Literature DB >> 32061862

Shall I trust the report? Variable performance of Sanger sequencing revealed by deep sequencing on HIV drug resistance mutation detection.

Nan-Yu Chen1, Shu-Wei Kao1, Zhuo-Hao Liu2, Ting-Shu Wu1, Chia-Lung Tsai3, Hsi-Hsun Lin4, Wing-Wai Wong5, Yea-Yuan Chang6, Shu-Sheng Chen5, Stephane Wen-Wei Ku7.   

Abstract

BACKGROUND: The clinical utilisation of deep sequencing in HIV treatment has been hindered due to its unknown correlation with standard Sanger genotyping and the undetermined value of minority drug resistance mutation (DRM) detection.
OBJECTIVES: To compare deep sequencing performance to standard Sanger genotyping with clinical samples, in an effort to delineate the correlation between the results from the two methods and to find the optimal deep sequencing threshold for clinical utilisation.
METHODS: We conducted a retrospective study using stored plasma collected from August 2014 to March 2018 for HIV genotyping with the commercial Sanger genotyping kit. Samples with available Sanger genotyping reports were further deep sequenced. Drug resistance was interpreted according to the Stanford HIV drug resistance database algorithm.
RESULTS: At 15-25% minority detection thresholds, 9-15% cases had underestimated DRMs by Sanger sequencing. The concordance between the Sanger and deep sequencing reports was 68-82% in protease-reverse transcriptase region and 88-97% in integrase region at 5-25% thresholds. The undetected drug resistant minority variants by Sanger sequencing contributed to the lower negative predictive value of Sanger genotyping in cases harbouring DRMs.
CONCLUSIONS: Use of deep sequencing improved detection of antiretroviral resistance mutations especially in cases with virological failure or previous treatment interruption. Deep sequencing with 10-15% detection thresholds may be considered a suitable substitute for Sanger sequencing on antiretroviral DRM detection.
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Deep sequencing; Drug resistance; HIV; Next-generation sequencing; Sanger sequencing

Mesh:

Substances:

Year:  2020        PMID: 32061862     DOI: 10.1016/j.ijid.2020.02.004

Source DB:  PubMed          Journal:  Int J Infect Dis        ISSN: 1201-9712            Impact factor:   3.623


  5 in total

1.  HIV-1 Drug Resistance Assay Using Ion Torrent Next Generation Sequencing and On-Instrument End-to-End Analysis Software.

Authors:  Michael T Pyne; Keith E Simmon; Melanie A Mallory; Weston C Hymas; Jeffery Stevenson; Adam P Barker; David R Hillyard
Journal:  J Clin Microbiol       Date:  2022-06-14       Impact factor: 11.677

2.  HIV Drug Resistance Mutations Detection by Next-Generation Sequencing during Antiretroviral Therapy Interruption in China.

Authors:  Miaomiao Li; Shujia Liang; Chao Zhou; Min Chen; Shu Liang; Chunhua Liu; Zhongbao Zuo; Lei Liu; Yi Feng; Chang Song; Hui Xing; Yuhua Ruan; Yiming Shao; Lingjie Liao
Journal:  Pathogens       Date:  2021-02-25

Review 3.  Potential challenges to sustained viral load suppression in the HIV treatment programme in South Africa: a narrative overview.

Authors:  Pascal O Bessong; Nontokozo D Matume; Denis M Tebit
Journal:  AIDS Res Ther       Date:  2021-01-06       Impact factor: 2.250

4.  Establishment and application of a method of tagged-amplicon deep sequencing for low-abundance drug resistance in HIV-1.

Authors:  Yang Li; Leilei Han; Yanglan Wang; Xiaolin Wang; Lei Jia; Jingyun Li; Jingwan Han; Jin Zhao; Hanping Li; Lin Li
Journal:  Front Microbiol       Date:  2022-08-22       Impact factor: 6.064

Review 5.  Next-Generation Sequencing for HIV Drug Resistance Testing: Laboratory, Clinical, and Implementation Considerations.

Authors:  Santiago Ávila-Ríos; Neil Parkin; Ronald Swanstrom; Roger Paredes; Robert Shafer; Hezhao Ji; Rami Kantor
Journal:  Viruses       Date:  2020-06-05       Impact factor: 5.048

  5 in total

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