Genome-Scale Screening and Validation of Targets for Identification of Salmonella enterica and Serovar Prediction

摘要

Salmonella enterica is the most common foodborne pathogen worldwide, with 2,500 recognized serovars. Detection of S. enterica and its classification into serovars are essential for food safety surveillance and clinical diagnosis. The PCR method is useful for these applications because of its rapidity and high accuracy. We obtained 412 candidate detection targets for S. enterica using a comparative genomics mining approach. Gene ontology (GO) functional enrichment analysis of these candidate targets revealed that the GO term with the largest number of unigenes with known function (38 of 177, 21.5%) was significantly involved in pathogenesis (P ＜ 10~(-24)). All the candidate targets were then evaluated by PCR assays. Fifteen targets showed high specificity for the detection of S. enterica by verification with 151 S. enterica, strains and 34 non-Salmonella strains. The phylogenetic trees of verified targets were highly comparable with those of housekeeping genes, especially for differentiating S. enterica strains into serovars. The serovar prediction ability was validated by sequencing one target (S9) for 39 5. enterica strains belonging to six serovars. Identical mutation sites existed in the same serovar, and different mutation sites were found in diverse serovars. Our findings revealed that 15 verified targets can be potentially used for molecular detection, and some of them can be used for serotyping of S. enterica strains.