# ROLE OF CD1- AND MR1-RESTRICTED T CELLS IN IMMUNITY AND DISEASE

EDITED BY : Kazuya Iwabuchi and Luc Van Kaer PUBLISHED IN : Frontiers in Immunology

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# ROLE OF CD1- AND MR1-RESTRICTED T CELLS IN IMMUNITY AND DISEASE

Topic Editors:

Kazuya Iwabuchi, Kitasato University School of Medicine, Sagamihara, Japan Luc Van Kaer, Vanderbilt University School of Medicine, United States

CD1 and MR1 are major histocompatibility complex (MHC) class I-related proteins that bind and present non-peptide antigens to subsets of T cells with specialized functions. CD1 proteins typically present lipid antigens to CD1-restricted T cells, whereas MR1 presents vitamin B-based ligands and a variety of drugs and drug-like molecules to MR1-restricted T cells. The CD1 family of antigen presenting molecules has been divided into two groups: Group 1 contains CD1a, CD1b and CD1c, and Group 2 contains CD1d. Additionally, CD1e is expressed intracellularly and is involved in the loading of lipid antigens onto Group 1 CD1 proteins. Humans express both Groups 1 and 2 CD1 proteins, whereas mice only express CD1d. Group 1 CD1 proteins present lipid antigens to T cells that generally express diverse T cell receptors (TCRs) and exhibit adaptive-like functions, whereas CD1d presents lipid antigens to subsets of T cells that express either diverse or highly restricted TCRs and exhibit innate-like functions. CD1d-restricted T cells are called natural killer T (NKT) cells, which includes Type I or invariant NKT (iNKT) cells expressing semi-invariant TCRs, and Type II NKT cells expressing more diverse TCRs. CD1-restricted T cells have been implicated in a wide variety of diseases, including cancer, infections, and autoimmune, inflammatory and metabolic diseases. Additionally, NKT cells have been targeted for immunotherapy of disease with ligands such as α-galactosylceramide for iNKT cells, or sulfatide for Type II NKT cells. Like iNKT cells, MR1-restricted T cells express semi-invariant TCRs and display innate-like functions. MR1-restricted T cells, also called mucosal-associated invariant T (MAIT) cells, have been implicated in immune responses against a variety of pathogens such as Mycobacterium tuberculosis, Pseudomonas aeruginosa, Helicobacter pylori, hepatitis C virus and influenza virus. Moreover, these cells contribute to autoimmune and inflammatory diseases, including colitis, rheumatoid arthritis, psoriasis, lupus, and diabetes.

Citation: Iwabuchi, K., Van Kaer, L., eds. (2019). Role of CD1- and MR1-restricted T cells in Immunity and Disease. Lausanne: Frontiers Media. doi: 10.3389/978-2-88963-122-3

# Table of Contents

*06 Editorial: Role of CD1- and MR1-Restricted T Cells in Immunity and Disease*

Kazuya Iwabuchi and Luc Van Kaer

*12 Recruitment of MAIT Cells to the Intervillous Space of the Placenta by Placenta-Derived Chemokines*

Martin Solders, Laia Gorchs, Eleonor Tiblad, Sebastian Gidlöf, Edwin Leeansyah, Joana Dias, Johan K. Sandberg, Isabelle Magalhaes, Anna-Carin Lundell and Helen Kaipe

*28 T Cell Receptor Expression Timing and Signal Strength in the Functional Differentiation of Invariant Natural Killer T Cells*

Nyambayar Dashtsoodol, Sabrina Bortoluzzi and Marc Schmidt-Supprian

Maroua Haroun Ferhat, Aurélie Robin, Louise Barbier, Antoine Thierry, Jean-Marc Gombert, Alice Barbarin and André Herbelin

*64 The Pathophysiological Relevance of the iNKT Cell/Mononuclear Phagocyte Crosstalk in Tissues*

Filippo Cortesi, Gloria Delfanti, Giulia Casorati and Paolo Dellabona

*75 iNKT Cells Suppress Pathogenic NK1.1+CD8+ T Cells in DSS-Induced Colitis*

Sung Won Lee, Hyun Jung Park, Jae Hee Cheon, Lan Wu, Luc Van Kaer and Seokmann Hong

Dorian Stolk, Hans J. van der Vliet, Tanja D. de Gruijl, Yvette van Kooyk and Mark A. Exley

*119 Complex Network of NKT Cell Subsets Controls Immune Homeostasis in Liver and Gut*

Idania Marrero, Igor Maricic, Ariel E. Feldstein, Rohit Loomba, Bernd Schnabl, Jesus Rivera-Nieves, Lars Eckmann and Vipin Kumar

*126 Clinical Application of iNKT Cell-mediated Anti-tumor Activity Against Lung Cancer and Head and Neck Cancer*

Mariko Takami, Fumie Ihara and Shinichiro Motohashi

*132 Type II NKT Cells: An Elusive Population With Immunoregulatory Properties*

Avadhesh Kumar Singh, Prabhanshu Tripathi and Susanna L. Cardell

*140 Role of CD1d- and MR1-Restricted T Cells in Asthma* Chiaki Iwamura and Toshinori Nakayama *153 Tissue-Specific Roles of NKT Cells in Tumor Immunity* Masaki Terabe and Jay A. Berzofsky *164 Natural Killer T Cells and Mucosal-Associated Invariant T Cells in Lung Infections* François Trottein and Christophe Paget *181 Increased iNKT17 Cell Frequency in the Intestine of Non-Obese Diabetic Mice Correlates With High* Bacterioidales *and Low* Clostridiales *Abundance* Lorena De Giorgi, Chiara Sorini, Ilaria Cosorich, Roberto Ferrarese, Filippo Canducci and Marika Falcone *188 Invariant Natural Killer T and Mucosal-Associated Invariant T Cells in Asthmatic Patients* Guillaume Lezmi and Maria Leite-de-Moraes *197 Linking CD1-Restricted T Cells With Autoimmunity and Dyslipidemia: Lipid Levels Matter* Sreya Bagchi, Samantha Genardi and Chyung-Ru Wang *209 Factors Influencing Functional Heterogeneity in Human Mucosa-Associated Invariant T Cells* Joana Dias, Caroline Boulouis, Michał J. Sobkowiak, Kerri G. Lal, Johanna Emgård, Marcus Buggert, Tiphaine Parrot, Jean-Baptiste Gorin, Edwin Leeansyah and Johan K. Sandberg *216 CD1d-Invariant Natural Killer T Cell-Based Cancer Immunotherapy:* a*-Galactosylceramide and Beyond* Lisa A. King, Roeland Lameris, Tanja D. de Gruijl and Hans J. van der Vliet *223 It Takes "Guts" to Cause Joint Inflammation: Role of Innate-Like T Cells* Céline Mortier, Srinath Govindarajan, Koen Venken and Dirk Elewaut *231 Insights Into Mucosal-Associated Invariant T Cell Biology From Studies of Invariant Natural Killer T Cells* Lucy C. Garner, Paul Klenerman and Nicholas M. Provine *256 How Lipid-Specific T Cells Become Effectors: The Differentiation of iNKT Subsets* Haiguang Wang and Kristin A. Hogquist *269 Invariant Natural Killer T Cell Subsets—More Than Just Developmental Intermediates* S. Harsha Krovi and Laurent Gapin *286 Latent* Mycobacterium tuberculosis *Infection is Associated With a Higher Frequency of Mucosal-Associated Invariant T and Invariant Natural Killer T Cells* Dominic Paquin-Proulx, Priscilla R. Costa, Cassia G. Terrassani Silveira, Mariana P. Marmorato, Natalia B. Cerqueira, Matthew S. Sutton, Shelby L. O'Connor, Karina I. Carvalho, Douglas F. Nixon and Esper G. Kallas *295 Activation and Regulation of B Cell Responses by Invariant Natural Killer T Cells*

Derek G. Doherty, Ashanty M. Melo, Ana Moreno-Olivera and Andreas C. Solomos

Yoon Jeong Park, Jeu Park, Jin Young Huh, Injae Hwang, Sung Sik Choe and Jae Bum Kim

Günther Schönrich and Martin J. Raftery

*398 CD1d-Restricted Type II NKT Cells Reactive With Endogenous Hydrophobic Peptides*

Yusuke Nishioka, Sakiko Masuda, Utano Tomaru and Akihiro Ishizu

# Editorial: Role of CD1- and MR1-Restricted T Cells in Immunity and Disease

Kazuya Iwabuchi 1 \* and Luc Van Kaer 2 \*

*1 Department of Immunology, Kitasato University School of Medicine, Sagamihara, Japan, 2 Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine, Nashville, TN, United States*

Keywords: CD1, MR1, natural killer T cells, mucosal-associated invariant T cells, non-peptide antigens, immunity, immune-mediated disease

**Editorial on the Research Topic**

#### **Role of CD1- and MR1-Restricted T Cells in Immunity and Disease**

Products encoded by the major histocompatibility complex (MHC) present peptide antigens to T lymphocytes. MHC class I and class II products present peptide antigens to CD8+ or CD4+ T lymphocytes, respectively. In addition to these classical MHC class I molecules (also known as MHC class Ia molecules), numerous non-classical MHC class I molecules (also known as MHC class Ib molecules) have been identified (1). Some of these products are encoded by genes within the MHC, whereas others are encoded by genes outside the MHC. Key differences between class Ia and class Ib molecules are that the former are highly polymorphic, are expressed by most cell types, and present pathogen-derived peptides to CD8+ T cells, whereas the latter are oligomorphic, are less widely expressed, and are diverse in their capacity to present antigens to subsets of T lymphocytes with innate or adaptive immune functions. Some class Ib molecules such as mouse Qa-1 (HLA-E in human) and H-2M3 bind peptide antigens, others such as CD1 (cluster of differentiation-1) and MR1 (MHC-related protein-1) bind non-peptide antigens, and again others such as the mouse TL (thymus leukemia) and the human MIC (MHC class I polypeptide-related sequence) antigens are not known to bind antigen of any kind. This Research Topic focuses on the immunological functions of T lymphocytes restricted by CD1 or MR1 molecules, which present lipids or small metabolites, respectively, to subsets of T lymphocytes with conventional or unconventional functions [see (2–5) for a general review of these topics].

The CD1 family of antigen-presenting molecules has been divided into two groups: Group 1 contains CD1a, CD1b, and CD1c, and Group 2 contains CD1d (6). Additionally, human CD1e is expressed intracellularly and is involved in the loading of lipid antigens onto the other CD1 isotypes, which are all displayed at the cell surface. Humans express both Groups 1 and 2 CD1 proteins, whereas mice only express Group 2 CD1 proteins (i.e., CD1d). Group 1 CD1 proteins present lipid antigens to T cells that generally express diverse T cell receptors (TCRs) and exhibit adaptive-like functions, whereas CD1d presents glycolipid antigens to subsets of T cells that express restricted TCRs and exhibit innate-like functions (7, 8). CD1-restricted T cells have been implicated in a wide variety of diseases, including cancer, infections, and autoimmune, inflammatory and metabolic diseases.

Seminal studies with human autoreactive T cell lines led to the identification of lipid-reactive T cells restricted by CD1 molecules (9). Subsequent studies identified CD1-restricted T cells specific for microbial lipids, especially those derived from the cell wall of mycobacterial species (10, 11). While some of the initial T cell clones isolated expressed γδ TCRs, it is now clear that the majority of CD1-reactive T cells express αβ TCRs. The antigen-binding groove of CD1 is hydrophobic and

#### Edited and reviewed by:

*Hongbo Chi, St. Jude Children's Research Hospital, United States Lewis Zhichang Shi, University of Alabama at Birmingham, United States*

#### \*Correspondence:

*Kazuya Iwabuchi<EMAIL_ADDRESS>Luc Van Kaer<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to T Cell Biology, a section of the journal Frontiers in Immunology*

Received: *19 June 2019* Accepted: *22 July 2019* Published: *06 August 2019*

#### Citation:

*Iwabuchi K and Van Kaer L (2019) Editorial: Role of CD1- and MR1-Restricted T Cells in Immunity and Disease. Front. Immunol. 10:1837. doi: 10.3389/fimmu.2019.01837*

**6**

differs in size between distinct CD1 isoforms, which permits these molecules to bind diverse lipid or glycolipid antigens (7, 12). Some lipids, such as the self-antigen sulfatide, can bind with all CD1 isoforms. Each of the CD1 isoforms can present mycobacterial lipid antigens, albeit distinct in structure, to CD1 restricted T cells. Tetrameric CD1 molecules loaded with lipid antigens have been generated for all CD1 isotypes and have greatly assisted in understanding the biology of CD1-restricted T cells (5).

