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Updated: Sep 23, 2026

An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Published on: March 30, 2014
Sources and magnitude of intralaboratory variability in a sequence-based genotypic assay for human immunodeficiency
R A Galli1, B Sattha, B Wynhoven
1BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada V6Z 1Y6.
Abstract:
We assessed the intralaboratory reproducibility of a system for sequencing human immunodeficiency virus type 1 (HIV-1) protease (PR) and reverse transcriptase (RT) by using replicate subanalyses of 46 plasma samples collected from HIV-1-infected, antiretroviral-experienced patients in order to determine the relative contributions of the different procedural steps to final sequence variability. Complete sequence concordance between duplicates of each sample was 99.4%. Complete and partial mismatches occurred scattered throughout the PR-RT genome segment at >300 positions. Approximately 75% of the discordances involved mixtures, some of which appeared at key resistance sites. Most differences were the result of the first-round RT-PCR procedure. Inter-rater concordance for sequence analysis and assembly was >99.9%. There was no observed correlation between the number or frequency of mismatches and plasma viral loads. A separate longitudinal analysis of a single routine control sample sequenced 103 times over 9 months consistently gave highly reproducible sequences (median percentage of nucleotide discordances, 0.04%; range, 0 to 0.2%). Finally, sequence data from 168 sequential samples collected from 22 patients with long-term, predominantly wild type HIV showed that intrapatient nucleotide concordance with individual index sequences ranged from 96.5 to 100%. Together, these results confirm that sequence-based genotyping can be a precise and reliable tool for monitoring HIV drug resistance, and they suggest that efforts to reduce variability should focus on the first RT-PCR step. Consequently, the data suggest that the composition of external quality assessment panels should be based on clinical HIV isolates rather than DNA clones.
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