Skip to content
1887

Microbial Genomics logo Microbial Genomics

Volume 11, Issue 3

The utility of integrating nanopore sequencing into routine HIV-1 drug resistance surveillance Open Access

Abstract

HIV continues to be a significant global public health concern. In 2022, an estimated 29.8 million people living with HIV received antiretroviral treatment (ART). From this, an estimated 10–15% of individuals living with HIV have drug-resistant strains of the virus. Testing for resistance to antiretroviral drugs is recommended before initiating ART. However, such services are often inaccessible due to costs and the need for complex laboratory infrastructure. The assessment of HIV drug resistance (HIVDR) relies on genotyping sequencing and algorithms to interpret genotypic resistance test results. Genotypic assays involve Sanger sequencing of the reverse transcriptase (), protease () and integrase () genes of circulating RNA in plasma to detect mutations that are known to confer drug resistance. While state-of-the-art sequencing technologies have swept the globe and enhanced our global pandemic response capabilities, they are still sparingly used for HIVDR surveillance. The scale-up of ART, especially in low- and middle-income countries, necessitates the establishment of cheap, expeditious and decentralized methods for HIVDR monitoring. Here, we outline how one low-capital next-generation sequencing platform, namely, nanopore sequencing, could augment efforts in expanding HIVDR surveillance efforts, especially in resource-limited settings. We discuss that because of its versatility, nanopore sequencing can accelerate HIVDR surveillance in conjunction with scaling up ART efforts and outline some of the challenges that need to be considered before its widespread and routine adaptation to detect drug resistance rapidly.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): drug resistance , HIV , nanopore sequencing and next-generation sequencing
Funding
This study was supported by the:
  • Medical Research Council (Award LID DTP MR/N013638/1)
    • Principal Award Recipient: DanielBugembe Lule
  • National Institute of Health (Award R21AI162268)
    • Principal Award Recipient: DamienTully
© 2025 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.001375
2025-03-20
2026-01-13

Metrics

Loading full text...

Full text loading...

/deliver/fulltext/mgen/11/3/mgen001375.html?itemId=/content/journal/mgen/10.1099/mgen.0.001375&mimeType=html&fmt=ahah

References

  1. Dybul M, Attoye T, Baptiste S, Cherutich P, Dabis F et al. The case for an HIV cure and how to get there. Lancet HIV 2021; 8:e51–e58 [View Article] [PubMed]
     [Google Scholar]
  2. Sankaranantham M. HIV - is a cure possible?. Indian J Sex Transm Dis AIDS 2019; 40:1–5 [View Article] [PubMed]
     [Google Scholar]
  3. Bavinton BR, Rodger AJ. Undetectable viral load and HIV transmission dynamics on an individual and population level: where next in the global HIV response?. Curr Opin Infect Dis 2020; 33:20–27 [View Article] [PubMed]
     [Google Scholar]
  4. Brault MA, Spiegelman D, Abdool Karim SS, Vermund SH. Integrating and interpreting findings from the latest treatment as prevention trials. Curr HIV/AIDS Rep 2020; 17:249–258 [View Article] [PubMed]
     [Google Scholar]
  5. Coffin JM. HIV population dynamics in vivo: implications for genetic variation, pathogenesis, and therapy. Science 1995; 267:483–489 [View Article] [PubMed]
     [Google Scholar]
  6. Osterholzer DA, Goldman M. Dolutegravir: a next-generation integrase inhibitor for treatment of HIV infection. Clin Infect Dis 2014; 59:265–271 [View Article] [PubMed]
     [Google Scholar]
  7. Hauser A, Kusejko K, Johnson LF, Günthard HF, Riou J et al. Impact of scaling up dolutegravir on antiretroviral resistance in South Africa: a modeling study. PLoS Med 2020; 17:e1003397 [View Article] [PubMed]
     [Google Scholar]
  8. Salou M, Butel C, Comlan AS, Konou AA, Tegueni K et al. Challenges of scale-up to dolutegravir-based regimens in sub-Saharan Africa. AIDS 2020; 34:783–787 [View Article] [PubMed]
     [Google Scholar]
  9. Siedner MJ, Moorhouse MA, Simmons B, de Oliveira T, Lessells R et al. Reduced efficacy of HIV-1 integrase inhibitors in patients with drug resistance mutations in reverse transcriptase. Nat Commun 2020; 11:5922 [View Article] [PubMed]
