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

Type 2 and Type 17 Invariant Natural Killer T Cells Contribute to Local Eosinophilic and Neutrophilic Inflammation and Their Function Is Regulated by Mucosal Microenvironment in Nasal Polyps

Chronic rhinosinusitis with nasal polyps (CRSwNP) is characterized by heterogeneous inflammatory endotypes of unknown etiology. Invariant natural killer T (iNKT) cells are multifunctional innate T cells that exhibit Th1-, Th2-, and Th17-like characteristics. We investigated functional relationships between iNKT cells and inflammatory subtypes of CRSwNP. Eighty patients with CRSwNP and thirty-two control subjects were recruited in this study. Flow cytometry was used to analyze the frequencies and functions of iNKT cells and their subsets in peripheral blood mononuclear cells (PBMCs) and tissues. Polyp tissue homogenates were used to study the multifunctionality of iNKT cells. iNKT cells were significantly increased in polyps (0.41%) than in control mucosa (0.12%). iNKT cells were determined in the paucigranunlocytic (n=20), eosinophilic (n=22), neutrophilic (n=23), and mixed granulocytic (n=13) phenotypes of CRSwNP. The percentages of iNKT cells and HLA-DR⁺PD-1⁺ subsets were lower in eosinophilic or mixed granulocytic polyps than those of other phenotypes. iNKT cells and subsets were enriched in polyp tissues than in matched PBMCs. The evaluation of surface markers, transcription factors, and signature cytokines indicated that the frequencies of iNKT2 and iNKT17 subsets were significantly increased in eosinophilic and neutrophilic polyps, respectively, than in the paucigranulocytic group. Moreover, the production of type 2 (partially dependent on IL-7) and type 17 (partially dependent on IL-23) iNKT cells could be stimulated by eosinophilic and neutrophilic homogenates, respectively. Our study revealed that type 2 and type 17 iNKT cells were involved in eosinophilic and neutrophilic inflammation, respectively, in CRSwNP, while different inflammatory microenvironments could modulate the functions of iNKT cells, suggesting a role of iNKT cells in feedback mechanisms and local inflammation.

Deconstructing iNKT cell development at single-cell resolution

Invariant natural killer T (iNKT) cells are increasingly regarded as disease biomarkers and immunotherapeutic targets. However, a greater understanding of their biology is necessary to effectively target these cells in the clinic. The discovery of iNKT1/2/17 cell effector subsets was a milestone in our understanding of iNKT cell development and function. Recent transcriptomic studies have uncovered an even greater heterogeneity and challenge our understanding of iNKT cell ontogeny and effector differentiation. We propose a refined model whereby iNKT cells differentiate through a dynamic and continuous instructive process that requires the accumulation and integration of various signals within the thymus or peripheral tissues. Within this framework, we question the existence of true iNKT2 cells and discuss the parallels between mouse and human iNKT cells.

Differential location of NKT and MAIT cells within lymphoid tissue

Natural Killer T (NKT) cells and Mucosal-Associated Invariant T (MAIT) cells are innate-like T cells that express semi-invariant αβ T cell receptors (TCRs) through which they recognise CD1d and MR1 molecules, respectively, in complex with specific ligands. These cells play important roles in health and disease in many organs, but their precise intra-organ location is not well established. Here, using CD1d and MR1 tetramer staining techniques, we describe the precise location of NKT and MAIT cells in lymphoid and peripheral organs. Within the thymus, NKT cells were concentrated in the medullary side of the corticomedullary junction. In spleen and lymph nodes, NKT cells were mainly localised within T cell zones, although following in vivo activation with the potent NKT-cell ligand α-GalCer, they expanded throughout the spleen. MAIT cells were clearly detectable in Vα19 TCR transgenic mice and were rare but detectable in lymphoid tissue of non-transgenic mice. In contrast to NKT cells, MAIT cells were more closely associated with the B cell zone and red pulp of the spleen. Accordingly, we have provided an extensive analysis of the in situ localisation of NKT and MAIT cells and suggest differences between the intra-organ location of these two cell types.

iNKT: A new avenue for CAR-based cancer immunotherapy

Chimeric antigen receptor (CAR) T cell is a T lymphocyte-based immunotherapy, which achieves great successes in treating blood malignancies and provides new hope to cue advanced cancer patients. Invariant natural killer T (iNKT) cells are a kind of special T lymphocytes characterized by expressing invariant TCR of Vα24Vβ11 to recognize CD1d-presented glycolipid antigens, which bridge innate and adaptive immune responses. iNKT cells themselves show strong anti-tumor effect in tumor models via CD1d-mediated killing of CD1d-positive tumor cells and immunosuppressive TAMs and MDSCs, and are closely related to the prognosis of cancer patients. iNKT cells are not restricted to polymorphic human leukocyte antigen (HLA) and can prevent Graft versus Host Disease (GvHD), which makes it to be an ideal CAR vector for allogeneic therapy. Although CAR-iNKT was developed and verified by several different teams and attracts more and more attentions, many obstacles are still needed to be resolved before obtaining CAR-iNKT therapeutics. In this review, we summarized the current status of clinical application of iNKT cells and the latest achievements of CAR-iNKT cells, which provides new insight in CAR-iNKT development and usages.

Current insights in mouse iNKT and MAIT cell development using single cell transcriptomics data

Innate T (T_inn) cells are a collection of T cells with important regulatory functions that have a crucial role in immunity towards tumors, bacteria, viruses, and in cell-mediated autoimmunity. In mice, the two main αβ T_inn cell subsets include the invariant NKT (iNKT) cells that recognize glycolipid antigens presented by non-polymorphic CD1d molecules and the mucosal associated invariant T (MAIT) cells that recognize vitamin B metabolites presented by the non-polymorphic MR1 molecules. Due to their ability to promptly secrete large quantities of cytokines either after T cell antigen receptor (TCR) activation or upon exposure to tissue- and antigen-presenting cell-derived cytokines, T_inn cells are thought to act as a bridge between the innate and adaptive immune systems and have the ability to shape the overall immune response. Their swift response reflects the early acquisition of helper effector programs during their development in the thymus, independently of pathogen exposure and prior to taking up residence in peripheral tissues. Several studies recently profiled, in an unbiased manner, the transcriptomes of mouse thymic iNKT and MAIT cells at the single cell level. Based on these data, we re-examine in this review how T_inn cells develop in the mouse thymus and undergo effector differentiation.

