A molecular epidemiological and transmission analysis of Clostridioides difficile using draft whole-genome sequencing in a single hospital.

Background: The nosocomial transmission of toxin-producing Clostridioides difficile is a significant concern in infection control. C. difficile, which resides in human intestines, poses a risk of transmission, especially when patients are in close contact with medical staff.
Methods: To investigate the nosocomial transmission of C. difficile in a single center, we analyzed the genetic relationships of the bacteria. This was done using draft whole-genome sequencing (WGS) and examining single nucleotide polymorphisms (SNPs) in core-genome, alongside data regarding the patient's hospital wards and room changes. Our retrospective analysis covered 38 strains, each isolated from a different patient, between April 2014 and January 2015.
Results: We identified 38 strains that were divided into 11 sequence types (STs). ST81 was the most prevalent (n = 11), followed by ST183 (n = 10) and ST17 (n = 7). A cluster of strains that indicated suspected nosocomial transmission (SNT) was identified through SNP analysis. The draft WGS identified five clusters, with 16 of 38 strains belonging to these clusters. There were two clusters for ST81 (ST81-SNT-1 and ST81-SNT-2), two for ST183 (ST183-SNT-1 and ST183-SNT-2), and one for ST17 (ST17-SNT-1). ST183-SNT-1 was the largest SNT cluster, encompassing five patients who were associated with Wards A, B, and K. The most frequent room changer was a patient labeled Pt08, who changed rooms seven times in Ward B. Patients Pt36 and Pt10, who were also in Ward B, had multiple admissions and discharges during the study period.
Conclusions: Additional culture tests and SNP analysis of C. difficile using draft WGS revealed silent transmission within the wards, particularly in cases involving frequent room changes and repeated admissions and discharges. Monitoring C. difficile transmission using WGS-based analysis could serve as a valuable marker in infection control management.
(© 2024. The Author(s).)