     [Google Scholar]
  10. UNAIDS UNAIDS Joint United Nations Programme on HIV/AIDS. Understanding fast-track targets, accelerating action to end the AIDS epidemic by 2030; 2015 https://www.unaids.org/sites/default/files/media_asset/201506_JC2743_Understanding_FastTrack_en.pdf
  11. The World Health Organisation (WHO) HIV drug resistance report; 2021
  12. Crowell TA, Danboise B, Parikh A, Esber A, Dear N et al. Pretreatment and acquired antiretroviral drug resistance among persons living with HIV in four African countries. Clin Infect Dis 2021; 73:e2311–e2322 [View Article] [PubMed]
     [Google Scholar]
  13. Miranda MNS, Pingarilho M, Pimentel V, Martins M do RO, Kaiser R et al. Trends of transmitted and acquired drug resistance in Europe from 1981 to 2019: a comparison between the populations of late presenters and non-late presenters. Front Microbiol 2022; 13:846943 [View Article] [PubMed]
     [Google Scholar]
  14. Mahy M, Stover J, Stanecki K, Stoneburner R, Tassie J-M. Estimating the impact of antiretroviral therapy: regional and global estimates of life-years gained among adults. Sex Transm Infect 2010; 86 Suppl 2:ii67–71 [View Article] [PubMed]
     [Google Scholar]
  15. Organisation, W.H Update of recommendations on first- and second-line antiretroviral regimens; 2024 https://www.who.int/publications/i/item/WHO-CDS-HIV-19.15
  16. Llibre JM, Pulido F, García F, García Deltoro M, Blanco JL et al. Genetic barrier to resistance for dolutegravir. AIDS Rev 2015; 17:56–64 [PubMed]
     [Google Scholar]
  17. Boffito M, Waters L, Cahn P, Paredes R, Koteff J et al. Perspectives on the barrier to resistance for dolutegravir + lamivudine, a two-drug antiretroviral therapy for HIV-1 infection. AIDS Res Hum Retroviruses 2020; 36:13–18 [View Article] [PubMed]
     [Google Scholar]
  18. The World Health Organisation (WHO) HIV drug resistance – brief report 2024; 2024 https://www.who.int/publications/i/item/9789240086319
  19. Temereanca A, Ruta S. Strategies to overcome HIV drug resistance-current and future perspectives. Front Microbiol 2023; 14:1133407
     [Google Scholar]
  20. Inc GS. Gilead Sciences statement on FDA acceptance of new drug application for investigational lenacapavir; 2022 https://www.gilead.com/company/company-statements/2022/gilead-sciences-statement-on-fda-acceptance-of-new-drug-application-for-investigational-lenacapavir
  21. Paik J. Lenacapavir: first approval. Drugs 2022; 82:1499–1504 [View Article]
     [Google Scholar]
  22. Paik J. Correction to: lenacapavir: first approval. Drugs 2023; 83:1061 [View Article] [PubMed]
     [Google Scholar]
  23. Segal-Maurer S, DeJesus E, Stellbrink H-J, Castagna A, Richmond GJ et al. Capsid inhibition with lenacapavir in multidrug-resistant HIV-1 infection. N Engl J Med 2022; 386:1793–1803 [View Article] [PubMed]
     [Google Scholar]
  24. Ogbuagu O, Segal-Maurer S, Ratanasuwan W, Avihingsanon A, Brinson C et al. Efficacy and safety of the novel capsid inhibitor lenacapavir to treat multidrug-resistant HIV: week 52 results of a phase 2/3 trial. Lancet HIV 2023; 10:e497–e505 [View Article] [PubMed]
     [Google Scholar]
  25. Dvory-Sobol H, Shaik N, Callebaut C, Rhee MS. Lenacapavir: a first-in-class HIV-1 capsid inhibitor. Curr Opin HIV AIDS 2022; 17:15–21 [View Article] [PubMed]
     [Google Scholar]
  26. Hitchcock AM, Kufel WD, Dwyer KAM, Sidman EF. Lenacapavir: a novel injectable HIV-1 capsid inhibitor. Int J Antimicrob Agents 2024; 63:107009 [View Article] [PubMed]
     [Google Scholar]
  27. Link JO, Rhee MS, Tse WC, Zheng J, Somoza JR et al. Clinical targeting of HIV capsid protein with a long-acting small molecule. Nature 2020; 584:614–618 [View Article] [PubMed]
     [Google Scholar]
  28. Bester SM, Wei G, Zhao H, Adu-Ampratwum D, Iqbal N et al. Structural and mechanistic bases for a potent HIV-1 capsid inhibitor. Science 2020; 370:360–364 [View Article] [PubMed]
     [Google Scholar]
  29. Markham A. Ibalizumab: first global approval. Drugs 2018; 78:781–785 [View Article]
     [Google Scholar]
  30. Grant PM, Kozal MJ. Fostemsavir: a first-in-class HIV-1 attachment inhibitor. Curr Opin HIV AIDS 2022; 17:32–35 [View Article] [PubMed]
     [Google Scholar]
  31. Spagnuolo V, Castagna A, Lazzarin A. Bictegravir. Curr Opin HIV AIDS 2018; 13:326–333 [View Article]
     [Google Scholar]