Stimulation of a subset of natural killer T cells by CD103+ DC is required for GM-CSF and protection from pneumococcal infection

Innate-like T cells, including invariant natural killer T cells, mucosal-associated invariant T cells, and γδ T cells, are present in various barrier tissues, including the lung, where they carry out protective responses during infections. Here, we investigate their roles during pulmonary pneumococcal infection. Following infection, innate-like T cells rapidly increase in lung tissue, in part through recruitment, but T cell antigen receptor activation and cytokine production occur mostly in interleukin-17-producing NKT17 and γδ T cells. NKT17 cells are preferentially located within lung tissue prior to infection, as are CD103⁺ dendritic cells, which are important both for antigen presentation to NKT17 cells and γδ T cell activation. Whereas interleukin-17-producing γδ T cells are numerous, granulocyte-macrophage colony-stimulating factor is exclusive to NKT17 cells and is required for optimal protection. These studies demonstrate how particular cellular interactions and responses of functional subsets of innate-like T cells contribute to protection from pathogenic lung infection.

Longitudinal analysis of invariant natural killer T cell activation reveals a cMAF-associated transcriptional state of NKT10 cells

Innate T cells, including CD1d-restricted invariant natural killer T (iNKT) cells, are characterized by their rapid activation in response to non-peptide antigens, such as lipids. While the transcriptional profiles of naive, effector, and memory adaptive T cells have been well studied, less is known about the transcriptional regulation of different iNKT cell activation states. Here, using single-cell RNA-sequencing, we performed longitudinal profiling of activated murine iNKT cells, generating a transcriptomic atlas of iNKT cell activation states. We found that transcriptional signatures of activation are highly conserved among heterogeneous iNKT cell populations, including NKT1, NKT2, and NKT17 subsets, and human iNKT cells. Strikingly, we found that regulatory iNKT cells, such as adipose iNKT cells, undergo blunted activation and display constitutive enrichment of memory-like cMAF⁺ and KLRG1⁺ populations. Moreover, we identify a conserved cMAF-associated transcriptional network among NKT10 cells, providing novel insights into the biology of regulatory and antigen-experienced iNKT cells.

Modulation of TCR signalling components occurs prior to positive selection and lineage commitment in iNKT cells

iNKT cells play a critical role in controlling the strength and character of adaptive and innate immune responses. Their unique functional characteristics are induced by a transcriptional program initiated by positive selection mediated by CD1d expressed by CD4⁺CD8⁺ (double positive, DP) thymocytes. Here, using a novel Vα14 TCR transgenic strain bearing greatly expanded numbers of CD24^hiCD44^loNKT cells, we examined transcriptional events in four immature thymic iNKT cell subsets. A transcriptional regulatory network approach identified transcriptional changes in proximal components of the TCR signalling cascade in DP NKT cells. Subsequently, positive and negative selection, and lineage commitment, occurred at the transition from DP NKT to CD4 NKT. Thus, this study introduces previously unrecognised steps in early NKT cell development, and separates the events associated with modulation of the T cell signalling cascade prior to changes associated with positive selection and lineage commitment.

Human intestinal and circulating invariant natural killer T cells are cytotoxic against colorectal cancer cells via the perforin-granzyme pathway

Invariant natural killer T (iNKT) cells are lipid-specific T lymphocytes endowed with cytotoxic activities and are thus considered important in antitumor immunity. While several studies have demonstrated iNKT cell cytotoxicity against different tumors, very little is known about their cell-killing activities in human colorectal cancer (CRC). Our aim was to assess whether human iNKT cells are cytotoxic against colon cancer cells and the mechanisms underlying this activity. For this purpose, we generated stable iNKT cell lines from peripheral blood and colon specimens and used NK-92 and peripheral blood natural killer cells as cell-mediated cytotoxicity controls. In vitro cytotoxicity was assessed using a panel of well-characterized human CRC cell lines, and the cellular requirements for iNKT cell cytotoxic functions were evaluated. We demonstrated that both intestinal and circulating iNKT cells were cytotoxic against the entire panel of CRC lines, as well as against freshly isolated patient-derived colonic epithelial cancer cells. Perforin and/or granzyme inhibition impaired iNKT cell cytotoxicity, whereas T-cell receptor (TCR) signaling was a less stringent requirement for efficient killing. This study is the first evidence of tissue-derived iNKT cell cytotoxic activity in humans, as it shows that iNKT cells depend on the perforin-granzyme pathway and both adaptive and innate signal recognition for proper elimination of colon cancer cells.

iNKT subsets differ in their developmental and functional requirements on Foxo1

Invariant natural killer T (iNKT) cells play important roles in regulating immune responses. Based on cytokine profiling and key transcriptional factors, iNKT cells are classified into iNKT1, iNKT2, and iNKT17 subsets. However, whether the development and functions of these subsets are controlled by distinct mechanisms remains unclear. Here, we show that forkhead box protein O1 (Foxo1) promotes differentiation of iNKT1 and iNKT2 cells but not iNKT17 cells because of its distinct contributions to IL7R expression in these subsets. Nuclear Foxo1 is essential for Il7r expression in iNKT1 and iNKT2 cells at early stages of differentiation but is dispensable in iNKT17 cells. RORγt, instead of Foxo1, promotes IL7R expression in iNKT17 cells. Additionally, Foxo1 is required for the effector function of iNKT1 and iNKT2 cells but not iNKT17 cells. Cytoplasmic Foxo1 promotes activation of mTORC1 in iNKT1 and iNKT2 cells through inhibiting TSC1-TSC2 interaction, whereas it is dispensable for mTORC1 activation in iNKT17 cells. iNKT17 cells display distinct metabolic gene expression patterns from iNKT1 and iNKT2 cells that match their different functional requirements on Foxo1. Together, our results demonstrate that iNKT cell subsets differ in their developmental and functional requirements on Foxo1.

