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Determination of Genomic Epidemiology of Historical Clostridium perfringens Outbreaks in New York State by Use of Two Web-Based Platforms: National Center for Biotechnology Information Pathogen Detection and FDA GalaxyTrakr.

Jaclyn CareyJocelyn ColeSai Laxmi Gubbala VenkataHannah HoytLisa MingleDavid NicholasKimberlee A MusserWilliam J Wolfgang
Published in: Journal of clinical microbiology (2021)
Clostridium perfringens is the second leading cause of bacterial foodborne illness in the United States. The Wadsworth Center (WC) at the New York State Department of Health enumerates infectious dose from primary patient and food samples and, until recently, identified C. perfringens to the species level only. We investigated whether whole-genome sequence-based subtyping could benefit epidemiological investigations of this pathogen, as it has with other enteric organisms. We retrospectively sequenced 76 patient and food samples received between May 2010 and February 2020, including 52 samples linked epidemiologically to 13 outbreaks and 24 sporadic samples not linked to other samples. Phylogenetic trees were built using two Web-based platforms: National Centers for Biotechnology Information Pathogen Detection (NCBI-PD) and GalaxyTrakr (a Galaxy instance supported by the GenomeTrakr initiative). For GalaxyTrakr analyses, single nucleotide polymorphism (SNP) matrices and maximum-likelihood (ML) trees were generated using 3 different reference genomes. Across the four separate analyses, phylogenetic clustering was generally concordant with epidemiologically identified outbreaks. SNP diversity among phylogenetically linked samples from an outbreak ranged from 0 to 20 SNPs, excepting one outbreak ranging from 4 to 62 SNPs. Importantly, four of the 13 outbreak isolates harbored one or more samples that were phylogenetic outliers, and for two outbreaks, no samples were closely related. Two specimens were found harboring two distinct genotypes. For samples below CDC enumeration dose threshold, phylogenetic clustering was robust and linked patient and/or food samples. We concluded that WGS phylogenetic clusters (i) are largely concordant with epidemiologically defined outbreaks, irrespective of analysis platform or reference genome we employed; (ii) have limited pairwise SNP diversity, allowing phylogenetic clusters to be distinguished from sporadic cases; and (iii) can aid in epidemiological investigations by identifying outlier and polyclonal samples.
Keyphrases
  • genome wide
  • mental health
  • high throughput
  • climate change
  • dna methylation
  • health information
  • mass spectrometry
  • cell proliferation
  • high density
  • amino acid
  • simultaneous determination
  • tandem mass spectrometry