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Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses

BACKGROUND: In human immunodeficiency virus type 1 (HIV-1) infection, transmitted viruses generally use the CCR5 chemokine receptor as a coreceptor for host cell entry. In more than 50% of subtype B infections, a switch in coreceptor tropism from CCR5- to CXCR4-use occurs during disease progression....

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Autores principales: Crous, Saleema, Shrestha, Ram Krishna, Travers, Simon A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482586/
https://www.ncbi.nlm.nih.gov/pubmed/22938574
http://dx.doi.org/10.1186/1471-2334-12-203
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author Crous, Saleema
Shrestha, Ram Krishna
Travers, Simon A
author_facet Crous, Saleema
Shrestha, Ram Krishna
Travers, Simon A
author_sort Crous, Saleema
collection PubMed
description BACKGROUND: In human immunodeficiency virus type 1 (HIV-1) infection, transmitted viruses generally use the CCR5 chemokine receptor as a coreceptor for host cell entry. In more than 50% of subtype B infections, a switch in coreceptor tropism from CCR5- to CXCR4-use occurs during disease progression. Phenotypic or genotypic approaches can be used to test for the presence of CXCR4-using viral variants in an individual’s viral population that would result in resistance to treatment with CCR5-antagonists. While genotyping approaches for coreceptor-tropism prediction in subtype B are well established and verified, they are less so for subtype C. METHODS: Here, using a dataset comprising V3 loop sequences from 349 CCR5-using and 56 CXCR4-using HIV-1 subtype C viruses we perform a comparative analysis of the predictive ability of 11 genotypic algorithms in their prediction of coreceptor tropism in subtype C. We calculate the sensitivity and specificity of each of the approaches as well as determining their overall accuracy. By separating the CXCR4-using viruses into CXCR4-exclusive (25 sequences) and dual-tropic (31 sequences) we evaluate the effect of the possible conflicting signal from dual-tropic viruses on the ability of a of the approaches to correctly predict coreceptor phenotype. RESULTS: We determined that geno2pheno with a false positive rate of 5% is the best approach for predicting CXCR4-usage in subtype C sequences with an accuracy of 94% (89% sensitivity and 99% specificity). Contrary to what has been reported for subtype B, the optimal approaches for prediction of CXCR4-usage in sequence from viruses that use CXCR4 exclusively, also perform best at predicting CXCR4-use in dual-tropic viral variants. CONCLUSIONS: The accuracy of genotyping approaches at correctly predicting the coreceptor usage of V3 sequences from subtype C viruses is very high. We suggest that genotyping approaches can be used to test for coreceptor tropism in HIV-1 group M subtype C with a high degree of confidence that they will identify CXCR4-usage in both CXCR4-exclusive and dual tropic variants.
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spelling pubmed-34825862012-11-05 Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses Crous, Saleema Shrestha, Ram Krishna Travers, Simon A BMC Infect Dis Research Article BACKGROUND: In human immunodeficiency virus type 1 (HIV-1) infection, transmitted viruses generally use the CCR5 chemokine receptor as a coreceptor for host cell entry. In more than 50% of subtype B infections, a switch in coreceptor tropism from CCR5- to CXCR4-use occurs during disease progression. Phenotypic or genotypic approaches can be used to test for the presence of CXCR4-using viral variants in an individual’s viral population that would result in resistance to treatment with CCR5-antagonists. While genotyping approaches for coreceptor-tropism prediction in subtype B are well established and verified, they are less so for subtype C. METHODS: Here, using a dataset comprising V3 loop sequences from 349 CCR5-using and 56 CXCR4-using HIV-1 subtype C viruses we perform a comparative analysis of the predictive ability of 11 genotypic algorithms in their prediction of coreceptor tropism in subtype C. We calculate the sensitivity and specificity of each of the approaches as well as determining their overall accuracy. By separating the CXCR4-using viruses into CXCR4-exclusive (25 sequences) and dual-tropic (31 sequences) we evaluate the effect of the possible conflicting signal from dual-tropic viruses on the ability of a of the approaches to correctly predict coreceptor phenotype. RESULTS: We determined that geno2pheno with a false positive rate of 5% is the best approach for predicting CXCR4-usage in subtype C sequences with an accuracy of 94% (89% sensitivity and 99% specificity). Contrary to what has been reported for subtype B, the optimal approaches for prediction of CXCR4-usage in sequence from viruses that use CXCR4 exclusively, also perform best at predicting CXCR4-use in dual-tropic viral variants. CONCLUSIONS: The accuracy of genotyping approaches at correctly predicting the coreceptor usage of V3 sequences from subtype C viruses is very high. We suggest that genotyping approaches can be used to test for coreceptor tropism in HIV-1 group M subtype C with a high degree of confidence that they will identify CXCR4-usage in both CXCR4-exclusive and dual tropic variants. BioMed Central 2012-09-02 /pmc/articles/PMC3482586/ /pubmed/22938574 http://dx.doi.org/10.1186/1471-2334-12-203 Text en Copyright ©2012 Crous et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Crous, Saleema
Shrestha, Ram Krishna
Travers, Simon A
Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses
title Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses
title_full Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses
title_fullStr Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses
title_full_unstemmed Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses
title_short Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses
title_sort appraising the performance of genotyping tools in the prediction of coreceptor tropism in hiv-1 subtype c viruses
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482586/
https://www.ncbi.nlm.nih.gov/pubmed/22938574
http://dx.doi.org/10.1186/1471-2334-12-203
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