Abstract
BackgroundThe majority of HIV-1 subjects worldwide are infected with HIV-1 subtype C (C-HIV). Although C-HIV predominates in developing regions of the world such as Southern Africa and Central Asia, C-HIV is also spreading rapidly in countries with more developed economies and health care systems, whose populations are more likely to have access to wider treatment options, including the CCR5 antagonist maraviroc (MVC). The ability to reliably determine C-HIV coreceptor usage is therefore becoming increasingly more important. In silico V3 sequence based coreceptor usage prediction algorithms are a relatively rapid and cost effective method for determining HIV-1 coreceptor specificity. In this study, we elucidated the V3 sequence determinants of C-HIV coreceptor usage, and used this knowledge to develop and validate a novel, user friendly, and highly sensitive C-HIV specific coreceptor usage prediction algorithm.ResultsWe characterized every phenotypically-verified C-HIV gp120 V3 sequence available in the Los Alamos HIV Database. Sequence analyses revealed that compared to R5 C-HIV V3 sequences, CXCR4-using C-HIV V3 sequences have significantly greater amino acid variability, increased net charge, increased amino acid length, increased frequency of insertions and substitutions within the GPGQ crown motif, and reduced frequency of glycosylation sites. Based on these findings, we developed a novel C-HIV specific coreceptor usage prediction algorithm (CoRSeqV3-C), which we show has superior sensitivity for determining CXCR4 usage by C-HIV strains compared to all other available algorithms and prediction rules, including Geno2pheno[coreceptor] and WebPSSMSINSI-C, which has been designed specifically for C-HIV.ConclusionsCoRSeqV3-C is now openly available for public use at http://www.burnet.edu.au/coreceptor. Our results show that CoRSeqV3-C is the most sensitive V3 sequence based algorithm presently available for predicting CXCR4 usage of C-HIV strains, without compromising specificity. CoRSeqV3-C may be potentially useful for assisting clinicians to decide the best treatment options for patients with C-HIV infection, and will be helpful for basic studies of C-HIV pathogenesis.
Highlights
The majority of Human immunodeficiency virus type 1 (HIV-1) subjects worldwide are infected with HIV-1 subtype C (C-HIV)
The significant overlap pattern between CXCR4-using and R5 V3 sequences with a net amino acid length of 35 (Figure 1B) suggests that V3 length may not be a characteristic sensitive enough to predict coreceptor usage of most C HIV-1 (C-HIV) strains
Development of a novel C-HIV specific coreceptor usage prediction algorithm we developed a C-HIV specific V3 sequence based coreceptor usage prediction algorithm, founded principally on the V3 characteristics that we showed in the preceding studies could help distinguish CXCR4-using from R5 C-HIV viruses (CoRSeqV3-C)
Summary
The majority of HIV-1 subjects worldwide are infected with HIV-1 subtype C (C-HIV). C-HIV predominates in developing regions of the world such as Southern Africa and Central Asia, C-HIV is spreading rapidly in countries with more developed economies and health care systems, whose populations are more likely to have access to wider treatment options, including the CCR5 antagonist maraviroc (MVC). In silico V3 sequence based coreceptor usage prediction algorithms are a relatively rapid and cost effective method for determining HIV-1 coreceptor specificity. In 40-50% of individuals infected with subtype B HIV-1 (B-HIV), R5X4 and/or X4 viruses (collectively referred to hereafter as CXCR4-using viruses) emerge during disease progression [6,7]. Individuals infected with subtype C HIV-1 (C-HIV) frequently harbor R5 viruses throughout all stages of disease [9] (reviewed in [10,11]). Recent studies are reporting increased incidence of CXCR4-using C-HIV strains emerging at late stages of infection (up to 52%) [12,13,14,15], which may be associated with exposure to antiretroviral therapies (ART). C-HIV is spreading rapidly in more developed nations such as Brazil and neighboring countries [16]
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