Models of natural mutations including site heterogeneity

Koshi, Jeffrey M.; Goldstein, Richard A.

doi:10.1002/(sici)1097-0134(19980815)32:3<289::aid-prot4>3.0.co;2-d

Cited by 69 publications

(27 citation statements)

References 34 publications

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“…Early simple evolutionary models, that assume that the rate of substitutions at all locations in all proteins at all times followed the same substitution matrix, have been gradually supplemented by mixture models that allow differences in the absolute substitution rates [24], relative substitution rates at different locations [25]–[28], and differences in the substitution rates at different times [29],[30]. Each component of the mixture model, represented by a distinct substitution matrix, reflects a different degree or form of selective pressure.…”

Section: Methodsmentioning

confidence: 99%

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Changing Selective Pressure during Antigenic Changes in Human Influenza H3

Blackburne¹,

Hay²,

Goldstein³

2008

PLoS Pathog

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107

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The rapid evolution of influenza viruses presents difficulties in maintaining the optimal efficiency of vaccines. Amino acid substitutions result in antigenic drift, a process whereby antisera raised in response to one virus have reduced effectiveness against future viruses. Interestingly, while amino acid substitutions occur at a relatively constant rate, the antigenic properties of H3 move in a discontinuous, step-wise manner. It is not clear why this punctuated evolution occurs, whether this represents simply the fact that some substitutions affect these properties more than others, or if this is indicative of a changing relationship between the virus and the host. In addition, the role of changing glycosylation of the haemagglutinin in these shifts in antigenic properties is unknown. We analysed the antigenic drift of HA1 from human influenza H3 using a model of sequence change that allows for variation in selective pressure at different locations in the sequence, as well as at different parts of the phylogenetic tree. We detect significant changes in selective pressure that occur preferentially during major changes in antigenic properties. Despite the large increase in glycosylation during the past 40 years, changes in glycosylation did not correlate either with changes in antigenic properties or with significantly more rapid changes in selective pressure. The locations that undergo changes in selective pressure are largely in places undergoing adaptive evolution, in antigenic locations, and in locations or near locations undergoing substitutions that characterise the change in antigenicity of the virus. Our results suggest that the relationship of the virus to the host changes with time, with the shifts in antigenic properties representing changes in this relationship. This suggests that the virus and host immune system are evolving different methods to counter each other. While we are able to characterise the rapid increase in glycosylation of the haemagglutinin during time in human influenza H3, an increase not present in influenza in birds, this increase seems unrelated to the observed changes in antigenic properties.

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Section: Methodsmentioning

confidence: 99%

“…Model 1 involves a standard single substitution matrix with Gamma-distributed rate variation [24]. In Model 2, we consider that different locations in the protein follow, or ‘are assigned’, to one of a number of different possible substitution matrices [25]–[28]. We do not initially know which sites belong to which substitution matrix.…”

Section: Methodsmentioning

confidence: 99%

Changing Selective Pressure during Antigenic Changes in Human Influenza H3

Blackburne¹,

Hay²,

Goldstein³

2008

PLoS Pathog

Self Cite

107

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“…More advanced phylogenetic methods sometimes allow for different “average” substitution tendencies for different classes of protein residues (such as surface versus core residues, or residues involved in different types of secondary structures) [19]–[24]. Still other methods use simulations or other structure-based methods to derive site-specific substitution matrices for different positions in a protein [25]–[28]. However, none of these methods relate the substitution probabilities to the effects of mutations on experimentally measurable properties such as protein stability, nor do they provide a method for predicting the effects of the mutations from the protein phylogenies.…”

Section: Introductionmentioning

confidence: 99%

Inferring Stabilizing Mutations from Protein Phylogenies: Application to Influenza Hemagglutinin

Bloom

Glassman²

2009

PLoS Comput Biol

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One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution.

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“…Thorne et al (2007) relaxed the standard assumption of independent sites, considering the selective constraints imposed by the need to maintain a stable well-defined structure; this was estimated using protein structure prediction algorithms, despite their construction being motivated by a quite different problem. Rodrigue et al (2010) adapted a mixture-model approach that grouped locations under similar selective constraints and developed more specific models for characterizing these different types of locations; each individual location was then represented by a mixture of these models (Koshi and Goldstein 1998). The available data determined the number of components in the mixture that could be justified.…”

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confidence: 99%

Estimating the Distribution of Selection Coefficients from Phylogenetic Data Using Sitewise Mutation-Selection Models

2012

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Estimation of the distribution of selection coefficients of mutations is a long-standing issue in molecular evolution. In addition to population-based methods, the distribution can be estimated from DNA sequence data by phylogenetic-based models. Previous models have generally found unimodal distributions where the probability mass is concentrated between mildly deleterious and nearly neutral mutations. Here we use a sitewise mutation–selection phylogenetic model to estimate the distribution of selection coefficients among novel and fixed mutations (substitutions) in a data set of 244 mammalian mitochondrial genomes and a set of 401 PB2 proteins from influenza. We find a bimodal distribution of selection coefficients for novel mutations in both the mitochondrial data set and for the influenza protein evolving in its natural reservoir, birds. Most of the mutations are strongly deleterious with the rest of the probability mass concentrated around mildly deleterious to neutral mutations. The distribution of the coefficients among substitutions is unimodal and symmetrical around nearly neutral substitutions for both data sets at adaptive equilibrium. About 0.5% of the nonsynonymous mutations and 14% of the nonsynonymous substitutions in the mitochondrial proteins are advantageous, with 0.5% and 24% observed for the influenza protein. Following a host shift of influenza from birds to humans, however, we find among novel mutations in PB2 a trimodal distribution with a small mode of advantageous mutations.

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Models of natural mutations including site heterogeneity

Cited by 69 publications

References 34 publications

Changing Selective Pressure during Antigenic Changes in Human Influenza H3

Changing Selective Pressure during Antigenic Changes in Human Influenza H3

Inferring Stabilizing Mutations from Protein Phylogenies: Application to Influenza Hemagglutinin

Estimating the Distribution of Selection Coefficients from Phylogenetic Data Using Sitewise Mutation-Selection Models

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