Abstract
Virtual memory T (TVM) cells are a T cell subtype with a memory phenotype but no prior exposure to foreign antigen. Although TVM cells have antiviral and antibacterial functions, whether these cells can be pathogenic effectors of inflammatory disease is unclear. Here we identified a TVM cell-originated CD44super-high(s-hi)CD49dlo CD8+ T cell subset with features of tissue residency. These cells are transcriptionally, phenotypically and functionally distinct from conventional CD8+ TVM cells and can cause alopecia areata. Mechanistically, CD44s-hiCD49dlo CD8+ T cells could be induced from conventional TVM cells by interleukin (IL)-12, IL-15 and IL-18 stimulation. Pathogenic activity of CD44s-hiCD49dlo CD8+ T cells was mediated by NKG2D-dependent innate-like cytotoxicity, which was further augmented by IL-15 stimulation and triggered disease onset. Collectively, these data suggest an immunological mechanism through which TVM cells can cause chronic inflammatory disease by innate-like cytotoxicity.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
RNA-seq data generated in this study have been deposited in the Gene Expression Omnibus under accession code GSE229631. Source data are provided with this paper. All other data that support the findings of this study are present in the article and Supplementary files or are available from the corresponding author (S.-H.P.) upon reasonable request.
Code availability
All the custom codes used in this study are available from the corresponding author (S.-H.P.) upon reasonable request.
References
Haluszczak, C. et al. The antigen-specific CD8+ T cell repertoire in unimmunized mice includes memory phenotype cells bearing markers of homeostatic expansion. J. Exp. Med. 206, 435–448 (2009).
Chiu, B. -C., Martin, B. E., Stolberg, V. R. & Chensue, S. W. Cutting edge: central memory CD8 T cells in aged mice are virtual memory cells. J. Immunol. 191, 5793–5796 (2013).
White, J. T., Cross, E. W. & Kedl, R. M. Antigen-inexperienced memory CD8+ T cells: where they come from and why we need them. Nat. Rev. Immunol. 17, 391–400 (2017).
Lee, J. Y., Hamilton, S. E., Akue, A. D., Hogquist, K. A. & Jameson, S. C. Virtual memory CD8 T cells display unique functional properties. Proc. Natl Acad. Sci. USA 110, 13498–13503 (2013).
Quinn, K. M. et al. Age-related decline in primary CD8+ T cell responses is associated with the development of senescence in virtual memory CD8+ T cells. Cell Rep. 23, 3512–3524 (2018).
Sosinowski, T. et al. CD8α+ dendritic cell trans presentation of IL-15 to naive CD8+ T cells produces antigen-inexperienced T cells in the periphery with memory phenotype and function. J. Immunol. 190, 1936–1947 (2013).
White, J. et al. Virtual memory T cells develop and mediate bystander protective immunity in an IL-15-dependent manner. Nat. Commun. 7, 11291 (2016).
Rolot, M. et al. Helminth-induced IL-4 expands bystander memory CD8+ T cells for early control of viral infection. Nat. Commun. 9, 4516 (2018).
Lin, J. S. et al. Virtual memory CD8 T cells expanded by helminth infection confer broad protection against bacterial infection. Mucosal Immunol. 12, 258–264 (2019).
Jin, J. H. et al. Virtual memory CD8+ T cells restrain the viral reservoir in HIV-1-infected patients with antiretroviral therapy through derepressing KIR-mediated inhibition. Cell. Mol. Immunol. 17, 1257–1265 (2020).
Miller, C. H. et al. Eomes identifies thymic precursors of self-specific memory-phenotype CD8+ T cells. Nat. Immunol. 21, 567–577 (2020).
Wang, X. et al. MHC class I-independent activation of virtual memory CD8 T cells induced by chemotherapeutic agent-treated cancer cells. Cell. Mol. Immunol. https://doi.org/10.1038/s41423-020-0463-2 (2020).
McElwce, K. J., Boggess, D., King, J. & Sundberg, J. P. Experimental induction of alopecia areata-like hair loss in C3H/HeJ mice using a full-thickness skin grafts. J. Invest. Dermatol. 111, 797–803 (1998).
