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Identification of HCV protease inhibitor resistance mutations by selection pressure-based method

A major challenge to successful antiviral therapy is the emergence of drug-resistant viruses. Recent studies have developed several automated analyses of HIV sequence polymorphism based on calculations of selection pressure (K(a)/K(s)) to predict drug resistance mutations. Similar resistance analysi...

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Autores principales: Qiu, Ping, Sanfiorenzo, Vincent, Curry, Stephanie, Guo, Zhuyan, Liu, Shaotang, Skelton, Angela, Xia, Ellen, Cullen, Constance, Ralston, Robert, Greene, Jonathan, Tong, Xiao
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691846/
https://www.ncbi.nlm.nih.gov/pubmed/19395595
http://dx.doi.org/10.1093/nar/gkp251
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author Qiu, Ping
Sanfiorenzo, Vincent
Curry, Stephanie
Guo, Zhuyan
Liu, Shaotang
Skelton, Angela
Xia, Ellen
Cullen, Constance
Ralston, Robert
Greene, Jonathan
Tong, Xiao
author_facet Qiu, Ping
Sanfiorenzo, Vincent
Curry, Stephanie
Guo, Zhuyan
Liu, Shaotang
Skelton, Angela
Xia, Ellen
Cullen, Constance
Ralston, Robert
Greene, Jonathan
Tong, Xiao
author_sort Qiu, Ping
collection PubMed
description A major challenge to successful antiviral therapy is the emergence of drug-resistant viruses. Recent studies have developed several automated analyses of HIV sequence polymorphism based on calculations of selection pressure (K(a)/K(s)) to predict drug resistance mutations. Similar resistance analysis programs for HCV inhibitors are not currently available. Taking advantage of the recently available sequence data of patient HCV samples from a Phase II clinical study of protease inhibitor boceprevir, we calculated the selection pressure for all codons in the HCV protease region (amino acid 1–181) to identify potential resistance mutations. The correlation between mutations was also calculated to evaluate linkage between any two mutations. Using this approach, we identified previously known major resistant mutations, including a recently reported mutation V55A. In addition, a novel mutation V158I was identified, and we further confirmed its resistance to boceprevir in protease enzyme and replicon assay. We also extended the approach to analyze potential interactions between individual mutations and identified three pairs of correlated changes. Our data suggests that selection pressure-based analysis and correlation mapping could provide useful tools to analyze large amount of sequencing data from clinical samples and to identify new drug resistance mutations as well as their linkage and correlations.
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spelling pubmed-26918462009-07-17 Identification of HCV protease inhibitor resistance mutations by selection pressure-based method Qiu, Ping Sanfiorenzo, Vincent Curry, Stephanie Guo, Zhuyan Liu, Shaotang Skelton, Angela Xia, Ellen Cullen, Constance Ralston, Robert Greene, Jonathan Tong, Xiao Nucleic Acids Res Methods Online A major challenge to successful antiviral therapy is the emergence of drug-resistant viruses. Recent studies have developed several automated analyses of HIV sequence polymorphism based on calculations of selection pressure (K(a)/K(s)) to predict drug resistance mutations. Similar resistance analysis programs for HCV inhibitors are not currently available. Taking advantage of the recently available sequence data of patient HCV samples from a Phase II clinical study of protease inhibitor boceprevir, we calculated the selection pressure for all codons in the HCV protease region (amino acid 1–181) to identify potential resistance mutations. The correlation between mutations was also calculated to evaluate linkage between any two mutations. Using this approach, we identified previously known major resistant mutations, including a recently reported mutation V55A. In addition, a novel mutation V158I was identified, and we further confirmed its resistance to boceprevir in protease enzyme and replicon assay. We also extended the approach to analyze potential interactions between individual mutations and identified three pairs of correlated changes. Our data suggests that selection pressure-based analysis and correlation mapping could provide useful tools to analyze large amount of sequencing data from clinical samples and to identify new drug resistance mutations as well as their linkage and correlations. Oxford University Press 2009-06 2009-04-24 /pmc/articles/PMC2691846/ /pubmed/19395595 http://dx.doi.org/10.1093/nar/gkp251 Text en © 2009 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Qiu, Ping
Sanfiorenzo, Vincent
Curry, Stephanie
Guo, Zhuyan
Liu, Shaotang
Skelton, Angela
Xia, Ellen
Cullen, Constance
Ralston, Robert
Greene, Jonathan
Tong, Xiao
Identification of HCV protease inhibitor resistance mutations by selection pressure-based method
title Identification of HCV protease inhibitor resistance mutations by selection pressure-based method
title_full Identification of HCV protease inhibitor resistance mutations by selection pressure-based method
title_fullStr Identification of HCV protease inhibitor resistance mutations by selection pressure-based method
title_full_unstemmed Identification of HCV protease inhibitor resistance mutations by selection pressure-based method
title_short Identification of HCV protease inhibitor resistance mutations by selection pressure-based method
title_sort identification of hcv protease inhibitor resistance mutations by selection pressure-based method
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691846/
https://www.ncbi.nlm.nih.gov/pubmed/19395595
http://dx.doi.org/10.1093/nar/gkp251
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