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Highly Automated Deep Sequencing-based HIV-1 Drug Resistance Monitoring System
Poster Title: Highly Automated Deep Sequencing-based HIV-1 Drug Resistance Monitoring System
Submitted on 13 Sep 2017
Author(s): Rakhmanaliev Elian, Yee Mei Qi, Villy Caroline, Tan Kevin, Yeo Alex, Ariyaratne Pramila, Luo Raymond, Huang Wen, Michel Gerd, Lee Charlie
Affiliations: Vela Diagnostics Pte. Ltd.
This poster was presented at 2nd Asia Pacific AIDS and Co-infections Conference. Hong Kong, China. 1-3 Jun 2017
Poster Views: 1,692
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Poster Information
Abstract: Deep sequencing or Next Generation Sequencing (NGS) technology is increasingly used for HIV drug resistance testing in research field. The objective was to develop and validate an automated integrated NGS-based workflow for detection of drug resistance mutations in HIV-1 Group M for in vitro diagnostics. We developed a highly automated “sample-to-result” HIV drug-resistance monitoring system which comprised of 1) a robotic liquid handling system for RNA extraction and NGS library preparation (Sentosa SX101); 2) Ion Torrent NGS platform; 3) kits for RNA extraction, HIV NGS library preparation (Sentosa SQ HIV Genotyping Assay) and deep sequencing, and 4) data analysis and reporting software. The data reports include 276 amino acid (AA) mutations in 103 AA positions across the Reverse Transcriptase (RT), Protease (PR) and Integrase HIV-1 genes. However, the system does not make direct treatment recommendations, which are left to the investigator. The Sentosa HIV NGS workflow is highly automated and required <3 hrs. hands-on time with total turn around time about 27 hrs. The assay is able to process up to 15 clinical samples simultaneously. The limit of detection was determined to be 1000 copies/mL; reproducibility was 100% (95%CI: 96.2%-100%) for sample detection and 100% (95%CI: 99.7%-100%) for variant detection. Clinical evaluation was performed on 200 prospective and retrospective HIV-1 plasma samples. Clinical sensitivity (ability of the test assay to detect HIV-1 in clinical samples and successfully sequence the target regions) for the Sentosa SQ HIV Genotyping Assay was defined at 98.50% (95% CI: 96.77% - 99.31%). For evaluation of variant detection correctness (ability of the test workflow correctly report targeted variants) Sanger sequencing was used as a reference method. Considering limitations of Sanger sequencing only mutations with variant frequency greater than or equal to 20% were taken into analysis. Variant detection correctness for the Sentosa SQ HIV workflow was defined at 99.82% (95% CI: 99.77% - 99.86%). Considering the crucial role of drug resistance monitoring in HIV treatment management, the Sentosa HIV NGS workflow appears as a highly reliable tool for clinical diagnostics. More sensitive detection of low-frequency variants (up to 5%) resulting a higher predicted level of drug resistance, which offers improvements in HIV-1 drug resistance monitoring.Summary: Highly Automated Deep Sequencing-based HIV-1 Drug Resistance Monitoring System.Report abuse »
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