  32. Judith S. Biktarvy FDA Approval History. Food and Drug Administration (FDA) Approval History 2024 https://www.drugs.com/history/biktarvy.html
     [Google Scholar]
  33. Urano E, Ablan SD, Mandt R, Pauly GT, Sigano DM et al. Alkyl amine bevirimat derivatives are potent and broadly active HIV-1 maturation inhibitors. Antimicrob Agents Chemother 2016; 60:190–197 [View Article] [PubMed]
     [Google Scholar]
  34. Martin DE, Galbraith H, Schettler J, Ellis C, Doto J. Pharmacokinetic properties and tolerability of bevirimat and atazanavir in healthy volunteers: an open-label, parallel-group study. Clin Ther 2008; 30:1794–1805 [View Article] [PubMed]
     [Google Scholar]
  35. Qian K, Bori ID, Chen C-H, Huang L, Lee K-H. Anti-AIDS agents 90. novel C-28 modified bevirimat analogues as potent HIV maturation inhibitors. J Med Chem 2012; 55:8128–8136 [View Article]
     [Google Scholar]
  36. Smith PF, Ogundele A, Forrest A, Wilton J, Salzwedel K et al. Phase I and II study of the safety, virologic effect, and pharmacokinetics/pharmacodynamics of single-dose 3-o-(3’,3’-dimethylsuccinyl)betulinic acid (bevirimat) against human immunodeficiency virus infection. Antimicrob Agents Chemother 2007; 51:3574–3581 [View Article] [PubMed]
     [Google Scholar]
  37. Matthews RP, Jackson Rudd D, Fillgrove KL, Zhang S, Tomek C et al. A phase 1 study to evaluate the drug interaction between islatravir (MK-8591) and doravirine in adults without HIV. Clin Drug Investig 2021; 41:629–638 [View Article] [PubMed]
     [Google Scholar]
  38. Molina J-M, Yazdanpanah Y, Afani Saud A, Bettacchi C, Chahin Anania C et al. Islatravir in combination with doravirine for treatment-naive adults with HIV-1 infection receiving initial treatment with islatravir, doravirine, and lamivudine: a phase 2b, randomised, double-blind, dose-ranging trial. Lancet HIV 2021; 8:e324–e333 [View Article] [PubMed]
     [Google Scholar]
  39. Matthews RP, Cao Y, Patel M, Weissler VL, Bhattacharyya A et al. Safety and pharmacokinetics of islatravir in individuals with severe renal insufficiency. Antimicrob Agents Chemother 2022; 66:e0093122 [View Article] [PubMed]
     [Google Scholar]
  40. Schürmann D, Rudd DJ, Zhang S, De Lepeleire I, Robberechts M et al. Safety, pharmacokinetics, and antiretroviral activity of islatravir (ISL, MK-8591), a novel nucleoside reverse transcriptase translocation inhibitor, following single-dose administration to treatment-naive adults infected with HIV-1: an open-label, phase 1b, consecutive-panel trial. Lancet HIV 2020; 7:e164–e172 [View Article] [PubMed]
     [Google Scholar]
  41. Zang X, Ankrom W, Kraft WK, Vargo R, Stoch SA et al. Intracellular islatravir-triphosphate half-life supports extended dosing intervals. Antimicrob Agents Chemother 2024; 68:e0045824 [View Article] [PubMed]
     [Google Scholar]
  42. Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci USA 1977; 74:5463–5467 [View Article] [PubMed]
     [Google Scholar]
  43. Derache A, Iwuji CC, Baisley K, Danaviah S, Marcelin A-G et al. Impact of next-generation sequencing defined human immunodeficiency virus pretreatment drug resistance on virological outcomes in the ANRS 12249 treatment-as-prevention trial. Clin Infect Dis 2019; 69:207–214 [View Article] [PubMed]
     [Google Scholar]
  44. Inzaule SC, Hamers RL, Noguera-Julian M, Casadellà M, Parera M et al. Clinically relevant thresholds for ultrasensitive HIV drug resistance testing: a multi-country nested case-control study. Lancet HIV 2018; 5:e638–e646 [View Article] [PubMed]
     [Google Scholar]
  45. Kyeyune F, Gibson RM, Nankya I, Venner C, Metha S et al. Low-frequency drug resistance in HIV-infected ugandans on antiretroviral treatment is associated with regimen failure. Antimicrob Agents Chemother 2016; 60:3380–3397 [View Article] [PubMed]
     [Google Scholar]
  46. Milne RS, Silverman RA, Beck IA, Mckernan-Mullin J, Deng W et al. Minority and majority pretreatment HIV-1 drug resistance associated with failure of first-line nonnucleoside reverse-transcriptase inhibitor antiretroviral therapy in kenyan women. AIDS 2019; 33:941–951 [View Article] [PubMed]
     [Google Scholar]
  47. Eshleman SH, Hackett J Jr, Swanson P, Cunningham SP, Drews B et al. Performance of the celera diagnostics viroseq HIV-1 genotyping system for sequence-based analysis of diverse human immunodeficiency virus type 1 strains. J Clin Microbiol 2004; 42:2711–2717 [View Article] [PubMed]
