Evidence map›Paper›PMID 38273357›Full record

ArticleJournal of animal science and biotechnology2024

Diet and monensin influence the temporal dynamics of the rumen microbiome in stocker and finishing cattle.

Jianmin Chai, Caleb P Weiss, Paul A Beck, Wei Zhao, Ying Li, Jiangchao Zhao

Open access · goldAbstract read
In one paragraph

Article in Journal of animal science and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
13.6field-weighted citation impact, top 1% of its field
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

19 citing papers in PubMed, 24 citations in OpenAlex.

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  9. Effects of aAnimals : an open access journal from MDPI · 2025
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  11. Animals : an open access journal from MDPI · 2025
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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

6 authors at 4 institutions in 2 countries.

Jianmin ChaiGuangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, College of Life Science and Engineering, Foshan University, Foshan, China.
Caleb P WeissDivision of Agriculture, Department of Animal Science, University of Arkansas, Fayetteville, AR, USA.
Paul A BeckDivision of Agriculture, Department of Animal Science, University of Arkansas, Fayetteville, AR, USA.ORCID http://orcid.org/0000-0001-6494-9563
Wei ZhaoInstitute of Feed Research of Chinese Academy of Agricultural Sciences, Key Laboratory of Feed Biotechnology of the Ministry of Agriculture and Rural Affairs, Beijing, 100193, China.
Ying LiGuangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, College of Life Science and Engineering, Foshan University, Foshan, China.
Jiangchao ZhaoDivision of Agriculture, Department of Animal Science, University of Arkansas, Fayetteville, AR, USA. jzhao77@uark.edu.ORCID http://orcid.org/0000-0002-2894-8560
United States Department of Agriculture · USChinese Academy of Agricultural Sciences · CNFoshan University · CNOklahoma State University · US

Funding

Animal Breeding and Genetics Key Laboratory of Sichuan Province 2019B030301010Key Laboratory of Animal Molecular Design and Precise Breeding of Guangdong Higher Education Institutes 2019KSYS011National Natural Science Foundation of China 32170430University of Arkansas Agricultural Experiment Station, Hatch Project AR002234
6 · The paper itself

Abstract

backgroundStocker cattle diet and management influence beef cattle performance during the finishing stage, but knowledge of the dynamics of the rumen microbiome associated with the host are lacking. A longitudinal study was conducted to determine how the feeding strategy from the stocker to the finishing stages of production affects the temporal dynamics of rumen microbiota. During the stocker phase, either dry hay or wheat pasture were provided, and three levels of monensin were administrated. All calves were then transported to a feedlot and received similar finishing diets with or without monensin. Rumen microbial samples were collected on d 0, 28, 85 during the stocker stage (S0, S28 and S85) and d 0, 14, 28, 56, 30 d before slaughter and the end of the trial during the finishing stage (F0, F14, F28, F56, Pre-Ba, and Final). The V4 region of the bacterial 16S rRNA gene of 263 rumen samples was sequenced.

resultsHigher alpha diversity, including the number of observed bacterial features and the Shannon index, was observed in the stocker phase compared to the finishing phase. The bacterial amplicon sequence variants (ASVs) differentiating different sampling time points were identified. Dietary treatments during the stocker stage temporally impact the dynamics of rumen microbiota. For example, shared bacteria, including Bacteroidales (ASV19) and Streptococcus infantarius (ASV94), were significantly higher in hay rumen on S28, S85, and F0, while Bacteroidaceae (ASV11) and Limivicinus (ASV15) were more abundant in wheat. Monensin affected rumen microbial composition at a specific time. Transportation to feedlot significantly influenced microbiome structure and diversity in hay-fed calves. Bacterial taxa associated with body weight were classified, and core microbiotas interacted with each other during the trial.

conclusionsIn summary, the temporal dynamics of the rumen microbiome in cattle at the stocker and finishing stage are influenced by multiple factors of the feeding strategy. Diet at the stocker phase may temporarily affect the microbial composition during this stage. Modulating the rumen microbiome in the steers at the stocker stage affects the microbial interactions and performance in the finishing stage.

Indexed as

Beef cattleDietFeedlot phaseMonensinNext-generation sequencingRumen microbiotaStocker

Identifiers

PMID38273357
PMCPMC10811932
OpenAlexW4391261201

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.