Innate-like functions of natural killer T cell subsets result from highly divergent gene programs

Single-cell transcriptomics in dermatology

The skin is an ecosystem composed of specialized cell types that work together to serve as a physical protective barrier. Single-cell resolution is therefore essential to deconvolve skin's heterogeneity by identifying novel, distinct cell subsets in health and disease. Single-cell RNA sequencing is a highly meticulous methodology used to study the distinct transcriptional profiles of each cell within large tissue libraries at uniquely high resolution. The investigative capabilities achieved by this methodology allow previously unattainable analyses, including identification of rare cell populations, evaluation of cell-to-cell variation, and the ability to track trajectories of distinct cell lineages through development. In the past decade, application of transcriptomic analysis to skin biology and dermatology has greatly advanced understanding of homeostatic physiology in the skin, as well as a multitude of dermatologic diseases. Single-cell RNA sequencing offers tremendous promise for identification of novel therapeutic targets in dermatologic diseases, with broad implications of improving therapeutic interventions.

Impact of Aging on the Phenotype of Invariant Natural Killer T Cells in Mouse Thymus

Invariant natural killer T (iNKT) cells represent a subclass of T cells possessing a restricted repertoire of T cell receptors enabling them to recognize lipid derived ligands. iNKT cells are continuously generated in thymus and differentiate into three main subpopulations: iNKT1, iNKT2, and iNKT17 cells. We investigated the transcriptomes of these subsets comparing cells isolated from young adult (6–10 weeks old) and aged BALB/c mice (25–30 weeks of age) in order to identify genes subject to an age-related regulation of expression. These time points were selected to take into consideration the consequences of thymic involution that radically alter the existing micro-milieu. Significant differences were detected in the expression of histone genes affecting all iNKT subsets. Also the proliferative capacity of iNKT cells decreased substantially upon aging. Several genes were identified as possible candidates causing significant age-dependent changes in iNKT cell generation and/or function such as genes coding for granzyme A, ZO-1, EZH2, SOX4, IGF1 receptor, FLT4, and CD25. Moreover, we provide evidence that IL2 differentially affects homeostasis of iNKT subsets with iNKT17 cells engaging a unique mechanism to respond to IL2 by initiating a slow rate of proliferation.

Serpinb1a Is Dispensable for the Development and Cytokine Response of Invariant Natural Killer T Cell Subsets

Invariant natural killer T (iNKT) cells are innate-like T lymphocytes. They quickly respond to antigenic stimulation by producing copious amounts of cytokines and chemokines. iNKT precursors differentiate into three subsets iNKT1, iNKT2, and iNKT17 with specific cytokine production signatures. While key transcription factors drive subset differentiation, factors that regulate iNKT subset homeostasis remain incompletely defined. Transcriptomic analyses of thymic iNKT subsets indicate that Serpinb1a is one of the most specific transcripts for iNKT17 cells suggesting that iNKT cell maintenance and function may be regulated by Serpinb1a. Serpinb1a is a major survival factor in neutrophils and prevents cell death in a cell-autonomous manner. It also controls inflammation in models of bacterial and viral infection as well as in LPS-driven inflammation. Here, we examined the iNKT subsets in neutropenic Serpinb1a^−/− mice as well as in Serpinb1a^−/− mice with normal neutrophil counts due to transgenic re-expression of SERPINB1 in neutrophils. In steady state, we found no significant effect of Serpinb1a-deficiency on the proliferation and numbers of iNKT subsets in thymus, lymph nodes, lung, liver and spleen. Following systemic activation with α-galactosylceramide, the prototypic glycolipid agonist of iNKT cells, we observed similar serum levels of IFN-γ and IL-4 between genotypes. Moreover, splenic dendritic cells showed normal upregulation of maturation markers following iNKT cell activation with α-galactosylceramide. Finally, lung instillation of α-galactosylceramide induced a similar recruitment of neutrophils and production of iNKT-derived cytokines IL-17, IFN-γ, and IL-4 in wild-type and Serpinb1a^−/− mice. Taken together, our results indicate that Serpinb1a, while dominantly expressed in iNKT17 cells, is not essential for iNKT cell homeostasis, subset differentiation and cytokine release.

Unveiling the heterogeneity of NKT cells in the liver through single cell RNA sequencing

CD1d-dependent type I NKT cells, which are activated by lipid antigen, are known to play important roles in innate and adaptive immunity, as are a portion of type II NKT cells. However, the heterogeneity of NKT cells, especially NKT-like cells, remains largely unknown. Here, we report the profiling of NKT (NK1.1⁺CD3e⁺) cells in livers from wild type (WT), Jα18-deficient and CD1d-deficient mice by single-cell RNA sequencing. Unbiased transcriptional clustering revealed distinct cell subsets. The transcriptomic profiles identified the well-known CD1d-dependent NKT cells and defined two CD1d-independent NKT cell subsets. In addition, validation of marker genes revealed the differential organ distribution and landscape of NKT cell subsets during liver tumor progression. More importantly, we found that CD1d-independent Sca-1⁻CD62L⁺ NKT cells showed a strong ability to secrete IFN-γ after costimulation with IL-2, IL-12 and IL-18 in vitro. Collectively, our findings provide a comprehensive characterization of NKT cell heterogeneity and unveil a previously undefined functional NKT cell subset.

Modulation of Immune Responses to Influenza A Virus Vaccines by Natural Killer T Cells

Influenza A viruses (IAVs) circulate widely among different mammalian and avian hosts and sometimes give rise to zoonotic infections. Vaccination is a mainstay of IAV prevention and control. However, the efficacy of IAV vaccines is often suboptimal because of insufficient cross-protection among different IAV genotypes and subtypes as well as the inability to keep up with the rapid molecular evolution of IAV strains. Much attention is focused on improving IAV vaccine efficiency using adjuvants, which are substances that can modulate and enhance immune responses to co-administered antigens. The current review is focused on a non-traditional approach of adjuvanting IAV vaccines by therapeutically targeting the immunomodulatory functions of a rare population of innate-like T lymphocytes called invariant natural killer T (iNKT) cells. These cells bridge the innate and adaptive immune systems and are capable of stimulating a wide array of immune cells that enhance vaccine-mediated immune responses. Here we discuss the factors that influence the adjuvant effects of iNKT cells for influenza vaccines as well as the obstacles that must be overcome before this novel adjuvant approach can be considered for human or veterinary use.

High-parametric evaluation of human invariant natural killer T cells to delineate heterogeneity in allo- and autoimmunity

Human invariant natural killer T (iNKT) cells are a rare innate-like lymphocyte population that recognizes glycolipids presented on CD1d. Studies in mice have shown that these cells are heterogeneous and are capable of enacting diverse functions, and the composition of iNKT cell subsets can alter disease outcomes. In contrast, far less is known about how heterogeneity in human iNKT cells relates to disease. To address this, we used a high-dimensional, data-driven approach to devise a framework for parsing human iNKT heterogeneity. Our data revealed novel and previously described iNKT cell phenotypes with distinct functions. In particular, we found 2 phenotypes of interest: (1) a population with T helper 1 function that was increased with iNKT activation characterized by HLA-II+CD161- expression, and (2) a population with enhanced cytotoxic function characterized by CD4-CD94+ expression. These populations correlate with acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation and with new onset type 1 diabetes, respectively. Our study identifies human iNKT cell phenotypes associated with human disease that could aid in the development of biomarkers or therapeutics targeting iNKT cells.

