Stem-like intestinal Th17 cells give rise to pathogenic effector T cells during autoimmunity.

While intestinal Th17 cells are critical for maintaining tissue homeostasis, recent studies have implicated their roles in the development of extra-intestinal autoimmune diseases including multiple sclerosis. However, the mechanisms by which tissue Th17 cells mediate these dichotomous functions remain unknown. Here, we characterized the heterogeneity, plasticity, and migratory phenotypes of tissue Th17 cells in vivo by combined fate mapping with profiling of the transcriptomes and TCR clonotypes of over 84,000 Th17 cells at homeostasis and during CNS autoimmune inflammation. Inter- and intra-organ single-cell analyses revealed a homeostatic, stem-like TCF1+ IL-17+ SLAMF6+ population that traffics to the intestine where it is maintained by the microbiota, providing a ready reservoir for the IL-23-driven generation of encephalitogenic GM-CSF+ IFN-γ+ CXCR6+ T cells. Our study defines a direct in vivo relationship between IL-17+ non-pathogenic and GM-CSF+ and IFN-γ+ pathogenic Th17 populations and provides a mechanism by which homeostatic intestinal Th17 cells direct extra-intestinal autoimmune disease.

Blockade of IL-22 signaling reverses erythroid dysfunction in stress-induced anemias.

Patients with myelodysplastic syndromes (MDSs) display severe anemia but the mechanisms underlying this phenotype are incompletely understood. Right open-reading-frame kinase 2 (RIOK2) encodes a protein kinase located at 5q15, a region frequently lost in patients with MDS del(5q). Here we show that hematopoietic cell-specific haploinsufficient deletion of Riok2 (Riok2f/+Vav1cre) led to reduced erythroid precursor frequency leading to anemia. Proteomic analysis of Riok2f/+Vav1cre erythroid precursors suggested immune system activation, and transcriptomic analysis revealed an increase in p53-dependent interleukin (IL)-22 in Riok2f/+Vav1cre CD4+ T cells (TH22). Further, we discovered that the IL-22 receptor, IL-22RA1, was unexpectedly present on erythroid precursors. Blockade of IL-22 signaling alleviated anemia not only in Riok2f/+Vav1cre mice but also in wild-type mice. Serum concentrations of IL-22 were increased in the subset of patients with del(5q) MDS as well as patients with anemia secondary to chronic kidney disease. This work reveals a possible therapeutic opportunity for reversing many stress-induced anemias by targeting IL-22 signaling.

A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells.

Reversing the dysfunctional T cell state that arises in cancer and chronic viral infections is the focus of therapeutic interventions; however, current therapies are effective in only some patients and some tumor types. To gain a deeper molecular understanding of the dysfunctional T cell state, we analyzed population and single-cell RNA profiles of CD8(+) tumor-infiltrating lymphocytes (TILs) and used genetic perturbations to identify a distinct gene module for T cell dysfunction that can be uncoupled from T cell activation. This distinct dysfunction module is downstream of intracellular metallothioneins that regulate zinc metabolism and can be identified at single-cell resolution. We further identify Gata-3, a zinc-finger transcription factor in the dysfunctional module, as a regulator of dysfunction, and we use CRISPR-Cas9 genome editing to show that it drives a dysfunctional phenotype in CD8(+) TILs. Our results open novel avenues for targeting dysfunctional T cell states while leaving activation programs intact.

Endogenous Glucocorticoid Signaling Regulates CD8+ T Cell Differentiation and Development of Dysfunction in the Tumor Microenvironment.

Identifying signals in the tumor microenvironment (TME) that shape CD8+ T cell phenotype can inform novel therapeutic approaches for cancer. Here, we identified a gradient of increasing glucocorticoid receptor (GR) expression and signaling from naïve to dysfunctional CD8+ tumor-infiltrating lymphocytes (TILs). Conditional deletion of the GR in CD8+ TILs improved effector differentiation, reduced expression of the transcription factor TCF-1, and inhibited the dysfunctional phenotype, culminating in tumor growth inhibition. GR signaling transactivated the expression of multiple checkpoint receptors and promoted the induction of dysfunction-associated genes upon T cell activation. In the TME, monocyte-macrophage lineage cells produced glucocorticoids and genetic ablation of steroidogenesis in these cells as well as localized pharmacologic inhibition of glucocorticoid biosynthesis improved tumor growth control. Active glucocorticoid signaling associated with failure to respond to checkpoint blockade in both preclinical models and melanoma patients. Thus, endogenous steroid hormone signaling in CD8+ TILs promotes dysfunction, with important implications for cancer immunotherapy.

