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Microbiome-Informed Food Safety and Quality: Longitudinal Consistency and Cross-Sectional Distinctiveness of Retail Chicken Breast Microbiomes

Authors :
Shaoting Li
David Ames Mann
Shaokang Zhang
Yan Qi
Richard J. Meinersmann
Xiangyu Deng
Source :
mSystems, Vol 5, Iss 5 (2020)
Publication Year :
2020
Publisher :
American Society for Microbiology, 2020.

Abstract

ABSTRACT Microorganisms and their communities on foods are important determinants and indicators of food safety and quality. Despite growing interests in studying food and food-related microbiomes, how effective and practical it is to glean various food safety and quality information from food commodity microbiomes remains underinvestigated. Microbiomes of retail chicken breast from 4 processing establishments in 3 major U.S. broiler production states displayed longitudinal consistency over 7 months and cross-sectional distinctiveness associated with individual processing environments. Packaging type and processing environment but not antibiotic usage and seasonality affected composition and diversity of the microbiomes. Low abundances of antimicrobial resistance genes were found on chicken breasts, and no significant resistome difference was observed between antibiotic-free and conventional products. Benchmarked by culture enrichment, shotgun metagenomics sequencing delivered sensitive and specific detection of Salmonella enterica from chicken breasts. IMPORTANCE Chicken has recently overtaken beef as the most-consumed meat in the United States. The growing popularity of chicken is accompanied by frequent occurrences of foodborne pathogens and increasing concerns over antibiotic usage. Our study represents a proof-of-concept investigation into the possibility and practicality of leveraging microbiome-informed food safety and quality. Through a longitudinal and cross-sectional survey, we established the chicken microbiome as a robust and multifaceted food microbiology attribute that could provide a variety of safety and quality information and retain systematic signals characteristic of overall processing environments.

Details

Language :
English
ISSN :
23795077
Volume :
5
Issue :
5
Database :
Directory of Open Access Journals
Journal :
mSystems
Publication Type :
Academic Journal
Accession number :
edsdoj.b55408d4dfba405ba09d2461f90181f1
Document Type :
article
Full Text :
https://doi.org/10.1128/mSystems.00589-20