Integrated single-cell analysis of multicellular immune dynamics during hyperacute HIV-1 infection

Nature Medicine

Volumn 26, Issue 4, 2020, Pages 511-518

  Kazer, Samuel W ^a,b,c   Aicher, Toby P ^a,b,c   Muema, Daniel M ^d,e   Carroll, Shaina L ^f   Ordovas Montanes, Jose ^a,b,c,g,h   Miao, Vincent N ^a,b,c,i   Tu, Ang A ^a,b,c   Ziegler, Carly G K ^a,b,c,i   Nyquist, Sarah K ^a,b,c,j   Wong, Emily B ^d,i,k,l   Ismail, Nasreen ^e   Dong, Mary ^a   Moodley, Amber ^e   Berger, Bonnie ^a,j   Love, J Christopher ^a,b   Dong, Krista L ^a   Leslie, Alasdair ^d,l   Ndhlovu, Zaza M ^a,d,e,m   Ndung’u, Thumbi ^a,d,e,l,n   Walker, Bruce D ^a,e,m   Shalek, Alex K ^a,b,c,i   more..

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b Massachusetts Institute of Technology   (United States)

^c BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^d AFRICA HEALTH RESEARCH INSTITUTE   (South Africa)

^e UNIVERSITY OF KWAZULU NATAL   (South Africa)

^f UNIVERSITY OF CALIFORNIA   (United States)

^g BOSTON CHILDREN S HOSPITAL   (United States)

^h HARVARD STEM CELL INSTITUTE   (United States)

ⁱ HARVARD MEDICAL SCHOOL   (United States)

^j MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^k MASSACHUSETTS GENERAL HOSPITAL   (United States)

^l UNIVERSITY COLLEGE LONDON   (United Kingdom)

^m HOWARD HUGHES MEDICAL INSTITUTE   (United States)

ⁿ MAX PLANCK INSTITUTE FOR INFECTION BIOLOGY   (Germany)

more..

Author keywords

[No Author keywords available]

Indexed keywords

CXCL9 CHEMOKINE; GAMMA INTERFERON INDUCIBLE PROTEIN 10; INTERFERON; INTERFERON REGULATORY FACTOR 7; INTERLEUKIN 12; INTERLEUKIN 15; INTERLEUKIN 21; INTERLEUKIN 6; INTERLEUKIN 8; STAT1 PROTEIN; TUMOR NECROSIS FACTOR;

ADULT; ARTICLE; CD4 LYMPHOCYTE COUNT; CONTROLLED STUDY; FEMALE; FLOW CYTOMETRY; GENE EXPRESSION; HUMAN; HUMAN CELL; HUMAN IMMUNODEFICIENCY VIRUS 1 INFECTION; IMMUNE RESPONSE; LYMPHOCYTE DIFFERENTIATION; MAJOR HISTOCOMPATIBILITY COMPLEX; MONOCYTE COUNT; NATURAL KILLER CELL; PERIPHERAL BLOOD MONONUCLEAR CELL; PRIORITY JOURNAL; PROSPECTIVE STUDY; PROTEIN EXPRESSION; QUALITATIVE ANALYSIS; SINGLE CELL ANALYSIS; SINGLE CELL RNA SEQ; UPREGULATION; VIRUS DETECTION; VIRUS LOAD; YOUNG ADULT; ACUTE DISEASE; ACUTE PHASE RESPONSE; ADOLESCENT; CELL COMMUNICATION; CELLULAR IMMUNITY; CYTOTOXIC T LYMPHOCYTE; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETICS; HUMAN IMMUNODEFICIENCY VIRUS 1; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; IMMUNOLOGY; LONGITUDINAL STUDY; METABOLISM; MONONUCLEAR CELL; PATHOGENICITY; PATHOLOGY; PHYSIOLOGY; PROCEDURES; SEQUENCE ANALYSIS; SYSTEM ANALYSIS;

ACUTE DISEASE; ACUTE-PHASE REACTION; ADOLESCENT; ADULT; CELL COMMUNICATION; FEMALE; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HIV INFECTIONS; HIV-1; HUMANS; IMMUNITY, CELLULAR; KILLER CELLS, NATURAL; LEUKOCYTES, MONONUCLEAR; LONGITUDINAL STUDIES; SEQUENCE ANALYSIS, RNA; SINGLE-CELL ANALYSIS; SYSTEMS INTEGRATION; T-LYMPHOCYTES, CYTOTOXIC; VIRAL LOAD; YOUNG ADULT;

