ARTICLES https://doi.org/10.1038/s41590-018-0051-0 Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR David Zemmour1, Rapolas Zilionis2,3, Evgeny Kiner1, Allon M. Klein2, Diane Mathis1* and Christophe Benoist 1* + CD4 T regulatory cells (Treg) are central to immune homeostasis, their phenotypic heterogeneity reflecting the diverse envi- ronments and target cells that they regulate. To understand this heterogeneity, we combined single-cell RNA-seq, activation + – reporter and T cell receptor (TCR) analysis to profile thousands of Treg or conventional CD4 FoxP3 T cells (Tconv) from mouse lymphoid organs and human blood. Treg and Tconv pools showed areas of overlap, as resting ‘furtive’ Tregs with overall similarity to Tconvs or as a convergence of activated states. All Tregs expressed a small core of FoxP3-dependent transcripts, onto which additional programs were added less uniformly. Among suppressive functions, Il2ra and Ctla4 were quasiconstant, inhibitory cytokines being more sparsely distributed. TCR signal intensity did not affect resting/activated Treg proportions but molded acti- vated Treg programs. The main lines of Treg heterogeneity in mice were strikingly conserved in human blood. These results reveal unexpected TCR-shaped states of activation, providing a framework to synthesize previous observations of Treg heterogeneity. egulatory T cells are dominant-negative regulators of many contexts, in order to promote peaceful coexistence with commensal facets of the immune system, controlling immune responses microbiota17 or fetal antigens. 18 and enforcing peripheral tolerance to self, symbiotic com- The TCR plays a central role in the Treg life story . It is neces- R 1 mensals and fetal antigens . In addition, some Tregs reside in non- sary for Treg differentiation, and the signals that it delivers upon lymphoid tissues, where they help control tissue homeostasis and major histocompatibility complex (MHC)-peptide recognition, sterile inflammation2. conditioned by costimulatory and other modulators, rescues pre- 1, 3 Tregs constitute a diverse constellation of cells . They have mul- cursor cells from clonal deletion. Continued TCR presence and 4 tiple origins : many Tregs differentiate in the thymus, but others engagement by MHC molecules is required for suppressive activ- + 19 arise in the periphery from naive CD4 T cells upon suboptimal ity and differentiation to an activated phenotype . The Treg TCR exposure to antigens, in particular microbial antigens. Their organ- repertoire is skewed toward recognition of self-antigens but is as 18 ismal locations vary: they reside not only in the T cell zones of lym- broad as that of Tconvs . phoid organs but also in B cell areas, where they control antibody Understanding Treg molecular diversity and definition, in rela- maturation and production (T follicular regulators (Tfr cells)) in tion to Tconv cells, is thus complex and confounded by the different autoimmune or tumoral lesions or at body–microbiota interfaces. states that both populations can adopt in response to various stim- Their effector pathways are heterogeneous: Tregs utilize cell-surface uli. Single-cell transcriptome analysis offers the potential to illumi- inhibitors, such as CTLA4; inhibitory cytokines, such as IL-10, nate these questions, in an unbiased manner that does not rely on IL-35 or TGF-β ; cytokine capture via the IL-2 receptor; purine- assumptions of cell-type identities. Although single-cell (sc) RNA- mediated suppression; or direct cytoxicity5. These facets correspond seq remains challenging20,21 because of the limiting sensitivity of 1,3 to diverse Treg subphenotypes . Particular Treg subtypes have been detection and the large dimensionality of the data, the approach has recognized on the basis of expression of chemokine receptors, such been transformative, for example, in identifying novel cell types and + as CXCR3 (CXCR3 Tregs are particularly adept at suppressing Th1 in dissecting transcriptional differences previously masked by the responses6) or CXCR5 (in Tfr cells)7), or activation markers (in ‘averaging’ inherent in profiling RNA from pooled cells22. 