Pratt, C. H., King, L. E., Messenger, A. G., Christiano, A. M. & Sundberg, J. P. Alopecia areata. Nat. Rev. Dis. Prim. 3, 1–17 (2017).
Xing, L. et al. Alopecia areata is driven by cytotoxic T lymphocytes and is reversed by JAK inhibition. Nat. Med. 20, 1043–1049 (2014).
Qiu, X. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods 14, 979–982 (2017).
Becker, J. C., Varki, N., Bröcker, E. B. & Reisfeld, R. A. Lymphocyte-mediated alopecia in C57BL/6 mice following successful immunotherapy for melanoma. J. Invest. Dermatol. 107, 627–632 (1996).
Gilhar, A. et al. Melanocyte-associated T cell epitopes can function as autoantigens for transfer of alopecia areata to human scalp explants on Prkdc(scid) mice. J. Invest. Dermatol. 117, 1357–1362 (2001).
Wang, E. H. C. et al. Identification of autoantigen epitopes in alopecia areata. J. Invest. Dermatol. 136, 1617–1626 (2016).
Chu, T. et al. Bystander-activated memory CD8 T cells control early pathogen load in an innate-like, NKG2D-dependent manner. Cell Rep. 3, 701–708 (2013).
Ashouri, J. F. & Weiss, A. Endogenous Nur77 is a specific indicator of antigen receptor signaling in human T and B cells. J. Immunol. 198, 657–668 (2017).
Borcherding, N. et al. A transcriptomic map of murine and human alopecia areata. JCI Insight 5, e137424 (2020).
Jacomet, F. et al. Evidence for eomesodermin-expressing innate-like CD8+ KIR/NKG2A+ T cells in human adults and cord blood samples. Eur. J. Immunol. 45, 1926–1933 (2015).
Mackay, L. K. et al. The developmental pathway for CD103+CD8+ tissue-resident memory T cells of skin. Nat. Immunol. 14, 1294–1301 (2013).
Petukhova, L. et al. Genome-wide association study in alopecia areata implicates both innate and adaptive immunity. Nature 466, 113–117 (2010).
Lee, S., Lee, H., Lee, C. H. & Lee, W. S. Comorbidities in alopecia areata: a systematic review and meta-analysis. J. Am. Acad. Dermatol. 80, 466–477 (2019).
Egeberg, A., Anderson, S., Edson-Heredia, E. & Burge, R. Comorbidities of alopecia areata: a population-based cohort study. Clin. Exp. Dermatol. 46, 651–656 (2021).
Shin, J. W. et al. Time-dependent risk of acute myocardial infarction in patients with alopecia areata in Korea. JAMA Dermatol. 156, 763–771 (2020).
McPhee, C. G. et al. Increased expression of Cxcr3 and its ligands, Cxcl9 and Cxcl10, during the development of alopecia areata in the mouse. J. Invest. Dermatol. 132, 1736–1738 (2012).
Dai, Z. et al. CXCR3 blockade inhibits T cell migration into the skin and prevents development of alopecia areata. J. Immunol. 197, 1089–1099 (2016).
Wang, E. H. C. et al. Transfer of alopecia areata to C3H/HeJ mice using cultured lymph node-derived cells. J. Invest. Dermatol. 135, 2530–2532 (2015).
Hirai, T. et al. Competition for active TGFβ cytokine allows for selective retention of antigen-specific tissue-resident memory T cells in the epidermal niche. Immunity 54, 84–98 (2021).
Jaing, X. et al. Skin infection generates non-migratory memory CD8+ TRM cells providing global skin immunity. Nature 483, 227–231 (2012).
Jennings, E. et al. Nr4a1 and Nr4a3 reporter mice are differentially sensitive to T cell receptor signal strength and duration. Cell Rep. 33, 108328 (2020).
Luckey, C. J. et al. Memory T and memory B cells share a transcriptional program of self-renewal with long-term hematopoietic stem cells. Proc. Natl Acad. Sci. USA 103, 3304–3309 (2006).
