Predominance of positive epistasis among drug resistance-associated mutations in HIV-1 protease


Autoři: Tian-hao Zhang aff001;  Lei Dai aff002;  John P. Barton aff003;  Yushen Du aff004;  Yuxiang Tan aff002;  Wenwen Pang aff006;  Arup K. Chakraborty aff007;  James O. Lloyd-Smith aff009;  Ren Sun aff005
Působiště autorů: Molecular Biology Institute, University of California, Los Angeles, CA 90095, USA aff001;  CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China aff002;  Department of Physics and Astronomy, University of California, Riverside, CA 92521, USA aff003;  School of Medicine, ZheJiang University, Hangzhou, 210000, China aff004;  Molecular and Medical Pharmacology, University of California, Los Angeles, CA 90095, USA aff005;  Department of Public Health Laboratory Science, West China School of Public Health, Sichuan University, Chengdu 610041, China aff006;  Institute for Medical Engineering and Science, Departments of Chemical Engineering, Physics, & Chemistry, Massachusetts Institute of Technology, MA 21309, USA aff007;  Ragon Institute of MGH, MIT, & Harvard, Cambridge, MA 21309, USA aff008;  Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA aff009
Vyšlo v časopise: Predominance of positive epistasis among drug resistance-associated mutations in HIV-1 protease. PLoS Genet 16(10): e32767. doi:10.1371/journal.pgen.1009009
Kategorie: Research Article
doi: 10.1371/journal.pgen.1009009

Souhrn

Drug-resistant mutations often have deleterious impacts on replication fitness, posing a fitness cost that can only be overcome by compensatory mutations. However, the role of fitness cost in the evolution of drug resistance has often been overlooked in clinical studies or in vitro selection experiments, as these observations only capture the outcome of drug selection. In this study, we systematically profile the fitness landscape of resistance-associated sites in HIV-1 protease using deep mutational scanning. We construct a mutant library covering combinations of mutations at 11 sites in HIV-1 protease, all of which are associated with resistance to protease inhibitors in clinic. Using deep sequencing, we quantify the fitness of thousands of HIV-1 protease mutants after multiple cycles of replication in human T cells. Although the majority of resistance-associated mutations have deleterious effects on viral replication, we find that epistasis among resistance-associated mutations is predominantly positive. Furthermore, our fitness data are consistent with genetic interactions inferred directly from HIV sequence data of patients. Fitness valleys formed by strong positive epistasis reduce the likelihood of reversal of drug resistance mutations. Overall, our results support the view that strong compensatory effects are involved in the emergence of clinically observed resistance mutations and provide insights to understanding fitness barriers in the evolution and reversion of drug resistance.

Klíčová slova:

Deletion mutation – HIV – HIV-1 – Protease inhibitors – Proteases – Viral evolution – Viral replication – Fitness epistasis


Zdroje

1. Palella FJ Jr, Delaney KM, Moorman AC, Loveless MO, Fuhrer J, Satten GA, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. New England Journal of Medicine. 1998;338(13):853–860. doi: 10.1056/NEJM199803263381301

2. Maggiolo F, Airoldi M, Kleinloog HD, Callegaro A, Ravasio V, Arici C, et al. Effect of adherence to HAART on virologic outcome and on the selection of resistance-conferring mutations in NNRTI-or PI-treated patients. HIV Clinical Trials. 2007;8(5):282–292. doi: 10.1310/hct0805-282 17956829

3. Shafer RW. Rationale and Uses of a Public HIV Drug-Resistance Database. The Journal of Infectious Diseases. 2006;194(Supplement_1):S51–S58. doi: 10.1086/505356 16921473

4. Lin J, Nishino K, Roberts MC, Tolmasky M, Aminov RI, Zhang L. Mechanisms of antibiotic resistance. Frontiers in Microbiology. 2015;6:34. doi: 10.3389/fmicb.2015.00034 25699027

