The clarifying role of time series data in the population genetics of HIV
Autoři:
Alison F. Feder aff001; Pleuni S. Pennings aff002; Dmitri A. Petrov aff003
Působiště autorů:
Department of Integrative Biology, University of California, Berkeley, Berkeley, California, United States of America
aff001; Department of Biology, San Francisco State University, San Francisco, California, United States of America
aff002; Department of Biology, Stanford University, Stanford, California, United States of America
aff003
Vyšlo v časopise:
The clarifying role of time series data in the population genetics of HIV. PLoS Genet 17(1): e1009050. doi:10.1371/journal.pgen.1009050
Kategorie:
Viewpoints
doi:
https://doi.org/10.1371/journal.pgen.1009050
Souhrn
HIV can evolve remarkably quickly in response to antiretroviral therapies and the immune system. This evolution stymies treatment effectiveness and prevents the development of an HIV vaccine. Consequently, there has been a great interest in using population genetics to disentangle the forces that govern the HIV adaptive landscape (selection, drift, mutation, and recombination). Traditional population genetics approaches look at the current state of genetic variation and infer the processes that can generate it. However, because HIV evolves rapidly, we can also sample populations repeatedly over time and watch evolution in action. In this paper, we demonstrate how time series data can bound evolutionary parameters in a way that complements and informs traditional population genetic approaches. Specifically, we focus on our recent paper (Feder et al., 2016, eLife), in which we show that, as improved HIV drugs have led to fewer patients failing therapy due to resistance evolution, less genetic diversity has been maintained following the fixation of drug resistance mutations. Because soft sweeps of multiple drug resistance mutations spreading simultaneously have been previously documented in response to the less effective HIV therapies used early in the epidemic, we interpret the maintenance of post-sweep diversity in response to poor therapies as further evidence of soft sweeps and therefore a high population mutation rate (θ) in these intra-patient HIV populations. Because improved drugs resulted in rarer resistance evolution accompanied by lower post-sweep diversity, we suggest that both observations can be explained by decreased population mutation rates and a resultant transition to hard selective sweeps. A recent paper (Harris et al., 2018, PLOS Genetics) proposed an alternative interpretation: Diversity maintenance following drug resistance evolution in response to poor therapies may have been driven by recombination during slow, hard selective sweeps of single mutations. Then, if better drugs have led to faster hard selective sweeps of resistance, recombination will have less time to rescue diversity during the sweep, recapitulating the decrease in post-sweep diversity as drugs have improved. In this paper, we use time series data to show that drug resistance evolution during ineffective treatment is very fast, providing new evidence that soft sweeps drove early HIV treatment failure.
Klíčová slova:
DNA recombination – Evolutionary genetics – Evolutionary immunology – HIV – Human genetics – Population genetics – Protease inhibitor therapy – Species diversity
Zdroje
1. Voight BF, Kudaravalli S, Wen X, Pritchard JK. A map of recent positive selection in the human genome. PLoS Biol. 2006;4(3):e72. doi: 10.1371/journal.pbio.0040072 16494531
2. Sabeti PC, Varilly P, Fry B, Lohmueller J, Hostetter E, Cotsapas C, et al. Genome-wide detection and characterization of positive selection in human populations. Nature. 2007;449(7164):913. doi: 10.1038/nature06250 17943131
3. Garud NR, Messer PW, Buzbas EO, Petrov DA. Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps. PLoS Genet. 2015;11(2):e1005004. doi: 10.1371/journal.pgen.1005004 25706129
4. Schrider DR, Kern AD. S/HIC: robust identification of soft and hard sweeps using machine learning. PLoS Genet. 2016;12(3):e1005928. doi: 10.1371/journal.pgen.1005928 26977894
5. Karasov T, Messer PW, Petrov DA. Evidence that adaptation in Drosophila is not limited by mutation at single sites. PLoS Genet. 2010;6(6):e1000924. doi: 10.1371/journal.pgen.1000924 20585551
6. Wilson BA, Petrov DA, Messer PW. Soft selective sweeps in complex demographic scenarios. Genetics. 2014;198:669–84. doi: 10.1534/genetics.114.165571 25060100
7. Khatri BS, Burt A. Robust estimation of recent effective population size from number of independent origins in soft sweeps. bioRxiv. 2018;472266.
