68 research outputs found
Segment self-repulsion is the major driving force of influenza genome packaging
The genome of influenza A virus consists of eight separate RNA segments, which are selectively packaged into virions prior to virus budding. The microscopic mechanism of highly selective packaging involves molecular interactions between packaging signals in the genome segments and remains poorly understood. We propose that the condition of proper packaging can be formulated as a large gap between RNA-RNA interaction energies in the viable virion with eight unique segments and in improperly packed assemblages lacking the complete genome. We then demonstrate that selective packaging of eight unique segments into an infective influenza virion can be achieved by self-repulsion of identical segments at the virion assembly stage, rather than by previously hypothesized intricate molecular recognition of particular segments. Using Monte Carlo simulations to maximize the energy gap, without any other assumptions, we generated model eight-segment virions, which all display specific packaging, strong self-repulsion of the segments, and reassortment patterns similar to natural influenza. The model provides a biophysical foundation of influenza genome packaging and reassortment and serves as an important step towards robust sequence-driven prediction of reassortment patterns of the influenza virus
Thermophilic Adaptation in Prokaryotes Is Constrained by Metabolic Costs of Proteostasis
Prokaryotes evolved to thrive in an extremely diverse set of habitats, and their proteomes bear signatures of environmental conditions. Although correlations between amino acid usage and environmental temperature are well-documented, understanding of the mechanisms of thermal adaptation remains incomplete. Here, we couple the energetic costs of protein folding and protein homeostasis to build a microscopic model explaining both the overall amino acid composition and its temperature trends. Low biosynthesis costs lead to low diversity of physical interactions between amino acid residues, which in turn makes proteins less stable and drives up chaperone activity to maintain appropriate levels of folded, functional proteins. Assuming that the cost of chaperone activity is proportional to the fraction of unfolded client proteins, we simulated thermal adaptation of model proteins subject to minimization of the total cost of amino acid synthesis and chaperone activity. For the first time, we predicted both the proteome-average amino acid abundances and their temperature trends simultaneously, and found strong correlations between model predictions and 402 genomes of bacteria and archaea. The energetic constraint on protein evolution is more apparent in highly expressed proteins, selected by codon adaptation index. We found that in bacteria, highly expressed proteins are similar in composition to thermophilic ones, whereas in archaea no correlation between predicted expression level and thermostability was observed. At the same time, thermal adaptations of highly expressed proteins in bacteria and archaea are nearly identical, suggesting that universal energetic constraints prevail over the phylogenetic differences between these domains of life
Protein and DNA sequence determinants of thermophilic adaptation
Prokaryotes living at extreme environmental temperatures exhibit pronounced
signatures in the amino acid composition of their proteins and nucleotide
compositions of their genomes reflective of adaptation to their thermal
environments. However, despite significant efforts, the definitive answer of
what are the genomic and proteomic compositional determinants of Optimal Growth
Temperature of prokaryotic organisms remained elusive. Here the authors
performed a comprehensive analysis of amino acid and nucleotide compositional
signatures of thermophylic adaptation by exhaustively evaluating all
combinations of amino acids and nucleotides as possible determinants of Optimal
Growth Temperature for all prokaryotic organisms with fully sequences genomes..
The authors discovered that total concentration of seven amino acids in
proteomes, IVYWREL, serves as a universal proteomic predictor of Optimal Growth
Temperature in prokaryotes. Resolving the old-standing controversy the authors
determined that the variation in nucleotide composition (increase of purine
load, or A+G content with temperature) is largely a consequence of thermal
adaptation of proteins. However, the frequency with which A and G nucleotides
appear as nearest neighbors in genome sequences is strongly and independently
correlated with Optimal Growth Temperature. as a result of codon bias in
corresponding genomes. Together these results provide a complete picture of
proteomic and genomic determinants of thermophilic adaptation.Comment: in press PLoS Computational Biology; revised versio
A first-principles model of early evolution: Emergence of gene families, species and preferred protein folds
In this work we develop a microscopic physical model of early evolution,
where phenotype,organism life expectancy, is directly related to genotype, the
stability of its proteins in their native conformations which can be determined
exactly in the model. Simulating the model on a computer, we consistently
observe the Big Bang scenario whereby exponential population growth ensues as
soon as favorable sequence-structure combinations (precursors of stable
proteins) are discovered. Upon that, random diversity of the structural space
abruptly collapses into a small set of preferred proteins. We observe that
protein folds remain stable and abundant in the population at time scales much
greater than mutation or organism lifetime, and the distribution of the
lifetimes of dominant folds in a population approximately follows a power law.
The separation of evolutionary time scales between discovery of new folds and
generation of new sequences gives rise to emergence of protein families and
superfamilies whose sizes are power-law distributed, closely matching the same
distributions for real proteins. On the population level we observe emergence
of species, subpopulations which carry similar genomes. Further we present a
simple theory that relates stability of evolving proteins to the sizes of
emerging genomes. Together, these results provide a microscopic first
principles picture of how first gene families developed in the course of early
evolutionComment: In press, PLoS Computational Biolog
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