5. Lontok E, Harrington P, Howe A, Kieffer T, Lennerstrand J, Lenz O, et al. Hepatitis C virus drug resistance–associated substitutions: state of the art summary. Hepatology. 2015;62(5):1623–1632. doi: 10.1002/hep.27934 26095927

6. McKimm-Breschkin JL. Resistance of influenza viruses to neuraminidase inhibitors—a review. Antiviral Research. 2000;47(1):1–17. doi: 10.1016/S0166-3542(00)00103-0 10930642

7. Alexander BD, Perfect JR. Antifungal resistance trends towards the year 2000. Drugs. 1997;54(5):657–678. doi: 10.2165/00003495-199754050-00002 9360056

8. Kontoyiannis DP, Lewis RE. Antifungal drug resistance of pathogenic fungi. The Lancet. 2002;359(9312):1135–1144. doi: 10.1016/S0140-6736(02)08162-X

9. on Antimicrobial Resistance R. Tackling drug-resistant infections globally: final report and recommendations. Review on Antimicrobial Resistance; 2016.

10. Forum WE. The Global Risks Report 2018, 13th Edition. World Economic Forum; 2018.

11. Blair JM, Webber MA, Baylay AJ, Ogbolu DO, Piddock LJ. Molecular mechanisms of antibiotic resistance. Nature Reviews Microbiology. 2015;13(1):42. doi: 10.1038/nrmicro3380 25435309

12. Altmann A, Beerenwinkel N, Sing T, Savenkov I, Däumer M, Kaiser R, et al. Improved prediction of response to antiretroviral combination therapy using the genetic barrier to drug resistance. Antiviral Therapy. 2007;12(2):169. 17503659

13. Brenner BG, Wainberg MA. Clinical benefit of dolutegravir in HIV-1 management related to the high genetic barrier to drug resistance. Virus Research. 2017;239:1–9. doi: 10.1016/j.virusres.2016.07.006 27422477

14. Deforche K, Cozzi-Lepri A, Theys K, Clotet B, Camacho RJ, Kjaer J, et al. Modelled in vivo HIV fitness under drug selective pressure and estimated genetic barrier towards resistance are predictive for virological response. Antiviral Therapy. 2008;13(3):399. 18572753

15. Devereux HL, Emery VC, Johnson MA, Loveday C. Replicative fitness in vivo of HIV-1 variants with multiple drug resistance-associated mutations. Journal of Medical Virology. 2001;65(2):218–224. doi: 10.1002/jmv.2023 11536226

16. Andersson DI, Levin BR. The biological cost of antibiotic resistance. Current Opinion in Microbiology. 1999;2(5):489–493. doi: 10.1016/S1369-5274(99)00005-3 10508723

17. Andersson DI, Hughes D. Antibiotic resistance and its cost: is it possible to reverse resistance? Nature Reviews Microbiology. 2010;8(4):260. doi: 10.1038/nrmicro2319 20208551

18. Götte M. The distinct contributions of fitness and genetic barrier to the development of antiviral drug resistance. Current Opinion in Virology. 2012;2(5):644–650. doi: 10.1016/j.coviro.2012.08.004 22964133

19. Mesplède T, Quashie PK, Osman N, Han Y, Singhroy DN, Lie Y, et al. Viral fitness cost prevents HIV-1 from evading dolutegravir drug pressure. Retrovirology. 2013;10(1):22. doi: 10.1186/1742-4690-10-22 23432922

20. Sibley CH, Hyde JE, Sims PF, Plowe CV, Kublin JG, Mberu EK, et al. Pyrimethamine–sulfadoxine resistance in Plasmodium falciparum: what next? Trends in Parasitology. 2001;17(12):570–571. doi: 10.1016/S1471-4922(01)02085-2

21. Zhou J, Price AJ, Halambage UD, James LC, Aiken C. HIV-1 resistance to the capsid-targeting inhibitor PF74 results in altered dependence on host factors required for virus nuclear entry. Journal of Virology. 2015;89(17):9068–9079. doi: 10.1128/JVI.00340-15 26109731

