Development and Application of Performance Assessment Criteria for Next-Generation Sequencing-Based HIV Drug Resistance Assays

Becker, Michael G.; Liang, Dun; Cooper, Barry; Yan, Lianshan; Taylor, Tracy; Lee, Emma R.; Wu, Sutan; Sandstrom, Paul; Ji, Hezhao

doi:10.3390/v12060627

Cited by 10 publications

(7 citation statements)

References 49 publications

(65 reference statements)

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“…However, slight variations that affected precision were noted at relative abundances below 20%, but more prominent at 1%. This could be attributed to the sequence error rate of ~ 1% and the increased likelihood of cross-contamination and sampling/PCR biases [ 19 ]. Although, minority mutations at frequencies < 0.5% could result in treatment failure [ 20 ], the clinical relevance of variants below 5% is still a question of debate [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

Next generation sequencing based in-house HIV genotyping method: validation report

2021

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Background HIV genotyping has had a significant impact on the care and treatment of HIV/AIDS. At a clinical level, the test guides physicians on the choice of treatment regimens. At the surveillance level, it informs policy on consolidated treatment guidelines and microbial resistance control strategies. Until recently, the conventional test has utilized the Sanger sequencing (SS) method. Unlike Next Generation Sequencing (NGS), SS is limited by low data throughput and the inability of detecting low abundant drug-resistant variants. NGS can improve sensitivity and quantitatively identify low-abundance variants; in addition, it has the potential to improve efficiency as well as lowering costs when samples are batched. Despite the NGS benefits, its utilization in clinical drug resistance profiling is faced with mixed reactions. These are largely based on a lack of a consensus regarding the quality control strategy. Nonetheless, transitional views suggest validating the method against the gold-standard SS. Therefore, we present a validation report of an NGS-based in-house HIV genotyping method against the SS method in Uganda. Results Since there were no established proficiency test panels for NGS-based HIV genotyping, 15 clinical plasma samples for routine care were utilized. The use of clinical samples allowed for accuracy and precision studies. The workflow involved four main steps; viral RNA extraction, targeted amplicon generation, amplicon sequencing and data analysis. Accuracy of 98% with an average percentage error of 3% was reported for the NGS based assay against the SS platform demonstrating similar performance. The coefficient of variation (CV) findings for both the inter-run and inter-personnel precision showed no variability (CV ≤ 0%) at the relative abundance of ≥ 20%. For both inter-run and inter-personnel, a variation that affected the precision was observed at 1% frequency. Overall, for all the frequencies, CV registered a small range of (0–2%). Conclusion The NGS-based in-house HIV genotyping method fulfilled the minimum requirements that support its utilization for drug resistance profiling in a clinical setting of a low-income country. For more inclusive quality control studies, well-characterized wet panels need to be established.

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Section: Discussionmentioning

confidence: 99%

Next generation sequencing based in-house HIV genotyping method: validation report

2021

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“…Samples were then tested for AIVs using a matrix (M) gene-specific real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) method according to the WHO guideline for animal influenza virus detection [ 16 ]. Continuously, the samples containing influenza A virus were examined for HPAIV and clade detection based on an RT-qPCR assay following a previous report [ 17 ]. Positive AIV samples were isolated by inoculating 10-day-old embryonated chicken eggs in a biosafety level two plus facility at the College of Veterinary Medicine, Vietnam National University of Agriculture, Hanoi, Vietnam.…”

Section: Methodsmentioning

confidence: 99%

Reassortant Highly Pathogenic H5N6 Avian Influenza Virus Containing Low Pathogenic Viral Genes in a Local Live Poultry Market, Vietnam

Lee

et al. 2021

Curr Microbiol

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Sites of live poultry trade and marketing are hot spots for avian influenza virus (AIV) transmission. We conducted active surveillance at a local live poultry market (LPM) in northern Vietnamese provinces in December 2016. Feces samples from the market were collected and tested for AIV. A new reassorted AIV strain was isolated from female chickens, named A/chicken/Vietnam/AI-1606/2016 (H5N6), and was found to belong to group C of clade 2.3.4.4 H5N6 highly pathogenic (HP) AIVs. The neuraminidase gene belongs to the reassortant B type. The viral genome also contained polymerase basic 2 and polymerase acidic, which were most closely related to domestic-duck-origin low pathogenic AIVs in Japan (H3N8) and Mongolia (H4N6). The other six genes were most closely related to poultry-origin H5N6 HP AIVs in Vietnam and had over 97% sequence identity with human AIV isolate A/Guangzhou/39715/2014 (H5N6). The new reassorted AIV isolate A/chicken/Vietnam/AI-1606/2016 (H5N6) identified in this study exemplifies AIVs reassortment and evolution through contact among wild birds, poultry farms, and LPMs. Therefore, active surveillance of AIVs is necessary to prevent potential threats to human and animal health.

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“…The sensitivity and specificity assessment of NGS HIV-DRT pose different challenges, compared to SS HIV-DRT, because of the quantitative nature and higher sensitivity of such assays [24]. NGS HIV-DRT is privileged to have the capacity to detect MRVs in the viral population.…”

Section: Ngs Accuracy Assessmentmentioning

confidence: 99%

Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing

Noguera-Julián

Lee

Shafer

et al. 2020

Viruses

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External quality assessment (EQA) is a keystone element in the validation and implementation of next generation sequencing (NGS)-based HIV drug resistance testing (DRT). Software validation and evaluation is a critical element in NGS EQA programs. While the development, sharing, and adoption of wet lab protocols is coupled with the increasing access to NGS technology worldwide, rendering it easy to produce NGS data for HIV-DRT, bioinformatic data analysis remains a bottleneck for most of the diagnostic laboratories. Several computational tools have been made available, via free or commercial sources, to automate the conversion of raw NGS data into an actionable clinical report. Although different software platforms yield equivalent results when identical raw NGS datasets are analyzed for variations at higher abundance, discrepancies arise when variations at lower frequencies are considered. This implies that validation and performance assessment of the bioinformatics tools applied in NGS HIV-DRT is critical, and the origins of the observed discrepancies should be determined. Well-characterized reference NGS datasets with ground truth on the genotype composition at all examined loci and the exact frequencies of HIV variations they may harbor, so-called dry panels, would be essential in such cases. The strategic design and construction of such panels are challenging but imperative tasks in support of EQA programs for NGS-based HIV-DRT and the validation of relevant bioinformatics tools. Here, we present criteria that can guide the design of such dry panels, which were discussed in the Second International Winnipeg Symposium themed for EQA strategies for NGS HIVDR assays.

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Development and Application of Performance Assessment Criteria for Next-Generation Sequencing-Based HIV Drug Resistance Assays

Cited by 10 publications

References 49 publications

Next generation sequencing based in-house HIV genotyping method: validation report

Next generation sequencing based in-house HIV genotyping method: validation report

Reassortant Highly Pathogenic H5N6 Avian Influenza Virus Containing Low Pathogenic Viral Genes in a Local Live Poultry Market, Vietnam

Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing

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