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Precision long-read metagenomics sequencing for food safety by detection and assembly of Shiga toxin-producing Escherichia coli in irrigation water
Author(s) -
Meghan Maguire,
Julie A. Kase,
Dwayne Roberson,
Tim Muruvanda,
Eric W. Brown,
Marc W. Allard,
Steven M. Musser,
Narjol González-Escalona
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0245172
Subject(s) - escherichia coli , metagenomics , biology , microbiology and biotechnology , nanopore sequencing , genome , shiga toxin , virulence , in silico , sequence assembly , genetics , gene , gene expression , transcriptome
Shiga toxin-producing Escherichia coli (STEC) contamination of agricultural water might be an important factor to recent foodborne illness and outbreaks involving leafy greens. Closed bacterial genomes from whole genome sequencing play an important role in source tracking. We aimed to determine the limits of detection and classification of STECs by qPCR and nanopore sequencing using 24 hour enriched irrigation water artificially contaminated with E . coli O157:H7 (EDL933). We determined the limit of STEC detection by qPCR to be 30 CFU/reaction, which is equivalent to 10 5 CFU/ml in the enrichment. By using Oxford Nanopore’s EPI2ME WIMP workflow and de novo assembly with Flye followed by taxon classification with a k-mer analysis software (Kraken2), E . coli O157:H7 could be detected at 10 3 CFU/ml (68 reads) and a complete fragmented E . coli O157:H7 metagenome-assembled genome (MAG) was obtained at 10 5 −10 8 CFU/ml. Using a custom script to extract the E . coli reads, a completely closed MAG was obtained at 10 7 −10 8 CFU/ml and a complete, fragmented MAG was obtained at 10 5 −10 6 CFU/ml. In silico virulence detection for E . coli MAGs for 10 5 −10 8 CFU/ml showed that the virulotype was indistinguishable from the spiked E . coli O157:H7 strain. We further identified the bacterial species in the un-spiked enrichment, including antimicrobial resistance genes, which could have important implications to food safety. We propose this workflow provides proof of concept for faster detection and complete genomic characterization of STECs from a complex microbial sample compared to current reporting protocols and could be applied to determine the limit of detection and assembly of other foodborne bacterial pathogens.

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