22. Piana S, Carloni P, Rothlisberger U. Drug resistance in HIV-1 protease: flexibility-assisted mechanism of compensatory mutations. Protein Science. 2002;11(10):2393–2402. doi: 10.1110/ps.0206702 12237461

23. Deeks SG, Wrin T, Liegler T, Hoh R, Hayden M, Barbour JD, et al. Virologic and immunologic consequences of discontinuing combination antiretroviral-drug therapy in HIV-infected patients with detectable viremia. New England Journal of Medicine. 2001;344(7):472–480. doi: 10.1056/NEJM200102153440702 11172188

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. Journal of Virology. 2000;74(14):6262–6268. doi: 10.1128/jvi.74.14.6262-6268.2000 10864635

25. Deeks SG, Hoh R, Neilands TB, Liegler T, Aweeka F, Petropoulos CJ, et al. Interruption of treatment with individual therapeutic drug classes in adults with multidrug-resistant HIV-1 infection. Journal of Infectious Diseases. 2005;192(9):1537–1544. doi: 10.1086/496892 16206068

26. Rosenbloom DI, Hill AL, Rabi SA, Siliciano RF, Nowak MA. Antiretroviral dynamics determines HIV evolution and predicts therapy outcome. Nature Medicine. 2012;18(9):1378. doi: 10.1038/nm.2892 22941277

27. Nijhuis M, Schuurman R, De Jong D, Erickson J, Gustchina E, Albert J, et al. Increased fitness of drug resistant HIV-1 protease as a result of acquisition of compensatory mutations during suboptimal therapy. Aids. 1999;13(17):2349–2359. doi: 10.1097/00002030-199912030-00006 10597776

28. zur Wiesch PS, Engelstädter J, Bonhoeffer S. Compensation of fitness costs and reversibility of antibiotic resistance mutations. Antimicrobial Agents and Chemotherapy. 2010;54(5):2085–2095. doi: 10.1128/AAC.01460-09

29. Maisnier-Patin S, Andersson DI. Adaptation to the deleterious effects of antimicrobial drug resistance mutations by compensatory evolution. Research in Microbiology. 2004;155(5):360–369. doi: 10.1016/j.resmic.2004.01.019 15207868

30. Bonhoeffer S, Chappey C, Parkin NT, Whitcomb JM, Petropoulos CJ. Evidence for positive epistasis in HIV-1. Science. 2004;306(5701):1547–1550. doi: 10.1126/science.1101786 15567861

31. Hinkley T, Martins J, Chappey C, Haddad M, Stawiski E, Whitcomb JM, et al. A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase. Nature Genetics. 2011;43(5):487. doi: 10.1038/ng.795 21441930

32. Starr TN, Thornton JW. Epistasis in protein evolution. Protein Science. 2016;25(7):1204–1218. doi: 10.1002/pro.2897 26833806

33. Michalakis Y, Roze D. Epistasis in RNA viruses. Science. 2004;306(5701):1492–1493. doi: 10.1126/science.1106677 15567846

34. Parera M, Perez-Alvarez N, Clotet B, Martínez MA. Epistasis among deleterious mutations in the HIV-1 protease. Journal of Molecular Biology. 2009;392(2):243–250. doi: 10.1016/j.jmb.2009.07.015 19607838

35. Olson CA, Wu NC, Sun R. A comprehensive biophysical description of pairwise epistasis throughout an entire protein domain. Current Biology. 2014;24(22):2643–2651. doi: 10.1016/j.cub.2014.09.072 25455030

36. Bank C, Hietpas RT, Jensen JD, Bolon DN. A systematic survey of an intragenic epistatic landscape. Molecular Biology and Evolution. 2014;32(1):229–238. doi: 10.1093/molbev/msu301 25371431

37. Sarkisyan KS, Bolotin DA, Meer MV, Usmanova DR, Mishin AS, Sharonov GV, et al. Local fitness landscape of the green fluorescent protein. Nature. 2016;533(7603):397. doi: 10.1038/nature17995 27193686

