized inflammatory (M1) and alternatively polarized reparative osteopontin to induce adipogenesis around dead adipocytes to compensate dead adipocytes ICAM-1, intercellular adhesion molecule 1; ICOS, inducible costimulator; ICOSL, inducible costimulator ligand; IFN, interferon; iNKT, invariant natural killer T cells; LFA-1, leukocyte function-associated (M2) 108 . This early the M1/M2 classification, only accurately describes the in vitro polarization with new ones 120 . Moreover, Buorlier et al. showed that ATMs are active players of the AT
	antigen-1; MCP-1, monocyte chemoattractant protein-1; MHC, major histocompatibility complex; MPO, status of the macrophages that can be obtained by using the combination of the LPS and IFNg remodeling through the extension of a capillary network by release of proangiogenic VEGF-A,
	myeloperoxidase; NK, natural killer cells; RANTES, regulated on activation, normal T-cell expressed treatments for M1 polarization and IL-4 for the M2 polarization 109 . In vivo, the pro/anti-MMP-2, and MMP-9, promoting angiogenesis 121 . Thus, regulation of angiogenesis by ATMs
	and secreted; TCR, T-cell receptor; and TNFa, tumor necrosis factor alpha 98 . inflammatory phenotype represents a broad and heterogenous spectrum with M1 and M2 restricts hypoxia, supplies a sufficient amount of nutrients and oxygen to maintain tissue
	markers, representing extreme cases that we will discuss some examples within the context homeostasis by ATMs.
	1.4.1 Immune cells at homeostasis in white adipose tissue of obesity in the following section (1.4.2) 110 . Intracellular energy metabolism of the
	polarized macrophages utilize glycolysis and pentose phosphate pathway to support a. Monocytes macrophages is a fundamental determinant of their functional response. So, the classically c. Dendritic cells
	Dendritic cells (DCs) are heterogenous, professional antigen presenting cells (APCs) that microbicidal functions, like secretion of lysozyme M, cathepsin proteases, and lipocalin. By Monocytes are circulating, short-lived mononuclear phagocytes and one of the fast-responsive patrol diverse anatomical locations, capture antigens, process and present to the adaptive contrast, the alternatively polarized macrophages employs fatty acid oxidation 111 . Yet, several cells to the inflammation. Monocytes originate from hematopoietic stem cells (HSCs) in the immune cells 122 . The current classification of the DC relies on combined approaches, based recent studies showed that macrophages in different tissue environments adopt a range of bone marrow and subdivided into three distinct subsets based on their surface markers: inflammatory phenotypes through metabolic reprogramming, which we will discuss in detail on surface markers, key gene signature, and ontogeny. DCs are subdivided as conventional classical monocytes (CD14 + CD16 -in human, CX3CR1 int CCR2 + CD62L + CD43 low Ly6C hi , after (see section 1.4.2) 112 . also known as classical DCs (cDCs), plasmacytoid DCs (pDCs), monocyte-derived DCs shortly, Ly6C + , in mice), intermediate monocytes (CD14 int CD16 -in human, CX3CR1 int CCR2 + (MoDCs), and epidermal Langerhans cells 123 , expressing high-level expression of major CD62L + CD43 low Ly6C int , shortly, Ly6C int , in mice), and non-classical monocytes (CD14 -CD16 + ATMs derived from the primitive progenitor cells during the development in the yolk sac and histocompatibility complex class two (MHC-II) in mice 124 and humans (HLA-DR) 125 . cDCs and in human, CX3CR1 high CCR2 -CD62L -CD43 high Ly6C low , shortly, Ly6C -, in mice) 99 . The classical self-renew through proliferation independently from the HSCs at homeostasis 113 , 114 . ATMs pDCs are originates from the bone-marrow resident hematopoietic precursors named Ly6C + monocytes are able to migrate into the tissues through a CCR2/CCL2 are characterized as, CD64 + , CD68 + , F4/80 + , CD11b + , CD206 + , CD301 + , Arg1 + cells in mice ''common DC progenitors'' (CDPs) that is distinct from the one of monocytes/macrophages 126 receptor/chemokine dependent manner 100 . Silva et al. reported minor Ly6C + subset in mouse and CD163 + , CD204 + , CD206 + , CD301 + in humans at homeostasis, represent the most and the tyrosine kinase receptor Fms-related tyrosine kinase 3 (Flt3) is required for their eWAT depot at steady-state 101 . The Ly6C int monocyte population has been identified to display abundant immune cell population in AT 115 . ATMs display an alternatively polarized reparative differentiation in mice 127 as well as in humans 128 , 125 , 129 . The cDCs are able to differentiate transitional monocyte phenotype, which is distinct from the Ly6C + and Ly6 -monocyte subsets phenotype at steady-state and produces high levels of anti-inflammatory molecules, such as into either cDC1 subset under the control of the interferon regulatory factor 8 (IRF8), inhibitor 102 . The non-classical Ly6C -monocyte subset, also known as patrolling monocytes, crawl along of DNA-binding 2 (ID2), and basic leucine zipper ATF-like transcription factor 3 (BATF3) IL-10, transforming growth factor-beta (TGF-b), and Th2-attracting chemokines CCL17 and the vasculature and maintain vascular homeostasis via LFA-1/ICAM-dependent manner under CCL22, favoring resolution of inflammation, tissue repair and remodeling 116 . This subset of transcription factors 130 or IRF4-dependent cDC2 subset 131 . Mouse cDC1 subset is identified physiological conditions in mice, 103 , 104 as well as in human 105 . A recent study reported that monocytes display plasticity and have a potential to differentiate into inflammatory macrophage ATMs express the master regulator of fatty acid oxidation transcription factor peroxisome based on the expression of MHC-II, CD11c, CD8a or CD103 and absence of CD11b and B220.
	or DC subtypes, depending on the positioned tissue environment 106 . proliferator-activated receptor gamma (PPAR-g) to support their intracellular energy
	metabolism and adapted to a lipid-rich milieu 117 . ATMs insure tissue homeostasis through
	b. Macrophages eliminating dying adipocytes and engulfing debris from dead cells, facilitating the cellular
	turnover of these cells. Indeed, a recent study described a cellular process, termed exophagy,
	Macrophages are heterogeneous population of cells that phagocytose pathogens, debris, and providing a mechanism for the removal of dead adipocytes by ATMs. ATMs constitute around
	dead cells, can trigger or regulate inflammation, tissue repair, and wound healing thanks to dead adipocytes, a hydrolytic extracellular compartment, which composed of acidic lysosomal
	phenotypic plasticity, responding to the environmental demands. In addition, macrophages are enzymes. Consequently, this process leads to the degradation of adipocyte fragments and the

  response to stimulation by LPS, CXCL12, and free fatty acids, in mice 180 as well as in humans181 . Lean AT-resident IL-10-producing Bregs originate from B1 subset182 . Nevertheless, these studies also revealed that with obesity Bregs, diminished in AT 180 , 181 , like anti-inflammatory markers at levels similar to lean conditions, suggesting obesity induces a phenotypic switch in ATM polarization 188 . Obesity-induced switch in ATM activation state coupled to the recruitment of inflammatory macrophage clusters from the circulation rather than conversion of resident M2-like macrophages into M1-like ATM is an essential step 189 . A proinflammatory CD11c + macrophage population has also been identified as a marker of insulin resistance in human obesity190 . Importantly, in this study, CD11c + macrophages were also expressing CD206, which is a marker for the M2-like ATMs, illustrating They further confirmed that in humans 193 . Hill et al. reported that obese AT of mice and humans contain multiple distinct populations of ATMs with the unique tissue distributions, transcriptomes, chromatin landscapes, and functions 194 . They identified three discrete ATMs in mice, which are CD11b + CD9 + Ly6C + , CD11b + CD9 -Ly6C -, and CD11b + CD9 - Ly6C + . They described that CD9 + and Ly6C + ATMs are characteristic of obesity, and both of them express CD11c at different levels. However, they assumed that CD9 On the other hand, Ly6C + ATMs homogeneously spread in obese AT. Furthermore, Ly6C + ATMs overexpresses genes associated with angiogenesis and extracellular matrix remodeling while lacking intracellular lipid droplets194 .In a recent study, Jaitin et al. described a novel Trem2 + lipid-associated macrophages (LAMs) in AT195 , possibly similar to that described by Hill et al. as CD9 + macrophages 194 . Importantly, they showed that the genetic ablation of the lipid receptor triggering receptor expressed on myeloid cells 2 (Trem2) in mice regulates the downstream molecular program for the protective functions of the LAMs. Furthermore, Trem2 exhibited to prevents adipocyte hypertrophy, systemic hypercholesterolemia, body fat mass, and glucose intolerance195 . Consistent with that, a distinct subset of the ATMs, the vasculature-associated macrophages (VAMs) identified in WAT at steady-state, adopting inflammatory phenotype in response to metabolic challenges in obesity 101 , presumably corresponds to previously reported monocyte-derived Ly6C + ATMs

