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Dectin-1 signaling on colonic γδ T cells promotes psychosocial stress responses

Nature Immunology volume 24, pages 625–636 (2023)Cite this article

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Abstract

The intestinal immune system interacts with commensal microbiota to maintain gut homeostasis. Furthermore, stress alters the microbiome composition, leading to impaired brain function; yet how the intestinal immune system mediates these effects remains elusive. Here we report that colonic γδ T cells modulate behavioral vulnerability to chronic social stress via dectin-1 signaling. We show that reduction in specific Lactobacillus species, which are involved in T cell differentiation to protect the host immune system, contributes to stress-induced social-avoidance behavior, consistent with our observations in patients with depression. Stress-susceptible behaviors derive from increased differentiation in colonic interleukin (IL)-17-producing γδ T cells (γδ17 T cells) and their meningeal accumulation. These stress-susceptible cellular and behavioral phenotypes are causally mediated by dectin-1, an innate immune receptor expressed in γδ T cells. Our results highlight the previously unrecognized role of intestinal γδ17 T cells in the modulation of psychological stress responses and the importance of dectin-1 as a potential therapeutic target for the treatment of stress-induced behaviors.

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Fig. 1: Alteration of intestinal microbiota correlates with social avoidance in CSDS mice as well as disease severity in patients with MDD.
Fig. 2: Increase and differentiation of γδ T cells in the colon and meninges of susceptible mice.
Fig. 3: Inhibition of peripheral γδ T cells blocks CSDS-induced social avoidance.
Fig. 4: Peripheral γδ17 T cell differentiation contributes to CSDS-induced social avoidance.
Fig. 5: Dectin-1 mediates increased colonic γδ T cell populations and γδ17 T cell differentiation as well as the social avoidance induced by CSDS.
Fig. 6: CSDS-induced colonic IL-1β production in myeloid cells is independent of dectin-1 signaling.

Data availability

The raw data of the shotgun metagenomic sequencing of mouse fecal samples that support the findings of this study have been deposited to NCBI Sequence Read Archive under BioProject PRJNA758357. The 16S rRNA gene sequences obtained from human fecal samples have been deposited to the DNA DataBank of Japan (DDBJ) under the accession number DRA010810 (patients with MDD) and DRA012712 (healthy controls). Human data have been de-identified to protect confidentiality. The SILVA132 database can be downloaded at https://www.arb-silva.de/fileadmin/silva_databases/qiime/Silva_132_release.zip. Source data are provided with this paper.

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Acknowledgements

We thank S. Poynton and S. Madireddy for critical reading of the manuscript. We thank Y. Iwakura (Tokyo University of Science), R. Giger (University of Michigan) and T. Hohl (Sloan Kettering Institute) for providing us with Clec7a−/− mice. We thank the Johns Hopkins University School of Medicine (JHU SOM) Flow Cytometry Core Facility, the JHU SOM Microscopy Core Facility and the JHU SOM Behavioral Core Facility. We thank S. Duboux (Société des Produits Nestlé S.A.) and Y. Fukushima (Nestlé Japan Manufacturing, Tokyo, Japan) for their help with culturing L. johnsonii La1, which was supplied from NESTEC.LTD (Lausanne, Switzerland). Some elements in Fig. 4a and Extended Data Fig. 4a were created using BioRender.com (2021). We also thank D. Tamura for providing a gift fund. This work was supported by grants from the National Institute of Health Awards grant nos DA041208 (A.K.), AG065168 (A.K.), MH094268 (A.K.), MH128765 (A.K.), AT008547 (A.K.), AT010984 (X.Z.), NS041435 (P.A.C.) and MH113645 (S.-i.K.) as well as institutional and foundation grants from the JHU catalyst award (A.K.), JSCNP (S.S.), Kanae (Y.H.), JST ERATO (grant no. JPMJER1902; S.F.), AMED-CREST (grant no. JP22gm1010009; S.F.), JSPS KAKENHI (grant no. 22H03541; S.F.), the Food Science Institute Foundation (S.F.) and the Japan Dairy Association (J-milk) (K.S.).