38. Borrell S, Gagneux S. Strain diversity, epistasis and the evolution of drug resistance in Mycobacterium tuberculosis. Clinical Microbiology and Infection. 2011;17(6):815–820. doi: 10.1111/j.1469-0691.2011.03556.x 21682802

39. Trindade S, Sousa A, Xavier KB, Dionisio F, Ferreira MG, Gordo I. Positive epistasis drives the acquisition of multidrug resistance. PLoS Genetics. 2009;5(7):e1000578. doi: 10.1371/journal.pgen.1000578 19629166

40. Silva RF, Mendonça SC, Carvalho LM, Reis AM, Gordo I, Trindade S, et al. Pervasive sign epistasis between conjugative plasmids and drug-resistance chromosomal mutations. PLoS Genetics. 2011;7(7):e1002181. doi: 10.1371/journal.pgen.1002181 21829372

41. Yang WL, Kouyos RD, Böni J, Yerly S, Klimkait T, Aubert V, et al. Persistence of transmitted HIV-1 drug resistance mutations associated with fitness costs and viral genetic backgrounds. PLoS Pathogens. 2015;11(3):e1004722. doi: 10.1371/journal.ppat.1004722 25798934

42. Fragata I, Blanckaert A, Louro MAD, Liberles DA, Bank C. Evolution in the light of fitness landscape theory. Trends in Ecology & Evolution. 2018.

43. Cong Me, Heneine W, García-Lerma JG. The fitness cost of mutations associated with human immunodeficiency virus type 1 drug resistance is modulated by mutational interactions. Journal of Virology. 2007;81(6):3037–3041. doi: 10.1128/JVI.02712-06 17192300

44. Martinez-Picado J, Savara AV, Sutton L, Richard T. Replicative fitness of protease inhibitor-resistant mutants of human immunodeficiency virus type 1. Journal of Virology. 1999;73(5):3744–3752. doi: 10.1128/JVI.73.5.3744-3752.1999 10196268

45. Lv Z, Chu Y, Wang Y. HIV protease inhibitors: a review of molecular selectivity and toxicity. HIV/AIDS (Auckland, NZ). 2015;7:95.

46. Strack PR, Frey MW, Rizzo CJ, Cordova B, George HJ, Meade R, et al. Apoptosis mediated by HIV protease is preceded by cleavage of Bcl-2. Proceedings of the National Academy of Sciences. 1996;93(18):9571–9576. doi: 10.1073/pnas.93.18.9571

47. Gougeon ML. Cell death and immunity: apoptosis as an HIV strategy to escape immune attack. Nature Reviews Immunology. 2003;3(5):392. doi: 10.1038/nri1087 12766761

48. Velazquez-Campoy A, Kiso Y, Freire E. The binding energetics of first-and second-generation HIV-1 protease inhibitors: implications for drug design. Archives of Biochemistry and Biophysics. 2001;390(2):169–175. doi: 10.1006/abbi.2001.2333 11396919

49. Harrigan PR, Hogg RS, Dong WW, Yip B, Wynhoven B, Woodward J, et al. Predictors of HIV drug-resistance mutations in a large antiretroviral-naive cohort initiating triple antiretroviral therapy. The Journal of Infectious Diseases. 2005;191(3):339–347. doi: 10.1086/427192 15633092

50. Lu Z. Second generation HIV protease inhibitors against resistant virus. Expert opinion on drug discovery. 2008;3(7):775–786. doi: 10.1517/17460441.3.7.775 23496220

51. Eshleman SH, Jones D, Galovich J, Paxinos EE, Petropoulos CJ, Jackson JB, et al. Phenotypic drug resistance patterns in subtype A HIV-1 clones with nonnucleoside reverse transcriptase resistance mutations. AIDS Research & Human Retroviruses. 2006;22(3):289–293. doi: 10.1089/aid.2006.22.289

52. De Meyer S, Vangeneugden T, Van Baelen B, De Paepe E, Van Marck H, Picchio G, et al. Resistance profile of darunavir: combined 24-week results from the POWER trials. AIDS Research and Human Retroviruses. 2008;24(3):379–388. doi: 10.1089/aid.2007.0173 18327986