Brief homogeneous TCR signals instruct common iNKT progenitors whose effector diversification is characterized by subsequent cytokine signaling

Innate-like T cell populations expressing conserved TCRs play critical roles in immunity through diverse developmentally acquired effector functions. Focusing on the prototypical lineage of invariant natural killer T (iNKT) cells, we sought to dissect the mechanisms and timing of fate decisions and functional effector differentiation. Utilizing induced expression of the semi-invariant NKT cell TCR on double positive thymocytes, an initially highly synchronous wave of iNKT cell development was triggered by brief homogeneous TCR signaling. After reaching a uniform progenitor state characterized by IL-4 production potential and proliferation, effector subsets emerged simultaneously, but then diverged toward different fates. While NKT17 specification was quickly completed, NKT1 cells slowly differentiated and expanded. NKT2 cells resembled maturing progenitors, which gradually diminished in numbers. Thus, iNKT subset diversification occurs in dividing progenitor cells without acute TCR input but utilizes multiple active cytokine signaling pathways. These data imply a two-step model of iNKT effector differentiation.

Identification of liver-specific CD24+ invariant NK T cells with low granzyme B production and high proliferative capacity

Invariant NK T (iNKT) cells are innate-like lymphocytes that can recognize the lipid Ag presented by MHC I like molecule CD1d. Distinct tissue distribution of iNKT cells subsets implies a contribution of these subsets to their related tissue regional immunity. iNKT cells are enriched in liver, an organ with unique immunological properties. Whether liver-specific iNKT cells exist and dedicate to the liver immunity remains elusive. Here, a liver-specific CD24⁺ iNKT subset is shown. Hepatic CD24⁺ iNKT cells show higher levels of proliferation, glucose metabolism, and mTOR activity comparing to CD24^- iNKT cells. Although CD24⁺ iNKT cells and CD24^- iNKT cells in the liver produce similar amounts of cytokines, the hepatic CD24⁺ iNKT cells exhibit lower granzyme B production. These liver-specific CD24⁺ iNKT cells are derived from thymus and differentiate into CD24⁺ iNKT in the liver microenvironment. Moreover, liver microenvironment induces the formation of CD24⁺ conventional T cells as well, and these cells exhibit higher proliferation ability but lower granzyme B production in comparison with CD24^- T cells. The results propose that liver microenvironment might induce the generation of liver-specific iNKT subset that might play an important role in maintaining liver homeostasis.

The immune niche of the liver

The liver is an essential organ that is critical for the removal of toxins, the production of proteins, and the maintenance of metabolic homeostasis. Behind each liver functional unit, termed lobules, hides a heterogeneous, complex, and well-orchestrated system. Despite parenchymal cells being most commonly associated with the liver's primary functionality, it has become clear that it is the immune niche of the liver that plays a central role in maintaining both local and systemic homeostasis by propagating hepatic inflammation and orchestrating its resolution. As such, the immunological processes that are at play in healthy and diseased livers are being investigated thoroughly in order to understand the underpinnings of inflammation and the potential avenues for restoring homeostasis. This review highlights recent advances in our understanding of the immune niche of the liver and provides perspectives for how the implementation of new transcriptomic, multimodal, and spatial technologies can uncover the heterogeneity, plasticity, and location of hepatic immune populations. Findings from these technologies will further our understanding of liver biology and create a new framework for the identification of therapeutic targets.

Invariant natural killer T-cell subsets have diverse graft-versus-host-disease-preventing and antitumor effects

Invariant natural killer T (iNKT) cells are a T-cell subset with potent immunomodulatory properties. Experimental evidence in mice and observational studies in humans indicate that iNKT cells have antitumor potential as well as the ability to suppress acute and chronic graft-versus-host-disease (GVHD). Murine iNKT cells differentiate during thymic development into iNKT1, iNKT2, and iNKT17 sublineages, which differ transcriptomically and epigenomically and have subset-specific developmental requirements. Whether distinct iNKT sublineages also differ in their antitumor effect and their ability to suppress GVHD is currently unknown. In this work, we generated highly purified murine iNKT sublineages, characterized their transcriptomic and epigenomic landscape, and assessed specific functions. We show that iNKT2 and iNKT17, but not iNKT1, cells efficiently suppress T-cell activation in vitro and mitigate murine acute GVHD in vivo. Conversely, we show that iNKT1 cells display the highest antitumor activity against murine B-cell lymphoma cells both in vitro and in vivo. Thus, we report for the first time that iNKT sublineages have distinct and different functions, with iNKT1 cells having the highest antitumor activity and iNKT2 and iNKT17 cells having immune-regulatory properties. These results have important implications for the translation of iNKT cell therapies to the clinic for cancer immunotherapy as well as for the prevention and treatment of GVHD.

Visualization and Analysis of Single cell RNA-seq Data by Maximizing Correntropy based Non-negative Low Rank Representation

The exploration of single cell RNA-sequencing (scRNA-seq) technology generates a new perspective to analyze biological problems. One of the major applications of scRNA-seq data is to discover subtypes of cells by cell clustering. Nevertheless, it is challengeable for traditional methods to handle scRNA-seq data with high level of technical noise and notorious dropouts. To better analyze single cell data, a novel scRNA-seq data analysis model called Maximum correntropy criterion based Non-negative and Low Rank Representation (MccNLRR) is introduced. Specifically, the maximum correntropy criterion, as an effective loss function, is more robust to the high noise and large outliers existed in the data. Moreover, the low rank representation is proven to be a powerful tool for capturing the global and local structures of data. Therefore, some important information, such as the similarity of cells in the subspace, is also extracted by it. Then, an iterative algorithm on the basis of the half-quadratic optimization and alternating direction method is developed to settle the complex optimization problem. Before the experiment, we also analyze the convergence and robustness of MccNLRR. At last, the results of cell clustering, visualization analysis, and gene markers selection on scRNA-seq data reveal that MccNLRR method can distinguish cell subtypes accurately and robustly.

Calcium signals regulate the functional differentiation of thymic iNKT cells

How natural or innate-like lymphocytes generate the capacity to produce IL-4 and other cytokines characteristic of type 2 immunity remains unknown. Invariant natural killer T (iNKT) cells differentiate in the thymus into NKT1, NKT2, and NKT17 subsets, similar to mature, peripheral CD4+ T helper cells. The mechanism for this differentiation was not fully understood. Here, we show that NKT2 cells required higher and prolonged calcium (Ca2+ ) signals and continuing activity of the calcium release-activated calcium (CRAC) channel, than their NKT1 counterparts. The sustained Ca2+ entry via CRAC pathway in NKT2 cells was apparently mediated by ORAI and controlled in part by the large mitochondrial Ca2+ uptake. Unique properties of mitochondria in NKT2 cells, including high activity of oxidative phosphorylation, may regulate mitochondrial Ca2+ buffering in NKT2 cells. In addition, the low Ca2+ extrusion rate may also contribute to the higher Ca2+ level in NKT2 cells. Altogether, we identified ORAI-dependent Ca2+ signaling connected with mitochondria and cellular metabolism, as a central regulatory pathway for the differentiation of NKT2 cells.

