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Long-read sequencing data from pure cultures of <i>Escherichia coli</i> O157:H7 and ground beef inoculated with <i>E. coli</i> O157:H7
,Foodborne pathogens are a significant cause of illness and infection with Shiga toxin-producing Escherichia coli (STEC) has the potential to produce life-threatening complications. The current methods to identify STEC in meat involve culture-based, molecular, and proteomic assays and take at least four days to complete. This time could be reduced by using long-read whole genome sequencing to identify foodborne pathogens. Therefore, the goal of this project was to evaluate using long-read sequencing to detect STEC in ground beef. The objectives of the project included: establishing optimal sequencing parameters, determining the limit of detection of all STEC virulence genes of interest in pure cultures and spiked ground beef, and evaluating selective sequencing to enhance STEC detection in ground beef. Sequencing libraries were run on Oxford Nanopore Technologies’ MinION sequencer. Optimal sequencing output was obtained using the default parameters in MinKNOW, except for setting the minimum read length to 1 kb. All genes of interest (eae, stx1, stx2, fliC, wzx, wzy, rrsC) were detected in DNA extracted from STEC pure cultures within 1 hour of sequencing, and 30X coverage was obtained within 2 hours. All virulence genes were confidently detected in STEC DNA quantities as low as 12.5 ng. In STEC inoculated ground beef, software-controlled selective sequencing improved virulence gene detection; however, several virulence genes were not detected due to high bovine DNA concentrations in the samples. Growth enrichment of inoculated meat samples in mTSB resulted in a 100-fold increase in virulence gene detection as compared to the unenriched samples. The results of this project suggest that further development of long-read sequencing protocols may result in a faster, less labor-intensive method to detect STEC in ground beef. The sequencing data from this project has been uploaded.,
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Data from: Use of long-read sequencing simulators to assess real-world applications for food safety
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,Shiga toxin-producing Escherichia coli (STEC) and Listeria monocytogenes are responsible for severe foodborne illnesses in the United States. Current identification methods require at least four days to identify STEC and six days for L. monocytogenes. Adoption of long-read, whole genome sequencing for testing could significantly reduce the time needed for identification, but method development costs are high. Therefore, the goal of this project was to use NanoSim-H software to simulate Oxford Nanopore sequencing reads to assess the feasibility of sequencing-based foodborne pathogen detection and guide experimental design. Sequencing reads were simulated for STEC, L. monocytogenes, and a 1:1 combination of STEC and Bos taurus genomes using NanoSim-H. This dataset includes all of the simulated reads generated by the project in fasta format. This dataset can be analyzed bioinformatically or used to test bioinformatic pipelines.,
Data from: Detection of live Shiga toxin-producing Escherichia coli with long-read sequencing
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,A requirement of any foodborne pathogen testing method is that it only detects live bacteria. Ethidium monoazide (EMA) and propidium monoazide (PMA) are dyes that penetrate the membranes of dead cells and form cross-linkages in the DNA, which prevents its amplification in PCR. This study investigated whether treatment with EMA or PMA would inhibit sequencing of DNA from dead Escherichia coli. Range finding experiments with qPCR were conducted to determine the optimal concentrations of EMA and PMA needed to inhibit amplification of DNA from dead cells while not influencing live cells. An EMA concentration that differentiated between live and dead cells could not be established. However, a PMA concentration of 25 µM effectively prevented qPCR amplification of DNA from dead E. coli while not impacting the amplification of live E. coli DNA. Sequencing experiments were conducted with PMA-treated live, untreated live, PMA-treated dead, and untreated dead E. coli. There were no significant differences in the detection of virulence genes of interest between the PMA-treated live, untreated live, and untreated dead E. coli. However, no DNA sequencing data was obtained from the PMA-treated dead E. coli. These results suggest that PMA could be incorporated into sample preparation methods prior to sequencing to selectively detect live cells of foodborne pathogens.,