Author information

Author notes

  1. Hui Li

    Present address: School of Electrical, Computer and Biomedical Engineering, Southern Illinois University, Carbondale, IL, USA

  2. These authors contributed equally: Xiaolei Zhu, Shinji Sakamoto.

Authors and Affiliations

  1. Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Xiaolei Zhu, Shinji Sakamoto, Koki Ito, Mizuho Obayashi, Lisa Unger, Yuto Hasegawa & Atsushi Kamiya

  2. Department of Neuropsychiatry, Okayama University Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama, Japan

    Shinji Sakamoto

  3. Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan

    Chiharu Ishii & Shinji Fukuda

  4. Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Matthew D. Smith & Peter A. Calabresi

  5. Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan

    Koki Ito

  6. Institute of Neuroimmunology and Multiple Sclerosis, University Medical Centre Hamburg–Eppendorf, Hamburg, Germany

    Lisa Unger

  7. Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan

    Shunya Kurokawa & Taishiro Kishimoto

  8. Hills Joint Research Laboratory for Future Preventive Medicine and Wellness, Keio University School of Medicine, Tokyo, Japan

    Taishiro Kishimoto

  9. Departments of Mechanical Engineering and Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA

    Hui Li & Tza-Huei Wang

  10. Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan

    Shinya Hatano & Yasunobu Yoshikai

  11. Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA

    Shin-ichi Kano

  12. Gut Environmental Design Group, Kanagawa Institute of Industrial Science and Technology, Kawasaki, Japan

    Shinji Fukuda

  13. Transborder Medical Research Center, University of Tsukuba, Tsukuba, Japan

    Shinji Fukuda

  14. Laboratory for Regenerative Microbiology, Graduate School of Medicine, Juntendo University, Tokyo, Japan

    Shinji Fukuda

  15. Department of Psychiatry, School of Medicine, Showa University, Tokyo, Japan

    Kenji Sanada

  16. Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Peter A. Calabresi

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  1. Xiaolei Zhu
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Contributions

X.Z., S.S. and A.K. designed the study. X.Z. and S.S. performed cellular, behavioral and immunohistochemical experiments, and contributed to data analysis for all experiments. K.I., M.D.S., L.U., Y.H. and M.O. assisted X.Z. and S.S. with the cellular, behavioral and histochemical assays. X.Z. and S.S. performed shotgun metagenomic sequencing and analyzed taxonomic data. C.I. and S.F. performed 16S rRNA gene sequencing and analyzed taxonomic data together with S.S., X.Z. and K.S. S.K., T.K. and K.S. contributed to human data collection and analysis. H.L. and T.-H.W. contributed to the La1 culture, and helped X.Z. and M.O. perform in vivo La1 administration. S.H. and Y.Y. contributed to the production and characterization of antibody to Vγ6 as well as data interpretation of the flow cytometry experiments. P.A.C. and S.-i.K. contributed to study design, data analysis and interpretation, and provided technical assistance in the cellular experiments. A.K. contributed to the concept or design of the work, and drafting the manuscript with X.Z. and S.S. All authors have approved the final manuscript.

Corresponding author

Correspondence to Atsushi Kamiya.

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Nature Immunology thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: L. A. Dempsey, in collaboration with the Nature Immunology team.

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Extended data

Extended Data Fig. 1 CSDS-induced social-avoidance phenotype assessed using a three-chamber social interaction test.

a, CSDS results in a spectrum of social-avoidance behavior, divided between susceptible and resilient phenotypes using their social interaction ratio (SIR) score. b, Time the mice spent in the chamber with an inanimate object versus with a stranger mouse (top left). Time the mice spent sniffing an inanimate object versus a stranger mouse (top right). Representative heatmaps depict movements of the control, resilient and susceptible mice (bottom). c, Body-weight change ratio of control, resilient and susceptible mice between before and after CSDS. a–c, n = 18 control mice, n = 16 resilient mice and n = 16 susceptible mice. **P < 0.01 (time spent in chambers: P = 0.0067, P < 0.0001, P < 0.0001; time spent sniffing: P < 0.0001, P = 0.0006 and P < 0.0001), determined using an unpaired two-tailed Student’s t-test. Error bars represent the mean ± s.e.m.

Source data

Extended Data Fig. 2 CSDS induces alteration of intestinal bacteria.

a, Bray–Curtis β-diversity index of grouped data of fecal bacteria at the species level (n = 5 per group). Analyzed by one-way ANOVA with Tukey’s post-hoc test; adjustments were made for multiple comparisons. b, Relative abundance of fecal bacteria at the genus level in control, resilient and susceptible mice (n = 5 per group). For details about altered species across conditions, refer to Supplementary Table 1.