8. Pennings PS, Kryazhimskiy S, Wakeley J. Loss and recovery of genetic diversity in adapting populations of HIV. PLoS Genet. 2014;10(1):e1004000. doi: 10.1371/journal.pgen.1004000 24465214
9. Anderson TJ, Nair S, McDew-White M, Cheeseman IH, Nkhoma S, Bilgic F, et al. Population parameters underlying an ongoing soft sweep in southeast Asian malaria parasites. Mol Biol Evol. 2016;34(1):131–44. doi: 10.1093/molbev/msw228 28025270
10. Garud NR, Messer PW, Petrov DA. Detection of hard and soft selective sweeps from Drosophila melanogaster population genomic data. bioRxiv. 2020;.
11. Feder AF, Rhee SY, Holmes SP, Shafer RW, Petrov DA, Pennings PS. More effective drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1. eLife. 2016;5:e10670. doi: 10.7554/eLife.10670 26882502
12. Harris RB, Sackman A, Jensen JD. On the unfounded enthusiasm for soft selective sweeps II: Examining recent evidence from humans, flies, and viruses. PLoS Genet. 2018;14(12):1–21. doi: 10.1371/journal.pgen.1007859 30592709
13. Schuurman R, Nijhuis M, van Leeuwen R, Schipper P, de Jong D, Collis P, et al. Rapid changes in human immunodeficiency virus type 1 RNA load and appearance of drug-resistant virus populations in persons treated with lamivudine (3TC). J Infect Dis. 1995;171(6):1411–9. doi: 10.1093/infdis/171.6.1411 7539472
14. Jain V, Sucupira MC, Bacchetti P, Hartogensis W, Diaz RS, Kallas EG, et al. Differential persistence of transmitted HIV-1 drug resistance mutation classes. J Infect Dis. 2011;203(8):1174–81. doi: 10.1093/infdis/jiq167 21451005
15. Kellam P, Boucher CA, Tijnagel JM, Larder BA. Zidovudine treatment results in the selection of human immunodeficiency virus type 1 variants whose genotypes confer increasing levels of drug resistance. J Gen Virol. 1994;75(2):341–51. doi: 10.1099/0022-1317-75-2-341 7509370
16. Larder BA, Darby G, Richman DD. HIV with reduced sensitivity to zidovudine (AZT) isolated during prolonged therapy. Science. 1989;243(4899):1731–4. doi: 10.1126/science.2467383 2467383
17. Boucher CA, O’Sullivan E, Mulder JW, Ramautarsing C, Kellam P, Darby G, et al. Ordered appearance of zidovudine resistance mutations during treatment of 18 human immunodeficiency virus-positive subjects. J Infect Dis. 1992;165(1):105–10. doi: 10.1093/infdis/165.1.105 1370174
18. Rohatgi A. WebPlotDigitizer. 2011.
19. Abram ME, Ferris AL, Shao W, Alvord WG, Hughes SH. Nature, position, and frequency of mutations made in a single cycle of HIV-1 replication. J Virol. 2010;84(19):9864–78. doi: 10.1128/JVI.00915-10 20660205
20. German Advisory Committee Blood (Arbeitskreis Blut), Subgroup ‘Assessment of Pathogens Transmissible by Blood’. Human Immunodeficiency Virus (HIV). Transfus Med Hemother. 2016;43(3):203–22. doi: 10.1159/000445852 27403093
21. Hermisson J, Pennings PS. Soft sweeps and beyond: understanding the patterns and probabilities of selection footprints under rapid adaptation. Methods Ecol Evol. 2017;8(6):700–16.