	dependent stimulation of M2-like ATMs that improve glucose tolerance of mice in response to g. Regulatory T cells i. Natural Killer T cells cells, somatic hypermutation and gene rearrangement processes lead to the production of a liposome-mediated depletion of visceral ATMs improves metabolic parameters of diet-induced
	HFD feeding 154 . Also, it has been suggested that eosinophils involve in beiging process of wide variety of antibodies against the antigens. Affinity maturation and isotype switching further obese mice, implying a direct role of ATMs in obesity-associated insulin resistance 187 . Lumeng
	WAT via the regulation of transcriptomic profile by the transcriptional repressor Kruppel-like Regulatory T cells (Tregs) are crucial for the maintenance of immunological self-tolerance and Natural killer T (NKT) cells belongs to the innate-like T cell subset and displays both NK cell increase the antibody repertoire 178 . B cells are subdivided into two main subsets B1 and B2 et al. identified a CD11c + macrophage population with the M1-like proinflammatory phenotype
	factor 3 (KLF3) 155 . the prevention of various autoimmune as well as allergic diseases, like rheumatoid arthritis, markers, like NK1.1 and CD56 as well as T cell characteristics, such as ab TCR expression. subsets. Innate like B1 cells are derived from fetal liver and are the principal source of IgM in AT of obese mice, which does not exist in AT of lean mice. Moreover, obese CCR2-KO mice
	psoriasis through negatively regulating B and T cell responses by immunosuppressive cytokine NKT cells recognizes lipids and glycolipids, like a-galactosylceramide, b-D-glucopyranosyl antibodies 179 . B1 cells are abundant in pleural and peritoneal cavities 179 . B2 cells arise from express M2-
	e. Type 2 Innate Lymphoid Cells production (IL-10, TGF-b) 161 . Tissue Tregs represent a unique Treg population compared to the ceramide, isoglobotriosyl ceramide (iGb3) by an MHC-I-like molecule, CD1d. Two subtypes bone marrow progenitors and are produce all IgG isotypes in response to Th cell-mediated
	lymphoid organ resident ones 162 . WAT-resident Tregs have a more restricted TCR repertoire are identified on the basis of the expression of an invariant TCRa chain, which is Va14-Ja18 stimulation and migrate into secondary lymphoid organs, as follicular B cells and splenic
	1 interferon, in response to Type 2 innate lymphoid cells (ILC2) originate from the inhibitor of DNA-binding 2 (ID2) + ILC (limited a-chain diversity and a single b chain) in lean mice than Tregs from lymphoid organs in mouse and Va24-Ja18 in human. The type I NKT cells, also known as invariant NKT (iNKT) marginal zone B cells 179 . Besides antibody production, B cells are also professional antigen-
	viral infections 144 . The mouse eWAT depots mainly contain cDC1 and cDC2 subsets, while the precursors, under the control of GATA-binding protein 3 (GATA3) and retinoic acid receptor-163 . Tissue Tregs originate from the thymus, display tissue-specific transcriptional and epigenetic cells, express the invariant TCRa chain together with definite TCRb chains, which are presenting cells and regulate both innate and adaptive immunity through immunoregulatory
	pDC subset is extremely rare at steady-state. Indeed, the cDC2 subset represents the most related orphan receptor alpha (RORa) transcription factors, in response to IL-33 156 . WAT-programs and have pleiotropic actions, like control of metabolic homeostasis in WAT, Vb8.2,7,2 in mouse and Vb11 in humans. On the other hand, the type II NKT cells, so-called cytokine secretion. It has been reported that AT contains a distinctive population of IL-10-
	abundant DC population in mouse eWAT, at homeostasis, whereas the cDC1 subset defines resident ILC2s maintain local eosinophils and M2-like macrophages by secreting Th2 regeneration process in skeletal muscle 164 . Feuerer et al. showed that CD4 + GATA3 + Foxp3 + diverse NKT (dNKT) cells, display various expression patterns of TCRa and TCRb chains 172 . producing regulatory B cells (Bregs) at steady-state to sustain AT homeostasis and limit obesity-
	only a minor portion 145 . Recently, Wnt and PPARg pathways, which regulate adipocyte differentiation and expansion has been shown to controlled by cDC subsets at homeostasis in VAT. Activation of the Wnt/b-catenin pathway in the cDC1 subset, upregulates PPARg signaling in the cDC2 subset and control adipocyte differentiation as well as expansion in VAT. Thus, the combined action of cDC1 and cDC2 subsets in the regulation of Wnt/b-catenin pathway-dependent PPARg signaling in VAT, displays a tolerogenic phenotype by controlling adipocyte differentiation and expansion in VAT at steady-state, contributing to tissue homeostasis 146 . cytokines, like IL-4, IL-5, and IL-13, as the primary source under homeostasis 157 . Moreover, WAT-resident ILC2s control the beiging of WAT and thermogenesis in humans via methionine-enkephalin peptides production independent from eosinophils or IL-4 receptor signaling 158 . f. CD4 + T cells The second subset of T cells, according to the TCR composition, is the ab T cells that further classified as two main subgroups, which are CD4 + T cells and CD8 + T cells. The development of naïve CD4 + T cells takes place in the thymus. Subsequently, they migrate into secondary Tregs enriched in eWAT of lean mice, while their number strikingly reduced with obesity in both mouse and human, moreover whole-body depletion of Tregs negatively correlates with metabolic parameters, like impaired glucose homeostasis and insulin signaling in WAT 165 . The same group also reported that the master regulator of adipocyte differentiation PPARg is a crucial driver of the accumulation and phenotype of AT-resident Tregs 166 . Moreover, IL-33 the main cytokine promoting the expansion of AT-resident Treg population in the lean state 162 by the activity of the interferon regulatory factor 4 (IRF4) and basic-leucine zipper transcription factor (BATF) transcription factors 167 . Recently, Schmidleithner et al. revealed that AT-resident Tregs suppresses conventional T cells (Tconv) by the enzymatic activity of the hydroxy-At steady-state, the AT contains iNKT cells in both mouse and human 173 that represents a unique tissue-resident iNKT subset with their distinct Th2 cytokine repertoire, such as IL-4 and IL10 compared to the liver and spleen resident subsets in mouse 174 . Lynch et al. also showed that AT-resident iNKT cells are depleted in diet-induced obesity and are restored after weight loss. Moreover, iNKT-deficient mice exhibited enhanced obesity-associated outcomes compared to the control group, and the adoptive transfer of iNKT cells into these obese mice reversed the phenotype. After the identification of CD1d expression in adipocytes and direct interaction between CD1d-expressing adipocytes and iNKT cells 175 , Huh et al. reported that relevant inflammation in Two independent studies revealed that the number of macrophages considerably expands d. Eosinophils Eosinophils are key players in allergic inflammation and mainly, parasitic but also bacterial and viral infections 147 . Eosinophils derived from bone-marrow progenitors that GM-CSF, IL3, lymphoid tissues like spleen and lymph nodes and non-lymphoid organs, such as AT. Under prostaglandin-dehydrogenase (HPDG), which in part mediated by PPARg signaling, adipocytes selectively stimulate AT-resident iNKT cells to mediate anti-inflammatory during obesity within WAT in both mice and humans, which represents more than 50% of the the lean status, AT harbors not only naïve CD4 + T cells, but also dominated by several effector contributing tissue homeostasis 168 . responses and attenuate excess pro-inflammatory responses in HFD-induced obese adipose WAT immune population. Weisberg et al. reported that macrophage content of various WAT T-helper (Th) lineages, including Th2 cells, and Tregs that coordinate tissue homeostasis 159 . tissue by using an adipocyte specific CD1d-deficicient mouse model 176 . It has also been depots positively correlates with BMI and adipocyte size. Moreover, they also showed that
	and IL-5 are crucial mediators of the eosinophil development and survival 148 . Eosinophils consist of primary granules, which are filled with hydrophobic protein family Galectin-10 (Charcot-Leyden crystals) and specific/crystalloid granules that are contain vast quantities of toxic and basic proteins, including lysozyme M, major basic proteins (MBP), eosinophil-derived neurotoxin (EDN), and eosinophil cationic protein (ECP), contributing to fight against pathogens 149 . Eosinophils engage another defense mechanism against microbial pathogens, called catapults or extracellular eosinophilic traps (EET) in that mitochondrial DNA together with granule proteins form a structure to kill pathogens in a ROS-dependent manner 150 , 151 . Under physiological conditions, eosinophils are mostly present in skin, respiratory and gastrointestinal tract as well as in several other tissues, such as adipose tissue, liver, kidney where exhibit protective and immunoregulatory functions to maintain tissue homeostasis 152 . At steady-state VAT and SAT depots, harbor a higher number of eosinophils, than in obesity h. gdT cells suggested that AT-resident iNKT cells help to maintain AT-resident Tregs by being an IL-2 macrophages are the primary sources of TNFa and other proinflammatory cytokines in obese AT-resident Th2 cells regulated by the transcription factor GATA3 and produces a high level of Members of the innate-like T cell family, gdT cells are abundant at barrier surfaces, including source 177 . WAT 183 . Xu et al. suggested that macrophages in WAT play an active role in morbid obesity IL-4, IL-5 and IL-13 cytokines, which are the main cytokines to maintain M2-like phenotype for skin, lung, gastrointestinal, and genital tracts 169 . In a recent study, Kohlgruber et al. reported in that macrophage-related inflammatory cytokines contribute to the pathogenesis of obesity-ATMs. Nearly decades ago, Winer et al. highlighted the significance of the GATA3 + Th2 cells that CD4 -C D8 -double negative gdT cells, which expressing mostly Vg4 and enriched in various j. B cells induced insulin resistance 184 . Weisberg et al. showed that antagonism or deficiency of the C-by first observing in a mouse model that the absence of T and B lymphocytes (Recombination activating gene, Rag-deficient) prone to develop more severe obese and insulin-resistant phenotype than their WT littermates, in response to HFD-feeding. Secondly, they showed that CD4 + T cells displaying a Th2 profile following the adoptive transfer in obese Rag-deficient mice and converted HFD-induced metabolic outcomes. Moreover, they revealed that transferring of CD4 + T cells lacking a transcription factor for Th2 polarization, which is the signal transducer and activator of transcription 6 (STAT6), led to Th2 cell depletion in AT and loss of protective effects against HFD-feeding 160 . C motif chemokine receptor-2 (CCR2), which is the main chemokine for monocyte and VAT depots at steady-state in mice, as well as in human omental AT depots that control age-B cells play a crucial role in host defense through immunoglobulin (antibody) production, which macrophage recruitment, reduced food intake and attenuated development of obesity in mice dependent regulatory T cell (Tregs) expansion through promoting preadipocytes/stromal cell recognize and eliminate pathogens but also activates the CD8 + T, and CD4 + T cells via TCR, upon HFD feeding. CCR2-deficient obese mice also exhibit alleviated hepatic steatosis and production of IL33 and control core body temperature in response to environmental fluctuations MHC-I, and MHC-II-mediated interactions as well as stimulates the ATM polarization towards improved systemic glucose homeostasis through decrease macrophage content and the by the production of IL-17A and TNFa 170 . Also, Goldberg et al. suggested that the beneficial M1-like phenotype. B cells produce five immunoglobulin isotypes that include IgA, IgD, IgE, inflammatory profile of the WAT, evidencing the importance of the recruitment of circulating impact of the short-term ketogenic diet feeding on metabolic control is mediated by the IgG, and IgM, which are secreted or expressed on their cell surface as the main components monocytes besides macrophages in this pathophysiology 185 . Nagareddy et al. revealed that activation of AT-resident gd T cells with a specific gene signature, supporting tissue repair and of B cell receptors (BCR) that bind epitopes of protein, carbohydrate, or nucleic acid antigens adipose tissue-derived S100A8/A9 stimulates ATMs by TLR4/MyD88 and NLRP3 homeostasis 171 . 178 . Upon either a direct antigen engagement through BCR or Th cell-mediated activation, B inflammasome-dependent IL-1b production that interacts with IL-1 receptor on bone marrow
	where their quantity is very low. However, is reversed by a low-calorie dietary intervention 153 . cells initiate serial of molecular processes, like migration, proliferation, and differentiation into progenitors, inducing the monocytosis in obesity 186 . Feng et al. showed that clodronate
	Eosinophils in AT contributes metabolic homeostasis through IL-4 and IL-13 production antibody-producing plasma cell 178 . Through the development of antibody-producing plasma

182 .

Immune drivers of inflammation in obese white adipose tissue a. Adipose tissue macrophages, recruited monocytes and macrophages the heterogeneity of ATM populations that exist in obesity, well beyond M1 and M2, besides changes in macrophage numbers, according to the pathophysiological states. In fact, the expansion of AT across models of obesity has induces a program of lysosome biogenesis in ATMs, which is associated with lipid catabolism but not a classic inflammatory phenotype, as explained in the AT homeostasis part, lipid buffering capacities of ATMs maintain tissue homeostasis

191

. Krazt et al. identified that obesity induces a metabolically activated phenotype distinct from the classical activation of ATMs in mice and humans by using a proteomic approach. These metabolically activated macrophages contain a combination of M1-like proinflammatory markers and M2-like lipid metabolism markers 192 . Catecholamine norepinephrine (NE) is a monoamine neurotransmitter that regulates thermogenesis and lipolysis of the WAT. A recent study discovered a new subset of sympathetic nerve associated macrophages (SAMs) in WAT that mediates NE transport and degradation by expression of solute carrier family 6 member 2 (SLC6A2) and monoamine oxidase A (MAOA). They showed that activation of the sympathetic nervous system upregulates NE uptake by SAMs, as a result, SAM exhibits a pro-inflammatory phenotype. Moreover, they revealed that SAM population is rising with two mouse models of obesity, and Slc6a2-deficient SAMs increase brown adipose tissue mass, cause beiging of WAT, stimulate thermogenesis, leading to significant weight loss in obese mice. + ATMs are most similar to the CD11c hi population identified in prior studies. According to their findings, CD9 + and Ly6C + ATMs are both monocyte-derived that CD9 + ATMs predominantly found around CLSs and contain high amounts of intracellular lipids in lysosome-like structures and possess an inflammatory chromatin landscape.

196 .

  play central roles in both the development of SS and the subsequent progression to NASH.Mitochondrial defects, ER stress and oxidative stress link lipotoxicity and glucotoxicity with SS and NASH. When inflammation prolongs, fibrogenesis starts with HSCs as key players. Aggravation of fibrogenesis that may result in cirrhosis may represent an impaired mechanism of tissue regeneration, during the replacement of hepatocytes subjected to cell death or apoptosis is unsuccessful. 275 , 276 , 277 , 278 . Regarding this, Wei et al. reported that a large amount of non-obese individuals with NAFLD carry variants in the PNPLA3 allele compared to obese NAFLD patients, suggesting that PNPLA3 polymorphism is an independent risk factor for lean NAFLD by using a population-based study in China 279 . In addition, Adams et al. reported that the in two independent studies comparing non-obese NASH individuals with BMI-matched control patients and obese NASH patients 283 ,284 . In line, high cholesterol supplementation to the diet is one of the widely-used strategies to induce NAFLD in animal models without affecting obesity parameters285 , 286 . Overabundant cholesterol induces de novo lipogenesis by stimulating the LXR and oxysterol-dependent SREBP-1C pathway 287 .High fructose intake, especially the consumption of soft drinks, which contains large amounts of fructose corn syrup, has been associated with NAFLD, as fructose is mainly metabolized in the liver288 . NAFLD has been reported in non-obese/lean individuals who display some metabolic abnormalities, such as insulin resistance, dyslipidemia, and hypertension 289 . This group of patients with a normal weight are known as metabolically obese and exhibit visceral adiposity more than subcutaneous adiposity 290 . Indeed, visceral adiposity has been recognized as an independent risk factor for lean NAFLD291 . In a large cohort study,Sinn et

	Abbreviations: ER, endoplasmic reticulum; FFAs, free fatty acids; ILs, interleukins; HSCs, hepatic
	stellate cells; IR, insulin resistance; NASH, nonalcoholic steatohepatitis; SS, simple steatosis 271 .
	2.2 Pathogenesis of obesity-independent non-alcoholic fatty liver
	diseases
	cholesteryl ester transfer protein (CETP) gene polymorphisms are the strong risk factor for the
	lean NAFLD 280 . Furthermore, a polymorphism in sterol regulatory element-binding factor 2
	(SREBF-2) gene predisposes to lean-NAFLD 281 . Moreover, a single nucleotide polymorphism

Even though NAFLD strongly correlated with obesity, lean individuals can also suffer from NAFLD, known as lean NAFLD or non-obese NAFLD that is mostly found in the Asian population

272

. Several constituents have been associated with the pathophysiology of obesityindependent NAFLD, including genetic factors, diet, metabolic abnormalities, infectiousinflammatory disorders, and certain drugs 273 . Genetic polymorphisms in genes related to lipid metabolism have been implied as significant contributing factors in lean NAFLD patients. First, Romeo et al. revealed that genetic variations in the patatin-like phospholipase domaincontaining protein 3 (PNPLA3) gene contribute to ancestry-related and inter-individual differences in hepatic fat content, as they found a variant allele (rs738409) that positively correlates with hepatic TG content and inflammation. In contrast, another variant allele (rs6006460), negatively correlates with this phenotype as identified by using a genome-wide association study in a population consisting of Hispanic, African American, and European American individuals

274

. Subsequent studies further discovered that the variants in the PNPLA3 gene are not only correlated with hepatic TG content but also with NASH, fibrosis, and hepatocellular carcinoma dependent or independent from obesity, supporting lean NAFLD phenotype in transmembrane 6 superfamily member 2 (TM6SF2) allele is associated with hepatic TG content and fibrosis independently from age, obesity, insulin resistance, and PNPLA3 genotype 282 . Dietary high cholesterol intake was proposed as a factor contributing to lean NAFLD phenotype, al. found that lean NAFLD is a higher risk factor for incidence of diabetes than the presence of overweight/obesity without NAFLD, suggesting that individuals with lean NAFLD are more prone to develop metabolic abnormalities 292 . Chronic hepatitis C and B virus infections are the most common reasons for liver complications with prevalence of hepatic steatosis in infected individuals being about 50% of patients and with prevalence of progression into cirrhosis, and hepatocellular carcinoma being even higher 293 . Moreover, another cause of morbidity and mortality in chronic liver diseases is the human immunodeficiency virus (HIV) infection that leads to the whole spectrum of NAFLD and can co-exist with the chronic hepatitis C virus, worsening the phenotype 294 . Drug-induced steatosis is one of the well-recognized pathologies in NAFLD. Identified steatogenic drugs include acetaminophen, acetylsalicylic acid, amiodarone, diltiazem, tamoxifen, and several others 295 .

