Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C.

Autor: Posada-Céspedes S; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.; SIB Swiss Institute of Bioinformatics, Basel, Switzerland., Van Zyl G; Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.; National Health Laboratory Service, Cape Town, South Africa., Montazeri H; Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran., Kuipers J; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.; SIB Swiss Institute of Bioinformatics, Basel, Switzerland., Rhee SY; Department of Medicine, Stanford University, Stanford, California, United States of America., Kouyos R; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.; Institute of Medical Virology, University of Zurich, Zurich, Switzerland., Günthard HF; Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.; Institute of Medical Virology, University of Zurich, Zurich, Switzerland., Beerenwinkel N; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.; SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
Jazyk: angličtina
Zdroj: PLoS computational biology [PLoS Comput Biol] 2021 Sep 07; Vol. 17 (9), pp. e1008363. Date of Electronic Publication: 2021 Sep 07 (Print Publication: 2021).
DOI: 10.1371/journal.pcbi.1008363
Abstrakt: Although combination antiretroviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance mutations accumulate in different subtypes also remain poorly understood. Most of this knowledge is derived from studies of subtype B genotypes, despite not being the most abundant subtype worldwide. Here, we present a methodology for the comparison of mutational networks in different HIV-1 subtypes, based on Hidden Conjunctive Bayesian Networks (H-CBN), a probabilistic model for inferring mutational networks from cross-sectional genotype data. We introduce a Monte Carlo sampling scheme for learning H-CBN models for a larger number of resistance mutations and develop a statistical test to assess differences in the inferred mutational networks between two groups. We apply this method to infer the temporal progression of mutations conferring resistance to the protease inhibitor lopinavir in a large cross-sectional cohort of HIV-1 subtype C genotypes from South Africa, as well as to a data set of subtype B genotypes obtained from the Stanford HIV Drug Resistance Database and the Swiss HIV Cohort Study. We find strong support for different initial mutational events in the protease, namely at residue 46 in subtype B and at residue 82 in subtype C. The inferred mutational networks for subtype B versus C are significantly different sharing only five constraints on the order of accumulating mutations with mutation at residue 54 as the parental event. The results also suggest that mutations can accumulate along various alternative paths within subtypes, as opposed to a unique total temporal ordering. Beyond HIV drug resistance, the statistical methodology is applicable more generally for the comparison of inferred mutational networks between any two groups.
Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: H. F. G. has received unrestricted research grants from Gilead Sciences and Roche, fees for data and safety monitoring board membership from Merck; consulting/advisory board membership fees from Gilead Sciences, Viiv and Merck; and grants from SystemsX, and the National Institutes of Health.
Databáze: MEDLINE
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