Most Group 1 CD1-restricted T cell clones described are autoreactive, and likely represent a substantial part of the T cell repertoire in humans, estimated at 1/300 to 1/10 circulating T cells (13). The majority of these T cell clones express diverse αβ TCRs, although subsets of Group 1 CD1-restricted T cells expressing conserved TCRs have also been identified (14). As argued in the review article by Bagchi et al., emerging evidence indicates that Group 1 CD1-restricted T cells can contribute to autoimmunity, especially in diseases associated with dyslipidemia. For example, CD1c-restricted T cells have been implicated in progression of systemic lupus erythematosus (SLE). Additionally, CD1a-restricted autoreactive T cells have been implicated in psoriasis and the response to insect venoms. Since Group 1 CD1-restricted T cells recognizing mycobacterial lipids are expanded in patients infected with Mycobacterium tuberculosis or vaccinated with Bacillus Calmette-Guérin, it is likely that these cells exhibit adaptive-like properties and play a protective role during infection. A major challenge in studying the functions of Group 1 CD1 molecules is their absence from mice. Some researchers have therefore resorted to analyzing CD1-restricted T cell responses in guinea pigs, which express several CD1 isoforms. Guinea pigs induce Group 1 CD1-restricted T cell responses to mycobacterial lipids (15), suggesting adaptive-like functions of these cells. Other studies have employed a humanized CD1 transgenic mouse model (16) or humanized immunodeficient mice engrafted with human fetal thymic tissue and hematopoietic stem cells (17). These studies similarly revealed that M. tuberculosis-reactive Group 1 CD1-restricted T cells exhibit adaptive-like functions, suggesting promise for the development of lipid-based vaccines for mycobacterial and other infections. Studies with human CD1 transgenic mice also suggested a role of CD1b-restricted T cells in the generation of skin inflammation (18). Thus, as discussed in the review article by Lepore et al., the available evidence indicates that Group 1 CD1-restricted T cells share many functional properties with conventional, MHC class I-restricted T cells. Group 1 CD1-restricted T cells also hold promise for immunotherapy, as illustrated by studies showing that a subset of CD1c-restricted T cells exhibits strong reactivity for methyllysophosphatidic acid, a lipid antigen produced by leukemic cells (19). When adoptively transferred into immunodeficient mice, such T cells were able to limit the spread of CD1cexpressing human leukemia cells (19). Additionally, the CD1apresented skin antigen, squalene (20), is a widely used adjuvant that enhances vaccine efficacy. Other antigens presented by Group 1 CD1 molecules could be similarly employed to modulate CD1-restricted T cell responses during vaccination or immunotherapy.

CD1d-restricted T cells are also called natural killer T (NKT) cells, which includes Type I or invariant NKT (iNKT) cells expressing semi-invariant TCRs, and Type II or diverse NKT (dNKT) cells expressing more diverse or oligoclonal TCRs (21). NKT cells have been targeted for immunotherapy of disease with ligands such as α-galactosylceramide (α-GalCer) for iNKT cells (22), or sulfatide for dNKT cells (23).

iNKT cells were originally identified as a subset of T cells expressing an invariant TCR in mice and humans (11, 24). The reactivity of these cells was subsequently shown to be restricted by CD1d (25). iNKT cells are highly conserved between mice, humans and other mammalian species (26). The iNKT TCR is made of Vα14-Jα18 and Vβ8.2/7/2 chains in mice or homologous Vα24-Jα18 and Vβ11 chains in humans (2, 3, 21). In mice, iNKT cells are most abundant in liver and adipose tissue, where they can represent up to 30–40% of the T cell population, are present at significant numbers in peripheral blood, spleen, thymus, and bone marrow (1–5% of all mature T cells), and are also found in lymph nodes, skin, and mucosal surfaces in the intestine and lungs (<1% of all T cells). However, these cells are quite rare and have variable frequency in humans (e.g., 0.005–0.2% of all T cells in peripheral blood). A variety of endogenous and exogenous lipid antigens for these cells have been identified (7, 8). All iNKT cells react with α-GalCer (27), an optimized version of a natural product originally isolated from a marine sponge, and α-GalCer-loaded CD1d tetramers selectively bind with iNKT cells. As described in the review by Ren et al., genetic tools to study iNKT cells include Jα18- and CD1d-deficient mice, as well as mouse Vα14-Jα18 and human Vα24-Jα18 TCR transgenic animals. iNKT cells express markers that are characteristic of the natural killer (NK) cell lineage, exhibit an activated or memory phenotype, are enriched in liver and mucosal tissues, have a tendency for autoreactivity, and are unable to generate classical memory responses. In addition to TCR-mediated activation signals, these cells are highly responsive to innate immune activation signals, such as innate cytokines produced in response to toll-like receptor (TLR) signaling in antigen-presenting cells (28). iNKT cells often become activated during situations of sterile inflammation involving release of damage-associated molecular patterns, also called alarmins. As discussed in the perspective by Ferhat et al., the alarmin IL-33 might play a key role in recruiting iNKT cells to the inflammatory site and in enhancing their regulatory and effector functions. iNKT cells can produce a variety of pro- and anti-inflammatory cytokines, and subsets of iNKT cells biased for production of type 1, 2, or 3 cytokines, called iNKT1, iNKT2 and iNKT17 cells, respectively, are enriched in different tissues (29). iNKT cells acquire these unusual properties during their development in the thymus, as discussed in the reviews by Krovi and Gapin,Wang and Hogquist, Yang et al., and Dashtsoodol et al.. A key driver in the acquisition of an innate effector program by these cells is the induction of the transcription factor promyelocytic leukemia zinc finger (PLZF) during thymic selection on CD1d-expressing CD4+CD8+ (double-positive) thymocytes (30, 31). Additionally, iNKT cells undergo unique epigenetic modifications in the thymus that influence their development, maturation and functional differentiation. Following the activation of iNKT cells by lipids and/or innate signals, these cells can activate and modulate a variety of innate and adaptive immune cells and thus impact overall immune responses and disease (32). The review article by Cortesi et al. discusses how reciprocal interactions between iNKT cells and mononuclear phagocytes in tissues impact physiological and pathological conditions. Additionally, the review articles by Lang, Doherty et al., and Fujii et al. discuss how iNKT cells can interact with B cells to influence humoral immune responses, and Fujii et al. further review the capacity of iNKT cells to license dendritic cells to augment humoral and cellular immune responses.

Consistent with their potent immunomodulatory properties, iNKT cells contribute to protective immune responses against a variety of microorganisms, as discussed in the review articles by Kinjo et al., Trottein and Paget, and Huang et al.. For example, the original research article by Paquin-Proulx et al. provides evidence for dynamic regulation of iNKT cell numbers and functions during M. tuberculosis infection, suggesting a role for these cells in immunity against this organism. Interestingly, several microbial organisms, especially viruses that cause persistent infections, can evade CD1d-restricted immune responses (33), a topic discussed in the review article by Schönrich and Raftery. One particularly clever way to evade iNKT cell responses is illustrated by human immunodeficiency virus (HIV), which can infect iNKT cells, resulting in their depletion during disease progression (34). The original research article by Singh et al. provides evidence that patients with non-progressive HIV infection contain functionally competent iNKT cells, whereas anti-retroviral treatment of patients with progressive infection fails to restore iNKT cell functions.

iNKT cells have been implicated in natural immunity against tumors, a topic discussed by Terabe and Berzofsky and Stolk et al.. These cells also contribute to a variety of autoimmune and inflammatory diseases (28). The review by Bagchi et al. focuses on the role of iNKT cells in autoimmune diseases such as SLE, psoriasis, diabetes, and rheumatoid arthritis that are characterized by dyslipidemia. iNKT cells also play a role in the generation of inflammatory bowel disease, as illustrated by the original research article by Lee et al., which provides evidence for a role of iNKT cells in suppressing disease in a model of colitis mediated by pathogenic CD8+ T cells. The review articles by Lezmi and Leite-de-Moraes, Iwamura and Nakayama, and Ryu et al. focus on the role of lung iNKT cells in asthma and other pulmonary disorders. These cells also contribute to the pathogenesis of alcoholic and non-alcoholic fatty liver disease, which is discussed in the review articles by Huang et al. and Marrero et al.. The review article by Ververs et al. describes the response of iNKT cells to metabolic activation in diseases such as atherosclerosis and obesity. Several review articles, including those by Park et al., Satoh and Iwabuchi, and Ren et al., discuss the role of iNKT cells in the development of obesity and obesity-associated insulin-resistance, which is influenced by many different factors (35, 36). The divergent findings obtained in different laboratories for the role of iNKT cells in obesityassociated conditions might be caused in part by different models of iNKT cell-deficiency employed, a possibility discussed in the review article by Ren et al.. Additionally, differences in the microbiota present in different mouse colonies might play a role, as the functional status of iNKT cells is impacted by microbiota (37–39). The topic of functional alterations in iNKT cells imparted by gut microbiota is discussed by Marrero et al. in the context of liver diseases and by Mortier et al. in the context of rheumatic diseases. Additionally, the original research article by De Giorgi et al. provides evidence that the abundance of certain microbiota in the gut of diabetes-prone non-obese diabetic mice increases the intestinal iNKT17 subset in these animals, possibly contributing to disease pathogenesis.

The immunomodulatory properties of iNKT cells have been exploited for the development of disease prophylaxis and therapy (22). Many of these studies have been performed with the iNKT cell ligand α-GalCer or its structural analogs. The adjuvant activities of iNKT cells have been exploited for the development of vaccines against microbes and tumors, as discussed in the review articles by Lang, Doherty et al., Fujii et al., and Kinjo et al.. As discussed by Kinjo et al., glycolipid activation of iNKT cells during infection can enhance antimicrobial immunity and hasten microbial clearance. Many studies have explored the therapeutic activities of iNKT cells against tumors and, as discussed in the review articles by Takami et al. and King et al., multiple clinical trials have already been performed. The therapeutic potential of iNKT cells in autoimmune diseases is discussed by Van Kaer and Wu.. In addition to these glycolipid antigen-mediated methods to elicit the therapeutic properties of iNKT cells, diseases where iNKT cells play a pathogenic role might benefit from iNKT cell depletion, a possibility that is being explored in sickle cell disease with antibodies directed against the invariant iNKT TCR (40).

dNKT cells express a more diverse TCR repertoire than iNKT cells (21, 23). In mice, dNKT cells are less prevalent than iNKT cells, whereas in humans dNKT cells outnumber iNKT cells. dNKT cells interact with multiple different lipid antigens, and a prominent subset reacts with the self-antigen sulfatide. While the sulfatide-reactive subset can be identified with sulfatide-loaded CD1d tetramers, rigorous identification of the entire dNKT cell population remains challenging. Curiously, as discussed in the review article by Nishioka et al., a subset of dNKT cells can react with hydrophobic peptides, including a peptide derived from type II collagen. As discussed in the review by Ren et al., the functions of dNKT cells are often deduced from studies comparing CD1d-deficient mice lacking both iNKT and dNKT cells with Jα18-deficient mice lacking only iNKT cells. dNKT cells share with iNKT cells expression of NK and memory markers, response to innate activation signals, innatelike effector functions, and absence of immunological memory. As discussed in the review article by Singh et al., dNKT cells can play both protective and pathogenic roles in a variety of diseases. Several review articles included in this Research Topic discuss the roles of dNKT cells in specific diseases. Trottein and Paget focus on lung infections, Terabe and Berzofsky and Stolk et al. on cancer, Iwamura and Nakayama on asthma, Satoh and Iwabuchi on obesity and insulin resistance, and Marrero et al. on inflammatory diseases of the liver and gut. In some conditions, such as cancer and steatohepatitis, dNKT appear

to play opposing roles to iNKT cells (41). Emerging evidence, discussed in the review article by Marrero et al., has revealed substantial cross-regulation between iNKT and dNKT cells.

Sulfatide has been employed to target the sulfatide-reactive subset of dNKT cells for therapeutic purposes (23). As discussed in the review articles by Singh et al. and Marrero et al., sulfatide has beneficial effects in some infections and models of autoimmunity and liver inflammation. dNKT cells reactive with collagen type II peptide have also been targeted therapeutically (using cognate peptide), employing an experimental model of rheumatoid arthritis, as discussed in the review article by Nishioka et al..

The antigen-binding groove of MR1 is lined with aromatic residues, which facilitates binding with microbial vitamin B metabolites and similar compounds (42). The majority of MR1 restricted T cells express semi-invariant TCRs (43). Such cells are called mucosal-associated invariant T (MAIT) cells, were first identified as a clonally enriched T cell population in humans and mice (44, 45), and were subsequently shown to be restricted by MR1 (46) and to react with vitamin B metabolites (47). MAIT cells express Vα19-Jα33 chains in mice and homologous Vα7.2- Jα33 chains in humans, and these cells can be identified by staining with vitamin B metabolite-loaded MR1 tetramers. In humans, they represent ∼3–5% of T cells in peripheral blood and intestine and up to 40% of T cells in liver. However, these cells are very rare in laboratory mice (<1% of all T cells). In addition to vitamin B metabolites, MAIT cells can react with a range of drugs and drug-like molecules, which can either activate or suppress these cells (48). Genetic tools to study MAIT cells include MR1- and Jα33-deficient mice and transgenic mice carrying the invariant Vα19-Jα33 TCR. As discussed in the review article by Garner et al., many of the studies on MAIT cells have been guided by the available biology on iNKT cells. MAIT cells share with iNKT cells an effector-memory phenotype, enrichment in liver and mucosal sites, expression of PLZF that drives an innate effector phenotype, response to innate signals, and the absence of classical immune memory. The antigen-specificity and activation requirements of MAIT cells are discussed in the review article by Xiao and Cai. Emerging evidence, discussed in the review article from Dias et al., has revealed functional heterogeneity within the MAIT population with regard to cytokine production, akin to the iNKT1 and iNKT17 subsets of iNKT cells (49). MAIT cells have been implicated in immune responses against a variety of pathogens, including but not limited to organisms containing vitamin B metabolites, a topic discussed in the review article by Trottein and Paget for lung infections. For example, the original research article by Paquin-Proulx et al. reports increased frequency of MAIT cells in individuals infected latently with M. tuberculosis, an organism that contains an intact riboflavin synthesis pathway, suggesting a potential role in disease pathogenesis. Moreover, MAIT cells can infiltrate tumors, and their potential role in anti-tumor immunity is discussed in the review article by Stolk et al.. The original research article by Solders et al. shows that MAIT cells are recruited to the intervillous space of the placenta, where they might play a role in fetal-maternal interactions. The review articles by Lezmi and Leite-de-Moraes and Iwamura and Nakayama discuss the potential role of MAIT cells in allergic asthma. The review article by Huang et al. discusses the role of these cells in inflammatory diseases of the liver, and the review article by Chiba et al. discusses their functions in animal models of autoimmune and inflammatory diseases. Finally, like iNKT cells, the development and functions of MAIT cells are substantially modulated by the presence of microbiota, which has a significant impact on disease, a topic discussed in the review article by Mortier et al. for rheumatic diseases. Although not yet fully explored, MAIT cells hold significant potential for therapeutic targeting, using vitamin B metabolites or drug-like molecules that could be employed to either potentiate or suppress MAIT cell responses.