  297 , 298 . Firstly, Le Roy et al. demonstrated that gut microbiota directly modulates NAFLD development independent from obesity by using fecal microbiota transplantation (FMT) from HFD-responder and not responder mice to the germfree mice 299 . Furthermore, in a recent study,Mouries et al. showed that fecal microbiota transplantation from the HFD-fed mice into the germ-free mice causes dysbiosis-induced NASH development through WNT/b catenin signaling 300 . These findings imply that the effects of the diet on microbiome composition are able to trigger the NASH pathogenesis in the absence of the other factors related to HFD-feeding. The methionine choline-deficient (MCD) diet is another commonly used approach to induce NAFLD in experimental animals to

investigate obesity-independent molecular mechanisms of the disease. It has also been reported that MCD diet-feeding leads to alteration of gut microbiota and metabolome with dysbiosis in mice

301

. Interestingly, a recent study, using microbiota depletion with broadspectrum of antibiotic treatment, suggested that intestinal microbiota protect against MCD dietinduced steatohepatitis 302 . Moreover, Duarte et al. by comparing obese and lean patients with or without NASH, reported that gut-microbiome composition in lean individuals with NASH associated with liver damage independent from caloric intake in a small study awaiting confirmation

303

. Data regarding NAFLD and gut microbiota independently from obesity are quite limited. Recently, Yuan et al. observed that high ethanol-producing bacterial strain

  Figure 10: Crosstalk between hepatic stromal and immune cells in NAFLD. Liver contains a collection of immune cells. These include KCs, neutrophils, DCs, MCs, resident lymphocytes, hepatocytes, and LSECs. KCs, DCs, MCs, hepatocytes, and LSECs detect the presence of gut-derived P/MAMPs, endogenous DAMPs, and excessive metabolites mainly through PRRs, resulting in the increased release of proinflammatory cytokines and chemokines. These stressors also up-regulate expression of adhesion molecules in LSECs and, in combination with chemokines, stimulate recruitment of neutrophils and monocytes to the liver. Activated neutrophils initiate liver damage mainly by releasing enzymes and ROS. Apart from releasing proinflammatory cytokines, activated DCs also present antigens to T cells and initiate adaptive responses; KCs and hepatocytes regulate release and endocytosis of APPs, thus extending their innate immune function to extrahepatic organs; and KCs, MCs, and hepatocytes increase expression of MMPs, Ang II, TGF, and HGF to stimulate HSC activation and LF. In addition, innate immune signals also mediate metabolic changes (e.g., lipogenesis and IR) and cell apoptosis, pyroptosis, or necrosis in hepatocytes. KCs and LESCs express high levels of SR, which clears circulating molecules and organisms and is considered a critical mechanism that triggers the innate immune response. Innate-like lymphocytes, including NKs, ILCs, iNKTs, and MAITs, also generate multiple cytokines and influence their local microenvironment of the liver. Together, these events result in liver steatosis, inflammation, and fibrosis and lead to NASH and advanced complications. distinct, self-renewal origin in EMPs 318 . Recently, Scott et al. revealed that the Clec4f surface marker is specific to KC, allowing to distinguish from the other macrophage subsets. Authors also showed that bone marrow-derived monocytes display KC-like phenotype in response to diphtheria toxin-mediated KC-depletion 319 . Sakai et al., in a recent and provoke T cell hypo-responsiveness associated with expansion of Treg population even in homeostasis compared to splenic DCs 333 .

	313 . Kupffer cells are liver-resident macrophage population, which represents a majority of total 2.4.1 Immune guardians of homeostasis in liver a. Kupffer cells body macrophages and a sheer volume of hepatic non-parenchymal cell proportion in homeostasis that estimated to 80% and 20%, respectively 314 . Similar to other tissue-resident macrophages, the KCs primarily and transiently originate from c-Kit lo CD41 lo primitive progenitors, in the yolk sac under the control of PU.1 transcription factor early in the mammalian development (E7.5) 315 . Following the formation of the heart and fetal cardiovascular system (E8-E8.5), c-Kit + CD41 + CD93 + FcgII and FcgIII + CD45 lo hematopoietic progenitors, known as erythro-myeloid precursors (EMPs), derived from the yolk sac endothelium in a Runx-1-dependent manner, are seeded into the fetal liver at E9 and give rise to the KCs 316 . At the end of gestation, the hematopoietic stem cells (HSCs) migrate into the study, also revealed that diphtheria toxin-induced KC depletion drives liver expression of several factors, including the delta-like canonical Notch ligand 4 (DLL4), TGF-b, and desmosterol, which promote KC identity in bone marrow-derived monocytes by re-programming the transcriptomic landscape of KC-identity regulator, liver-X receptor (LXR) 320 . Thus, KCs are identified as CD11b + CD11c int F4/80 hi CD64 + CD68 + Clec4f + (C-type lectin domain family 4, member f) cells in mice and CD68 + CD14 + in humans 321 . Presumably because of their non-monocytic origin at homeostasis, KCs are uniquely do not express fractalkine receptor CX3CR1, as reported previously 322 . Recently, Freitas-Lopez et al. In homeostasis, liver contains the cDC1, cDC2, and pDC subsets that have been found in the portal triad, centrilobular vein, and space of Disse, and represent 1% of the total hepatic immune population 332 . Recently, a distinct subset of DCs has been identified with the particular morphological hallmarks, which possess broader and much more of numerous dendrites within The liver is the only tissue to harbor a vast quantity of natural killer cells (NKs) in the body, which approximately represent 50% of total hepatic lymphocytes, which are sentinel for viral and bacterial infections. NK cells regulate hepatic immune response both at homeostasis and pathological circumstances 334 . Indeed, liver is enriched by either hepatic-resident NK (hNK) cells and circulating NK (cNK) cells, which are distinguishable through the differential expression of the CD49a + DX5 -and CD49a -DX5 + , respectively in mice 335 . Development of the space of Disse, being the CX3CR1 c. Natural Killer Cells hNK cells highly depends on the T-bet transcription factor, while cNK originates from Eomes

Abbreviations: CCL2, C-C motif chemokine 2; HGF, hepatic growth factor; MAMPs, microbe-associated molecular pattern molecules; ROS, reactive oxygen species; TF, transcriptional factor; Th1, T helper 1 bone-marrow and take the place of the fetal liver as the site of hematopoiesis throughout the adult life 317 . Thus, EMP-derived tissue-resident macrophages are partly or entirely replaced by the HSCs-derived cells in the course of development except for microglia and KCs, which are maintaining a confirmed by CXCR1 and F4/80 double staining and intravital imaging technique that at steady-state KCs do not express CX3CR1 308 . The principal function of the KCs is that phagocytose systemic and gut-derived pathogens from the bloodstream to sustain homeostasis at steady-state 323 . KCs contribute to immune homeostasis by inducing Treg response and priming tolerogenic CD8 + T cells

324, 325

. In addition to that KCs regulate iron metabolism through eliminating hemoglobin-haptoglobin complexes 326 and erythrocytederived hemoglobin-containing vesicles from the circulation through the CD163 scavenger receptor 327 , likewise by modulating the hepcidin expression through IL-6-induced STAT3 signaling, which is the master regulator of body iron balance in homeostasis 328 , 329 . Moreover,

Wang et al.

showed that the cholesteryl ester transfer protein (CETP), which is the regulator of high-density lipoprotein (HDL) and very-low-density lipoprotein (VLDL) levels in plasma mainly produced by KCs, suggesting KCs plays a role in cholesterol metabolism

330

. In addition to KCs, the hepatic portal triad-resident Ly6C hi monocyte-derived ferrotorpin-1-expressing macrophages participate cholesterol and iron metabolism at steady-state in mice 331 . b. Dendritic Cells + cells 322 . Hepatic DCs originate from the HSCs and present unique characteristic features by displaying a tolerogenic and immature phenotype with lesser endocytic capacity, low MHC-II, and co-stimulatory molecule expressions at steadystate 332 . Furthermore, hepatic DCs have been shown to exhibit higher sensitivity to LPS-induced maturation

336

. Recently, several new transcription factors were found to be necessary for the maintenance of the NK cells among the aryl hydrocarbon receptor is specific to the hNK cells, while the binterferon gene positive regulatory domain 1-binding factor (BLIMP1) and homologue of BLIMP1 in T cell (HOBIT) are common to both subsets 337 , 338 . Functionally cNK cells primarily produce IFNg, whereas hNK cells produce a wide variety of cytokines and chemokines, including IFNg, TNFa, CCL3, CCL5, and CXCL16 in response to microbial stimulation

339

. The liver-resident NK cell subset has also been reported in humans as CD49 + NK cells and their development is likewise dependent upon T-bet expression 340 . NK cells kill the HSCs in an inhibitory receptor NKG2D-dependent manner, thereby ameliorating fibrosis and contributing to homeostasis in mice as well as in humans 341 , 342 . d. gdT cells gdT cells reflect nearly 20% of the total hepatic T cell population at the steady-state and contribute homeostasis by producing mainly IL-17 that stimulates stromal cells to secrete IL-33, retaining Tregs 343 . Recently, Li et al. showed that activation, survival, and proliferation of the hepatic gdT cells variable with gut microbiota composition and highly dependent upon hepatocyte-expressed CD1d receptor, apart from the TLRs or IL1/IL23 receptor signaling 344 .

Table 3 :

 3 Classification of human nuclear receptor super family.

	Family	Common name	Abbreviation	Gene	Ligand
		Dosage-sensitive sex reversal-adrenal
	0B	the X chromosome, Gene 1 hypoplasia congenital critical region on	DAX1	NR0B1	Orphan
		Short heterodimeric partner	SHP	NR0B2	Orphan
	1A	Thyroid hormone receptor-a Thyroid hormone receptor-b	TRa TRb	THRA THRB	Thyroid hormones Thyroid hormones
		Retinoic acid receptor-a	RARa	RARA	Retinoic acids
	1B	Retinoic acid receptor-b	RARb	RARB	Retinoic acids
		Retinoic acid receptor-g	RARg	RARG	Retinoic acids
		Peroxisome proliferator-activated receptor-a	PPARa	PPARA	Fatty acids
	1C	Peroxisome proliferator-activated receptor-b	PPARb	PPARD	Fatty acids
		Peroxisome proliferator-activated receptor-g	PPARg	PPARG	Fatty acids
	1D	Reverse-Erb-a Reverse-Erb-b	REV-ERBa REV-ERBb	NR1D1 NR1D2	Heme Heme
		Retinoic acid-related orphan-a	RORa	RORA	Sterols
	1F	Retinoic acid-related orphan-b	RORb	RORB	Sterols
		Retinoic acid-related orphan-g	RORg	RORC	Sterols
		Farnesoid X receptor-a	FXRa	NR1H4	Bile Acids
	1H	Farnesoid X receptor-b Liver X receptor-a	FXRb LXRa	NR1H5P NR1H3	Orphan Oxysterols
		Liver X receptor-b	LXRb	NR1H2	Oxysterols
					1α,25-
		Vitamin D receptor	VDR	VDR	dihydroxyvitamin D3
	1I	Pregnane X receptor	PXR	NR1I2	Endobiotics and xenobiotics
		Constitutive androstane receptor		NR1I3	Xenobiotics
	2A	Hepatocyte nuclear Factor-4-a Hepatocyte nuclear Factor-4-g	HNF4a HNF4g	HNF4A HNF4G	Fatty acids Fatty acids
		Retinoid X receptor-a	RXRa	RXRA	9-Cis retinoic acid
	2B	Retinoid X receptor-b	RXRb	RXRB	9-Cis retinoic acid
		Retinoid X receptor-g	RXRg	RXRG	9-Cis retinoic acid
	2C	Testicular Receptor 2 Testicular Receptor 4	TR2 TR4	NR2C1 NR2C2	Orphan Orphan
		Tailless homolog orphan receptor	TLX	NR2E1	Orphan
	2E	Photoreceptor-cell-specific nuclear receptor	PNR	NR2E3	Orphan

