Drugs and drug-like molecules can modulate the function of mucosal-associated invariant T cells

The major-histocompatibility-complex-(MHC)-class-I-related molecule MR1 can present activating and non-activating vitamin-B-based ligands to mucosal-associated invariant T cells (MAIT cells). Whether MR1 binds other ligands is unknown. Here we identified a range of small organic molecules, drugs, drug metabolites and drug-like molecules, including salicylates and diclofenac, as MR1-binding ligands. Some of these ligands inhibited MAIT cells ex vivo and in vivo, while others, including diclofenac metabolites, were agonists. Crystal structures of a T cell antigen receptor (TCR) from a MAIT cell in complex with MR1 bound to the non-stimulatory and stimulatory compounds showed distinct ligand orientations and contacts within MR1, which highlighted the versatility of the MR1 binding pocket. The findings demonstrated that MR1 was able to capture chemically diverse structures, spanning mono- and bicyclic compounds, that either inhibited or activated MAIT cells. This indicated that drugs and drug-like molecules can modulate MAIT cell function in mammals

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer‐reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state‐of‐the‐art handbook for basic and clinical researchers.DFG, 389687267, Kompartimentalisierung, Aufrechterhaltung und Reaktivierung humaner Gedächtnis-T-Lymphozyten aus Knochenmark und peripherem BlutDFG, 80750187, SFB 841: Leberentzündungen: Infektion, Immunregulation und KonsequenzenEC/H2020/800924/EU/International Cancer Research Fellowships - 2/iCARE-2DFG, 252623821, Die Rolle von follikulären T-Helferzellen in T-Helferzell-Differenzierung, Funktion und PlastizitätDFG, 390873048, EXC 2151: ImmunoSensation2 - the immune sensory syste

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion

TCR Bias and Affinity Define Two Compartments of the CD1b- Glycolipid-Specific T Cell Repertoire

Current views emphasize TCR diversity as a key feature that differentiates the group 1 (CD1a, CD1b, CD1c) and group 2 (CD1d) CD1 systems. Whereas TCR sequence motifs define CD1d-reactive NKT cells, the available data do not allow a TCR-based organization of the group 1 CD1 repertoire. The observed TCR diversity might result from donor-to-donor differences in TCR repertoire, as seen for MHC-restricted T cells. Alternatively, diversity might result from differing CD1 isoforms, Ags, and methods used to identify TCRs. Using CD1b tetramers to isolate clones recognizing the same glycolipid, we identified a previously unknown pattern of V gene usage (TRAV17, TRBV4-1) among unrelated human subjects. These TCRs are distinct from those present on NKT cells and germline-encoded mycolyl lipid–reactive T cells. Instead, they resemble the TCR of LDN5, one of the first known CD1b-reactive clones that was previously thought to illustrate the diversity of the TCR repertoire. Interdonor TCR conservation was observed in vitro and ex vivo, identifying LDN5-like T cells as a distinct T cell type. These data support TCR-based organization of the CD1b repertoire, which consists of at least two compartments that differ in TCR sequence motifs, affinity, and coreceptor expression

Diversity of T cells restricted by the MHC class I-related molecule MR1 facilitates differential antigen recognition

A characteristic of mucosal-associated invariant T (MAIT) cells is the expression of TRAV1-2(+) T cell receptors (TCRs) that are activated by riboflavin metabolite- based antigens (Ag) presented by the MHC-I related molecule, MR1. Whether the MR1-restricted T cell repertoire and associated Ag responsiveness extends beyond these cells remains unclear. Here, we describe MR1 autoreactivity and folate-derivative reactivity in a discrete subset of TRAV1-2(+) MAIT cells. This recognition was attributable to CDR3 beta loop-mediated effects within a consensus TRAV1-2(+) TCR-MR1-Ag footprint. Furthermore, we have demonstrated differential folate-and riboflavin-derivative reactivity by a diverse population of "atypical'' TRAV1-2(-) MR1-restricted T cells. We have shown that TRAV1-2(-) T cells are phenotypically heterogeneous and largely distinct from TRAV1-2(+) MAIT cells. A TRAV1-2(-) TCR docks more centrally on MR1, thereby adopting a markedly different molecular footprint to the TRAV1-2(+) TCR. Accordingly, diversity within the MR1-restricted T cell repertoire leads to differing MR1-restricted Ag specificity

CD3(bright) signals on γδ T cells identify IL-17A-producing Vγ6Vδ1(+) T cells.