Intratumoral follicular regulatory T cells curtail anti-PD-1 treatment efficacy

Immune-checkpoint blockade (ICB) has shown remarkable clinical success in boosting antitumor immunity. However, the breadth of its cellular targets and specific mode of action remain elusive. We find that tumor-infiltrating follicular regulatory T (TFR) cells are prevalent in tumor tissues of several cancer types. They are primarily located within tertiary lymphoid structures and exhibit superior suppressive capacity and in vivo persistence as compared with regulatory T cells, with which they share a clonal and developmental relationship. In syngeneic tumor models, anti-PD-1 treatment increases the number of tumor-infiltrating TFR cells. Both TFR cell deficiency and the depletion of TFR cells with anti-CTLA-4 before anti-PD-1 treatment improve tumor control in mice. Notably, in a cohort of 271 patients with melanoma, treatment with anti-CTLA-4 followed by anti-PD-1 at progression was associated with better a survival outcome than monotherapy with anti-PD-1 or anti-CTLA-4, anti-PD-1 followed by anti-CTLA-4 at progression or concomitant combination therapy.

RFCell: A Gene Selection Approach for scRNA-seq Clustering Based on Permutation and Random Forest

In recent years, the application of single cell RNA-seq (scRNA-seq) has become more and more popular in fields such as biology and medical research. Analyzing scRNA-seq data can discover complex cell populations and infer single-cell trajectories in cell development. Clustering is one of the most important methods to analyze scRNA-seq data. In this paper, we focus on improving scRNA-seq clustering through gene selection, which also reduces the dimensionality of scRNA-seq data. Studies have shown that gene selection for scRNA-seq data can improve clustering accuracy. Therefore, it is important to select genes with cell type specificity. Gene selection not only helps to reduce the dimensionality of scRNA-seq data, but also can improve cell type identification in combination with clustering methods. Here, we proposed RFCell, a supervised gene selection method, which is based on permutation and random forest classification. We first use RFCell and three existing gene selection methods to select gene sets on 10 scRNA-seq data sets. Then, three classical clustering algorithms are used to cluster the cells obtained by these gene selection methods. We found that the gene selection performance of RFCell was better than other gene selection methods.

Prognostic Roles of Phosphofructokinase Platelet in Clear Cell Renal Cell Carcinoma and Correlation with Immune Infiltration

Background

Abnormal expression of phosphofructokinase platelet (PFKP) has been reported in various cancer types. However, the role of PFKP in clear cell renal cell carcinoma (ccRCC) remains unclear.

Methods

In this study, the PFKP expression levels in various cancers were systemically described by integrating multiple kinds of publicly available databases. The relationship between PFKP expression and clinical prognosis of ccRCC patients was analyzed based on the TCGA database. Furthermore, PFKP-related genes and the top 10 hub genes were identified. The enrichment analysis, PPI network, and the relationship between PFKP and tumor-infiltrating immune cells were conducted to explore why PFKP was associated with clinical outcomes in ccRCC patients.

Results

PFKP was significantly highly expressed in kidney cancer, especially in ccRCC. Moreover, patients with low expression of PFKP were correlated with poor 5-year and 10-year overall survival (OS) (P < 0.05). Low PFKP expression was a risk factor associated with decreased OS in subgroups including males, females, grade 3–4, and stage III–IV (all P < 0.05). GO and KEGG enrichment analyses showed that 10 hub genes were mainly enriched in the tumor immune response. Finally, PFKP expression level was highly correlated with the infiltration of B cell, CD8⁺ T cell, CD4⁺ T cell, macrophage, neutrophil, and dendritic cell.

Conclusion

In short, our findings suggested that PFKP is highly expressed in ccRCC significantly and facilitated tumor immune response which in turn associated with a good prognosis.

PLZF Acetylation Levels Regulate NKT Cell Differentiation

The transcription factor promyelocytic leukemia zinc finger (PLZF) is encoded by the BTB domain-containing 16 (Zbtb16) gene. Its repressor function regulates specific transcriptional programs. During the development of invariant NKT cells, PLZF is expressed and directs their effector program, but the detailed mechanisms underlying PLZF regulation of multistage NKT cell developmental program are not well understood. This study investigated the role of acetylation-induced PLZF activation on NKT cell development by analyzing mice expressing a mutant form of PLZF mimicking constitutive acetylation (PLZF^ON) mice. NKT populations in PLZF^ON mice were reduced in proportion and numbers of cells, and the cells present were blocked at the transition from developmental stage 1 to stage 2. NKT cell subset differentiation was also altered, with T-bet⁺ NKT1 and RORγt⁺ NKT17 subsets dramatically reduced and the emergence of a T-bet^-RORγt^- NKT cell subset with features of cells in early developmental stages rather than mature NKT2 cells. Preliminary analysis of DNA methylation patterns suggested that activated PLZF acts on the DNA methylation signature to regulate NKT cells' entry into the early stages of development while repressing maturation. In wild-type NKT cells, deacetylation of PLZF is possible, allowing subsequent NKT cell differentiation. Interestingly, development of other innate lymphoid and myeloid cells that are dependent on PLZF for their generation is not altered in PLZF^ON mice, highlighting lineage-specific regulation. Overall, we propose that specific epigenetic control of PLZF through acetylation levels is required to regulate normal NKT cell differentiation.

