Strain Variation in Clostridioides difficile Cytotoxicity Associated with Genomic Variation at Both Pathogenic and...

Clinical disease from Clostridioides difficile infection can be mediated by two toxins and their neighboring regulatory genes located within the five-gene pathogenicity locus (PaLoc). We provide several lines of evidence that the cytotoxicity of C. difficile may be modulated by genomic variants outside the PaLoc. We used a phylogenetic tree-based approach to demonstrate discordance between cytotoxicity and PaLoc evolutionary history, an elastic net method to show the insufficiency of PaLoc variants alone to model cytotoxicity, and a convergence-based bacterial genome-wide association study (GWAS) to identify correlations between non-PaLoc loci and changes in cytotoxicity. Combined, these data support a model of C. difficile disease wherein cytotoxicity may be strongly affected by many non-PaLoc loci. Additionally, we characterize multiple other in vitro phenotypes relevant to human infections, including germination and sporulation. These phenotypes vary greatly in their clonality, variability, convergence, and concordance with genomic variation. Finally, we highlight the intersection of loci identified by the GWAS for different phenotypes and clinical severity. This strategy to identify overlapping loci can facilitate the identification of genetic variation linking phenotypic variation to clinical outcomes. IMPORTANCE Clostridioides difficile has two major disease-mediating toxins, A and B, encoded within the pathogenicity locus (PaLoc). In this study, we demonstrate via multiple approaches that genomic variants outside the PaLoc are associated with changes in cytotoxicity. These genomic variants may provide new avenues of exploration in the hunt for novel disease-modifying interventions. Additionally, we provide insight into the evolution of several additional phenotypes also critical for clinical infection, such as sporulation, germination, and growth rate. These in vitro phenotypes display a range of responses to evolutionary pressures and, as such, vary in their appropriateness for certain bacterial genome-wide association study approaches. We used a convergence-based association method to identify the genomic variants most correlated with both changes in these phenotypes and disease severity. These overlapping loci may be important for both bacterial function and human clinical disease.