TY - JOUR
T1 - Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain
AU - Yang, Xiang
AU - Noyes, Noelle R.
AU - Doster, Enrique
AU - Martin, Jennifer
AU - Linke, Lyndsey M.
AU - Magnuson, Roberta J.
AU - Yang, Hua
AU - Geornaras, Ifigenia
AU - Woerner, Dale
AU - Jones, Kenneth L.
AU - Ruiz, Jaime
AU - Boucher, Christina
AU - Morley, Paul S.
AU - Belk, Keith E.
N1 - Funding Information:
ACKNOWLEDGMENTS We thank Santiago Luzardo, Megan Webb, Shuang Hu, and Kathryn Mc-Cullough for sampling assistance. We also thank Jennifer Parker and Zaid Abdo for their comments on the manuscript. Sequencing and bioinformatic analysis were supported in part by the Biostatistics/Bioinformatics and Genomics Shared Resources of Colorado?s NIH/NCI Cancer Center. We declare no conflicts of interest. FUNDING INFORMATION The Beef Checkoff provided funding to Xiang Yang, Noelle R. Noyes, Enrique Doster, Jennifer N. Martin, Lyndsey M. Linke, Roberta J. Magnuson, Hua Yang, Ifigenia Geornaras, Dale R. Woerner, Kenneth L. Jones, Jaime Ruiz, Christina Boucher, Paul S. Morley, and Keith E. Belk. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Publisher Copyright:
© 2016, American Society for Microbiology. All Rights Reserved.
PY - 2016/4/1
Y1 - 2016/4/1
N2 - Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica, Listeria monocytogenes, Escherichia coli, Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni, C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica, E. coli, and C. botulinum were greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.
AB - Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica, Listeria monocytogenes, Escherichia coli, Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni, C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica, E. coli, and C. botulinum were greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes.
UR - http://www.scopus.com/inward/record.url?scp=84963569080&partnerID=8YFLogxK
U2 - 10.1128/AEM.00078-16
DO - 10.1128/AEM.00078-16
M3 - Article
C2 - 26873315
SN - 0099-2240
VL - 82
SP - 2433
EP - 2443
JO - Default journal
JF - Default journal
IS - 8
ER -