Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109657
PIRA download icon_1.1View/Download Full Text
Title: Long-read sequencing with hierarchical clustering for antiretroviral resistance profiling of mixed human immunodeficiency virus quasispecies
Authors: Ng, TTL 
Su, J
Lao, HY 
Lui, WW
Chan, CTM 
Leung, AWS
Jim, SHC 
Lee, LK 
Shehzad, S 
Tam, KKG
Leung, KSS
Tang, F 
Yam, WC
Luo, R
Siu, GKH 
Issue Date: Oct-2023
Source: Clinical chemistry, Oct. 2023, v. 69, no. 10, p. 1174-1185
Abstract: Background: HIV infections often develop drug resistance mutations (DRMs), which can increase the risk of virological failure. However, it has been difficult to determine if minor mutations occur in the same genome or in different virions using Sanger sequencing and short-read sequencing methods. Oxford Nanopore Technologies (ONT) sequencing may improve antiretroviral resistance profiling by allowing for long-read clustering.
Methods: A new ONT sequencing-based method for profiling DRMs in HIV quasispecies was developed and validated. The method used hierarchical clustering of long amplicons that cover regions associated with different types of antiretroviral drugs. A gradient series of an HIV plasmid and 2 plasma samples was prepared to validate the clustering performance. The ONT results were compared to those obtained with Sanger sequencing and Illumina sequencing in 77 HIV-positive plasma samples to evaluate the diagnostic performance.
Results: In the validation study, the abundance of detected quasispecies was concordant with the predicted result with the R2 of > 0.99. During the diagnostic evaluation, 59/77 samples were successfully sequenced for DRMs. Among 18 failed samples, 17 were below the limit of detection of 303.9 copies/μL. Based on the receiver operating characteristic analysis, the ONT workflow achieved an F1 score of 0.96 with a cutoff of 0.4 variant allele frequency. Four cases were found to have quasispecies with DRMs, in which 2 harbored quasispecies with more than one class of DRMs. Treatment modifications were recommended for these cases.
Conclusions: Long-read sequencing coupled with hierarchical clustering could differentiate the quasispecies resistance profiles in HIV-infected samples, providing a clearer picture for medical care.
Publisher: Oxford University Press
Journal: Clinical chemistry 
ISSN: 0009-9147
EISSN: 1530-8561
DOI: 10.1093/clinchem/hvad108
Rights: © American Association for Clinical Chemistry 2023.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
The following publication Timothy Ting-Leung Ng, Junhao Su, Hiu-Yin Lao, Wui-Wang Lui, Chloe Toi-Mei Chan, Amy Wing-Sze Leung, Stephanie Hoi-Ching Jim, Lam-Kwong Lee, Sheeba Shehzad, Kingsley King-Gee Tam, Kenneth Siu-Sing Leung, Forrest Tang, Wing-Cheong Yam, Ruibang Luo, Gilman Kit-Hang Siu, Long-Read Sequencing with Hierarchical Clustering for Antiretroviral Resistance Profiling of Mixed Human Immunodeficiency Virus Quasispecies, Clinical Chemistry, Volume 69, Issue 10, October 2023, Pages 1174–1185 is available at https://doi.org/10.1093/clinchem/hvad108.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
hvad108.pdf1.09 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

9
Citations as of Nov 17, 2024

Downloads

6
Citations as of Nov 17, 2024

SCOPUSTM   
Citations

5
Citations as of Nov 21, 2024

WEB OF SCIENCETM
Citations

5
Citations as of Nov 21, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.