LRSK: a low-rank self-representation K-means method for clustering single-cell RNA-sequencing data

The development of single-cell RNA-sequencing (scRNA-seq) technologies brings tremendous opportunities for quantitative research and analyses at the cellular level. In particular, as a crucial task of scRNA-seq analysis, single cell clustering shines a light on natural groupings of cells to give new insights into the biological mechanisms and disease studies. However, it remains a challenge to identify cell clusters from lots of cell mixtures effectively and accurately. In this paper, we propose a novel adaptive joint clustering framework, named the low-rank self-representation K-means method (LRSK), to learn the data representation matrix and cluster indicator matrix jointly from scRNA-seq data. Specifically, instead of calculating the similarities among cells from the original data, we seek a low-rank representation of the original data to better reflect the underlying relationships among cells. Moreover, an Augmented Lagrangian Multiplier (ALM) based optimization algorithm is adopted to solve this problem. Experimental results on various scRNA-seq datasets and case studies demonstrate that our method performs better than other state-of-the-art single cell clustering algorithms. The analysis of unlabeled large single-cell liver cancer sequencing data further shows that our prediction results are more reasonable and interpretable.

RIPK1 gene variants associate with obesity in humans and can be therapeutically silenced to reduce obesity in mice

Obesity is a major public health burden worldwide and is characterized by chronic low-grade inflammation driven by the cooperation of the innate immune system and dysregulated metabolism in adipose tissue and other metabolic organs. Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) is a central regulator of inflammatory cell function that coordinates inflammation, apoptosis and necroptosis in response to inflammatory stimuli. Here we show that genetic polymorphisms near the human RIPK1 locus associate with increased RIPK1 gene expression and obesity. We show that one of these single nucleotide polymorphisms is within a binding site for E4BP4 and increases RIPK1 promoter activity and RIPK1 gene expression in adipose tissue. Therapeutic silencing of RIPK1 in vivo in a mouse model of diet-induced obesity dramatically reduces fat mass, total body weight and improves insulin sensitivity, while simultaneously reducing macrophage and promoting invariant natural killer T cell accumulation in adipose tissue. These findings demonstrate that RIPK1 is genetically associated with obesity, and reducing RIPK1 expression is a potential therapeutic approach to target obesity and related diseases.

Characterization of the developmental landscape of murine RORγt+ iNKT cells

Invariant natural killer T (iNKT) cells expressing the retinoic acid receptor-related orphan receptor γt (RORγt) and producing IL-17 represent a minor subset of CD1d-restricted iNKT cells (iNKT17) in C57BL/6J (B6) mice. We aimed in this study to define the reasons for their low distribution and the sequence of events accompanying their normal thymic development. We found that RORγt+ iNKT cells have higher proliferation potential and a greater propensity to apoptosis than RORγt- iNKT cells. These cells do not likely reside in the thymus indicating that thymus emigration, and higher apoptosis potential, could contribute to RORγt+ iNKT cell reduced thymic distribution. Ontogeny studies suggest that mature HSAlow RORγt+ iNKT cells might develop through developmental stages defined by a differential expression of CCR6 and CD138 during which RORγt expression and IL-17 production capabilities are progressively acquired. Finally, we found that RORγt+ iNKT cells perceive a strong TCR signal that could contribute to their entry into a specific 'Th17 like' developmental program influencing their survival and migration. Overall, our study proposes a hypothetical thymic developmental sequence for iNKT17 cells, which could be of great use to study molecular mechanisms regulating this developmental program.

SPARSim single cell: a count data simulator for scRNA-seq data

MOTIVATION

Single cell RNA-seq (scRNA-seq) count data show many differences compared with bulk RNA-seq count data, making the application of many RNA-seq pre-processing/analysis methods not straightforward or even inappropriate. For this reason, the development of new methods for handling scRNA-seq count data is currently one of the most active research fields in bioinformatics. To help the development of such new methods, the availability of simulated data could play a pivotal role. However, only few scRNA-seq count data simulators are available, often showing poor or not demonstrated similarity with real data.

RESULTS

In this article we present SPARSim, a scRNA-seq count data simulator based on a Gamma-Multivariate Hypergeometric model. We demonstrate that SPARSim allows to generate count data that resemble real data in terms of count intensity, variability and sparsity, performing comparably or better than one of the most used scRNA-seq simulator, Splat. In particular, SPARSim simulated count matrices well resemble the distribution of zeros across different expression intensities observed in real count data.

AVAILABILITY AND IMPLEMENTATION

SPARSim R package is freely available at http://sysbiobig.dei.unipd.it/? q=SPARSim and at https://gitlab.com/sysbiobig/sparsim.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Recognition of Candida albicans and Role of Innate Type 17 Immunity in Oral Candidiasis

Candida albicans is an opportunistic pathogenic fungus considered to be a common member of the human microflora. Similar to some other opportunistic microbes, C. albicans can invade and benefit from its host when the immune status of that host is weakened. Most often this happens to immunocompromised individuals, leading to the infection of oral and vaginal mucosae or the systemic spread of the pathogen throughout the entire body. Oropharyngeal candidiasis (OPC) occurs in up to 90 percent of patients with acquired immunodeficiency syndrome (AIDS), making it the most frequent opportunistic infection for this group. Upon first signs of fungal invasion, a range of host signaling activates in order to eliminate the threat. Epithelial and myeloid type cells detect C. albicans mainly through receptor tyrosine kinases and pattern-recognition receptors. This review provides an overview of downstream signaling resulting in an adequate immune response through the activation of various transcription factors. The study discusses recent advances in research of the interleukin-17 (IL-17) producing innate cells, including natural T helper 17 (nTh17) cells, γδ T cells, invariant natural killer T (iNKT) cells and type 3 innate lymphoid cells (ILC3) that are involved in response to oral C. albicans infections.

Single-cell RNA sequencing identifies shared differentiation paths of mouse thymic innate T cells

Invariant natural killer T (iNKT), mucosal-associated invariant T (MAIT), and γδ T cells are innate T cells that acquire memory phenotype in the thymus and share similar biological characteristics. However, how their effector differentiation is developmentally regulated is still unclear. Here, we identify analogous effector subsets of these three innate T cell types in the thymus that share transcriptional profiles. Using single-cell RNA sequencing, we show that iNKT, MAIT and γδ T cells mature via shared, branched differentiation rather than linear maturation or TCR-mediated instruction. Simultaneous TCR clonotyping analysis reveals that thymic maturation of all three types is accompanied by clonal selection and expansion. Analyses of mice deficient of TBET, GATA3 or RORγt and additional in vivo experiments corroborate the predicted differentiation paths, while human innate T cells from liver samples display similar features. Collectively, our data indicate that innate T cells share effector differentiation processes in the thymus.

