Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

CD8+ T cells induce cachexia during chronic viral infection

Nature Immunology volume 20, pages 701–710 (2019)Cite this article

Subjects

Abstract

Cachexia represents a leading cause of morbidity and mortality in various cancers, chronic inflammation and infections. Understanding of the mechanisms that drive cachexia has remained limited, especially for infection-associated cachexia (IAC). In the present paper we describe a model of reversible cachexia in mice with chronic viral infection and identify an essential role for CD8+ T cells in IAC. Cytokines linked to cancer-associated cachexia did not contribute to IAC. Instead, virus-specific CD8+ T cells caused morphologic and molecular changes in the adipose tissue, which led to depletion of lipid stores. These changes occurred at a time point that preceded the peak of the CD8+ T cell response and required T cell–intrinsic type I interferon signaling and antigen-specific priming. Our results link systemic antiviral immune responses to adipose-tissue remodeling and reveal an underappreciated role of CD8+ T cells in IAC.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Infection with LCMV clone 13 leads to transient cachexia.
Fig. 2: Infection-associated cachexia triggers severe adipose tissue remodeling and increased lipolysis.
Fig. 3: Type I IFN and CD8 T cells play critical roles in inducing infection-associated cachexia.
Fig. 4: CD8 T cells modulate adipose tissue lipid metabolism in a type I IFN-dependent manner.
Fig. 5: CD8 T cells trigger cachexia during the early stage of T cell priming and antigen recognition.

Similar content being viewed by others

Data availability

The accession number for the raw data of the RNA-seq is GSE118819.

References

  1. Von Haehling, S. & Anker, S. D. Treatment of cachexia: an overview of recent developments. Int. J. Cardiol. 184, 726–742 (2014).

    Google Scholar 

  2. Baracos, V. E., Martin, L., Korc, M., Guttridge, D. C. & Fearon, K. C. H. Cancer-associated cachexia. Nat. Rev. Dis. Primers 4, 1–18 (2018).

    Article  Google Scholar 

  3. Fearon, K. et al. Definition and classifi cation of cancer cachexia: an international consensus. Lancet Oncol. 12, 489–495 (2011).

    Article  Google Scholar 

  4. Kotler, D. Challenges to diagnosis of HIV-associated wasting. J. Acquir. Immune Defic. Syndr. 37, S280–S283 (2004).

    Article  Google Scholar 

  5. Tisdale, M. J. Cachexia in cancer patients. Nat. Rev. Cancer 2, 862–871 (2002).

    Article  CAS  Google Scholar 

  6. Porporato, P. E. Understanding cachexia as a cancer metabolism syndrome. Oncogenesis 5, 200 (2016).

    Article  Google Scholar 

  7. Morley, J. E., Thomas, D. R. & Wilson, M.-M. G. Cachexia: pathophysiology and clinical relevance. Am. J. Clin. Nutr. 83, 735–743 (2006).

    Article  CAS  Google Scholar 

  8. Fearon, K. C. H., Glass, D. J. & Guttridge, D. C. Cancer cachexia: Mediators, signaling, and metabolic pathways. Cell Metab. 16, 153–166 (2012).

    Article  CAS  Google Scholar 

  9. Vaitkus, J. A. & Celi, F. S. The role of adipose tissue in cancer-associated cachexia. Exp. Biol. Med. 242, 473–481 (2017).

    Article  CAS  Google Scholar 

  10. Petruzzelli, M. & Wagner, E. F. Mechanisms of metabolic dysfunction in cancer-associated cachexia. Genes Dev. 30, 489–501 (2016).

    Article  CAS  Google Scholar 

  11. Flint, T. R., Fearon, D. T. & Janowitz, T. Connecting the metabolic and immune responses to cancer. Trends Mol. Med. 23, 451–464 (2017).

    Article  CAS  Google Scholar 

  12. Bergthaler, A. et al. Viral replicative capacity is the primary determinant of lymphocytic choriomeningitis virus persistence and immunosuppression. Proc. Natl Acad. Sci. USA 107, 21641–21646 (2010).