Induction and transcriptional regulation of the co-inhibitory gene module in T cells.

The expression of co-inhibitory receptors, such as CTLA-4 and PD-1, on effector T cells is a key mechanism for ensuring immune homeostasis. Dysregulated expression of co-inhibitory receptors on CD4+ T cells promotes autoimmunity, whereas sustained overexpression on CD8+ T cells promotes T cell dysfunction or exhaustion, leading to impaired ability to clear chronic viral infections and diseases such as cancer1,2. Here, using RNA and protein expression profiling at single-cell resolution in mouse cells, we identify a module of co-inhibitory receptors that includes not only several known co-inhibitory receptors (PD-1, TIM-3, LAG-3 and TIGIT) but also many new surface receptors. We functionally validated two new co-inhibitory receptors, activated protein C receptor (PROCR) and podoplanin (PDPN). The module of co-inhibitory receptors is co-expressed in both CD4+ and CD8+ T cells and is part of a larger co-inhibitory gene program that is shared by non-responsive T cells in several physiological contexts and is driven by the immunoregulatory cytokine IL-27. Computational analysis identified the transcription factors PRDM1 and c-MAF as cooperative regulators of the co-inhibitory module, and this was validated experimentally. This molecular circuit underlies the co-expression of co-inhibitory receptors in T cells and identifies regulators of T cell function with the potential to control autoimmunity and tumour immunity.

A bilateral tumor model identifies transcriptional programs associated with patient response to immune checkpoint blockade.

Immune checkpoint blockade (ICB) is efficacious in many diverse cancer types, but not all patients respond. It is important to understand the mechanisms driving resistance to these treatments and to identify predictive biomarkers of response to provide best treatment options for all patients. Here we introduce a resection and response-assessment approach for studying the tumor microenvironment before or shortly after treatment initiation to identify predictive biomarkers differentiating responders from nonresponders. Our approach builds on a bilateral tumor implantation technique in a murine metastatic breast cancer model (E0771) coupled with anti-PD-1 therapy. Using our model, we show that tumors from mice responding to ICB therapy had significantly higher CD8+ T cells and fewer Gr1+CD11b+ myeloid-derived suppressor cells (MDSCs) at early time points following therapy initiation. RNA sequencing on the intratumoral CD8+ T cells identified the presence of T cell exhaustion pathways in nonresponding tumors and T cell activation in responding tumors. Strikingly, we showed that our derived response and resistance signatures significantly segregate patients by survival and associate with patient response to ICB. Furthermore, we identified decreased expression of CXCR3 in nonresponding mice and showed that tumors grown in Cxcr3-/- mice had an elevated resistance rate to anti-PD-1 treatment. Our findings suggest that the resection and response tumor model can be used to identify response and resistance biomarkers to ICB therapy and guide the use of combination therapy to further boost the antitumor efficacy of ICB.

Combinatorial prediction of marker panels from single-cell transcriptomic data.

Single-cell transcriptomic studies are identifying novel cell populations with exciting functional roles in various in vivo contexts, but identification of succinct gene marker panels for such populations remains a challenge. In this work, we introduce COMET, a computational framework for the identification of candidate marker panels consisting of one or more genes for cell populations of interest identified with single-cell RNA-seq data. We show that COMET outperforms other methods for the identification of single-gene panels and enables, for the first time, prediction of multi-gene marker panels ranked by relevance. Staining by flow cytometry assay confirmed the accuracy of COMET's predictions in identifying marker panels for cellular subtypes, at both the single- and multi-gene levels, validating COMET's applicability and accuracy in predicting favorable marker panels from transcriptomic input. COMET is a general non-parametric statistical framework and can be used as-is on various high-throughput datasets in addition to single-cell RNA-sequencing data. COMET is available for use via a web interface (http://www.cometsc.com/) or a stand-alone software package (https://github.com/MSingerLab/COMETSC).

Molecular Dissection of CD8+ T-Cell Dysfunction.

