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Stable integrant-specific differences in bimodal HIV-1 expression patterns revealed by high-throughput analysis


Autoři: David F. Read aff001;  Edmond Atindaana aff002;  Kalyani Pyaram aff002;  Feng Yang aff002;  Sarah Emery aff001;  Anna Cheong aff001;  Katherine R. Nakama aff002;  Cleo Burnett aff002;  Erin T. Larragoite aff004;  Emilie Battivelli aff005;  Eric Verdin aff005;  Vicente Planelles aff004;  Cheong-Hee Chang aff002;  Alice Telesnitsky aff002;  Jeffrey M. Kidd aff001
Působiště autorů: Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America aff001;  Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America aff002;  West African Centre for Cell Biology of Infectious Pathogens (WACCBIP) and Department of Biochemistry, Cell & Molecular Biology, University of Ghana, Legon, Greater Accra Region, Ghana aff003;  Department of Pathology, University of Utah, Salt Lake City, Utah, United States of America aff004;  Department of Medicine, University of California San Francisco, San Francisco, California, United States of America aff005;  Buck Institute for Research on Aging, Novato, California, United States of America aff006
Vyšlo v časopise: Stable integrant-specific differences in bimodal HIV-1 expression patterns revealed by high-throughput analysis. PLoS Pathog 15(10): e32767. doi:10.1371/journal.ppat.1007903
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.ppat.1007903

Souhrn

HIV-1 gene expression is regulated by host and viral factors that interact with viral motifs and is influenced by proviral integration sites. Here, expression variation among integrants was followed for hundreds of individual proviral clones within polyclonal populations throughout successive rounds of virus and cultured cell replication, with limited findings using CD4+ cells from donor blood consistent with observations in immortalized cells. Tracking clonal behavior by proviral “zip codes” indicated that mutational inactivation during reverse transcription was rare, while clonal expansion and proviral expression states varied widely. By sorting for provirus expression using a GFP reporter in the nef open reading frame, distinct clone-specific variation in on/off proportions were observed that spanned three orders of magnitude. Tracking GFP phenotypes over time revealed that as cells divided, their progeny alternated between HIV transcriptional activity and non-activity. Despite these phenotypic oscillations, the overall GFP+ population within each clone was remarkably stable, with clones maintaining clone-specific equilibrium mixtures of GFP+ and GFP- cells. Integration sites were analyzed for correlations between genomic features and the epigenetic phenomena described here. Integrants inserted in the sense orientation of genes were more frequently found to be GFP negative than those in the antisense orientation, and clones with high GFP+ proportions were more distal to repressive H3K9me3 peaks than low GFP+ clones. Clones with low frequencies of GFP positivity appeared to expand more rapidly than clones for which most cells were GFP+, even though the tested proviruses were Vpr-. Thus, much of the increase in the GFP- population in these polyclonal pools over time reflected differential clonal expansion. Together, these results underscore the temporal and quantitative variability in HIV-1 gene expression among proviral clones that are conferred in the absence of metabolic or cell-type dependent variability, and shed light on cell-intrinsic layers of regulation that affect HIV-1 population dynamics.

Klíčová slova:

Gene expression – Cell cycle and cell division – HIV-1 – Viral replication – Polymerase chain reaction – Primary cells – Gene pool


Zdroje

1. Finzi D., et al., Identification of a reservoir for HIV-1 in patients on highly active antiretroviral therapy. Science, 1997. 278(5341): p. 1295–300. doi: 10.1126/science.278.5341.1295 9360927

2. Wong J.K., et al., Recovery of replication-competent HIV despite prolonged suppression of plasma viremia. Science, 1997. 278(5341): p. 1291–5. doi: 10.1126/science.278.5341.1291 9360926

3. Chun T.W., et al., Presence of an inducible HIV-1 latent reservoir during highly active antiretroviral therapy. Proc Natl Acad Sci U S A, 1997. 94(24): p. 13193–7. doi: 10.1073/pnas.94.24.13193 9371822

4. Archin N.M., et al., Administration of vorinostat disrupts HIV-1 latency in patients on antiretroviral therapy. Nature, 2012. 487(7408): p. 482–5. doi: 10.1038/nature11286 22837004