    Article  CAS  Google Scholar 

  13. Stamm, A., Valentine, L., Potts, R. & Premenko-Lanier, M. An intermediate dose of LCMV clone 13 causes prolonged morbidity that is maintained by CD4+T cells. Virology 425, 122–132 (2012).

    Article  CAS  Google Scholar 

  14. Zechner, R. et al. FAT SIGNALS—lipases and lipolysis in lipid metabolism and signaling. Cell Metab. 15, 279–291 (2012).

    Article  CAS  Google Scholar 

  15. Tsoli, M. et al. Depletion of white adipose tissue in cancer cachexia syndrome is associated with inflammatory signaling and disrupted circadian regulation. PLoS ONE 9, e92966 (2014).

    Article  Google Scholar 

  16. Das, S. K. et al. Adipose triglyceride lipase contributes to cancer-associated cachexia. Science 333, 233–238 (2011).

    Article  CAS  Google Scholar 

  17. Ruud, J. & Brüning, J. C. Metabolism: light on leptin link to lipolysis. Nature 527, 43–44 (2015).

    Article  CAS  Google Scholar 

  18. Baatar, D., Patel, K. & Taub, D. D. The effects of ghrelin on inflammation and the immune system. Mol. Cell Endocrinol. 340, 44–58 (2011).

    Article  CAS  Google Scholar 

  19. Kandarian, S. C. et al. Tumour-derived leukaemia inhibitory factor is a major driver of cancer cachexia and morbidity in C26 tumour-bearing mice. J. Cachexia Sarcopenia Muscle 9, 1–12 (2018).

    Article  Google Scholar 

  20. Patel, H. J. & Patel, B. M. TNF-α and cancer cachexia: molecular insights and clinical implications. Life Sci. 170, 56–63 (2016).

    Article  Google Scholar 

  21. Bhattacharya, A. et al. Superoxide dismutase 1 protects hepatocytes from type i interferon-driven oxidative damage. Immunity 43, 974–986 (2015).

    Article  CAS  Google Scholar 

  22. Curtsinger, J. M., Valenzuela, J. O., Agarwal, P., Lins, D. & Mescher, M. F. Cutting edge: type I IFNS provide a third signal to CD8 T cells to stimulate clonal expansion and differentiation. J. Immunol. 174, 4465–4469 (2005).

    Article  CAS  Google Scholar 

  23. Kolumam, G. A., Thomas, S., Thompson, L. J., Sprent, J. & Murali-Krishna, K. Type I interferons act directly on CD8 T cells to allow clonal expansion and memory formation in response to viral infection. J. Exp. Med. 202, 637–650 (2005).

    Article  CAS  Google Scholar 

  24. Xu, C. et al. Direct effect of glucocorticoids on lipolysis in adipocytes. Mol. Endocrinol. 23, 1161–1170 (2009).

    Article  CAS  Google Scholar 

  25. Pinschewer, D. D. et al. FTY720 immunosuppression impairs effector T cell peripheral homing without affecting induction, expansion, and memory. J. Immunol. 164, 5761–5770 (2000).

    Article  CAS  Google Scholar 

  26. Petruzzelli, M. et al. A switch from white to brown fat increases energy expenditure in cancer-associated cachexia. Cell Metab. 20, 433–447 (2014).

    Article  CAS  Google Scholar 

  27. Kir, S. et al. PTH/PTHrP receptor mediates cachexia in models of kidney failure and cancer. Cell Metab. 23, 315–323 (2016).

    Article  CAS  Google Scholar 

  28. Cao, Y. Angiogenesis and vascular functions in modulation of obesity, adipose metabolism, and insulin sensitivity. Cell Metab. 18, 478–489 (2013).

    Article  CAS  Google Scholar 

  29. Vegiopoulos, A., Rohm, M. & Herzig, S. Adipose tissue: between the extremes. EMBO J. 36, 1999–2017 (2017).

    Article  CAS  Google Scholar 

  30. Quatrini, L. et al. Endogenous glucocorticoids control host resistance to viral infection through the tissue-specific regulation of PD-1 expression on NK cells. Nat. Immunol. 19, 954–962 (2018).