8–11 ‘eTregs’ or ‘aTregs’) . These more activated types of Tregs are particu- Here, we applied scRNA-seq to profile thousands of single Treg 2 larly represented among extralymphoid Tregs in inflammatory sites . and Tconv cells, in mice and humans, to reveal the diversity of tran- Tregs and Tconvs have opposite immune functions, but their molec- scriptional phenotypes that can be adopted by Tregs. We concentrated ular distinction can be complicated. Stable expression of FoxP3 is on two driving questions: how are Tregs and Tconvs related, and how do semantically eponymous for Tregs, and FoxP3 controls a substantial TCR-mediated signals affect Treg activation. For focus, we limited 12 fraction of the characteristic transcriptional signature of Treg cells . the present analysis to Treg and Tconv cells from lymphoid organs. The However, FoxP3 is not sufficient, and several other transcription results reveal an unexpected degree of overlap between Tregs and factors not specific to Tregs but also present in Tconvs are required by Tconvs and provide a framework integrating many prior observations 4 Tregs . Further blurring the Treg/Tconv distinction, FoxP3 itself can be on effector-Treg states. 13 14 expressed transiently upon activation in human and mouse Tconvs. Conversely, whereas the Treg phenotype is generally stable, Tregs can Results 15,16 + lose FoxP3 expression under stress, such as IL-2 deprivation . CD4 Treg and Tconv scRNA-seq datasets. In order to maximize the Finally, Tregs can differentiate directly from Tconvs in tolerogenic power to find small (sub)populations of cells and significant gene 1Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, and Evergrande Center for Immunologic Diseases, Harvard Medical School and Brigham and Women’s Hospital, Boston, MA, USA. 2Department of Systems Biology, Harvard Medical School, Boston, MA, USA. 3Institute of Biotechnology, Vilnius University, Vilnius, Lithuania. *e-mail: [email protected]; [email protected] NatURE IMMUNOLOGY | VOL 19 | MARCH 2018 | 291–301 | www.nature.com/natureimmunology 291 © 2018 Nature America Inc., part of Springer Nature. All rights reserved. ARTICLES NATURE IMMUNOLOGY in T , as expected (Fig. 1c). More generally, the changes in gene a c conv 8 Foxp3 expression between Tregs and Tconvs were conserved, as compared with Treg standard-population RNA-seq data, and substantially overlapped 12 published Treg- and Tconv-specific signatures (Supplementary Fig. 1d). + Tconv Transcriptional relationship between CD4 Treg and Tconv cells. As /FoxP3 4 discussed above, Treg and Tconv cells are ontogenetically related and GFP CD4 can derive from one another in some circumstances. Many profiling + + analyses at the population level have shown that a clear and repro- Gated on TCRβ CD4 ducible gene expression signature distinguishes the two cell types, b T #1 T #3 with Foxp3 as the most extreme example of a Treg-specific gene. The reg reg Tconv Treg Treg #2 Tconv averaging generated by population-level profiling can mask com- 15 Il2ra plexities in this relationship, so we explored our scRNA-seq data Normalized counts ) 10 g specifically in this light. We focus here on splenic populations from 3 unperturbed mice, in which Treg and Tconv populations are generally thought to be stable, as opposed to locations of cell stress, where instability has been observed24. 5 We first used t-distributed Stochastic Neighbor Embedding (tSNE)25 for dimensionality reduction to relate independently Number of expressed genes detected (lo 2 sorted splenic Treg and Tconv cells (sorted independently according 234 gfp to phenotype in the Foxp3 mice; Fig. 2a,b). Although Treg and Tconv Number of unique T T conv reg cells generally partitioned into two main areas (D and E in Fig. 2a), mRNA molecules (log ) 10 Single cell they were also somewhat imbricated. First, some Treg cells (hereaf- ter referred to as ‘furtive’ Tregs) were found in the main Tconv area, Fig. 1 | Treg and Tconv scRNA-seq datasets. a, Flow cytometric plot of gated and vice versa (best seen in Fig. 2b, top); second, there were groups + + gfp CD4 TCRβ Treg and Tconv cells from Foxp3 mice, sorted for scRNA-seq of cells in which Tregs and Tconvs comingled apart from the bulk Treg library construction. Representative of 5 experiments. b, Single-cell and Tconv pools (areas A–C, demarcated in Fig. 2a by bootstrap- transcriptome coverage, shown as the number of uniquely identified mRNA optimized partition clustering). Differences in sequencing coverage reads per cell (x axis) versus the number of expressed genes per single cell, were unlikely to explain this clustering, because the distributions of in three Treg biological-replicate datasets (details in Supplementary Table the detected genes and number of reads were similar in the different 1) and the Tconv dataset. Single cells with < 500 transcripts (dashed line) areas (Supplementary Fig. 2a,b). In addition, similar patterns were sequenced were excluded from further analysis. c, Scatter plot representing observed in additional Treg and Tconv datasets generated with two the expression (normalized counts) of Foxp3 and Il2ra in the single Treg other scRNA-seq platforms: the 10x Genomics platform or 96-well- (n = 708) and Tconv cells (n = 1,098). sorted cells profiled by CEL-seq (Supplementary Fig. 2c–e). Furtive