Recent studies have identified subsets of MR1-restricted T cells that do not express the invariant MAIT TCR (42, 50). Some of these cells react with riboflavin-based antigens and exhibit innate-like effector functions, whereas others have a distinct antigen-reactivity and exhibit characteristics of adaptive immune effector functions, as discussed in the review article by Lepore et al.. Thus, these findings suggest additional similarities in the biology of MR1- and CD1d-restricted T cells.

The articles included in this Research Topic illustrate the breath of immune responses regulated by CD1- and MR1 restricted T cells, which include subsets with innate- and adaptive-like properties. An attractive property of the CD1 and MR1 antigen presentation systems, as compared with the classical MHC antigen presentation system, is that they can be more easily targeted in vaccines and immunotherapies. CD1 and MR1 exhibit limited polymorphism and are recognized by T cells that include subsets expressing conserved (i.e., public) TCRs (14). As such, it is feasible to target these cells across the genetically diverse human population in an antigen-specific manner. A better understanding of the basic biology of these cells and their role in different disease processes, together with the development of improved tools to target them, should facilitate the realization of this therapeutic promise.

#### AUTHOR CONTRIBUTIONS

KI and LV served as co-editors for the Research Topic and edited the manuscript. LV wrote the first draft.

# FUNDING

Work in the authors' labs was supported by the Japan Society for Promotion of Science (to KI), the Japan Agency for Medical Research and Development (to KI), the Japan Ministry of Education, Culture, Sports, Science and Technology (to KI), the National Institutes of Health (to LV), the National Multiple Sclerosis Society (to LV), and the American Heart Association (to LV).

#### ACKNOWLEDGMENTS

We are grateful to all colleagues who contributed and/or reviewed manuscripts for this Research Topic.

# REFERENCES

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Iwabuchi and Van Kaer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Recruitment of MAIT Cells to the Intervillous Space of the Placenta by Placenta-Derived Chemokines

Martin Solders 1,2 \*, Laia Gorchs 2 , Eleonor Tiblad3 , Sebastian Gidlöf 3,4, Edwin Leeansyah5,6 , Joana Dias 5 , Johan K. Sandberg5 , Isabelle Magalhaes 7 , Anna-Carin Lundell 8 and Helen Kaipe1,2 \*

1 Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden, 2 Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden, 3 Center for Fetal Medicine, Karolinska University Hospital and Department of CLINTEC, Karolinska Insitutet, Stockholm, Sweden, 4 Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden, 5 Center for Infectious Medicine, Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden, 6 Program in Emerging Infectious Diseases, Duke-National University of Singapore Medical School, Singapore, Singapore, 7 Department of Oncology/Pathology, Karolinska Institutet, Stockholm, Sweden, 8 Department of Rheumatology and Inflammation Research, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

#### Edited by:

Kazuya Iwabuchi, Kitasato University School of Medicine, Japan

#### Reviewed by:

Mariolina Salio, University of Oxford, United Kingdom Marco Lepore, Immunocore, United Kingdom

> \*Correspondence: Martin Solders<EMAIL_ADDRESS>Helen Kaipe<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to T Cell Biology, a section of the journal Frontiers in Immunology

Received: 30 January 2019 Accepted: 22 May 2019 Published: 06 June 2019

#### Citation:

Solders M, Gorchs L, Tiblad E, Gidlöf S, Leeansyah E, Dias J, Sandberg JK, Magalhaes I, Lundell A-C and Kaipe H (2019) Recruitment of MAIT Cells to the Intervillous Space of the Placenta by Placenta-Derived Chemokines. Front. Immunol. 10:1300. doi: 10.3389/fimmu.2019.01300 The intervillous space of the placenta is a part of the fetal-maternal interface, where maternal blood enters to provide nutrients and gas exchange. Little is known about the maternal immune cells at this site, which are in direct contact with fetal tissues. We have characterized the T cell composition and chemokine profile in paired intervillous and peripheral blood samples from healthy mothers giving birth following term pregnancies. Mucosal-associated invariant T (MAIT) cells and effector memory (EM) T cells were enriched in the intervillous blood compared to peripheral blood, suggesting that MAIT cells and other EM T cells home to the placenta during pregnancy. Furthermore, pregnant women had lower proportions of peripheral blood MAIT cells compared to non-pregnant women. The levels of several chemokines were significantly higher in intervillous compared to peripheral blood, including macrophage migration inhibitory factor (MIF), CXCL10, and CCL25, whereas CCL21, CCL27 and CXCL12 were lower. Migration assays showed that MAIT cells and EM T cells migrated toward conditioned medium from placental explants. A multivariate factor analysis indicated that high levels of MIF and CCL25 were associated with high proportions of MAIT cells in intervillous blood. Blocking of MIF or a combination of MIF, CCL25, and CCL20 in migration assays inhibited MAIT cell migration toward placenta conditioned medium. Finally, MAIT cells showed migratory capacities toward recombinant MIF. Together, these findings indicate that term placental tissues attract MAIT cells, and that this effect is at least partly mediated by MIF.

Keywords: MAIT cells, placenta, chemokines, reproductive immunology, intervillous space, T cells, MIF

# INTRODUCTION

During pregnancy, one of the main functions of the placenta is to provide the growing fetus with oxygen and nutrients from the maternal blood circulation. The pregnant woman's arterial blood fills the intervillous space of the placenta, where it comes in direct contact with the fetal villi protruding from the fetal part of the placenta. Fetal blood vessels run inside the villi, and gas and nutrients

**12**

are exchanged over a thin membrane of fetal cytotrophoblasts and syncytiotrophoblasts (1). Another site for fetal-maternal interactions is the decidua, a maternal membrane reformed from the endometrium during pregnancy. The decidua is readily infiltrated by maternal immune cells that can interact with invasive fetal extravillous trophoblasts [reviewed in (2)].

The circulation of maternal blood in the intervillous space from a physiological perspective has been described (3). The intervillous blood (IVB) is exchanged 2–3 times per minute (1), suggesting that the cell composition in IVB may reflect that of peripheral blood (PB). However, our recent findings showed that mucosal-associated invariant T (MAIT) cells and effector memory (EM) T cells are enriched in the IVB of term placentas (4), indicating that certain immune cell subsets are recruited to or retained in the intervillous space. The potential factors involved in the migration of maternal immune cells to the placenta is still unexplored.

MAIT cells are an invariant type of T cell that respond to microbial derived metabolites from riboflavin synthesis presented by the non-polymorphic MHC class I related molecule (MR1) (5). The MAIT cell T cell receptor invariably uses the Vα7.2-segment coupled with either Jα33, 12 or 20, paired with a limited set of β chains (6–8). Besides the MR1- and T cell receptor-dependent activation, MAIT cells can be partially activated or co-stimulated by cytokines, including IL-7, IL-12, IL-15, and IL-18 (8–11). Thus, MAIT cells can respond in a T cell receptor-independent manner, broadening their relevance to viral infections and autoimmune disorders (12–15). Upon activation, MAIT cells secrete IFN-γ and TNF-α, (16, 17) and MAIT cells from the liver and the female genital tract also secrete measurable levels of IL-17 and IL-22 (18, 19). Activated MAIT cells upregulate the expression of the cytotoxic effector molecules granzyme B and perforin, and can kill infected target cells in an MR1-restricted manner (20). The importance of MAIT cells in pregnancy is unknown.

Placental tissue and fetal trophoblasts produce a wide array of chemokines in early pregnancy (21), and chemokines and their receptors play an instrumental role in trophoblast invasiveness, angiogenesis, and recruitment of immune cells to the decidua [reviewed in (22)]. Macrophage migration inhibitory factor (MIF) is a chemokine-like cytokine highly expressed in placental tissues (23, 24). MIF expression has been shown in syncytiotrophoblasts, cytotrophoblasts and extravillous trophoblasts (23, 25), but its function in pregnancy is unclear.

Since particular immune cell subsets are enriched in IVB compared to PB (4), we hypothesized that the placenta produces chemotactic mediators that are involved in attracting certain maternal immune cells to the intervillous space. Therefore, the main aim of this study was to examine if placental-derived factors are involved in recruiting MAIT cells to the placenta.

#### MATERIALS AND METHODS

#### Sample Collection

Healthy individuals (n = 36, median age 34, range 21–42) donated their placentas after informed consent, subsequent to planned cesarean sections following uncomplicated term pregnancies (median gestational week 39, range 38–42). The regional review board of ethics in research at Karolinska Institutet approved the donation of peripheral blood and placentas (entry numbers 2009/418-31/4, 2010/2061-32, and 2015/1848-31/2). Female blood donors were used as a control for non-pregnant women (n = 27, median age 46, range 22–71).

Data on MAIT cell frequencies from pregnant women has been published previously for 21 out of 36 donors (4). Parts of the T- and MAIT cell phenotype data were published previously for 11 out of 36 donors (4).

#### Cell Isolation

Peripheral blood (PB) samples were collected a few hours before the caesarian sections. The description of isolation of IVB and decidua parietalis has been published previously (4). Briefly, placentas were placed in a sterile container in the operation room, and then taken directly to the lab. After removal of the fetal membranes and clamping of the umbilical cord, the placentas were placed with the maternal side facing up.  The placenta was turned around and lifted so that the maternal side faced downwards and IVB was collected on a sterile petri dish and immediately transferred to heparin tubes. The samples of PB and IVB were centrifuged at 600 g for 8 min after which plasma samples were collected and stored at −80◦C until use. The blood was diluted 1:2 with PBS, and mononuclear cells were isolated by density gradient centrifugation (Lymphoprep, Axis-Shield, Oslo, Norway). The fetal membranes were placed with the decidua facing up. After extensive washing and removal of visible blood clots, the decidua parietalis was mechanically scraped off from the chorion, pooled and washed with PBS by repeated short centrifugations. Cells were released from the tissue by using a GentleMACS Dissociator (Miltenyi Biotec, Bergisch Gladbach, Germany). After filtering and washing, mononuclear cells were isolated by density gradient centrifugation (Lymphoprep, Axis-Shield, Dundee, Scotland).

Cells were either stained directly for flow cytometry, or resuspended in RPMI (HyClone, GE Health Sciences, South Logan, UT) medium supplemented with 10% fetal calf serum, 100 U/ml penicillin, 100µg/ml streptomycin (complete medium) containing 10% DMSO and frozen in aliquots in liquid nitrogen. In our previous publication, we found the isolated maternal cell product to have a median fetal DNA contamination of 12.1% (range 5.2–19.4, n = 6) (4).

### Flow Cytometry

IVB and PB samples were analyzed in pairs, either fresh or thawed after freezing. Frozen cells were thawed in complete medium, washed in PBS and counted, and fresh cells were used directly after isolation. The cells were plated in a 96-well plate, ≤ 1 × 106 cells/well. Staining was carried out in 50 µL of CliniMACS PBS/EDTA buffer (Miltenyi Biotech, Bergish Gladbach, Germany) supplemented with 0.1% bovine serum albumin (FACS-buffer) to which antibodies were added, and incubated for 30 min at 4◦C. After washing, the cells were stained with 7AAD, which was used to distinguish live from dead cells. The MR1 tetramers were produced by the NIH Tetramer Core Facility as permitted to be distributed by the University of Melbourne, and the MR1 tetramer technology was developed jointly by Dr. James McCluskey, Dr. Jamie Rossjohn, and Dr. David Fairlie. The flow cytometry antibodies used in this study are listed in **Supplementary Table S1**. Data were collected using a BD FACSCanto flow cytometer and analyzed with FlowJo software (Tree Star, Ashland, OR, USA). Data on conventional T cells were analyzed after excluding CD161+ and Vα7.2+ T cells.

#### Placenta Conditioned Medium

Placental explant conditioned medium were isolated using a slightly modified version of the method described for 1st trimester placentas by Svensson-Arvelund et al. (21). Following extraction of IVB, the placenta was placed with the maternal side facing up. Using scissors, the decidua basalis was removed, and from the underlying tissue, biopsies of approximately 1 cm3 were cut. Between 5 and 10 biopsies were taken from different places of the placenta. The tissue biopsies were then pooled and dissected into as small pieces as possible using forceps and a scalpel. Macroscopically identifiable blood vessels were removed. The dissected tissue was then washed extensively with PBS by repeated cycles of short centrifugations until the PBS was no longer colored by the tissue, usually 10–20 times. The tissue was then placed in 24- (50–100 mg of tissue) or 6-well plates (250–500 mg of tissue), and 10 µL of complete medium/mg of tissue was added. Multiple plates were set up at the same time, and incubated at 37◦C for 48 and 72 h. At the end of incubation, the content of multiple wells was harvested and pooled, and following centrifugation (600 g, 8 min), supernatants were collected and frozen in aliquots at −80◦C.