5. Deeks S.G., HIV: Shock and kill. Nature, 2012. 487(7408): p. 439–40. 22836995

6. Spivak A.M. and Planelles V., Novel Latency Reversal Agents for HIV-1 Cure. Annu Rev Med, 2018. 69: p. 421–436. doi: 10.1146/annurev-med-052716-031710 29099677

7. Rasmussen T.A. and Lewin S.R., Shocking HIV out of hiding: where are we with clinical trials of latency reversing agents? Curr Opin HIV AIDS, 2016. 11(4): p. 394–401. doi: 10.1097/COH.0000000000000279 26974532

8. Mbonye U. and Karn J., The Molecular Basis for Human Immunodeficiency Virus Latency. Annu Rev Virol, 2017. 4(1): p. 261–285. doi: 10.1146/annurev-virology-101416-041646 28715973

9. Ne E., Palstra R.J., and Mahmoudi T., Transcription: Insights From the HIV-1 Promoter. Int Rev Cell Mol Biol, 2018. 335: p. 191–243. doi: 10.1016/bs.ircmb.2017.07.011 29305013

10. Kaczmarek K., Morales A., and Henderson A.J., T Cell Transcription Factors and Their Impact on HIV Expression. Virology (Auckl), 2013. 2013(4): p. 41–47.

11. Verdin E., Paras P. Jr., and Van Lint C., Chromatin disruption in the promoter of human immunodeficiency virus type 1 during transcriptional activation. EMBO J, 1993. 12(8): p. 3249–59. 8344262

12. Schroder A.R., et al., HIV-1 integration in the human genome favors active genes and local hotspots. Cell, 2002. 110(4): p. 521–9. doi: 10.1016/s0092-8674(02)00864-4 12202041

13. Jordan A., Defechereux P., and Verdin E., The site of HIV-1 integration in the human genome determines basal transcriptional activity and response to Tat transactivation. EMBO J, 2001. 20(7): p. 1726–38. doi: 10.1093/emboj/20.7.1726 11285236

14. Ciuffi A., et al., A role for LEDGF/p75 in targeting HIV DNA integration. Nat Med, 2005. 11(12): p. 1287–9. doi: 10.1038/nm1329 16311605

15. Wong R.W., Mamede J.I., and Hope T.J., Impact of Nucleoporin-Mediated Chromatin Localization and Nuclear Architecture on HIV Integration Site Selection. J Virol, 2015. 89(19): p. 9702–5. doi: 10.1128/JVI.01669-15 26136574

16. Chen H.C., et al., Position effects influence HIV latency reversal. Nat Struct Mol Biol, 2017. 24(1): p. 47–54. doi: 10.1038/nsmb.3328 27870832

17. Lewinski M.K., et al., Genome-wide analysis of chromosomal features repressing human immunodeficiency virus transcription. J Virol, 2005. 79(11): p. 6610–9. doi: 10.1128/JVI.79.11.6610-6619.2005 15890899

18. Sherrill-Mix S., et al., HIV latency and integration site placement in five cell-based models. Retrovirology, 2013. 10: p. 90. doi: 10.1186/1742-4690-10-90 23953889

19. Sunshine S., et al., HIV Integration Site Analysis of Cellular Models of HIV Latency with a Probe-Enriched Next-Generation Sequencing Assay. J Virol, 2016. 90(9): p. 4511–4519. doi: 10.1128/JVI.01617-15 26912621

20. Dahabieh M.S., Battivelli E., and Verdin E., Understanding HIV latency: the road to an HIV cure. Annu Rev Med, 2015. 66: p. 407–21. doi: 10.1146/annurev-med-092112-152941 25587657

21. Anderson E.M. and Maldarelli F., The role of integration and clonal expansion in HIV infection: live long and prosper. Retrovirology, 2018. 15(1): p. 71. doi: 10.1186/s12977-018-0448-8 30352600

22. Mullins J.I. and Frenkel L.M., Clonal Expansion of Human Immunodeficiency Virus-Infected Cells and Human Immunodeficiency Virus Persistence During Antiretroviral Therapy. J Infect Dis, 2017. 215(suppl_3): p. S119–S127. doi: 10.1093/infdis/jiw636 28520966

23. Satou Y., et al., Dynamics and mechanisms of clonal expansion of HIV-1-infected cells in a humanized mouse model. Sci Rep, 2017. 7(1): p. 6913. doi: 10.1038/s41598-017-07307-4 28761140

24. Ho Y.C., et al., Replication-competent noninduced proviruses in the latent reservoir increase barrier to HIV-1 cure. Cell, 2013. 155(3): p. 540–51. doi: 10.1016/j.cell.2013.09.020 24243014

25. Battivelli E., et al., Distinct chromatin functional states correlate with HIV latency reactivation in infected primary CD4(+) T cells. Elife, 2018. 7.

