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Interferon-mediated reprogramming of membrane cholesterol to evade bacterial toxins

Nature Immunology volume 21, pages 746–755 (2020)Cite this article

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Abstract

Plasma membranes of animal cells are enriched for cholesterol. Cholesterol-dependent cytolysins (CDCs) are pore-forming toxins secreted by bacteria that target membrane cholesterol for their effector function. Phagocytes are essential for clearance of CDC-producing bacteria; however, the mechanisms by which these cells evade the deleterious effects of CDCs are largely unknown. Here, we report that interferon (IFN) signals convey resistance to CDC-induced pores on macrophages and neutrophils. We traced IFN-mediated resistance to CDCs to the rapid modulation of a specific pool of cholesterol in the plasma membrane of macrophages without changes to total cholesterol levels. Resistance to CDC-induced pore formation requires the production of the oxysterol 25-hydroxycholesterol (25HC), inhibition of cholesterol synthesis and redistribution of cholesterol to an esterified cholesterol pool. Accordingly, blocking the ability of IFN to reprogram cholesterol metabolism abrogates cellular protection and renders mice more susceptible to CDC-induced tissue damage. These studies illuminate targeted regulation of membrane cholesterol content as a host defense strategy.

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Fig. 1: IFN signaling mediates resistance to CDCs.
Fig. 2: IFN signals decrease ALO-D4 binding to the plasma membrane.
Fig. 3: IFN signals reprogram cholesterol metabolism to decrease the pool of cholesterol targeted by CDCs.
Fig. 4: Cholesterol synthesis is linked to CDC susceptibility.
Fig. 5: Production of 25HC is required to maintain changes in plasma membrane cholesterol and mediates resistance to CDCs.
Fig. 6: Cholesterol esterification contributes to CDC resistance of macrophages.
Fig. 7: 25HC mediates protection against CDC-induced tissue damage.

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Data availability

All original data are available from the corresponding author upon request.

References

  1. Lange, Y., Swaisgood, M. H., Ramos, B. V. & Steck, T. L. Plasma membranes contain half the phospholipid and 90% of the cholesterol and sphingomyelin in cultured human fibroblasts. J. Biol. Chem. 264, 3786–3793 (1989).

    CAS  PubMed  Google Scholar 

  2. Ikonen, E. Cellular cholesterol trafficking and compartmentalization. Nat. Rev. Mol. Cell Biol. 9, 125–138 (2008).

    Article  CAS  PubMed  Google Scholar 

  3. van Meer, G., Voelker, D. R. & Feigenson, G. W. Membrane lipids: where they are and how they behave. Nat. Rev. Mol. Cell Biol. 9, 112–124 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Luo, J., Yang, H. & Song, B. L. Mechanisms and regulation of cholesterol homeostasis. Nat. Rev. Mol. Cell Biol. 21, 225–245 (2020).

    Article  CAS  PubMed  Google Scholar 

  5. Blanc, M. et al. The transcription factor STAT-1 couples macrophage synthesis of 25-hydroxycholesterol to the interferon antiviral response. Immunity 38, 106–118 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Reboldi, A. et al. 25-hydroxycholesterol suppresses interleukin-1-driven inflammation downstream of type I interferon. Science 345, 679–684 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Dang, E. V., McDonald, J. G., Russell, D. W. & Cyster, J. G. Oxysterol restraint of cholesterol synthesis prevents AIM2 inflammasome activation. Cell 171, 1057–1071 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Araldi, E. et al. Lanosterol modulates TLR4-mediated innate immune responses in macrophages. Cell Rep. 19, 2743–2755 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Blanc, M. et al. Host defense against viral infection involves interferon-mediated down-regulation of sterol biosynthesis. PLoS Biol. 9, e1000598 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. York, A. G. et al. Limiting cholesterol biosynthetic flux spontaneously engages type I IFN signaling. Cell 163, 1716–1729 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Shibata, N. & Glass, C. K. Regulation of macrophage function in inflammation and atherosclerosis. J. Lipid Res. 50 (Suppl.), S277–S281 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Tall, A. R. & Yvan-Charvet, L. Cholesterol, inflammation and innate immunity. Nat. Rev. Immunol. 15, 104–116 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bauman, D. R. et al. 25-hydroxycholesterol secreted by macrophages in response to Toll-like receptor activation suppresses immunoglobulin A production. Proc. Natl Acad. Sci. USA 106, 16764–16769 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Liu, S.-Y. et al. Interferon-inducible cholesterol-25-hydroxylase broadly inhibits viral entry by production of 25-hydroxycholesterol. Immunity 38, 92–105 (2013).