Dendritic Cells Require TMEM176A/B Ion Channels for Optimal MHC Class II Antigen Presentation to Naive CD4+ T Cells

Intracellular ion fluxes emerge as critical actors of immunoregulation but still remain poorly explored. In this study, we investigated the role of the redundant cation channels TMEM176A and TMEM176B (TMEM176A/B) in retinoic acid-related orphan receptor γt⁺ cells and conventional dendritic cells (DCs) using germline and conditional double knockout mice. Although Tmem176a/b appeared surprisingly dispensable for the protective function of Th17 and group 3 innate lymphoid cells in the intestinal mucosa, we found that they were required in conventional DCs for optimal Ag processing and presentation to CD4⁺ T cells. Using a real-time imaging method, we show that TMEM176A/B accumulate in dynamic post-Golgi vesicles preferentially linked to the late endolysosomal system and strongly colocalize with HLA-DM. Taken together, our results suggest that TMEM176A/B ion channels play a direct role in the MHC class II compartment of DCs for the fine regulation of Ag presentation and naive CD4⁺ T cell priming.

Similarity and Dissimilarity Regularized Nonnegative Matrix Factorization for Single-Cell RNA-seq Analysis

In traditional sequencing techniques, the different functions of cells and the different roles they play in differentiation are often ignored. With the advancement of single-cell RNA sequencing (scRNA-seq) techniques, scientists can measure the gene expression value at the single-cell level, and it is helping to understand the heterogeneity hidden in cells. One of the most powerful ways to find heterogeneity is using the unsupervised clustering method to get separate subpopulations. In this paper, we propose a novel clustering method Similarity and Dissimilarity Regularized Nonnegative Matrix Factorization (SDCNMF) that simultaneously impose similarity and dissimilarity constraints on low-dimensional representations. SDCNMF both considers the similarity of closer cells and the dissimilarity of cells that are farther away. It can not only keep the similar cells getting closer in low-dimensional space, but also can push the dissimilar cells away from each other. We test the validity of our proposed method on five scRNA-seq datasets. Clustering results show that SDCNMF is better than other comparative methods, and the gene markers we find are also consistent with previous studies. Therefore, we can conclude that SDCNMF is effective in scRNA-seq data analysis. This paper proposes a novel clustering method Similarity and Dissimilarity Regularized Nonnegative Matrix Factorization (SDCNMF) that simultaneously impose similarity and dissimilarity constraints on low-dimensional representations. SDCNMF both considers the similarity of closer cells and the dissimilarity of cells that are farther away. It can not only keep the similar cells getting closer in low-dimensional space, but also can push the dissimilar cells away from each other. Clustering results show that SDCNMF is better than other comparative methods, and the gene markers we find are also consistent with previous studies.

Integrative Single-Cell Transcriptomic Analysis of Human Fetal Thymocyte Development

Intrathymic differentiation of T lymphocytes begins as early as intrauterine stage, yet the T cell lineage decisions of human fetal thymocytes at different gestational ages are not currently understood. Here, we performed integrative single-cell analyses of thymocytes across gestational ages. We identified conserved candidates underlying the selection of T cell receptor (TCR) lineages in different human fetal stages. The trajectory of early thymocyte commitment during fetal growth was also characterized. Comparisons with mouse data revealed conserved and species-specific transcriptional dynamics of thymocyte proliferation, apoptosis and selection. Genome-wide association study (GWAS) data associated with multiple autoimmune disorders were analyzed to characterize susceptibility genes that are highly expressed at specific stages during fetal thymocyte development. In summary, our integrative map describes previously underappreciated aspects of human thymocyte development, and provides a comprehensive reference for understanding T cell lymphopoiesis in a self-tolerant and functional adaptive immune system.

Reduced dose of PTCy followed by adjuvant α-galactosylceramide enhances GVL effect without sacrificing GVHD suppression

Posttransplantation cyclophosphamide (PTCy) has become a popular option for haploidentical hematopoietic stem cell transplantation (HSCT). However, personalized methods to adjust immune intensity after PTCy for each patient’s condition have not been well studied. Here, we investigated the effects of reducing the dose of PTCy followed by α-galactosylceramide (α-GC), a ligand of iNKT cells, on the reciprocal balance between graft-versus-host disease (GVHD) and the graft-versus-leukemia (GVL) effect. In a murine haploidentical HSCT model, insufficient GVHD prevention after reduced-dose PTCy was efficiently compensated for by multiple administrations of α-GC. The ligand treatment maintained the enhanced GVL effect after reduced-dose PTCy. Phenotypic analyses revealed that donor-derived B cells presented the ligand and induced preferential skewing to the NKT2 phenotype rather than the NKT1 phenotype, which was followed by the early recovery of all T cell subsets, especially CD4⁺Foxp3⁺ regulatory T cells. These studies indicate that α-GC administration soon after reduced-dose PTCy restores GVHD-preventing activity and maintains the GVL effect, which is enhanced by reducing the dose of PTCy. Our results provide important information for the development of a novel strategy to optimize PTCy-based transplantation, particularly in patients with a potential relapse risk.

Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data based on Non-negative Matrix Factorization

The development of single-cell RNA sequencing (scRNA-seq) technology has made it possible to measure gene expression levels at the resolution of a single cell, which further reveals the complex growth processes of cells such as mutation and differentiation. Recognizing cell heterogeneity is one of the most critical tasks in scRNA-seq research. To solve it, we propose a non-negative matrix factorization framework based on multi-subspace cell similarity learning for unsupervised scRNA-seq data analysis (MscNMF). MscNMF includes three parts: data decomposition, similarity learning, and similarity fusion. The three work together to complete the data similarity learning task. MscNMF can learn the gene features and cell features of different subspaces, and the correlation and heterogeneity between cells will be more prominent in multi-subspaces. The redundant information and noise in each low-dimensional feature space are eliminated, and its gene weight information can be further analyzed to calculate the optimal number of subpopulations. The final cell similarity learning will be more satisfactory due to the fusion of cell similarity information in different subspaces. The advantage of MscNMF is that it can calculate the number of cell types and the rank of Non-negative matrix factorization (NMF) reasonably. Experiments on seven real scRNA-seq datasets show that MscNMF can effectively perform clustering tasks and extract useful genetic markers. To verify its clustering performance, the framework is compared with other latest clustering algorithms and satisfactory results are obtained. The code of MscNMF is free available for academic https://github.com/wangchuanyuan1/project-MscNMF).