Table 3 :

 3 Classification of the human NRs together with the gene names and their activating ligands 453 .

  Acid Receptor-related Orphan Receptor Alpha as aMetabolic RegulatorPrimarily, RORa has been shown to activate apolipoprotein A-I, which is the principal component of the HDL that transports cholesterol from the periphery to the liver and inhibits excessive cholesterol accumulation in the arterial walls, suggesting a regulatory role for RORa in the plasma cholesterol level498 . Subsequent studies have also demonstrated that RORa regulates expression of several gene involved in lipid metabolism, including apoC-III in humans and mice 499 , apo-AV in humans 500 , and the fibroblast growth factor-21 (FGF-21) in human liver cancer cell line HepG2 cells 501 . Cholesterol, cholesterol derivates, like cholesterol sulfate, and oxysterols have been identified as the potential endogenous ligands for RORa 502 , 503 . Rora gene, which hereupon are known as, RORa sg/sg mice. A spontaneous mutation leads to a shift in the reading frame, causing a premature stop codon within the LBD 510 . This discovery highlighted the significance of RORa in Purkinje cell development of the cerebellum.Steinmayr et al. generated RORa-deficient mice by using a targeted insertion of a lacZ reporter gene vector, encoding beta-galactosidase that replaced the second zinc finger of the DBD of RORa. The generated mice displayed a staggerer phenotype 511 . Subsequently, this validation initiated a comprehensive analysis of the staggerer mice to seek for functional properties of the RORa. Mamontova et al. revealed that lipid metabolism was altered in staggerer mice with low levels of total plasma HDL, apoA-I, and apoA-II observed at steady-state, leading to severe atherosclerosis development in response to atherogenic diet feeding 512 . On the other hand, the Srebp-1c and fatty-acid synthase, which are the key genes for the regulation of lipid homeostasis are dysregulated in staggerer mice, leading to a lower AT masses and hepatic TG content, suggesting a protective role against obesity 513 . Relatedly, staggerer mice are protected from HFD-induced obesity, IR, and NAFLD 514 . One of the underlying mechanisms accounting for this protection is attributed to increased thermoregulation in the SAT and BAT depots of the staggerer mice 515 . Consistent observed, leaving open the question about how RORa influences NASH 524 .Besides, in humans, mutations in the RORA gene have been associated with obesity 525 , T2D 526 , and liver diseases 527 .

	metabolic parameters 517 , 518 . Concomitantly, the development of new synthetic ligands that
	include the SR1078 (RORa and RORg double agonist) and JC1-40 (RORa agonist) also
	identified the benzene sulfonamide (T0901317) as a first high-affinity synthetic RORa and provided evidence for a role of RORa in IR and NAFLD by modulating endoplasmic reticulum
	RORg ligand that suppresses the G6Pase gene expression via inhibition of the SRC-2 stress and hepatic oxidative stress 519 , 520 . Recently, to decipher the precise function of RORa
	recruitment by RORa in HepG2 cells 507 . The same group also identified that the 7-a-in NASH pathogenesis several independent groups generated hepatocyte-specific RORa-
	hydroxycholesterol (7-a-OHC), which is the intermediate molecule of the bile acid metabolism, deficient mice. Firstly, Zhang et al. showed that hepatocyte-specific RORa/g-double knock-out
	acts as a natural inverse agonist of the RORa by repressing expression of the ROR target mice up-regulate the expression of lipogenic genes at a definite time of day (circadian),
	genes, such as the G6Pase and phosphoenolpyruvate carboxykinase (PEPCK) 508 . highlighting the importance of the time in a day, as a key parameter in the treatment of liver
	diseases 521 . Secondly, Kim K. et al. determined that hepatocyte-specific deletion of RORa
	In 1962, Sidman et al. reported several spontaneous mutant mice with the neuropathological leads to dysregulation of PPARg signaling and increases hepatic glucose and lipid metabolism

Since altered cholesterol metabolism or transport observed in aging. RORa has been involved to atherosclerosis and Alzheimer's diseases, RORa has been implied to possesses protective effects in the vascular system by modulating intracellular cholesterol content

504

. Indeed, in a recent study, Choi et al. determined that the cholesterol 25-hydroxylase (CH25), the 25hydroxycholesterol 7-hydroxylase (CYP7B1)-RORa axis of cholesterol metabolism in chondrocytes is a catabolic regulator of osteoarthritis pathogenesis, which is one of the most common form of the age-related degenerative whole-joint disease 505 . Additionally, Chopra et al. identified that hepatic gluconeogenesis, in response to fasting, regulated by RORa and the transcriptional co-activator steroid receptor co-activator-2 (SRC-2), through the modulation of the rate-limiting enzyme glucose-6 phosphatase (G6Pase) expression 506 . Inline, Kumar et al. features, which they called them staggerer mice as they exhibited cerebellar defects leading to severe ataxia, motor defect, and tremor in a stock of obese mice at the Jackson Memorial Laboratory in 1955 509 . A few decades later, Hamilton et al. identified the mutant gene in staggerer mice as the with this finding, recently, Monnier et al. determined that RORa controls thermogenesis-related gene expression, which are overlapping with those previously published genes, in the inguinal and perigonadal WAT depots via in a circadian-dependent manner 516 . Nonetheless, several additional defects were found in staggerer mice, which makes poorly suited for the precise delineation of pathophysiological mechanisms. Abnormalities include thymopoiesis and lymphocyte development, evidenced by the reduced spleen and thymus masses, as well as hyper induction of the cytokine secretion by macrophages that might directly impact on in response to HFD feeding 522 . Another group suggested that lack of RORa in hepatocytes leads to the development of severe NASH due to mitochondrial dysfunction in HFD-fed mice 523 . Nevertheless, in an independent study, no effect of hepatocyte-specific RORa deletion on NASH was

Table 4 )

 4 1. Generation of macrophage-specific RORa knock out miceWe generated mice harboring a floxed allele of Rora (Rora fl/fl ) by flanking exon 3 with two loxP Rora fl/fl mice were crossed with LysM-Cre transgenic mice (Jackson laboratory) in which Cre recombinase is expressed under the control of endogenous Lyz2 promoter. Littermates RORa-deficient (MKO, Rora fl/fl Lyz2 Cre/+ ) and WT (Rora +/+ Lyz2 Cre/+ ) mice were generated by crossing Rora fl/+ Lyz2 Cre/Cre with Rora fl/+ Lyz2 +/+ mice. All mice were and the following cycling conditions: 1 cycle at 94°C for 3 min; 35 cycles at 94°C for 1 min, 63°C for 1 min, 72°C for 90 s; and 1 cycle at 72 °C for 10 min; hold at 4°C. Samples were separated by gel electrophoresis on a 1.5% agarose gel. Lyz2 +/+ gave a single band at 350 bp for Lyz2 PCR while Lyz2 Cre/Cre gave a single band at 700 bp for Cre PCR. Lyz2 Cre/+ gave bands for both Lyz2 and Cre PCR.

	sequences. Briefly, a targeting vector containing loxP sites, an FRT-floxed neomycin cassette
	and homologous regions surrounding exon 3 was constructed and transfected in embryonic
	stem (ES) cells derived from 129/Sv. After screening for homologous recombination by
	southern blot and PCR, ES cells were injected into C57BL/6 blastocysts. Neomycin cassette
	was removed in vivo by using FLP deleter mice in C57BL/6 background. Finally, mice were
	backcrossed with C57BL/6J mice for at least six generations. To achieve the deletion of RORa
	in myeloid cells, genotyped twice.
	2. Mouse genotyping

DNA was extracted from tail with REDExtract-N-Amp Tissue PCR Kit (Sigma, #XNAT-1000RXN). Floxed Rora was detected by PCR with the Rora genotyping primers (Supplementary table

1

) and the following cycling conditions: 1 cycle at 94°C for 3 min; 35 cycles at 94°C for 30 s, 55°C for 30 s, 72°C for 1 min; and 1 cycle at 72 °C for 10 min; hold at 4°C. Samples were separated by gel electrophoresis on a 1.5% agarose gel. Rora +/+ gave a single band at 250 bp, Rora fl/f at 340 bp and Rora fl/+ had both bands. Endogenous Lyz2 and Cre were detected with the Lyz2 genotyping and Cre genotyping primers respectively (

Table 5 :

 5 List of the antibodies used in cell sorting.

  RORa, KCs were the only macrophage population without transcriptional effect on the ROR target gene Arntl. We found no compensatory expression of other ROR genes in MKO, but we evidenced a high level of Rorc expression specifically in KC that might offset the RORa deletion. The redundancy between ROR proteins is well established 541 , 102 , 521 . Hepatocytes express high levels of RORg in addition to RORa 521 . It was shown that a single deletion of RORa or RORg in hepatocytes affects only 2 and 6 transcripts, respectively in whole liver transcriptome, while RORa/g double deletion leads to a broader effect with 299 genes affected, unambiguously demonstrating the redundancy between RORa and RORg in hepatocytes 521 . Such a redundancy might be at play in KCs and further investigation with a double RORa/g double deficient mouse model might address this question. Moreover, usage of the new KCspecific Clec4f-Cre mouse line would improve the specificity towards KC and may result in a better deletion efficiency than the one reached with the LysM-Cre mice 319 .It is worth noting that the LysM-Cre mice model gives rise to a variability in deletion efficiency among the different macrophage populations, as previously reported555 . In our mouse model, we observed the highest deletion of Rora in lung macrophages (94%) and the lowest in Kupffer cells (KC, 46%), while the deletion in other macrophage populations was around 75%. Despite the fact that a lower deletion efficiency occurs in KC compared to other macrophage populations using this Cre model, different groups succeeded to demonstrate a role of several genes, such as Pparg 556 ,Tlr9 557 , and Il4ra 558 on NAFL/NASH development by employing the same LysM-Cre-driven gene deletion. These findings led us to conclude that RORa expressed by macrophages is not a major player in NASH development, unlike what was previously reported by Han and colleagues who employed the same LysM-Cre-based deletion strategy

548

. Furthermore, using scRNA-seq technology, heterogeneous and novel macrophage populations have been identified at basal sate as well as during onset and progression of obesity, IR, and NAFLD leading to determination of tissue-specific macrophage signatures (i.e., WAT, liver) prompting for more elaborated techniques than LysM-Cre-mediated deletion

  CORO6, and CORO7 563 . Based on phylogenetic analysis coronins are subdivided into 3 types 564 . Coronins display distinct cell and tissue expression patterns.The best-studied type I coronin, Coro1a is highly enriched in several immune subsets that include neutrophils, macrophages, and T cells. Coro1a is involved in the generation of microbicidal superoxide burst in neutrophils by binding to p40phox, the cytosolic subunit of NADPH oxidase complex 565 . Moreover, Coro1a is required for chemotaxis and phagocytosis in human neutrophils 566 . Coro1a has also been associated with neutrophil survival 567 . In addition, Coro1a is transiently recruited to the phagosomes throughout the phagocytosis of pathogens by macrophages and it is required for the early-phase phagosome formation 568 , 569 , 570 , 571 . Phosphorylation of Coro1a by protein kinase C (PKC) regulate its disassociation from phagosomes after ingestion is completed and stimulate the phagosome-lysosome fusion to initiate degradation of the pathogens 572 . Interestingly, retention of Coro1a on the phagosomal membrane upon mycobacterial infection activates Ca 2+ -dependent phosphatase calcineurin that block the lysosomal delivery and killing of mycobacteria 573 . Thus, the balance between the PKC and calcineurin regulatory loops for Coro1a, control the phagosomelysosome fusion in response to microbial infection. Furthermore, Coro1a-deficient T cells are defective in chemokine-mediated migration and display impaired egress from the thymus 574 .Coro2b is expressed at lower levels in macrophages compared to other immune cells, for instance, ILC2 where RORa shown to be essential 539 ,585 . Moreover, based on our investigation, Coro2b is expressed at similar levels than RORa in various sorted macrophage populations, i.e., KCs, ATMs, and alveolar macrophages (data not shown). Nevertheless, the

	role of Coro2b in macrophages is completely unknown. Mammalian Coro2b share 44% of
	amino acid identity with Coro1a 586 and some of the mechanisms that identified for Coro1a
	might also apply to Coro2b. However, different localization and expression levels could
	indicate distinct functional roles of these proteins 587 .
	Besides Coro2b, pathway analysis by DAVID showed that circadian rhythm pathway was
	significantly (p=0.0367) dysregulated in RORa-deficient alveolar macrophages. Among 9
	genes belonging to circadian rhythm pathway, 2 of them were significantly downregulated in
	RORa-deficient alveolar macrophages: Arntl (p=0.000002) and Cry1 (p=0.00145),
	respectively. It has been reported that even though expression of the Bmal1, Clock, NPAS2,
	Genome Nomenclature Committee (HGNC) in 2011, as CORO1A, CORO1B, CORO1C, focal adhesion turnover 576 . Other type II coronin, Coro2b, also known as, Clipin C is predominantly expressed in the brain and at lower levels in other tissues 577 . Immunostaining techniques revealed that Coro2b is localized in cerebral cortex, hippocampus, thalamus, olfactory bulb, and cerebellum in mouse brain 577 . Importantly, in the cerebellum, the Purkinje cell layer is reported to be intensely labeled with anti-Coro2b antibodies 577 . Considering the expression levels and the significance of RORa in the nervous system, particularly, in Purkinje cells 578 , 579 , 580 , 581 , as well as our microarray results, it appears highly relevant that Coro2b expression regulated by RORa and represents a potential target gene. Chip-Seq experiments would be necessary to formally demonstrate that it is actually the case. This prove might technically challenging due to the absence of reliable RORa-specific antibodies. Coro2b is also enriched in glomerular epithelial cells (namely podocytes) of kidney and regulates the ventral actin cytoskeleton that partially protect glomerular function and the glomerular filtration CORO2A, CORO2B, The type 2 coronins are much less studied. However, Coro2a is associated to the control of barrier 582 . Recently, Coro2b expression was found to be downregulated in podocytes of