     [Google Scholar]
  48. Moore HP, Palumbo PJ, Notarte KI, Fogel JM, Cummings V et al. Performance of the applied biosystems HIV-1 genotyping kit with integrase. J Clin Microbiol 2024; 62:e0013624 [View Article] [PubMed]
     [Google Scholar]
  49. Saravanan S, Vidya M, Balakrishnan P, Kumarasamy N, Solomon SS et al. Evaluation of two human immunodeficiency virus-1 genotyping systems: viroseq 2.0 and an in-house method. J Virol Methods 2009; 159:211–216 [View Article] [PubMed]
     [Google Scholar]
  50. Manyana S, Gounder L, Pillay M, Manasa J, Naidoo K et al. HIV-1 drug resistance genotyping in resource limited settings: current and future perspectives in sequencing technologies. Viruses 2021; 13:1125 [View Article] [PubMed]
     [Google Scholar]
  51. Frank M, Prenzler A, Eils R, Graf von der Schulenburg J-M. Genome sequencing: a systematic review of health economic evidence. Health Econ Rev 2013; 3:29 [View Article] [PubMed]
     [Google Scholar]
  52. Ávila-Ríos S, Parkin N, Swanstrom R, Paredes R, Shafer R et al. Next-generation sequencing for HIV drug resistance testing: laboratory, clinical, and implementation considerations. Viruses 2020; 12:617 [View Article] [PubMed]
     [Google Scholar]
  53. Wright IA, Delaney KE, Katusiime MGK, Botha JC, Engelbrecht S et al. NanoHIV: a bioinformatics pipeline for producing accurate, near full-length HIV proviral genomes sequenced using the Oxford Nanopore technology. Cells 2021; 10:10 [View Article] [PubMed]
     [Google Scholar]
  54. Lee ER, Parkin N, Jennings C, Brumme CJ, Enns E et al. Performance comparison of next generation sequencing analysis pipelines for HIV-1 drug resistance testing. Sci Rep 2020; 10:1634 [View Article] [PubMed]
     [Google Scholar]
  55. Park SY, Faraci G, Ganesh K, Dubé MP, Lee HY. Portable nanopore sequencing solution for next-generation HIV drug resistance testing. J Clin Virol 2024; 171:105639 [View Article] [PubMed]
     [Google Scholar]
  56. Delaney KE, Ngobeni T, Woods CK, Gordijn C, Claassen M et al. Nano-recall provides an integrated pipeline for HIV-1 drug resistance testing from oxford nanopore sequence data. Trop Med Int Health 2023; 28:186–193 [View Article] [PubMed]
     [Google Scholar]
  57. Su J, Li S, Zheng Z, Lam T-W, Luo R. ClusterV-Web: a user-friendly tool for profiling HIV quasispecies and generating drug resistance reports from nanopore long-read data. Bioinform Adv 2024; 4:vbae006 [View Article]
     [Google Scholar]
  58. Tzou PL, Ariyaratne P, Varghese V, Lee C, Rakhmanaliev E et al. Comparison of an in vitro diagnostic next-generation sequencing assay with sanger sequencing for HIV-1 genotypic resistance testing. J Clin Microbiol 2018; 56:e00105-18 [View Article] [PubMed]
     [Google Scholar]
  59. Ode H, Matsuda M, Shigemi U, Mori M, Yamamura Y et al. Population-based nanopore sequencing of the HIV-1 pangenome to identify drug resistance mutations. Sci Rep 2024; 14:12099 [View Article]
     [Google Scholar]
  60. Ji H, Sandstrom P, Paredes R, Harrigan PR, Brumme CJ et al. Are we ready for NGS HIV drug resistance testing? the second "Winnipeg Consensus" symposium. Viruses 2020; 12:586 [View Article] [PubMed]
     [Google Scholar]
  61. Fine SM. HIV Resistance Assays Baltimore (MD); 2023
     [Google Scholar]
  62. Parkin N, Harrigan PR, Inzaule S, Bertagnolio S. Need assessment for HIV drug resistance testing and landscape of current and future technologies in low- and middle-income countries. PLoS Glob Public Health 2023; 3:e0001948 [View Article] [PubMed]
     [Google Scholar]
  63. Jain M, Olsen HE, Paten B, Akeson M. The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biol 2016; 17:239 [View Article]
     [Google Scholar]
  64. Lu H, Giordano F, Ning Z. Oxford Nanopore MinION sequencing and genome assembly. Genom Proteomic Bioinform 2016; 14:265–279 [View Article] [PubMed]
     [Google Scholar]
  65. Akeson M, Branton D, Kasianowicz JJ, Brandin E, Deamer DW. Microsecond time-scale discrimination among polycytidylic acid, polyadenylic acid, and polyuridylic acid as homopolymers or as segments within single RNA molecules. Biophys J 1999; 77:3227–3233 [View Article] [PubMed]
     [Google Scholar]