53. Barbour JD, Wrin T, Grant RM, Martin JN, Segal MR, Petropoulos CJ, et al. Evolution of phenotypic drug susceptibility and viral replication capacity during long-term virologic failure of protease inhibitor therapy in human immunodeficiency virus-infected adults. Journal of Virology. 2002;76(21):11104–11112. doi: 10.1128/JVI.76.21.11104-11112.2002 12368352

54. Stoddart CA, Liegler TJ, Mammano F, Linquist-Stepps VD, Hayden MS, Deeks SG, et al. Impaired replication of protease inhibitor-resistant HIV-1 in human thymus. Nature Medicine. 2001;7(6):712. doi: 10.1038/89090 11385509

55. Bangsberg DR, Moss AR, Deeks SG. Paradoxes of adherence and drug resistance to HIV antiretroviral therapy. Journal of Antimicrobial Chemotherapy. 2004;53(5):696–699. doi: 10.1093/jac/dkh162 15044425

56. Condra JH, Schleif WA, Blahy OM, Gabryelski LJ, Graham DJ, Quintero J, et al. In vivo emergence of HIV-1 variants resistant to multiple protease inhibitors; 1995.

57. Dam E, Quercia R, Glass B, Descamps D, Launay O, Duval X, et al. Gag mutations strongly contribute to HIV-1 resistance to protease inhibitors in highly drug-experienced patients besides compensating for fitness loss. PLoS pathogens. 2009;5(3). doi: 10.1371/journal.ppat.1000345

58. Chang MW, Torbett BE. Accessory mutations maintain stability in drug-resistant HIV-1 protease. Journal of molecular biology. 2011;410(4):756–760. doi: 10.1016/j.jmb.2011.03.038 21762813

59. Robinson LH, Myers RE, Snowden BW, Tisdale M, Blair ED. HIV type 1 protease cleavage site mutations and viral fitness: implications for drug susceptibility phenotyping assays. AIDS research and human retroviruses. 2000;16(12):1149–1156. doi: 10.1089/088922200414992 10954890

60. Flynn WF, Chang MW, Tan Z, Oliveira G, Yuan J, Okulicz JF, et al. Deep sequencing of protease inhibitor resistant HIV patient isolates reveals patterns of correlated mutations in Gag and protease. PLoS computational biology. 2015;11(4). doi: 10.1371/journal.pcbi.1004249 25894830

61. Rhee SY, Taylor J, Fessel WJ, Kaufman D, Towner W, Troia P, et al. HIV-1 protease mutations and protease inhibitor cross-resistance. Antimicrobial Agents and Chemotherapy. 2010;54(10):4253–4261. doi: 10.1128/AAC.00574-10 20660676

62. Brenner BG, Routy JP, Petrella M, Moisi D, Oliveira M, Detorio M, et al. Persistence and fitness of multidrug-resistant human immunodeficiency virus type 1 acquired in primary infection. Journal of Virology. 2002;76(4):1753–1761. doi: 10.1128/JVI.76.4.1753-1761.2002 11799170

63. Johnson JA, Li JF, Wei X, Lipscomb J, Irlbeck D, Craig C, et al. Minority HIV-1 drug resistance mutations are present in antiretroviral treatment–naïve populations and associate with reduced treatment efficacy. PLoS Medicine. 2008;5(7):e158. doi: 10.1371/journal.pmed.0050158 18666824

64. Barbour JD, Hecht FM, Wrin T, Liegler TJ, Ramstead CA, Busch MP, et al. Persistence of primary drug resistance among recently HIV-1 infected adults. Aids. 2004;18(12):1683–1689. doi: 10.1097/01.aids.0000131391.91468.ff 15280779

65. Flynn WF, Haldane A, Torbett BE, Levy RM. Inference of epistatic effects leading to entrenchment and drug resistance in HIV-1 protease. Molecular biology and evolution. 2017;34(6):1291–1306. doi: 10.1093/molbev/msx095 28369521

