CSESA: an R package to predict Salmonella enterica serotype based on newly incorporated spacer pairs of CRISPR

In silico species identification and serotyping for Cronobacter isolates by use of whole-genome sequencing data

Cronobacter spp. are foodborne pathogens that can cause severe infections in neonates through contaminated powdered infant formula. Accurate and rapid pathogen identification and serotyping are crucial to limit the detrimental effects of bacterial infections, and to prevent outbreaks and sporadic infections. Conventional serotyping is tedious, laborious, and time-consuming; however, with whole-genome sequencing (WGS) becoming faster and cheaper, WGS has vast potential in routine typing and surveillance. Hence, in this study, we developed a publicly available tool, CroTrait (CronobacterTraits), for in silico species identification and O serotyping of Cronobacter isolates based on WGS data. CroTrait showed excellent performance in species identification and O serotyping when 810 genomes with known species identities and 276 genomes with known O serotype were tested. Moreover, CroTrait allows rapid prediction of new potential O serotypes. We identified 11 novel potential O serotypes of Cronobacter using CroTrait. Therefore, CroTrait is a convenient and promising tool for species identification and O serotyping of Cronobacter isolates.

Typing methods based on whole genome sequencing data

Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.