Genomic Tools for Customized Recovery and Detection of Foodborne Shiga Toxigenic Escherichia coli

Abstract

ABSTRACT Genomic antimicrobial resistance (AMR) prediction tools have the potential to support foodborne illness outbreak investigations through their application in the analysis of bacterial genomes from causative strains. The AMR marker profile of a strain of interest, initially identified in outbreak-associated clinical samples, may serve as the basis for customization of selective enrichment media, facilitating its recovery from samples in a food safety investigation. Different possibilities for AMR analyses include the use of comprehensive AMR gene databases such as the Comprehensive Antibiotic Resistance Database, which can be mined with in-house bioinformatics alignment tools (e.g., Antimicrobial Resistance Marker Identifier), or publicly available tools based on clinically relevant acquired AMR gene databases (e.g., ResFinder). In combination with a previously reported pipeline (SigSeekr) designed to identify specific DNA sequences associated with a particular strain for its rapid identification by PCR, it should be possible to deploy custom recovery and identification tools for the efficient detection of priority pathogens such as Shiga toxigenic Escherichia coli (STEC) outbreak strains within the time frame of an active investigation. Using a laboratory STEC strain as a model, trimethoprim resistance identified by both Antimicrobial Resistance Marker Identifier and ResFinder was used as the basis for its selective recovery against a background of commensal E. coli bacteria in ground beef samples. Enrichment in modified tryptic soy broth containing trimethoprim greatly enhanced the recovery of low numbers of model strain cells inoculated in ground beef samples, as verified by the enumeration of colonies on plating media using a strain-specific PCR method to determine the recovery efficiency for the target strain. We discuss the relative merits of different AMR marker prediction tools for this purpose and describe how such tools can be utilized to good effect in a typical outbreak investigation scenario.