Lymphocyte innateness defined by transcriptional states reflects a balance between proliferation and effector functions

ARTICLE https://doi.org/10.1038/s41467-019-08604-4 OPEN Lymphocyte innateness defined by transcriptional states reflects a balance between proliferation and effector functions 1234567890():,; Maria Gutierrez-Arcelus 1,2,3,4, Nikola Teslovich 1,2,3, Alex R. Mola3, Rafael B. Polidoro3, Aparna Nathan1,2,3,4, Hyun Kim 1,2,3, Susan Hannes1,2,3,4, Kamil Slowikowski 1,2,3,4, Gerald F.M. Watts3, Ilya Korsunsky 1,2,3,4, Michael B. Brenner3, Soumya Raychaudhuri 1,2,3,4,5 & Patrick J. Brennan3 How innate T cells (ITC), including invariant natural killer T (iNKT) cells, mucosal-associated invariant T (MAIT) cells, and γδ T cells, maintain a poised effector state has been unclear. Here we address this question using low-input and single-cell RNA-seq of human lymphocyte populations. Unbiased transcriptomic analyses uncover a continuous ‘innateness gradient’, with adaptive T cells at one end, followed by MAIT, iNKT, γδ T and natural killer cells at the other end. Single-cell RNA-seq reveals four broad states of innateness, and heterogeneity within canonical innate and adaptive populations. Transcriptional and functional data show that innateness is characterized by pre-formed mRNA encoding effector functions, but impaired proliferation marked by decreased baseline expression of ribosomal genes. Together, our data shed new light on the poised state of ITC, in which innateness is defined by a transcriptionally-orchestrated trade-off between rapid cell growth and rapid effector function. 1 Department of Medicine, Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA 02115. 2 Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA. 3 Department of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA. 4 Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA. 5 Faculty of Medical and Human Sciences, University of Manchester, Manchester M13 9PL, UK. Correspondence and requests for materials should be addressed to S.R. (email: ) or to P.J.B. (email: ) NATURE COMMUNICATIONS | (2019)10:687 | https://doi.org/10.1038/s41467-019-08604-4 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-019-08604-4 W ithin the spectrum of immune defense, “innate” and “adaptive” refer to pre-existing and learned responses, respectively. Mechanistically, innate immunity is largely ascribed to ‘hardwired,’ germline-encoded immune responses, while adaptive immunity derives from recombination and mutation of germline DNA to generate specific receptors that recognize pathogen-derived molecules, such as occurs in T and B cell receptors. However, the paradigm that somatic recombination leads only to adaptive immunity is incorrect. Over the past 15 years, T-cell populations have been identified with T-cell antigen receptors (TCRs) that are conserved between individuals. Many of these effector-capable T-cell populations are established in the absence of pathogen encounter. Examples of such T-cell populations include invariant natural killer T (iNKT) cells, mucosal-associated invariant T (MAIT) cells, γδ T cells, and other populations for which we have a more limited understanding1. These “donor unrestricted” T-cell populations have been estimated to account for as much as 10–20% of human T cells2, and have critical roles in host defense and other immune processes. We and others now refer to these cells as innate T cells (ITC). ITC develop from the same thymic progenitor cells as adaptive T cells, and each of these populations is thought to develop independently. However, ITC populations share several important features that distinguish them from adaptive cells. First, they do not recognize peptides presented by MHC class I and class II. iNKT cells recognize lipids presented by a non-MHC-encoded molecule named CD1d3. MAIT cells recognize small molecules, including bacterial vitamin B-like metabolites presented by another non-MHC-encoded molecule, MR14. It is not known whether specific antigen-presenting elements drive the development or activation of γδ T cells. One major γδ T-cell population bearing Vγ2-Vδ9 TCRs is activated by self- and foreign phosphoantigens in conjunction with a transmembrane butyrophilinfamily receptor, BTN3A15,6. The antigens recognized by other human γδ T-cell populations are not clear, although a subset of these cells recognizes lipids presented by CD1 family proteins7. A second shared feature of ITC is that their responses during inflammation and infection exhibit innate characteristics, such as rapid activation kinetics without prior pathogen exposure, and the capacity for antigen receptor-independent activation. Inflammatory cytokines such as IL-12, IL-18, and type I interferons can activate ITC even in the absence of concordant signaling through their TCRs, and such TCR-independent responses have been reported in iNKT cells8, MAIT cells9, and γδ T cells10. Given the similar functions reported among different ITC populations, we hypothesize that shared effector capabilities may be driven by common transcriptional programs. Here, using lowinput RNA-seq and single-cell RNA-seq, we transcriptionally b 100 Results Human ITC immunophenotyping. To characterize the abundance and variability of ITC in humans, we quantified four major populations of ITC from 101 healthy individuals aged 20–58 years by flow cytometry, directly from peripheral blood mononuclear cells (PBMCs) in the resting state. We assessed the frequencies of iNKT cells, MAIT cells, and the two most abundant peripheral γδ T-cell groups, those expressing a Vδ2 TCR chain (Vδ2) and those expressing a Vδ1 TCR chain (Vδ1). MAIT cells contributed from 0.1 to 15% of T cells (mean 2.4%), iNKT cells from undetectable to 1.1% (mean 0.09%), Vδ1 cells 0.25–6.2% (mean 1.25%), and Vδ2 from 0.08 to 22% (mean 4.7%). The sum of these four cell types accounted for 0.9–25.7% of an individual subject’s T cells (mean 8.4%) (Fig. 1a, Supplementary Data 1). Vδ2 cells were more abundant than Vδ1 in 82% of subjects, with the ratio of these two cell types ranging from 0.2 to 67.8 (mean 8.5). Age negatively associated with the total percentage of ITC (P = 1.4e–05, Pearson correlation, t test). MAIT (r = −0.42, P = 9.9e–06, Pearson correlation, t test) and Vδ2 (r = −0.43, P = 4.7e–06, Pearson correlation, t test) populations drove this association (Supplementary Figure 1a, b), even after accounting for the abundances of other cell types (P = 5.9e–04, P = 1.2e–04, respectively, linear regression, t test), which is consistent with previous findings11,12. We observed covariance between the frequencies of MAIT and iNKT cells (P = 0.02, Spearman correlation, t test), corrected for the other cell types and age (Supplementary Figure 1c, d). We observed no significant associations between ITC percentage and gender (P = 0.12, (...truncated)