  66. Kasianowicz JJ, Brandin E, Branton D, Deamer DW. Characterization of individual polynucleotide molecules using a membrane channel. Proc Natl Acad Sci USA 1996; 93:13770–13773 [View Article] [PubMed]
     [Google Scholar]
  67. Castro-Wallace SL, Chiu CY, John KK, Stahl SE, Rubins KH et al. Nanopore DNA sequencing and genome assembly on the International Space Station. Sci Rep 2017; 7:18022 [View Article] [PubMed]
     [Google Scholar]
  68. Goordial J, Altshuler I, Hindson K, Chan-Yam K, Marcolefas E et al. In situ field sequencing and life detection in remote (79°26’N) Canadian High Arctic permafrost ice wedge microbial communities. Front Microbiol 2017; 8:2594 [View Article] [PubMed]
     [Google Scholar]
  69. Quick J, Grubaugh ND, Pullan ST, Claro IM, Smith AD et al. Multiplex PCR method for MinION and Illumina sequencing of Zika and other virus genomes directly from clinical samples. Nat Protoc 2017; 12:1261–1276 [View Article] [PubMed]
     [Google Scholar]
  70. Quick J, Loman NJ, Duraffour S, Simpson JT, Severi E et al. Real-time, portable genome sequencing for Ebola surveillance. Nature 2016; 530:228–232 [View Article] [PubMed]
     [Google Scholar]
  71. Avershina E, Frye SA, Ali J, Taxt AM, Ahmad R. Ultrafast and cost-effective pathogen identification and resistance gene detection in a clinical setting using nanopore Flongle sequencing. Front Microbiol 2022; 13:822402 [View Article] [PubMed]
     [Google Scholar]
  72. Andrade M de S, Campos FS, Campos AAS, Abreu FVS, Melo FL et al. Real-time genomic surveillance during the 2021 re-emergence of the yellow fever virus in Rio Grande do Sul state, Brazil. Viruses 2021; 13:10 [View Article] [PubMed]
     [Google Scholar]
  73. Kafetzopoulou LE, Pullan ST, Lemey P, Suchard MA, Ehichioya DU et al. Metagenomic sequencing at the epicenter of the Nigeria 2018 Lassa fever outbreak. Science 2019; 363:74–77 [View Article] [PubMed]
     [Google Scholar]
  74. Charalampous T, Alcolea-Medina A, Snell LB, Alder C, Tan M et al. Routine metagenomics service for ICU patients with respiratory infection. Am J Respir Crit Care Med 2024; 209:164–174 [View Article] [PubMed]
     [Google Scholar]
  75. Parkin N, Bremer J, Bertagnolio S. Genotyping external quality assurance in the World Health Organization HIV drug resistance laboratory network during 2007-2010. Clin Infect Dis 2012; 54 Suppl 4:S266–72 [View Article] [PubMed]
     [Google Scholar]
  76. Mbiva F, Tweya H, Satyanarayana S, Takarinda K, Timire C et al. Long turnaround times in viral load monitoring of people living with HIV in resource-limited settings. J Glob Infect Dis 2021; 13:85–90 [View Article] [PubMed]
     [Google Scholar]
  77. Vereecke N, Bokma J, Haesebrouck F, Nauwynck H, Boyen F et al. High quality genome assemblies of Mycoplasma bovis using a taxon-specific Bonito basecaller for MinION and Flongle long-read nanopore sequencing. BMC Bioinf 2020; 21:517 [View Article] [PubMed]
     [Google Scholar]
  78. Zheng P, Zhou C, Ding Y, Liu B, Lu L et al. Nanopore sequencing technology and its applications. MedComm 2023; 4:e316 [View Article]
     [Google Scholar]
  79. Dirlikov E, Kamoga J, Talisuna SA, Namusobya J, Kasozi DE et al. Scale-up of HIV antiretroviral therapy and estimation of averted infections and HIV-related deaths - Uganda, 2004-2022. MMWR Morb Mortal Wkly Rep 2023; 72:90–94 [View Article] [PubMed]
     [Google Scholar]
  80. Chun HM, Dirlikov E, Cox MH, Sherlock MW, Obeng-Aduasare Y et al. Vital signs: progress toward eliminating HIV as a global public health threat through scale-up of antiretroviral therapy and health system strengthening supported by the U.S. President's Emergency Plan for AIDS Relief - worldwide, 2004-2022. MMWR Morb Mortal Wkly Rep 2023; 72:317–324 [View Article] [PubMed]
     [Google Scholar]
  81. Dirlikov E. Rapid scale-up of an antiretroviral therapy program before and during the COVID-19 pandemic - nine states. MMWR Morb Mortal Wkly Rep 2019; 70:421–426
     [Google Scholar]
  82. Boyd AT, Ogbanufe O, Onyenuobi C, Mgbakor I, Bachanas P et al. Scale-up of antiretroviral treatment access among people living with HIV in Rivers State, Nigeria, 2019--2020. AIDS 2021; 35:1127–1134 [View Article]
     [Google Scholar]
  83. Bekker L-G, Alleyne G, Baral S, Cepeda J, Daskalakis D et al. Advancing global health and strengthening the HIV response in the era of the Sustainable Development Goals: the International AIDS Society—Lancet Commission. The Lancet 2018; 392:312–358 [View Article]