    Article  CAS  Google Scholar 

  31. Miller, A. H. et al. Effects of viral infection on corticosterone secretion and glucocorticoid receptor binding in immune tissues. Psychoneuroendocrinology 22, 455–474 (1997).

    Article  CAS  Google Scholar 

  32. Jamieson, A. M., Yu, S., Annicelli, C. H. & Medzhitov, R. Influenza virus-induced glucocorticoids compromise innate host defense against a secondary bacterial infection. Cell Host Microbe 7, 103–114 (2010).

    Article  CAS  Google Scholar 

  33. Doherty, P. C., Hou, S. & Southern, P. J. Lymphocytic choriomeningitis virus induces a chronic wasting disease in mice lacking class I major histocompatibility complex glycoproteins. J. Neuroimmunol. 46, 11–17 (1993).

    Article  CAS  Google Scholar 

  34. Hildeman, D. & Muller, D. Immunopathologic weight loss in intracranial LCMV infection initiated by the anorexigenic effects of IL-1β. Viral Immunol. 13, 273–285 (2000).

    Article  CAS  Google Scholar 

  35. Kamperschroer, C. & Quinn, D. G. The role of proinflammatory cytokines in wasting disease during lymphocytic choriomeningitis virus infection. J. Immunol. 169, 340–349 (2002).

    Article  CAS  Google Scholar 

  36. Wang, A. et al. Opposing effects of fasting metabolism on tissue tolerance in bacterial and viral inflammation. Cell 166, 1512–1525.e12 (2016).

    Article  CAS  Google Scholar 

  37. Pietrocola, F. et al. Caloric restriction mimetics enhance anticancer immunosurveillance. Cancer Cell 30, 147–160 (2016).

    Article  CAS  Google Scholar 

  38. Nencioni, A., Caffa, I., Cortellino, S. & Longo, V. D. Fasting and cancer: molecular mechanisms and clinical application. Nat. Rev. Cancer 18, 707–719 (2018).

    Article  CAS  Google Scholar 

  39. Longo, V. D. & Mattson, M. P. Fasting: molecular mechanisms and clinical applications. Cell Metab. 19, 181–192 (2014).

    Article  CAS  Google Scholar 

  40. Rouse, B. T. & Sehrawat, S. Immunity and immunopathology to viruses: what decides the outcome? Nat. Rev. Immunol. 10, 514–526 (2010).

    Article  CAS  Google Scholar 

  41. Virgin, H. W., Wherry, E. J. & Ahmed, R. Redefining chronic viral infection. Cell 138, 30–50 (2009).

    Article  CAS  Google Scholar 

  42. Sullivan, B. M., Teijaro, J. R., De La Torre, J. C. & Oldstone, M. B. A. Early virus–host interactions dictate the course of a persistent infection. PLoS Pathog. 11, 1004588 (2015).

    Article  Google Scholar 

  43. Danai, L. V. et al. Altered exocrine function can drive adipose wasting in early pancreatic cancer. Nature 558, 600–604 (2018).

    Article  CAS  Google Scholar 

  44. Wherry, E. J. & Kurachi, M. Molecular and cellular insights into T cell exhaustion. Nat. Rev. Immunol. 15, 486–499 (2015).

    Article  CAS  Google Scholar 

  45. Perry, R. J. et al. Hepatic acetyl CoA links adipose tissue inflammation to hepatic insulin resistance and type 2 diabetes. Cell 160, 745–758 (2015).

    Article  CAS  Google Scholar 

  46. Norata, G. D. et al. The cellular and molecular basis of translational immunometabolism. Immunity 43, P421–P434 (2015).

    Article  Google Scholar 

  47. Buck, M. D., Sowell, R. T., Kaech, S. M. & Pearce, E. L. Metabolic instruction of immunity. Cell 169, 570–586 (2017).

