A local-scale One Health genomic surveillance of Clostridioides difficile demonstrates highly related strains from humans, canines, and the environment.

Although infections caused by have historically been attributed to hospital acquisition, growing evidence supports the role of community acquisition in infection (CDI). Symptoms of CDI can range from mild, self-resolving diarrhoea to toxic megacolon, pseudomembranous colitis, and death. In this study, we sampled from clinical, environmental, and canine reservoirs in Flagstaff, Arizona, USA, to understand the distribution and transmission of the pathogen in a One Health framework; Flagstaff is a medium-sized, geographically isolated city with a single hospital system, making it an ideal site to characterize genomic overlap between sequenced isolates across reservoirs. An analysis of 562 genomes from Flagstaff isolates identified 65 sequence types (STs), with eight STs being found across all three reservoirs and another nine found across two reservoirs. A screen of toxin genes in the pathogenicity locus identified nine STs where all isolates lost the toxin genes needed for CDI manifestation (, ), demonstrating the widespread distribution of non-toxigenic (NTCD) isolates in all three reservoirs; 15 NTCD genomes were sequenced from symptomatic, clinical samples, including two from mixed infections that contained both and - isolates. A comparative single nucleotide polymorphism (SNP) analysis of clinically derived isolates identified 78 genomes falling within clusters separated by ≤2 SNPs, indicating that ~19 % of clinical isolates are associated with potential healthcare-associated transmission clusters; only symptomatic cases were sampled in this study, and we did not sample asymptomatic transmission. Using this same SNP threshold, we identified genomic overlap between canine and soil isolates, as well as putative transmission between environmental and human reservoirs. The core genome of isolates sequenced in this study plus a representative set of public genomes (=136), was 2690 coding region sequences, which constitutes ~70 % of an individual genome; this number is significantly higher than has been published in some other studies, suggesting that genome data quality is important in understanding the minimal number of genes needed by . This study demonstrates the close genomic overlap among isolates sampled across reservoirs, which was facilitated by maximizing the genomic search space used for comprehensive identification of potential transmission events. Understanding the distribution of toxigenic and non-toxigenic across reservoirs has implications for surveillance sampling strategies, characterizing routes of infections, and implementing mitigation measures to limit human infection.