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Genotypic Prediction of Co-Receptor Tropism of Hiv-1 Subtypes a and C Publisher Pubmed



Riemenschneider M1 ; Cashin KY2 ; Budeus B3 ; Sierra S4 ; Shirvanidastgerdi E5 ; Bayanolhagh S6 ; Kaiser R4 ; Gorry PR2, 7 ; Heider D1, 8
Authors
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Authors Affiliations
  1. 1. Department of Bioinformatics, Straubing Center of Science, University of Applied Sciences Weihenstephan-Triesdorf, Straubing, Germany
  2. 2. Center for Biomedical Research, Burnet Institute, Melbourne, Australia
  3. 3. Department of Bioinformatics, University of Duisburg-Essen, Essen, Germany
  4. 4. Institute of Virology, University of Cologne, Cologne, Germany
  5. 5. Viral Hepatitis and Immunobiology Lab, University Hospital Aachen, Aachen, Germany
  6. 6. Iranian Research Center of HIV/AIDS, Tehran University of Medical Sciences, Tehran, Iran
  7. 7. School of Applied Sciences, and Program in Metabolism Exercise and Disease, Health Initiatives Research Institute, RMIT University, Melbourne, Australia
  8. 8. Wissenschaftszentrum Weihenstephan, Technische Universitat Munchen, Freising, Germany

Source: Scientific Reports Published:2016


Abstract

Antiretroviral treatment of Human Immunodeficiency Virus type-1 (HIV-1) infections with CCR5-antagonists requires the co-receptor usage prediction of viral strains. Currently available tools are mostly designed based on subtype B strains and thus are in general not applicable to non-B subtypes. However, HIV-1 infections caused by subtype B only account for approximately 11% of infections worldwide. We evaluated the performance of several sequence-based algorithms for co-receptor usage prediction employed on subtype A V3 sequences including circulating recombinant forms (CRFs) and subtype C strains. We further analysed sequence profiles of gp120 regions of subtype A, B and C to explore functional relationships to entry phenotypes. Our analyses clearly demonstrate that state-of-the-art algorithms are not useful for predicting co-receptor tropism of subtype A and its CRFs. Sequence profile analysis of gp120 revealed molecular variability in subtype A viruses. Especially, the V2 loop region could be associated with co-receptor tropism, which might indicate a unique pattern that determines co-receptor tropism in subtype A strains compared to subtype B and C strains. Thus, our study demonstrates that there is a need for the development of novel algorithms facilitating tropism prediction of HIV-1 subtype A to improve effective antiretroviral treatment in patients.