Wang, C. et al. High-throughput sequencing reveals a complex pattern of dynamic interrelationships among human T cell subsets. Proc. Natl Acad. Sci. USA 107, 1518–1523 (2010).
Yang, X. et al. TCRklass: a new K-string-based algorithm for human and mouse TCR repertoire characterization. J. Immunol. 194, 446–454 (2015).
ImmunoMind Team. Immunarch: an R package for painless analysis of large-scale immune repertoire data https://doi.org/10.5281/zenodo.3367200 (2019).
Acknowledgements
This work was supported by the 2020 Joint Research Project of Institutes of Science and Technology and a grant from the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT; NRF-2022R1A2C3007292 and 2021R1A4A1032094, to S.-H.P). This work was also supported by the 2022 Basic Research Funds from The Korean Hair Research Society (to J.S.) and by a grant of the MD-Phd/Medical Scientist Training Program through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (to S.-D.C). GFP-expressing retroviral vectors were kindly provided by Y.-M. Kim (KAIST, Daejeon, Korea).
Author information
Authors and Affiliations
Contributions
Study design: J.S., E.-C.S. and S.-H.P.; experiment and data collection: J.S., S.-D.C., J.L., Y.C., S.-Y.K., S.-M.L., S.-H.K., S.J., M.J., H.L., A.R.K. and B.C.; data analysis and interpretation: J.S., S.-D.C., J.L., B.C., S.-J.H., I.J., K.-J.Y., J.-E.P., J.H.K., B.J.K., E.-C.S., and S.-H.P.; writing: J.S., S.-D.C. and S.-H.P. with comments from all authors.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Immunology thanks Stephen Jameson, Nicole La Gruta, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: N. Bernard, in collaboration with the Nature Immunology team.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 CD44s-hiCD49dlo CD8+ T cells are exclusively found in AA SDLNs, and CD44s-hiCD49dlo CD8+ T cells from skin exhibit higher expression of genes relevant for cell motility and inflammatory response compared to CD44s-hiCD49dlo CD8+ T cells from SDLNs.
a, The proportion of CD44highCD49dlo CD8+ T cells in SDLN CD8+ T cells (n = 16, naive; n = 29, AA). b, CD44s-hiCD49dlo CD8+ T cells were nearly absent in the spleens, liver, and skin non-draining mesenteric lymph nodes of alopecic mice (n = 5, liver; n = 4, others). c, Heatmap of differentially expressed genes (DEGs) in CD44s-hiCD49dlo CD8+ T cells from SDLNs relative naive TN cells, naive TVM cells, and AA TVM cells (pairwise comparison). Numbers in overlapping regions indicate gene transcripts shared by the overlapping DEG, whereas numbers in non-overlapping regions indicate unique DEGs to each cell subset. d, e, Heatmap of DEGs from skin CD44s-hiCD49dlo CD8+ T cells compared to SDLN CD44s-hiCD49dlo CD8+ T cells (d) and enriched GO biological process gene sets (padj < 0.05) (e). Data were acquired from AtAA mice. mLN, mesenteric lymph node. Data are presented as mean values ± SD. A Mann-Whitney test was performed for comparisons between two groups. All tests were two sided. *P < 0.05, ****P < 0.0001.
Extended Data Fig. 2 CD44s-hiCD49dlo CD8+ T cells had high enrichment of genes related to T-cell effector functions.
a, Heatmap of the gene set33. b, GSEA confirmed that CD44s-hiCD49dlo CD8+ T cells exhibited significant enrichment of the effector CD8+ T cell gene set33 compared to TVM cells from naive or AA mice and TN cells from naive mice. GSEA was performed for pairwise comparison between two groups. All tests were two sided. Data were acquired from AtAA mice. SDLN, skin draining lymph node; NES, normalized enrichment score.