REBET: a method to determine the number of cell clusters based on batch effect removal

In single-cell RNA-seq (scRNA-seq) data analysis, a fundamental problem is to determine the number of cell clusters based on the gene expression profiles. However, the performance of current methods is still far from satisfactory, presumably due to their limitations in capturing the expression variability among cell clusters. Batch effects represent the undesired variability between data measured in different batches. When data are obtained from different labs or protocols batch effects occur. Motivated by the practice of batch effect removal, we considered cell clusters as batches. We hypothesized that the number of cell clusters (i.e. batches) could be correctly determined if the variances among clusters (i.e. batch effects) were removed. We developed a new method, namely, removal of batch effect and testing (REBET), for determining the number of cell clusters. In this method, cells are first partitioned into k clusters. Second, the batch effects among these k clusters are then removed. Third, the quality of batch effect removal is evaluated with the average range of normalized mutual information (ARNMI), which measures how uniformly the cells with batch-effects-removal are mixed. By testing a range of k values, the k value that corresponds to the lowest ARNMI is determined to be the optimal number of clusters. We compared REBET with state-of-the-art methods on 32 simulated datasets and 14 published scRNA-seq datasets. The results show that REBET can accurately and robustly estimate the number of cell clusters and outperform existing methods. Contact: H.D.L. (hongdong@csu.edu.cn) or Q.S.X. (qsxu@csu.edu.cn).

Single cell analysis of host response to helminth infection reveals the clonal breadth, heterogeneity, and tissue-specific programming of the responding CD4+ T cell repertoire

The CD4⁺ T cell response is critical to host protection against helminth infection. How this response varies across different hosts and tissues remains an important gap in our understanding. Using IL-4-reporter mice to identify responding CD4⁺ T cells to Nippostrongylus brasiliensis infection, T cell receptor sequencing paired with novel clustering algorithms revealed a broadly reactive and clonally diverse CD4⁺ T cell response. While the most prevalent clones and clonotypes exhibited some tissue selectivity, most were observed to reside in both the lung and lung-draining lymph nodes. Antigen-reactivity of the broader repertoires was predicted to be shared across both tissues and individual mice. Transcriptome, trajectory, and chromatin accessibility analysis of lung and lymph-node repertoires revealed three unique but related populations of responding IL-4⁺ CD4⁺ T cells consistent with T follicular helper, T helper 2, and a transitional population sharing similarity with both populations. The shared antigen reactivity of lymph node and lung repertoires combined with the adoption of tissue-specific gene programs allows for the pairing of cellular and humoral responses critical to the orchestration of anti-helminth immunity.

Using various “omic” approaches, the CD4⁺ T cell receptor (TCR) repertoire was explored after primary helminth infection. Infection generated a broadly reactive and clonally diverse CD4⁺ T cell response with the most prevalent clonotypes and predicted antigen specificities residing in both the lung and lung-draining lymph nodes. Tissue-specific programming of responding CD4⁺ T cells directed the establishment of committed Tfh and Th2 cells, both critical for driving distinct hallmarks of type-2 inflammation. These datasets help to explore the diverse yet tissue-specific nature of anti-helminth immunity.

Adaptive Total-Variation Regularized Low-Rank Representation for Analyzing Single-Cell RNA-seq Data

High-throughput sequencing of single-cell gene expression reveals a complex mechanism of individual cell's heterogeneity in a population. An important purpose for analyzing single-cell RNA sequencing (scRNA-seq) data is to identify cell subtypes and functions by cell clustering. To deal with high levels of noise and cellular heterogeneity, we introduced a new single cell data analysis model called Adaptive Total-Variation Regularized Low-Rank Representation (ATV-LRR). In scRNA-seq data, ATV-LRR can reconstruct the low-rank subspace structure to learn the similarity of cells. The low-rank representation can not only segment multiple linear subspaces, but also extract important information. Moreover, adaptive total variation also can remove cell noise and preserve cell feature details by learning the gradient information of the data. At the same time, to analyze scRNA-seq data with unknown prior information, we introduced the maximum eigenvalue method into the ATV-LRR model to automatically identify cell populations. The final clustering results show that the ATV-LRR model can detect cell types more effectively and stably.

High Dimensional Single-Cell Analysis Reveals iNKT Cell Developmental Trajectories and Effector Fate Decision

CD1d-restricted invariant Natural Killer T (iNKT) cells represent a unique class of T lymphocytes endowed with potent regulatory and effector immune functions. Although these functions are acquired during thymic ontogeny, the sequence of events that gives rise to discrete effector subsets remains unclear. Using an unbiased single-cell transcriptomic analysis combined with functional assays, we reveal an unappreciated diversity among thymic iNKT cells, especially among iNKT1 cells. Mathematical modeling and biological methods unravel a developmental map whereby iNKT2 cells constitute a transient branching point toward the generation of iNKT1 and iNKT17 cells, which reconciles the two previously proposed models. In addition, we identify the transcription co-factor Four-and-a-half LIM domains protein 2 (FHL2) as a critical cell-intrinsic regulator of iNKT1 specification. Thus, these data illustrate the changing transcriptional network that guides iNKT cell effector fate.

Chromatin assembly factor 1B critically controls the early development but not function acquisition of invariant natural killer T cells in mice

CD4⁺ CD8⁺ double-positive thymocytes give rise to both conventional TCRαβ⁺ T cells and invariant natural killer T cells (iNKT cells), but these two kinds of cells display different characteristics. The molecular mechanism underlying iNKT cell lineage development and function acquisition remain to be elucidated. We show that the loss of chromatin assembly factor 1B (CHAF1b) maintains the normal development of conventional TCRαβ⁺ T cells but severely impairs early development of iNKT cells. This dysregulation is accompanied by the impairment in chromatin activation and gene transcription at Vα14-Jα18 locus. Notably, ectopic expression of a Vα14-Jα18 TCR rescues Chaf1b-deficient iNKT cell developmental defects. Moreover, cytokine secretion and antitumor activity are substantially maintained in Vα14-Jα18 TCR transgene-rescued Chaf1b-deficient iNKT cells. Our study identifies CHAF1b as a critical factor that controls the early development but not function acquisition of iNKT cells via lineage- and stage-specific regulation.

PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data

To investigate molecular mechanisms underlying cell state changes, a crucial analysis is to identify differentially expressed (DE) genes along the pseudotime inferred from single-cell RNA-sequencing data. However, existing methods do not account for pseudotime inference uncertainty, and they have either ill-posed p-values or restrictive models. Here we propose PseudotimeDE, a DE gene identification method that adapts to various pseudotime inference methods, accounts for pseudotime inference uncertainty, and outputs well-calibrated p-values. Comprehensive simulations and real-data applications verify that PseudotimeDE outperforms existing methods in false discovery rate control and power.

