Evidence map›Paper›PMID 41832510›Full record

ArticleVirology journal2026

Leveraging the Oxford Nanopore MinION sequencing platform for HIV-1 drug resistance surveillance in resource-limited settings: a post-COVID implementation opportunity.

Tendai Washaya, Benjamin Chimukangara, Justin Mayini, Sandra Bote, Nyasha Chin'ombe, Shungu Munyati, Justen Manasa

Abstract read
In one paragraph

Article in Virology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Tendai WashayaMedical Microbiology Unit, Department of Laboratory Diagnostic and Investigative Science, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare, Zimbabwe. washayatendai@gmail.com.
Benjamin ChimukangaraCritical Care Medicine Department, NIH Clinical Centre, Bethesda, MD, USA.
Justin MayiniBiomedical Research and Training Institute, Harare, Zimbabwe.
Sandra BoteAIDS Healthcare Foundation, Harare, Zimbabwe.
Nyasha Chin'ombeMedical Microbiology Unit, Department of Laboratory Diagnostic and Investigative Science, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare, Zimbabwe.
Shungu MunyatiBiomedical Research and Training Institute, Harare, Zimbabwe.
Justen ManasaMedical Microbiology Unit, Department of Laboratory Diagnostic and Investigative Science, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare, Zimbabwe.

Funding

Advanced Training in Community Based Research; training in Bio-informatics, Drug Resistance and PathogenesisD43TW011326 · FIC · BIOMEDICAL RESEARCH & TRAINING INSTITUTE · PI MUNYATI, SHUNGU · 2020 to 2024
$1.6M
NIH HHS D43 TW011326
6 · The paper itself

Abstract

backgroundHIV drug resistance (HIVDR) testing remains essential for optimizing antiretroviral therapy (ART), yet access remains constrained by high cost, low throughput, and limited availability of Sanger sequencing in resource-limited settings (RLS). Recent improvements in Oxford Nanopore Technologies (ONT) sequencing offer a potential alternative, especially following the expansion of genomic surveillance infrastructure established during the COVID-19 pandemic.

methodsA cross-sectional laboratory validation study was conducted comparing ONT MinION sequencing with Sanger sequencing for HIV-1 protease/reverse transcriptase (PR/RT) and integrase (IN) genotyping. Sixty-four stored amplicons from patients with virological failure on second-line protease inhibitor (PI)- or integrase strand transfer inhibitor (INSTI)-based regimens were sequenced on the MinION Mk1C (R10.4.1). ONT-derived consensus sequences were generated using a custom pipeline and compared to Sanger reference sequences to assess nucleotide identity and drug resistance mutation (DRM) concordance using the Stanford HIVdb v9.8. We also evaluated the cost and scalability of ONT to determine its feasibility for broader implementation.

resultsONT MinION sequencing produced high-quality consensus sequences with a median pairwise identity of 99.4% (IQR: 99.2-99.7). After resolving initial discrepancies through chromatogram review and high-depth Nanopore data, high concordance for major DRMs was observed across PR, RT, and IN coding regions. Using a 48-sample multiplexing configuration, the estimated reagent and consumable cost for ONT sequencing was approximately US$23.47 per sample. Published Sanger-based HIV drug resistance assays report per-sample costs in the range of approximately US$43 to US$100, although costs vary depending on laboratory workflow and testing volume. Moreover, ONT provided a substantially shorter turnaround time (~ 5 h from library prep to sequence data), offering a more efficient and cost-effective workflow overall.

conclusionsONT MinION sequencing provides an accurate, rapid, and cost-effective alternative to Sanger sequencing for HIVDR genotyping in RLS. Its scalability, ability to detect minority variants, and compatibility with infrastructure setup up in response to the COVID-19 pandemic, make it a viable platform for both national HIVDR surveillance and decentralized clinical testing. Integrating ONT workflows into routine HIVDR monitoring could expand diagnostic access and enable more timely ART optimization in high-burden settings.

Indexed as

Drug Resistance, ViralHIV-1HIV InfectionsNanopore SequencingAnti-HIV AgentsCOVID-19Cross-Sectional StudiesGenotyping TechniquesHigh-Throughput Nucleotide SequencingHIV IntegraseHIV ProteaseHIV Reverse TranscriptaseHumansMutationAnti-HIV AgentsHIV IntegraseHIV ProteaseHIV Reverse TranscriptaseDrug resistanceGenotypingHIV-1Oxford Nanopore Technologies

Identifiers

PMID41832510
PMCPMC13104186

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.