Evidence map›Paper›PMID 36299720›Full record

ReviewFrontiers in microbiology2022

Rumen microbiota of indigenous and introduced ruminants and their adaptation to the Qinghai-Tibetan plateau.

Bin Li, Gaobin Jia, Dongxu Wen, Xiuxin Zhao, Junxing Zhang, Qing Xu, Xialing Zhao, Nan Jiang, Zhenjiang Liu, Yachun Wang

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
5.7field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
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  5. Review
  6. Effects of DietaryMicroorganisms · 2026
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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

10 authors at 6 institutions in 1 country.

Bin LiInstitute of Animal Husbandry and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, Lhasa, China.
Gaobin JiaInstitute of Animal Husbandry and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, Lhasa, China.
Dongxu WenInstitute of Animal Husbandry and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, Lhasa, China.
Xiuxin ZhaoAgricultural College, Ningxia University, Yinchuan, China.
Junxing ZhangAgricultural College, Ningxia University, Yinchuan, China.
Qing XuInstitute of Life Sciences and Bio-Engineering, Beijing Jiaotong University, Beijing, China.
Xialing ZhaoInstitute of Animal Husbandry and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, Lhasa, China.
Nan JiangColleges of Life Science and Technology, Dalian University, Dalian Economic Technological Development Zone, Dalian, China.
Zhenjiang LiuNational Engineering Laboratory for AIDS Vaccine, School of Life Sciences, Jilin University, Changchun, China.
Yachun WangAgricultural College, Ningxia University, Yinchuan, China.
Ningxia University · CNDalian University · CNAnimal Science Research Institute · CNBeijing Jiaotong University · CNJilin University · CNTibet Academy of Agricultural and Animal Husbandry Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The grassland in the Qinghai-Tibetan plateau provide habitat for many indigenous and introduced ruminants which perform important ecological functions that impact the whole Qinghai-Tibetan plateau ecosystem. These indigenous Tibetan ruminants have evolved several adaptive traits to withstand the severe environmental conditions, especially cold, low oxygen partial pressure, high altitude, strong UV radiation, and poor forage availability on the alpine rangelands. Despite the challenges to husbandry associated with the need for enhanced adaptation, several domesticated ruminants have also been successfully introduced to the alpine pasture regions to survive in the harsh environment. For ruminants, these challenging conditions affect not only the host, but also their commensal microbiota, especially the diversity and composition of the rumen microbiota; multiple studies have described tripartite interactions among host-environment-rumen microbiota. Thus, there are significant benefits to understanding the role of rumen microbiota in the indigenous and introduced ruminants of the Qinghai-Tibetan plateau, which has co-evolved with the host to ensure the availability of specific metabolic functions required for host survival, health, growth, and development. In this report, we systemically reviewed the dynamics of rumen microbiota in both indigenous and introduced ruminants (including gut microbiota of wild ruminants) as well as their structure, functions, and interactions with changing environmental conditions, especially low food availability, that enable survival at high altitudes. We summarized that three predominant driving factors including increased VFA production, enhanced fiber degradation, and lower methane production as indicators of higher efficiency energy harvest and nutrient utilization by microbiota that can sustain the host during nutrient deficit. These cumulative studies suggested alteration of rumen microbiota structure and functional taxa with genes that encode cellulolytic enzymes to potentially enhance nutrient and energy harvesting in response to low quality and quantity forage and cold environment. Future progress toward understanding ruminant adaptation to high altitudes will require the integration of phenotypic data with multi-omics analyses to identify host-microbiota co-evolutionary adaptations enabling survival on the Qinghai-Tibetan plateau.

Indexed as

adaptationinteractionmicrobiotaplateauruminants

Identifiers

PMID36299720
PMCPMC9589358
OpenAlexW4304160981

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.