Literature DB >> 30721995

Constrained Mutational Sampling of Amino Acids in HIV-1 Protease Evolution.

Jeffrey I Boucher1, Troy W Whitfield2,3, Ann Dauphin4, Gily Nachum1, Carl Hollins1, Konstantin B Zeldovich4, Ronald Swanstrom5, Celia A Schiffer1, Jeremy Luban2,4, Daniel N A Bolon1.   

Abstract

The evolution of HIV-1 protein sequences should be governed by a combination of factors including nucleotide mutational probabilities, the genetic code, and fitness. The impact of these factors on protein sequence evolution is interdependent, making it challenging to infer the individual contribution of each factor from phylogenetic analyses alone. We investigated the protein sequence evolution of HIV-1 by determining an experimental fitness landscape of all individual amino acid changes in protease. We compared our experimental results to the frequency of protease variants in a publicly available data set of 32,163 sequenced isolates from drug-naïve individuals. The most common amino acids in sequenced isolates supported robust experimental fitness, indicating that the experimental fitness landscape captured key features of selection acting on protease during viral infections of hosts. Amino acid changes requiring multiple mutations from the likely ancestor were slightly less likely to support robust experimental fitness than single mutations, consistent with the genetic code favoring chemically conservative amino acid changes. Amino acids that were common in sequenced isolates were predominantly accessible by single mutations from the likely protease ancestor. Multiple mutations commonly observed in isolates were accessible by mutational walks with highly fit single mutation intermediates. Our results indicate that the prevalence of multiple-base mutations in HIV-1 protease is strongly influenced by mutational sampling.
© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  HIV; fitness landscape; mutation

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Year:  2019        PMID: 30721995      PMCID: PMC6804413          DOI: 10.1093/molbev/msz022

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


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