Combining Whole-Genome Sequencing and Multimodel Phenotyping To Identify Genetic Predictors of Salmonella Virulence.

Salmonella comprises more than 2,600 serovars. Very few environmental and uncommon serovars have been characterized for their potential role in virulence and human infections. A complementary in vitro and in vivo systematic high-throughput analysis of virulence was used to elucidate the association between genetic and phenotypic variations across Salmonella isolates. The goal was to develop a strategy for the classification of isolates as a benchmark and predict virulence levels of isolates. Thirty-five phylogenetically distant strains of unknown virulence were selected from the Salmonella Foodborne Syst-OMICS (SalFoS) collection, representing 34 different serovars isolated from various sources. Isolates were evaluated for virulence in 4 complementary models of infection to compare virulence traits with the genomics data, including interactions with human intestinal epithelial cells, human macrophages, and amoeba. In vivo testing was conducted using the mouse model of Salmonella systemic infection. Significant correlations were identified between the different models. We identified a collection of novel hypothetical and conserved proteins associated with isolates that generate a high burden. We also showed that blind prediction of virulence of 33 additional strains based on the pan-genome was high in the mouse model of systemic infection (82% agreement) and in the human epithelial cell model (74% agreement). These complementary approaches enabled us to define virulence potential in different isolates and present a novel strategy for risk assessment of specific strains and for better monitoring and source tracking during outbreaks.IMPORTANCESalmonella species are bacteria that are a major source of foodborne disease through contamination of a diversity of foods, including meat, eggs, fruits, nuts, and vegetables. More than 2,600 different Salmonella enterica serovars have been identified, and only a few of them are associated with illness in humans. Despite the fact that they are genetically closely related, there is enormous variation in the virulence of different isolates of Salmonella enterica Identification of foodborne pathogens is a lengthy process based on microbiological, biochemical, and immunological methods. Here, we worked toward new ways of integrating whole-genome sequencing (WGS) approaches into food safety practices. We used WGS to build associations between virulence and genetic diversity within 83 Salmonella isolates representing 77 different Salmonella serovars. Our work demonstrates the potential of combining a genomics approach and virulence tests to improve the diagnostics and assess risk of human illness associated with specific Salmonella isolates.

New Roles for Two-Component System Response Regulators of Salmonella enterica Serovar Typhi during Host Cell Interactions.

In order to survive external stresses, bacteria need to adapt quickly to changes in their environment. One adaptive mechanism is to coordinate and alter their gene expression by using two-component systems (TCS). TCS are composed of a sensor kinase that activates a transcriptional response regulator by phosphorylation. TCS are involved in motility, virulence, nutrient acquisition, and envelope stress in many bacteria. The pathogenic bacteria Salmonella enterica serovar Typhi (S. Typhi) possess 30 TCSs, is specific to humans, and causes typhoid fever. Here, we have individually deleted each of the 30 response regulators. We have determined their role during interaction with host cells (epithelial cells and macrophages). Deletion of most of the systems (24 out of 30) resulted in a significant change during infection. We have identified 32 new phenotypes associated with TCS of S. Typhi. Some previously known phenotypes associated with TCSs in Salmonella were also confirmed. We have also uncovered phenotypic divergence between Salmonella serovars, as distinct phenotypes between S. Typhi and S. Typhimurium were identified for cpxR. This finding highlights the importance of specifically studying S. Typhi to understand its pathogenesis mechanisms and to develop strategies to potentially reduce typhoid infections.

A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis.

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.