    Article  CAS  PubMed  Google Scholar 

  15. Viard, M. et al. Role of cholesterol in human immunodeficiency virus type 1 envelope protein-mediated fusion with host cells. J. Virol. 76, 11584–11595 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Goluszko, P. & Nowicki, B. Membrane cholesterol: a crucial molecule affecting interactions of microbial pathogens with mammalian cells. Infect. Immun. 73, 7791–7796 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Rawat, S. S. et al. Modulation of entry of enveloped viruses by cholesterol and sphingolipids. Mol. Membr. Biol. 20, 243–254 (2003).

    Article  CAS  PubMed  Google Scholar 

  18. Mazzon, M. & Mercer, J. Lipid interactions during virus entry and infection. Cell. Microbiol. 16, 1493–1502 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Tweten, R. K. Cholesterol-dependent cytolysins, a family of versatile pore-forming toxins. Infect. Immun. 73, 6199–6209 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Tweten, R. K., Hotze, E. M. & Wade, K. R. The unique molecular choreography of giant pore formation by the cholesterol-dependent cytolysins of Gram-positive bacteria. Annu. Rev. Microbiol. 69, 323–340 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Gilbert, R. J. Inactivation and activity of cholesterol-dependent cytolysins: what structural studies tell us. Structure 13, 1097–1106 (2005).

    Article  CAS  PubMed  Google Scholar 

  22. Timmer, A. M. et al. Streptolysin O promotes group A Streptococcus immune evasion by accelerated macrophage apoptosis. J. Biol. Chem. 284, 862–871 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Bhattacharjee, P. & Keyel, P. A. Cholesterol-dependent cytolysins impair pro-inflammatory macrophage responses. Sci. Rep. 8, 6458 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Corrotte, M., Fernandes, M. C., Tam, C. & Andrews, N. W. Toxin pores endocytosed during plasma membrane repair traffic into the lumen of MVBs for degradation. Traffic 13, 483–494 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. McNeil, P. L. & Kirchhausen, T. An emergency response team for membrane repair. Nat. Rev. Mol. Cell Biol. 6, 499–505 (2005).

    Article  CAS  PubMed  Google Scholar 

  26. Romero, M. et al. Intrinsic repair protects cells from pore-forming toxins by microvesicle shedding. Cell Death Differ. 24, 798–808 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Oishi, Y. et al. SREBP1 contributes to resolution of pro-inflammatory TLR4 signaling by reprogramming fatty acid metabolism. Cell Metab. 25, 412–427 (2017).

    Article  CAS  PubMed  Google Scholar 

  28. Stetson, D. B. & Medzhitov, R. Type I interferons in host defense. Immunity 25, 373–381 (2006).

    Article  CAS  PubMed  Google Scholar 

  29. McNab, F., Mayer-Barber, K., Sher, A., Wack, A. & O’Garra, A. Type I interferons in infectious disease. Nat. Rev. Immunol. 15, 87–103 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Takeuchi, O. & Akira, S. Pattern recognition receptors and inflammation. Cell 140, 805–820 (2010).

    Article  CAS  PubMed  Google Scholar 

  31. Woodward, J. J., Iavarone, A. T. & Portnoy, D. A. c-di-AMP secreted by intracellular Listeria monocytogenes activates a host type I interferon response. Science 328, 1703–1705 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Pandey, A. K. et al. NOD2, RIP2 and IRF5 play a critical role in the type I interferon response to Mycobacterium tuberculosis. PLoS Pathog. 5, e1000500 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Gay, A., Rye, D. & Radhakrishnan, A. Switch-like responses of two cholesterol sensors do not require protein oligomerization in membranes. Biophys. J. 108, 1459–1469 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Chakrabarti, R. S. et al. Variability of cholesterol accessibility in human red blood cells measured using a bacterial cholesterol-binding toxin. Elife 6, e23355 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Infante, R. E. & Radhakrishnan, A. Continuous transport of a small fraction of plasma membrane cholesterol to endoplasmic reticulum regulates total cellular cholesterol. Elife 6, e25466 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Endapally, S., Infante, R. E. & Radhakrishnan, A. Monitoring and modulating intracellular cholesterol trafficking using ALOD4, a cholesterol-binding protein. Methods Mol. Biol. 1949, 153–163 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Maxfield, F. R. & Wustner, D. Analysis of cholesterol trafficking with fluorescent probes. Methods Cell Biol. 108, 367–393 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Endapally, S. et al. Molecular discrimination between two conformations of sphingomyelin in plasma membranes. Cell 176, 1040–1053 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. He, C. et al. High-resolution imaging and quantification of plasma membrane cholesterol by NanoSIMS. Proc. Natl Acad. Sci. USA 114, 2000–2005 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. He, C. et al. Macrophages release plasma membrane-derived particles rich in accessible cholesterol. Proc. Natl Acad. Sci. USA 115, E8499–E8508 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Kandutsch, A. A. & Chen, H. W. Regulation of sterol synthesis in cultured cells by oxygenated derivatives of cholesterol. J. Cell Physiol. 85, 415–424 (1975).

