Epidemic Clostridioides difficile Ribotype 027 Lineages: Comparisons of Texas Versus Worldwide Strains. (9th February 2019) - Endres, Bradley T; Begum, Khurshida; Sun, Hua; Walk, Seth T; Memariani, Ali; Lancaster, Chris; Gonzales-Luna, Anne J; Dotson, Kierra M; Bassères, Eugénie; Offiong, Charlene; Tupy, Shawn; Kuper, Kristi; et al.
Abstract: Background: The epidemic Clostridioides difficil e ribotype 027 strain resulted from the dissemination of 2 separate fluoroquinolone-resistant lineages: FQR1 and FQR2. Both lineages were reported to originate in North America; however, confirmatory large-scale investigations of C difficile ribotype 027 epidemiology using whole genome sequencing has not been undertaken in the United States. Methods: Whole genome sequencing and single-nucleotide polymorphism (SNP) analysis was performed on 76 clinical ribotype 027 isolates obtained from hospitalized patients in Texas with C difficile infection and compared with 32 previously sequenced worldwide strains. Maximum-likelihood phylogeny based on a set of core genome SNPs was used to construct phylogenetic trees investigating strain macro- and microevolution. Bayesian phylogenetic and phylogeographic analyses were used to incorporate temporal and geographic variables with the SNP strain analysis. Results: Whole genome sequence analysis identified 2841 SNPs including 900 nonsynonymous mutations, 1404 synonymous substitutions, and 537 intergenic changes. Phylogenetic analysis separated the strains into 2 prominent groups, which grossly differed by 28 SNPs: the FQR1 and FQR2 lineages. Five isolates were identified as pre-epidemic strains. Phylogeny demonstrated unique clustering and resistance genes in Texas strains indicating that spatiotemporal bias has defined the microevolution of ribotype 027 genetics. Conclusions: Clostridioides difficile ribotype 027 lineages emerged earlier than previously reported, coinciding with increased use of fluoroquinolones. Both FQR1 and FQR2 ribotype 027 epidemic lineages are present in Texas, but they have evolved geographically to represent region-specific public health threats.