Abstract
Vibrio parahaemolyticus has emerged as a significant enteropathogen in human and marine habitats worldwide, notably in regions where aquaculture products constitute a major nutritional source. It is a growing cause of diseases including gastroenteritis, wound infections, and septicemia. Serotyping assays use commercially available antisera to identify V. parahaemolyticus strains, but this approach is limited by high costs, complicated procedures, cross-immunoreactivity, and often subjective interpretation. By leveraging high-throughput sequencing technologies, we developed an in silico method based on comparison of gene clusters for lipopolysaccharide (LPSgc) and capsular polysaccharide (CPSgc) by firstly using the unique-gene strategy. The algorithm, VPsero, which exploits serogroup-specific genes as markers, covers 43 K and all 12 O serogroups in serotyping assays. VPsero is capable of predicting serotypes from assembled draft genomes, outputting LPSgc/CPSgc sequences, and recognizing possible novel serogroups or populations. Our tool displays high specificity and sensitivity in prediction toward V. parahaemolyticus strains, with an average sensitivity in serogroup prediction of 0.910 for O and 0.961 for K serogroups and a corresponding average specificity of 0.990 for O and 0.998 for K serogroups.
Highlights
Serotyping is fundamentally important to disease control processes based on epidemiological surveys and identification of pathogenic signatures
After reviewing literatures on in silico serotyping methods, we found that majority of the typing methods were based on two modes of strategies: identification by comparing the genome assembly or short reads with entire PS loci (PSgc) of reference serotype strains or identification by comparing the genome assembly or short reads with conserved genes in PSgc from reference serotype strains
We presented VPsero as a novel tool for rapid determination of serotypes of V. parahaemolyticus using serogroup-specific genes, based on whole genome or polysaccharide biosynthesis locus sequencing data
Summary
Serotyping is fundamentally important to disease control processes based on epidemiological surveys and identification of pathogenic signatures. With the advent of highthroughput sequencing technologies in research practice and in medical laboratories, there is a constant demand for robust bioinformatics tools utilizing genomic information to dissect serotype landscapes for characterization of pathogenic bacteria. In silico serotyping methods for several common pathogenic bacteria have been successfully developed (Mostowy and Holt, 2018). This approach offers alternative and validatory solutions to standard laboratory serotyping methods. Further innovation could prove helpful to bridging technological gaps between traditional serological serotyping and genomic typing in epidemiological investigation and diagnostic practice
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