Genome-Wide Association Study of Listeria monocytogenes Isolates Causing Three Different Clinical Outcomes

Abstract

Heterogeneity in virulence potential of L. monocytogenes subgroups have been associated with genetic elements that could provide advantages in certain environments to invade, multiply, and survive within a host. The presence of gene mutations has been found to be related to attenuated phenotypes, while the presence of groups of genes, such as pathogenicity islands (PI), has been associated with hypervirulent or stress-resistant clones. We evaluated 232 whole genome sequences from invasive listeriosis cases in human and ruminants from the US and Europe to identify genomic elements associated with strains causing three clinical outcomes: central nervous system (CNS) infections, maternal-neonatal (MN) infections, and systemic infections (SI). Phylogenetic relationships and virulence-associated genes were evaluated, and a gene-based and single nucleotide polymorphism (SNP)-based genome-wide association study (GWAS) were conducted in order to identify loci associated with the different clinical outcomes. The orthologous results indicated that genes of phage phiX174, transfer RNAs, and type I restriction-modification (RM) system genes along with SNPs in loci involved in environmental adaptation such as rpoB and a phosphotransferase system (PTS) were associated with one or more clinical outcomes. Detection of phenotype-specific candidate loci represents an approach that could narrow the group of genetic elements to be evaluated in future studies.

Improvement of quantitative microbiological risk assessment (QMRA) methodology through integration with gaenetic data

“…Recent studies highlighted differences in virulence among Lm strains based on the presence or absence of a truncated inlA gene, suggesting that the severity of illness should be considered when improving QMRA models using WGS data (Pouillot et al., 2015; Chen et al., 2020). Moreover, several studies reported differences in virulence between strains based on variations in lineages, serotypes and CCs (Nielsen et al., 2017; Fritsch et al., 2019; Maury et al., 2019; Quereda et al., 2021; Cardenas‐Alvarez et al., 2022; Muchaamba et al., 2022).…”

Virotyping and genetic antimicrobial susceptibility testing of porcine ETEC/STEC strains and associated plasmid types

“…Nevertheless, ARG database searches often result in extensive lists of genes, which do not necessarily contribute to phenotypic resistance. By applying combined searches of databases (e.g., abricate and Resfinder) in combination with GWAS tools (e.g., gene- and k-mer based) a more comprehensive output can be generated ( Jaillard et al, 2018 ; Farhat et al, 2019 ; Bokma et al, 2021 ; Weber et al, 2021 ; Cardenas-Alvarez et al, 2022 ). Here, good predictive power was shown for 13 different antimicrobial drugs for which a non-WT population (ECOFF) was determined based on the NRI method for their AMR phenotypes.…”