Innate T cells such as iNKT, MAIT and γδ T cells all develop in the thymus, but their differentiation paths are still unclear. Here, the authors show, using single-cell RNA sequencing, that all three cell types develop via shared and branched differentiation paths that are corroborated by additional results from gene-deficient mice and human liver T cells.

A Semiautomated ChIP-Seq Procedure for Large-scale Epigenetic Studies

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) is a powerful and widely used approach to profile chromatin DNA associated with specific histone modifications, such as H3K27ac, to help identify cis-regulatory DNA elements. The manual process to complete a ChIP-Seq is labor intensive, technically challenging, and often requires large-cell numbers (>100,000 cells). The method described here helps to overcome those challenges. A complete semiautomated, microscaled H3K27ac ChIP-Seq procedure including cell fixation, chromatin shearing, immunoprecipitation, and sequencing library preparation, for batch of 48 samples for cell number inputs less than 100,000 cells is described in detail. The semiautonomous platform reduces technical variability, improves signal-to-noise ratios, and drastically reduces labor. The system can thereby reduce costs by allowing for reduced reaction volumes, limiting the number of expensive reagents such as enzymes, magnetic beads, antibodies, and hands-on time required. These improvements to the ChIP-Seq method suit perfectly for large-scale epigenetic studies of clinical samples with limited cell numbers in a highly reproducible manner.

Distinct iNKT Cell Populations Use IFNγ or ER Stress-Induced IL-10 to Control Adipose Tissue Homeostasis

Adipose tissue invariant natural killer T (iNKT) cells are phenotypically different from other iNKT cells because they produce IL-10 and control metabolic homeostasis. Why that is the case is unclear. Here, using single-cell RNA sequencing, we found several adipose iNKT clusters, which we grouped into two functional populations based on NK1.1 expression. NK1.1^NEG cells almost exclusively produced IL-10 and other regulatory cytokines, while NK1.1^POS iNKT cells predominantly produced IFNγ. Mechanistically, biochemical fractionation revealed that free fatty acids drive IL-10 production primarily in NK1.1^NEG iNKT cells via the IRE1α-XBP1s arm of the unfolded protein response. Correspondingly, adoptive transfer of adipose tissue NK1.1^NEG iNKT cells selectively restored metabolic function in obese mice. Further, we found an unexpected role for NK1.1^POS iNKT cells in lean adipose tissue, as IFNγ licenses natural killer cell-mediated macrophage killing to limit pathological macrophage expansion. Together, these two iNKT cell populations utilize non-redundant pathways to preserve metabolic integrity.

The transcription factor BCL-6 controls early development of innate-like T cells

Innate T cells, including invariant natural killer T (iNKT) and mucosal-associated innate T (MAIT) cells, are a heterogeneous T lymphocyte population with effector properties pre-programmed during their thymic differentiation. How this program is initiated is currently unclear. Here, we show that the transcription factor BCL-6 was transiently expressed in iNKT cells upon exit from positive selection and was required for their proper development beyond stage 0. Notably, development of MAIT cells was also impaired in the absence of Bcl6. BCL-6–deficient iNKT cells had reduced expression of genes that were associated with the innate T cell lineage, including Zbtb16, which encodes PLZF, and PLZF-targeted genes. BCL-6 contributed to a chromatin accessibility landscape that was permissive for the expression of development-related genes and inhibitory for genes associated with naïve T cell programs. Our results revealed novel functions for BCL-6 and illuminated how this transcription factor controls early iNKT cell development.

Nur77 controls tolerance induction, terminal differentiation, and effector functions in semi-invariant natural killer T cells

Semi-invariant natural killer T (iNKT) cells are self-reactive lymphocytes, yet how this lineage attains self-tolerance remains unknown. iNKT cells constitutively express high levels of Nr4a1-encoded Nur77, a transcription factor that integrates signal strength downstream of the T cell receptor (TCR) within activated thymocytes and peripheral T cells. The function of Nur77 in iNKT cells is unknown. Here we report that sustained Nur77 overexpression (Nur77tg) in mouse thymocytes abrogates iNKT cell development. Introgression of a rearranged Vα14-Jα18 TCR-α chain gene into the Nur77tg (Nur77tg;Vα14tg) mouse rescued iNKT cell development up to the early precursor stage, stage 0. iNKT cells in bone marrow chimeras that reconstituted thymic cellularity developed beyond stage 0 precursors and yielded IL-4-producing NKT2 cell subset but not IFN-γ-producing NKT1 cell subset. Nonetheless, the developing thymic iNKT cells that emerged in these chimeras expressed the exhaustion marker PD1 and responded poorly to a strong glycolipid agonist. Thus, Nur77 integrates signals emanating from the TCR to control thymic iNKT cell tolerance induction, terminal differentiation, and effector functions.

The Impact of Single-Cell Genomics on Adipose Tissue Research

Adipose tissue is an important regulator of whole-body metabolism and energy homeostasis. The unprecedented growth of obesity and metabolic disease worldwide has required paralleled advancements in research on this dynamic endocrine organ system. Single-cell RNA sequencing (scRNA-seq), a highly meticulous methodology used to dissect tissue heterogeneity through the transcriptional characterization of individual cells, is responsible for facilitating critical advancements in this area. The unique investigative capabilities achieved by the combination of nanotechnology, molecular biology, and informatics are expanding our understanding of adipose tissue's composition and compartmentalized functional specialization, which underlie physiologic and pathogenic states, including adaptive thermogenesis, adipose tissue aging, and obesity. In this review, we will summarize the use of scRNA-seq and single-nuclei RNA-seq (snRNA-seq) in adipocyte biology and their applications to obesity and diabetes research in the hopes of increasing awareness of the capabilities of this technology and acting as a catalyst for its expanded use in further investigation.

M1hot tumor-associated macrophages boost tissue-resident memory T cells infiltration and survival in human lung cancer

BACKGROUND

The role of tumor-associated macrophages (TAMs) in determining the outcome between the antitumor effects of the adaptive immune system and the tumor's anti-immunity stratagems, is controversial. Macrophages modulate their activities and phenotypes by integration of signals in the tumor microenvironment. Depending on how macrophages are activated, they may adopt so-called M1-like, antitumor or M2-like, protumor profiles. In many solid tumors, a dominance of M2-like macrophages is associated with poor outcomes but in some tumor types, strong M1-like profiles are linked to better outcomes. We aimed to investigate the interrelationship of these TAM populations to establish how they modulate the efficacy of the adaptive immune system in early lung cancer.

METHODS

Macrophages from matched lung (non-tumor-associated macrophages (NTAMs)) and tumor samples (TAMs) from resected lung cancers were assessed by bulk and single-cell transcriptomic analysis. Protein expression of genes characteristic of M1-like (chemokine (C-X-C motif) ligand 9) or M2-like (matrix metallopeptidase 12) functions was confirmed by confocal microscopy. Immunohistochemistry related the distribution of TAM transcriptomic signatures to density of CD8+ tissue-resident memory T cells (TRM) in tumors and survival data from an independent cohort of 393 patients with lung cancer.