22. Barton N. Understanding adaptation in large populations. PLoS Genet. 2010;6(6):e1000987. doi: 10.1371/journal.pgen.1000987 20585547
23. Wainberg MA, Salomon H, Gu Z, Montaner J, Cooley TP, McCaffrey R, et al. Development of HIV-1 resistance to (-) 2’-deoxy-3’-thiacytidine in patients with AIDS or advanced AIDS-related complex. AIDS (London, England). 1995;9(4):351–7. 7540846
24. Frost SD, Nijhuis M, Schuurman R, Boucher CA, Brown AJL. Evolution of lamivudine resistance in human immunodeficiency virus type 1-infected individuals: the relative roles of drift and selection. J Virol. 2000;74(14):6262–8. doi: 10.1128/jvi.74.14.6262-6268.2000 10864635
25. Flys T, Nissley DV, Claasen CW, Jones D, Shi C, Guay LA, et al. Sensitive drug-resistance assays reveal long-term persistence of HIV-1 variants with the K103N nevirapine (NVP) resistance mutation in some women and infants after the administration of single-dose NVP: HIVNET 012. J Infect Dis. 2005;192(1):24–9. doi: 10.1086/430742 15942890
26. Lecossier D, Shulman NS, Morand-Joubert L, Shafer RW, Joly V, Zolopa AR, et al. Detection of minority populations of HIV-1 expressing the K103N resistance mutation in patients failing nevirapine. J Acquir Immune Defic Syndr. 2005;38(1):37–42. doi: 10.1097/00126334-200501010-00007 15608522
27. Palmer S, Boltz V, Maldarelli F, Kearney M, Halvas EK, Rock D, et al. Selection and persistence of non-nucleoside reverse transcriptase inhibitor-resistant HIV-1 in patients starting and stopping non-nucleoside therapy. AIDS. 2006;20(5):701–10. doi: 10.1097/01.aids.0000216370.69066.7f 16514300
28. Hauser A, Mugenyi K, Kabasinguzi R, Bluethgen K, Kuecherer C, Harms G, et al. Detection and quantification of minor human immunodeficiency virus type 1 variants harboring K103N and Y181C resistance mutations in subtype A and D isolates by allele-specific real-time PCR. Antimicrob Agents Chemother. 2009;53(7):2965–73. doi: 10.1128/AAC.01672-08 19433556
29. Rowley CF, Boutwell CL, Lee EJ, MacLeod IJ, Ribaudo HJ, Essex M, et al. Ultrasensitive detection of minor drug-resistant variants for HIV after nevirapine exposure using allele-specific PCR: clinical significance. AIDS Res Hum Retrovir. 2010;26(3):293–300. doi: 10.1089/aid.2009.0082 20334564
30. Ambrose Z, Palmer S, Boltz VF, Kearney M, Larsen K, Polacino P, et al. Suppression of viremia and evolution of human immunodeficiency virus type 1 drug resistance in a macaque model for antiretroviral therapy. J Virol. 2007;81(22):12145–55. doi: 10.1128/JVI.01301-07 17855539
31. Shao W, Kearney M, Maldarelli F, Mellors JW, Stephens RM, Lifson JD, et al. RT-SHIV subpopulation dynamics in infected macaques during anti-HIV therapy. Retrovirology. 2009;6(1):101. doi: 10.1186/1742-4690-6-101 19889213
32. Boltz VF, Ambrose Z, Kearney MF, Shao W, KewalRamani VN, Maldarelli F, et al. Ultrasensitive allele-specific PCR reveals rare preexisting drug-resistant variants and a large replicating virus population in macaques infected with a simian immunodeficiency virus containing human immunodeficiency virus reverse transcriptase. J Virol. 2012;86(23):12525–30. doi: 10.1128/JVI.01963-12 22933296
33. Feder AF, Kline C, Polacino P, Cottrell M, Kashuba AD, Keele BF, et al. A spatio-temporal assessment of simian/human immunodeficiency virus (SHIV) evolution reveals a highly dynamic process within the host. PLoS Pathog. 2017;13(5):e1006358. doi: 10.1371/journal.ppat.1006358 28542550
34. Gillespie JH. Population genetics: a concise guide. JHU Press; 2010.
35. Neher RA, Leitner T. Recombination Rate and Selection Strength in HIV Intra-patient Evolution. PLoS Comput Biol. 2010;6(1):1–7. doi: 10.1371/journal.pcbi.1000660 20126527
36. Nielsen R, Akey JM, Jakobsson M, Pritchard JK, Tishkoff S, Willerslev E. Tracing the peopling of the world through genomics. Nature. 2017;541(7637):302–10. doi: 10.1038/nature21347 28102248
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