Evidence map›Paper›PMID 40713906›Full record

ArticleAnimal microbiome2025

Strain-resolved comparison of beef and draft cattle rumen microbiomes using single-microbe genomics.

Feifei Guan, Jianhan Liu, Lincong Zhou, Qichang Tong, Ningfeng Wu, Tao Tu, Yuan Wang, Bin Yao, Huiying Luo, Jian Tian and 1 more

Abstract read
In one paragraph

Article in Animal microbiome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Feifei Guan *National Key Laboratory of Agricultural Microbiology, Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Jianhan Liu *State Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
Lincong Zhou *National Key Laboratory of Agricultural Microbiology, Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Qichang TongState Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
Ningfeng WuNational Key Laboratory of Agricultural Microbiology, Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Tao TuState Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
Yuan WangState Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
Bin YaoState Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
Huiying LuoState Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China. luohuiying@caas.cn.
Jian TianState Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China. tianjian@caas.cn.
Huoqing HuangState Key Laboratory of Animal Nutrition and Feeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China. huanghuoqing@caas.cn.

Funding

the Agricultural Science and Technology Innovation Program CAAS-ZDRW202304the China Agriculture Research System of MOF and MARA CARS-41the National Key R&D Program of China 2023YFD1302200the National Natural Science Foundation of China 32222082
6 · The paper itself

Abstract

backgroundBeef and draft cattle have distinct rumen microbiota that can influence their metabolic processes and body composition. However, traditional metagenomic sequencing methods only provide broad surveys of the rumen microbial genomic contents. In this study, we utilized high-throughput single-cell genome sequencing to investigate these differences at the strain level.

resultsFollowing quality control and contig assembly, we obtained 97 bacterial genomes, 17 archaeal genomes, and 241 subspecies genomes from the rumen samples of Angus and Wuling cattle. Our analysis revealed a higher bacterial abundance in Angus rumen, characterized by an enrichment of the Succiniclasticum and Limivicinus genera. In contrast, the rumen of Wuling cattle exhibited a higher archaeal abundance. Additionally, we observed variations in the types and abundance of microbial-derived enzymes responsible for plant fiber degradation and volatile fatty acid (VFA) production between the two cattle breeds. The Angus rumen was found to harbor a higher diversity and abundance of cellulases and hemicellulases, particularly from the Ruminococcus unknown_0 genus. Furthermore, genera such as Succiniclasticum, Butyrivibrio, Limivicinus, UBA2868, and Prevotella were identified as key contributors to VFA production. Our findings suggest that the Angus rumen may have a stronger VFA production capacity due to the higher abundance of acidogenic genera. Interestingly, we also observed a greater abundance of Methanobrevibacter_A methanogens, which play a crucial role in energy flow in the rumen ecosystem, in Wuling cattle compared to Angus cattle.

conclusionOur study highlights differences in the rumen microbiome of Angus and Wuling cattle. This difference could, at least partially, account for the variation in fat content that ultimately results in the superior meat quality of Angus cattle and the sustained muscle activity required by draft cattle. Overall, single-cell genome sequencing reveals distinct microbial composition and metabolic pathways between the two breeds, providing insights into their unique physiological and metabolic needs.

Indexed as

Beef cattleDraft cattleHigh-throughputRumen microbeSingle-microbe genomics sequencing

Identifiers

PMID40713906
PMCPMC12291375

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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.