RESULTS

TAMs have significantly different transcriptomic profiles from NTAMs with >1000 differentially expressed genes. TAMs displayed a strong M2-like signature with no significant variation between patients. However, single-cell RNA-sequencing supported by immuno-stained cells revealed that additionally, in 25% of patients the M2-like TAMs also co-expressed a strong/hot M1-like signature (M1hot). Importantly, there was a strong association between the density of M1hot TAMs and TRM cells in tumors that was in turn linked to better survival. Our data suggest a mechanism by which M1hot TAMs may recruit TRM cells via CXCL9 expression and sustain them by making available more of the essential fatty acids on which TRM depend.

CONCLUSIONS

We showed that in early lung cancer, expression of M1-like and M2-like gene signatures are not mutually exclusive since the same TAMs can simultaneously display both gene-expression profiles. The presence of M1hot TAMs was associated with a strong TRM tumor-infiltrate and better outcomes. Thus, therapeutic approaches to re-program TAMs to an M1hot phenotype are likely to augment the adaptive antitumor responses.

Latency-associated Peptide Identifies Immunoevasive Subtype Gastric Cancer With Poor Prognosis and Inferior Chemotherapeutic Responsiveness

OBJECTIVE

To examine the clinical significance of LAP to predict survival outcomes and chemotherapeutic responsiveness in gastric cancer.

BACKGROUND

LAP has been shown to possess significant immunoregulatory roles in several malignancies. However, the role and clinical significance of LAP in gastric cancer still remains unknown.

METHODS

Four hundred and fifty-six tumor tissue microarray specimens, 80 fresh tumor tissue samples of gastric cancer patients from Zhongshan Hospital, Fudan University and transcriptomic and clinical data of 328 gastric cancer patients from the Cancer Genome Atlas were analyzed. LAP expression and immune contexture were examined by immunohistochemistry, CIBERSORT, and flow cytometry. Clinical outcomes of patient subgroups were compared by Kaplan-Meier curves, Cox model and interaction test.

RESULTS

High LAP expression predicted poor overall survival (P < 0.001, P < 0.001, and P = 0.022) and inferior therapeutic responsiveness to fluorouracil-based adjuvant chemotherapy (P = 0.008 for interaction) in gastric cancer. LAP was associated with immunoevasive tumor microenvironment featured by dysfunctional CD8 T cells infiltration (P < 0.001). The LAP-associated dysfunctional CD8 T cells had an exhausted phenotype with decreased effector molecules such as interferon-γ, granzyme B, and perforin, but also elevated programmed cell death protein-1, which resulted in poor prognosis and inferior therapeutic responsiveness.

CONCLUSIONS

This study revealed that LAP could identify immunoevasive subtype gastric cancer, indicating LAP might be a potential immunotherapeutic target and facilitate patient counseling on individualized adjuvant therapy and follow-up scheduling in gastric cancer.

Hippo/Mst signaling coordinates cellular quiescence with terminal maturation in iNKT cell development and fate decisions

Invariant natural killer T (iNKT) cells acquire effector functions during development by mechanisms that remain poorly understood. Here, we show that the Hippo kinases Mst1 and Mst2 act as molecular rheostats for the terminal maturation and effector differentiation programs of iNKT cells. Loss of Mst1 alone or together with Mst2 impedes iNKT cell development, associated with defective IL-15-dependent cell survival. Mechanistically, Mst1 enforces iNKT cellular and transcriptional quiescence associated with maturation and commitment to iNKT1 cells by suppressing proliferation and Opa1-related mitochondrial metabolism that are dynamically regulated during iNKT cell development. Furthermore, Mst1 shapes the reciprocal fate decisions between iNKT1 and iNKT17 effector cells, which respectively depend upon mitochondrial dynamics and ICOS-mTORC2 signaling. Collectively, these findings establish Mst1 as a crucial regulator of mitochondrial homeostasis and quiescence in iNKT cell development and effector lineage differentiation and highlight that establishment of quiescence programs underlies iNKT cell development and effector maturation.

License to Kill: When iNKT Cells Are Granted the Use of Lethal Cytotoxicity

Invariant Natural Killer T (iNKT) cells are a non-conventional, innate-like, T cell population that recognize lipid antigens presented by the cluster of differentiation (CD)1d molecule. Although iNKT cells are mostly known for mediating several immune responses due to their massive and diverse cytokine release, these cells also work as effectors in various contexts thanks to their cytotoxic potential. In this Review, we focused on iNKT cell cytotoxicity; we provide an overview of iNKT cell subsets, their activation cues, the mechanisms of iNKT cell cytotoxicity, the specific roles and outcomes of this activity in various contexts, and how iNKT killing functions are currently activated in cancer immunotherapies. Finally, we discuss the future perspectives for the better understanding and potential uses of iNKT cell killing functions in tumor immunosurveillance.

Thymic resident NKT cell subsets show differential requirements for CD28 co-stimulation during antigenic activation

Natural killer T (NKT) cells rapidly respond to antigenic stimulation with cytokine production and direct cytotoxicity. These innate-like characteristics arise from their differentiation into mature effector cells during thymic development. A subset of mature NKT cells remain thymic resident, but their activation and function remain poorly understood. We examined the roles of CD28 and CTLA-4 in driving the activation of thymic resident NKT cells. In contrast to studies with peripheral NKT cells, the proliferation of thymic NKT cells was significantly impaired when CD28 engagement was blocked, but unaffected by CTLA-4 activation or blockade. Within NKT subsets, however, stage 3 NKT cells, marked by higher NK1.1 expression, were significantly more sensitive to the loss of CD28 signals compared to NK1.1- stage 2 NKT cells. In good agreement, CD28 blockade suppressed NKT cell cytokine secretion, lowering the ratio of IFN-γ:IL-4 production by NK1.1+ NKT cells. Intriguingly, the activation-dependent upregulation of the master transcription factor PLZF did not require CD28-costimulation in either of the thymic NKT subsets, underlining a dichotomy between requirements for early activation vs subsequent proliferation and effector function by these cells. Collectively, our studies demonstrate the ability of CD28 co-stimulation to fine tune subset-specific responses by thymic resident NKT cells and contextually shape the milieu in this primary lymphoid organ.

Diversity in medullary thymic epithelial cells controls the activity and availability of iNKT cells

The thymus supports multiple αβ T cell lineages that are functionally distinct, but mechanisms that control this multifaceted development are poorly understood. Here we examine medullary thymic epithelial cell (mTEC) heterogeneity and its influence on CD1d-restricted iNKT cells. We find three distinct mTEC^low subsets distinguished by surface, intracellular and secreted molecules, and identify LTβR as a cell-autonomous controller of their development. Importantly, this mTEC heterogeneity enables the thymus to differentially control iNKT sublineages possessing distinct effector properties. mTEC expression of LTβR is essential for the development thymic tuft cells which regulate NKT2 via IL-25, while LTβR controls CD104⁺CCL21⁺ mTEC^low that are capable of IL-15-transpresentation for regulating NKT1 and NKT17. Finally, mTECs regulate both iNKT-mediated activation of thymic dendritic cells, and iNKT availability in extrathymic sites. In conclusion, mTEC specialization controls intrathymic iNKT cell development and function, and determines iNKT pool size in peripheral tissues.