    Article  CAS  PubMed  Google Scholar 

  42. Goldstein, J. L., DeBose-Boyd, R. A. & Brown, M. S. Protein sensors for membrane sterols. Cell 124, 35–46 (2006).

    Article  CAS  PubMed  Google Scholar 

  43. Panousis, C. G. & Zuckerman, S. H. Regulation of cholesterol distribution in macrophage-derived foam cells by interferon-γ. J. Lipid Res. 41, 75–83 (2000).

    CAS  PubMed  Google Scholar 

  44. Keyel, P. A., Tkacheva, O. A., Larregina, A. T. & Salter, R. D. Coordinate stimulation of macrophages by microparticles and TLR ligands induces foam cell formation. J. Immunol. 189, 4621–4629 (2012).

    Article  CAS  PubMed  Google Scholar 

  45. Collins, J. L. et al. Identification of a nonsteroidal liver X receptor agonist through parallel array synthesis of tertiary amines. J. Med. Chem. 45, 1963–1966 (2002).

    Article  CAS  PubMed  Google Scholar 

  46. Das, A., Brown, M. S., Anderson, D. D., Goldstein, J. L. & Radhakrishnan, A. Three pools of plasma membrane cholesterol and their relation to cholesterol homeostasis. Elife 3, e02882 (2014).

    Article  PubMed Central  CAS  Google Scholar 

  47. Pike, L. J. Lipid rafts: bringing order to chaos. J. Lipid Res. 44, 655–667 (2003).

    Article  CAS  PubMed  Google Scholar 

  48. Das, D. K., Baker, M. G. & Venugopal, K. Risk factors, microbiological findings and outcomes of necrotizing fasciitis in New Zealand: a retrospective chart review. BMC Infect. Dis. 12, 348 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Arif, N., Yousfi, S. & Vinnard, C. Deaths from necrotizing fasciitis in the United States, 2003–2013. Epidemiol. Infect. 144, 1338–1344 (2016).

    Article  CAS  PubMed  Google Scholar 

  50. Timmins, J. M. et al. Targeted inactivation of hepatic Abca1 causes profound hypoalphalipoproteinemia and kidney hypercatabolism of apoA-I. J. Clin. Invest. 115, 1333–1342 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Sag, D., Cekic, C., Wu, R., Linden, J. & Hedrick, C. C. The cholesterol transporter ABCG1 links cholesterol homeostasis and tumour immunity. Nat. Commun. 6, 6354 (2015).

    Article  CAS  PubMed  Google Scholar 

  52. Divakaruni, A. S. et al. Thiazolidinediones are acute, specific inhibitors of the mitochondrial pyruvate carrier. Proc. Natl Acad. Sci. USA 110, 5422–5427 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Bligh, E. G. & Dyer, W. J. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917 (1959).

    Article  CAS  PubMed  Google Scholar 

  54. Williams, K. J. et al. An essential requirement for the SCAP/SREBP signaling axis to protect cancer cells from lipotoxicity. Cancer Res. 73, 2850–2862 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Argus, J. P. et al. Development and application of FASA, a model for quantifying fatty acid metabolism using stable isotope labeling. Cell Rep. 25, 2919–2934 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. He, C., Fong, L. G., Young, S. G. & Jiang, H. NanoSIMS imaging: an approach for visualizing and quantifying lipids in cells and tissues. J. Investig. Med. 65, 669–672 (2017).