A point mutation in Coronin 1A gene was identified in peripheral T cell-deficient (Ptcd) mice, which are characterized by severe defects in T cell migration and thymic egress, as well as in an atypical T -NK + B + severe combined immunodeficiency (SCID) patients 575 . human diabetic nephropathy patients and is suggested to be involved in the pathogenesis of glomerulopathies 583 . More recently, CORO2B was identified as a member of micro RNA (miRNA) and mRNA interaction network that regulates the malignant transformation of human bronchial epithelial cells induced by cigarette smoking 584 . According to the ImmGen database, and Cry1 were downregulated in fibroblasts of the staggerer mice, Bmal1, Clock, Cry1, and Per2 expressions were still oscillating with rhythmicity 497 . These findings suggested that RORa is not dispensable for circadian oscillations of the clock genes but regulates their level of expression 497 . Overall, it is thus possible RORa might regulate chemotaxis and/or phagosome formation of alveolar macrophages in response to microbial infection or magnitude of response upon activation in a circadian manner.

  In addition to its enzymatic activity, lysozyme, as a cationic protein can create pores by insertion into negatively-charged bacterial membrane 590 , 591 , 592 . In humans, lysozyme is encoded by a single gene LYZ, whereas 2 genes exist in mouse, Lyz1 and Lyz2 encoding for lysozyme P and lysozyme M, respectively. Lyz1 expression is restricted to the Paneth cells in small intestine. However, Lyz2 is a widely-expressed lysozyme gene in mice with a high expression in the myeloid lineage, mainly neutrophils, macrophages and dendritic cells similar to what is found for human LYZ gene. Myeloid cells not only secrete lysozyme M extracellularly, but also deliver it to the bacterium-containing phagosomes 593 , 594 , 595 . It has been reported that Lyz1 can compensate Lyz2 deficiency in lung by increased mRNA and protein levels 596 .However, it has also been shown that lysozyme P exhibits lower muramidase and bactericidal activities compared to lysozyme M, indicating the compensatory effect of lysozyme P for lysozyme M may not be fully effective 596 , 591 . Interestingly, LYZ gene is positioned in the neighborhood of an ulcerative colitis (UC) risk locus 597 , 598 . Moreover, point mutations in LYZ gene have been associated with familial visceral amyloidosis that result in hepatomegaly and cholestasis liver phenotypes in humans 599 . Relatedly, familial visceral amyloidosis patients carrying mutant LYZ gene display gastritis and inflammatory bowel disease (IBD) symptoms like abdominal pain, malabsorption, diarrhea, and weight loss 600 , 601 . Expectedly, Lyz2deficient mice develop more severe bacterial infections 602 , 603 , 604 . In addition to its anti-well as suppressed cytokine production, inflammatory response, and ROS signaling in basal conditions compared to wild-type littermates, suggesting that Lyz1 deficiency diminishes the intestinal mucosal response to bacterial molecular patterns 609 . Moreover, in response to dextran sulfate sodium (DSS)-induced colitis, Lyz1-deficient mice exhibit reduced NLR signaling and anti-colitogenic type 2 immune response compared to wild-type mice, indicating that Lyz1 deficiency ameliorates mucosal inflammation during DSS-induced colitis609 . Interestingly, authors also observed in ileum of Lyz1-deficient mice increased Tuft and goblet cell populations and concluded that the skewed type 2 immune profile of Lyz1-deficient mice in intestine was consistent with an activated goblet and Tuft cell program 609 .

	microbial properties, lysozyme is also an anti-inflammatory factor. Lysozyme inhibits serum
	complement activation 605 and possesses a LPS-binding ability that reduces LPS-related
	inflammation 606 . Peptides derived from lysozyme cleavage inhibit production of pro-
	inflammatory cytokines, including TNFa and IL-1b, by macrophages 607 . In a recent study, Yu

588 .

et al. reported that Paneth cell-derived lysozyme (Lyz1) defines the composition of mucolytic microbiota and the inflammatory tone of the intestine 609 . Authors using bulk RNA-seq analysis of ileum revealed that Lyz1-deficient mice exhibit diminished NLR and muramyl-dipeptide signaling as

  WT/WT ), heterozygous (Lyz2 WT/Cre ), and deficient (Lyz2 Cre/Cre ) mice to evaluate intestinal permeability to bacterial products. Moreover, to investigate impact of Lyz2 deficiency on inflammatory response and intestinal permeability, we collected small intestine (duodenum, jejunum and ileum) and colon samples for qPCR and histological analysis from chow diet and HFD-fed wild-type (Lyz2 WT/WT ), heterozygous (Lyz2 WT/Cre ), and deficient (Lyz2 Cre/Cre ) littermates. Likewise, to examine effect of Lyz2 deficiency on dysbiosis, we also collected fecal and cecal content in sterile conditions from these mice. Analyses are currently

