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Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling.

ABSTRACT: The Binary State Speciation and Extinction (BiSSE) model is a branching process based model that allows the diversification rates to be controlled by a binary trait. We develop a general approach, based on the BiSSE model, for predicting pathogenicity in bacterial populations from microsatellites profiling data. A comprehensive approach for predicting pathogenicity in E. coli populations is proposed using the state-dependent branching process model combined with microsatellites TRS-PCR profiling. Additionally, we have evaluated the possibility of using the BiSSE model for estimating parameters from genetic data. We analyzed a real dataset (from 251 E. coli strains) and confirmed previous biological observations demonstrating a prevalence of some virulence traits in specific bacterial sub-groups. The method may be used to predict pathogenicity of other bacterial taxa.

SUBMITTER: Bartoszek K

PROVIDER: S-EPMC5809097 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling.

Bartoszek Krzysztof K Majchrzak Marta M Sakowski Sebastian S Kubiak-Szeligowska Anna B AB Kaj Ingemar I Parniewski Pawel P

PLoS computational biology 20180131 1

The Binary State Speciation and Extinction (BiSSE) model is a branching process based model that allows the diversification rates to be controlled by a binary trait. We develop a general approach, based on the BiSSE model, for predicting pathogenicity in bacterial populations from microsatellites profiling data. A comprehensive approach for predicting pathogenicity in E. coli populations is proposed using the state-dependent branching process model combined with microsatellites TRS-PCR profiling ...[more]

PMID: 29385125

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Project description:BackgroundThere are several studies describing loss of genes through reductive evolution in microbes, but how selective forces are associated with genome expansion due to horizontal gene transfer (HGT) has not received similar attention. The aim of this study was therefore to examine how selective pressures influence genome expansion in 53 fully sequenced and assembled Escherichia coli strains. We also explored potential connections between genome expansion and the attainment of virulence factors. This was performed using estimations of several genomic parameters such as AT content, genomic drift (measured using relative entropy), genome size and estimated HGT size, which were subsequently compared to analogous parameters computed from the core genome consisting of 1729 genes common to the 53 E. coli strains. Moreover, we analyzed how selective pressures (quantified using relative entropy and dN/dS), acting on the E. coli core genome, influenced lineage and phylogroup formation.ResultsHierarchical clustering of dS and dN estimations from the E. coli core genome resulted in phylogenetic trees with topologies in agreement with known E. coli taxonomy and phylogroups. High values of dS, compared to dN, indicate that the E. coli core genome has been subjected to substantial purifying selection over time; significantly more than the non-core part of the genome (p<0.001). This is further supported by a linear association between strain-wise dS and dN values (β = 26.94 ± 0.44, R2~0.98, p<0.001). The non-core part of the genome was also significantly more AT-rich (p<0.001) than the core genome and E. coli genome size correlated with estimated HGT size (p<0.001). In addition, genome size (p<0.001), AT content (p<0.001) as well as estimated HGT size (p<0.005) were all associated with the presence of virulence factors, suggesting that pathogenicity traits in E. coli are largely attained through HGT. No associations were found between selective pressures operating on the E. coli core genome, as estimated using relative entropy, and genome size (p~0.98).ConclusionsOn a larger time frame, genome expansion in E. coli, which is significantly associated with the acquisition of virulence factors, appears to be independent of selective forces operating on the core genome.

Project description:BackgroundThe modification of glucose import capacity is an engineering strategy that has been shown to improve the characteristics of Escherichia coli as a microbial factory. A reduction in glucose import capacity can have a positive effect on production strain performance, however, this is not always the case. In this study, E. coli W3110 and a group of four isogenic derivative strains, harboring single or multiple deletions of genes encoding phosphoenolpyruvate:sugar phosphotransferase system (PTS)-dependent transporters as well as non-PTS transporters were characterized by determining their transcriptomic response to reduced glucose import capacity.ResultsThese strains were grown in bioreactors with M9 mineral salts medium containing 20 g/L of glucose, where they displayed specific growth rates ranging from 0.67 to 0.27 h-1, and specific glucose consumption rates (qs) ranging from 1.78 to 0.37 g/g h. RNA-seq analysis revealed a transcriptional response consistent with carbon source limitation among all the mutant strains, involving functions related to transport and metabolism of alternate carbon sources and characterized by a decrease in genes encoding glycolytic enzymes and an increase in gluconeogenic functions. A total of 107 and 185 genes displayed positive and negative correlations with qs, respectively. Functions displaying positive correlation included energy generation, amino acid biosynthesis, and sugar import.ConclusionChanges in gene expression of E. coli strains with impaired glucose import capacity could be correlated with qs values and this allowed an inference of the physiological state of each mutant. In strains with lower qs values, a gene expression pattern is consistent with energy limitation and entry into the stationary phase. This physiological state could explain why these strains display a lower capacity to produce recombinant protein, even when they show very low rates of acetate production. The comparison of the transcriptomes of the engineered strains employed as microbial factories is an effective approach for identifying favorable phenotypes with the potential to improve the synthesis of biotechnological products.

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Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling.

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Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling.

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