NOX4 Inhibition Potentiates Immunotherapy by Overcoming Cancer-Associated Fibroblast-Mediated CD8 T-cell Exclusion from Tumors

Determining mechanisms of resistance to αPD-1/PD-L1 immune-checkpoint immunotherapy is key to developing new treatment strategies. Cancer-associated fibroblasts (CAF) have many tumor-promoting functions and promote immune evasion through multiple mechanisms, but as yet, no CAF-specific inhibitors are clinically available. Here we generated CAF-rich murine tumor models (TC1, MC38, and 4T1) to investigate how CAFs influence the immune microenvironment and affect response to different immunotherapy modalities [anticancer vaccination, TC1 (HPV E7 DNA vaccine), αPD-1, and MC38] and found that CAFs broadly suppressed response by specifically excluding CD8+ T cells from tumors (not CD4+ T cells or macrophages); CD8+ T-cell exclusion was similarly present in CAF-rich human tumors. RNA sequencing of CD8+ T cells from CAF-rich murine tumors and immunochemistry analysis of human tumors identified significant upregulation of CTLA-4 in the absence of other exhaustion markers; inhibiting CTLA-4 with a nondepleting antibody overcame the CD8+ T-cell exclusion effect without affecting Tregs. We then examined the potential for CAF targeting, focusing on the ROS-producing enzyme NOX4, which is upregulated by CAF in many human cancers, and compared this with TGFβ1 inhibition, a key regulator of the CAF phenotype. siRNA knockdown or pharmacologic inhibition [GKT137831 (Setanaxib)] of NOX4 "normalized" CAF to a quiescent phenotype and promoted intratumoral CD8+ T-cell infiltration, overcoming the exclusion effect; TGFβ1 inhibition could prevent, but not reverse, CAF differentiation. Finally, NOX4 inhibition restored immunotherapy response in CAF-rich tumors. These findings demonstrate that CAF-mediated immunotherapy resistance can be effectively overcome through NOX4 inhibition and could improve outcome in a broad range of cancers. SIGNIFICANCE: NOX4 is critical for maintaining the immune-suppressive CAF phenotype in tumors. Pharmacologic inhibition of NOX4 potentiates immunotherapy by overcoming CAF-mediated CD8+ T-cell exclusion. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/9/1846/F1.large.jpg.See related commentary by Hayward, p. 1799.

An Adaptive Sparse Subspace Clustering for Cell Type Identification

The rapid development of single-cell transcriptome sequencing technology has provided us with a cell-level perspective to study biological problems. Identification of cell types is one of the fundamental issues in computational analysis of single-cell data. Due to the large amount of noise from single-cell technologies and high dimension of expression profiles, traditional clustering methods are not so applicable to solve it. To address the problem, we have designed an adaptive sparse subspace clustering method, called AdaptiveSSC, to identify cell types. AdaptiveSSC is based on the assumption that the expression of cells with the same type lies in the same subspace; one cell can be expressed as a linear combination of the other cells. Moreover, it uses a data-driven adaptive sparse constraint to construct the similarity matrix. The comparison results of 10 scRNA-seq datasets show that AdaptiveSSC outperforms original subspace clustering and other state-of-art methods in most cases. Moreover, the learned similarity matrix can also be integrated with a modified t-SNE to obtain an improved visualization result.

A focus on natural killer T-cell subset characterization and developmental stages

Almost 20 years ago, CD1d tetramers were developed to track invariant natural killer T (NKT) cells based on their specificity, and to define developmental steps during which differentiation markers and functional features are progressively acquired from early NKT cell precursor to fully mature NKT cell subsets. Based on these findings, a linear developmental model was proposed and subsequently used by all studies investigating the specific role of factors that control NKT cell development. More recently, based on intracellular staining patterns of lineage-specific transcription factors such as T-bet, GATA-3, promyelocytic leukemia zinc finger and RORγt, a lineage differentiation model was proposed for NKT cell development. Currently, studies on NKT cells development present lineage differentiation model data in addition to the linear maturation model. In the perspective presented here, we discuss current knowledge relating to NKT cell developmental models and particularly focus on the approaches and strategies, some of which appear nebulous, used to define NKT cell developmental stages and subsets.

Single-Cell Clustering Based on Shared Nearest Neighbor and Graph Partitioning

Clustering of single-cell RNA sequencing (scRNA-seq) data enables discovering cell subtypes, which is helpful for understanding and analyzing the processes of diseases. Determining the weight of edges is an essential component in graph-based clustering methods. While several graph-based clustering algorithms for scRNA-seq data have been proposed, they are generally based on k-nearest neighbor (KNN) and shared nearest neighbor (SNN) without considering the structure information of graph. Here, to improve the clustering accuracy, we present a novel method for single-cell clustering, called structural shared nearest neighbor-Louvain (SSNN-Louvain), which integrates the structure information of graph and module detection. In SSNN-Louvain, based on the distance between a node and its shared nearest neighbors, the weight of edge is defined by introducing the ratio of the number of the shared nearest neighbors to that of nearest neighbors, thus integrating structure information of the graph. Then, a modified Louvain community detection algorithm is proposed and applied to identify modules in the graph. Essentially, each community represents a subtype of cells. It is worth mentioning that our proposed method integrates the advantages of both SNN graph and community detection without the need for tuning any additional parameter other than the number of neighbors. To test the performance of SSNN-Louvain, we compare it to five existing methods on 16 real datasets, including nonnegative matrix factorization, single-cell interpretation via multi-kernel learning, SNN-Cliq, Seurat and PhenoGraph. The experimental results show that our approach achieves the best average performance in these datasets.

NKT cells and the regulation of intestinal immunity: a two‐way street

The mammalian gastrointestinal compartment is colonised by millions of microorganisms that have a central influence on human health. Intestinal homeostasis requires a continuous dialogue between the commensal bacteria and intestinal immune cells. While interactions between host and commensal bacteria are normally beneficial, allowing training and functional tuning of immune cells, dysregulated immune system-microbiota crosstalk can favour the development of chronic inflammatory diseases, as it is the case for inflammatory bowel disease (IBD). Natural killer T (NKT) cells, which recognise CD1-restricted microbial and self-lipids, contribute to the regulation of mucosal immunity by controlling intestinal homeostasis and participating in the development of IBD. Here, we provide an overview of the recently identified pathways underlying the crosstalk between commensal bacteria and NKT cells and discuss the effect of these interactions in intestinal health and disease.

Recent advances in iNKT cell development

Recent studies suggest that murine invariant natural killer T (iNKT) cell development culminates in three terminally differentiated iNKT cell subsets denoted as NKT1, 2, and 17 cells. Although these studies corroborate the significance of the subset division model, less is known about the factors driving subset commitment in iNKT cell progenitors. In this review, we discuss the latest findings in iNKT cell development, focusing in particular on how T-cell receptor signal strength steers iNKT cell progenitors toward specific subsets and how early progenitor cells can be identified. In addition, we will discuss the essential factors for their sustenance and functionality. A picture is emerging wherein the majority of thymic iNKT cells are mature effector cells retained in the organ rather than developing precursors.

