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Updated: May 24, 2025
An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Published on: March 30, 2014
Adaptation of single molecule real time (SMRT) sequence technology for hepatitis C virus genome sequencing and
Cui Zhang1, Pei Liu1, Jian Li1
1National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Background And Objective:
Hepatitis C virus (HCV) resistance-associated substitutions (RASs) impact HCV treatment with direct-acting antivirals (DAAs). Therefore, a sensitive sequencing assay for detecting HCV RASs is crucial. PacBio sequencing, a Single molecule real time (SMRT) platform, is capable of long-fragment sequencing. This study aims to assess the prospects of PacBio sequencing by comparing its accuracy with Sanger sequencing at distinct thresholds and its cost-effectiveness with next-generation sequencing (NGS).
Methods:
A total of 28 specimens were selected from the HCV RNA-positive individuals in Linzhou, China. Of these specimens, the NS3 to NS5B regions were amplified and sent for PacBio sequencing. Sequence processing was accomplished by lima, pbmm2 and quasitools software, with threshold setting at 1%, 5%, 10% and 15%.
Results:
High-frequency RASs (S122G in NS3, R30Q in NS5A, and C316N in NS5B), rare RASs (V55A, R155P, and S174AT in NS3; Y448H in NS5B), and low-threshold RASs (L31Q and L31QFHY in NS5A; L159F in NS5B) were identified. It was found that the results of HCV RASs at the 10% threshold of PacBio sequencing are comparable to those of Sanger sequencing. In terms of high-throughput sequencing, the price of PacBio sequencing (571 CNY per specimen) is significantly lower than that of NGS (1000 CNY per specimen).
Conclusions:
In summary, these findings suggest that the adoption of the 10% threshold in PacBio sequencing for the analysis of HCV RASs is advisable. Moreover, given its relatively lower cost, PacBio sequencing holds great promise as a valuable tool for large-scale population sequencing.
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