Comparative genomics reveals different population structures associated with host and geographic origin in antimicrobial-resistant Salmonella enterica.

Genetic variation in a pathogen, including the causative agent of salmonellosis, Salmonella enterica, can occur as a result of eco-evolutionary forces triggered by dissimilarities of ecological niches. Here, we applied comparative genomics to study 90 antimicrobial resistant (AMR) S. enterica isolates from bovine and human hosts in New York and Washington states to understand host- and geographic-associated population structure. Results revealed distinct presence/absence profiles of functional genes and pseudogenes (e.g., virulence genes) associated with bovine and human isolates. Notably, bovine isolates contained significantly more transposase genes but fewer transposase pseudogenes than human isolates, suggesting the occurrence of large-scale transposition in genomes of bovine and human isolates at different times. The high correlation between transposase genes and AMR genes, as well as plasmid replicons, highlights the potential role of horizontally transferred transposons in promoting adaptation to antibiotics. By contrast, a number of potentially geographic-associated single-nucleotide polymorphisms (SNPs), rather than geographic-associated genes, were identified. Interestingly, 38% of these SNPs were in genes annotated as cell surface protein-encoding genes, including some essential for antibiotic resistance and host colonization. Overall, different evolutionary forces and limited recent inter-population transmission appear to shape AMR S. enterica population structure in different hosts and geographic origins.

Serotype-specific evolutionary patterns of antimicrobial-resistant Salmonella enterica.

BACKGROUND: The emergence of antimicrobial-resistant (AMR) strains of the important human and animal pathogen Salmonella enterica poses a growing threat to public health. Here, we studied the genome-wide evolution of 90 S. enterica AMR isolates, representing one host adapted serotype (S. Dublin) and two broad host range serotypes (S. Newport and S. Typhimurium). RESULTS: AMR S. Typhimurium had a large effective population size, a large and diverse genome, AMR profiles with high diversity, and frequent positive selection and homologous recombination. AMR S. Newport showed a relatively low level of diversity and a relatively clonal population structure. AMR S. Dublin showed evidence for a recent population bottleneck, and the genomes were characterized by a larger number of genes and gene ontology terms specifically absent from this serotype and a significantly higher number of pseudogenes as compared to other two serotypes. Approximately 50% of accessory genes, including specific AMR and putative prophage genes, were significantly over- or under-represented in a given serotype. Approximately 65% of the core genes showed phylogenetic clustering by serotype, including the AMR gene aac (6')-Iaa. While cell surface proteins were shown to be the main target of positive selection, some proteins with possible functions in AMR and virulence also showed evidence for positive selection. Homologous recombination mainly acted on prophage-associated proteins. CONCLUSIONS: Our data indicates a strong association between genome content of S. enterica and serotype. Evolutionary patterns observed in S. Typhimurium are consistent with multiple emergence events of AMR strains and/or ecological success of this serotype in different hosts or habitats. Evolutionary patterns of S. Newport suggested that antimicrobial resistance emerged in one single lineage, Lineage IIC. A recent population bottleneck and genome decay observed in AMR S. Dublin are congruent with its narrow host range. Finally, our results suggest the potentially important role of positive selection in the evolution of antimicrobial resistance, host adaptation and serotype diversification in S. enterica.

An advanced bioinformatics approach for analyzing RNA-seq data reveals sigma H-dependent regulation of competence genes in Listeria monocytogenes.

BACKGROUND: Alternative σ factors are important transcriptional regulators in bacteria. While σ(B) has been shown to control a large regulon and play important roles in stress response and virulence in the pathogen Listeria monocytogenes, the function of σ(H) has not yet been well defined in Listeria, even though σ(H) controls a large regulon in the closely related non-pathogenic Bacillus subtilis. RESULTS: Using RNA-seq characterization of a L. monocytogenes strain with deletions of all 4 genes encoding alternative σ factors (ΔBCHL), which was further modified to overexpress sigH (ΔBCHL::P rha -sigH), we identified 6 transcription units (TUs) that are transcribed from σ(H)-dependent promoters. Five of these TUs had not been previously identified. Identification of these promoters was facilitated by use of a bio-informatics approach that compared normalized RNA-seq coverage (NRC), between ΔBCHL::P rha -sigH and a ΔBCHL control, using sliding windows of 51 nt along the whole genome rather than comparing NRC calculated only for whole genes. Interestingly, we found that three operons that encode competence genes (comGABCDEFG, comEABC, coiA) are transcribed from σ(H)-dependent promoters. While these promoters were highly conserved in L. monocytogenes, none of them were found in all Listeria spp. and coiA and its σ(H)-dependent promoter were only found in L. monocytogenes. CONCLUSIONS: Our data indicate that a number of L. monocytogenes competence genes are regulated by σ(H). This σ(H)-dependent regulation of competence related genes is conserved in the pathogen L. monocytogenes, but not in other non-pathogenic Listeria strains. Combined with prior data that indicated a role of σ(H) in virulence in a mouse model, this suggests a possible novel role of σ(H)-dependent competence genes in L. monocytogenes virulence. Development and implementation of a sliding window approach to identify differential transcription using RNA-seq data, not only allowed for identification of σ(H)-dependent promoters, but also provides a general approach for sensitive identification of differentially transcribed promoters and genes, particularly for genes that are transcribed from multiple promoter elements only some of which show differential transcription.