66. Biswas A, Haldane A, Arnold E, Levy RM. Epistasis and entrenchment of drug resistance in HIV-1 subtype B. eLife. 2019;8. doi: 10.7554/eLife.50524

67. Qi H, Olson CA, Wu NC, Ke R, Loverdo C, Chu V, et al. A quantitative high-resolution genetic profile rapidly identifies sequence determinants of hepatitis C viral fitness and drug sensitivity. PLoS Pathogens. 2014;10(4):e1004064. doi: 10.1371/journal.ppat.1004064 24722365

68. Wu NC, Dai L, Olson CA, Lloyd-Smith JO, Sun R. Adaptation in protein fitness landscapes is facilitated by indirect paths. Elife. 2016;5:e16965. doi: 10.7554/eLife.16965 27391790

69. Rhee SY, Liu T, Ravela J, Gonzales MJ, Shafer RW. Distribution of human immunodeficiency virus type 1 protease and reverse transcriptase mutation patterns in 4,183 persons undergoing genotypic resistance testing. Antimicrobial Agents and Chemotherapy. 2004;48(8):3122–3126. doi: 10.1128/AAC.48.8.3122-3126.2004 15273130

70. HIV Databases;. Available from: http://www.hiv.lanl.gov/.

71. Boucher JI, Whitfield TW, Dauphin A, Nachum G, Hollins C III, Zeldovich KB, et al. Constrained mutational sampling of amino acids in HIV-1 protease evolution. Molecular biology and evolution. 2019;36(4):798–810. doi: 10.1093/molbev/msz022 30721995

72. Parera M, Fernandez G, Clotet B, Martinez MA. HIV-1 protease catalytic efficiency effects caused by random single amino acid substitutions. Molecular Biology and Evolution. 2006;24(2):382–387. doi: 10.1093/molbev/msl168 17090696

73. Du Y, Zhang TH, Dai L, Zheng X, Gorin AM, Oishi J, et al. Effects of mutations on replicative fitness and major histocompatibility complex class I binding affinity are among the determinants underlying cytotoxic-T-lymphocyte escape of HIV-1 gag epitopes. mBio. 2017;8(6):e01050–17. doi: 10.1128/mBio.01050-17 29184023

74. Al-Mawsawi LQ, Wu NC, Olson CA, Shi VC, Qi H, Zheng X, et al. High-throughput profiling of point mutations across the HIV-1 genome. Retrovirology. 2014;11(1):124. doi: 10.1186/s12977-014-0124-6 25522661

75. Sanjuan R, Moya A, Elena SF. The contribution of epistasis to the architecture of fitness in an RNA virus. Proceedings of the National Academy of Sciences. 2004;101(43):15376–15379. doi: 10.1073/pnas.0404125101

76. Silander OK, Tenaillon O, Chao L. Understanding the evolutionary fate of finite populations: the dynamics of mutational effects. PLoS Biology. 2007;5(4):e94. doi: 10.1371/journal.pbio.0050094 17407380

77. Dai L, Du Y, Qi H, Wu NC, Lloyd-Smith JO, Sun R. Quantifying the evolutionary potential and constraints of a drug-targeted viral protein. bioRxiv. 2016; p. 078428.

78. Parera M, Martinez MA. Strong epistatic interactions within a single protein. Molecular Biology and Evolution. 2014;31(6):1546–1553. doi: 10.1093/molbev/msu113 24682281

79. Khan AI, Dinh DM, Schneider D, Lenski RE, Cooper TF. Negative epistasis between beneficial mutations in an evolving bacterial population. Science. 2011;332(6034):1193–1196. doi: 10.1126/science.1203801 21636772

80. Elena SF. Little evidence for synergism among deleterious mutations in a nonsegmented RNA virus. Journal of Molecular Evolution. 1999;49(5):703–707. doi: 10.1007/PL00000082 10552052