Metabolic Triggers of Invariant Natural Killer T-Cell Activation during Sterile Autoinflammatory Disease

Ample evidence exists for activation of invariant natural killer T (iNKT) cells in a sterile manner by endogenous ligands or microbial antigens from the commensal flora, indicating that iNKT cells are not truly self-tolerant. Their controlled autoreactivity state is disturbed in many types of sterile inflammatory disease, resulting in their central role in modulating autoimmune responses. This review focuses on sterile iNKT-cell responses that are initiated by metabolic triggers, such as obesity-associated inflammation and fatty liver disease, as a manifestation of metabolic disease and dyslipidemia, as well as ischemia reperfusion injuries and sickle cell disease, characterized by acute lack of oxygen and oxidative stress response on reperfusion. In the intestine, inflammation and iNKT-cell response type are shaped by the microbiome as an extended "self". Disease- and organ-specific differences in iNKT-cell response type are summarized and help to define common pathways that shape iNKT-cell responses in the absence of exogenous antigen.

Allergen-specific IgG+ memory B cells are temporally linked to IgE memory responses

BACKGROUND

IgE is the least abundant immunoglobulin and tightly regulated, and IgE-producing B cells are rare. The cellular origin and evolution of IgE responses are poorly understood.

OBJECTIVE

The cellular and clonal origin of IgE memory responses following mucosal allergen exposure by sublingual immunotherapy (SLIT) were investigated.

METHODS

In a randomized double-blind, placebo-controlled, time course SLIT study, PBMCs and nasal biopsy samples were collected from 40 adults with seasonal allergic rhinitis at baseline and at 4, 8, 16, 28, and 52 weeks. RNA was extracted from PBMCs, sorted B cells, and nasal biopsy samples for heavy chain variable gene repertoire sequencing. Moreover, mAbs were derived from single B-cell transcriptomes.

RESULTS

Combining heavy chain variable gene repertoire sequencing and single-cell transcriptomics yielded direct evidence of a parallel boost of 2 clonally and functionally related B-cell subsets of short-lived IgE⁺ plasmablasts and IgG⁺ memory B cells. Mucosal grass pollen allergen exposure by SLIT resulted in highly diverse IgE and IgG_E repertoires. These were extensively mutated and appeared relatively stable as per heavy chain isotype, somatic hypermutations, and clonal composition. Single IgG_E⁺ memory B-cell and IgE⁺ preplasmablast transcriptomes encoded antibodies that were specific for major grass pollen allergens and able to elicit basophil activation at very low allergen concentrations.

CONCLUSION

For the first time, we have shown that on mucosal allergen exposure, human IgE memory resides in allergen-specific IgG⁺ memory B cells. These cells rapidly switch isotype, expand into short-lived IgE⁺ plasmablasts, and serve as a potential target for therapeutic intervention.

Tissue-specific shaping of the TCR repertoire and antigen specificity of iNKT cells

Tissue homeostasis is critically dependent on the function of tissue-resident lymphocytes, including lipid-reactive invariant natural killer T (iNKT) cells. Yet, if and how the tissue environment shapes the antigen specificity of iNKT cells remains unknown. By analysing iNKT cells from lymphoid tissues of mice and humans we demonstrate that their T cell receptor (TCR) repertoire is highly diverse and is distinct for cells from various tissues resulting in differential lipid-antigen recognition. Within peripheral tissues iNKT cell recent thymic emigrants exhibit a different TCR repertoire than mature cells, suggesting that the iNKT population is shaped after arrival to the periphery. Consistent with this, iNKT cells from different organs show distinct basal activation, proliferation and clonal expansion. Moreover, the iNKT cell TCR repertoire changes following immunisation and is shaped by age and environmental changes. Thus, post-thymic modification of the TCR-repertoire underpins the distinct antigen specificity for iNKT cells in peripheral tissues

A divergent transcriptional landscape underpins the development and functional branching of MAIT cells

MR1-restricted mucosal-associated invariant T (MAIT) cells play a unique role in the immune system. These cells develop intrathymically through a three-stage process, but the events that regulate this are largely unknown. Here, using bulk and single-cell RNA sequencing-based transcriptomic analysis in mice and humans, we studied the changing transcriptional landscape that accompanies transition through each stage. Many transcripts were sharply modulated during MAIT cell development, including SLAM (signaling lymphocytic activation molecule) family members, chemokine receptors, and transcription factors. We also demonstrate that stage 3 "mature" MAIT cells comprise distinct subpopulations including newly arrived transitional stage 3 cells, interferon-γ-producing MAIT1 cells and interleukin-17-producing MAIT17 cells. Moreover, the validity and importance of several transcripts detected in this study are directly demonstrated using specific mutant mice. For example, MAIT cell intrathymic maturation was found to be halted in SLAM-associated protein (SAP)-deficient and CXCR6-deficient mouse models, providing clear evidence for their role in modulating MAIT cell development. These data underpin a model that maps the changing transcriptional landscape and identifies key factors that regulate the process of MAIT cell differentiation, with many parallels between mice and humans.

Programming for T-lymphocyte fates: modularity and mechanisms

In this review, Rothenburg discusses the gene regulatory network and chromatin-based kinetic constraints that determine activities of transcription factors in the primary establishment of T-cell identity.

T-cell development in mammals is a model for lineage choice and differentiation from multipotent stem cells. Although T-cell fate choice is promoted by signaling in the thymus through one dominant pathway, the Notch pathway, it entails a complex set of gene regulatory network and chromatin state changes even before the cells begin to express their signature feature, the clonal-specific T-cell receptors (TCRs) for antigen. This review distinguishes three developmental modules for T-cell development, which correspond to cell type specification, TCR expression and selection, and the assignment of cells to different effector types. The first is based on transcriptional regulatory network events, the second is dominated by somatic gene rearrangement and mutation and cell selection, and the third corresponds to establishing a poised state of latent regulator priming through an unknown mechanism. Interestingly, in different lineages, the third module can be deployed at variable times relative to the completion of the first two modules. This review focuses on the gene regulatory network and chromatin-based kinetic constraints that determine activities of transcription factors TCF1, GATA3, PU.1, Bcl11b, Runx1, and E proteins in the primary establishment of T-cell identity.

The human naive B cell repertoire contains distinct subclasses for a germline-targeting HIV-1 vaccine immunogen

Traditional vaccine development to prevent some of the worst current pandemic diseases has been unsuccessful so far. Germline-targeting immunogens have potential to prime protective antibodies (Abs) via more targeted immune responses. Success of germline-targeting vaccines in humans will depend on the composition of the human naive B cell repertoire, including the frequencies and affinities of epitope-specific B cells. However, the human naive B cell repertoire remains largely undefined. Assessment of antigen-specific human naive B cells among hundreds of millions of B cells from multiple donors may be used as pre-phase 1 ex vivo human testing to potentially forecast B cell and Ab responses to new vaccine designs. VRC01 is an HIV broadly neutralizing Ab (bnAb) against the envelope CD4-binding site (CD4bs). We characterized naive human B cells recognizing eOD-GT8, a germline-targeting HIV-1 vaccine candidate immunogen designed to prime VRC01-class Abs. Several distinct subclasses of VRC01-class naive B cells were identified, sharing sequence characteristics with inferred precursors of known bnAbs VRC01, VRC23, PCIN63, and N6. Multiple naive B cell clones exactly matched mature VRC01-class bnAb L-CDR3 sequences. Non-VRC01-class B cells were also characterized, revealing recurrent public light chain sequences. Unexpectedly, we also identified naive B cells related to the IOMA-class CD4bs bnAb. These different subclasses within the human repertoire had strong initial affinities (K_D) to the immunogen, up to 13 nM, and represent encouraging indications that multiple independent pathways may exist for vaccine-elicited VRC01-class bnAb development in most individuals. The frequencies of these distinct eOD-GT8 B cell specificities give insights into antigen-specific compositional features of the human naive B cell repertoire and provide actionable information for vaccine design and advancement.