Chronic viral infections and cancer often lead to the emergence of dysfunctional or 'exhausted' CD8+ T cells, and the restoration of their functions is currently the focus of therapeutic interventions. In this review, we detail recent advances in the annotation of the gene modules and the epigenetic landscape associated with T-cell dysfunction. Together with analysis of single-cell transcriptomes, these findings have enabled a deeper and more precise understanding of the transcriptional mechanisms that induce and maintain the dysfunctional state and highlight the heterogeneity of CD8+ T-cell phenotypes present in chronically inflamed tissue. We discuss the relevance of these findings for understanding the transcriptional and spatial regulation of dysfunctional T cells and for the design of therapeutics.

Effect of IL-7 Therapy on Phospho-Ribosomal Protein S6 and TRAF1 Expression in HIV-Specific CD8 T Cells in Patients Receiving Antiretroviral Therapy.

IL-7 therapy has been evaluated in patients who do not regain normal CD4 T cell counts after virologically successful antiretroviral therapy. IL-7 increases total circulating CD4 and CD8 T cell counts; however, its effect on HIV-specific CD8 T cells has not been fully examined. TRAF1, a prosurvival signaling adaptor required for 4-1BB-mediated costimulation, is lost from chronically stimulated virus-specific CD8 T cells with progression of HIV infection in humans and during chronic lymphocytic choriomeningitis infection in mice. Previous results showed that IL-7 can restore TRAF1 expression in virus-specific CD8 T cells in mice, rendering them sensitive to anti-4-1BB agonist therapy. In this article, we show that IL-7 therapy in humans increases the number of circulating HIV-specific CD8 T cells. For a subset of patients, we also observed an increased frequency of TRAF1+ HIV-specific CD8 T cells 10 wk after completion of IL-7 treatment. IL-7 treatment increased levels of phospho-ribosomal protein S6 in HIV-specific CD8 T cells, suggesting increased activation of the metabolic checkpoint kinase mTORC1. Thus, IL-7 therapy in antiretroviral therapy-treated patients induces sustained changes in the number and phenotype of HIV-specific T cells.

A diverse epigenetic landscape at human exons with implication for expression.

DNA methylation is an important epigenetic marker associated with gene expression regulation in eukaryotes. While promoter methylation is relatively well characterized, the role of intragenic DNA methylation remains unclear. Here, we investigated the relationship of DNA methylation at exons and flanking introns with gene expression and histone modifications generated from a human fibroblast cell-line and primary B cells. Consistent with previous work we found that intragenic methylation is positively correlated with gene expression and that exons are more highly methylated than their neighboring intronic environment. Intriguingly, in this study we identified a unique subset of hypomethylated exons that demonstrate significantly lower methylation levels than their surrounding introns. Furthermore, we observed a negative correlation between exon methylation and the density of the majority of histone modifications. Specifically, we demonstrate that hypo-methylated exons at highly expressed genes are associated with open chromatin and have a characteristic histone code comprised of significantly high levels of histone markings. Overall, our comprehensive analysis of the human exome supports the presence of regulatory hypomethylated exons in protein coding genes. In particular our results reveal a previously unrecognized diverse and complex role of the epigenetic landscape within the gene body.

Controlling for conservation in genome-wide DNA methylation studies.

BACKGROUND: A commonplace analysis in high-throughput DNA methylation studies is the comparison of methylation extent between different functional regions, computed by averaging methylation states within region types and then comparing averages between regions. For example, it has been reported that methylation is more prevalent in coding regions as compared to their neighboring introns or UTRs, leading to hypotheses about novel forms of epigenetic regulation. RESULTS: We have identified and characterized a bias present in these seemingly straightforward comparisons that results in the false detection of differences in methylation intensities across region types. This bias arises due to differences in conservation rates, rather than methylation rates, and is broadly present in the published literature. When controlling for conservation at coding start sites the differences in DNA methylation rates disappear. Moreover, a re-evaluation of methylation rates at intronexon junctions reveals that the magnitude of previously reported differences is greatly exaggerated. We introduce two correction methods to address this bias, an inferencebased matrix completion algorithm and an averaging approach, tailored to address different underlying biological questions. We evaluate how analysis using these corrections affects the detection of differences in DNA methylation across functional boundaries. CONCLUSIONS: We report here on a bias in DNA methylation comparative studies that originates in conservation rate differences and manifests itself in the false discovery of differences in DNA methylation intensities and their extents. We have characterized this bias and its broad implications, and show how to control for it so as to enable the study of a variety of biological questions.