    Article  CAS  Google Scholar 

  48. Huang, S. et al. Immune response in mice that lack the interferon-gamma receptor. Science 259, 1742–1745 (1993).

    Article  CAS  Google Scholar 

  49. Pasparakis, M., Alexopoulou, L., Episkopou, V. & Kollias, G. Immune and inflammatory responses in TNF alpha-deficient mice: a critical requirement for TNF alpha in the formation of primary B cell follicles, follicular dendritic cell networks and germinal centers, and in the maturation of the humoral immune response. J. Exp. Med. 184, 1397–1411 (1996).

    Article  CAS  Google Scholar 

  50. Peschon, J. J. et al. TNF receptor-deficient mice reveal divergent roles for p55 and p75 in several models of inflammation. J. Immunol. 160, 943–952 (1998).

    CAS  PubMed  Google Scholar 

  51. Muller, U. et al. Functional role of type I and type II interferons in antiviral defense. Science 264, 1918–1921 (1994).

    Article  CAS  Google Scholar 

  52. Prigge, J. R. et al. Type I IFNs act upon hematopoietic progenitors to protect and maintain hematopoiesis during pneumocystis lung infection in mice. J. Immunol. 195, 5347–5357 (2015).

    Article  CAS  Google Scholar 

  53. Sitnick, M. T. et al. Skeletal muscle triacylglycerol hydrolysis does not influence metabolic complications of obesity. Diabetes 62, 3350–3361 (2013).

    Article  CAS  Google Scholar 

  54. Eguchi, J. et al. Transcriptional control of adipose lipid handling by IRF4. Cell Metab. 13, 249–259 (2011).

    Article  CAS  Google Scholar 

  55. Sawada, S., Scarborough, J. D., Killeen, N. & Littman, D. R. A lineage-specific transcriptional silencer regulates CD4 gene expression during T lymphocyte development. Cell 77, 917–929 (1994).

    Article  CAS  Google Scholar 

  56. Coleman, D. L. & Hummel, K. The influence of genetic background on the expression of the obese (Ob) gene in the mouse. Diabetologia 9, 287–293 (1973).

    Article  CAS  Google Scholar 

  57. Komuro, K., Itakura, K., Boyse, E. A. & John, M. Ly-5: a new T-lymphocyte antigen system. Immunogenetics 1, 452–456 (1974).

    Article  Google Scholar 

  58. Fung-Leung, W. et al. CD8 is needed for development of cytotoxic T but not helper T cells. Cell 65, 443–449 (1991).

    Article  CAS  Google Scholar 

  59. Shinkai, Y. et al. RAG-2-deficient mice lack mature lymphocytes owing to inability to initiate V(D)J rearrangement. Cell 68, 855–867 (1992).

    Article  CAS  Google Scholar 

  60. Hogquist, K. A. et al. T cell receptor antagonist peptides induce positive selection. Cell 76, 17–27 (1994).

    Article  CAS  Google Scholar 

  61. Mombaerts, P. et al. RAG-l-deficient mice have no mature B and T lymphocytes. Cell 68, 869–877 (1992).

    Article  CAS  Google Scholar 

  62. Kägi, D. et al. Cytotoxicity mediated by T cells and natural killer cells is greatly impaired in perforin-deficient mice. Nature 369, 31–37 (1994).

    Article  Google Scholar 

  63. Smyth, G. K. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, 1–25 (2004).

    Article  Google Scholar 

Download references

Acknowledgements

We thank S. Niggemeyer, S. Jungwirth and J. Riede for animal husbandry. The authors would like to thank L. Bakiri, V. Baracos, Y. Belkaid, R. Medzhitov, G. Superti-Furga, E. Wagner and R. M. Zinkernagel for valuable feedback and discussions. This project has received funding from the European Research Council under the European Union’s Seventh Framework Programme and Horizon 2020 research and innovation program (grant agreement no. 677006, ‘CMIL’ to A.B., no. 340896 and ‘LipoCheX’ to R. Z.) from the German Research Council (grant nos. SFB974, KFO217, LA-2558/5-1 and Jürgen Manchot Graduate School MOI III to P.A.L.), from the Austrian Science Fund (grant no. FWF P26766 to T.S.) and from the US National Institutes of Health (grant nos. R01AI032972, U19AI100627 to A. Aderem). A.L. and M. Smyth are supported by DOC fellowships of the Austrian Academy of Sciences.

