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Competing evolutionary paths in growing populations with applications to multidrug resistance.

ABSTRACT: Investigating the emergence of a particular cell type is a recurring theme in models of growing cellular populations. The evolution of resistance to therapy is a classic example. Common questions are: when does the cell type first occur, and via which sequence of steps is it most likely to emerge? For growing populations, these questions can be formulated in a general framework of branching processes spreading through a graph from a root to a target vertex. Cells have a particular fitness value on each vertex and can transition along edges at specific rates. Vertices represent cell states, say genotypes or physical locations, while possible transitions are acquiring a mutation or cell migration. We focus on the setting where cells at the root vertex have the highest fitness and transition rates are small. Simple formulas are derived for the time to reach the target vertex and for the probability that it is reached along a given path in the graph. We demonstrate our results on several scenarios relevant to the emergence of drug resistance, including: the orderings of resistance-conferring mutations in bacteria and the impact of imperfect drug penetration in cancer.

SUBMITTER: Nicholson MD

PROVIDER: S-EPMC6483269 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Competing evolutionary paths in growing populations with applications to multidrug resistance.

Nicholson Michael D MD Antal Tibor T

PLoS computational biology 20190415 4

Investigating the emergence of a particular cell type is a recurring theme in models of growing cellular populations. The evolution of resistance to therapy is a classic example. Common questions are: when does the cell type first occur, and via which sequence of steps is it most likely to emerge? For growing populations, these questions can be formulated in a general framework of branching processes spreading through a graph from a root to a target vertex. Cells have a particular fitness value ...[more]

PMID: 30986219

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Project description:BACKGROUND: Streptococcus pyogenes (GAS) harbors several superantigens (SAgs) in the prophage region of its genome, although speG and smez are not located in this region. The diversity of SAgs is thought to arise during horizontal transfer, but their evolutionary pathways have not yet been determined. We recently completed sequencing the entire genome of S. dysgalactiae subsp. equisimilis (SDSE), the closest relative of GAS. Although speG is the only SAg gene of SDSE, speG was present in only 50% of clinical SDSE strains and smez in none. In this study, we analyzed the evolutionary paths of streptococcal and staphylococcal SAgs. RESULTS: We compared the sequences of the 12-60 kb speG regions of nine SDSE strains, five speG(+) and four speG(-). We found that the synteny of this region was highly conserved, whether or not the speG gene was present. Synteny analyses based on genome-wide comparisons of GAS and SDSE indicated that speG is the direct descendant of a common ancestor of streptococcal SAgs, whereas smez was deleted from SDSE after SDSE and GAS split from a common ancestor. Cumulative nucleotide skew analysis of SDSE genomes suggested that speG was located outside segments of steeper slopes than the stable region in the genome, whereas the region flanking smez was unstable, as expected from the results of GAS. We also detected a previously undescribed staphylococcal SAg gene, selW, and a staphylococcal SAg -like gene, ssl, in the core genomes of all Staphylococcus aureus strains sequenced. Amino acid substitution analyses, based on dN/dS window analysis of the products encoded by speG, selW and ssl suggested that all three genes have been subjected to strong positive selection. Evolutionary analysis based on the Bayesian Markov chain Monte Carlo method showed that each clade included at least one direct descendant. CONCLUSIONS: Our findings reveal a plausible model for the comprehensive evolutionary pathway of streptococcal and staphylococcal SAgs.

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Competing evolutionary paths in growing populations with applications to multidrug resistance.

Publications

Competing evolutionary paths in growing populations with applications to multidrug resistance.

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