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

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 S. 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.

[Establishment and evaluation of a real-time IAC-PCR for the detection of Salmonella].

OBJECTIVE: The aim of this study was to establish a new EvaGreen real-time IAC-PCR for the rapid detection of Salmonella. METHODS: We used Salmonella genomic comparison analysis to mine Salmonella-specific targets, and Primer Premier 5.0 to design primers which were evaluated by specificity and sensitivity tests. RESULTS: We obtained a Salmonella-specific gene that encodes putative type III secretion protein (ssaQ), and specific primers (SsaQ6L/SsaQ6R) were designed based on this gene. Then we established IAC-PCR and EvaGreen real-time IAC-PCR assays, which showed 100% inclusivity and 100% exclusivity on all strains tested. Their detection limits of purified Salmonella genomic DNA were 14.9 copies/PCR and 2.76 copies/PCR respectively. Artificial contamination assays showed that Salmonella could be detected after 10 hours and 8 hours enrichment when the original bacterial concentration was 4.2 cfu/10 mL. CONCLUSION: A new EvaGreen real-time IAC-PCR with high specificity and sensitivity was successfully developed for the rapid detection of Salmonella.

SMM-system: A mining tool to identify specific markers in Salmonella enterica.

This report presents SMM-system, a software package that implements various personalized pre- and post-BLASTN tasks for mining specific markers of microbial pathogens. The main functionalities of SMM-system are summarized as follows: (i) converting multi-FASTA file, (ii) cutting interesting genomic sequence, (iii) automatic high-throughput BLASTN searches, and (iv) screening target sequences. The utility of SMM-system was demonstrated by using it to identify 214 Salmonella enterica-specific protein-coding sequences (CDSs). Eighteen primer pairs were designed based on eighteen S. enterica-specific CDSs, respectively. Seven of these primer pairs were validated with PCR assay, which showed 100% inclusivity for the 101 S. enterica genomes and 100% exclusivity of 30 non-S. enterica genomes. Three specific primer pairs were chosen to develop a multiplex PCR assay, which generated specific amplicons with a size of 180bp (SC1286), 238bp (SC1598) and 405bp (SC4361), respectively. This study demonstrates that SMM-system is a high-throughput specific marker generation tool that can be used to identify genus-, species-, serogroup- and even serovar-specific DNA sequences of microbial pathogens, which has a potential to be applied in food industries, diagnostics and taxonomic studies. SMM-system is freely available and can be downloaded from http://foodsafety.sjtu.edu.cn/SMM-system.html.