Author information

Author notes

  1. These authors contributed equally: Martina Schweiger, Michael Moschinger.

Authors and Affiliations

  1. CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria

    Hatoon Baazim, Michael Moschinger, Alexandra Popa, Kseniya Khamina, Lindsay Kosack, Bojan Vilagos, Mark Smyth, Alexander Lercher & Andreas Bergthaler

  2. Institute of Molecular Biosciences, University of Graz, Graz, Austria

    Martina Schweiger & Rudolf Zechner

  3. Department of Molecular Medicine II, Heinrich Heine University, Düsseldorf, Germany

    Haifeng Xu & Philipp A. Lang

  4. Division of Endocrinology and Metabolism, Department of Medicine III, Medical University of Vienna, Vienna, Austria

    Thomas Scherer

  5. Division of Chronic Inflammation and Cancer, German Cancer Research Center, Heidelberg, Germany

    Suchira Gallage, Adnan Ali & Mathias Heikenwälder

  6. Department of Biomedical Imaging and Image-guided Therapy, Division of Gender and Molecular Imaging, Preclinical Imaging Laboratory, Medical University of Vienna, Vienna, Austria

    Joachim Friske & Thomas H. Helbich

  7. Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland

    Doron Merkler

  8. Center for Global Infectious Disease Research, Seattle Children’s Research Institute, Seattle, WA, USA

    Alan Aderem

Authors
  1. Hatoon Baazim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Martina Schweiger
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael Moschinger
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Haifeng Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Thomas Scherer
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alexandra Popa
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Suchira Gallage
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Adnan Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Kseniya Khamina
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Lindsay Kosack
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Bojan Vilagos
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Mark Smyth
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Alexander Lercher
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Joachim Friske
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Doron Merkler
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Alan Aderem
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Thomas H. Helbich
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Mathias Heikenwälder
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Philipp A. Lang
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Rudolf Zechner
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Andreas Bergthaler
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

H.B. conceived the project, designed and performed experiments, analyzed the data and wrote the manuscript. M. Schweiger, T.S., B.V., A. Aderem and R.Z. contributed to the experimental design, shared reagents and/or contributed to data interpretation. M.M., H.X., K.K., L.K., M. Smyth, A.L. and P.A.L. designed, performed and/or analyzed experiments. A.P. performed the bioinformatic data analyses. S.G., A. Ali and M.H. performed metabolic cage measurements. J.F. and T.H.H. performed MRI. D.M. provided histologic and immunohistochemical staining. A.B. conceived the project, designed experiments, analyzed the data, wrote the manuscript and supervised the project.

Corresponding author

Correspondence to Andreas Bergthaler.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Fig. 1 Characterization of the pathophysiologic changes induced by IAC.

a) Activity, oxygen consumption (VO2) and respiratory exchange ratio (RER) of LCMV-infected mice compared to uninfected controls (n = 10). Data are representative of a single experiment. b) Circulating viral load of LCMV-infected mice, measured using focus-forming assay (n = 4). Data are representative of two independent experiments. c,d) LCMV nuclear protein as measured by qPCR from tissue homogenate of inguinal, gonadal, and interscapular-brown adipose tissue up to 8 days post-infection, and 17 days post-infection (column graph) (n = 5), representative of three independent experiments (c), as well as quadriceps, gastrocnemius and soleus muscles (n = 5) representative of two independent experiments. e-g) RNA expression of myoblast differentiation 1 (MoyD1), and the proteasomal degradation markers Atrogin1 (Fbxo32) and Murf1 (Trim63) in the indicated muscle compartment (n = 5) (p-values: **0.0025, **0.0029, *0.0252, **0.0059 (e), **0.0087, **0.0071 (f), ***0.0003, *0.0295 (g) one-way ANOVA, Bonferroni correction). h) Body weight kinetics of mice infected with a titrated dose of LCMV-Cl13, ranging from 2 × 106 FFU to 2 × 102 FFU (n = 3), (p-values: **** < 0.0001, **0.0021 two-way ANOVA). i) Body weight kinetics of mice infected with high dose LCMV-Cl13 compared to LCMV-ARM (n = 4), (p-values: ****< 0.0001 two-way ANOVA). h-i) data are representative of three independent experiments. j) Body weight kinetics Of LCMV-infected mice after gavage supplementation of indicated diet between 4 and 7 days after infection (n = 4) (p-values: **0.0029, ****< 0.0001, two-way ANOVA) Data are representative of a single experiment. All data shows mean ± s.e.m.