#### Multiplex Chemokine Assay

Paired frozen plasma samples from IVB and PB (n = 25) and placental explant supernatants (n = 5) were analyzed for cytokine and chemokine concentrations using a Magpix with Luminex Xponent software (Luminexcorp, Austin, TX, USA) and the Bio-Plex Pro Human Chemokine 40-Plex kit (BIO-RAD, Hercules, CA, USA) according to the manufacturer's instructions. The detection level of each analyte is shown in **Supplementary Table S2**.

#### Migration Assay

T cells were purified from PBMCs from healthy donors by negative selection (Pan T Cell Isolation Kit, Miltenyi Biotec, Bergisch Gladbach, Germany) according to the manufacturer's instructions. Placenta conditioned medium from 48 or 72 h cultures was thawed, diluted 50% in complete medium, and 600 µL was added to a 24-well plate. Complete medium only was used as a negative control. Blocking reagents against CCL20 (clone 67310, 1µg/ml, R&D Systems, Minneapolis, MN, USA), CCL25 (clone 52513, 3µg/ml, R&D) and/or MIF (ISO-1, 100µM, Tocris Bioscience, Bristol, UK) or the corresponding isotype/diluent was then added to the wells. ISO-1 was diluted in PBS with 0.1% DMSO. For the MIF migration assay, RPMI medium without serum containing 100 or 250 ng/ml recombinant MIF (R&D Systems) were added to the lower well. The medium control well contained only RPMI without serum. Ten of the experiments were performed using purified T cells (isolated as described above). Six samples were performed by using purified T cells that were also depleted of CD4+ T cells, using CD4+ T cell isolation beads (Miltenyi), to enrich CD8+ T cells. Transwell inserts (5µm pore size, Costar, Cambridge, MA, USA) were placed into each well, and 1 × 106 T cells resuspended in 100 µL RPMI without serum were then added on top of the transwell insert. Plates were incubated at 37◦C for 3 h. The transwell inserts were removed, and the content of each well was harvested, transferred to a 15 ml tube, centrifugated (600 g, 8 min), re-suspended in FACS-buffer, and stained for flow cytometry. Careful measures were taken to treat all paired samples equally; they were re-suspended in the same volume of FACS-buffer, washed in parallel, and run for the same time in the flow cytometer. Results are presented as cell counts or proportions within the CD3+ or CD8+ T cell populations as indicated in the figures.

#### Statistical Analysis

We used multivariate orthogonal projection to latent structures (OPLS) analyses as a tool to screen for differences between PB and IVB and associations between specific immune cell subsets and chemokine levels. Variables that showed the strongest association to classes or variables were further evaluated by univariate analysis. Multivariate orthogonal projection to latent structures by means of partial least squares discriminant analysis (OPLS-DA) was used to obtain a maximum separation of X-variables (T cell phenotypes or chemokine levels) based on class information (peripheral and intervillous blood, i.e., PB and IVB) (SIMCA software, Sartorius Stedim Biotech, Umeå, Sweden). The twoclass (PB and IVB) discrimination OPLS-DA model presented in **Figure 1A** is a default score scatter observation plot with one predictive component t[1] and one orthogonal component to [1]. The scatter plot of t[1] vs. to[1] is a window in the X space in which the separation of the two classes of observations occurs in the horizontal t[1] direction and the within class variability is expressed in the vertical to[1] direction. Linear OPLS analysis was implemented to investigate associations between a selected Y-variable (proportion of MAIT cells) and a set of X-variables (chemokine levels in IVB). The contribution of each X-variable, variable influence of projection (VIP) values, to the OPLS models were calculated. For the analysis of T cell variabilities, X-variables with a VIP value below 0.81 were excluded and a new model was generated based on remaining variables. The scale presented on the x and y-axis in the OPLS-DA plot (**Figure 1A**) and on the y-axis of the OPLS plots (**Figures 1B**, **4A**) is a dimensionless scale in which the loading vector is normalized to unit length. The validation of OPLS analyses is based on the goodness of fit, or R2, which tells how well the data set can be mathematically reproduced. The goodness of predictivity, or Q2, tells how well the model can predict future data of a test set. Cross validation is performed by SIMCA software to estimate Q2. Briefly, cross validation is performed by dividing the data set into a number of groups and then developing a number of parallel models from the reduced data with one of the groups deleted. After developing a model, the deleted data are used as a test set, and differences between actual and predicted values are calculated for the test set, eventually leading forward to the Q2-value. Logarithmic values were used in the multivariate analysis. The factors contributing most to the separation were further analyzed using the twotailed Wilcoxon matched-pairs signed rank test. To investigate correlations between two factors, the Spearman's rank correlation test was used. To detect differences across two groups of unpaired samples, the two-tailed Mann-Whitney test was used (GraphPad Software, La Jolla, CA). A P of < 0.05 was considered significant.

#### RESULTS

### T Cell Subsets and Phenotypes Are Different in Intervillous Compared to Peripheral Blood

By using multivariate discriminant analysis, we first examined the T cell profiles in PB and IVB based on 53 parameters, which are all displayed in **Supplementary Figure S1**. As depicted in the observation plot in **Figure 1A**, a clear separation was found between PB and IVB based on the T cell variables assessed. The X-variables that showed the strongest associations with PB or IVB are shown in the loading plot in **Figure 1B**, a model based on X-variables with VIP values ≥ 0.81. A VIP column plot for all analyzed parameters is shown in **Supplementary Figure S1**. Further investigating the two groups using univariate statistical analysis, we found several significant differences in the T cell compartment between PB and IVB. The proportions of CD3+ T cells within CD45+ cells were similar in PB and IVB, but IVB had higher proportions of CD8+ and CD4 and CD8 double negative (DN) T cells compared to PB (**Figure 1C**). The proportion of EM CD8+ T cells was a median 2.1-fold higher in IVB compared to PB, with a concomitant lower proportion of naïve T cells (**Figure 1D**). A similar pattern was observed among CD4+ T cells, with a 1.7-fold higher proportion of EM cells in IVB compared to PB (data not shown). CD8+ T cells from IVB were more activated compared to PB CD8+ T cells, as shown by an increased expression of CD69 and HLA-DR (**Supplementary Figure S2A**). IVB CD8+ T cells also expressed the co-inhibitory markers PD-1 and TIM-3 to a larger degree compared to PB CD8+ T cells (**Supplementary Figure S2A**). Taken together, this shows that maternal T cells in the intervillous space to a larger degree are activated and of an EM phenotype compared to their peripheral counterparts. Representative flow cytometry plots are shown in **Supplementary Figure S3**.

## Enrichment of MAIT Cells in Intervillous Blood

As previously shown (4), but now with a larger number of donors, MAIT cells were enriched in IVB both within CD3+ T cells and within CD45+ leukocytes, with a median 2.1-fold and 2.3-fold higher proportion, respectively, in IVB compared to PB (**Figure 1E**). This suggests that MAIT cells accumulate in the intervillous space of the placenta during pregnancy. The proportion of MAIT cells in PB from the cohort of pregnant women was compared to that of healthy non-pregnant women. Despite the lower median age of the pregnant compared to the non-pregnant women (34 vs. 46 years, respectively), the non-pregnant women had significantly higher levels of MAIT cells in PB compared to pregnant women (**Figure 1F**). Together, this suggests that a proportion of MAIT cells may leave the circulation and enter the placenta during late healthy pregnancy. The proportion of CD4+, CD8+ or CD4/CD8 DN conventional T cells did not significantly differ between pregnant and non-pregnant women (**Supplementary Figure S4**). Data on the proportion of conventional EM T cells was not available in this cohort of non-pregnant women.

Throughout this study, MAIT cells were defined by the expression of CD161 and Vα7.2. To confirm that these cells were MR1-restricted, we stained PB and IVB cells from three donors with the MR1 5-OP-RU tetramers. It showed that similar proportions of MAIT cells were found when using the MR1 tetramer or the CD161 and Vα7.2 gating strategy both in PB and IVB (**Figure 1G**). Out of the CD161+Vα7.2+ cells, a median of 93.6% and 93.9% stained positive for the MR1 tetramer in PB and IVB, respectively (**Supplementary Figure S2B**). The negative control tetramer MR1 6-FP showed little or no staining (**Figure 1G**).

The majority of MAIT cells in both IVB and PB in the pregnant women were CD8+, but intervillous MAIT cells were to a larger degree CD4 and CD8 DN and to a lower extent CD4+ compared to peripheral MAIT cells (**Supplementary Figure S2C**). This pattern was similar when the cells were gated on MR1 tetramer+ cells in three donors (**Supplementary Figure S2D**). As observed for the conventional T cells, intervillous MAIT cells had more uniform EM characteristics as compared to peripheral MAIT cells (**Supplementary Figure S2E**). In contrast to conventional CD8+ T cells, IVB MAIT cells had a less activated phenotype compared to PB MAIT cells with lower expression of CD25 and PD-1, but similar expression of CD69 and HLA-DR (**Supplementary Figure S2F**). Together, intervillous and peripheral MAIT cells display different phenotypic patterns, and conventional T cells and MAIT cells show relative differences between IVB and PB in the expression patterns of both early and late activation markers.

### Placental Tissues Produce High Levels of Several Chemokines Which Attracts MAIT Cells and CD8+ Effector Memory T Cells

We hypothesized that the observed enrichment of certain T cell populations in the intervillous space of the placenta was due to chemotactic factors produced by the placental tissue. Therefore, we examined the chemokine secretion pattern from placental explants. Several small pieces of placental villous tissue were collected and pooled from the same placenta to provide a representative sample. The tissue was cultured for 48 h, and the supernatant was harvested and analyzed by a 40-plex luminex assay. As shown in **Figure 2A**, placental explants secreted high levels of several chemokines and cytokines, including MIF, IL-6, CXCL8, and CCL2. To investigate the potential chemoattractive capacity of placental tissue on MAIT cells and other T cells, an assay of immune cell migration toward placental tissue conditioned medium was set up. We found that the placental

(Continued)

FIGURE 1 | within class variability (PB, n = 25, IVB, n = 24). (B) OPLS-DA loading plot based on the same data as in (A), following a variable influence of projection (VIP) of 0.81 (Supplementary Figure S1), showing associations between IVB or PB and phenotypic markers on T cells. (C) Proportions of CD3+ cells within CD45+ cells (left), and CD4+, CD8+ and CD4−/CD8− cells within CD3+ cells compared between PB and IVB (right) (n = 24). (D) Median proportions of naïve, central memory (CM), effector memory (EM) and terminally differentiated (TD) cells within CD8+ T cells, based on the co-expression of CCR7 and CD45RA depicted in a pie chart (top) and as individual values (bottom) (n = 24). Representative dot plots are shown to the right. (E) Percentage of MAIT cells out of total CD3+ cells (left, n = 24) and CD45+ cells (right, n = 23) compared between PB and IVB. (F) Percentage of MAIT cells out of total CD3+ cells compared between peripheral blood from pregnant (n = 35) and non-pregnant women (n = 27). (G) Comparison of MAIT cell characterization methods between CD161+Vα7.2+ and 5-OP-RU tetramers in PB and IVB (left, n = 3), and representative plots of the stainings, including the negative control tetramer loaded with 6-FP (right). Line in graphs represents the median. Comparisons between paired samples were performed by Wilcoxon test (C–E and G) and unpaired samples by Mann-Whitney test (F). ns = not significant, \*p < 0.05, \*\*\*p < 0.001, \*\*\*\*p < 0.0001.

tissue conditioned medium promoted migration of CD3+ T cells, CD8+ T cells, MAIT cells, and CD8+ EM T cells, as compared to control medium (**Figure 2B**). The number of migrating CD4+ T cell, DN T cells, as well as CD8+, DN and CD4+ MAIT cells all increased in the presence of conditioned medium (**Supplementary Figures S5A,B**). The proportion of migrating CD8+, CD4+ and DN T cells out of CD3+ T cells was not altered when placenta conditioned medium and control medium was added (**Figure 2C**; **Supplementary Figure S5A**). On the other hand, the proportion of both MAIT cells and conventional CD8+ EM T cells were higher when placenta conditioned medium was added, compared to control medium (**Figure 2C**). The proportion of CD8+ and DN migrating MAIT cells was not significantly affected by the conditioned medium, but the percentage of CD4+ MAIT cells were lower in MAIT cells migrating toward the conditioned medium (**Supplementary Figure S5B**). No significant effect was observed for the proportion of CD4+ EM T cells (data not shown). Thus, this indicates that chemokines produced from fetal placental tissues attracts T cells in general, but have a stronger attracting capacity on MAIT cells and conventional CD8+ EM T cells compared to other T cell subsets.