EID: 85083357023     PISSN: 10788956     EISSN: 1546170X     Source Type: Journal    
DOI: 10.1038/s41591-020-0799-2     Document Type: Article

References (56)

1. Regev, A. et al. The human cell atlas. eLife 6, e27041 (2017).
2. Gomes, T., Teichmann, S. A. & Talavera-López, C. Immunology driven by large-scale single-cell sequencing. Trends Immunol. 40, 1011–1021 (2019).
3. Shalek, A. K. & Benson, M. Single-cell analyses to tailor treatments. Sci. Transl. Med. 9, eaan4730 (2017).
4. Martin-Gayo, E. et al. A reproducibility-based computational framework identifies an inducible, enhanced antiviral state in dendritic cells from HIV-1 elite controllers. Genome Biol. 19, 10 (2018).
5. Ndung’u, T., Dong, K. L., Kwon, D. S. & Walker, B. D. A FRESH approach: combining basic science and social good. Sci. Immunol. 3, eaau2798 (2018).
6. Joint United Nations Programme on HIV/AIDS. UNAIDS Data 2019. (UNAIDS, 2019).
7. Robb, M. & Ananworanich, J. Lessons from acute HIV infection. Curr. Opin. HIV AIDS 11, 555–560 (2016).
8. Fiebig, E. et al. Dynamics of HIV viremia and antibody seroconversion in plasma donors: implications for diagnosis and staging of primary HIV infection. AIDS 17, 1871–1879 (2003).
9. Pijuan-Sala, B., Guibentif, C. & Göttgens, B. Single-cell transcriptional profiling: a window into embryonic cell-type specification. Nat. Rev. Mol. Cell Biol. 19, 399 (2018).
10. Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference methods. Nat. Biotechnol. 37, 547–554 (2019).
11. Wang, T., Li, B., Nelson, C. E. & Nabavi, S. Comparative analysis of differential gene expression analysis tools for single-cell RNA-sequencing data. BMC Bioinformatics 20, 40 (2019).
12. Tirosh, I. & Suvà, M. L. Deciphering human tumor biology by single-cell expression profiling. Annu. Rev. Cancer Biol. 3, 151–166 (2019).
13. Schoggins, J. W. & Rice, C. M. Interferon-stimulated genes and their antiviral effector functions. Curr. Opin. Virol. 1, 519–525 (2011).
14. Corleis, B. et al. Early type I Interferon response induces upregulation of human β-defensin 1 during acute HIV-1 infection. PLoS ONE 12, e0173161 (2017).
15. Vargas-Inchaustegui, D. A. et al. CXCL10 production by human monocytes in response to Leishmania braziliensis infection. Infect. Immun. 78, 301–308 (2010).
16. Luban, J. Innate immune sensing of HIV-1 by dendritic cells. Cell Host Microbe 12, 408–418 (2012).
17. Ng, D. & Gommerman, J. L. The regulation of immune responses by DC derived type I IFN. Front. Immunol. 4, 94 (2013).
18. Kurtulus, S. et al. TIGIT predominantly regulates the immune response via regulatory T cells. J. Clin. Invest. 125, 4053–4062 (2015).
19. Samten, B. CD52 as both a marker and an effector molecule of T cells with regulatory action: identification of novel regulatory T cells. Cell Mol. Immunol. 10, 456–458 (2013).
20. Lugli, E., Marcenaro, E. & Mavilio, D. NK cell subset redistribution during the course of viral infections. Front. Immunol. 5, 390 (2014).
21. Bosinger, S. E. et al. Global genomic analysis reveals rapid control of a robust innate response in SIV-infected sooty mangabeys. J. Clin. Invest. 119, 3556–3572 (2009).
22. Bosinger, S. E. et al. Intact type I interferon production and IRF7 function in sooty mangabeys. PLoS Pathogens 9, e1003597 (2013).
23. O’Brien, M., Manches, O. & Bhardwaj, N. Plasmacytoid dendritic cells in HIV infection. Adv. Exp. Med. Biol. 762, 71–107 (2013).
24. Jiao, Y. et al. Plasma IP-10 is associated with rapid disease progression in early HIV-1 infection. Viral Immunol. 25, 333–337 (2012).
25. Shive, C. L., Jiang, W., Anthony, D. D. & Lederman, M. M. Soluble CD14 is a nonspecific marker of monocyte activation. AIDS 29, 1263–1265 (2015).
26. Athanasiadis, E. I. et al. Single-cell RNA-sequencing uncovers transcriptional states and fate decisions in haematopoiesis. Nat. Commun. 8, 2045 (2017).
27. Matsusaka, T. et al. Transcription factors NF-IL6 and NF-κB synergistically activate transcription of the inflammatory cytokines, interleukin 6 and interleukin 8. Proc. Natl Acad. Sci. USA 90, 10193–10197 (1993).
