Background: The frequent temporal recurrence of Clostridioides difficile infection (CDI) may be the result of relapse with the same strain or reinfection with a different strain; the role of genetic evolution of C. difficile in relapse is poorly understood. We used whole-genome sequencing (WGS) to determine the frequency of same strain relapse among CDI recurrences and changes in the genetic diversity of individual strains responsible for relapses over time. Methods: We analyzed data from active population- and laboratory-based surveillance of CDI in Minnesota, USA. We performed WGS on isolates collected from 306 patients with multiple CDI events during 2019-2021. We identified multi-locus sequence types (MLSTs), nucleotide variants, and putative mobile genetic elements (MGEs) from WGS data to study the genetic similarity and evolution of those C. difficile genomes. Results: Among patients with multiple CDI events in the total surveillance period, 198 (64.7%) had multiple infections of the same MLST. Of these patients, 17.6% had multiple same-MLST CDI events >8 weeks apart. Among 232 temporally defined cases of recurrent CDI, 155 (66.8%) involved isolates of the same MLST. Among same-MLST isolates, there were no statistically significant correlations between accumulated mutations and elapsed time between CDI events. Analysis of sequential same-MLST C. difficile genomes showed evidence of gain or loss of putative mobile genetic elements (MGEs) in 45.6% of genome pairs. Conclusions: Leveraging the largest CDI genomic dataset to date, our results confirm prior findings that recurrent CDI is a combination of reinfection and/or change in the ascendant strain in mixed infection, and relapse, while expanding knowledge on the evolution of pathogenic C. difficile strains in the human gastrointestinal tract.

Author DE is employed part-time as a Medical Service Corps officer in the United States Army Reserve, an organization which had no role in the contents of this manuscript. Author RL has held leadership positions in several public health organizations (the Council of State and Territorial Epidemiologists, the Infectious Diseases Society of America, the American Academy of Pediatrics, and the National Foundation for Infectious Diseases) and has received honoraria for serving as an Associate Editor for the AAP Red Book. The findings of this manuscript do not necessarily reflect the official positions of any of the declared organizations. All other authors declare no potential financial conflicts of interest.

This project was funded by CDC grants ELC/EIP HAI NU50CK000490-05-11, ELC AMD NU50CK000508-05-00, and ELC ARI NU50CK000508-05-00. The findings of this manuscript do not necessarily reflect the official positions of the CDC or the Department of Health and Human Services.

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Leadership in the Health Protection Bureau of the Minnesota Department of Health waived ethical approval for this work, as data collection and analysis were conducted as a component of public health surveillance subject to Minnesota Reporting Rules. The study used individual-level data from disease surveillance conducted according to Minnesota State Reporting Rules. Case investigation data were collected for each isolate from which a whole-genome sequence was also generated. All individual-level data were de-identified prior to their use in this study.

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