	ANNEXES Olfr378 Olfr172 Syne2 Gm16062 Trip10 Cypt8 Myrf	olfactory receptor 378 olfactory receptor 172 spectrin repeat containing, nu predicted gene 16062 thyroid hormone receptor inter NA myelin regulatory factor	0,0042 69 0,0084 62 0,0049 45 0,0015 54 0,0080 9 0,0036 58 0,0066 27	0,8828 0,5254 -0,9285 -3,446 0,9149 0,6115 -0,7097 -3,092 0,8828 0,6677 -0,5826 -3,37 0,8353 0,691 -0,5332 -3,972 0,9149 1,462 0,5475 3,115 0,8828 1,638 0,712 3,526 0,9149 1,946 0,9603 3,218
	underway. LIMMA Gene Coro2b Gm24561 Phlda3 Gm25388 Gm25819 Krtap19-9a Arntl Olfr1217 Fam214a 5430437J1 0Rik Rfx7 Gm24009 Cspg4 Gm22977 Gm25447 4930583P0 6Rik Gm25654 Mir466g Gm24786 Gm25930 Lmtk2 Tex9 Cd276 Pilrb2 Cry1 Olfr596 BC055324 Gm24855 Mir34a Gm22459 Gm23443 Igkv6-14 Olfr1472 Gm3414 Fam63b Hmga2-ps1 Vmn1r57 Cldn1 Adpgk Fam96a Ppp1r9a Tas2r126 Gm9789 Vmn1r217 Nnt Tnfrsf12a Cpne5 C5ar2 B430319H 21Rik Olfr213 Klk8 Sfn Mrps2 Mylip Mir3475 Mrgpra6 B4galt5 Xlr5c Trp53i13 Gm23404 Nid2 2810417H1 3Rik Pdcd4 Vmn1r42 Adam30 Vmn2r101 Gm3287 Gm13124 Zc3hav1l Rps27l Gm26535 Trerf1 Defa-ps1 Matn2 Mir30a Arl9 Lgals4 4932413F0 4Rik Ceacam11 Esp16 Pptc7 Gm26067 Gm26600 Krt17 Wfdc17 Taf1b Tmem86b Tpcn2 Gm24286 Fcgr2b Tifab Mxd4 Hfe Gm27701 Vmn2r68 Gm10037 Gm24376 Olfr837 Gm23192 Defb8 Gm26518 Tufm 1700047L1 4Rik Ighv1-20 Gm26411 Ttll3 Prox1 Zfp109 Serpinb9e Lrg1 Cyct E130112N 10Rik Mir32 Gm10073 Gm23806 Adgrl3 D930015E 06Rik Tcrg-V4 Gm26489 Mir1187 1700102P0 8Rik Olfr466 Bak1 Gm23795 Ifit1bl1 Gm14409 Stk40 A530032D 15Rik Gm5388 Cxcl16 Vamp1 4930548J0 1Rik Fads2 Olfr642 Glce Gm24471 Slc17a1 Adgrg1 Phf11d Crip1 Tstd1 Cysltr1 Tspan4 Cmpk2 Gm10509 Il1rn Lemd3 Mns1 Slc16a10 Smim3 Ubash3b Mir223 Peg13 Rara Gm10521 Ankrd49 Gm4910 Mir883b Olfr1274-ps Gm12631 Vmn1r56 Neo1 Gm25625 Gm23423 B230209E 15Rik Gm24076 Gm25846 Gm26263 Gm10499 Igkv3-4 Ptafr Cox7b2 Gm22763 Cyp2c40 Matn3 Gm22062 Vps13c Sbk2 Zfp933 Gm26078 Nup54 Mmp19 Olfr1109 Gm20927 LOC10263 7947 Vmn2r85 Olfr1300-ps1 2310009A0 5Rik LOC10004 1057 Cfap36 Wars Xdh Mustn1	Comparison Info coronin, actin binding protein predicted gene, 24561 pleckstrin homology like domai predicted gene, 25388 predicted gene, 25819 keratin associated protein 19-aryl hydrocarbon receptor nucl olfactory receptor 1217 family with sequence similarit RIKEN cDNA 5430437J10 gene regulatory factor X, 7 predicted gene, 24009 chondroitin sulfate proteoglyc predicted gene, 22977 predicted gene, 25447 RIKEN cDNA 4930583P06 gene predicted gene, 25654 microRNA 466g predicted gene, 24786 predicted gene, 25930 lemur tyrosine kinase 2 testis expressed gene 9 CD276 antigen paired immunoglobin-like type cryptochrome 1 (photolyase-like) olfactory receptor 596 cDNA sequence BC055324 predicted gene, 24855 microRNA 34a predicted gene, 22459 predicted gene, 23443 immunoglobulin kappa variable olfactory receptor 1472 NA NA NA vomeronasal 1 receptor 57 claudin 1 ADP-dependent glucokinase NA protein phosphatase 1, regulat taste receptor, type 2, member predicted gene 9789 vomeronasal 1 receptor 217 nicotinamide nucleotide transh tumor necrosis factor receptor copine V complement component 5a receptor RIKEN cDNA B430319H21 gene olfactory receptor 213 kallikrein related-peptidase 8 stratifin mitochondrial ribosomal protei myosin regulatory light chain microRNA 3475 MAS-related GPR, member A6 UDP-Gal:betaGlcNAc beta 1,4-ga X-linked lymphocyte-regulated transformation related protein predicted gene, 23404 nidogen 2 NA programmed cell death 4 vomeronasal 1 receptor 42 a disintegrin and metallopepti vomeronasal 2, receptor 101 predicted gene 3287 predicted gene 13124 zinc finger CCCH-type, antivir ribosomal protein S27-like predicted gene, 26535 transcriptional regulating fac defensin, alpha, pseudogene 1 matrilin 2 microRNA 30a ADP-ribosylation factor-like 9 lectin, galactose binding, sol RIKEN cDNA 4932413F04 gene carcinoembryonic antigen-relat exocrine gland secreted peptid PTC7 protein phosphatase homol predicted gene, 26067 predicted gene, 26600 keratin 17 WAP four-disulfide core domain TATA-box binding protein assoc transmembrane protein 86B two pore segment channel 2 predicted gene, 24286 Fc receptor, IgG, low affinity TRAF-interacting protein with Max dimerization protein 4 homeostatic iron regulator predicted gene, 27701 vomeronasal 2, receptor 68 predicted gene 10037 predicted gene, 24376 olfactory receptor 837 predicted gene, 23192 defensin beta 8 NA Tu translation elongation fact RIKEN cDNA 1700047L14 gene immunoglobulin heavy variable predicted gene, 26411 tubulin tyrosine ligase-like f prospero homeobox 1 zinc finger protein 109 serine (or cysteine) peptidase leucine-rich alpha-2-glycoprot cytochrome c, testis NA microRNA 32 predicted pseudogene 10073 predicted gene, 23806 adhesion G protein-coupled rec NA T cell receptor gamma, variabl predicted gene, 26489 microRNA 1187 RIKEN cDNA 1700102P08 gene olfactory receptor 466 BCL2-antagonist/killer 1 predicted gene, 23795 interferon induced protein wit predicted gene 14409 serine/threonine kinase 40 RIKEN cDNA A530032D15Rik gene predicted gene 5388 chemokine (C-X-C motif) ligand vesicle-associated membrane pr RIKEN cDNA 4930548J01 gene fatty acid desaturase 2 olfactory receptor 642 glucuronyl C5-epimerase predicted gene, 24471 solute carrier family 17 (sodi adhesion G protein-coupled rec PHD finger protein 11D cysteine-rich protein 1 (intes thiosulfate sulfurtransferase cysteinyl leukotriene receptor tetraspanin 4 cytidine monophosphate (UMP-CM predicted gene 10509 interleukin 1 receptor antagon LEM domain containing 3 meiosis-specific nuclear struc solute carrier family 16 (mono small integral membrane protei ubiquitin associated and SH3 d microRNA 223 paternally expressed 13 retinoic acid receptor, alpha predicted gene 10521 ankyrin repeat domain 49 predicted pseudogene 4910 microRNA 883b olfactory receptor 1274, pseud predicted gene 12631 vomeronasal 1 receptor 56 neogenin predicted gene, 25625 predicted gene, 23423 RIKEN cDNA B230209E15 gene predicted gene, 24076 predicted gene, 25846 predicted gene, 26263 predicted gene 10499 immunoglobulin kappa variable platelet-activating factor rec cytochrome c oxidase subunit 7 predicted gene, 22763 cytochrome P450, family 2, sub matrilin 3 predicted gene, 22062 vacuolar protein sorting 13C SH3-binding domain kinase fami zinc finger protein 933 predicted gene, 26078 nucleoporin 54 matrix metallopeptidase 19 olfactory receptor 1109 predicted gene, 20927 NA vomeronasal 2, receptor 85 olfactory receptor 1300, pseud RIKEN cDNA 2310009A05 gene NA cilia and flagella associated tryptophanyl-tRNA synthetase xanthine dehydrogenase musculoskeletal, embryonic nuc	KO VS WT p-val 1,32E-06 0,0096 25 0,0041 62 0,0010 78 0,0025 72 0,0079 57 2,10E-06 0,0094 64 0,0002 888 0,0002 152 7,79E-05 0,0093 55 5,43E-05 0,0033 56 0,0006 434 0,0077 26 0,0085 67 0,0075 35 0,0054 75 0,0043 91 0,0025 61 0,0002 751 0,0008 337 0,0031 9 0,0014 48 0,0002 002 0,0023 16 0,0016 36 0,0097 82 0,0050 24 0,0011 57 0,0066 72 0,0037 71 0,0001 389 0,0012 52 0,0024 64 0,0076 01 0,0071 46 1,55E-05 2,86E-05 0,0088 87 0,0025 02 0,0081 13 5,84E-05 0,0049 4 0,0058 26 0,0039 01 0,0001 261 0,0005 196 0,0080 1 0,0092 61 0,0073 68 0,0075 44 0,0002 22 0,0029 68 0,0024 67 0,0096 14 0,0018 49 0,0017 29 0,0073 06 0,0087 57 0,0084 83 0,0040 96 0,0085 87 0,0066 9 0,0092 63 0,0096 55 0,0012 56 0,0033 08 5,47E-05 0,0038 91 0,0042 26 0,0085 12 0,0036 72 0,0024 0,8828 0,6692 -0,5794 -3,745 KO VS WT KO VS WT KO VS WT KO VS WT FDR,p-val FC log2(F C) t-stat 0,0324 7 0,1984 -2,334 -8,324 0,9149 0,2912 -1,78 -3,025 0,8828 0,41 -1,286 -3,459 0,7923 0,4129 -1,276 -4,166 0,8828 0,42 -1,251 -3,709 0,9149 0,4509 -1,149 -3,124 0,0324 7 0,4522 -1,145 -7,983 0,9149 0,4684 -1,094 -3,034 0,47 0,4699 -1,089 -4,881 0,4153 0,4718 -1,084 -5,046 0,2188 0,4723 -1,082 -5,631 0,9149 0,4822 -1,052 -3,04 0,2188 0,483 -1,05 -5,845 0,8828 0,4828 -1,05 -3,57 0,6861 0,4895 -1,031 -4,442 0,9149 0,4906 -1,027 -3,139 0,9149 0,4973 -1,008 -3,086 0,9149 0,4979 -1,006 -3,152 0,9068 0,5069 -0,9802 -3,317 0,8828 0,5073 -0,979 -3,431 0,8828 0,5108 -0,9691 -3,711 0,47 0,5226 -0,9363 -4,908 0,733 0,5247 -0,9305 -4,303 0,8828 0,5304 -0,9149 -3,597 0,8019 0,5345 -0,9038 -4,01 0,4153 0,5375 -0,8956 -5,087 0,8828 0,5404 -0,8879 -3,763 0,8432 0,5473 -0,8697 -3,945 0,9149 0,5539 -0,8524 -3,017 0,8828 0,5542 -0,8514 -3,361 0,7923 0,5592 -0,8385 -4,129 0,9149 0,5648 -0,8241 -3,215 0,8828 0,5671 -0,8184 -3,51 0,3303 0,5726 -0,8045 -5,295 0,7923 0,5733 -0,8026 -4,087 0,8828 0,5772 -0,7929 -3,731 0,9149 0,5831 -0,7781 -3,147 0,9149 0,5877 -0,7669 -3,179 0,1592 0,5921 -0,7561 -6,625 0,2188 0,5953 -0,7482 -6,236 0,9149 0,5969 -0,7445 -3,067 0,8828 0,602 -0,7322 -3,723 0,9149 0,6033 -0,7291 -3,114 0,2188 0,6036 -0,7284 -5,802 0,8828 0,6045 -0,7261 -3,37 0,9149 0,6082 -0,7174 -3,285 0,8828 0,6083 -0,7172 -3,492 0,3249 0,6097 -0,7138 -5,35 0,6179 0,6221 -0,6847 -4,558 0,9149 0,6238 -0,6809 -3,12 0,9149 0,6245 -0,6792 -3,045 0,9149 0,625 -0,678 -3,164 0,9149 0,6277 -0,672 -3,151 0,4153 0,629 -0,6689 -5,029 0,8828 0,6295 -0,6677 -3,634 0,8828 0,63 -0,6665 -3,73 0,9149 0,6324 -0,6612 -3,026 0,8663 0,6353 -0,6544 -3,881 0,8625 0,6371 -0,6505 -3,916 0,9149 0,6377 -0,649 -3,168 0,9149 0,638 -0,6485 -3,074 0,9149 0,6427 -0,6377 -3,091 0,8828 0,6457 -0,6311 -3,467 0,9149 0,6459 -0,6307 -3,084 0,9149 0,6493 -0,6231 -3,213 0,9149 0,6514 -0,6183 -3,045 0,9149 0,6519 -0,6172 -3,024 0,7923 0,6529 -0,615 -4,085 0,8828 0,6561 -0,608 -3,578 0,2188 0,657 -0,6059 -5,841 0,8828 0,6591 -0,6015 -3,494 0,8828 0,662 -0,5951 -3,451 0,9149 0,6623 -0,5945 -3,089 0,8828 0,667 -0,5843 -3,524 0,0062 0,9149 0,6915 -0,5323 -3,253 0,0024 66 0,8828 1,466 0,5519 3,731 0,0041 43 0,8828 1,642 0,7157 3,461 0,0025 05 0,8828 1,974 0,9814 3,722 0,0082 89 0,9149 0,6707 -0,5764 -3,103 0,0048 36 0,0078 54 0,9149 0,6929 -0,5294 -3,131 0,0003 82 0,5135 1,469 0,5551 4,727 0,0029 4 0,8828 1,643 0,7163 3,639 0,0003 0,4869 2,027 1,02 4,833 149 0,8828 0,6722 -0,5731 -3,381 0,0003 578 0,0032 49 0,8828 0,6936 -0,5278 -3,587 0,0094 48 0,9149 1,471 0,5572 3,035 0,0032 52 0,8828 1,643 0,7167 3,587 0,0017 0,8625 2,061 1,043 3,916 3 0,5029 0,6732 -0,5708 -4,763 0,0045 47 0,0011 82 0,7923 0,6939 -0,5271 -4,117 0,0036 23 0,8828 1,476 0,5616 3,531 0,0099 49 0,9149 1,653 0,7251 3,008 0,0039 0,8828 2,067 1,047 3,488 35 0,8828 0,6741 -0,5691 -3,413 0,0065 82 0,0033 8 0,8828 0,6945 -0,5259 -3,567 0,0006 329 0,6861 1,486 0,5714 4,451 0,0045 03 0,8828 1,668 0,7384 3,418 0,0009 0,7634 2,144 1,1 4,254 135 0,9149 0,6747 -0,5677 -3,222 0,0051 45 0,8988 0,676 0,0049 72 0,8828 0,6957 -0,5236 -3,367 0,0037 21 0,8828 1,488 0,5732 3,517 0,0045 3 0,8828 1,677 0,7455 3,415 0,0039 0,8828 2,289 1,195 3,489 22 -0,5649 -3,349 0,0033 13 0,8828 0,677 0,0085 17 0,9149 0,6973 -0,5202 -3,089 0,0091 47 0,9149 1,493 0,5781 3,052 0,0045 07 0,8828 1,684 0,7522 3,418 0,0027 0,8828 2,317 1,212 3,68 19 -0,5628 -3,577 0,0035 85 0,8828 0,6778 -0,561 0,0010 64 0,7923 0,6977 -0,5194 -4,173 0,0020 88 0,8828 1,499 0,5836 3,817 0,0003 513 0,5029 1,693 0,7594 4,773 0,0055 0,9068 2,317 1,212 3,309 61 -3,536 0,0079 84 0,0080 47 0,9149 0,6993 -0,5161 -3,118 0,0034 14 0,8828 1,5 0,5846 3,561 0,0028 32 0,8828 1,712 0,7761 3,658 0,0066 0,9149 2,449 1,292 3,219 18 0,9149 0,6793 -0,5579 -3,122 0,0080 4 0,9149 0,6797 -0,557 0,0033 43 0,8828 0,6998 -0,515 -3,572 0,0004 704 0,5954 1,513 0,5974 4,612 0,0057 7 0,9149 1,714 0,7777 3,29 6,50E-0,2188 2,521 1,334 5,739 05 -3,118 0,0011 89 0,0070 56 0,9149 0,7006 -0,5133 -3,186 0,0067 86 0,9149 1,519 0,6029 3,206 0,0090 26 0,9149 1,726 0,7878 3,059 0,0079 0,9149 2,533 1,341 3,122 84 0,7923 0,6809 -0,5545 -4,114 0,0046 34 0,0019 95 0,8828 0,7011 -0,5123 -3,841 0,0067 28 0,9149 1,525 0,6086 3,21 0,0047 72 0,8828 1,742 0,801 3,388 5,00E-0,2188 2,623 1,391 5,896 05 0,8828 0,6814 -0,5534 -3,403 0,0065 17 0,9149 0,682 0,0008 441 0,733 0,7021 -0,5103 -4,296 0,0049 47 0,8828 1,537 0,62 3,369 0,0057 53 0,9149 1,744 0,8028 3,291 0,0095 0,9149 2,951 1,561 3,028 71 -0,5521 -3,227 0,0018 28 0,8663 0,7043 -0,5058 -3,887 0,0002 283 0,4153 1,549 0,631 5,013 0,0015 72 0,8353 1,755 0,8112 3,967 0,0079 0,9149 3,179 1,669 3,124 52 0,0037 96 0,8828 0,6821 -0,552 -3,506 0,0090 19 44 0,9149 0,6836 -0,5488 -3,087 0,0033 95 055 0,7037 0,684 -0,5479 -4,393 0,0091 83 0,9149 0,6841 -0,5478 85 0,8828 0,6861 -0,5436 -3,481 0,0068 95 6 0,8828 0,689 -0,5374 -3,57 0,0047 33 33 0,8828 0,6898 -0,5358 -3,371 0,0040 67 0,0033 63 0,8828 1,46 0,5458 3,569 0,0032 47 0,8828 1,633 0,7075 3,587 0,0021 97 0,8828 1,909 0,9327 3,791 0,8828 0,6904 -0,5346 -3,471 0,0088 65 0,9149 1,446 0,5324 3,068 0,0038 82 0,8828 1,628 0,7028 3,495 814 0,5954 1,898 0,9242 4,6 0,0004 0,0049 0,0046 63 0,8828 1,435 0,5215 3,4 0,0010 69 0,7923 1,61 0,6867 4,171 0,0020 08 0,8828 1,886 0,9151 3,838 0,8828 0,6897 -0,5359 -3,392 0,0043 9 0,8828 1,435 0,5215 3,431 0,0074 9 0,9149 1,586 0,6657 3,155 535 0,733 1,867 0,901 4,291 0,0008 0,0033 0,0082 76 0,9149 1,433 0,5189 3,104 0,0040 69 0,8828 1,585 0,6644 3,47 0,0039 51 0,8828 1,864 0,8983 3,486 0,9149 0,6862 -0,5432 -3,198 0,0018 2 0,8663 1,432 0,5177 3,889 0,0099 8 0,9149 1,575 0,6557 3,007 74 0,9149 1,863 0,8976 3,056 0,0090 0,0039 0,0015 94 0,8353 1,422 0,5074 3,959 0,0060 63 0,9149 1,572 0,6529 3,264 7,36E-05 0,2188 1,85 0,8878 5,664 -3,05 0,0059 47 0,9149 1,417 0,5029 3,274 0,0073 43 0,9149 1,57 0,6509 3,165 12 0,7923 1,842 0,8811 4,149 0,0011 0,0007 0,0064 77 0,9149 0,7059 -0,5025 -3,23 0,0067 08 0,9149 1,567 0,6477 3,212 0,0098 8 0,9149 1,827 0,8692 3,012 0,8828 0,6838 -0,5484 -3,564 0,0018 1 0,8663 0,7055 -0,5033 -3,892 0,0027 03 0,8828 1,562 0,6432 3,683 08 0,7923 1,796 0,8448 4,106 0,0012 0,0085 0,0070 39 0,9149 0,7045 -0,5052 -3,187 0,0061 3 0,9149 1,559 0,641 3,259 0,0047 89 0,8828 1,778 0,8301 3,386 0,9149 0,6822 -0,5517 -3,059 0,0021 41 0,8828 0,7045 -0,5053 -3,804 0,0045 45 0,8828 1,558 0,6397 3,413 0,0037 89 0,8828 1,776 0,829 3,507 0,0021 24 0,8828 3,553 1,829 3,809