28. + T cells are detectable in early human immunodeficiency virus type 1 infection. J. Virol. 82, 6767–6771 (2008).
29. Hou, W., Jin, Y.-H., Kang, H. S. & Kim, B. S. Interleukin-6 (IL-6) and IL-17 synergistically promote viral persistence by inhibiting cellular apoptosis and cytotoxic T cell function. J. Virol. 88, 8479–8489 (2014).
30. Sloan, R. D. et al. Productive entry of HIV-1 during cell-to-cell transmission via dynamin-dependent endocytosis. J. Virol. 87, 8110–8123 (2013).
31. Jakubzick, C. V., Randolph, G. J. & Henson, P. M. Monocyte differentiation and antigen-presenting functions. Nat. Rev. Immunol. 17, 349–362 (2017).
32. Gulzar, N. & Copeland, K. F. T. CD8+ T-cells: function and response to HIV infection. Curr. HIV Res. 2, 23–37 (2004).
33. Scully, E. & Alter, G. NK cells in HIV disease. Curr. HIV AIDS Rep. 13, 85–94 (2016).
34. Kaspersen, K. A. et al. Low-grade inflammation is associated with susceptibility to infection in healthy men: results from the Danish blood donor study (DBDS). PLoS ONE 11, e0164220 (2016).
35. + T cells restricted by human leukocyte antigen class II exist during natural HIV infection and exhibit clonal expansion. Immunity 45, 917–930 (2016).
36. Walker, B. D. & Yu, X. G. Unravelling the mechanisms of durable control of HIV-1. Nat. Rev. Immunol. 13, 487–498 (2013).
37. + T cell activation during hyperacute HIV infection impact viral set point. Immunity 43, 591–604 (2015).
38. Reeves, R. K. et al. Antigen-specific NK cell memory in rhesus macaques. Nat. Immunol. 16, 927–932 (2015).
39. Cerwenka, A. & Lanier, L. L. Natural killer cell memory in infection, inflammation and cancer. Nat. Rev. Immunol. 16, 112–123 (2016).
40. Hoffmann, M. et al. Exhaustion of activated CD8 T cells predicts disease progression in primary HIV-1 infection. PLoS Pathogens 12, e1005661 (2016).
41. Dong, K. L. et al. Detection and treatment of Fiebig stage I HIV-1 infection in young at-risk women in South Africa: a prospective cohort study. Lancet HIV 5, e35–e44 (2018).
42. Gierahn, T. M. et al. Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput. Nat. Methods 14, 395–398 (2017).
43. Ordovas-Montanes, J. et al. Allergic inflammatory memory in human respiratory epithelial progenitor cells. Nature 560, 649 (2018).
44. Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies and species. Nat. Biotechnol. 36, 411–420 (2018).
45. Linderman, G. C., Rachh, M., Hoskins, J. G., Steinerberger, S. & Kluger, Y. Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data. Nat. Methods 16, 243 (2019).
46. Gutierrez-Arcelus, M. et al. Lymphocyte innateness defined by transcriptional states reflects a balance between proliferation and effector functions. Nat. Commun. 10, 687 (2019).
47. Villani, A. C. et al. Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science 356, eaah4573 (2017).
48. Kang, H. M. et al. Multiplexed droplet single-cell RNA-sequencing using natural genetic variation. Nat. Biotechnol. 36, 89–94 (2018).
49. Zhang, B. & Horvath, S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, 17 (2005).
50. Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008).
51. Kumar, L. & E. Futschik, M. Mfuzz: a software package for soft clustering of microarray data. Bioinformation 2, 5–7 (2007).
52. Krämer, A., Green, J., Pollard, J. & Tugendreich, S. Causal analysis approaches in ingenuity pathway analysis. Bioinformatics 30, 523–530 (2014).
53. Trombetta, J. J. et al. Preparation of single-cell RNA-seq libraries for next generation sequencing. Curr. Protoc. Mol. Biol. 107, 1–17 (2014).
54. Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).
55. Trapnell, C., Pachter, L. & Salzberg, S. L. TopHat: discovering splice junctions with RNA-seq. Bioinformatics 25, 1105–1111 (2009).
56. Tu, A. A. et al. TCR sequencing paired with massively parallel 3′ RNA-seq reveals clonotypic T cell signatures. Nat. Immunol. 20, 1692–1699 (2019).