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This research was supported by NIH grants AI093768 (to S.J.B.), HL146358 (to S.J.B. and P.T.), AR073940 (to P.O.S), and HL136543 (to E.J.T.). M.S.L. is supported by Ruth L. Kirschstein National Research Service Award AI007323. The research described was also supported by an NIH/National Center for Advancing Translational Science (NCATS) UCLA CTSI grant (UL1TR001881). We thank S. Young, T. Weston and R.S. Jung for help with protein purification. We thank T. Weston for NanoSIMS sample preparation and SEM imaging. We thank A. Divakaruni for guidance with PFO permeabilization assays. We thank A. Radhakrishnan for ALO-D4 and full-length ALO plasmids. We thank S. Young, A. Hoffmann, Y. Du, R. Sun, T.-T. Wu, J. F. Miller and M. Li for thoughtful discussions.

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Authors and Affiliations

  1. Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, CA, USA

    Quan D. Zhou, Min Sub Lee, Autumn G. York, Robert Damoiseaux & Steven J. Bensinger

  2. Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, P.R. China

    Quan D. Zhou

  3. Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA

    Xun Chi, Wei Yuan Hsieh, Jonathan J. Mkrtchyan, An-Chieh Feng, Viet L. Bui, Eliza B. Kronenberger, Allison E. Daly, Philip O. Scumpia, Stephen T. Smale & Steven J. Bensinger

  4. Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA

    Cuiwen He, Elizabeth J. Tarling & Philip O. Scumpia

  5. Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA

    Autumn G. York

  6. Howard Hughes Medical Institute, Yale University, New Haven, CT, USA

    Autumn G. York

  7. Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA

    Alessandra Ferrari, Xu Xiao & Peter Tontonoz

  8. Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA

    Kevin J. Williams & Peter Tontonoz

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Contributions

S.J.B. conceived the study. Q.D.Z. led the design and execution of experiments. X.C. codesigned and performed all flow cytometry experiments and data analysis. V.L.B., W.Y.H. and J.J.M. contributed to flow cytometry experiments. J.J.M. and M.S.L. contributed to protein purification and staining experiments. Q.D.Z., M.S.L. and R.D. developed and performed live-cell imaging assays. C.H. performed NanoSIMS analysis and contributed to protein purification. J.J.M. and E.B.K. contributed to RNA analysis. W.Y.H. and A.G.Y. performed GC–MS analysis with help from Q.D.Z. and E.B.K. K.J.W. conducted lipidomic studies. X.X., A.F., P.T. and E.J.T. contributed to Abcg1, Abca1 and SCAP KO studies. A.E.D. analyzed gene expression data. A.-C.F., P.O.S., M.S.L. and S.T.S. conceptualized and developed the in vivo SLO challenge assay. W.Y.H. contributed to data visualization. S.J.B., Q.D.Z., W.Y.H., X.C. and P.T. contributed to construction of the manuscript.

Corresponding author

Correspondence to Steven J. Bensinger.

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Extended data

Extended Data Fig. 1 Interferon signaling mediates resistance to cholesterol-dependent cytolysins.

a, Percentage of PI-positive BMDMs treated with TLR1/2 agonist (Pam3CSK4; 50 ng/mL), TLR3 agonist (Poly(I:C); 1 μg/mL), TLR4 agonist (LPS; 50 ng/mL), TLR7 agonist (CL307; 100 nM), TLR9 (ODN1668; 100 nM) agonist, or unstimulated (NT) for 24 h and then challenged with PFO for up to 60 min in the presence of PI. Cells were imaged every 10 min to assess changes in PI incorporation. b, Percentage of PI-positive BMDMs treated with the various concentrations of TLR4 agonist for 24 h and then challenged with PFO for up to 60 min in the presence of PI. Cells were imaged every 7 min to assess changes in PI incorporation. c, Percentage of PI-positive BMDMs treated with IFN-β or IFN-γ (20 ng/mL) for 24 h and then challenged with PFO for 60 min in the presence of PI. d, Percentage of PI-positive BMDMs treated with NOD2 agonist (N-Glycolyl-MDP; 20 μg/ml), STING agonist (2’,3’cGAMP and c-di-GMP; both 2 μg/mL) for 24 h and then challenged with PFO for 60 min in the presence of PI. e, Percentage of PI-positive BMDMs treated with STING ligand for 24 h and then challenged with Streptolysin O (SLO) for 4 h in the presence of PI. f, Percentage of PI-positive BMDMs treated with IFN-β or IFN-γ (20 ng/mL) for 24 h and then challenged with SLO for 4 h in the presence of PI. g, Percentage of PI-positive BMDMs treated with IFN-β or IFN-γ (20 ng/mL) for 24 h and then challenged with ALO for 60 min in the presence of PI. h, Percentage of PI-positive BMDMs treated with IFN-β (100 ng/mL) or TLR1/2 agonist, or IFN-β (100 ng/mL) together with TLR1/2 agonist for 24 h and then challenged with PFO for 60 min in the presence of PI. i, Percentage of PI-positive BMDMs treated with IFN-β (100 ng/mL) or TLR1/2 agonist, or IFN-β (100 ng/mL) together with TLR1/2 agonist for 24 h and then challenged with SLO for 4 h in the presence of PI. Data are representatives of three independent experiments, and are shown as mean ± s.e.m. (n = 3). Statistical significance was determined using an RM one-way ANOVA with Dunnett’s correction (a-g) or a two-way ANOVA with Dunnett’s correction (h, i). ***P<0.001.