Table S1 . List of primers used in RT-qPCR and ChIP-qPCR.

 S1

	RT-qPCR	Forward	Reverse
	GDF15	GCAAGAACTCAGGACGGTGA	TGGAGTCTTCGGAGTGCAAC
	OAZ1	GGATCCTCAATAGCCACTGC	TACAGCAGTGGAGGGAGACC
	CDKN1A	GCGAGGCACAAGGGTACAAGACAG	TAATGGCGGGCTGCATCCAG
	MDM2	GCCCTTCGTGAGAATTGGCT	AAAGCCCTCTTCAGCTTGTGT
	HSPA5	TAGCGTATGGTGCTGCTGTC	TTTGTCAGGGGTCTTTCACC
	XBP1 spliced isoform	CTGAGTCCGCAGCAGGTG	ACTGGGTCCAAGTTGTCCAG
	ERN1	AGCAGTTAGAGAGAGGCGGG	CTGGAGGGGGACAGTGATGT
	ATF6	CAATTGGAAGCAGCAAATGA	ACCGAGGAGACGAGACTGAA
	EIF2AK3	GTGGGACCAAGACCGTGAAA	CGACAACCCAGAGCTGAACA
	ATF4	TCAAACCTCATGGGTTCTCC	GTGTCATCCAACGTGGTCAG
	DDIT3	GAACCAGGAAACGGAAACAGA	TCTCCTTCATGCGCTGCTT
	ATF3	ATTGTCCGGGCTCAGAATGG	ACCACGACTGCTTAGCTCTG
	ChIP-qPCR GDF15	Forward	Reverse
	Promoter site A	GCTGGAGCTTGCAGGTTGG	AAAATTTCAGAAATTAACCGGTCGTG
	Promoter site B	ACCACGACCGGTTAATTTCTGAA	AAAAATTAAAACTCTAGCCCCTGGC
	Promoter site C	TGCTCTTGTTGATCAGGCGGA	CTGGGCTTGGTGGTGGGATTA
	Promoter site D	AGAATGAGTAGGAGTTCTCCAGAGG	CATAGGAGGCACTTGATAAACTGGG
	Promoter site NS	ATTATGAATCCTGTGAGGATGGCTT	ATTATCTTTCCAGTCTAAGCAGGGT

Acknowledgments and funding

This research has been funded by the Interuniversity Attraction Poles (IAP) program initiated by the Belgian Science Policy Office (BELSPO) (IAP grant P7/32) (to JP), the University of Liege and the European Union in the context of the FP7-PEOPLE-COFUND-BeIPD project (to LL), the Leon Fredericq Foundation (to LL) and by grants from "European Genomic Institute for Diabetes" (E.G.I.D., ANR-10-LABX-46) (to DD & BS).

RORa and its target genes is unlikely to reveal a major phenotype. These results show that RORa does not regulate LPS-induced BMDM inflammatory response unlike reported earlier.

C. RORa deletion in macrophages does not affect obesity, IR nor hepatic steatosis

To investigate the role of macrophages RORa in metabolic functions, in particular obesity and IR, we fed WT and MKO mice with a 60% high fat diet (HFD) for 12 weeks. WT and MKO mice under HFD significantly gained weight, AT mass and leptin expression increased similarly in both genotypes (Figure 10A-C).

E. Effect of RORa deletion in KC is offset by high RORg expression

Contrasting with these results in 2 independent and complementary models of NAFLD, it was reported that RORa deletion in macrophages, achieved by using a similar strategy (Rora fl/fl Lyz2 Cre ), predisposes mice to NASH after 12 weeks of HFD feeding 548 . NASH exacerbation was attributed to a key role of RORa in Kupffer Cell (KC) function 548 . To determine a possible cause for this discrepancy, we first assessed the extent of Rora exon 3 deletion in KC. KC and other liver immune cell populations, sorted to a high level of purity (Figure 24-25). We further confirmed the Lyz2 deficiency at mRNA level by RT-qPCR in spleen of Lyz2 WT/WT (WT), Lyz2 WT/Cre (Het), and Lyz2 Cre/Cre (KO) mice (Figure 29C). A. Lyz2 deficiency slightly protects against HFD-induced obesity and IR, however, has no impact on NAFL To investigate the role of Lyz2 in diet-induced obesity, IR, and NAFL, we fed Lyz2 WT/WT (WT), Lyz2 WT/Cre (Het), and Lyz2 Cre/Cre (KO) littermate mice with a 60% of high fat diet (HFD) for 12 weeks. All the mice significantly gained weight upon HFD feeding, however KO mice displayed lower body weight gain compared to WT and Het littermates (Figure 30).

Supplementary Table 1: List of the modulated genes from microarrays performed on alveolar macrophages

Supplementary Table 1: List of the modulated genes from microarrays performed on alveolar macrophages from lung of 14 weeks old naïve WT and MKO mice. Genes are sorted by log2( FC) value from downregulated to upregulated ones. n=6 mice per genotype.

Saturated fatty acids promote GDF15 expression in macrophages through the PERK/eIF2/CHOP signaling pathway

Laurent L'homme 1,[START_REF] Ncd-Risc | Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128•9 million children, adolescents, and adults[END_REF] , Benan Pelin Sermikli 1 , Bart Staels 1 , Jacques Piette 2 , Sylvie Legrand-Poels 2,3, *, David Dombrowicz 1,3, * 1 Univ. Lille, INSERM, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France. [START_REF] Ncd-Risc | Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128•9 million children, adolescents, and adults[END_REF] University of Liege, GIGA-Signal Transduction, Laboratory of Virology and Immunology, Liège, Belgium. 3 DD and SLP contributed equally to this work. * Correspondence: david.dombrowicz@pasteur-lille.fr (DD) and S.Legrand@ulg.ac.be (SLP)

Abstract:

Growth differentiation factor-15 (GDF-15) and its receptor GFRAL are involved in the development of obesity and insulin resistance. GDF-15 level increases with obesity and is positively associated with disease progression. The molecular mechanism underlying GDF-15 production is unknown but macrophages have been recently proposed as a key source. In the present work, we sought for potential physiological activators of GDF15 expression in macrophages and identified saturated fatty acids (SFAs) as strong inducers of GDF15 expression and secretion. SFAs increase GDF15 expression following the induction of an ER stress and the activation of the unfolded protein response through the PERK/eIF2/CHOP signaling pathway. The transcription factor CHOP directly binds GDF15 promoter region and regulates GDF15 expression.

Unlike SFAs, unsaturated fatty acids do not promote GDF15 expression and rather prevent both SFA-induced GDF15 expression and ER stress. These results suggest that free fatty acids may be involved in the control of GDF-15 and provide new molecular insights about how diet and lipid metabolism may regulate the development of obesity and T2D.

Keywords:

GDF15; macrophage; obesity; saturated fatty acids; stearate; ER stress; CHOP. Suzuki et al., 2017). Indeed, CHOP-deficient mice are more susceptible to obesity (Han et al., 2013), but the molecular mechanism underlying the protective role of CHOP remains unclear.

In the present work, we sought for potential physiological activators of GDF15 expression in macrophages and identified saturated fatty acids (SFAs) as strong inducers of GDF15 expression and secretion. We show that SFAs induce GDF15 expression following induction of an ER stress. SFAs-induced ER stress initiates the activation of the eiF2 complex in a PERK-dependent manner and the expression of the transcription factor CHOP that directly binds GDF15 promoter region and regulates GDF15 expression. Interestingly, we show that unsaturated fatty acids (UFAs) prevent SFA-induced GDF15 expression and ER stress, bringing new findings about how diet and lipid metabolism may regulate the development of obesity and T2D.

(Santa Cruz #sc-7947) and anti-β-tubulin (Sigma #T5201). The secondary antibodies used for the revelation were Alexa Fluor 680 anti-mouse IgG (Jackson ImmunoResearch, #715-625-150), Alexa Fluor 790 anti-rabbit IgG (Jackson ImmunoResearch, #711-655-152), HRP-linked anti-rabbit IgG (Cell Signaling #7074) and HRP-linked anti-mouse IgG (Dako #7074). Fluorescent immunoblots were scanned with an OdysseyCLx Imaging System (LI-COR) and quantified with Image studio software (LI-COR). For chemoluminescent western blot, revelation was performed with ECL (Pierce) by using the digital imaging system ImageQuant LAS 4000 (GE Healthcare) and quantification achieved with the ImageQuant TL software (version 7.0, GE Healthcare). After phospho-eIF2a revelation, a stripping step of 1 hour at 50°C with Tris-HCl pH 6.8, 2% SDS, 0.8% b-mercaptoethanol was performed before the detection of eIF2a.

ChIP-qPCR

After 16 hours of treatment with BSA or C18:0, PMA-differentiated THP-1 cells were washed twice with PBS and crosslinked with 1% methanol-free formaldehyde (Pierce #28908) for 10 minutes at room temperature. Crosslink was quenched by addition of glycine. Cells were scrapped in buffer 1 (50 mM HEPES-KOH pH 7.5, 0.25% Triton X100, 10% glycerol, 0.5 mM EGTA, 1 mM EDTA, 140 mM NaCl, 0.5% Igepal, 1 mM PMSF, cOmplete protease inhibitor cocktail) and incubated for 10 min at 4°C under agitation. Samples were centrifuged at 600g, washed with buffer 2 (10 mM Tris-HCl pH 8.0, 0.5 mM EGTA, 1 mM EDTA, 200 mM NaCl, 1 mM PMSF, cOmplete protease inhibitor cocktail) and centrifuged at 600g. Nuclei pellets were resuspended in buffer 3 (50 mM Tris-HCl pH 8.0, 10 mM EDTA, 1% SDS, 1 mM PMSF, cOmplete protease inhibitor cocktail), sonicated by using a Bioruptor Plus (Diagenode) and incubated with 2 µg antibody overnight at 4°C under agitation. Immunocomplexes were captured with protein A/G magnetic beads previously blocked with BSA and tRNA from yeast (Sigma #R5636). Beads were successively washed with buffer 4 (50 mM Tris-HCl pH 8.0, 1% Triton X100, 1 mM EDTA, 150 mM NaCl, 0.1% SDS), buffer 5 (50 mM Tris-HCl pH 8.0, 1% Triton X100, 1 mM EDTA, 500 mM NaCl, 0.1% SDS), buffer 6 (50 mM Tris-HCl pH 8.0, 1 mM EDTA, 500 mM LiCl, 0.5% sodium deoxycholate, 1% igepal) and TE ( 50mM Tris-HCl pH 8.0, 1 mM EDTA). Beads were resuspended in elution buffer (1% SDS, 100mM NaHCO3) and incubated overnight at 65°C with agitation to reverse crosslink. DNA was purified with NucleoSpin gel and PCR Clean-up (Macherey-Nagel #740609) according to the manufacturer's instructions. qPCR was performed by using Brilliant II SYBR Green QPCR Master Mix (Agilent, #600828) and ran on a Mx3000P qPCR system (Agilent). The antibodies used were anti-CHOP (Santa Cruz #sc-575) and normal rabbit IgG (Cell Signaling #2729). Primer sequences are provided in supplementary table 1.