Source data

Extended Data Fig. 3 The effect of CSDS on other T cell subtypes in the colon, small intestine and spleen.

a, Representative flow cytometry plots of CD3+ T cells, CD4+ T cells (CD3+CD4+), CD8+ T cells (CD3+CD8+), TH17 cells (CD3+CD4+IL-17+) and Treg cells (CD3+CD4+FOXP3+) in the LP of the colon. b–d, Percentages of CD3+ T cells in viable cells, CD4+ T cells in CD3+ T cells, CD8+ T cells in CD3+ T cells, TH17 cells in CD4+ T cells and Treg cells in CD4+ T cells in the LP of the colon (b; n = 5, 5 and 5), small intestine (c; n = 6, 6 and 5) and spleen (d; n = 6, 7 and 5) of control, resilient and susceptible mice. *P < 0.05 (P values are P = 0.031 and P = 0.0402), determined by one-way ANOVA with Tukey’s post-hoc test. Error bars represent the mean ± s.e.m.

Source data

Extended Data Fig. 4 CSDS-induced changes in T cells and social avoidance in female mice.

a, Schematic representation of chronic stress paradigm for female mice. b,c, Attack number (b) and latency (c) of CD-1 aggressors on male versus female mice. n = 100 (ten mice × 10 d) per group. d,e, Attack number (d) and latency (e) of CD-1 aggressors during the proestrus (n = 20), estrus (n = 33), metestrus (n = 18) and diestrus (n = 29) cycle of female mice. f, The percentage of CD-1 behaviors directed towards female mice over the 10-d chronic stress period (left) and over the course of the estrous cycle (middle and right). g, Time the mice spent in the chamber with an inanimate object versus a stranger female mouse (top left). Time the mice spent sniffing an inanimate object versus a stranger female mouse (top right). The color in the dots represents the estrous cycle of the test female mouse. Representative heatmaps depict mice movements (bottom). Control, resilient and susceptible mice (n = 5, 5, 5). h, Percentage of γδ T cells in CD3+ T cells, γδ17 T cells in γδ T cells, CD3+ T cells in viable cells, CD4+ T cells in CD3+ T cells, CD8+ T cells in CD3+ T cells, TH17 cells in CD4+ T cells and Treg cells in CD4+ T cells in the meninges of control, resilient and susceptible female mice (n = 5, 5, 5). b,g, *P < 0.05 and **P < 0.01 (b, P < 0.0001; g, time spent in chambers: P = 0.0039 and P = 0.0033; time spent sniffing: P = 0.0012, P = 0.0237 and P = 0.0049), determined using an unpaired two-tailed Student’s t-test. h, *P < 0.05 (percentage γδ T cells: P = 0.0158, P = 0.0126; percentage γδ17 T cells: P = 0.0203), determined by one-way ANOVA with Tukey’s post-hoc test. Error bars represent the mean ± s.e.m.

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Extended Data Fig. 5 Quantification of La1 in the colonic fecal samples by quantitative real time PCR.

The graphs represent the La1 level in the fecal samples collected from the colon of ctr + vehicle and CSDS + vehicle groups of mice (n = 5, 5; left) as well as the colon of CSDS + vehicle and CSDS + La1 groups of mice (n = 5, 5; right). *P < 0.05 (P = 0.0039 and P = 0.0142), determined by an unpaired two-tailed Student’s t-test. Error bars represent the mean ± s.e.m.

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Extended Data Fig. 6 Inhibition effects of i.p. injection of anti-TCR-γδ on γδ T cells in the spleen and meninges as well as CSDS-induced behaviors and the effect of genetic deletion of TCRd on CSDS-induced social-avoidance behavior.