81. Goepfert PA, Lumm W, Farmer P, Matthews P, Prendergast A, Carlson JM, et al. Transmission of HIV-1 Gag immune escape mutations is associated with reduced viral load in linked recipients. Journal of Experimental Medicine. 2008;205(5):1009–1017. doi: 10.1084/jem.20072457 18426987

82. Sierra S, Dávila M, Lowenstein PR, Domingo E. Response of foot-and-mouth disease virus to increased mutagenesis: influence of viral load and fitness in loss of infectivity. Journal of Virology. 2000;74(18):8316–8323. doi: 10.1128/jvi.74.18.8316-8323.2000 10954530

83. Zhang H, Yang B, Pomerantz RJ, Zhang C, Arunachalam SC, Gao L. The cytidine deaminase CEM15 induces hypermutation in newly synthesized HIV-1 DNA. Nature. 2003;424(6944):94. doi: 10.1038/nature01707 12808465

84. Harris RS, Bishop KN, Sheehy AM, Craig HM, Petersen-Mahrt SK, Watt IN, et al. DNA deamination mediates innate immunity to retroviral infection. Cell. 2003;113(6):803–809. doi: 10.1016/S0092-8674(03)00423-9 12809610

85. Mangeat B, Turelli P, Caron G, Friedli M, Perrin L, Trono D. Broad antiretroviral defence by human APOBEC3G through lethal editing of nascent reverse transcripts. Nature. 2003;424(6944):99. doi: 10.1038/nature01709 12808466

86. Crotty S, Cameron CE, Andino R. RNA virus error catastrophe: direct molecular test by using ribavirin. Proceedings of the National Academy of Sciences. 2001;98(12):6895–6900. doi: 10.1073/pnas.111085598

87. Ferguson AL, Mann JK, Omarjee S, Ndung’u T, Walker BD, Chakraborty AK. Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design. Immunity. 2013;38(3):606–617. doi: 10.1016/j.immuni.2012.11.022 23521886

88. Mann JK, Barton JP, Ferguson AL, Omarjee S, Walker BD, Chakraborty A, et al. The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing. PLOS Computational Biology. 2014;10(8):1–11. doi: 10.1371/journal.pcbi.1003776

89. Butler TC, Barton JP, Kardar M, Chakraborty AK. Identification of drug resistance mutations in HIV from constraints on natural evolution. Physical Review E. 2016;93(2):022412. doi: 10.1103/PhysRevE.93.022412 26986367

90. Louie RH, Kaczorowski KJ, Barton JP, Chakraborty AK, McKay MR. Fitness landscape of the human immunodeficiency virus envelope protein that is targeted by antibodies. Proceedings of the National Academy of Sciences. 2018;115(4):E564–E573.

91. Barton JP, De Leonardis E, Coucke A, Cocco S. ACE: adaptive cluster expansion for maximum entropy graphical model inference. Bioinformatics. 2016;32(20):3089–3097. doi: 10.1093/bioinformatics/btw328 27329863

92. Solis M, Nakhaei P, Jalalirad M, Lacoste J, Douville R, Arguello M, et al. RIG-I-mediated antiviral signaling is inhibited in HIV-1 infection by a protease-mediated sequestration of RIG-I. Journal of Virology. 2011;85(3):1224–1236. doi: 10.1128/JVI.01635-10 21084468

93. Shah P, McCandlish DM, Plotkin JB. Contingency and entrenchment in protein evolution under purifying selection. Proceedings of the National Academy of Sciences. 2015;112(25):E3226–E3235. doi: 10.1073/pnas.1412933112

94. Draghi JA, Plotkin JB. Selection biases the prevalence and type of epistasis along adaptive trajectories. Evolution. 2013;67(11):3120–3131. doi: 10.1111/evo.12192 24151997

95. Kitayimbwa JM, Mugisha JYT, Saenz RA. Estimation of the HIV-1 backward mutation rate from transmitted drug-resistant strains. Theoretical Population Biology. 2016;112:33–42. doi: 10.1016/j.tpb.2016.08.001 27553875