Statistical analyses

All statistical analyses were carried out using GraphPad Prism 7 for Windows (GraphPad Software, Inc.) and presented as the means ± standard error of the mean (SEM). When one independent variable was involved, two-tailed Student's t-test was performed to compare two groups and one-way ANOVA with Dunnett's multiple comparisons test to compare more than two groups. Two-way ANOVA with Sidak's multiple comparisons test was performed when the experiment involved two independent variables. Tests used are described in the figure legends. Statistical significance was set at p < 0.05.

Results

SFAs promote GDF15 expression and secretion in macrophages

To better understand how GDF15 expression is regulated in macrophages, we analyzed a publicly available transcriptomic dataset of human primary macrophages treated with several physiological stimuli including cytokines, TLR ligands, glucocorticoid, prostaglandin, lipoprotein and free fatty acids (FFAs) (Fig. 1A) (Xue et al., 2014). FFAs, and particularly palmitate (C16:0) and stearate (C18:0), the two most common saturated fatty acids (SFAs), induced the highest GDF15 expression. Since both FFAs and GDF-15 concentrations increase in metabolic diseases (Bergman and Ader, 2000; Dostálová et al., 2009; Vila et al., 2011), FFAs may represent potential activators of GDF15 expression. To confirm this finding, we treated human primary monocyte-derived macrophages (MDMs) with physiological concentrations of FFAs (100 µM) (Hodson et al., 2008), including C16:0, C18:0 and their chain length-matched unsaturated fatty acids (UFAs) C16:1, C18:1 and C18:2. We confirmed that SFAs induced GDF15 expression (Fig. 1B) and secretion (Fig. 1C) compared to the vehicle alone (BSA) in MDMs. C18:0 induced a stronger response than C16:0. Interestingly, UFAs were unable to induce GDF15 expression and secretion.

ER stress, but not p53, is involved in SFAs-induced GDF15 expression

GDF-15 was extensively studied for its role in cancer and shown to be mainly regulated by the transcription factor p53 (Osada et al., 2007) and the ER stress pathway (Yang et al., 2010). SFAs did not induce the common p53 target genes such as CDKN1A, encoding for p21, and MDM2 (Fig. 2A-B) but strongly increased the expression of ER stress-related markers such as HSP5A, encoding for BIP, and the spliced form of XBP1 mRNA in MDMs (Fig. 2C-D) (Walter and Ron, 2011).

Inhibition of p53 with pifithrin-a did not reverse C18:0-induced GDF15 expression in MDMs (Fig. 2E) while ER stress inhibition by the chemical chaperone 4-phenylbutyric acid (PBA) decreased GDF15 expression (Fig. 2F) and secretion (Fig. 2G). On the other hand, induction of an ER stress with tunicamycin, a glycosylation inhibitor leading to the accumulation of misfolded proteins in ER, increased ER stress marker (Fig. 2H) and GDF15 expression (Fig. 2I), confirming that ER stress is able to induce GDF15 expression in macrophages.

PERK/eIF2a/CHOP pathway regulates SFAs-induced GDF15 expression

To better understand how ER stress leads to GDF15 expression, we inhibited each of the three UPR branches by silencing IRE1a, ATF6 or PERK through siRNA transfection in PMA-differentiated THP-1 cells. The human monocytic cell line THP-1, differentiable in macrophage-like cells by using PMA, was used for its better transfection efficiency compared to primary macrophages. SFAs induced GDF15 expression and ER stress in PMA-differentiated THP-1 cells as observed in primary MDMs (Fig. S2A-B). While the expression of each ER stress sensor was significantly downregulated after transfection of the corresponding siRNA (Fig. S3A-C), only the PERK silencing decreased C18:0-induced GDF15 expression (Fig. 3A & Fig. S3D-E).

Pharmacological inhibition of PERK with GSK2606414 or GSK2656157 reduced C18:0-induced GDF15 expression in PMA-differentiated THP-1 cells (Fig. 3B). PERK inhibition also decreased GDF15 expression and secretion following stimulation with C18:0 in primary MDMs (Fig. 3C-D). Similarly to C18:0-mediated GDF15 expression, tunicamycin-induced GDF15 expression was prevented by PERK inhibitors (Fig. 3E), demonstrating that PERK pathway is involved in ER stress-induced GDF15 expression in macrophages.

As a consequence of ER stress, PERK phosphorylates eIF2α that activates the ISR and increases the expression of ATF4, ATF3 and DDIT3, encoding for CHOP (Walter and Ron, 2011). In agreement with our results showing that SFAs initiated an ER stress, SFAs induced eIF2α phosphorylation (Fig. S4A) and expression of ATF4, ATF3 and DDIT3 (Fig. S4B-D). Treatment with trans-ISRIB, an eIF2 complex inhibitor, decreased both C18:0-and tunicamycin-induced GDF15 expression (Fig. 3F). In basal conditions and under ER stress, eIF2α is dephosphorylated by PP1/CReP and PP1/GADD34 complexes driving a negative regulation of eIF2 activity. Interestingly and as anticipated, preventing dephosphorylation of eIF2α by inhibiting these phosphatase complexes with salubrinal exacerbated C18:0-and tunicamycin-induced GDF15 expression (Fig. 3G). Altogether, these results show that eIF2 signaling pathway, namely the ISR, regulates GDF15 expression in macrophages.

ATF3 and CHOP are two key transcription factors involved in ISR which are both induced by SFAs (Fig. S4C-D). Transfection of siRNA against ATF3 or DDIT3 mRNA shortly before C18:0 treatment allowed us to mainly prevent the increase of mRNA level induced by C18:0 (Fig. 4A-B). CHOP silencing decreased GDF15 expression (Fig. 4C) while ATF3 knock down did not (Fig. 4D). Analysis of GDF15 promoter region revealed seven potential CHOP response elements (Fig. 4E). To determine whether CHOP is recruited in GDF15 promoter in response to C18:0 treatment, we performed a ChIP assay for these response elements that we grouped in 4 sites (Fig. 4E). BSA alone showed no enrichment at any sites suggesting no or few basal binding of CHOP in GDF15 promoter (Fig. 4F). This observation is correlated with an undetectable CHOP protein level under basal conditions (Fig. 4G). C18:0 increased CHOP protein level (Fig. 4G) and CHOP binding in GDF15 promoter (Fig. 4F). These results suggest that CHOP regulates GDF15 expression in macrophages by a direct binding to its promoter. It is worth noting that all the previous treatments restraining GDF15 expression such as PBA, PERK siRNAs, PERK inhibitors and trans-ISRIB also successfully decreased DDIT3 expression (Fig. 5A-E), while treatments exacerbating GDF15 expression such as p53 inhibitor pifithrin-a and salubrinal increased DDIT3 expression (Fig. 5F-G). Collectively, these data demonstrate that C18:0 promote GDF15 expression in macrophages following the induction of an ER stress through the PERK/eIF2/CHOP signaling pathway.

UFAs inhibit SFAs-induced ER stress and GDF15 expression

Unlike SFAs, UFAs did not induce GDF15 expression and secretion (Fig. 1B-C). It has been previously reported that UFAs were able to prevent SFAs-induced cytokine production such as IL-1b or IL-6 (Gianfrancesco et al., 2019; L'homme et al., 2013; Macrae et al., 2013). To investigate whether UFAs prevent C18:0-induced GDF15 expression, we treated PMA-differentiated THP-1 cells with C18:0 alone or in combination with an equimolar concentration of UFAs. C16:1, C18:1 and C18:2 were all able to prevent C18:0-induced GDF15 expression (Fig. 6A). Since CHOP is involved in SFAs-induced GDF15 expression, we next analyzed ER stress response upon cotreatment with C18:0 and UFAs. UFAs restrained C18:0-induced ER stress markers including the splicing of XBP1 mRNA (Fig. 6B), eIF2α phosphorylation (Fig. 6C) and the expression of HSPA5 and DDIT3 (Fig. 6D-E). In contrast, tunicamycin-induced GDF15 expression (Fig. 6F) and ER stress (Fig. 6G-J) were not inhibited by UFAs cotreatment, suggesting that UFAs have no general effect on ER stress but specifically restrain SFAs effect on ER stress. The protection mediated by UFAs against C18:0induced ER stress and CHOP upregulation likely account for the inhibition of GDF15 expression. Taken together, our results show the complex action of FFAs on GDF15

We showed that C18:0-induced GDF15 expression is ER stress-dependent and involves the UPR via the PERK/eIF2/CHOP signaling pathway and a direct binding of the transcription factor CHOP in GDF15 promoter. In basal conditions, macrophages express no or low level of CHOP, likely explaining the absence of CHOP binding in GDF15 promoter and the lack of effect of ER stress, UPR and ISR inhibitors in unstimulated cells. The basal GDF15 expression and secretion in macrophages is therefore ER stress-independent. Upon SFAs treatment, the PERK/eIF2/CHOP signaling pathway is activated leading to CHOP expression and binding to GDF15 promoter, as well as GDF15 expression and secretion by macrophages. Interestingly, the transcription factor CHOP has been involved in obesity development and CHOPdeficient mice are more susceptible to obesity (Han et al., 2013), similarly to Gdf15deficient mice (Tran et al., 2018). The molecular mechanism accounting for the higher weight gain of CHOP-deficient mice is not elucidated but, given the role of CHOP in the regulation of GDF15 and the role of GDF-15 on food intake, a decrease of GDF-15 level in these mice may play a role.

The role of ER stress and ISR on GDF15 regulation was previously described in cancer cell (Yang et al., 2010), myocyte (Chung et al., 2017), gut epithelial cells (Park et al., 2017) and hepatocytes (Li et al., 2018). These works revealed that various ISR stimuli including the non-steroidal anti-inflammatory compound sulindac sulfide (Yang et al., 2010), mitochondrial UPR (Chung et al., 2017), enteropathogenic Escherichia coli (Park et al., 2017), tunicamycin (Li et al., 2018; Patel et al., 2019) and thapsigargin (Li et al., 2018; Patel et al., 2019) induce GDF-15. Despite the fact that different ER stress stimuli are described to promote GDF15 expression, SFAs represent interesting physiological stimuli linking obesity and GDF-15. Indeed, obesity increases FFA levels and a disequilibrium in SFA/UFA balance is commonly associated with progression of obesity and the development of complications such as T2D (Klein-Platat et al., 2005; Ma et al., 2015).

Previous studies have demonstrated that UFAs are able to prevent cytokines production by SFAs, as described for IL-6 (Macrae et al., 2013) and IL-1b (Gianfrancesco et al., 2019; L'homme et al., 2013). We observed that an equimolar concentration of UFAs also prevents C18:0-induced GDF15 expression in macrophages. UFAs also suppress ER stress and CHOP expression, probably accounting for the inhibition of GDF15 expression. Inhibition of ER stress by UFAs is specific to SFAs as UFAs were unable to protect against tunicamycin-induced ER stress and increase in GDF15 expression. These results reveal the complexity of FFAmediated regulation of inflammatory process and provide evidences than the ratio SFAs/UFAs may be more important than the absolute value of SFAs.

It remains currently unclear whether FFAs, and particularly SFAs, play a direct role in macrophages activation during obesity. In vitro, SFAs activate macrophages to produce pro-inflammatory cytokines such as TNF-a and IL-1b (Haversen et al., 2009; L'homme et al., 2013). In obese adipose tissue, macrophages develop a proinflammatory phenotype in line with the presence of metabolic stimuli such as SFAs (Kratz et al., 2014). We showed that SFAs induces expression and secretion of GDF-15 by macrophages in vitro and further investigations are required to support this finding in vivo. GDF-15 is protective against obesity and T2D (Chrysovergis et al., 2014; Chung et al., 2017; Emmerson et al., 2017; Hsu et al., 2017; Macia et al., 2012; Mullican et al., 2017; Tran et al., 2018; Yang et al., 2017). However, GDF-15 shows a positive correlation with obesity progression and the development of complications such as T2D (Bao et al., 2019; Dostálová et al., 2009; Kempf et al., 2012; Vila et al., 2011). This puzzling discrepancy may result from SFAs properties. Since SFAs induce a pro-inflammatory phenotype in macrophages (Haversen et al., 2009), GDF-15 may be produced besides other cytokines and be considered as an independent marker of macrophage activation by SFAs. The positive association between GDF-15 level and obesity progression may therefore result from the pro-inflammatory status of SFAs-activated macrophages, given than pro-inflammatory macrophages are involved in the development of obesity complications (Wynn et al., 2013).

In conclusion, we show that SFAs promote GDF-15 expression and secretion in macrophages. SFAs-induced GDF15 expression involves ER stress and the PERK/eIF2/CHOP signaling pathway. UFAs prevent SFAs-induced GDF15 expression and ER stress. These new findings provide new molecular insights about how diet and lipid metabolism may regulate the development of obesity and T2D.