     [Google Scholar]
  84. Aleman S, Söderbärg K, Visco-Comandini U, Sitbon G, Sönnerborg A. Drug resistance at low viraemia in HIV-1-infected patients with antiretroviral combination therapy. AIDS 2002; 16:1039–1044 [View Article]
     [Google Scholar]
  85. Eron JJ, Cooper DA, Steigbigel RT, Clotet B, Gatell JM et al. Efficacy and safety of raltegravir for treatment of HIV for 5 years in the BENCHMRK studies: final results of two randomised, placebo-controlled trials. Lancet Infect Dis 2013; 13:587–596 [View Article] [PubMed]
     [Google Scholar]
  86. Laprise C, de Pokomandy A, Baril J-G, Dufresne S, Trottier H. Virologic failure following persistent low-level viremia in a cohort of HIV-positive patients: results from 12 years of observation. Clin Infect Dis 2013; 57:1489–1496 [View Article]
     [Google Scholar]
  87. Aldous JL, Haubrich RH. Defining treatment failure in resource-rich settings. Curr Opin HIV AIDS 2009; 4:459–466 [View Article] [PubMed]
     [Google Scholar]
  88. Havlir D, Lockman S, Ayles H, Larmarange J, Chamie G et al. What do the universal test and treat trials tell us about the path to HIV epidemic control?. J Intern AIDS Soc 2020; 23:e25455 [View Article]
     [Google Scholar]
  89. Havlir DV, Balzer LB, Charlebois ED, Clark TD, Kwarisiima D et al. HIV testing and treatment with the use of a community health approach in rural Africa. N Engl J Med 2019; 381:219–229 [View Article]
     [Google Scholar]
  90. Boeke C, Khan S, Walsh F, Hettema A, Lejeune C et al. Universal test and treat in relation to HIV disease progression: results from a stepped‐wedge trial in Eswatini. HIV Medicine 2021; 22:54–59 [View Article]
     [Google Scholar]
  91. Gardner EM, McLees MP, Steiner JF, Del Rio C, Burman WJ. The spectrum of engagement in HIV care and its relevance to test-and-treat strategies for prevention of HIV infection. Clin Infect Dis 2011; 52:793–800 [View Article] [PubMed]
     [Google Scholar]
  92. Girum T, Yasin F, Wasie A, Shumbej T, Bekele F et al. The effect of “universal test and treat” program on HIV treatment outcomes and patient survival among a cohort of adults taking antiretroviral treatment (ART) in low income settings of Gurage zone, South Ethiopia. AIDS Res Ther 2020; 17:19 [View Article] [PubMed]
     [Google Scholar]
  93. Tesfaye B, Ermias D, Moges S, Astatkie A. Effect of the test and treat strategy on mortality among HIV-positive adult clients on antiretroviral treatment in public hospitals of Addis Ababa, Ethiopia. HIV AIDS 2021; 13:349–360 [View Article] [PubMed]
     [Google Scholar]
  94. Fogel JM, Bonsall D, Cummings V, Bowden R, Golubchik T et al. Performance of a high-throughput next-generation sequencing method for analysis of HIV drug resistance and viral load. J Antimicrob Chemother 2020; 75:3510–3516 [View Article] [PubMed]
     [Google Scholar]
  95. Omooja J, Bbosa N, Lule DB, Nannyonjo M, Lunkuse S et al. HIV-1 drug resistance genotyping success rates and correlates of dried-blood spots and plasma specimen genotyping failure in a resource-limited setting. BMC Infect Dis 2022; 22:474 [View Article] [PubMed]
     [Google Scholar]
  96. Basapathi Raghavendra J, Zorzano M-P, Kumaresan D, Martin-Torres J. DNA sequencing at the picogram level to investigate life on Mars and Earth. Sci Rep 2023; 13:15277 [View Article] [PubMed]
     [Google Scholar]
  97. Ng TT-L, Su J, Lao H-Y, Lui W-W, Chan CT-M et al. Long-read sequencing with hierarchical clustering for antiretroviral resistance profiling of mixed human immunodeficiency virus quasispecies. Clin Chem 2023; 69:1174–1185 [View Article] [PubMed]
     [Google Scholar]
  98. Wensing AM, Calvez V, Ceccherini-Silberstein F, Charpentier C, Günthard HF et al. 2022 update of the drug resistance mutations in HIV-1. Top Antivir Med 2022; 30:559–574 [PubMed]
     [Google Scholar]
  99. Taylor T, Lee ER, Nykoluk M, Enns E, Liang B et al. A MiSeq-HyDRA platform for enhanced HIV drug resistance genotyping and surveillance. Sci Rep 2019; 9:8970 [View Article] [PubMed]
     [Google Scholar]
  100. Dudley DM, Chin EN, Bimber BN, Sanabani SS, Tarosso LF et al. Low-cost ultra-wide genotyping using Roche/454 pyrosequencing for surveillance of HIV drug resistance. PLoS One 2012; 7:e36494 [View Article] [PubMed]
     [Google Scholar]