A fetal wave of human type 3 effector γδ cells with restricted TCR diversity persists into adulthood

Accumulating evidence suggests that the mouse embryonic thymus produces distinct waves of innate effector γδ T cells. However, it is unclear whether this process occurs similarly in humans and whether it comprises a dedicated subset of innate-like type 3 effector γδ T cells. Here, we present a protocol for high-throughput sequencing of TRG and TRD pairs that comprise the clonal γδTCR. In combination with single-cell RNA sequencing, multiparameter flow cytometry, and TCR sequencing, we reveal a high heterogeneity of γδ T cells sorted from neonatal and adult blood that correlated with TCR usage. Immature γδ T cell clusters displayed mixed and diverse TCRs, but effector cell types segregated according to the expression of either highly expanded individual Vδ1⁺ TCRs or moderately expanded semi-invariant Vγ9Vδ2⁺ TCRs. The Vγ9Vδ2⁺ T cells shared expression of genes that mark innate-like T cells, including ZBTB16 (encoding PLZF), KLRB1, and KLRC1, but consisted of distinct clusters with unrelated Vγ9Vδ2⁺ TCR clones characterized either by TBX21, FCGR3A, and cytotoxicity-associated gene expression (type 1) or by CCR6, RORC, IL23R, and DPP4 expression (type 3). Effector γδ T cells with type 1 and type 3 innate T cell signatures were detected in a public dataset of early embryonic thymus organogenesis. Together, this study suggests that functionally distinct waves of human innate-like effector γδ T cells with semi-invariant Vγ9Vδ2⁺ TCR develop in the early fetal thymus and persist into adulthood.

Classical MHC expression by DP thymocytes impairs the selection of non-classical MHC restricted innate-like T cells

Conventional T cells are selected by peptide-MHC expressed by cortical epithelial cells in the thymus, and not by cortical thymocytes themselves that do not express MHC I or MHC II. Instead, cortical thymocytes express non-peptide presenting MHC molecules like CD1d and MR1, and promote the selection of PLZF⁺ iNKT and MAIT cells, respectively. Here, we report an inducible class-I transactivator mouse that enables the expression of peptide presenting MHC I molecules in different cell types. We show that MHC I expression in DP thymocytes leads to expansion of peptide specific PLZF⁺ innate-like (PIL) T cells. Akin to iNKT cells, PIL T cells differentiate into three functional effector subsets in the thymus, and are dependent on SAP signaling. We demonstrate that PIL and NKT cells compete for a narrow niche, suggesting that the absence of peptide-MHC on DP thymocytes facilitates selection of non-peptide specific lymphocytes.

Multi-Dimensional Gene Regulation in Innate and Adaptive Lymphocytes: A View From Regulomes

The precise control of cytokine production by innate lymphoid cells (ILCs) and their T cell adaptive system counterparts is critical to mounting a proper host defense immune response without inducing collateral damage and autoimmunity. Unlike T cells that differentiate into functionally divergent subsets upon antigen recognition, ILCs are developmentally programmed to rapidly respond to environmental signals in a polarized manner, without the need of T cell receptor (TCR) signaling. The specification of cytokine production relies on dynamic regulation of cis-regulatory elements that involve multi-dimensional epigenetic mechanisms, including DNA methylation, transcription factor binding, histone modification and DNA-DNA interactions that form chromatin loops. How these different layers of gene regulation coordinate with each other to fine tune cytokine production, and whether ILCs and their T cell analogs utilize the same regulatory strategy, remain largely unknown. Herein, we review the molecular mechanisms that underlie cell identity and functionality of helper T cells and ILCs, focusing on networks of transcription factors and cis-regulatory elements. We discuss how higher-order chromatin architecture orchestrates these components to construct lineage- and state-specific regulomes that support ordered immunoregulation.

Transcriptome and chromatin landscape of iNKT cells are shaped by subset differentiation and antigen exposure

Invariant natural killer T cells (iNKT cells) differentiate into thymic and peripheral NKT1, NKT2 and NKT17 subsets. Here we use RNA-seq and ATAC-seq analyses and show iNKT subsets are similar, regardless of tissue location. Lung iNKT cell subsets possess the most distinct location-specific features, shared with other innate lymphocytes in the lung, possibly consistent with increased activation. Following antigenic stimulation, iNKT cells undergo chromatin and transcriptional changes delineating two populations: one similar to follicular helper T cells and the other NK or effector like. Phenotypic analysis indicates these changes are observed long-term, suggesting that iNKT cells gene programs are not fixed, but they are capable of chromatin remodeling after antigen to give rise to additional subsets.

Invariant natural killer T cells are known to be composed of a number of phenotypic and functionally distinct populations. Here the authors use transcriptomic and epigenomic analysis to further characterize the peripheral iNKT compartment before and after antigenic stimulation.

SSRE: Cell Type Detection Based on Sparse Subspace Representation and Similarity Enhancement

Accurate identification of cell types from single-cell RNA sequencing (scRNA-seq) data plays a critical role in a variety of scRNA-seq analysis studies. This task corresponds to solving an unsupervised clustering problem, in which the similarity measurement between cells affects the result significantly. Although many approaches for cell type identification have been proposed, the accuracy still needs to be improved. In this study, we proposed a novel single-cell clustering framework based on similarity learning, called SSRE. SSRE models the relationships between cells based on subspace assumption, and generates a sparse representation of the cell-to-cell similarity. The sparse representation retains the most similar neighbors for each cell. Besides, three classical pairwise similarities are incorporated with a gene selection and enhancement strategy to further improve the effectiveness of SSRE. Tested on ten real scRNA-seq datasets and five simulated datasets, SSRE achieved the superior performance in most cases compared to several state-of-the-art single-cell clustering methods. In addition, SSRE can be extended to visualization of scRNA-seq data and identification of differentially expressed genes. The matlab and python implementations of SSRE are available at https://github.com/CSUBioGroup/SSRE.