International audienceInterleukin-17A (IL-17A) is a pro-inflammatory cytokine that has an important role at mucosal sites in a wide range of immune responses including infection, allergy and auto-immunity. γδ T cells are recognized as IL-17 producers, but based on the level of CD3 expression, we now define the remarkable ability of a CD3(bright) γδ T-cell subset with an effector memory phenotype to rapidly produce IL-17A, but not interferon-γ. CD3(bright) γδ T cells uniformly express the canonical germline encoded Vγ6/Vδ1(+) T-cell receptor. They are widely distributed with a preferential representation in the lungs and skin are negatively impacted in the absence of retinoic acid receptor-related orphan receptor gammat expression or endogenous flora. This population responded rapidly to various stimuli in a mechanism involving IL-23 and NOD-like receptor family, pyrin domain containing 3 (NLRP3)-inflammasome-dependent IL-1β. Finally, we demonstrated that IL-17-producing CD3(bright) γδ T cells responded promptly and strongly to pneumococcal infection and during skin inflammation. Here, we propose a new way to specifically analyze IL-17-producing Vγ6/Vδ1(+) T cells based on the level of CD3 signals. Using this gating strategy, our data reinforce the crucial role of this γδ T-cell subset in respiratory and skin disorders

Human blood MAIT cell subsets defined using MR1 tetramers

Mucosal-associated invariant T (MAIT) cells represent up to 10% of circulating human T-cells. They are usually defined using combinations of non-lineage-specific (surrogate) markers such as anti-TRAV1-2, CD161, IL-18Rα and CD26. The development of MR1-Ag tetramers now permits the specific identification of MAIT cells based on TCR specificity. Here, we compare these approaches for identifying MAIT cells and show that surrogate markers are not always accurate in identifying these cells, particularly the CD4fraction. Moreover, while all MAIT cell subsets produced comparable levels of IFNγ, TNF and IL-17A, the CD4population produced more IL-2 than the other subsets. In a human ontogeny study, we show that the frequencies of most MR1 tetramerMAIT cells, with the exception of CD4MAIT cells, increased from birth to about 25 years-of-age and declined thereafter. We also demonstrate a positive association between the frequency of MAIT cells and other unconventional T cells including Natural Killer T (NKT) cells and Vδ2γδ T cells. Accordingly, this study demonstrates that MAIT cells are phenotypically and functionally diverse, that surrogate markers may not reliably identify all of these cells, and that their numbers are regulated in an age-dependent manner and correlate with NKT and Vδ2γδ T cells. This article is protected by copyright. All rights reserved

Obesity Reduces mTORC1 Activity in Mucosal-Associated Invariant T Cells, Driving Defective Metabolic and Functional Responses

Obesity underpins the development of numerous chronic diseases, such as type II diabetes mellitus. It is well established that obesity negatively alters immune cell frequencies and functions. Mucosal-associated invariant T (MAIT) cells are a population of innate T cells, which we have previously reported are dysregulated in obesity, with altered circulating and adipose tissue frequencies and a reduction in their IFN-g production, which is a critical effector function of MAIT cells in host defense. Hence, there is increased urgency to characterize the key molecular mechanisms that drive MAIT cell effector functions and to identify those which are impaired in the obesity setting. In this study, we found that MAIT cells significantly upregulate their rates of glycolysis upon activation in an mTORC1-dependent manner, and this is essential for MAIT cell IFN-g production. Furthermore, we show that mTORC1 activation is dependent on amino acid transport via SLC7A5. In obese patients, using RNA sequencing, Seahorse analysis, and a series of in vitro experiments, we demonstrate that MAIT cells isolated from obese adults display defective glycolytic metabolism, mTORC1 signaling, and SLC7A5 aa transport. Collectively, our data detail the intrinsic metabolic pathways controlling MAIT cell cytokine production and highlight mTORC1 as an important metabolic regulator that is impaired in obesity, leading to altered MAIT cell responses