  101. Huang YT, Liu PY, Shih PW. Homopolish: a method for the removal of systematic errors in nanopore sequencing by homologous polishing. Genome Biol 2021; 22:95 [View Article] [PubMed]
     [Google Scholar]
  102. Hu J, Fan J, Sun Z, Liu S. NextPolish: a fast and efficient genome polishing tool for long-read assembly. Bioinformatics 2020; 36:2253–2255 [View Article] [PubMed]
     [Google Scholar]
  103. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 2017; 27:722–736 [View Article] [PubMed]
     [Google Scholar]
  104. Firtina C, Kim JS, Alser M, Senol Cali D, Cicek AE et al. Apollo: a sequencing-technology-independent, scalable and accurate assembly polishing algorithm. Bioinformatics 2020; 36:3669–3679 [View Article] [PubMed]
     [Google Scholar]
  105. Chen Y, Nie F, Xie S-Q, Zheng Y-F, Dai Q et al. Efficient assembly of nanopore reads via highly accurate and intact error correction. Nat Commun 2021; 12:60 [View Article]
     [Google Scholar]
  106. Vaser R, Šikić M. Time- and memory-efficient genome assembly with Raven. Nat Comput Sci 2021; 1:332–336 [View Article] [PubMed]
     [Google Scholar]
  107. Chin C-S, Alexander DH, Marks P, Klammer AA, Drake J et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods 2013; 10:563–569 [View Article] [PubMed]
     [Google Scholar]
  108. Sereika M, Kirkegaard RH, Karst SM, Michaelsen TY, Sørensen EA et al. Oxford Nanopore R10.4 long-read sequencing enables the generation of near-finished bacterial genomes from pure cultures and metagenomes without short-read or reference polishing. Nat Methods 2022; 19:823–826 [View Article] [PubMed]
     [Google Scholar]
  109. Wick R. Yet another ONT accuracy test: Dorado v0.5.0. Ryan Wick’s bioinformatics blog 2023; 2024 https://rrwick.github.io/2023/12/18/ont-only-accuracy-update.html
  110. Yu R, Abdullah SMU, Sun Y. HMMPolish: a coding region polishing tool for TGS-sequenced RNA viruses. Brief Bioinform 2023; 24:bbad264 [View Article] [PubMed]
     [Google Scholar]
  111. Sarkhouh H, Chehadeh W. CODEHOP-mediated PCR improves HIV-1 genotyping and detection of variants by MinION sequencing. Microbiol Spectr 2021; 9:e0143221 [View Article] [PubMed]
     [Google Scholar]
  112. Sebastião CS, Abecasis AB, Jandondo D, Sebastião JMK, Vigário J et al. HIV-1 diversity and pre-treatment drug resistance in the era of integrase inhibitor among newly diagnosed ART-naïve adult patients in Luanda, Angola. Sci Rep 2024; 14:15893 [View Article] [PubMed]
     [Google Scholar]
  113. Mori M, Ode H, Kubota M, Nakata Y, Kasahara T et al. Nanopore sequencing for characterization of HIV-1 recombinant forms. Microbiol Spectr 2022; 10:e0150722 [View Article] [PubMed]
     [Google Scholar]
  114. Ji H, Enns E, Brumme CJ, Parkin N, Howison M et al. Bioinformatic data processing pipelines in support of next-generation sequencing-based HIV drug resistance testing: the Winnipeg Consensus. J Int AIDS Soc 2018; 21:e25193 [View Article] [PubMed]
     [Google Scholar]
  115. Wang Y, Zhao Y, Bollas A, Wang Y, Au KF. Nanopore sequencing technology, bioinformatics and applications. Nat Biotechnol 2021; 39:1348–1365 [View Article] [PubMed]
     [Google Scholar]
  116. Sauerborn E, Corredor NC, Reska T, Perlas A, Vargas da Fonseca Atum S et al. Detection of hidden antibiotic resistance through real-time genomics. Nat Commun 2024; 15:5494 [View Article] [PubMed]
     [Google Scholar]
  117. Zhao K, Tu C, Chen W, Liang H, Zhang W et al. Rapid identification of drug-resistant tuberculosis genes using direct PCR amplification and Oxford nanopore technology sequencing. Can J Infect Dis Med Microbiol 2022; 2022:7588033 [View Article] [PubMed]
     [Google Scholar]
  118. Cabibbe AM, Moghaddasi K, Batignani V, Morgan GSK, Di Marco F et al. Nanopore-based targeted sequencing test for direct tuberculosis identification, genotyping, and detection of drug resistance mutations: a side-by-side comparison of targeted next-generation sequencing technologies. J Clin Microbiol 2024; 62:e0081524 [View Article] [PubMed]
     [Google Scholar]
  119. Hall MB, Rabodoarivelo MS, Koch A, Dippenaar A, George S et al. Evaluation of nanopore sequencing for Mycobacterium tuberculosis drug susceptibility testing and outbreak investigation: a genomic analysis. Lancet Microbe 2023; 4:e84–e92 [View Article] [PubMed]
     [Google Scholar]