Self-assembling manifolds in single-cell RNA sequencing data

Single-cell RNA sequencing has spurred the development of computational methods that enable researchers to classify cell types, delineate developmental trajectories, and measure molecular responses to external perturbations. Many of these technologies rely on their ability to detect genes whose cell-to-cell variations arise from the biological processes of interest rather than transcriptional or technical noise. However, for datasets in which the biologically relevant differences between cells are subtle, identifying these genes is challenging. We present the self-assembling manifold (SAM) algorithm, an iterative soft feature selection strategy to quantify gene relevance and improve dimensionality reduction. We demonstrate its advantages over other state-of-the-art methods with experimental validation in identifying novel stem cell populations of Schistosoma mansoni, a prevalent parasite that infects hundreds of millions of people. Extending our analysis to a total of 56 datasets, we show that SAM is generalizable and consistently outperforms other methods in a variety of biological and quantitative benchmarks.

scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data

Technical variation in feature measurements, such as gene expression and locus accessibility, is a key challenge of large-scale single-cell genomic datasets. We show that this technical variation in both scRNA-seq and scATAC-seq datasets can be mitigated by analyzing feature detection patterns alone and ignoring feature quantification measurements. This result holds when datasets have low detection noise relative to quantification noise. We demonstrate state-of-the-art performance of detection pattern models using our new framework, scBFA, for both cell type identification and trajectory inference. Performance gains can also be realized in one line of R code in existing pipelines.

Single-cell transcriptomic analysis of tissue-resident memory T cells in human lung cancer

High numbers of tissue-resident memory T (TRM) cells are associated with better clinical outcomes in cancer patients. However, the molecular characteristics that drive their efficient immune response to tumors are poorly understood. Here, single-cell and bulk transcriptomic analysis of TRM and non-TRM cells present in tumor and normal lung tissue from patients with lung cancer revealed that PD-1-expressing TRM cells in tumors were clonally expanded and enriched for transcripts linked to cell proliferation and cytotoxicity when compared with PD-1-expressing non-TRM cells. This feature was more prominent in the TRM cell subset coexpressing PD-1 and TIM-3, and it was validated by functional assays ex vivo and also reflected in their chromatin accessibility profile. This PD-1+TIM-3+ TRM cell subset was enriched in responders to PD-1 inhibitors and in tumors with a greater magnitude of CTL responses. These data highlight that not all CTLs expressing PD-1 are dysfunctional; on the contrary, TRM cells with PD-1 expression were enriched for features suggestive of superior functionality.

Random forest based similarity learning for single cell RNA sequencing data

Motivation

Genome-wide transcriptome sequencing applied to single cells (scRNA-seq) is rapidly becoming an assay of choice across many fields of biological and biomedical research. Scientific objectives often revolve around discovery or characterization of types or sub-types of cells, and therefore, obtaining accurate cell–cell similarities from scRNA-seq data is a critical step in many studies. While rapid advances are being made in the development of tools for scRNA-seq data analysis, few approaches exist that explicitly address this task. Furthermore, abundance and type of noise present in scRNA-seq datasets suggest that application of generic methods, or of methods developed for bulk RNA-seq data, is likely suboptimal.

Results

Here, we present RAFSIL, a random forest based approach to learn cell–cell similarities from scRNA-seq data. RAFSIL implements a two-step procedure, where feature construction geared towards scRNA-seq data is followed by similarity learning. It is designed to be adaptable and expandable, and RAFSIL similarities can be used for typical exploratory data analysis tasks like dimension reduction, visualization and clustering. We show that our approach compares favorably with current methods across a diverse collection of datasets, and that it can be used to detect and highlight unwanted technical variation in scRNA-seq datasets in situations where other methods fail. Overall, RAFSIL implements a flexible approach yielding a useful tool that improves the analysis of scRNA-seq data.

Availability and implementation

The RAFSIL R package is available at www.kostkalab.net/software.html

Supplementary information

Supplementary data are available at Bioinformatics online.

Tissue-specific functions of invariant natural killer T cells

Invariant natural killer T cells (iNKT cells) are an innate-like T cell subset that expresses an invariant T cell receptor (TCR) α-chain and recognizes lipids presented on CD1d. They secrete diverse cytokines and can influence many types of immune responses. Despite having highly similar TCR specificities, iNKT cells differentiate in the thymus into distinct subsets that are analogous to T helper 1 (T_H1), T_H2 and T_H17 cell subsets. Additional iNKT cell subsets that may require peripheral activation have also been described, including one that produces IL-10. In general, iNKT cells are non-circulating, tissue-resident lymphocytes, but the prevalence of different iNKT cell subsets differs markedly between tissues. Here, we summarize the functions of iNKT cells in four tissues in which they are prevalent, namely, the liver, the lungs, adipose tissue and the intestine. Importantly, we explain how local iNKT cell responses at each site contribute to tissue homeostasis and protection from infection but can also contribute to tissue inflammation and damage.

Clustering methods for single-cell RNA-sequencing expression data: performance evaluation with varying sample sizes and cell compositions

A number of specialized clustering methods have been developed so far for the accurate analysis of single-cell RNA-sequencing (scRNA-seq) expression data, and several reports have been published documenting the performance measures of these clustering methods under different conditions. However, to date, there are no available studies regarding the systematic evaluation of the performance measures of the clustering methods taking into consideration the sample size and cell composition of a given scRNA-seq dataset. Herein, a comprehensive performance evaluation study of 11 selected scRNA-seq clustering methods was performed using synthetic datasets with known sample sizes and number of subpopulations, as well as varying levels of transcriptome complexity. The results indicate that the overall performance of the clustering methods under study are highly dependent on the sample size and complexity of the scRNA-seq dataset. In most of the cases, better clustering performances were obtained as the number of cells in a given expression dataset was increased. The findings of this study also highlight the importance of sample size for the successful detection of rare cell subpopulations with an appropriate clustering tool.

Systems Immunology: Learning the Rules of the Immune System

Given the many cell types and molecular components of the human immune system, along with vast variations across individuals, how should we go about developing causal and predictive explanations of immunity? A central strategy in human studies is to leverage natural variation to find relationships among variables, including DNA variants, epigenetic states, immune phenotypes, clinical descriptors, and others. Here, we focus on how natural variation is used to find patterns, infer principles, and develop predictive models for two areas: (a) immune cell activation-how single-cell profiling boosts our ability to discover immune cell types and states-and (b) antigen presentation and recognition-how models can be generated to predict presentation of antigens on MHC molecules and their detection by T cell receptors. These are two examples of a shift in how we find the drivers and targets of immunity, especially in the human system in the context of health and disease.

