MiDRM<i>pol</i>: A High-Throughput Multiplexed Amplicon Sequencing Workflow to Quantify HIV-1 Drug Resistance Mutations against Protease, Reverse Transcriptase, and Integrase Inhibitors

The detection of drug resistance mutations (DRMs) in minor viral populations is of potential clinical importance. However, sophisticated computational infrastructure and competence for analysis of high-throughput sequencing (HTS) data lack at most diagnostic laboratories. Thus, we have proposed a ne...

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Bibliographic Details
Main Authors: Shambhu G. Aralaguppe, Anoop T. Ambikan, Manickam Ashokkumar, Milner M. Kumar, Luke Elizabeth Hanna, Wondwossen Amogne, Anders Sönnerborg, Ujjwal Neogi
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Viruses
Subjects:
Online Access:https://www.mdpi.com/1999-4915/11/9/806
Description
Summary:The detection of drug resistance mutations (DRMs) in minor viral populations is of potential clinical importance. However, sophisticated computational infrastructure and competence for analysis of high-throughput sequencing (HTS) data lack at most diagnostic laboratories. Thus, we have proposed a new pipeline, MiDRM<i>pol</i>, to quantify DRM from the HIV-1 <i>pol</i> region. The gag-vpu region of 87 plasma samples from HIV-infected individuals from three cohorts was amplified and sequenced by Illumina HiSeq2500. The sequence reads were adapter-trimmed, followed by analysis using in-house scripts. Samples from Swedish and Ethiopian cohorts were also sequenced by Sanger sequencing. The pipeline was validated against the online tool PASeq (Polymorphism Analysis by Sequencing). Based on an error rate of &lt;1%, a value of &gt;1% was set as reliable to consider a minor variant. Both pipelines detected the mutations in the dominant viral populations, while discrepancies were observed in minor viral populations. In five HIV-1 subtype C samples, minor mutations were detected at the &lt;5% level by MiDRM<i>pol</i> but not by PASeq. MiDRM<i>pol</i> is a computationally as well as labor efficient bioinformatics pipeline for the detection of DRM from HTS data. It identifies minor viral populations (&lt;20%) of DRMs. Our method can be incorporated into large-scale surveillance of HIV-1 DRM.
ISSN:1999-4915