Extended Data Fig. 3 Single-cell RNA-seq of CD45+ cells from the skin and SDLNs of AA and naïve mice.
a, UMAP visualization of CD45+ cell clusters detected in skin and SDLNs from AA and naive mice. b, UMAP visualization of cellular subsets obtained by ADT-labeling of the integrated CITE-Seq. c, CD44 and CD62L of ADT-labeling in CD8+ T cells. Overlays of CD44s-hiCD49dlo CD8+ T cells, TVM cells, TTM cells, and TN cells on total CD8+ T cells with effector memory T cell and central memory T cell gating (CD44hiCD62Llo and CD44hiCD62Lhi, respectively) in flow cytometric analysis. d, Different CD3+ T-cell clusters and their gene expression levels, with brightness indicating average expression and circle size indicating the percent expression. Data were acquired from AtAA mice.
Extended Data Fig. 4 Conventional memory CD8+ T cells primed by skin infection do not contribute to the induction of CD44s-hiCD49dlo CD8+ T cells.
a, Experimental scheme for testing whether skin infection could contribute to the induction of AA. After 4 weeks of vaccinia virus (VV) infection by skin scarification, VV-infected mice (VV-AT) or naïve mice (Control-AT) were induced AA by adoptive transfer method. b,c, Representative flow cytometry plots (b) and the proportion of true memory (TTM) T cells in CD8+ T cells 7 days post-VV infection (n = 3) (c). d, Disease free ratio between the VV-AT (n = 8), the control-AT (n = 10), and the historical control group (n = 74). e, Representative flow cytometry plots of CD8+ T cells after 12 weeks of adoptive transfer. f, Frequency of each cell populations in CD8+ T cells (n = 7, Control-AT; n = 5, VV-AT). g, gMFI of the NKG2D level in each cell population (n = 7, Control-AT; n = 5, VV-AT). Data are presented as mean values ± SD. A Log-rank (Mantel-Cox) test was used for comparison of survival curves. A Mann-Whitney test was performed for comparisons between two groups. All tests were two sided.
Extended Data Fig. 5 CD44s-hiCD49dlo CD8+ T cells are not generated by antigen-driven expansions.
a, Experimental scheme for evaluating the proportion of CD44s-hiCD49dlo CD8+T cells during the AA induction process in vitro (6 days) and in vivo ( > 6 weeks). b, The expressions of Nr4a1, Nr4a2 and Nr4a3, which are upregulated by TCR signalling, in the SDLNs of adoptively transferred C3H mice, measured by real-time PCR at 4 weeks after AT (before AA induction) and at a time-point post-AA onset (n = 4, naïve control; n = 3, naïve + α-CD3; n = 5 (n = 4 in Nr4a2), W4; n = 7, Post-AA). Data are presented as mean values ± SD.
Extended Data Fig. 6 CD44s-hiCD49dlo CD8+ T cells originate from TVM cells, not TN cells.
a, Representative flow cytometry plots of in vitro TN cell stimulation with various cytokines. b, Flow cytometric analysis of SDLNs from cultured naïve TN and TVM cell-adopted mice (n = 5 mice per group). The proportion of CD44s-hiCD49dlo cells in CD8+ T cells (closed square = AA developed mouse). Data are presented as mean values ± SD.
Extended Data Fig. 7 TVM cells may play a crucial role in human AA pathogenesis.
a, IL-12, IL-15, and IL-18 staining of hair follicles from a healthy volunteer and AA patient (n = 3 independent samples). Scale bars, 100μm. b, UMAP visualization of CD45+ cell clusters detected in skin from AA patients and healthy volunteers. c, Different CD3+ T-cell clusters and their gene expression levels, with brightness indicating average expression and circle size indicating the percent expression. d, CD8, pan-KIR2DL + KIR2DS, and NKG2A staining of hair follicles from a healthy volunteer and AA patient (n = 3 independent samples). Scale bars, 50μm. e, f, PBMC CD8+ T cells from healthy doners (n = 10) and patients with AA (n = 10) were analyzed by flow cytometry. The percentage of CD45RA+KIR+NKG2A+ cells among CD8+ T cells (e) and expression level of NKG2D in TVM cells (f). Data are presented as mean values ± SD. Between-group comparisons were made using the Mann-Whitney test. All tests were two sided.