96. Wensing AJ, van de Vijver D, Angarano G, Åsjö B, Balotta C, Boeri E, et al. Prevalence of Drug-Resistant HIV-1 Variants in Untreated Individuals in Europe: Implications for Clinical Management. The Journal of Infectious Diseases. 2005;192(6):958–966. doi: 10.1086/432916 16107947

97. Roberts JD, Bebenek K, Kunkel TA. The accuracy of reverse transcriptase from HIV-1. Science. 1988;242(4882):1171–1173. 2460925

98. Cuevas JM, Geller R, Garijo R, López-Aldeguer J, Sanjuán R. Extremely high mutation rate of HIV-1 in vivo. PLoS Biology. 2015;13(9):e1002251. doi: 10.1371/journal.pbio.1002251 26375597

99. Han TX, Xu XY, Zhang MJ, Peng X, Du LL. Global fitness profiling of fission yeast deletion strains by barcode sequencing. Genome biology. 2010;11(6):R60. doi: 10.1186/gb-2010-11-6-r60 20537132

100. Van Opijnen T, Bodi KL, Camilli A. Tn-seq: high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms. Nature methods. 2009;6(10):767. doi: 10.1038/nmeth.1377 19767758

101. Perelson AS, Neumann AU, Markowitz M, Leonard JM, Ho DD. HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science. 1996;271(5255):1582–1586. doi: 10.1126/science.271.5255.1582 8599114

102. Fernandes JD, Faust TB, Strauli NB, Smith C, Crosby DC, Nakamura RL, et al. Functional segregation of overlapping genes in HIV. Cell. 2016;167(7):1762–1773. doi: 10.1016/j.cell.2016.11.031 27984726

103. Weinberger ED. Fourier and Taylor series on fitness landscapes. Biological cybernetics. 1991;65(5):321–330. doi: 10.1007/BF00216965

104. Uguzzoni G, Lovis SJ, Oteri F, Schug A, Szurmant H, Weigt M. Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis. Proceedings of the National Academy of Sciences. 2017;114(13):E2662–E2671. doi: 10.1073/pnas.1615068114

105. Levy RM, Haldane A, Flynn WF. Potts Hamiltonian models of protein co-variation, free energy landscapes, and evolutionary fitness. Current opinion in structural biology. 2017;43:55–62. doi: 10.1016/j.sbi.2016.11.004 27870991

106. Chen L, Perlina A, Lee CJ. Positive selection detection in 40,000 human immunodeficiency virus (HIV) type 1 sequences automatically identifies drug resistance and positive fitness mutations in HIV protease and reverse transcriptase. Journal of Virology. 2004;78(7):3722–3732. doi: 10.1128/JVI.78.7.3722-3732.2004 15016892

107. He X, Qian W, Wang Z, Li Y, Zhang J. Prevalent positive epistasis in Escherichia coli and Saccharomyces cerevisiae metabolic networks. Nature genetics. 2010;42(3):272. doi: 10.1038/ng.524 20101242

108. Yerly S, Kaiser L, Race E, Bru JP, Clavel F, Perrin L. Transmission of antiretroviral-drug-resistant HIV-1 variants. The Lancet. 1999;354(9180):729–733. https://doi.org/10.1016/S0140-6736(98)12262-6.

109. Bershtein S, Segal M, Bekerman R, Tokuriki N, Tawfik DS. Robustness–epistasis link shapes the fitness landscape of a randomly drifting protein. Nature. 2006;444(7121):929. doi: 10.1038/nature05385 17122770

110. Kellogg EH, Leaver-Fay A, Baker D. Role of conformational sampling in computing mutation-induced changes in protein structure and stability. Proteins: Structure, Function, and Bioinformatics. 2011;79(3):830–838.

111. Barton JP, Goonetilleke N, Butler TC, Walker BD, McMichael AJ, Chakraborty AK. Relative rate and location of intra-host HIV evolution to evade cellular immunity are predictable. Nature Communications. 2016;7:11660. doi: 10.1038/ncomms11660 27212475


Článek vyšel v časopise

PLOS Genetics


2020 Číslo 10

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Přihlášení
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se