Single-cell transcriptomic analysis of allergen-specific T cells in allergy and asthma

CD4⁺ T helper (T_H) cells and regulatory T (T_reg) cells that respond to common allergens play an important role in driving and dampening airway inflammation in patients with asthma. Until recently, direct, unbiased molecular analysis of allergen-reactive T_H and T_reg cells has not been possible. To better understand the diversity of these T cell subsets in allergy and asthma, we analyzed the single-cell transcriptome of ~50,000 house dust mite (HDM) allergen-reactive T_H cells and T_reg cells from asthmatics with HDM allergy and from three control groups: asthmatics without HDM allergy and nonasthmatics with and without HDM allergy. Our analyses show that HDM allergen-reactive T_H and T_reg cells are highly heterogeneous and certain subsets are quantitatively and qualitatively different in individuals with HDM-reactive asthma. The number of interleukin-9 (IL-9)-expressing HDM-reactive T_H cells is greater in asthmatics with HDM allergy compared with nonasthmatics with HDM allergy, and this IL-9-expressing T_H subset displays enhanced pathogenic properties. More HDM-reactive T_H and T_reg cells expressing the interferon response signature (T_HIFNR and T_regIFNR) are present in asthmatics without HDM allergy compared with those with HDM allergy. In cells from these subsets (T_HIFNR and T_regIFNR), expression of TNFSF10 was enriched; its product, tumor necrosis factor-related apoptosis-inducing ligand, dampens activation of T_H cells. These findings suggest that the T_HIFNR and T_regIFNR subsets may dampen allergic responses, which may help explain why only some people develop T_H2 responses to nearly ubiquitous allergens.

Intravital imaging of interactions between iNKT and kupffer cells to clear free lipids during steatohepatitis

Rationale: Invariant natural killer T (iNKT) cells and Kupffer cells represent major hepatic populations of innate immune cells. However, their roles in steatohepatitis remain poorly understood. To elucidate their functions in steatohepatitis development, real-time, in vivo analysis is necessary to understand the pathophysiological events in the dynamic interactions between them during diet-induced steatohepatitis.

Methods: We used a steatohepatitis animal model induced by a methionine-choline-deficient (MCD) diet. Multi-photon confocal live imaging and conventional experimental techniques were employed to investigate the hepatic pathological microenvironment of iNKT and Kupffer cells, interactions between them, and the biological effects of these interactions in steatohepatitis.

Results: We found that iNKT cells were recruited and aggregated into small clusters and interacted dynamically with Kupffer cells in the early stage of steatohepatitis. Most significantly, the iNKT cells in the cluster cleared free lipids released by necrotic hepatocytes and presented a non-classical activation state with high IFN-γ expression. Furthermore, the Kupffer cells in the cell cluster were polarized to type M1. The transcriptome sequencing of iNKT cells showed upregulation of genes related to phagocytosis and lipid processing. Adoptive transfer of iNKT cells to Jα18^-/- mice showed that iNKT and Kupffer cell clusters were essential for balancing the liver and peripheral lipid levels and inhibiting liver fibrosis development.

Conclusions: Our study identified an essential role for dynamic interactions between iNKT cells and Kupffer cells in promoting lipid phagocytosis and clearance by iNKT cells during early liver steatohepatitis. Therefore, modulating iNKT cells is a potential therapeutic strategy for early steatohepatitis.

Investigating the Dynamic Changes in iNKT Cell Metabolic Profiles During Development

Emerging research has highlighted the importance of metabolic pathways and metabolites in dictating immune cell lineage decisions during thymocyte development. Here, we discuss several complementary approaches, including flow cytometry, metabolic flux, and transcriptome analyses, to characterize the dynamic changes in metabolic profiles associated with invariant natural killer T cell development.

Natural Killer T Lymphocytes Integrate Innate Sensory Information and Relay Context to Effector Immune Responses

It is now appreciated that a group of lymphoid lineage cells, collectively called innate-like effector lymphocytes, have evolved to integrate information relayed by the innate sensory immune system about the state of the local tissue environment and to pass on this context to downstream effector innate and adaptive immune responses. Thereby, innate functions engrained into such innate-like lymphoid lineage cells during development can control the quality and magnitude of an immune response to a tissue-altering pathogen and facilitate the formation of memory engrams within the immune system. These goals are accomplished by the innate lymphoid cells that lack antigen-specific receptors, γδ T cell receptor (TCR)-expressing T cells, and several αβ TCR-expressing T cell subsets-such as natural killer T cells, mucosal-associated invariant T cells, et cetera. Whilst we briefly consider the commonalities in the origins and functions of these diverse lymphoid subsets to provide context, the primary topic of this review is to discuss how the semi-invariant natural killer T cells got this way in evolution through lineage commitment and onward ontogeny. What emerges from this discourse is the question: Has a "limbic immune system" emerged (screaming quietly in plain sight!) out of what has been dubbed "in-betweeners"?

MAIT cell development in mice and humans

MAIT cells arise in the thymus following rearrangement of a T cell receptor (TCR) reactive against microbial vitamin B2-derived metabolites presented by the MHC-Ib molecule, MR1. Mechanisms that are conserved in mammals ensure the frequent production of MR1-restricted TCRs and the intra-thymic differentiation of MR1-restricted thymocytes into effector cells. Upon thymic egress and migration into non-lymphoid tissues, additional signals modulate MAIT cell functions according to each local tissue environment. Here, we review the recent progress made towards a better understanding of the establishment of this major immune cell subset.

Thymic iNKT single cell analyses unmask the common developmental program of mouse innate T cells

Most T lymphocytes leave the thymus as naïve cells with limited functionality. However, unique populations of innate-like T cells differentiate into functionally distinct effector subsets during their development in the thymus. Here, we profiled >10,000 differentiating thymic invariant natural killer T (iNKT) cells using single-cell RNA sequencing to produce a comprehensive transcriptional landscape that highlights their maturation, function, and fate decisions at homeostasis. Our results reveal transcriptional profiles that are broadly shared between iNKT and mucosal-associated invariant T (MAIT) cells, illustrating a common core developmental program. We further unmask a mutual requirement for Hivep3, a zinc finger transcription factor and adapter protein. Hivep3 is expressed in early precursors and regulates the post-selection proliferative burst, differentiation and functions of iNKT cells. Altogether, our results highlight the common requirements for the development of innate-like T cells with a focus on how Hivep3 impacts the maturation of these lymphocytes.

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.