26. Pinzone M.R., et al., Longitudinal HIV sequencing reveals reservoir expression leading to decay which is obscured by clonal expansion. Nat Commun, 2019. 10(1): p. 728. doi: 10.1038/s41467-019-08431-7 30760706

27. Wiegand A., et al., Single-cell analysis of HIV-1 transcriptional activity reveals expression of proviruses in expanded clones during ART. Proc Natl Acad Sci U S A, 2017. 114(18): p. E3659–E3668. doi: 10.1073/pnas.1617961114 28416661

28. Bruner K.M., et al., Defective proviruses rapidly accumulate during acute HIV-1 infection. Nat Med, 2016. 22(9): p. 1043–9. doi: 10.1038/nm.4156 27500724

29. Pollack R.A., et al., Defective HIV-1 Proviruses Are Expressed and Can Be Recognized by Cytotoxic T Lymphocytes, which Shape the Proviral Landscape. Cell Host Microbe, 2017. 21(4): p. 494–506 e4. doi: 10.1016/j.chom.2017.03.008 28407485

30. Lu K., et al., NMR detection of structures in the HIV-1 5'-leader RNA that regulate genome packaging. Science, 2011. 334(6053): p. 242–5. doi: 10.1126/science.1210460 21998393

31. Nolan-Stevaux O., et al., Measurement of Cancer Cell Growth Heterogeneity through Lentiviral Barcoding Identifies Clonal Dominance as a Characteristic of In Vivo Tumor Engraftment. PLoS One, 2013. 8(6): p. e67316. doi: 10.1371/journal.pone.0067316 23840661

32. Dahabieh M.S., et al., A doubly fluorescent HIV-1 reporter shows that the majority of integrated HIV-1 is latent shortly after infection. J Virol, 2013. 87(8): p. 4716–27. doi: 10.1128/JVI.03478-12 23408629

33. Chomont N., et al., HIV reservoir size and persistence are driven by T cell survival and homeostatic proliferation. Nat Med, 2009. 15(8): p. 893–900. doi: 10.1038/nm.1972 19543283

34. Quail M.A., et al., A large genome center’s improvements to the Illumina sequencing system. Nat Methods, 2008. 5(12): p. 1005–10. doi: 10.1038/nmeth.1270 19034268

35. Kircher M., Sawyer S., and Meyer M., Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res, 2012. 40(1): p. e3. doi: 10.1093/nar/gkr771 22021376

36. Serrao E. and Engelman A.N., Sites of retroviral DNA integration: From basic research to clinical applications. Crit Rev Biochem Mol Biol, 2016. 51(1): p. 26–42. doi: 10.3109/10409238.2015.1102859 26508664

37. Hnisz D., et al., Activation of proto-oncogenes by disruption of chromosome neighborhoods. Science, 2016. 351(6280): p. 1454–1458. doi: 10.1126/science.aad9024 26940867

38. Reeder J.E., et al., HIV Tat controls RNA Polymerase II and the epigenetic landscape to transcriptionally reprogram target immune cells. Elife, 2015. 4.

39. Mei J.M., et al., Identification of Staphylococcus aureus virulence genes in a murine model of bacteraemia using signature-tagged mutagenesis. Mol Microbiol, 1997. 26(2): p. 399–407. doi: 10.1046/j.1365-2958.1997.5911966.x 9383163

40. Fennessey C.M., et al., Genetically-barcoded SIV facilitates enumeration of rebound variants and estimation of reactivation rates in nonhuman primates following interruption of suppressive antiretroviral therapy. PLoS Pathog, 2017. 13(5): p. e1006359. doi: 10.1371/journal.ppat.1006359 28472156

41. Bieniasz P. and Telesnitsky A., Multiple, Switchable Protein:RNA Interactions Regulate Human Immunodeficiency Virus Type 1 Assembly. Annu Rev Virol, 2018.

