Dataset Information

HIV coreceptor tropism determination and mutational pattern identification.

ABSTRACT: In the early stages of infection, Human Immunodeficiency Virus Type 1 (HIV-1) generally selects CCR5 as the primary coreceptor for entering the host cell. As infection progresses, the virus evolves and may exhibit a coreceptor-switch to CXCR4. Accurate determination coreceptor usage and identification key mutational patterns associated tropism switch are essential for selection of appropriate therapies and understanding mechanism of coreceptor change. We developed a classifier composed of two coreceptor-specific weight matrices (CMs) based on a full-scale dataset. For this classifier, we found an AUC of 0.97, an accuracy of 95.21% and an MCC of 0.885 (sensitivity 92.92%; specificity 95.54%) in a ten-fold cross-validation, outperforming all other methods on an independent dataset (13% higher MCC value than geno2pheno and 15% higher MCC value than PSSM). A web server (http://spg.med.tsinghua.edu.cn/CM.html) based on our classifier was provided. Patterns of genetic mutations that occur along with coreceptor transitions were further identified based on the score of each sequence. Six pairs of one-AA mutational patterns and three pairs of two-AA mutational patterns were identified to associate with increasing propensity for X4 tropism. These mutational patterns offered new insights into the mechanism of coreceptor switch and aided in monitoring coreceptor switch.

SUBMITTER: Shen HS

PROVIDER: S-EPMC4756667 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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HIV coreceptor tropism determination and mutational pattern identification.

Shen Hui-Shuang HS Yin Jason J Leng Fei F Teng Rui-Fang RF Xu Chao C Xia Xia-Yu XY Pan Xian-Ming XM

Scientific reports 20160217

In the early stages of infection, Human Immunodeficiency Virus Type 1 (HIV-1) generally selects CCR5 as the primary coreceptor for entering the host cell. As infection progresses, the virus evolves and may exhibit a coreceptor-switch to CXCR4. Accurate determination coreceptor usage and identification key mutational patterns associated tropism switch are essential for selection of appropriate therapies and understanding mechanism of coreceptor change. We developed a classifier composed of two co ...[more]

PMID: 26883082

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Project description:CCR5 antagonists are a powerful new class of antiretroviral drugs that require a companion assay to evaluate the presence of CXCR4-tropic (non-R5) viruses prior to use in human immunodeficiency virus (HIV)-infected individuals. In this study, we have developed, characterized, verified, and prevalidated a novel phenotypic test to determine HIV-1 coreceptor tropism (VERITROP) based on a sensitive cell-to-cell fusion assay. A proprietary vector was constructed containing a near-full-length HIV-1 genome with the yeast uracil biosynthesis (URA3) gene replacing the HIV-1 env coding sequence. Patient-derived HIV-1 PCR products were introduced by homologous recombination using an innovative yeast-based cloning strategy. The env-expressing vectors were then used in a cell-to-cell fusion assay to determine the presence of R5 and/or non-R5 HIV-1 variants within the viral population. Results were compared with (i) the original version of Trofile (Monogram Biosciences, San Francisco, CA), (ii) population sequencing, and (iii) 454 pyrosequencing, with the genotypic data analyzed using several bioinformatics tools, i.e., the 11/24/25 rule, Geno2Pheno (2% to 5.75%, 3.5%, or 10% false-positive rate [FPR]), and webPSSM. VERITROP consistently detected minority non-R5 variants from clinical specimens, with an analytical sensitivity of 0.3%, with viral loads of ≥1,000 copies/ml, and from B and non-B subtypes. In a pilot study, a 73.7% (56/76) concordance was observed with the original Trofile assay, with 19 of the 20 discordant results corresponding to non-R5 variants detected using VERITROP and not by the original Trofile assay. The degree of concordance of VERITROP and Trofile with population and deep sequencing results depended on the algorithm used to determine HIV-1 coreceptor tropism. Overall, VERITROP showed better concordance with deep sequencing/Geno2Pheno at a 0.3% detection threshold (67%), whereas Trofile matched better with population sequencing (79%). However, 454 sequencing using Geno2Pheno at a 10% FPR and 0.3% threshold and VERITROP more accurately predicted the success of a maraviroc-based regimen. In conclusion, VERITROP may promote the development of new HIV coreceptor antagonists and aid in the treatment and management of HIV-infected individuals prior to and/or during treatment with this class of drugs.

Project description:HIV-1 entry into target cells influences several aspects of HIV-1 pathogenesis, including viral tropism, HIV-1 transmission and disease progression, and response to entry inhibitors. The evolution from CCR5- to CXCR4-using strains in a given human host is still unpredictable. Here we analyzed timing and predictors for coreceptor evolution among recently HIV-1-infected individuals. Proviral DNA was longitudinally evaluated in 66 individuals using Geno2pheno[coreceptor] Demographics, viral load, CD4+ and CD8+ T cell counts, CCR5?32 polymorphisms, GB virus C (GBV-C) coinfection, and HLA profiles were also evaluated. Ultradeep sequencing was performed on initial samples from 11 selected individuals. A tropism switch from CCR5- to CXCR4-using strains was identified in 9/49 (18.4%) individuals. Only a low baseline false-positive rate (FPR) was found to be a significant tropism switch predictor. No minor CXCR4-using variants were identified in initial samples of 4 of 5 R5/non-R5 switchers. Logistic regression analysis showed that patients with an FPR of >40.6% at baseline presented a stable FPR over time whereas lower FPRs tend to progressively decay, leading to emergence of CXCR4-using strains, with a mean evolution time of 27.29 months (range, 8.90 to 64.62). An FPR threshold above 40.6% determined by logistic regression analysis may make it unnecessary to further determine tropism for prediction of disease progression related to emergence of X4 strains or use of CCR5 antagonists. The detection of variants with intermediate FPRs and progressive FPR decay over time not only strengthens the power of Geno2pheno in predicting HIV tropism but also indirectly confirms a continuous evolution from earlier R5 variants toward CXCR4-using strains.IMPORTANCE The introduction of CCR5 antagonists in the antiretroviral arsenal has sparked interest in coreceptors utilized by HIV-1. Despite concentrated efforts, viral and human host features predicting tropism switch are still poorly understood. Limited longitudinal data are available to assess the influence that these factors have on predicting tropism switch and disease progression. The present study describes longitudinal tropism evolution in a group of recently HIV-infected individuals to determine the prevalence and potential correlates of tropism switch. We demonstrated here that a low baseline FPR determined by the Geno2pheno[coreceptor] algorithm can predict tropism evolution from CCR5 to CXCR4 coreceptor use.

Project description:BackgroundIn 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.MethodsHere, 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.ResultsWe 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.ConclusionsThe 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.

Dataset Information

HIV coreceptor tropism determination and mutational pattern identification.

Publications

HIV coreceptor tropism determination and mutational pattern identification.

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