Detection of O157:H7 in Ground Beef Using Long-Read Sequencing.

Foods

Eastern Regional Research Center, United States Department of Agriculture, Agricultural Research Service, Wyndmoor, PA 19038, USA.

Published: March 2024

Foodborne pathogens are a significant cause of illness, and infection with Shiga toxin-producing (STEC) may lead to 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 the use of 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 the 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 (, , , , , , and ) were detected in DNA extracted from STEC pure cultures within 1 h of sequencing, and 30× coverage was obtained within 2 h. 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. The 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10969500PMC
http://dx.doi.org/10.3390/foods13060828DOI Listing

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