# Chemokine Profile in Intervillous Blood Is Different From That of Peripheral Blood

Following our findings regarding the chemoattractive properties of term placental tissue, we investigated the chemokine pattern in the blood adjacent to the fetal villi in the intervillous space. Plasma from paired PB and IVB samples were analyzed to examine the chemokine profile in these compartments. As shown in the OPLS-DA loading plot in **Supplementary Figure S6**, a large proportion of the investigated chemokines were associated to either PB or IVB. The levels of chemokines and cytokines in PB and IVB in all individual samples are displayed in a heatmap, sorted based on the results from the OPLS-DA (**Figure 3A**). Univariate analysis showed significantly higher levels of a majority of the analyzed soluble factors in IVB compared to PB, whereas other were higher in PB, as indicated in **Figure 3A**. MIF displayed the strongest association with IVB and showed a median 182-fold higher level in IVB compared to PB (**Figure 3B**). Other factors that were higher in IVB included CXCL10, CCL25 and CXCL9 (**Figure 3B**). In contrast, levels of CCL27, CXCL12, and CCL21 were significantly lower in IVB compared to PB. Many of the chemokines that were produced in high levels from the placental explants (**Figure 2A**), were higher in IVB than PB plasma (**Figures 3A,B**). A direct comparison between the levels of chemokines in placental conditioned medium and IVB plasma are shown side by side in **Supplementary Figure S7A**. The relative differences between levels of chemokines in IVB and PB plasma, as determined by the ratio of levels in IVB divided by levels in PB, are shown in **Supplementary Figure S7B**. Together, this suggests that the placental villous tissue was responsible for the production of at least some of the chemokines detected at elevated levels in IVB plasma.

## MIF Levels in Intervillous Blood Correlate With the Proportion of MAIT Cells in the Placenta

The data on paired IVB plasma chemokine levels and IVB T cell composition allowed us to study associations between particular T cell subsets and levels of placenta-derived chemokines. In an attempt to identify factors related to MAIT cell homing to the intervillous space, the proportions of MAIT cells in IVB were analyzed for associations with levels of IVB chemokine levels using OPLS analysis. As shown in **Figure 4A**, higher proportions of MAIT cells were positively associated with higher levels of MIF and CCL25 (**Figure 4A**). In univariate analysis, the proportion of MAIT cells in IVB correlated directly to the levels of MIF in IVB, and there was a trend for correlation with CCL25 levels (**Figure 4B**). Paired data on proportions of MAIT cells from decidua parietalis and IVB chemokine levels was available from 18 of the donors, and showed an even stronger correlation with levels of both MIF and CCL25 in IVB (**Figure 4C**). These associations further support the notion that placenta-derived MIF and CCL25 are involved in attracting maternal MAIT cells to both the decidua and the intervillous space. In contrast, when analyzing the association between proportions of MAIT cells in PB with levels of MIF and CCL25 in the same samples, no correlation was found (**Figure 4D**). Thus, MIF and CCL25 did not appear to affect MAIT cell numbers in general, but rather seemed to be involved in directing MAIT cells from the periphery into the placental intervillous space and to the decidua. IVB plasma levels of CCL21 and CCL27 were inversely correlated to IVB MAIT cell proportions (**Supplementary Figure S8A**).

Conventional CD8+ EM T cells in IVB showed no correlation with IVB MIF or CCL25 levels (**Supplementary Figure S8B**). However, the proportions of conventional CD8+ EM T cells instead were significantly correlated to the levels of the CXCR3-ligands CXCL9, CXCL10, and CXCL11 (**Supplementary Figure S8C**). This suggests that MAIT cells and

conventional CD8+ EM T cells are recruited to the intervillous space by different chemokine gradients.

# Placenta-Derived Chemokines and MIF Promote MAIT Cell Migration

To further investigate the relationship between IVB MAIT cells and chemoattractive factors, we next blocked CCL25 and MIF, identified as putatively important for MAIT cell homing to the placenta, in a migration assay. Neutralizing antibodies to CCL25 or the MIF-inhibiting chemical ISO-1 were used to block these factors in the placental tissue conditioned medium. Since the majority of the MAIT cells are highly positive for CCR6, the receptor for CCL20, we also included neutralizing antibodies to this chemokine. For total CD3+ T cells, we found that the number of migrating T cells were reduced when ISO-1 or the combination of all three factors were added to the conditioned medium (**Figure 5A**). A similar pattern was observed for the number of migrating MAIT cells. Among the three conditions, only ISO-1 significantly decreased the migration of MAIT cells with a median of 24 % relative to the diluent control (**Figure 5A**). When all three factors were blocked, the number of migrating MAIT cells decreased with a median of 41% relative to isotype

indicate individual donors. (B) The levels of MIF, CXCL10, CXCL9, and CCL25 were significantly higher in IVB compared to PB, whereas the levels of CCL27, CXCL12, and CCL21 where significantly lower. Line in graphs represents the median. Comparisons between paired samples were made using the nonparametric Wilcoxon test. \*\*\*\*p < 0.0001.

and diluent control. When analyzing the proportion of MAIT cells within migrating CD3+ T cells, we found that the MAIT cell proportions were significantly reduced when all three factors were blocked, whereas there was no significant effect on MAIT cell proportion when only anti-CCL25, anti-CCL20, or ISO-1 were added on their own (**Figure 5A**).

For CD8+ EM T cells, we found that the number of cells that migrated was significantly blocked by ISO-1, but only with a

parietalis and the measured levels of MIF (left) and CCL25 (right) in paired IVB samples (n = 18). (D) Correlation between the frequency of peripheral blood (PB) MAIT cells and the measured levels of MIF (left) and CCL25 (right) in paired PB plasma samples (n = 24). Correlations between paired samples were made using the nonparametric Spearman correlation test.

median of 13% relative to the control (**Figure 5A**). Neutralization of CCL20 also led to a statistically significant, but small decrease in migration. Blocking of all three factors decreased the number of migrating CD8+ EM T cell with a median of 30 % relative to control. However, when the proportion of CD8+ EM T cells among total migrating CD8+ T cells was analyzed, we found no significant reduction in migration by blockade of any of the factor, either alone or in combination. Instead, an increase in CD8+ EM T cell proportion was observed when ISO-1 was added (**Figure 5A**). Thus, MIF appear to attract T cells in general, since the number of total migrating T cells were reduced when ISO-1 was added. However, the proportion of CD8+ EM T cells among migrating CD3+ T cells was increased when MIF was blocked, suggesting that MIF has little specific effect in promoting migration of CD8+ EM T cells as compared to other T cell subsets. On the other hand, the proportion of MAIT cells among migrating T cells was reduced when blockade of MIF in combination with CCL25 and CCL20 was performed. Raw data on cell counts after addition of isotype controls, diluent controls, and neutralizing agents are shown in **Supplementary Figure S9**.

Since MIF appeared to be an important factor for MAIT cell attraction, we next examined if recombinant MIF could promote migration of T cells and MAIT cells. MIF significantly increased the number of migrating MAIT cells at a concentration of 250 ng/ml (**Figure 5B**). However, MIF did not promote migration of conventional CD8+ EM T cells as determined by the number of migrating cells, although there was a trend at the higher concentration of 250 ng/ml (**Figure 5B**). When analyzing

FIGURE 5 | proportion of migrating MAIT cells within CD3+ T cells (bottom left) and CD8+ EM T cells among CD8+ T cells (bottom right) toward CM. Results are expressed as blocking relative to isotype or diluent control. (B) The chemoattractive effect of MIF on the migration of number of MAIT cells (top left) and CD8+ EM T cells (top right), using increasing concentrations of MIF. Proportion of migrated MAIT cells within CD3+ T cells (bottom left) and CD8+ EM T cells among CD8+ T cells (bottom right) in the absence and presence of recombinant MIF. P values refer to comparisons between the medium control and the indicated levels of MIF. (B) The data on the bottom y-axis for MAIT and CD8+ EM T cell counts were generated when adding purified T cells and the top y-axis when using CD4-depleted T cells. Line in graphs represents the median. Comparisons between paired samples were made using the nonparametric Wilcoxon test. ns, not significant.

the proportion of MAIT cells and CD8+ EM T cells among migrating T cells in the parent gate, we found that only MAIT cells were significantly increased when MIF was added and no effect was found for CD8+ EM T cells (**Figure 5B**). Sufficient counts were recorded in seven of the donors to allow sub-gating. For these, we found that the proportion of migrating CD8+ MAIT cells were reduced when MIF was added, and there was a trend for an increased proportion of migrating DN MAIT cells (**Supplementary Figure S10**). Thus, these findings support the notion that MIF has a T cell attracting capacity and that this effect is stronger on MAIT cells than on conventional CD8+ EM T cells.

## MAIT Cells Express Higher Levels of CXCR4 Compared to CD8+ Effector Memory T Cells

MIF has previously been reported to bind to CXCR4 (26), and we next compared the level of CXCR4 expression on MAIT cells and CD8+ EM T cells in medium control wells. Although a large proportion of both MAIT cells and CD8+ EM T cells expressed CXCR4, the proportion of MAIT cell expressing CXCR4 was significantly higher (**Figure 6A**). The median intensity expression (MFI) of CXCR4 was also higher in MAIT cells in five out of six samples (**Figure 6A**). When MIF was added to the migration assay, we found that the proportion of CXCR4+ CD8+ EM T cells increased compared to medium control and also that the intensity of expression of CXCR4 was higher (**Figures 6B,C**). We found no enrichment of CXCR4 expressing MAIT cells when MIF was added (**Figures 6B,C**), but this could be explained by that the median expression of CXCR4 on MAIT cells was as high as 99 % in the control condition, a finding also supported by Dias et al. (27). In summary, the higher expression of CXCR4 on MAIT cells may increase the capacity to more efficiently migrate toward MIF compared to CD8+ EM T cells, and our data support that CXCR4 is involved in the migration of T cells toward MIF.

# DISCUSSION

The decidua and the intervillous space are both sites for fetal-maternal immune interactions where maternal immune cells are in contact with fetal extravillous trophoblasts and syncytiotrophoblasts, respectively. Several studies have examined the composition of maternal immune cells in decidual tissues, in both healthy early and term pregnancies (28–30), as well as in miscarriage and pre-eclampsia (31, 32). In contrast, surprisingly little is known about immune cells in the IVB. In the present study, we show that the T cell compartment in IVB markedly differs from that in PB at term pregnancy, and that placentaderived factors may play a role in recruiting or retaining certain T cell subsets in the intervillous space and decidua.

The multivariate discriminant analysis showed that high proportions of conventional EM T cells and MAIT cells, and activated conventional T cells were strongly associated to IVB. Non-pregnant women had a higher proportion of MAIT cells in the circulation compared to our cohort of pregnant women, but it should be noted that the groups were not age-matched and the sample collection from the non-pregnant women were not adjusted to their menstrual cycles, which could affect the results. The non-pregnant women had a higher median age, and since it has been shown that MAIT cell proportions decrease with age (33), the age difference may mask an even bigger decline in circulating MAIT cell levels in pregnancy. Our findings are thus consistent with a possible homing of peripheral MAIT cells to the placenta during pregnancy. We have previously shown that IVB MAIT cells do not express the proliferation marker Ki67 (4), which further indicate that MAIT cells are recruited or retained rather than proliferating at the site. To further study whether the increase in IVB MAIT cell frequency is due to homing from PB, it would be interesting to follow PB MAIT cell frequencies longitudinally, including before, during, and after pregnancy.

The chemokine pattern in IVB was clearly different from that of PB, and we also found that placental villous explants produced high levels of several inflammatory chemokines. Svensson-Arvelund et. al. (21) and others [reviewed in (22)], have previously shown that first trimester placental tissues and trophoblasts produce several chemokines, but very little is known about how placenta-derived chemokines promote immune cell migration. Nancy et al. showed that murine decidual stromal cells undergo epigenetic modifications that decrease the production of the CXCR3-ligands CXCL9, CXCL10, and CXCL11, which prevented effector T cells from entering the decidua in mouse models (34). The number of T cells in human first trimester decidua is low, (28, 29) but the composition of immune cells changes during pregnancy and T cells become as numerous in decidua as in peripheral blood at term (29, 30). It is therefore reasonable to believe that the expression of chemokines changes as pregnancy proceeds. Our data from term placental villous explant medium and intervillous plasma indicate that the term placenta produces a wide array of chemokines and cytokines, which can be involved in recruiting inflammatory T cells to the decidua and intervillous space at term.

By using a multivariate factor analysis, we found MIF to be the factor most strongly associated with high MAIT cell proportions in IVB. Considering the large inter-individual proportions of MAIT cells and the elevated levels of a large number of

chemokines in IVB, we were surprised to find correlations between MAIT cell proportions and particular chemokine levels. However, the migration assays further supported that MIF was important for MAIT cell migration. Interestingly, decidual MAIT cell proportions from paired samples were strongly associated to MIF levels in the IVB, suggesting that MIF may also be involved in directing MAIT cell into adjacent tissues, and not only to retain them in a blood-filled space. However, it is likely that a combination of several chemokines ultimately regulates retention and migration of cells to a particular tissue, and that other chemokines may be of greater importance in settings other than pregnancy.