Extended Data Fig. 8 CD44s-hiCD49dlo CD8+ T cells from skin exhibited residential features.
a, Heatmap of the gene expression according to the TRM gene set24. b, GSEA confirmed that skin CD44s-hiCD49dlo CD8+ T cells exhibited significant enrichment of the TRM gene set24 compared to CD44s-hiCD49dlo CD8+ T cells and TVM cells from SDLNs. GSEA was performed for pairwise comparison between two groups. All tests were two sided. Data were acquired from AtAA mice. NES, normalized enrichment score.
Extended Data Fig. 9 CD44s-hiCD49dlo CD8+ T cells exhibit activation in a TCR-independent manner and enhanced proliferation capacity compared to other cell populations.
a-c, Following cytokine stimulation, various cells from SDLNs were incubated for 48 h and flow cytometric analysis performed (50 ng/ml IL-2, 50 ng/ml IL-7, 50 ng/ml IL-12, 50 ng/ml IL-15, or 50 ng/ml IL-18). a, The percentage of GzmB+ and perforin+ cells in AA and naïve TVM cells, respectively (n = 16, AA TVM; n = 17, naïve TVM). b, The percentage of IFNγ+ cells (n = 11, AA TVM; n = 8, naïve TVM) and TNF+ cells in AA TVM cells and naive TVM cells (n = 11, AA TVM; n = 12, naïve TVM). c, Comparison of the percentage of GzmB+ cells, perforin+ cells, IFNγ+ cells, and TNF+ cells among each cell population in the presence of IL-15 (n = 12, naïve; n = 11, AA) or IL-12/18 (n = 8, naïve TVM IFNγ+; n = 12, naïve TVM TNF+; n = 11, AA). d, e, Following cytokine stimulation, various cells from SDLNs were incubated for 96 h. Representative flow cytometry plot of CTVlow cells (d) and the percentage of CTVlow cells in AA TVM cells (n = 7) and naïve TVM cells (n = 4) (e). f, gMFI of NKG2D in each cell population (n = 4, AA TVM; n = 4, naïve TVM). g, Comparison of the gMFI of NKG2D among each cell population without stimulation or in the presence of IL-15 (n = 4 per group). Data were acquired from AtAA mice. Data are presented as mean values ± SD. A Mann-Whitney test was performed for comparisons between two groups. All tests were two sided. ****P < 0.0001.
Supplementary information
Supplementary Information
Supplementary Figs. 1–9 and Tables 1–4
Supplementary Source Data 1
Statistical source data for supplementary figures.
Supplementary Source Data 2
Source data for TCR-seq.
Source data
Source Data Fig. 1
Statistical source data for Fig. 1.
Source Data Fig. 2
Statistical source data for Fig. 2.
Source Data Fig. 3
Statistical source data for Fig. 3.
Source Data Fig. 4
Statistical source data for Fig. 4.
Source Data Fig. 5
Statistical source data for Fig. 5.
Source Data Extended Data Fig. 1
Statistical source data for Extended Data Fig. 1.
Source Data Extended Data Fig. 4
Statistical source data for Extended Data Fig. 4.
Source Data Extended Data Fig. 5
Statistical source data for Extended Data Fig. 5.
Source Data Extended Data Fig. 6
Statistical source data for Extended Data Fig. 6.
Source Data Extended Data Fig. 7
Statistical source data for Extended Data Fig. 7.
Source Data Extended Data Fig. 9
Statistical source data for Extended Data Fig. 9.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Seok, J., Cho, SD., Lee, J. et al. A virtual memory CD8+ T cell-originated subset causes alopecia areata through innate-like cytotoxicity. Nat Immunol 24, 1308–1317 (2023). https://doi.org/10.1038/s41590-023-01547-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41590-023-01547-5
This article is cited by
-
Better understanding CD8+ T cells in cancer and viral infections
Nature Immunology (2023)
-
Virtual memory is a big hairy deal
Nature Immunology (2023)
-
CD8 T-cell subsets: heterogeneity, functions, and therapeutic potential
Experimental & Molecular Medicine (2023)
