Cargando…

Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Xiang, Noyes, Noelle R., Doster, Enrique, Martin, Jennifer N., Linke, Lyndsey M., Magnuson, Roberta J., Yang, Hua, Geornaras, Ifigenia, Woerner, Dale R., Jones, Kenneth L., Ruiz, Jaime, Boucher, Christina, Morley, Paul S., Belk, Keith E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959480/
https://www.ncbi.nlm.nih.gov/pubmed/26873315
http://dx.doi.org/10.1128/AEM.00078-16
_version_ 1782444406944563200
author Yang, Xiang
Noyes, Noelle R.
Doster, Enrique
Martin, Jennifer N.
Linke, Lyndsey M.
Magnuson, Roberta J.
Yang, Hua
Geornaras, Ifigenia
Woerner, Dale R.
Jones, Kenneth L.
Ruiz, Jaime
Boucher, Christina
Morley, Paul S.
Belk, Keith E.
author_facet Yang, Xiang
Noyes, Noelle R.
Doster, Enrique
Martin, Jennifer N.
Linke, Lyndsey M.
Magnuson, Roberta J.
Yang, Hua
Geornaras, Ifigenia
Woerner, Dale R.
Jones, Kenneth L.
Ruiz, Jaime
Boucher, Christina
Morley, Paul S.
Belk, Keith E.
author_sort Yang, Xiang
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4959480
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher American Society for Microbiology
record_format MEDLINE/PubMed
spelling pubmed-49594802016-07-26 Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain Yang, Xiang Noyes, Noelle R. Doster, Enrique Martin, Jennifer N. Linke, Lyndsey M. Magnuson, Roberta J. Yang, Hua Geornaras, Ifigenia Woerner, Dale R. Jones, Kenneth L. Ruiz, Jaime Boucher, Christina Morley, Paul S. Belk, Keith E. Appl Environ Microbiol Public and Environmental Health Microbiology 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. American Society for Microbiology 2016-04-04 /pmc/articles/PMC4959480/ /pubmed/26873315 http://dx.doi.org/10.1128/AEM.00078-16 Text en Copyright © 2016 Yang et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Public and Environmental Health Microbiology
Yang, Xiang
Noyes, Noelle R.
Doster, Enrique
Martin, Jennifer N.
Linke, Lyndsey M.
Magnuson, Roberta J.
Yang, Hua
Geornaras, Ifigenia
Woerner, Dale R.
Jones, Kenneth L.
Ruiz, Jaime
Boucher, Christina
Morley, Paul S.
Belk, Keith E.
Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain
title Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain
title_full Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain
title_fullStr Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain
title_full_unstemmed Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain
title_short Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain
title_sort use of metagenomic shotgun sequencing technology to detect foodborne pathogens within the microbiome of the beef production chain
topic Public and Environmental Health Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959480/
https://www.ncbi.nlm.nih.gov/pubmed/26873315
http://dx.doi.org/10.1128/AEM.00078-16
work_keys_str_mv AT yangxiang useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT noyesnoeller useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT dosterenrique useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT martinjennifern useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT linkelyndseym useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT magnusonrobertaj useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT yanghua useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT geornarasifigenia useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT woernerdaler useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT joneskennethl useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT ruizjaime useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT boucherchristina useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT morleypauls useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain
AT belkkeithe useofmetagenomicshotgunsequencingtechnologytodetectfoodbornepathogenswithinthemicrobiomeofthebeefproductionchain