Virology. Mutation rate and genotype variation of Ebola virus from Mali case sequences.

The occurrence of Ebola virus (EBOV) in West Africa during 2013-2015 is unprecedented. Early reports suggested that in this outbreak EBOV is mutating twice as fast as previously observed, which indicates the potential for changes in transmissibility and virulence and could render current molecular diagnostics and countermeasures ineffective. We have determined additional full-length sequences from two clusters of imported EBOV infections into Mali, and we show that the nucleotide substitution rate (9.6 × 10(-4) substitutions per site per year) is consistent with rates observed in Central African outbreaks. In addition, overall variation among all genotypes observed remains low. Thus, our data indicate that EBOV is not undergoing rapid evolution in humans during the current outbreak. This finding has important implications for outbreak response and public health decisions and should alleviate several previously raised concerns.

Separation of phylogenetic and functional associations in biological sequences by using the parametric bootstrap.

Quantitative analyses of biological sequences generally proceed under the assumption that individual DNA or protein sequence elements vary independently. However, this assumption is not biologically realistic because sequence elements often vary in a concerted manner resulting from common ancestry and structural or functional constraints. We calculated intersite associations among aligned protein sequences by using mutual information. To discriminate associations resulting from common ancestry from those resulting from structural or functional constraints, we used a parametric bootstrap algorithm to construct replicate data sets. These data are expected to have intersite associations resulting solely from phylogeny. By comparing the distribution of our association statistic for the replicate data against that calculated for empirical data, we were able to assign a probability that two sites covaried resulting from structural or functional constraint rather than phylogeny. We tested our method by using an alignment of 237 basic helix-loop-helix (bHLH) protein domains. Comparison of our results against a solved three-dimensional structure confirmed the identification of several sites important to function and structure of the bHLH domain. This analytical procedure has broad utility as a first step in the identification of sites that are important to biological macromolecular structure and function when a solved structure is unavailable.

Correlations among amino acid sites in bHLH protein domains: an information theoretic analysis.

An information theoretic approach is used to examine the magnitude and origin of associations among amino acid sites in the basic helix-loop-helix (bHLH) family of transcription factors. Entropy and mutual information values are used to summarize the variability and covariability of amino acids comprising the bHLH domain for 242 sequences. When these quantitative measures are integrated with crystal structure data and summarized using helical wheels, they provide important insights into the evolution of three-dimensional structure in these proteins. We show that amino acid sites in the bHLH domain known to pack against each other have very low entropy values, indicating little residue diversity at these contact sites. Noncontact sites, on the other hand, exhibit significantly larger entropy values, as well as statistically significant levels of mutual information or association among sites. High levels of mutual information indicate significant amounts of intercorrelation among amino acid residues at these various sites. Using computer simulations based on a parametric bootstrap procedure, we are able to partition the observed covariation among various amino acid sites into that arising from phylogenetic (common ancestry) and stochastic causes and those resulting from structural and functional constraints. These results show that a significant amount of the observed covariation among amino acid sites is due to structural/functional constraints, over and above the covariation arising from phylogenetic constraints. These quantitative analyses provide a highly integrated evolutionary picture of the multidimensional dynamics of sequence diversity and protein structure.