42. Kharytonchyk S., et al., Influence of gag and RRE Sequences on HIV-1 RNA Packaging Signal Structure and Function. J Mol Biol, 2018. 430(14): p. 2066–2079. doi: 10.1016/j.jmb.2018.05.029 29787767

43. Menendez-Arias L., Mutation rates and intrinsic fidelity of retroviral reverse transcriptases. Viruses, 2009. 1(3): p. 1137–65. doi: 10.3390/v1031137 21994586

44. Finzi D., Plaeger S.F., and Dieffenbach C.W., Defective virus drives human immunodeficiency virus infection, persistence, and pathogenesis. Clin Vaccine Immunol, 2006. 13(7): p. 715–21. doi: 10.1128/CVI.00052-06 16829607

45. Re F., et al., Human immunodeficiency virus type 1 Vpr arrests the cell cycle in G2 by inhibiting the activation of p34cdc2-cyclin B. J Virol, 1995. 69(11): p. 6859–64. 7474100

46. Costin J.M., Cytopathic mechanisms of HIV-1. Virol J, 2007. 4: p. 100. doi: 10.1186/1743-422X-4-100 17945027

47. Carter C.C., et al., HIV-1 infects multipotent progenitor cells causing cell death and establishing latent cellular reservoirs. Nat Med, 2010. 16(4): p. 446–51. doi: 10.1038/nm.2109 20208541

48. Hakre S., et al., HIV latency: experimental systems and molecular models. FEMS Microbiol Rev, 2012. 36(3): p. 706–16. doi: 10.1111/j.1574-6976.2012.00335.x 22372374

49. Pace M.J., et al., HIV reservoirs and latency models. Virology, 2011. 411(2): p. 344–54. doi: 10.1016/j.virol.2010.12.041 21284992

50. Tyagi M. and Romerio F., Models of HIV-1 persistence in the CD4+ T cell compartment: past, present and future. Curr HIV Res, 2011. 9(8): p. 579–87. 22211662

51. Zentilin L., et al., Variegation of retroviral vector gene expression in myeloid cells. Gene Ther, 2000. 7(2): p. 153–66. doi: 10.1038/sj.gt.3301057 10673720

52. Kaern M., et al., Stochasticity in gene expression: from theories to phenotypes. Nat Rev Genet, 2005. 6(6): p. 451–64. doi: 10.1038/nrg1615 15883588

53. Coulon A., et al., Eukaryotic transcriptional dynamics: from single molecules to cell populations. Nat Rev Genet, 2013. 14(8): p. 572–84. doi: 10.1038/nrg3484 23835438

54. Battich N., Stoeger T., and Pelkmans L., Control of Transcript Variability in Single Mammalian Cells. Cell, 2015. 163(7): p. 1596–610. doi: 10.1016/j.cell.2015.11.018 26687353

55. Weinberger L.S., et al., Stochastic gene expression in a lentiviral positive-feedback loop: HIV-1 Tat fluctuations drive phenotypic diversity. Cell, 2005. 122(2): p. 169–82. doi: 10.1016/j.cell.2005.06.006 16051143

56. Singh A., et al., Transcriptional bursting from the HIV-1 promoter is a significant source of stochastic noise in HIV-1 gene expression. Biophys J, 2010. 98(8): p. L32–4. doi: 10.1016/j.bpj.2010.03.001 20409455

57. Pocock G.M., et al., Diverse activities of viral cis-acting RNA regulatory elements revealed using multicolor, long-term, single-cell imaging. Mol Biol Cell, 2017. 28(3): p. 476–487. doi: 10.1091/mbc.E16-08-0612 27903772

58. Kok Y.L., et al., Spontaneous reactivation of latent HIV-1 promoters is linked to the cell cycle as revealed by a genetic-insulators-containing dual-fluorescence HIV-1-based vector. Sci Rep, 2018. 8(1): p. 10204. doi: 10.1038/s41598-018-28161-y 29977044