Supplementary Fig. 2 IAC triggers severe adipose tissue remodeling and alters leptin expression and concentration.

a) Inguinal fat pad in LCMV-infected mice at 6 and 8 days post-infection compared to pair-fed mice. Similar results were observed across all experiments using LCMV-infected wild-type mice. b,c) Representative H/E staining taken from inguinal fat pad (b) and gonadal fat pad (c) at 6 and 8 days post-infection compared to uninfected controls (n = 3). d,e) Serum concentration of ghrelin (n = 5) (d) and leptin (n = 6) (e) as measured by ELISA in infected and uninfected mice (p-values: ***0.0002, ****<0.00001 one-way ANOVA, Bonferroni correction). Data are pooled from two independent experiments. f) Leptin (Lep) and Adiponectin (Adipoq) mRNA expression in inguinal fat pad of infected and uninfected mice, calculated from arbitrary units normalized to Ribosomal protein (Rplp0) and body weight (n = 4) (p-values: **0.0018 one-way ANOVA, Bonferroni correction). Data are representative of a single experiment. g,h) Infection of leptin knockout mice (LepOb/Ob) and heterogeneous control (LepOb/+) showing body weight kinetics and food intake (n = 4), representative of two independent experiments (g) and body composition as measured in live un-anesthetized mice using EchoMRI (n = 4), representative of a single experiment (h). d–h) data shows mean ± s.e.m.

Supplementary Fig. 3 The role of infection-induced proinflammatory cytokines and T cells in mediating weight loss during LCMV clone 13 and influenza infection.

a) Serum cytokines of LCMV-infected mice measured using Luminex multiplexing immunoassays (n = 4). Data are representative of a single experiment. b) Percent of initial body weight at 8 days post infection in genetic knockout and neutralizing antibody-treated mice for the indicated cytokines and cytokine receptors (n = 4) (p-values: *0.0122 unpaired two-tailed Student’s t-test). Data shows a summary of figure 2b-2d. c) Circulating viral load as measured using focus-forming assay at 8 days after infection. (n = 5) for antibody depletion and (n = 4) for Ifnar1−/− (p-values: **0.0092, *0.0371, **0.0015 unpaired two-tailed t-test). d) Percent of circulating CD4+ T cells or CD8+ as indicated, following treatment with either CD4 blocking antibody (n = 3) or CD8 blocking antibody (n = 4) respectively. e) Percent of initial body weight of mice treated with either anti-CD4 or anti-CD8 depleting antibodies, as well as CD8−/− (n = 4). f) Splenic viral load as measured with focus-forming assay at 8 days after infection. (n = 3) for anti-CD4 treated mice and (n = 4) for others. c-f) Data are representative of two independent experiments for antibody depletions and Ifnar1−/−, and a single experiment for Ifng−/−, Tnf−/−, TnfrI−/− and Cd8−/−. g,h) Body weight kinetics of WT and Rag2−/− mice infected with LCMV-Cl13 (n = 5) (g) or Influenza PR/8 (n = 4) (h) (p-values: ****< 0.0001 two-way ANOVA). Data are representative of two independent experiments. i) Body weight kinetics and j) food intake of influenza-infected mice compared to pair-fed uninfected mice up to 8 days post-infection (n = 4), data represent a single experiment. Data shows mean ± s.e.m.