It was further evident that MAIT cells and conventional CD8+ EM T cells were associated with different chemokine patterns. Whereas proportions of MAIT cells were associated to high MIF and CCL25 levels, conventional CD8+ EM T cells correlated to the CXCR3-ligands CXCL9, CXLC10 and CXCL11. These findings support the results by Nancy et al. showing that the CXCR3-binding chemokines are important for attracting effector T cells to the placenta, but may also contradict the findings that these chemokines are silenced at the fetal maternal interface during pregnancy (34). Powell et al. observed an increased frequency of CXCR3+ CD4+ T cells in human 3rd trimester decidua compared to PB following uncomplicated pregnancies (35). Together, this points to differences in homing mechanisms and immune cell recruitment between early and term pregnancy, and also between the human and murine placenta. We have here mainly focused on trying to delineate how MAIT cells are recruited or retained in the intervillous space, but for future studies it would be interesting to investigate if migration of CD8+ EM T cells toward placental conditioned medium could be blocked by neutralizing antibodies to CXCL9, CXCL10, and CXCL11.

MIF has been described to act as a promoter of inflammation by aiding monocyte and macrophage survival by suppressing p53 (36), increasing their inflammatory response (37, 38), and by counteracting the anti-inflammatory effect of glucocorticoid hormones (39). MIF has a predominant role in the innate immune response, where for example bacterial lipopolysaccharide has been shown to induce systemic release of MIF (40) Apart from monocytes and macrophages, MIF also has a potentiating effect on the pro-inflammatory activity of T cells (26). MIF attracts monocytes by interacting with either CXCR2 or the complex CXCR2/CD74, T cells by binding CXCR4 (26) and B cells by interactions with the complex CXCR4/CD74 (41). The functional effect of the interactions between MIF and monocytes and T cells has been shown in mice with advanced atherosclerosis, where MIF-blockade led to decreased plaque infiltration by monocytes and T cells, together with a regression in plaque size (26). The mechanisms for MIF secretion is poorly understood, but it has been shown that ATP-binding cassette transporter (ABCA1) can impair secretion of MIF (42).

MIF expression has been previously observed in first and third trimester decidual cells (25, 43). NK cells isolated from first trimester decidua synthesize and secrete MIF, and MIF negatively regulates their cytolytic capacity (44). In the placenta, MIF expression has been detected in syncytiotrophoblasts, cytotrophoblasts and extravillous trophoblasts from term pregnancies (23, 25). It was recently shown that MIF has antiapoptotic effects on trophoblasts during early pregnancy, (45) and that MIF is involved in trophoblast invasion (46). In line with our findings, the levels of MIF have been found to be higher in IVB compared to paired samples of PB in women following vaginal delivery at term pregnancy. In the same study, it was further noted that the levels of MIF in IVB was significantly lower in multigravidae women (24). Moreover, high levels of IVB MIF have been correlated to placental malaria in two cohorts (24, 47).

MAIT cells have been shown to express high levels of CXCR4 (27) and moderate levels of CCR9 (17), but low or no expression of CXCR2 (27), suggesting that CXCR4 and CCR9 are the receptors involved in the MAIT cell attracting capacity of MIF and CCL25, respectively. We have here confirmed that the majority of MAIT cells express CXCR4, and that a larger proportion of MAIT cells express CXCR4 compared to CD8+ EM T cells. Furthermore, the proportion of CXCR4+ migrating EM T cells increased when MIF was added to the migration assay, suggesting that CXCR4 is involved in the migration of T cells towards MIF. Since MAIT cells express high levels of CCR6, we evaluated blocking of the ligand CCL20, a chemokine that was also highly secreted from placental explants. However, blocking CCL20 did not significantly prevent MAIT cell migration, although there was an effect of blocking CCL20 in the majority of the experiments. This could be due to that other chemotactic factors produced by the placenta, including high levels of MIF, are more important for attracting MAIT cells in this context. On the other hand, migration of conventional EM CD8+ T cells was partly decreased by the addition by anti-CCL20 antibodies. The relative importance of different chemotactic factors for the migration of MAIT cells and conventional EM CD8+ T cells and the corresponding biological activity of chemokines is still largely unknown. It has been suggested that MAIT cells are recruited to the liver via CXCR6 and CCR6 and their ligands CXCL16 and CCL20 (48). It would be of great interest to study and compare MAIT cell and EM T cell migration in different physiological settings, including the intervillous space and the liver sinusoids, which are both characterized by low pressure blood flow.

Levels of CCL21 and CCL27 were significantly higher in PB compared to IVB, and inversely related to MAIT cell proportions in IVB. CCL21 is the ligand to CCR7, a chemokine receptor that is highly expressed by naïve T cells and is important for homing to lymph nodes. This is in accordance with the higher proportion of naïve T cells in PB compared to IVB, which are constantly circulating in PB to visit lymph nodes. CCL27 is predominantly expressed by keratinocytes and has been shown to attract CCR10+ T cells to the skin (49), and MAIT cells only express low levels of CCR10 (50). For future studies, it would be interesting to further study the reverse relationship between low MAIT cell proportions and high levels of CCL21 and CCL27 in IVB.

One limitation with this study is that the number of migrating MAIT cells and CD8+ EM T cells in the migration assay sometimes were low, which can question the relevance of the results. Indeed, in the assays in which the chemoattractive capacity of MIF was investigated, many of the experiments contained low numbers of migrating MAIT cells. The majority of the experiments were performed with purified T cells, but we also included six experiments where CD4-depleted T cells were added to the transwell. In this way, the cells that were put in the migration assay were enriched for MAIT cells and CD8+ EM T cells, which consequently also led to higher migrating cell counts. Although MIF appeared to have an attracting effect on T cells in general, as determined by cell counts, the proportion of MAIT cells among migrating CD3+ was increased after addition of MIF. In contrast, proportions of CD8+ EM T cells were unaltered in the presence of MIF. Thus, although the robustness of the flow cytometry-based migration assay might be questioned, the results are still in line with the positive correlation between levels of MIF and proportions of MAIT cells in IVB.

The physiological role of MAIT cells in the placenta and their importance during pregnancy is not known. One possible function is protection of the fetus against bacterial and fungal infections, but also against viral infections since MAIT cells are also activated by inflammatory signals in an MR1-independent manner (11, 12, 14). Their rapid cytotoxic effects could provide an efficient innate-like defense mechanism to prevent pathogens from crossing the fetal-maternal barrier. The direct anti-bacterial and tissue protective activity of MAIT cells mediated by IL-17 and IL-22 production, (19), respectively, may also be important. Since many commensal and pathogenic microbes synthesize riboflavin, whereas human cells do not, MAIT cells provide an essentially different mechanism of discrimination between self and non-self compared to conventional T cells (5).

We have previously found that MAIT cells in IVB respond more vigorously with production of cytokines and cytotoxic molecules compared to peripheral blood MAIT cells after stimulation with Escherichia coli, (4) further indicating their importance in mediating anti-microbial inflammatory responses in placental tissues. On the other hand, it can be speculated that aggravated MAIT cell activation in intervillous space could be involved in initiation of preterm birth or play a role in other pregnancy complications. It was recently shown that the proportion of MAIT cells in peripheral blood of patients with pre-eclampsia was lower compared to noncomplicated pregnancies (51), indicating that MAIT cells may have accumulated in the placenta and that they possibly could be involved in mediating the pathophysiological traits of preeclampsia. It is therefore interesting that patients who later developed pre-eclampsia had low levels of MIF in PB at gestational week 13 (52), which was followed by a subsequent pathological rise in MIF in patients with pre-eclampsia, and the highest levels were seen in the patients who developed pre-eclampsia before gestational week 34 (53). This warrants further studies of the role of MIF, MAIT cell homing, and MAIT cell function at the fetal maternal interface in the context of pregnancy complications.

Our data suggests that certain immune cell subsets are enriched in the intervillous space in healthy term placentas. These findings challenge the general conception about placental blood circulation, since the entire blood content does not seem to be exchanged. Since the intervillous blood is surrounded by the fetal placenta, this compartment may be optimal for studying immune dysregulation and for identifying immunological factors involved in complicated pregnancies.

#### ETHICS STATEMENT

This study was carried out in accordance with the recommendations of the regional review board of ethics in research at Karolinska Institutet with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was

# REFERENCES

approved by the regional review board of ethics in research at Karolinska Institutet.

## AUTHOR CONTRIBUTIONS

MS conceived, designed, performed, and analyzed the experiments, interpreted the results and wrote the paper. LG performed and analyzed the experiments and interpreted the results. ET and SG interpreted the results. EL and JD designed and performed the experiments. JS designed the experiments and interpreted the results. IM designed the experiments and interpreted the results. A-CL performed all multivariate factor analyses and interpreted the results. HK conceived, designed and analyzed the experiments, interpreted the results, wrote the paper and was the principal investigator of the project. All authors participated in final approval of the manuscript.

## FUNDING

HK was supported by grants from the Swedish Research Council, The Swedish Cancer Foundation, the Swedish Childhood Cancer Foundation, the Cancer Foundation in Stockholm, Stockholm County, and the Karolinska Institutet. MS was supported by Karolinska Institutet. A-CL was supported by grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALFGBG-773381). JD was supported by Fundação para a Ciência e a Tecnologia Doctoral Fellowship SFRH/BD/85290/2012, cofunded by the Programa Operacional Potencial Humano-Quadro de Referência Estratégico Nacional and the European Social Fund.

#### ACKNOWLEDGMENTS

We thank Boel Niklasson and Catarina Arnelo and the other midwifes at Karolinska University Hospital in Huddinge for their excellent help in recruiting patients and help with collection of placentas.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2019.01300/full#supplementary-material

The Placenta, From Development to Disease. Oxford: Wiley-Blackwell (2011). p. 17–26.

invariant T cells by MR1. Nature. (2003) 422:164–9. doi: 10.1038/nature 01433

lesional skin comprises mucosa-associated invariant T cells and conventional T cells. J Invest Dermatol. (2014) 134:2898–907. doi: 10.1038/jid.20 14.261

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Solders, Gorchs, Tiblad, Gidlöf, Leeansyah, Dias, Sandberg, Magalhaes, Lundell and Kaipe. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# T Cell Receptor Expression Timing and Signal Strength in the Functional Differentiation of Invariant Natural Killer T Cells

#### Nyambayar Dashtsoodol 1,2 \*, Sabrina Bortoluzzi 1 and Marc Schmidt-Supprian1 \*

1 Department of Hematology and Medical Oncology, Klinikum rechts der Isar and TranslaTUM Cancer Center, Technische Universität München, München, Germany, 2 Department of Microbiology and Immunology, School of Biomedicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia

#### Edited by:

Kazuya Iwabuchi, Kitasato University School of Medicine, Japan

#### Reviewed by:

Paolo Dellabona, San Raffaele Scientific Institute (IRCCS), Italy Hyun Park, National Cancer Institute (NCI), United States

#### \*Correspondence:

Nyambayar Dashtsoodol<EMAIL_ADDRESS>Marc Schmidt-Supprian<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to T Cell Biology, a section of the journal Frontiers in Immunology

Received: 31 January 2019 Accepted: 01 April 2019 Published: 26 April 2019

#### Citation:

Dashtsoodol N, Bortoluzzi S and Schmidt-Supprian M (2019) T Cell Receptor Expression Timing and Signal Strength in the Functional Differentiation of Invariant Natural Killer T Cells. Front. Immunol. 10:841. doi: 10.3389/fimmu.2019.00841 The CD1d-restricted Vα14 invariant NKT (iNKT) cell lineage in mice (Vα24 in humans) represents an evolutionary conserved innate-like immune cell type that recognizes glycolipid antigens. Because of their unique ability to promptly secrete copious amounts of both pro-inflammatory and anti-inflammatory cytokines, typically produced by different T helper cell types, iNKT cells are implicated in the regulation of various pathologic conditions such as infection, allergy, autoimmune disease, maintenance of transplantation tolerance, and cancer. This striking multifaceted role in immune regulation is correlated with the presence of multiple functionally distinct iNKT cell subsets that can be distinguished based on the expression of characteristic surface markers and transcription factors. However, to date it, remains largely unresolved how this puzzling diversity of iNKT cell functional subsets emerges and what factors dictate the type of effector cell differentiation during the thymic differentiation considering the mono-specific nature of their T cell receptor (TCR) and their selecting molecule CD1d. Here, we summarize recent findings focusing on the role of TCR-mediated signaling and discuss possible mechanisms that may influence the sub-lineage choice of iNKT cells.

Keywords: NKT, CD1d, lymphocyte, development, functional subset, thymus, T cell receptor, developmental pathway

#### INTRODUCTION

Innate-like T lymphocytes are a special group of immune cells assumed to play important immunoregulatory functions by linking and orchestrating the functions of multiple cell types of the innate and adaptive arms of the immune system (1, 2).

The invariant NKT (iNKT) cells, often referred to as Vα14 iNKT cells in mice (Vα24 in humans), represent an evolutionary conserved innate-like immune cell type characterized by the expression of a unique semi-invariant T cell receptor (TCR). This TCR is composed of a single invariant α-chain Vα14Jα18 (encoded by Trav11Traj18) usually paired with a limited range of TCRβ-chains, mostly Vβ8.2, Vβ7, or Vβ2 (TRBV13-2, TRBV29, and TRBV1), in mice and a Vα24Jα18 TCRα-chain (encoded by Trav10Traj18) paired exclusively with Vβ11 (TRBV25) in humans. As opposed to the conventional peptide-recognizing CD8 T cells or CD4 T cells, iNKT cells are specialized in recognizing glycolipid antigens including alpha-galactosylceramide (α-GalCer) presented by the monomorphic MHC class I-like CD1d molecule (3–7). Owing to the

early availability of specific analysis tools such as CD1d tetramers (8, 9), as well as various gene-manipulated mouse models that either lack (10–17) or overexpress (18–22) these cells, to date iNKT cells represent the best-studied innate-like T lymphocyte lineage.

