Evidence map›Paper›PMID 38868437›Full record

ArticleiMeta2023

Quantitative microbiome profiling reveals the developmental trajectory of the chicken gut microbiota and its connection to host metabolism.

Yuqing Feng, Meihong Zhang, Yan Liu, Xinyue Yang, Fuxiao Wei, Xiaolu Jin, Dan Liu, Yuming Guo, Yongfei Hu

Abstract read
In one paragraph

Article in iMeta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing 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

54 citing papers in PubMed.

  1. Article
  2. Microorganisms · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Diet-vaccine interactions: SQM Iron andApplied and environmental microbiology · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. 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

9 authors.

Yuqing FengState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.ORCID 0000-0002-7742-5272
Meihong ZhangState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.
Yan LiuState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.
Xinyue YangState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.
Fuxiao WeiState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.
Xiaolu JinState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.
Dan LiuState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.
Yuming GuoState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.
Yongfei HuState Key Laboratory of Animal Nutrition, College of Animal Science and Technology China Agricultural University Beijing China.ORCID 0000-0002-2158-6018

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Revealing the assembly and succession of the chicken gut microbiota is critical for a better understanding of its role in chicken physiology and metabolism. However, few studies have examined dynamic changes of absolute chicken gut microbes using the quantitative microbiome profiling (QMP) method. Here, we revealed the developmental trajectory of the broiler chicken gut bacteriome and mycobiome by combining high-throughput sequencing with a microbial load quantification assay. We showed that chicken gut microbiota abundance and diversity reached a plateau at 7 days posthatch (DPH), forming segment-specific community types after 1 DPH. The bacteriome was more impacted by deterministic processes, and the mycobiome was more affected by stochastic processes. We also observed stage-specific microbes in different gut segments, and three microbial occurrence patterns including "colonization," "disappearance," and "core" were defined. The microbial co-occurrence networks were very different among gut segments, with more positive associations than negative associations. Furthermore, we provided links between the absolute changes in chicken gut microbiota and their serum metabolite variations. Time-course untargeted metabolomics revealed six metabolite clusters with different changing patterns of abundance. The foregut microbiota had more connections with chicken serum metabolites, and the gut microbes were closely related to chicken lipid and amino acid metabolism. The present study provided a full landscape of chicken gut microbiota development in a quantitative manner, and the associations between gut microbes and chicken serum metabolites further highlight the impact of gut microbiota in chicken growth and development.

Indexed as

chicken gut microbiotadevelopmental trajectoryquantitative microbiome profilingrelative microbiome profilingserum metabolites

Identifiers

PMID38868437
PMCPMC10989779

What OpenQuestion holds

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LicenceCC BY
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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.