A publicly accessible database for Clostridioides difficile genome sequences supports tracing of transmission chains and epidemics

Abstract

Clostridioides difficile is the primary infectious cause of antibiotic-associated diarrhea. Local transmissions and international outbreaks of this pathogen have been previously elucidated by bacterial whole-genome sequencing, but comparative genomic analyses at the global scale were hampered by the lack of specific bioinformatic tools. Here we introduce a publicly accessible database within EnteroBase (http://enterobase.warwick.ac.uk) that automatically retrieves and assembles C. difficile short-reads from the public domain, and calls alleles for core-genome multilocus sequence typing (cgMLST). We demonstrate that comparable levels of resolution and precision are attained by EnteroBase cgMLST and single-nucleotide polymorphism analysis. EnteroBase currently contains 18 254 quality-controlled C. difficile genomes, which have been assigned to hierarchical sets of single-linkage clusters by cgMLST distances. This hierarchical clustering is used to identify and name populations of C. difficile at all epidemiological levels, from recent transmission chains through to epidemic and endemic strains. Moreover, it puts newly collected isolates into phylogenetic and epidemiological context by identifying related strains among all previously published genome data. For example, HC2 clusters (i.e. chains of genomes with pairwise distances of up to two cgMLST alleles) were statistically associated with specific hospitals (P<10−4) or single wards (P=0.01) within hospitals, indicating they represented local transmission clusters. We also detected several HC2 clusters spanning more than one hospital that by retrospective epidemiological analysis were confirmed to be associated with inter-hospital patient transfers. In contrast, clustering at level HC150 correlated with k-mer-based classification and was largely compatible with PCR ribotyping, thus enabling comparisons to earlier surveillance data. EnteroBase enables contextual interpretation of a growing collection of assembled, quality-controlled C. difficile genome sequences and their associated metadata. Hierarchical clustering rapidly identifies database entries that are related at multiple levels of genetic distance, facilitating communication among researchers, clinicians and public-health officials who are combatting disease caused by C. difficile .

Accurate reconstruction of bacterial pan- and core genomes with PEPPAN

“…A pangenome for the genus Streptococcus PEPPAN can construct a pangenome from thousands of genomes with high genetic diversity, and earlier versions of this pipeline were used to generate cgMLST schemes for the genera represented in EnteroBase (Alikhan et al 2018;Frentrup et al 2020;Zhou et al 2020), as well as for ancient DNA analyses (Zhou et al 2018b;Achtman and Zhou 2020). To show PEPPAN's capability on genetically diverse data sets, we chose the genus Streptococcus, which includes highly significant zoonotic and human pathogens (Gao et al 2014).…”

Retrospective Definition of Clostridioides difficile PCR Ribotypes on the Basis of Whole Genome Polymorphisms: A Proof of Principle Study

“…Some of the unitigs were shared by closely related RTs. Unitigs for RT001 were able to identify the genetically closely related RT087, RT241, and RT012, which altogether form a clonal complex (CC) 141 [ 44 ]. One of the markers identified for RT017 showed no false-positives or false negatives.…”

“…Other markers for RT017 initially generated a small number of false-positives, but 100% true-positives in the validation dataset. Markers for RT078 identified 78 out of 79 isolates of RT126 and all of the RT413 strains from the test dataset, likely due to the close genetic relatedness of these RTs (CC 1) [ 44 , 48 , 49 ]. Unitig sequences for RT106 were also able to identify C. difficile RT500 along with RT106 from the test set.…”

“…Validation of novel unitig markers was performed by means of BLAST searches against the test set of genomes ( Table 3 ). A wide range of 2425 genomes covering 132 different C. difficile RTs was downloaded [ 44 ] and processed using a Linux shell script. These sequences represented PCR ribotyped strains from different countries and clinical and environmental specimens for which phylogenetic analyses were already performed by Frentrup et al [ 44 ] ( Supplementary Table S3 ).…”

“…A wide range of 2425 genomes covering 132 different C. difficile RTs was downloaded [ 44 ] and processed using a Linux shell script. These sequences represented PCR ribotyped strains from different countries and clinical and environmental specimens for which phylogenetic analyses were already performed by Frentrup et al [ 44 ] ( Supplementary Table S3 ). A database of this test set was created to perform local command line BLAST searches against the set of significant unitigs identified above.…”