The hallmark feature of iNKT cells is their unique ability to secrete very large amounts of both pro-inflammatory and anti-inflammatory cytokines, typically produced by T helper cell type 1 (TH1), TH2, and TH17 cells. Cytokine secretion occurs rapidly upon activation and does not require clonal expansion or antigenic priming. Therefore, in line with their innate-like ability to robustly produce multiple immunoregulatory cytokines, iNKT cells were implicated in the regulation of various pathologic conditions such as infection, allergy, autoimmune disease, maintenance of transplantation tolerance, and cancer (23, 24). Because of this unique feature to elicit protective, regulatory, and pathogenic functions, it was proposed that iNKT cells constitute a heterogenous population. In fact, recent publications have demonstrated the presence of multiple functionally distinct subsets with discrete cytokine polarization within the iNKT cell lineage that can be distinguished based on the expression of characteristic surface markers and transcription factors (**Table 1**) (25, 26). The differentiation of iNKT cells proceeds within highly restricted context dictated by the recognition of self-glycolipids on CD1d by their semi-invariant TCR. To date, it remains largely unresolved how this puzzling diversity of iNKT cell functional subsets emerges and what factors dictate the type of effector cell differentiation during thymic differentiation.

As a number of excellent reviews have extensively covered advances in the iNKT cell developmental field (27, 30–34), in this mini-review, we attempted to summarize recent findings focusing on the role of TCR-mediated signaling and discuss possible mechanisms that may influence the sub-lineage choice of iNKT cells. A better understanding of the mechanisms underlying the differentiation of iNKT cell functional subsets will eventually help in designing new strategies to explore the therapeutic potential of these cells for the benefit of immunocompromised patients.

#### INKT FUNCTIONAL SUBSETS

In contrast to conventional T cells, iNKT cells can acquire functional maturity in the thymus before their egress to peripheral tissues. Historically, a linear differentiation model was proposed, which postulated that CD1d-selected CD24+ stage 0 (st0) immature iNKT cells mature through sequential stages: via CD44low NK1.1− stage 1 (st1) iNKT cells characterized by IL-4-producing capabilities to CD44high NK1.1− (st2) iNKT cells with IL-4- and IL-17-biased features, and finally to terminally matured CD44high NK1.1+ (st3) iNKT cells with IFN-γ-biased polarization (35). However, direct evidence of differentiation of st1 and st2 iNKT cells into terminally matured st3 iNKT cells was not demonstrated (36). The first evidence probing the above question on whether IL-4-producing thymic iNKT cells can give rise to IFN-γ-producing iNKT cells was addressed by Watarai et al., who demonstrated that IL-4-producing IL-17 receptor TABLE 1 | Differential expression of surface markers and transcription factors on iNKT cell functional subsets.

iNKT, invariant NKT.

B (IL-17RB) expressing thymic iNKT cells do not generate IFN-γ-producing T-bet+ thymic iNKT cells upon intrathymic transfer (25).

More recently, based on intracellular staining patterns of lineage-specific transcription factors such as T-bet, GATA-3, PLZF, and RORγt, Lee et al. demonstrated that there are at least three distinct iNKT functional subsets in the thymus, designated as iNKT1, iNKT2, and iNKT17, akin to the classification of classical CD4 T helper cell types (TH1, TH2, and TH17 cells, respectively) (26). iNKT1 cells express NK cell-related markers, are T-bet+ PLZFlow, and produce mainly IFN-γ. Moreover, iNKT2 cells are GATA-3high PLZFhigh and produce high levels of IL-4, whereas iNKT17 cells are defined as RORγt + PLZFintermediate and produce IL-17 upon stimulation. Thus, NKT functional subsets can be distinguished on the basis of their expression profile of characteristic surface markers and signature transcription factors (**Table 1**).

iNKT cells also can be subdivided into CD4+ and CD4− subsets, where both murine and human CD4− subsets show TH1 biased cytokine polarization and enhanced cytotoxic activity compared with CD4+ counterparts (37–39). In line with this, granzyme A (Gzma) and granzyme B (Gzmb), key genes involved in NK-triggered killing, are expressed specifically on CD4− iNKT cells (40). Of note, hepatic CD4− iNKT cells possess superior antitumor activity compared with thymic or splenic CD4+ and CD4− iNKT cells, suggesting that organ-specific mechanisms might dictate the functional capabilities of resident NKT cells (39). Although it remains incompletely understood whether the development of these diverse functional NKT cell subsets is related to the existence of dedicated precursor cells or is due to specific differentiation programs, a revised model, termed "lineage diversification," is proposed, which suggests thymic iNKT functional subsets represent stable distinct lineages rather than functional maturation stages (26, 30).

In addition to these subsets, iNKT follicular helper cells (iNKTFH) and IL-10-producing iNKT10 cell subsets were described (41–44). Although it is unclear whether iNKTFH cells originate from the thymus, iNKT10 cells can arise in the thymus of F108Y mice, which harbor a mutation in the TCRβ-chain that results in altered iNKT TCR conformation (45). In addition to this, iNKT cells convert into IL-10-producing cells upon repeated injection with agonistic glycolipid α-GalCer (46), which suggests iNKT cells might have some degree of sub-lineage plasticity. In regard to this, there is a report on induction of TGF-β-dependent FOXP3+ iNKT cells in the periphery upon administration of α-GalCer (47).

Moreover, the relative frequencies of functional subsets differ between inbred mouse strains, such as C57BL/6 mice possess mostly iNKT1 cells, while BALB/c mice have a significantly larger iNKT2 cell subset. Additionally, iNKT cells are tissue resident and show unique tissue distribution patterns (27, 48).

#### THYMIC SELECTION AND DIFFERENTIATION

The development of the iNKT cell lineage proceeds in the thymus, where the precursor cells that successfully assembled their antigen receptor through recombination mediated by the recombination-activating gene (RAG) are positively selected on CD1d-expressing cortical CD4+CD8+ double-positive (DP) thymocytes (49). Although the majority of iNKT cells are generated from DP thymocytes, it was recently demonstrated that a fraction of iNKT cells develops directly from the CD4−CD8− double-negative (DN) stage of thymic ontogeny, bypassing the DP stage. Fate-mapping experiments as well as conditional ablation of RAG2 at the DP stage demonstrated that a fraction of CD4− iNKT cells were able to develop directly from DN-stage thymocytes without passing through the DP stage (50). This suggested a scenario in which DNstage thymocyte precursors expressing rearranged Vα14Jα18 generated by random rearrangement events are positively selected on CD1d and develop into mature CD4− iNKT cells (**Figure 1**).

Although the exact nature of endogenous ligands presented by CD1d responsible for positive selection of iNKT cells remains to be determined, it was recently reported that mammalian αlinked glycosylceramides represent a candidate for an iNKT cell self-ligand in mice (6). In striking contrast to conventional T cells that undergo clonal deletion upon receiving strong signaling via TCR-MHC interaction, iNKT cells are considered to be selected via strong TCR signals in the thymus. The evidence suggesting agonist selection of iNKT cells is based, among others, on the previously activated and/or memory phenotype of iNKT cells as well as the elevated expression levels of markers associated with TCR signaling such as Egr2 (51) and Nur77 (52) on early iNKT cells. In addition to this strong TCR signaling during selection, the development of iNKT cells requires homotypic interactions between signaling lymphocytic activation molecule family (SLAM) receptors Slamf1 (CD150) and Slamf6 (Ly108) expressed on selector DP thymocytes (53). Reporter mice for TCR signal strength revealed that iNKT cells receive TCR signals during a relatively short developmental time window exclusively at the st0 immature iNKT cell stage (52). These selection signals induce Ras- and Ca2+-dependent transcription factors Egr1 and Egr2, where Egr2 is shown to directly regulate the expression of promyelocytic leukemia zinc finger (PLZF) (51). PLZF represents a key regulator of the innate-like effector functions of iNKT cells (54, 55). However, there is currently no clear consensus on how PLZF is induced, as it was shown that TCR stimulation is not sufficient to induce PLZF expression on pre-selection DP thymocytes (56), suggesting other unknown signals are likely to be required for the development of PLZFexpressing innate T cells such as iNKT. One important factor might be the property of the positively selecting cell type, as CD4 T cells selected by MHC class II-expressing thymocytes express PLZF and show innate-like characteristics (57–59). Moreover, as PLZF expression can be detected in a subset of DN2 thymocytes (60), it is possible that those early-stage precursors expressing PLZF could differentiate later into a PLZF-expressing iNKT cells. In addition to this, premature expression of PLZF on DP thymocytes was demonstrated in pTα/Id2/Id3-deficient mice (61), which suggests a heterogeneity within pre-selection developmental intermediates (62, 63).

Much less is known regarding the negative selection of NKT cells. It was reported that intrathymic injection of α-GalCer and forced expression of CD1d on thymocytes or thymic antigenpresenting cells (APCs) such as dendritic cells (DCs) led to reduced numbers of iNKT cells (64–66). Whether negative selection shapes the iNKT cell population in normal development remains unclear.

#### DEVELOPMENTAL TIMING OF T CELL RECEPTOR EXPRESSION

The early thymic development of iNKT cells presumably mirrors that of conventional αβ T lymphocytes, where the early multipotential bone marrow-derived progenitors differentiate through tightly regulated DN stages 1 to 4 defined based on expression of CD117, CD25, and CD44 markers (67, 68). Major commitment to the αβ T cell lineage occurs at the DN3 stage, where rearrangement of the TCRβ-chain genes and subsequent beta-selection take place (69). Those DN3-stage thymocytes expressing functional pre-TCR, composed of pre-TCRα/TCRβ, differentiate further into the DN4 stage to become DP thymocytes. Although it is well-accepted that rearrangement

of the TCRα-chain occurs at the DP stage, there are some reports demonstrating the presence of TCRα transcripts within DN-stage thymocytes prior to differentiation into the DP stage (70–72). In this regard, it was reported that the DN4-stage thymocytes express Vα14Jα18 iTCR and RAG transcripts and possess iNKT cell potential in vivo (72). Furthermore, TCR sequencing experiments revealed the presence of out-of-frame Trav11Traj18 sequences, providing compelling evidence for ongoing stochastic TCRα-chain rearrangements within late DNstage thymocytes (50).

It seems that iNKT TCR expression during the late DN stage of thymic ontogeny plays a role in shaping the iNKT functional subset choice. Although both DN and DP pathways contribute to the generation of CD4− iNKT cells, the former pathway "preferentially" gives rise to IFN-γ-producing TH1 type iNKT cells with augmented cytotoxicity, compared to their counterparts of DP cell origin (50). Of note, such "preferential" development of TH1-type cells appears to be a general attribute of unconventional T cells that are generated as a result of early TCR expression at the DN stage of thymic ontogeny (73).

A potential mechanism for the "preferential" development of TH1-biased iNKT cells might be related to the differentiation stage of precursor cells undergoing positive selection. In this context, it was shown that DN-stage thymocytes normally express the IL-7 receptor (IL-7R), downregulate its expression after differentiating into the DP stage, and then reexpress it as post-selection αβ T cells (74). It was reported that IL-7R determines the fate of cytotoxic effector cells via induction of Runx3, which upregulates genes associated with cytotoxic lineage cells (75). In line with this, gene expression-profiling experiments revealed that the iNKT cells of DN cell origin had elevated expression of the IL-7R and its downstream associated genes characteristic of cytotoxic cells, such as Runx3, Gzmb, and Prf1, compared to iNKT cells of DP cell origin (50).

In addition to their functional bias, NKT cells of DN cell origin had a peripheral distribution pattern different from that of NKT cells of DP cell origin. NKT cells of DN cell origin were present mainly in the liver, a result that could be explained in part by their elevated expression of genes encoding liverhoming factors. In contrast, the NKT cells of DP cell origin were present mainly in the spleen but also in mesenteric lymph nodes, lamina propria, and adipose tissues, and they had high expression of genes encoding the homing factors responsible for peripheral localization, such as CCR6, CCR7, and CCR9 (50, 76–78).

Collectively, the above results suggest that the acquisition of diverse functional characteristics by iNKT cells might be dependent on the timing of TCR expression as well as on the differentiation stage of precursor cells undergoing positive selection.

#### T CELL RECEPTOR SIGNAL STRENGTH

Recently, two groups reported that the TCR signal strength directs the differentiation of iNKT functional subsets (79, 80). Both studies made use of the well-characterized SKG mouse strain, which contains a hypomorphic ZAP70 allele due to a spontaneous mutation in an SH2 domain. ZAP70 (ζchain-associated protein kinase of 70 kDa) is a Syk family tyrosine kinase that is activated upon engagement of TCR and phosphorylates the linker of activated T cells (LAT) and the SH2 domain-containing leukocyte protein of 76 kDa (SLP-76), and thus is thought to play an essential role for T cell development (81–84). Strikingly, analyses of iNKT cells from SKG mice demonstrated that decreased TCR signaling strength leads to a predominance of NKT1 cells, whereas iNKT2 and iNKT17 cell subsets are reduced (79, 80). Based on the above results, it was proposed that higher TCR signals are necessary for the development of iNKT2 and iNKT17 cells, while iNKT1 cell development is relatively undisturbed in the context of reduced TCR signaling capacity (79, 80).