Extended Data Fig. 2 IFN signals decrease plasma membrane binding to ALO-D4 protein.

a, Confocal images of neutrophils stimulated with IFN-β or IFN-γ (20 ng/mL) for 6 h, and then stained with fluorescent ALO-D4 and DAPI. b, Violin plots of cellular fluorescent intensity quantified from a (n = 20334, 18546, 16290). c, Confocal images of WT or type I interferon receptor–deficient (IFNAR KO) BMDMs stimulated with TLR3 agonist (1 μg/mL) or IFN-β (20 ng/mL) for 24 h, and then stained with fluorescent ALO-D4 and DAPI. d, Violin plots of cellular fluorescent intensity quantified from c (n = 5543, 6682, 4673, 8231, 5201, 7906). Data are representatives of three independent experiments. Violin plots are shown with median (solid lines in b, d) and 25% and 75% percentiles (dashed lines in b), and statistical significance was determined using a Kruskal-Wallis test with Dunn’s correction. ***P<0.001. Scale bars in a, c represent 50 μm.

Extended Data Fig. 3 IFN signals reprogram cholesterol metabolism to decrease the pool of cholesterol targeted by CDCs.

a, Total cholesterol (nmol/107 cells) from C57BL/6 bone marrow–derived macrophages (BMDMs) stimulated with cGAMP (2 μg/mL), TLR3 agonist (Poly(I:C); 1 μg/mL), or unstimulated (NT) for 48 h. Total cholesterol was determined by GC-MS (n = 4). b, Total plasma membrane cholesterol (normalized to total FAMEs) from C57BL/6 bone marrow–derived macrophages (BMDMs) stimulated with IFN-γ (40 ng/mL) or unstimulated (NT) for 24 h (n = 4). c, Relative Fillipin III fluorescence intensity of plasma membranes of untreated macrophages or macrophages stimulated with IFN-β (20 ng/mL) or IFN-γ (20 ng/mL) for 24 h (n = 32, 38, 34, 42). MβCD-Cholesterol loaded macrophages indicate dynamic range of Fillipin III fluorescence and are included as a positive control. d, Confocal images of BMDM stimulated with IFN-β (20 ng/mL) for 24 h, and then stained with fluorescent ALO-D4 or OlyA and DAPI. Scale bar, 50 μm. e, Violin plots of cellular fluorescent intensity quantified from d (n = 2225, 2021, 2225, 2021). f, Cholera Toxin B staining of BMDM stimulated with IFN-β or IFN-γ (20 ng/mL) for 24 h. Median fluorescence intensity (MFI) are indicated on the left. Data are representative of three (a, d, e, f) independent experiments, three independent samples (c) or from 4 biological replicates (b). Data in a-c are shown as mean ± s.e.m., violin plots in e are shown with median (solid lines). Statistical significance was determined using an unpaired two-tailed Student’s t-test (a, b), a one-way ANOVA with Dunnett’s correction (c), or a two-tailed Mann–Whitney test (e) ***P<0.001.

