Genotyping of Campylobacter jejuni using seven single-nucleotide polymorphisms in combination with flaA short variable region sequencing

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Abstract

This investigation describes the development of a generally applicable, bioinformatics-driven, single-nucleotide polymorphism (SNP) genotyping assay for the common bacterial gastrointestinal pathogen Campylobacter jejuni. SNPs were identified in silico using the program ‘Minimum SNPs’, which selects for polymorphisms providing the greatest resolution of bacterial populations based on Simpson's index of diversity (D). The high-D SNPs identified in this study were derived from the combined C. jejuni/Campylobacter coli multilocus sequence typing (MLST) database. Seven SNPs were found that provided a D of 0.98 compared with full MLST characterization, based on 959 sequence types (STs). The seven high-D SNPs were interrogated using allele-specific real-time PCR (AS kinetic PCR), which negates the need for expensive labelled primers or probes and requires minimal assay optimization. The total turnaround time of the SNP typing assay was approximately 2 h. Concurrently, 69 C. jejuni isolates were subjected to MLST and flagellin A short variable region (flaA SVR) sequencing and combined with a population of 84 C. jejuni and C. coli isolates previously characterized by these methods. Within this collection of 153 isolates, 19 flaA SVR types (D=0.857) were identified, compared with 40 different STs (D=0.939). When MLST and flaA SVR sequencing were used in combination, the discriminatory power was increased to 0.959. In comparison, SNP typing of the 153 isolates alone provided a D of 0.920 and was unable to resolve a small number of unrelated isolates. However, addition of the flaA SVR locus to the SNP typing procedure increased the resolving power to 0.952 and clustered isolates similarly to MLST/flaA SVR. This investigation has shown that a seven-member C. jejuni SNP typing assay, used in combination with sequencing of the flaA SVR, efficiently discriminates C. jejuni isolates.

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