Transnuclear mice reveal Peyer's patch iNKT cells that regulate B-cell class switching to IgG1

Tissue-resident iNKT cells maintain tissue homeostasis and peripheral surveillance against pathogens; however, studying these cells is challenging due to their low abundance and poor recovery from tissues. We here show that iNKT transnuclear mice, generated by somatic cell nuclear transfer, have increased tissue resident iNKT cells. We examined expression of PLZF, T-bet, and RORγt, as well as cytokine/chemokine profiles, and found that both monoclonal and polyclonal iNKT cells differentiated into functional subsets that faithfully replicated those seen in wild-type mice. We detected iNKT cells from tissues in which they are rare, including adipose, lung, skin-draining lymph nodes, and a previously undescribed population in Peyer's patches (PP). PP-NKT cells produce the majority of the IL-4 in Peyer's patches and provide indirect help for B-cell class switching to IgG1 in both transnuclear and wild-type mice. Oral vaccination with α-galactosylceramide shows enhanced fecal IgG1 titers in iNKT cell-sufficient mice. Transcriptional profiling reveals a unique signature of PP-NKT cells, characterized by tissue residency. We thus define PP-NKT as potentially important for surveillance for mucosal pathogens.

Neutrophils Driving Unconventional T Cells Mediate Resistance against Murine Sarcomas and Selected Human Tumors

Neutrophils are a component of the tumor microenvironment and have been predominantly associated with cancer progression. Using a genetic approach complemented by adoptive transfer, we found that neutrophils are essential for resistance against primary 3-methylcholantrene-induced carcinogenesis. Neutrophils were essential for the activation of an interferon-γ-dependent pathway of immune resistance, associated with polarization of a subset of CD4- CD8- unconventional αβ T cells (UTCαβ). Bulk and single-cell RNA sequencing (scRNA-seq) analyses unveiled the innate-like features and diversity of UTCαβ associated with neutrophil-dependent anti-sarcoma immunity. In selected human tumors, including undifferentiated pleomorphic sarcoma, CSF3R expression, a neutrophil signature and neutrophil infiltration were associated with a type 1 immune response and better clinical outcome. Thus, neutrophils driving UTCαβ polarization and type 1 immunity are essential for resistance against murine sarcomas and selected human tumors.

GPBAR1 Functions as Gatekeeper for Liver NKT Cells and provides Counterregulatory Signals in Mouse Models of Immune-Mediated Hepatitis

BACKGROUND & AIMS

GPBAR1, also known as TGR5, is a G protein-coupled receptor activated by bile acids. Hepatic innate immune cells are involved in the immunopathogenesis of human liver diseases and in several murine hepatitis models. Here, by using genetic and pharmacological approaches, we provide evidence that GPBAR1 ligation attenuates the inflammation in rodent models of hepatitis.

MATERIAL AND METHODS

Hepatitis was induced by concanavalin A (Con A) or α-galactosyl-ceramide (α-GalCer). 6b-Ethyl-3a,7b-dihydroxy-5b-cholan-24-ol (BAR501), a selective agonist of GPBAR1, was administrated by o.s.

RESULTS

In the mouse models of hepatitis, the genetic ablation of Gpabar1 worsened the severity of liver injury and resulted in a type I NKT cells phenotype that was biased toward a NKT1, a proinflammatory, IFN-γ producing, NKT cells subtype. Further on, NKT cells from GPBAR1^-/- mice were sufficient to cause a severe hepatitis when transferred to naïve mice. In contrast, GPBAR1 agonism rescued wild-type mice from acute liver damage and redirects the NKT cells polarization toward a NKT10, a regulatory, IL-10 secreting, type I NKT cell subset. In addition, GPBAR1 agonism significantly expanded the subset of IL-10 secreting type II NKT cells. RNAseq analysis of both NKT cells type confirmed that IL-10 is a major target for GPABR1. Accordingly, IL-10 gene ablation abrogated protection afforded by GPBAR1 agonism in the Con A model.

CONCLUSION

Present results illustrate a role for GPBAR1 in regulating liver NKT ecology. Because NKT cells are an essential component of liver immune system, our data provide a compelling evidence for a GPBAR1-IL-10 axis in regulating of liver immunity.

γδTCR-independent origin of neonatal γδ T cells prewired for IL-17 production

A classical view of T cell lineages consists of two major clades of T cells expressing either the αβ or γδ T cell receptor (TCR). However, genome-wide assessments indicate molecular clusters segregating T cell subsets that are preprogrammed for effector function (innate) from those that mediate conventional adaptive response, regardless of the TCR types. Within this paradigm, γδ T cells remain the prototypic innate-like lymphocytes, many subsets of which are programmed during intrathymic development for committed peripheral tissue localization and effector responses. Emerging evidence for innate γδ T cell lineage choice dictated by developmental gene programs rather than the sensory TCR is discussed in this review.

NKT Cells in Neurological Diseases

Natural killer T (NKT) cells are a unique subset of T lymphocytes with the expression of T cell receptor (TCR) and NK cell lineage receptors. These cells can rapidly release large quantities of cytokines and function as a bridge between innate and adaptive immunity. To date, multiple reports have investigated the role of NKT cells under various pathological conditions, such as cancer, autoimmune disease, and infection. Knowledge about NKT cells in neurological diseases is increasing, albeit limited. Here, we review evidence for the involvement of NKT cells in neurological diseases, and discuss immunotherapeutic potential and future study goals. As the development and function of NKT cells become increasingly well understood, the next few years should yield many new insights into NKT cell function, and mechanistic regulation in neurological disorders.

Generation of a Jurkat-based fluorescent reporter cell line to evaluate lipid antigen interaction with the human iNKT cell receptor

Invariant natural killer T (iNKT) cells are a specialized subset of T cells contributing to both, the innate and adaptive immune responses. In contrast to conventional T lymphocytes they recognize lipid antigens. The aim of the project is to establish a novel model system, to study iNKT-TCR - ligand interaction. An iNKT reporter cell line (JE6-1REP-iNKT) was engineered by introducing the human iNKT-TCR into a human leukemic T cell line carrying an NF-κB-driven fluorescent transcriptional reporter construct. Antigen presenting BWSTIM cells expressing human CD1d and CD80 were generated. Reporter induction in JE6-1REP-iNKT cells was assessed by flow cytometry. CRISPR/Cas9 was used for β2M knock out in JE6-1REP-iNKT cells to abrogate CD1d expression and thus excluding antigen self-presentation. Reporter cells were shown to specifically react with iNKT antigens presented via CD1d. Their sensitivity towards α-GalCer was comparable to a murine iNKT hybridoma cell line. In conclusion, we created a novel iNKT reporter platform which, compared to traditional iNKT cell assays, is characterized by a shorter turnaround time and lower costs. It thus facilitates the identification of antigenic structures that drive the activation of iNKT cells in health and disease.