Evidence map›Paper›PMID 36503572›Full record

ArticleMicrobiome2022

Integrated multi-omics of the gastrointestinal microbiome and ruminant host reveals metabolic adaptation underlying early life development.

Xiaoting Yan, Huazhe Si, Yuhang Zhu, Songze Li, Yu Han, Hanlu Liu, Rui Du, Phillip B Pope, Qiang Qiu, Zhipeng Li

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

22 citing papers in PubMed, 26 citations in OpenAlex.

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  19. Microbiota and Metabolite Profiles in the Feces of Juvenile Sika Deer (Animals : an open access journal from MDPI · 2024
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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 5 institutions in 2 countries.

Xiaoting Yan *College of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China.
Huazhe Si *College of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China.
Yuhang Zhu *College of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China.
Songze LiCollege of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China.
Yu HanCollege of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China.
Hanlu LiuDepartment of Special Animal Nutrition and Feed Science, Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun, 130112, China.
Rui DuCollege of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China.
Phillip B PopeFaculty of Biosciences, Norwegian University of Life Sciences, 1433, Ås, Norway. phil.pope@nmbu.no.
Qiang QiuSchool of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710100, China. qiuqiang@lzu.edu.cn.
Zhipeng LiCollege of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China. zhipengli@jlau.edu.cn.ORCID http://orcid.org/0000-0001-8474-045X
Jilin Agricultural University · CNNorthwestern Polytechnical University · CNChinese Academy of Agricultural Sciences · CNJilin University · CNNorwegian University of Life Sciences · NO

Funding

National Natural Science Foundation of China 32122083Novo Nordisk Fonden 054575 - SuPAcow
6 · The paper itself

Abstract

backgroundThe gastrointestinal tract (GIT) microbiome of ruminants and its metabolic repercussions vastly influence host metabolism and growth. However, a complete understanding of the bidirectional interactions that occur across the host-microbiome axis remains elusive, particularly during the critical development stages at early life. Here, we present an integrative multi-omics approach that simultaneously resolved the taxonomic and functional attributes of microbiota from five GIT regions as well as the metabolic features of the liver, muscle, urine, and serum in sika deer (Cervus nippon) across three key early life stages.

resultsWithin the host, analysis of metabolites over time in serum, urine, and muscle (longissimus lumborum) showed that changes in the fatty acid profile were concurrent with gains in body weight. Additional host transcriptomic and metabolomic analysis revealed that fatty acid β-oxidation and metabolism of tryptophan and branched chain amino acids play important roles in regulating hepatic metabolism. Across the varying regions of the GIT, we demonstrated that a complex and variable community of bacteria, viruses, and archaea colonized the GIT soon after birth, whereas microbial succession was driven by the cooperative networks of hub populations. Furthermore, GIT volatile fatty acid concentrations were marked by increased microbial metabolic pathway abundances linked to mannose (rumen) and amino acids (colon) metabolism. Significant functional shifts were also revealed across varying GIT tissues, which were dominated by host fatty acid metabolism associated with reactive oxygen species in the rumen epithelium, and the intensive immune response in both small and large intestine. Finally, we reveal a possible contributing role of necroptosis and apoptosis in enhancing ileum and colon epithelium development, respectively.

conclusionsOur findings provide a comprehensive view for the involved mechanisms in the context of GIT microbiome and ruminant metabolic growth at early life. Video Abstract.

Indexed as

DeerGastrointestinal MicrobiomeAnimalsFatty Acids, VolatileMultiomicsRumenFatty Acids, VolatileButyrateCooperationEarly lifeFatty acid metabolismImmune responseOntogenyRegion- and stage-specific development

Identifiers

PMID36503572
PMCPMC9743514
OpenAlexW4311671243

What Socratic 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 Socratic graph.