IDENTIFICATION OF SALMONELLA STRAINS OF PHYLLOSPHERE FOOD POISONING BY MELT CURVE ANALYSIS: IN SILICO APPROACH

Abstract

During last few decades, there have been increased incidences of outbreak of diseases due to consumption of fresh vegetables and fruits contaminated with human pathogens.  Such threats warrant rapid detection test. The standard method of diagnosis relies on culture-plate and serological methods which lack discrimination and are time consuming having several drawbacks, inconsistency and are less efficient. We applied bioinformatics approaches to develop of a real- time PCR simulation for detecting Salmonella serovars which are involved in most disease outbreaks associated with phyllosphere. Salmonella enterica subspecies enterica (designated as S. enterica ) are common in plants, on surface as well as present internally in tissues. Though more than 2500 serovars of Salmonella enterica are known but the reports of serovars colonizing in plants are limited. Nucleotide sequence variation in target genes, viz. PurE, SucA, hisD, hivA and fliC were used in in silico to differentiate Salmonella serovars . A large number of reference sequences of target genes were retrieved from NCBI, and common conserved region were used for development of multiplex primer design using muPlex. Primer thermodynamic properties and secondary structure were assessed using Beacon designer. Sequences were truncated to remove sequences outside of the region bounded by the primers.  We performed in silico DNA melting simulations with several Salmonella serovars using the programs umelt, and tested the utility of the programs for assay design, which will save time and cost of in vitro testing several multiple primers in RT PCR. Keywords - In Silico ; Salmonella ; Phyllosphere;Real-time PCR (RT-PCR)