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

Abstract

<jats:title>Summary</jats:title><jats:p>Genetic variation in a pathogen, including the causative agent of salmonellosis, <jats:italic>Salmonella enterica</jats:italic>, 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) <jats:italic>S. enterica</jats:italic> isolates from bovine and human hosts in New York state and Washington state 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 <jats:italic>S. enterica</jats:italic> population structure in different hosts and geographic origins.</jats:p><jats:sec><jats:title>Originality/Significance Statement</jats:title><jats:p><jats:italic>Salmonella enterica</jats:italic>, which is the causative agent of salmonellosis, poses a growing public health concern due to the emergence and spread of antimicrobial resistant (AMR) strains. The mechanisms underlying the population structure associated with different hosts and geographic origins of AMR <jats:italic>S. enterica</jats:italic> are underexplored due to limited genome-wide studies assessing the impact of ecological niches on genetic variations. By employing comparative genomics, our study provided insights into the genomic profiles of AMR <jats:italic>S. enterica</jats:italic> associated with two distinct hosts and two distant geographic locations, improving the mechanistic understanding of how bacterial population structure is shaped by different ecological niches. Our findings have broad implications for elucidating the impact of ecological and evolutionary forces on the adaptation, antimicrobial resistance, and pathogenicity of bacteria. Also, specific genetic markers we identified may help predict host or geographic origin of AMR <jats:italic>Salmonella</jats:italic> isolates, which could benefit the source tracking (e.g., host and geographic origins) of human disease cases and contamination events caused by AMR <jats:italic>S. enterica</jats:italic>.</jats:p></jats:sec>

Disentangle genus microdiversity within a complex microbial community by using a multi‐distance long‐read binning method: example of Candidatus Accumulibacter

“…Even though, they can carry genes of importance such as antimicrobial resistance genes (Konstantinidis and Tiedje, 2005; Zowawi et al ., 2015). For example, plasmids can play an important role in strain‐level adaptation to a specific niche or virulence factor (Arredondo‐Alonso et al ., 2020; Koch et al ., 2020; Liao et al ., 2020), but they are often not included in MAGs. It has been suggested that plasmids contain a common pool of genes that contribute to the adaptation of the whole bacterial community to specific selective conditions (Sentchilo et al ., 2013).…”

Systems-based approach for optimization of a scalable bacterial ST mapping assembly-free algorithm

“…The incorporation of WGS technology has advanced the study of bacterial populations, since it has facilitated genotyping at different levels of resolution, which in turn has proven to be predictive of, or associated with, inferable ecological traits or epidemiological patterns [21] [32] [33][34] [35][36][37] [38]. In particular, the use of a hierarchical population structure analysis allows for ancestral relationships and patterns of diversification to be inferred, while determining the most important informative genotypic unit to be tracked over time [21][39] [40][41] [12][42] [43]. ST-based classification is an integral part of the hierarchical genotyping approach [21] [27].…”

Monitoring the Antimicrobial Resistance Dynamics of Salmonella enterica in Healthy Dairy Cattle Populations at the Individual Farm Level Using Whole-Genome Sequencing

“…Geography has been shown to play an important role in shaping bacterial populations (Achtman, 2008;Strachan et al, 2015), including some Salmonella lineages (Carroll et al, 2017b;Palma et al, 2018;Fenske et al, 2019;Liao et al, 2020). However, for some foodborne pathogens, including some Salmonella populations, global spread of lineages due to human migration and movement of food and animals can often obfuscate local phylogeographic signals (Wong et al, 2015;Llarena et al, 2016;The et al, 2016;Palma et al, 2018).…”