a, Representative flow cytometry plots of γδ T cells (CD3+TCR-β−TCR-γδ+) in the spleen of WT mice injected with IgG or anti-TCR-γδ (10, 50 and 250 µg per mouse, respectively) at post-injection day 12. b, Representative flow cytometry plots of γδ T cells in the spleen of WT mice injected with IgG or anti-TCR-γδ (50 µg per mouse) at post-injection days 3 and day 7, respectively. c, Representative flow cytometry plots of γδ T cells in the meninges of WT mice injected with IgG or anti-TCR-γδ (50 µg per mouse) at post-injection day 12. The boxes in the dot plots identify γδ T cells and represent the percentage of γδ T cells in CD3+ T cells in all groups of mice. d, Locomotion activity as assessed by total counts in the OFT of ctr + IgG, CSDS + IgG, ctr + anti-TCR-γδ and CSDS + anti-TCR-γδ groups of mice (n = 9, 9, 10 and 10). e, Percentage of time spent in the open arms during the elevated plus maze (EPM) test of mice: ctr + IgG, CSDS + IgG, ctr + anti-TCR-γδ and CSDS + anti-TCR-γδ (n = 9, 10, 9 and 10). f,g, The average of total fluid consumption (f) and the average percentage of sucrose consumption when given a choice between 1.5% sucrose and water (g) on days 5–8 of ctr + IgG, CSDS + IgG, ctr + anti-TCR-γδ and CSDS + anti-TCR-γδ groups of mice (n = 8, 9, 7, 9). h, Time test mice spend in the chambers (top left). Time test mice spent sniffing (top right). Representative heatmaps depicting mice movements (bottom). n = 10 for WT + CSDS and n = 7 for TCRd-KO + CSDS groups of mice. e,g, *P < 0.05 and **P < 0.01 (e, P = 0.0384 and P = 0.0045; g, P = 0.0207), determined by two-way ANOVA with Tukey’s post-hoc test. h, **P < 0.01 (time spent in chambers: P = 0.0041; time spent in sniffing: P < 0.0001), determined by an unpaired two-tailed Student’s t-test. Error bars represent the mean ± s.e.m.

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Extended Data Fig. 7 No change in dectin-1 expression in the colonic CD3+, CD4+ and CD8+ T cells of C57BL/6 mice after CSDS.

Representative flow cytometry plots (left). Percentage of dectin-1+ cells in CD3+ (top right), CD4+ (middle right) and CD8+ (bottom right) T cells in the LP of the colon of control, resilient and susceptible mice (n = 4, 4, 4). The boxes in the dot plots identify dectin-1+ cells in each group of mice. Error bars represent the mean ± s.e.m.

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Extended Data Fig. 8 The effects of genetic deletion of dectin-1 and treatment with pachyman on CSDS-induced phenotypes in colonic non-γδ T lymphocytes and sucrose preference test.

a–e, Percentage of CD3+ T cells in viable cells (a), CD4+ T cells in CD3+ cells (b), CD8+ T cells in CD3+ cells (c), TH17 cells in CD4+ cells (d) and Treg cells in CD4+ cells (e) in the LP of the colon of WT + ctr, WT + CSDS, dectin-1 KO + ctr and dectin-1 KO + CSDS groups of mice (n = 5, 5, 5, 5). f,g, The average of total fluid consumption (f) and the average percentage of sucrose consumption when given a choice between 1.5% sucrose and water (g) on days 5–8 for WT + ctr, WT + CSDS, dectin-1 KO + ctr and dectin-1 KO + CSDS groups of mice (n = 9, 9, 8, 9). h, Schematic of the experimental design. Eight-week-old TCRd-KO mice received i.v. injection of γδ T cells collected from Clec7a−/− (dectin-1 KO) mice or their WT littermates 1 d before and 5 d after the start of CSDS, followed by a social interaction test (SIT) and tissue collection. i, Schematic of the experimental design. Eight-week-old C57BL/6 mice were orally treated with the vehicle or pachyman daily during the CSDS period, followed by SIT and sucrose preference test (SPT; left). An independent cohort of mice was subjected to tissue harvest 1 d after CSDS (right). j–n, Percentage of CD3+ cells in viable cells (j), CD4+ cells in CD3+ cells (k), CD8+ cells in CD3+ cells (l), TH17 cells in CD4+ cells (m) and Treg cells in CD4+ cells (n) in the LP of the colon of ctr + vehicle, CSDS + vehicle, ctr + pachyman and CSDS + pachyman groups of mice (n = 5, 6, 6, 5). o,p, The average of total fluid consumption (o) and the average percentage of sucrose consumption when given a choice between 1.5% sucrose and water (p) on days 5–8 for four groups of mice: ctr + vehicle, CSDS + vehicle, ctr + pachyman and CSDS + pachyman (n = 10, 10, 10 and 10). *P < 0.05 and **P < 0.01 (c, P = 0.0429; g, P < 0.0001 and P < 0.0001; l, P = 0.0252; p, P < 0.0001 and P < 0.0001), determined by two-way ANOVA with Tukey’s post-hoc test. Error bars represent the mean ± s.e.m.

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Zhu, X., Sakamoto, S., Ishii, C. et al. Dectin-1 signaling on colonic γδ T cells promotes psychosocial stress responses. Nat Immunol 24, 625–636 (2023). https://doi.org/10.1038/s41590-023-01447-8

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