Extended Data Fig. 4 Cholesterol synthesis is linked to CDC susceptibility.

a, Net synthesized cholesterol (nmol/107 cells) from C57BL/6 bone marrow–derived macrophages (BMDMs) stimulated with cGAMP (2 μg/mL), or unstimulated (NT) for 48 h. Synthesized cholesterol was determined by GC-MS and isotopomer spectral analysis modeling (n = 4). b, Net synthesized cholesterol (nmol/107 cells) from C57BL/6 bone marrow–derived macrophages (BMDMs) stimulated with TLR1/2 agonist (Pam3CSK4; 50 ng/mL), TLR3 agonist (Poly(I:C); 1 μg/mL), TLR4 agonist (LPS; 50 ng/mL), TLR7 agonist (CL307; 100 nM), TLR9 (ODN1668; 100 nM) agonist, or unstimulated (NT) for 48 h. Synthesized cholesterol was determined by GC-MS and isotopomer spectral analysis modeling (n = 4). c, Percentage of PI–positive WT BMDMs treated with Simvastatin (1 μM) for 4 h and then challenged with PFO for 60 min in the presence of PI (n = 3). Data are representative of three independent experiments and are shown as mean + s.e.m. Statistical significance was determined using an unpaired two-tailed Student’s t-test (a), a one-way ANOVA with Dunnett’s correction (b), or a paired two-tailed Student’s t-test (c). ***P<0.001.

Extended Data Fig. 5 Production of 25-hydroxycholesterol is required to maintain changes in plasma membrane cholesterol and mediates resistance to CDCs.

a, Percentage of PI–positive control or CH25H KO BMDMs stimulated with IFNs (20 ng/mL) for 24 h and then challenged with PFO for 60 minutes in the presence of PI. b, Percentage of PI–positive control or CH25H KO BMDMs stimulated with IFNs (20 ng/mL) for 24 h and then challenged with SLO for 2 h in the presence of PI. Data are representative of three independent experiments and are shown as mean + s.e.m. (n = 3) and statistical significance was determined using a two-way ANOVA with Dunnett’s correction. ***P<0.001.

Extended Data Fig. 6 Cholesterol esterification contributes to CDC resistance of macrophages.

a, Quantification (nmol/107 cells) of cholesterol ester species (16:0. 18:1, 20:4) in BMDMs stimulated with TLR3 agonist (1 μg/mL) in FBS or LPDS for 48 h. CE species pool sizes were determined by direct infusion MS. b, Percentage of PI–positive WT BMDMs treated with IFN-β, or IFN-γ (20 ng/mL), or in combination with ACATi 58-035 (4.3 μM) for 24 h and then challenged with PFO for 60 min in the presence of PI. c, Quantification (nmol/107 cells) of total cholesterol ester (CE) in control or CH25H KO BMDMs stimulated with IFN-β (20 ng/mL) or IFN-γ (20 ng/mL) for 48 h. CE pool sizes were determined by direct infusion mass spectrometry. d, Percentage of PI-positive CH25H KO BMDMs treated with ACATi 58-035 (4.3 μM) for 24 h and then challenged PFO for 60 min in the presence of PI. e, Violin plots of cellular fluorescent intensity quantified from control or ABCA1 KO or ABCG1 KO BMDMs stimulated with IFNs (20 ng/mL) for 24 h and then stained with fluorescent ALO-D4 and DAPI (n = 5943, 4126, 5727, 6914, 5740, 7898; n=7201, 7532, 7563, 7417). f, Percentage of PI-positive control or ABCA1 KO BMDMs treated with IFNs (20 ng/mL) for 24 h and then challenged PFO for 60 min in the presence of PI. g, Percentage of PI-positive control or CH25H KO BMDMs treated with LXR agonist GW3965 (1 μM) for 24 h and then challenged PFO for 60 min in the presence of PI. Data are representatives of two (a, c) or three (b, d, e, f, g) independent experiments. Data in a, b, c, d, f and g are shown as mean + s.e.m. (n = 3 in a, b, d, g; n = 4 in c). Violin plots in e are shown with median (solid lines) and 25% and 75% percentiles (dashed lines). Statistical significance was determined using an unpaired two-tailed Student’s t-test (a), a two-way ANOVA with Tukey’s correction (b, c, f, g), a paired two-tailed Student’s t-test (d), or a Kruskal–Wallis test with Dunn’s correction (e). ***P<0.001.

Extended Data Fig. 7 25HC mediates protection to CDC induced tissue damage.

a, Lesion images of control or CH25H KO mice challenged intradermally with SLO (8 kU/mouse) for 48 h. b, Lesion images of vehicle or 25HC pretreated mice challenged intradermally with ALO (20 nM) for 48 h.

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Zhou, Q.D., Chi, X., Lee, M.S. et al. Interferon-mediated reprogramming of membrane cholesterol to evade bacterial toxins. Nat Immunol 21, 746–755 (2020). https://doi.org/10.1038/s41590-020-0695-4

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