Supplementary Fig. 4 Loss of T cell–intrinsic type I IFN signaling abrogates infection-induced adipose tissue lipolysis.

a) Body weight kinetics of Ifnar1fl/flAdipoqCre/+ mice in comparison to Ifnar1fl/fl controls (n = 4) Data are representative of two independent experiments. b, c) FACS analysis of CD8+ T cells in spleen (n = 4) (p-values: ***0.0005, **0.0017, **0.0059, *0.0124 two-way ANOVA, Bonferroni correction) (b) and inguinal LN (n = 4) (p-values: **0.0049 two-way ANOVA, Bonferroni correction) (c), harvested on 6 days post-infection from Ifnar1fl/flCD4Cre/+ and Ifnar1fl/fl controls. Data represents a single experiment. d) Schematic representation of fasting lipolysis, showing circulating cortisol (p-values: **0.0010, *0.137 two-way ANOVA, Bonferroni correction), corticosterone (p-values: ***0.0001, ***0.0004 two-way ANOVA, Bonferroni correction), norepinephrine (p-values: ***0.0004 two-way ANOVA, Bonferroni correction), free T3 (p-values: **0.0036 two-way ANOVA, Bonferroni correction) and free T4 levels, as well as adipose tissue norepinephrine (n = 3). Data are representative of two independent experiments. RNA-seq data (n = 3) shows mRNA expression of β-AR (Abrd2) (p-values: ***0.0001 one way ANOVA, Bonferroni correction), GNAS (p-values: ****< 0.0001, **0.0014 one-way ANOVA, Bonferroni correction), ATGL (Pnpla2), CGI-58 (Abhd5) (p-values: *0.0271, *0.048 one-way ANOVA, Bonferroni correction), G0S2 (G0s2) and HSL (Lipe), in addition to protein expression of ATGL, HSL, pHSL and Perilipin. Western blot data are representative of two independent experiments were (n = 3). Data shows mean ± s.e.m. for bar graphs and (a).

Supplementary Fig. 5 CD8 T cell egress from lymph nodes is dispensable for the induction of IAC, but antigen-specific activation is required.

a–d) Virus-specific CD3+CD8+ T cells of LCMV-infected and uninfected mice after daily gavage administration of either FTY720 or water. Cell were isolated from blood at day 6 (n = 5) (p-values: **** < 0.0001, **0.0083 two-way ANOVA, Bonferroni correction) (a) and day 8 post infection (n = 5) (p-values: ****<0.0001, **0.0013, **0.0012 two-way ANOVA, Bonferroni correction) (b). At day 8 post-infection, cells were also isolated from inguinal LN (n = 5) (p-values: **** < 0.0001, **0.0036, *0.0142 two way ANOVA, Bonferroni correction) (c) and spleen (n = 5) (p-values: ****<0.0001, ***0.0002 two way ANOVA, Bonferroni correction) (d). e, f) Flow cytometry analysis showing the percent of CD8+ T cells carrying CD45.1+ vs CD45.2+ congenic markers after bone marrow reconstitution in indicated chimeras (n = 6) (p-values: ****<0.0001 unpaired two-tailed Student’s t-test). g,h) Percentage and total number of GP33+CD8+ T cells in chimeric mice at 12 days after LCMV infection (n = 6) (p-values: **0.0038, *0.0282 unpaired two-tailed Student’s t-test). e-h) Data are pooled from two independent experiments. All data shows mean ± s.e.m.

Supplementary Fig. 6 Unprocessed images of all western blots.

(left) unprocessed image acquired for indicated antibodies. (right) merge images show the chemo-luminescence image automatically merged with ladder image as acquired using Bio-Rad ChemiDocTM XRS+ system.

Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Supplementary Table 1

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baazim, H., Schweiger, M., Moschinger, M. et al. CD8+ T cells induce cachexia during chronic viral infection. Nat Immunol 20, 701–710 (2019). https://doi.org/10.1038/s41590-019-0397-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41590-019-0397-y

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing