Multiplex Strategy for Multilocus Sequence Typing, fla Typing, and Genetic Determination of Antimicrobial Resistance of Campylobacter jejuni and Campylobacter coli Isolates Collected in Switzerland

摘要

We present an optimized multilocus sequence typing (MLST) scheme with universal primer sets for amplifying and sequencing the seven target genes of Campylobacter jejuni and Campylobacter coli. Typing was expanded by sequence determination of the genes flaA and flaB using optimized primer sets. This approach is compatible with the MLST and flaA schemes used in the PubMLST database and results in an additional typing method using the flaB gene sequence. An identification module based on the 16S rRNA and rpoB genes was included, as well as the genetic determination of macrolide and quinolone resistances based on mutations in the 23S rRNA and gyrA genes. Experimental procedures were simplified by multiplex PCR of the 13 target genes. This comprehensive approach was evaluated with C. jejuni and C. coli isolates collected in Switzerland. MLST of 329 strains resulted in 72 sequence types (STs) among the 186 C. jejuni strains and 39 STs for the 143 C. coli isolates. Fourteen (19%) of the C. jejuni and 20 (51%) of the C. coli STs had not been found previously. In total, 35% of the C. coli strains collected in Switzerland contained mutations conferring antibiotic resistance only to quinolone, 15% contained mutations conferring resistance only to macrolides, and 6% contained mutations conferring resistance to both classes of antibiotics. In C. jejuni, these values were 31% and 0% for quinolone and macrolide resistance, respectively. The rpoB sequence allowed phylogenetic differentiation between C. coli and C. jejuni, which was not possible by 16S rRNA gene analysis. An online Integrated Database Network System (SmartGene, Zug, Switzerland)-based platform for MLST data analysis specific to Campylobacter was implemented. This Web-based platform allowed automated allele and ST designation, as well as epidemiological analysis of data, thus streamlining and facilitating the analysis workflow. Data networking facilitates the exchange of information between collaborating centers. The described approach simplifies and improves the genotyping of Campylobacter, allowing cost- and time-efficient routine monitoring.