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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
A reliable phenotype predictor for human immunodeficiency virus type 1 subtype C based on envelope V3 sequences
Journal of Virology, Volume 80, No. 10, Year 2006
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Description
In human immunodeficiency virus type 1 (HIV-1) subtype B infections, the emergence of viruses able to use CXCR4 as a coreceptor is well documented and associated with accelerated CD4 decline and disease progression. However, in HIV-1 subtype C infections, responsible for more than 50% of global infections, CXCR4 usage is less common, even in individuals with advanced disease. A reliable phenotype prediction method based on genetic sequence analysis could provide a rapid and less expensive approach to identify possible CXCR4 variants and thus increase our understanding of subtype C coreceptor usage. For subtype B V3 loop sequences, genotypic predictors have been developed based on position-specific scoring matrices (PSSM). In this study, we apply this methodology to a training set of 279 subtype C sequences of known phenotypes (228 non-syncytium-inducing [NSI] CCR5+ and 51 SI CXCR4+ sequences) to derive a C-PSSM predictor. Specificity and sensitivity distributions were estimated by combining data set bootstrapping with leave-one-out cross-validation, with random sampling of single sequences from individuals on each bootstrap iteration. The C-PSSM had an estimated specificity of 94% (confidence interval [CI], 92% to 96%) and a sensitivity of 75% (CI, 68% to 82%), which is significantly more sensitive than predictions based on other methods, including a commonly used method based on the presence of positively charged residues (sensitivity, 47.8%). A specificity of 83% and a sensitivity of 83% were achieved with a validation set of 24 SI and 47 NSI unique subtype C sequences. The C-PSSM performs as well on subtype C V3 loops as existing subtype B-specific methods do on subtype B V3 loops. We present bioinformatic evidence that particular sites may influence coreceptor usage differently, depending on the subtype. Copyright © 2006, American Society for Microbiology. All Rights Reserved.
Available Materials
https://efashare.b-cdn.net/share/pmc/articles/PMC1472078/bin/jvirol_80_10_4698__index.html
https://efashare.b-cdn.net/share/pmc/articles/PMC1472078/bin/jvirol_80_10_4698__JVI02525_05_supplement_022106.xls
Authors & Co-Authors
Jensen, Mark A.
United States, Seattle
University of Washington
United States, Atlanta
Rollins School of Public Health
Coetzer, Mia E.
South Africa, Johannesburg
National Institute for Communicable Diseases
Van't Wout, Angélique B.
United States, Seattle
University of Washington
Netherlands, Amsterdam
Sanquin Research
Morris, Lynn
South Africa, Johannesburg
National Institute for Communicable Diseases
Mullins, James I.
United States, Seattle
University of Washington
Statistics
Citations: 151
Authors: 5
Affiliations: 4
Identifiers
Doi:
10.1128/JVI.80.10.4698-4704.2006
ISSN:
0022538X
Research Areas
Genetics And Genomics
Infectious Diseases