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

基因组 肠沙门氏菌 生物 微生物群 弯曲杆菌 空肠弯曲杆菌 产气荚膜梭菌 霰弹枪测序 单核细胞增生李斯特菌 饲养场 致病菌 沙门氏菌 微生物学 生物技术 细菌 DNA测序 遗传学 生态学 基因 DNA
作者
Xiang Yang,Noelle Noyes,Enrique Doster,J. N. Martin,Lyndsey Linke,Roberta J. Magnuson,Hua Yang,Ifigenia Geornaras,Dale R. Woerner,Kenneth L. Jones,Jaime Ruiz,Christina Boucher,Paul S. Morley,K. E. Belk
出处
期刊:Applied and Environmental Microbiology [American Society for Microbiology]
卷期号:82 (8): 2433-2443 被引量:132
标识
DOI:10.1128/aem.00078-16
摘要

ABSTRACT 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.
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