59. Swain P.S., Elowitz M.B., and Siggia E.D., Intrinsic and extrinsic contributions to stochasticity in gene expression. Proc Natl Acad Sci U S A, 2002. 99(20): p. 12795–800. doi: 10.1073/pnas.162041399 12237400

60. Gallastegui E., et al., Chromatin reassembly factors are involved in transcriptional interference promoting HIV latency. J Virol, 2011. 85(7): p. 3187–202. doi: 10.1128/JVI.01920-10 21270164

61. Han Y., et al., Orientation-dependent regulation of integrated HIV-1 expression by host gene transcriptional readthrough. Cell Host Microbe, 2008. 4(2): p. 134–46. doi: 10.1016/j.chom.2008.06.008 18692773

62. Ma Y., Kanakousaki K., and Buttitta L., How the cell cycle impacts chromatin architecture and influences cell fate. Front Genet, 2015. 6: p. 19. doi: 10.3389/fgene.2015.00019 25691891

63. Reveron-Gomez N., et al., Accurate Recycling of Parental Histones Reproduces the Histone Modification Landscape during DNA Replication. Mol Cell, 2018. 72(2): p. 239–249 e5. doi: 10.1016/j.molcel.2018.08.010 30146316

64. Alabert C., et al., Two distinct modes for propagation of histone PTMs across the cell cycle. Genes Dev, 2015. 29(6): p. 585–90. doi: 10.1101/gad.256354.114 25792596

65. Chavez L., Calvanese V., and Verdin E., HIV Latency Is Established Directly and Early in Both Resting and Activated Primary CD4 T Cells. PLoS Pathog, 2015. 11(6): p. e1004955. doi: 10.1371/journal.ppat.1004955 26067822

66. Pace M.J., et al., Directly infected resting CD4+T cells can produce HIV Gag without spreading infection in a model of HIV latency. PLoS Pathog, 2012. 8(7): p. e1002818. doi: 10.1371/journal.ppat.1002818 22911005

67. Yang S., et al., Generation of retroviral vector for clinical studies using transient transfection. Hum Gene Ther, 1999. 10(1): p. 123–32. doi: 10.1089/10430349950019255 10022537

68. Kharytonchyk S., et al., Resolution of Specific Nucleotide Mismatches by Wild-Type and AZT-Resistant Reverse Transcriptases during HIV-1 Replication. Journal of molecular biology, 2016. 428(11): p. 2275–2288. doi: 10.1016/j.jmb.2016.04.005 27075671

69. Keene S.E., King S.R., and Telesnitsky A., 7SL RNA is retained in HIV-1 minimal virus-like particles as an S-domain fragment. Journal of virology, 2010. 84(18): p. 9070–9077. doi: 10.1128/JVI.00714-10 20610725

70. Kim Y.H., et al., PLZF-expressing CD4 T cells show the characteristics of terminally differentiated effector memory CD4 T cells in humans. Eur J Immunol, 2018. 48(7): p. 1255–1257. doi: 10.1002/eji.201747426 29572809

71. Martins L.J., et al., Modeling HIV-1 Latency in Primary T Cells Using a Replication-Competent Virus. AIDS Res Hum Retroviruses, 2016. 32(2): p. 187–93. doi: 10.1089/aid.2015.0106 26171776

72. Maldarelli F., et al., HIV latency. Specific HIV integration sites are linked to clonal expansion and persistence of infected cells. Science, 2014. 345(6193): p. 179–83. 24968937

73. Magoc T. and Salzberg S.L., FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics, 2011. 27(21): p. 2957–63. doi: 10.1093/bioinformatics/btr507 21903629

74. Corman T.H., et al., Introduction to Algorithms, Third Edition. 3rd ed. 2009: The MIT Press. 1312.

75. Consortium E.P., An integrated encyclopedia of DNA elements in the human genome. Nature, 2012. 489(7414): p. 57–74. doi: 10.1038/nature11247 22955616

76. Zhang Y., et al., Model-based analysis of ChIP-Seq (MACS). Genome Biol, 2008. 9(9): p. R137. doi: 10.1186/gb-2008-9-9-r137 18798982

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Hygiena a epidemiológia Infekčné lekárstvo Laboratórium

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PLOS Pathogens


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