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      Driving forces shaping the microbial ecology in meat packing plants

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          Abstract

          Meat production is a complex system, continually receiving animals, water, air, and workers, all of which serve as carriers of bacteria. Selective pressures involved in different meat processing stages such as antimicrobial interventions and low temperatures, may promote the accumulation of certain residential microbiota in meat cutting facilities. Bacteria including human pathogens from all these sources can contaminate meat surfaces. While significant advancements have been made in enhancing hygienic standards and pathogen control measures in meat plants, resulting in a notable reduction in STEC recalls and clinical cases, STEC still stands as a predominant contributor to foodborne illnesses associated with beef and occasionally with pork. The second-and third-generation sequencing technology has become popular in microbiota related studies and provided a better image of the microbial community in the meat processing environments. In this article, we reviewed the potential factors influencing the microbial ecology in commercial meat processing facilities and conducted a meta-analysis on the microbiota data published in the last 10 years. In addition, the mechanisms by which bacteria persist in meat production environments have been discussed with a focus on the significant human pathogen E. coli O157:H7 and generic E. coli, an indicator often used for the hygienic condition in food production.

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          Most cited references127

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              Cutadapt removes adapter sequences from high-throughput sequencing reads

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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/862408/overviewRole: Role: Role: Role: Role: Role:
                Role: Role: Role: Role: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2564766/overviewRole: Role: Role: Role: Role: Role: Role: Role:
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                23 January 2024
                2023
                : 14
                : 1333696
                Affiliations
                [1] 1Lacombe Research and Development Centre, Agriculture and Agri-Food Canada , Lacombe, AB, Canada
                [2] 2Food and Human Nutritional Sciences, University of Manitoba , Winnipeg, MB, Canada
                [3] 3Department of Animal Sciences, Center for Meat Safety and Quality, Colorado State University , Fort Collins, CO, United States
                Author notes

                Edited by: Mehran Moradi, Urmia University, Iran

                Reviewed by: Eleftherios H. Drosinos, Agricultural University of Athens, Greece

                Leyla Kahyaoglu, Middle East Technical University, Türkiye

                Yolande Thérèse Rose Proroga, Experimental Zooprophylactic Institute of Southern Italy (IZSM), Italy

                *Correspondence: Xianqin Yang, xianqin.yang@ 123456agr.gc.ca
                Article
                10.3389/fmicb.2023.1333696
                10844536
                38322759
                8cb38b08-e50b-42c4-b78f-6674760af79a
                Copyright © 2024 Claudia Narvaez, and His Majesty the King in Right of Canada, as represented by the Minister of Agriculture and Agri-Food Canada for the contribution of Xianqin Yang and Peipei Zhang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 November 2023
                : 22 December 2023
                Page count
                Figures: 5, Tables: 1, Equations: 0, References: 129, Pages: 16, Words: 13054
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. PZ acknowledges the library funding for publication provided by Colorado State University. XY acknowledges funding support from Beef Cattle Research Council and Results Driven Agricultural Research (FOS.01.21 and 2022F027R). CN-B acknowledges funding support from Beef Cattle Research Council (FOS.04.18).
                Categories
                Microbiology
                Review
                Custom metadata
                Food Microbiology

                Microbiology & Virology
                microbiota,meat processing facilities,beef,pork,persistent bacteria,sequencing,shiga toxin-producing escherichia coli,biofilm

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