PathFams: statistical detection of pathogen-associated protein domains

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 facili...

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Bibliographic Details
Main Authors: Briallen Lobb, Benjamin Jean-Marie Tremblay, Gabriel Moreno-Hagelsieb, Andrew C. Doxey
Format: Article
Language:English
Published: BMC 2021-09-01
Series:BMC Genomics
Subjects:
Online Access:https://doi.org/10.1186/s12864-021-07982-8
Description
Summary: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 .
ISSN:1471-2164