In contrast to the above, analyses of iNKT cells from the YYAA mouse strain (85), another mouse model of hypomorphic ZAP70, revealed that while the frequency of the iNKT2 subset is reduced, the proportion of iNKT17 is actually higher than that of wild-type mice and the percentage of iNKT1 cells is unchanged (80). In addition, more recently, it was shown that the iNKT1 subset is reduced in CD2476F/6F mice, in which the TCR signaling capacity is reduced by ∼60% as a result of phenylalanine (F) substitution of tyrosine phosphorylation sites of the six endogenous immunoreceptor tyrosine-based activation motifs (ITAMs) of CD3ζ, an obligate signal transducer of the TCR/CD3 complex (86).

Moreover, deficiency in the TCR signaling-independent transcription factor SOX4 results in specific reduction of the iNKT1 subset (86). In Sox4-deficient thymocytes, the levels of miR181, which regulates the TCR signaling threshold of DP thymocytes (87), are diminished (86). While the iNKT cell development is impaired in miR181-deficient mice (88), residual iNKT cells in these mice show increased proportions of the iNKT2 and iNKT17 subsets at the expense of reduced frequency of the iNKT1 subset (89). The above-mentioned defects in the iNKT cell development and in the proportion of iNKT subsets seen in miR181-deficient mice are normalized upon introduction of a pre-rearranged Vα14 iTCR transgene (89). Furthermore, the differentiation and functional diversification of PLZF-expressing γδNKT cells occur completely unperturbed in the absence of miR181 (90). As agonist selected T cells depend on miR181 expression, this suggests that γδNKT cells are not agonist selected. Nevertheless, these cells acquire PLZF expression and the ability to produce IFN-γ (with and without miR181), and they expand in the liver in the absence of iNKT cells. These findings argue against a sole role of agonist TCR signals to govern later functional differentiation of innate-like T cells. It was also reported that autophagy influences the iNKT functional maturation, whereby the iNKT1 cell subset is mostly affected via regulation of the cell cycle and survival processes (34, 91, 92). Additionally, let-7 and miR-17 contribute to iNKT subset development via post-transcriptional regulation of PLZF or TGF-βR II expression in post-selection iNKT cells, respectively (93, 94).

Collectively, the current literature does not provide a clear consensus interpretation on how differential TCR signaling strength affects iNKT functional maturation into distinct subsets. Further complicating the matter, it is possible that the kinetics of acquiring TCR signals over time might be as important as the avidity or quantity of individual TCR signaling events per se (95). Sub-lineage choices might occur based on whether TCR signaling persists or ceases as the case of conventional CD4 T or CD8 T cell choice proposed by the kinetic signaling model (96). It is also possible that positive selection and sub-lineage choices are sequential but not simultaneous events. Finally, other undefined TCR-independent factors provided by the microenvironment might affect the differentiation of iNKT functional subsets, as it was reported that iNKT1, iNKT2, and iNKT17 subsets develop, albeit with subtle variations, in mouse models with the monoclonal iNKT TCR specificity (22, 97).

# CONCLUDING REMARKS

Despite tremendous progress in the field, a number of important questions regarding the development of iNKT cell subsets remain unanswered. First, it is not completely understood why strong agonist signaling, which normally results with the clonal deletion in conventional T cells, culminates in the positive selection of the iNKT cell lineage. Second, how stable are these functional subsets and can they interconvert? In this context, it remains unknown what iNKT cell subsets are the precursors of iNKTFH and iNKT10 cells. Third, what are the factors that dictate homing and maintenance of iNKT cell subsets to different tissue sites? As currently there is no consensus view on the precise mechanisms driving the development of the functionally distinct iNKT sub-lineages, it is tempting to hypothesize that multiple mutually nonexclusive mechanisms might exist. A better understanding of functional differentiation mechanisms of the iNKT cell lineage could contribute in developing optimized strategies intended to exploit the unique features of iNKT cells for the benefit of patients.

# AUTHOR CONTRIBUTIONS

ND wrote the first draft. ND, SB, and MS-S edited the manuscript.

# FUNDING

This work was supported by the Deutsche Forschungsgemeinschaft through an SFB 1054 A02 to MS and by the Science and Technology Center Research Grant from the Mongolian National University of Medical Sciences to ND.

# REFERENCES

conventional selection in human thymus. Sci Immunol. (2017) 2:eaah4232. doi: 10.1126/sciimmunol.aah4232

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Dashtsoodol, Bortoluzzi and Schmidt-Supprian. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# The Role of Autophagy in iNKT Cell Development

#### Guan Yang1 , John P. Driver 2 and Luc Van Kaer 1 \*

*1 Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine, Nashville, TN, United States, 2 Department of Animal Sciences, University of Florida, Gainesville, FL, United States*

CD1d-restricted invariant natural killer T (iNKT) cells are innate-like T cells that express an invariant T cell receptor (TCR) α-chain and recognize self and foreign glycolipid antigens. They can rapidly respond to agonist activation and stimulate an extensive array of immune responses. Thymic development and function of iNKT cells are regulated by many different cellular processes, including autophagy, a self-degradation mechanism. In this mini review, we discuss the current understanding of how autophagy regulates iNKT cell development and effector lineage differentiation. Importantly, we propose that iNKT cell development is tightly controlled by metabolic reprogramming.

Keywords: invariant natural killer T cells, CD1d, autophagy, thymic development, metabolic switch

#### INTRODUCTION

#### Edited by:

*Remy Bosselut, National Cancer Institute (NCI), United States*

#### Reviewed by:

*Yuan Zhuang, Duke University, United States Mihalis Verykokakis, Alexander Fleming Biomedical Sciences Research Center, Greece*

\*Correspondence:

*Luc Van Kaer<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to T Cell Biology, a section of the journal Frontiers in Immunology*

Received: *17 September 2018* Accepted: *29 October 2018* Published: *14 November 2018*

#### Citation:

*Yang G, Driver JP and Van Kaer L (2018) The Role of Autophagy in iNKT Cell Development. Front. Immunol. 9:2653. doi: 10.3389/fimmu.2018.02653* Invariant natural killer T (iNKT) cells are an innate-like T cell subset found in most mammalian species. Unlike conventional T cells, iNKT cells recognize glycolipid antigens presented by the MHC class I-like, CD1d molecule. iNKT cells express a semi-invariant T cell receptor (TCR) composed of Trav11 (Vα14)-Traj18 (Jα18) and Trbv13-2, Trbv29, or Trbv1 (Vβ8.2, −7, or −2) in mice (1–3) or TRAV10 (Vα24)-TRAJ18 (Jα18) and TRBV25-1 (Vβ11) in humans (1, 4, 5). Analogous invariant TCR chain usage was found in other mammals such as rats (6) and pigs. iNKT cells can be universally activated with the prototypical iNKT cell antigen α-galactosylceramide (α-GalCer) that was originally isolated from the marine sponge Agelas mauritianus (7). Once activated, iNKT cells provide a universal source of T cell help primarily through the rapid production of multiple effector cytokines capable of transactivating an array of immune cells (8, 9). In humans and animal models, α-GalCer has been used to therapeutically target iNKT cells to induce multiple profound effects during different pathological conditions, including cancer, autoimmunity, and infectious disease (8, 10–14).

Like the development of conventional T lymphocytes, iNKT cell development depends on somatic DNA recombination and selection in the thymus. CD1d presentation of endogenous ligands is critical for iNKT cell development and animals lacking CD1d have no detectable iNKT cells (15–17). In sharp contrast with conventional T cells, which require MHC expression by thymic epithelial cells for their development, iNKT cells are positively selected by CD1d-expressing CD4+CD8+ double positive (DP) thymocytes (16, 18) (**Figure 1**). Nevertheless, a recent study provided evidence that a fraction of iNKT cells develop from late CD4−CD8− double negative (DN) stage thymocytes, bypassing the DP stage (19). Negative selection of iNKT cells is not yet clearly defined. Evidence showing that overexpression of CD1d on thymic stromal cells, dendritic cells (DCs), or DP thymocytes in transgenic mice resulted in a variable reduction in the number of iNKT cells suggests that iNKT cells are susceptible to negative selection during their development (20, 21). After the initial selection, iNKT cells transit through four maturation stages, each characterized by sequential acquisition of surface markers: stage 0, CD24+CD44−NK1.1−; stage

**36**

1, CD24−CD44−NK1.1−; stage 2, CD24−CD44+NK1.1−; and stage 3, CD24−CD44+NK1.1+ (22, 23). iNKT cells become functionally competent to respond to TCR engagement during their maturation in the thymus. Functionally, thymic iNKT cells can be subdivided into iNKT1, iNKT2, and iNKT17 subsets according to their expression of particular transcription factors, surface markers, and cytokines that are expressed by conventional CD4+ T helper (Th) cell subsets (Th1, Th2, and Th17 cells, respectively). Although the relationships between the different stages of iNKT cells and their subsets remain to be fully explored, stage 1 iNKT cells comprise mainly progenitor cells and include cells with the capacity to produce interleukin (IL)-4 that may be related to iNKT2 cells, stage 2 cells likely include all three subsets, and stage 3 cells predominantly include iNKT1 cells (**Figure 1**). Recent studies have provided evidence that TCR signaling strength governs this iNKT cell subset development, with strong signaling favoring iNKT2 and iNKT17 cell development (24, 25). In addition to these subsets, iNKT follicular helper cells and iNKT10 cells have been identified that resemble T follicular helper cells and regulatory T cells, respectively. Recent studies have revealed a critical role of autophagy, a cellular self-degradation mechanism, in iNKT cell development and function. Here, we review these findings in the context of changes in the metabolic status of developing iNKT cells.

#### SIGNALING PATHWAYS THAT CONTROL iNKT CELL DEVELOPMENT

Many signaling proteins and transcription factors are important for iNKT cell development and/or function. Deficiency of the invariant Vα14 TCR or its ligand CD1d results in a failure in iNKT cell generation (7, 17, 26). Runt-related transcription factor 1 is critical for the ontogeny of functional iNKT cells (18). The E protein transcription factor, HEB, is essential for iNKT cells to develop at their earliest developmental stage. This HEB-mediated regulation, in part, is controlled by modulating the expression of retinoic acid receptor-related orphan nuclear receptor gamma t, a possible HEB target, and the anti-apoptotic molecule Bcl-xL (18, 27–29). Once committed to the iNKT cell lineage, multiple other molecules are required for iNKT cell maturation. TCR engagement activates phospholipase Cγ1, which further leads to production of diacylglycerol (DAG) and inositol-1,4,5-trisphosphate (IP3), both of which are critical for iNKT cell development. DAG induces activation of the Ras guanyl nucleotide-releasing protein 1-Ras-extracellular signalregulated kinase 1/2 pathways and is involved in early iNKT cell development, as well as, late iNKT cell maturation (30). DAG kinases, which are important for controlling intracellular DAG concentration and therefore negatively regulate DAG signaling, are also critical for iNKT cell development (31). IP3 activates the Ca2+-calcineurin-NFAT pathway and regulates the generation of stage 1 and 2 iNKT cells via the early growth response protein

**Abbreviations:** α-GalCer, α-galactosylceramide; Atg, autophagy-related gene; DAG, diacylglycerol; DC, dendritic cell; DN, double negative; DP, double positive; Egr2, early growth response protein 2; HDACs, histone deacetylases; IFN-γ, interferon-gamma; IL, interleukin; iNKT, invariant natural killer T; IP3, inositol-1,4,5-trisphosphate; LC3, microtubule-associated protein 1A/1Blight chain 3; LKB1, liver kinase B1; mTOR, mechanistic target of rapamycin; PI3P, phosphatidylinositol 3-phosphate; PLZF, promyelocytic leukemia zinc finger; RACK1, receptor for activated C kinase 1; SLAM, signaling lymphocyte-activation molecule; Tbkbp1, TBK-binding protein 1; TCR, T cell receptor; Th, T helper; Tsc1, tuberous sclerosis 1; Vps, vacuolar protein sorting.

2 (Egr2) (32). Egr2 directly binds to the Zbtb16 promoter and activates transcription factor promyelocytic leukemia zinc finger (PLZF) that supports iNKT cell transition from stage 1 to stage 2 (33, 34). PLZF is thought to control the innate phenotype and is also expressed by MAIT cells, γδ T cells, and innate lymphoid precursor cells in the fetal liver and adult bone marrow (35–37).

Signaling lymphocyte-activation molecule (SLAM) receptors are critical for early iNKT cell maturation (38). Homotypic interactions of SLAM molecules, Slamf1, and Slamf6 and the downstream recruitment of SLAM adaptor protein and the Src kinase Fyn control formation of the stage 0 iNKT cell lineage by activating the NF-κB signaling cascade (39). Other transcription factors including c-Myc, T-bet, Id2, and GATA-3 were shown to regulate different stages of iNKT cell maturation after they migrate to peripheral lymphoid tissues (29). Many additional transcription factors and signaling molecules such as thymocyte selection-associated HMG box protein, Notch signaling, lymphoid enhancer factor, mechanistic target of rapamycin (mTOR), etc., have been reported to impact iNKT cell development and effector function (29, 40, 41). In addition to these pathways, autophagy and autophagy-related pathways also have been reported to be involved in iNKT cell development.

# A BRIEF INTRODUCTION TO AUTOPHAGY