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Updated: Jan 23, 2026

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
Published on: August 25, 2018
Comparison of 16S rDNA Next Sequencing of Microbiome Communities From Post-scalder and Post-picker Stages in Three
Jennifer A Wages1, Kristina M Feye1, Si Hong Park1
1Center for Food Safety and Department of Food Science, University of Arkansas, Fayetteville, AR, United States.
Abstract:
Poultry processing systems are a complex network of equipment and automation systems that require a proactive approach to monitoring in order to protect the food supply. Process oversight requires the use of multi-hurdle intervention systems to ensure that any undesirable microorganisms are reduced or eliminated by the time the carcasses are processed into final products. In the present study, whole bird carcass rinses (WBCR) collected at the post-scalder and post-picker locations from three different poultry processing facilities (Plant A: mid-weight broiler processing, B: large-weight broiler processing, C: young broiler (Cornish) processing) were subjected to next generation sequencing (NGS) and microbial quantification using direct plating methods to assess the microbial populations present during these stages of the poultry process. The quantification of aerobic plate counts (APC) and Enterobacteriaceae (EB) demonstrated that reductions for these microbial classes were not consistent between the two sampling locations for all facilities, but did not provide a clear picture of what microorganism(s) may be affecting those shifts. With the utilization of NGS, a more complete characterization of the microbial communities present including microorganisms that would not have been identified with the employed direct plating methodologies were identified. Although the foodborne pathogens typically associated with raw poultry, Salmonella and Campylobacter, were not identified, sequence analysis performed by Quantitative Insights of Microbiology Ecology (QIIME) indicated shifts of Erwinia, Serratia, and Arcobacter, which are microorganisms closely related to Salmonella and Campylobacter. Additionally, the presence of Chryseobacterium and Pseudomonas at both sampling locations and at all three facilities provides evidence that these microorganisms could potentially be utilized to assess the performance of multi-hurdle intervention systems.
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