Phyloepigenomic comparison of great apes reveals a correlation between somatic and germline methylation states.

We have determined methylation state differences in the epigenomes of uncultured cells purified from human, chimpanzee, and orangutan, using digestion with a methylation-sensitive enzyme, deep sequencing, and computational analysis of the sequence data. The methylomes show a high degree of conservation, but the methylation states of ~10% of CpG island-like regions differ significantly between human and chimp. The differences are not associated with changes in CG content and recapitulate the known phylogenetic relationship of the three species, indicating that they are stably maintained within each species. Inferences about the relationship between somatic and germline methylation states can be made by an analysis of CG decay, derived from methylation and sequence data. This indicates that somatic methylation states are highly related to germline states and that the methylation differences between human and chimp have occurred in the germline. These results provide evidence for epigenetic changes that occur in the germline and distinguish closely related species and suggest that germline epigenetic states might constrain somatic states.

Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chains.

Recent experimental and computational work confirms that CpGs can be unmethylated inside coding exons, thereby showing that codons may be subjected to both genomic and epigenomic constraint. It is therefore of interest to identify coding CpG islands (CCGIs) that are regions inside exons enriched for CpGs. The difficulty in identifying such islands is that coding exons exhibit sequence biases determined by codon usage and constraints that must be taken into account. We present a method for finding CCGIs that showcases a novel approach we have developed for identifying regions of interest that are significant (with respect to a Markov chain) for the counts of any pattern. Our method begins with the exact computation of tail probabilities for the number of CpGs in all regions contained in coding exons, and then applies a greedy algorithm for selecting islands from among the regions. We show that the greedy algorithm provably optimizes a biologically motivated criterion for selecting islands while controlling the false discovery rate. We applied this approach to the human genome (hg18) and annotated CpG islands in coding exons. The statistical criterion we apply to evaluating islands reduces the number of false positives in existing annotations, while our approach to defining islands reveals significant numbers of undiscovered CCGIs in coding exons. Many of these appear to be examples of functional epigenetic specialization in coding exons.

Identification and correction of systematic error in high-throughput sequence data.

BACKGROUND: A feature common to all DNA sequencing technologies is the presence of base-call errors in the sequenced reads. The implications of such errors are application specific, ranging from minor informatics nuisances to major problems affecting biological inferences. Recently developed "next-gen" sequencing technologies have greatly reduced the cost of sequencing, but have been shown to be more error prone than previous technologies. Both position specific (depending on the location in the read) and sequence specific (depending on the sequence in the read) errors have been identified in Illumina and Life Technology sequencing platforms. We describe a new type of systematic error that manifests as statistically unlikely accumulations of errors at specific genome (or transcriptome) locations. RESULTS: We characterize and describe systematic errors using overlapping paired reads from high-coverage data. We show that such errors occur in approximately 1 in 1000 base pairs, and that they are highly replicable across experiments. We identify motifs that are frequent at systematic error sites, and describe a classifier that distinguishes heterozygous sites from systematic error. Our classifier is designed to accommodate data from experiments in which the allele frequencies at heterozygous sites are not necessarily 0.5 (such as in the case of RNA-Seq), and can be used with single-end datasets. CONCLUSIONS: Systematic errors can easily be mistaken for heterozygous sites in individuals, or for SNPs in population analyses. Systematic errors are particularly problematic in low coverage experiments, or in estimates of allele-specific expression from RNA-Seq data. Our characterization of systematic error has allowed us to develop a program, called SysCall, for identifying and correcting such errors. We conclude that correction of systematic errors is important to consider in the design and interpretation of high-throughput sequencing experiments.

Nitrogen source interacts with ROP signalling in root hair tip-growth.

