The utility of protein structure as a predictor of site-wise d<i>N</i>/d<i>S</i>varies widely among HIV-1 proteins

Meyer, Austin G.; Wilke, Claus O.

doi:10.1098/rsif.2015.0579

Cited by 12 publications

(18 citation statements)

References 54 publications

(72 reference statements)

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“…In a similar manner, volatility of individual amino acids is controlled by immune and fitness pressures applied on each position. The effect of such pressures is associated with the degree of solvent exposure of the residue [131, 132]. As expected, our data suggest that a cryptic state is associated with lower volatility (Fig 4D).…”

Section: Discussionsupporting

confidence: 78%

Accurate predictions of population-level changes in sequence and structural properties of HIV-1 Env using a volatility-controlled diffusion model

et al. 2017

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The envelope glycoproteins (Envs) of HIV-1 continuously evolve in the host by random mutations and recombination events. The resulting diversity of Env variants circulating in the population and their continuing diversification process limit the efficacy of AIDS vaccines. We examined the historic changes in Env sequence and structural features (measured by integrity of epitopes on the Env trimer) in a geographically defined population in the United States. As expected, many Env features were relatively conserved during the 1980s. From this state, some features diversified whereas others remained conserved across the years. We sought to identify “clues” to predict the observed historic diversification patterns. Comparison of viruses that cocirculate in patients at any given time revealed that each feature of Env (sequence or structural) exists at a defined level of variance. The in-host variance of each feature is highly conserved among individuals but can vary between different HIV-1 clades. We designate this property “volatility” and apply it to model evolution of features as a linear diffusion process that progresses with increasing genetic distance. Volatilities of different features are highly correlated with their divergence in longitudinally monitored patients. Volatilities of features also correlate highly with their population-level diversification. Using volatility indices measured from a small number of patient samples, we accurately predict the population diversity that developed for each feature over the course of 30 years. Amino acid variants that evolved at key antigenic sites are also predicted well. Therefore, small “fluctuations” in feature values measured in isolated patient samples accurately describe their potential for population-level diversification. These tools will likely contribute to the design of population-targeted AIDS vaccines by effectively capturing the diversity of currently circulating strains and addressing properties of variants expected to appear in the future.

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Section: Discussionsupporting

confidence: 78%

Accurate predictions of population-level changes in sequence and structural properties of HIV-1 Env using a volatility-controlled diffusion model

et al. 2017

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“…For instance, sites on the apical surface of Env evolve especially rapidly [104]. These differences in evolutionary rate arise from two factors.…”

Section: Resultsmentioning

confidence: 99%

Experimental Estimation of the Effects of All Amino-Acid Mutations to HIV’s Envelope Protein on Viral Replication in Cell Culture

2016

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HIV is notorious for its capacity to evade immunity and anti-viral drugs through rapid sequence evolution. Knowledge of the functional effects of mutations to HIV is critical for understanding this evolution. HIV’s most rapidly evolving protein is its envelope (Env). Here we use deep mutational scanning to experimentally estimate the effects of all amino-acid mutations to Env on viral replication in cell culture. Most mutations are under purifying selection in our experiments, although a few sites experience strong selection for mutations that enhance HIV’s replication in cell culture. We compare our experimental measurements of each site’s preference for each amino acid to the actual frequencies of these amino acids in naturally occurring HIV sequences. Our measured amino-acid preferences correlate with amino-acid frequencies in natural sequences for most sites. However, our measured preferences are less concordant with natural amino-acid frequencies at surface-exposed sites that are subject to pressures absent from our experiments such as antibody selection. Our data enable us to quantify the inherent mutational tolerance of each site in Env. We show that the epitopes of broadly neutralizing antibodies have a significantly reduced inherent capacity to tolerate mutations, rigorously validating a pervasive idea in the field. Overall, our results help disentangle the role of inherent functional constraints and external selection pressures in shaping Env’s evolution.

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“…One strategy is to predict site-specific constraints from higher-level properties such as solvent accessibility [64–66] or via molecular simulation [67–70]. It remains unclear whether such non-experimental strategies can predict site-specific amino-acid preferences with sufficient accuracy to inform substitution models that can match the ExpCM used here.…”

Section: Discussionmentioning

confidence: 99%

Identification of positive selection in genes is greatly improved by using experimentally informed site-specific models

Bloom

2017

Biol Direct

122

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BackgroundSites of positive selection are identified by comparing observed evolutionary patterns to those expected under a null model for evolution in the absence of such selection. For protein-coding genes, the most common null model is that nonsynonymous and synonymous mutations fix at equal rates; this unrealistic model has limited power to detect many interesting forms of selection.ResultsI describe a new approach that uses a null model based on experimental measurements of a gene’s site-specific amino-acid preferences generated by deep mutational scanning in the lab. This null model makes it possible to identify both diversifying selection for repeated amino-acid change and differential selection for mutations to amino acids that are unexpected given the measurements made in the lab. I show that this approach identifies sites of adaptive substitutions in four genes (lactamase, Gal4, influenza nucleoprotein, and influenza hemagglutinin) far better than a comparable method that simply compares the rates of nonsynonymous and synonymous substitutions.ConclusionsAs rapid increases in biological data enable increasingly nuanced descriptions of the constraints on individual protein sites, approaches like the one here can improve our ability to identify many interesting forms of selection in natural sequences.ReviewersThis article was reviewed by Sebastian Maurer-Stroh, Olivier Tenaillon, and Tal Pupko. All three reviewers are members of the Biology Direct editorial board.Electronic supplementary materialThe online version of this article (doi:10.1186/s13062-016-0172-z) contains supplementary material, which is available to authorized users.

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The utility of protein structure as a predictor of site-wise dN/dSvaries widely among HIV-1 proteins

Cited by 12 publications

References 54 publications

Accurate predictions of population-level changes in sequence and structural properties of HIV-1 Env using a volatility-controlled diffusion model

Accurate predictions of population-level changes in sequence and structural properties of HIV-1 Env using a volatility-controlled diffusion model

Experimental Estimation of the Effects of All Amino-Acid Mutations to HIV’s Envelope Protein on Viral Replication in Cell Culture

Identification of positive selection in genes is greatly improved by using experimentally informed site-specific models

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