BMC Genomics (Sep 2021)

PathFams: statistical detection of pathogen-associated protein domains

  • Briallen Lobb,
  • Benjamin Jean-Marie Tremblay,
  • Gabriel Moreno-Hagelsieb,
  • Andrew C. Doxey

DOI
https://doi.org/10.1186/s12864-021-07982-8
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 11

Abstract

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Abstract Background A substantial fraction of genes identified within bacterial genomes encode proteins of unknown function. Identifying which of these proteins represent potential virulence factors, and mapping their key virulence determinants, is a challenging but important goal. Results To facilitate virulence factor discovery, we performed a comprehensive analysis of 17,929 protein domain families within the Pfam database, and scored them based on their overrepresentation in pathogenic versus non-pathogenic species, taxonomic distribution, relative abundance in metagenomic datasets, and other factors. Conclusions We identify pathogen-associated domain families, candidate virulence factors in the human gut, and eukaryotic-like mimicry domains with likely roles in virulence. Furthermore, we provide an interactive database called PathFams to allow users to explore pathogen-associated domains as well as identify pathogen-associated domains and domain architectures in user-uploaded sequences of interest. PathFams is freely available at https://pathfams.uwaterloo.ca .

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