  120. Liu A, Liu S, Lv K, Zhu Q, Wen J et al. Rapid detection of multidrug resistance in tuberculosis using nanopore-based targeted next-generation sequencing: a multicenter, double-blind study. Front Microbiol 2024; 15:1349715 [View Article] [PubMed]
     [Google Scholar]
  121. Imai K, Tarumoto N, Misawa K, Runtuwene LR, Sakai J et al. A novel diagnostic method for malaria using loop-mediated isothermal amplification (LAMP) and MinION nanopore sequencer. BMC Infect Dis 2017; 17:621 [View Article] [PubMed]
     [Google Scholar]
  122. Girgis ST, Adika E, Nenyewodey FE, Senoo Jnr DK, Ngoi JM et al. Drug resistance and vaccine target surveillance of Plasmodium falciparum using nanopore sequencing in Ghana. Nat Microbiol 2023; 8:2365–2377 [View Article] [PubMed]
     [Google Scholar]
  123. Shafer RW. Rationale and uses of a public HIV drug-resistance database. J Infect Dis 2006; 194 Suppl 1:S51–8 [View Article] [PubMed]
     [Google Scholar]
  124. Nykoluk M, Taylor T. HyDRA web user guide; 2016 https://hydra.canada.ca/HyDRA_Web_User_Guide_Final_6Sept2016.pdf
  125. Amarasinghe SL, Su S, Dong X, Zappia L, Ritchie ME et al. Opportunities and challenges in long-read sequencing data analysis. Genome Biol 2020; 21:30 [View Article] [PubMed]
     [Google Scholar]
  126. Kono N, Arakawa K. Nanopore sequencing: review of potential applications in functional genomics. Dev Growth Differ 2019; 61:316–326 [View Article] [PubMed]
     [Google Scholar]
  127. Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 2018; 34:3094–3100 [View Article] [PubMed]
     [Google Scholar]
  128. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J et al. The sequence alignment/map format and SAMtools. Bioinformatics 2009; 25:2078–2079 [View Article]
     [Google Scholar]
  129. Gerhardt L, Bhimji W, Canon S, Fasel M, Jacobsen D et al. Shifter: containers for HPC. J Phys: Conf Ser 2017; 898:082021 [View Article]
     [Google Scholar]
  130. Merkel D. Docker: lightweight linux containers for consistent development and deployment. Linux J 2014; 2: [View Article]
     [Google Scholar]
  131. Kurtzer GM, Sochat V, Bauer MW. Singularity: scientific containers for mobility of compute. PLoS One 2017; 12:e0177459 [View Article] [PubMed]
     [Google Scholar]
  132. Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E et al. Nextflow enables reproducible computational workflows. Nat Biotechnol 2017; 35:316–319 [View Article] [PubMed]
     [Google Scholar]
  133. Mölder F, Jablonski KP, Letcher B, Hall MB, Tomkins-Tinch CH et al. Sustainable data analysis with snakemake. F1000Res 2021; 10:33 [View Article] [PubMed]
     [Google Scholar]
  134. Ssekagiri A, Jjingo D, Bbosa N, Bugembe DL, Kateete DP et al. HIVseqDB: a portable resource for NGS and sample metadata integration for HIV-1 drug resistance analysis. Bioinform Adv 2024; 4:vbae008 [View Article] [PubMed]
     [Google Scholar]
  135. Ssekagiri A, Jjingo D, Lujumba I, Bbosa N, Bugembe DL et al. QuasiFlow: a nextflow pipeline for analysis of NGS-based HIV-1 drug resistance data. Bioinform Adv 2022; 2:vbac089 [View Article] [PubMed]
     [Google Scholar]
  136. Ho J, Ng G, Renaud M, Poon A. sierra-local: a lightweight standalone application for drug resistance prediction. J Open Source Softw 2019; 4:1186 [View Article]
     [Google Scholar]
  137. Barker M, Chue Hong NP, Katz DS, Lamprecht A-L, Martinez-Ortiz C et al. Introducing the FAIR principles for research software. Sci Data 2022; 9:622 [View Article]
     [Google Scholar]
  138. Au KF, Underwood JG, Lee L, Wong WH. Improving PacBio long read accuracy by short read alignment. PLoS One 2012; 7:e46679 [View Article]
     [Google Scholar]
  139. Haghshenas E, Hach F, Sahinalp SC, Chauve C. CoLoRMap: correcting long reads by mapping short reads. Bioinformatics 2016; 32:i545–i551 [View Article] [PubMed]
     [Google Scholar]
/content/journal/mgen/10.1099/mgen.0.001375
Loading
The utility of integrating nanopore sequencing into routine HIV-1 drug resistance surveillance
M Gen 11, 001375 (2025); https://doi.org/10.1099/mgen.0.001375
/content/journal/mgen/10.1099/mgen.0.001375
/content/journal/mgen/10.1099/mgen.0.001375
Loading

Data & Media loading...

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An error occurred
Approval was partially successful, following selected items could not be processed due to error