title: 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.
authors.affiliation: The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, China.
authors.forename: Hui-Shuang
authors.initials: HS
authors.lastname: Shen
authors.affiliation: Department of Biostatistics, Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
authors.forename: Jason
authors.initials: J
authors.lastname: Yin
authors.affiliation: The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, China.
authors.forename: Fei
authors.initials: F
authors.lastname: Leng
authors.affiliation: The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, China.
authors.forename: Rui-Fang
authors.initials: RF
authors.lastname: Teng
authors.affiliation: The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, China.
authors.forename: Chao
authors.initials: C
authors.lastname: Xu
authors.affiliation: The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, China.
authors.forename: Xia-Yu
authors.initials: XY
authors.lastname: Xia
authors.affiliation: The Key Laboratory of Bioinformatics, Ministry of Education, School of Life Sciences, Tsinghua University, China.
authors.forename: Xian-Ming
authors.initials: XM
authors.lastname: Pan
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D066264:Datasets as Topic; D015658:HIV Infections / Q000235:genetics* / Q000378:metabolism / Q000821:virology*; D015497:HIV-1 / Q000502:physiology*; D006801:Humans; D009154:Mutation; D012372:ROC Curve; D019713:Receptors, CCR5 / Q000235:genetics* / Q000378:metabolism; D015728:Receptors, HIV / Q000235:genetics* / Q000378:metabolism; D015203:Reproducibility of Results; D056189:Viral Tropism
chemical_list: D019713:Receptors, CCR5; D015728:Receptors, HIV