Evidence map›Paper›PMID 31849891›Full record

ArticleFrontiers in microbiology2019

A Comparison of 16S rRNA Profiles Through Slaughter in Australian Export Beef Abattoirs.

Sanga Kang, Joshua Ravensdale, Ranil Coorey, Gary A Dykes, Robert Barlow

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sanga KangSchool of Public Health, Curtin University, Bentley, WA, Australia.
Joshua RavensdaleSchool of Public Health, Curtin University, Bentley, WA, Australia.
Ranil CooreySchool of Molecular and Life Sciences, Curtin University, Bentley, WA, Australia.
Gary A DykesSchool of Public Health, Curtin University, Bentley, WA, Australia.
Robert BarlowAgriculture and Food, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Brisbane, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial contamination of beef cattle carcases and subsequent cross-contamination during processing is inevitable and virtually impossible to prevent. The understanding of microbial contamination in the beef industry is currently limited to hypotheses based on traditional microbiological tools. Additionally, the complex structural and functional responses of beef cattle microbial communities to the fragmentation in the supply chain remain unknown. This study used 16S rRNA gene sequencing in combination with traditional microbiology to monitor and compare changes in the microbiota throughout slaughter in an integrated (abattoir A) and a fragmented (abattoir B) beef abattoir in Australia. Briefly, the primary difference between an integrated and a fragmented abattoir is that fragmented abattoirs receive cattle from multiple sources, whereas integrated abattoirs typically receive cattle that has been produced using the same production system and from a limited number of sources. The composition in the bacterial communities varied between the abattoirs, though the presence of the most predominant bacterial species within the microbiota at each abattoir was similar. Lactobacillales (2.4-56.2%) and Pseudomonadales (2.4-59.4%) most notably dominated hides, carcases, and the environment in abattoir B. In abattoir A, Bacteroidales (3.9-43.8%), Lactobacillales (0.0-61.9%), and Pseudomonadales (0.5-72.1%) fluctuated but generally shared the dominance over the rest. Combined results of total viable count (TVC) and 16S rRNA gene profiling indicated that an upward hide pulling system adopted by abattoir B may lead to increased transmission of hide contaminants to post-hide pull carcases. Abattoir B had 3.2 log

Indexed as

16S rRNA sequencingbeef contaminationbeef microbiotabeef slaughterbeef supply chainmicrobial contamination

Identifiers

PMID31849891
PMCPMC6895009

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.