Microbial Genomics · 2020 · 40 citations · 49 references
Life SciencesGeneticsMicrobiologyGenome EvolutionGenomicsMicrobial EvolutionBacterial Virulence FactorsHorizontal Gene TransferMicrobial Virulence FactorsPangenome EvolutionPathogen Virulence FactorsPhage GeneticsBacterial Genome EvolutionEscherichia ColiPhage-encoded Virulence GenesPlasmid EvolutionPlasmid Evolutionary DynamicsPlasmid-borne Virulence FactorsShiga ToxinsVirulence Gene Transfer
Phages and plasmids play important roles in bacterial evolution and diversification. Although many draft genomes have been generated, phage and plasmid genomes are usually fragmented, limiting our understanding of their dynamics. Here, we performed a systematic analysis of 239 draft genomes and 7 complete genomes of Shiga toxin (Stx)-producing Escherichia coli O145:H28, the major virulence factors of which are encoded by prophages (PPs) or plasmids. The results indicated that PPs are more stably maintained than plasmids. A set of ancestrally acquired PPs was well conserved, while various PPs, including Stx phages, were acquired by multiple sublineages. In contrast, gains and losses of a wide range of plasmids have frequently occurred across the O145:H28 lineage, and only the virulence plasmid was well conserved. The different dynamics of PPs and plasmids have differentially impacted the pangenome of O145:H28, with high proportions of PP- and plasmid-associated genes in the variably present and rare gene fractions, respectively. The dynamics of PPs and plasmids have also strongly impacted virulence gene repertoires, such as the highly variable distribution of stx genes and the high conservation of a set of type III secretion effectors, which probably represents the core effectors of O145:H28 and the genes on the virulence plasmid in the entire O145:H28 population. These results provide detailed insights into the dynamics of PPs and plasmids, and show the application of genomic analyses using a large set of draft genomes and appropriately selected complete genomes.
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CD-HIT: accelerated for clustering the next-generation sequencing data
LiMin Fu, Beifang Niu, Zhengwei Zhu et al. · Bioinformatics · 2012 · 11.8K citations · Full text
Life Sciences, Bioinformatics, High-performance Computing +12
Bayesian Phylogenetics with BEAUti and the BEAST 1.7
Alexei J. Drummond, Marc A. Suchard, Dong Xie et al. · Molecular Biology and Evolution · 2012 · 10.4K citations · Full text