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PathFams: statistical detection of...
Journal article

PathFams: statistical detection of pathogen-associated protein domains

Abstract

BackgroundA 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.ResultsTo 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.ConclusionsWe 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.

Authors

Lobb B; Tremblay BJ-M; Moreno-Hagelsieb G; Doxey AC

Journal

BMC Genomics, Vol. 22, No. 1,

Publisher

Springer Nature

Publication Date

December 1, 2021

DOI

10.1186/s12864-021-07982-8

ISSN

1471-2164

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