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HIV-1 A和C亚型共受体嗜性的基因分型预测

Genotypic Prediction of Co-receptor Tropism of HIV-1 Subtypes A and C.

作者信息

Riemenschneider Mona, Cashin Kieran Y, Budeus Bettina, Sierra Saleta, Shirvani-Dastgerdi Elham, Bayanolhagh Saeed, Kaiser Rolf, Gorry Paul R, Heider Dominik

机构信息

Department of Bioinformatics, Straubing Center of Science, University of Applied Sciences Weihenstephan-Triesdorf, Straubing, Germany.

Center for Biomedical Research, Burnet Institute, Melbourne, Australia.

出版信息

Sci Rep. 2016 Apr 29;6:24883. doi: 10.1038/srep24883.

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.

摘要

使用CCR5拮抗剂对抗人类免疫缺陷病毒1型(HIV-1)感染进行抗逆转录病毒治疗需要预测病毒株的共受体使用情况。目前可用的工具大多基于B亚型毒株设计,因此一般不适用于非B亚型。然而,由B亚型引起的HIV-1感染仅占全球感染的约11%。我们评估了几种基于序列的算法在A亚型V3序列(包括循环重组形式(CRF)和C亚型毒株)上进行共受体使用预测的性能。我们进一步分析了A、B和C亚型gp120区域的序列特征,以探索与进入表型的功能关系。我们的分析清楚地表明,最先进的算法对于预测A亚型及其CRF的共受体嗜性无用。gp120的序列特征分析揭示了A亚型病毒的分子变异性。特别是,V2环区域可能与共受体嗜性相关,这可能表明与B和C亚型毒株相比,A亚型毒株中决定共受体嗜性的独特模式。因此,我们的研究表明,需要开发新的算法来促进HIV-1 A亚型的嗜性预测,以改善患者的有效抗逆转录病毒治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3637/4850382/277fa4c72b20/srep24883-f1.jpg

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