Root hairs elongate in a highly polarized manner known as tip growth. Overexpression of constitutively active Rho of Plant (ROP)/RAC GTPases mutants induces swelling of root hairs. Here, we demonstrate that Atrop11(CA)-induced swelling of root hairs depends on the composition of the growth medium. Depletion of ammonium allowed normal root hair elongation in Atrop11(CA) plants, induced the development of longer root hairs in wild-type plants and suppressed the effect of Atrop11(CA) expression on actin organization and reactive oxygen species distribution, whereas membrane localization of the protein was not affected. Ammonium at concentrations higher than 1 mM and the presence of nitrate were required for induction of swelling. Oscillations in wall and cytoplasmic pH are known to accompany tip growth in root hairs, and buffering of the growth medium decreased Atrop11(CA)-induced swelling. Fluorescence ratio imaging experiments revealed that in wild-type root hairs, the addition of NH4NO3 to the growth medium induced an increase in the amplitude of extracellular and intracellular pH oscillations and an overall decrease in cytoplasmic pH at the cell apex. Based on these results, we suggest a model in which ROP GTPases and nitrogen-dependent pH oscillations function in parallel pathways, creating a positive feedback loop during root hair growth.

MetMap enables genome-scale Methyltyping for determining methylation states in populations.

The ability to assay genome-scale methylation patterns using high-throughput sequencing makes it possible to carry out association studies to determine the relationship between epigenetic variation and phenotype. While bisulfite sequencing can determine a methylome at high resolution, cost inhibits its use in comparative and population studies. MethylSeq, based on sequencing of fragment ends produced by a methylation-sensitive restriction enzyme, is a method for methyltyping (survey of methylation states) and is a site-specific and cost-effective alternative to whole-genome bisulfite sequencing. Despite its advantages, the use of MethylSeq has been restricted by biases in MethylSeq data that complicate the determination of methyltypes. Here we introduce a statistical method, MetMap, that produces corrected site-specific methylation states from MethylSeq experiments and annotates unmethylated islands across the genome. MetMap integrates genome sequence information with experimental data, in a statistically sound and cohesive Bayesian Network. It infers the extent of methylation at individual CGs and across regions, and serves as a framework for comparative methylation analysis within and among species. We validated MetMap's inferences with direct bisulfite sequencing, showing that the methylation status of sites and islands is accurately inferred. We used MetMap to analyze MethylSeq data from four human neutrophil samples, identifying novel, highly unmethylated islands that are invisible to sequence-based annotation strategies. The combination of MethylSeq and MetMap is a powerful and cost-effective tool for determining genome-scale methyltypes suitable for comparative and association studies.

Circulating clonally expanded T cells reflect functions of tumor-infiltrating T cells.

Understanding the relationship between tumor and peripheral immune environments could allow longitudinal immune monitoring in cancer. Here, we examined whether T cells that share the same TCRαß and are found in both tumor and blood can be interrogated to gain insight into the ongoing tumor T cell response. Paired transcriptome and TCRαß repertoire of circulating and tumor-infiltrating T cells were analyzed at the single-cell level from matched tumor and blood from patients with metastatic melanoma. We found that in circulating T cells matching clonally expanded tumor-infiltrating T cells (circulating TILs), gene signatures of effector functions, but not terminal exhaustion, reflect those observed in the tumor. In contrast, features of exhaustion are displayed predominantly by tumor-exclusive T cells. Finally, genes associated with a high degree of blood-tumor TCR sharing were overexpressed in tumor tissue after immunotherapy. These data demonstrate that circulating TILs have unique transcriptional patterns that may have utility for the interrogation of T cell function in cancer immunotherapy.

Tim-3 adaptor protein Bat3 is a molecular checkpoint of T cell terminal differentiation and exhaustion.

T cell exhaustion has been associated with poor prognosis in persistent viral infection and cancer. Conversely, in the context of autoimmunity, T cell exhaustion has been favorably correlated with long-term clinical outcome. Understanding the development of exhaustion in autoimmune settings may provide underlying principles that can be exploited to quell autoreactive T cells. Here, we demonstrate that the adaptor molecule Bat3 acts as a molecular checkpoint of T cell exhaustion, with deficiency of Bat3 promoting a profound exhaustion phenotype, suppressing autoreactive T cell-mediated neuroinflammation. Mechanistically, Bat3 acts as a critical mTORC2 inhibitor to suppress Akt function. As a result, Bat3 deficiency leads to increased Akt activity and FoxO1 phosphorylation, indirectly promoting Prdm1 expression. Transcriptional analysis of Bat3 -/- T cells revealed up-regulation of dysfunction-associated genes, concomitant with down-regulation of genes associated with T cell effector function, suggesting that absence of Bat3 can trigger T cell dysfunction even under highly proinflammatory autoimmune conditions.