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

Nan Yu Chen, Shu Wei Kao, Zhuo Hao Liu, Ting Shu Wu, Chia Lung Tsai, Hsi Hsun Lin, Wing Wai Wong, Yea Yuan Chang, Shu Sheng Chen, Stephane Wen Wei Ku*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

10 Scopus citations

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.

Original languageEnglish
Pages (from-to)182-191
Number of pages10
JournalInternational Journal of Infectious Diseases
Volume93
DOIs
StatePublished - 04 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 The Author(s)

Keywords

  • Deep sequencing
  • Drug resistance
  • HIV
  • Next-generation sequencing
  • Sanger sequencing

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