Evidence map›Paper›PMID 41674575›Full record

ArticleiMetaOmics2025

Microbiota humanization drives human-like metabolic and immune transcriptomic shifts in pigs.

Zhaoqi Zhang, Yanan Xu, Kun Pang, Changhong Wu, Chenxu Zhao, Tong Lei, Jiayu Zhang, Tang Hai, Fangqing Zhao, Yong Zhao

Abstract read
In one paragraph

Article in iMetaOmics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

10 authors.

Zhaoqi ZhangState Key Laboratory of Membrane Biology, Institute of Zoology Chinese Academy of Sciences Beijing China.ORCID https://orcid.org/0000-0003-1568-0857
Yanan XuState Key Laboratory of Membrane Biology, Institute of Zoology Chinese Academy of Sciences Beijing China.
Kun PangInstitute of Zoology Chinese Academy of Sciences Beijing China.
Changhong WuState Key Laboratory of Membrane Biology, Institute of Zoology Chinese Academy of Sciences Beijing China.
Chenxu ZhaoState Key Laboratory of Membrane Biology, Institute of Zoology Chinese Academy of Sciences Beijing China.
Tong LeiState Key Laboratory of Membrane Biology, Institute of Zoology Chinese Academy of Sciences Beijing China.
Jiayu ZhangState Key Laboratory of Membrane Biology, Institute of Zoology Chinese Academy of Sciences Beijing China.
Tang HaiBeijing Institute for Stem Cell and Regenerative Medicine Beijing China.
Fangqing ZhaoInstitute of Zoology Chinese Academy of Sciences Beijing China.
Yong ZhaoState Key Laboratory of Membrane Biology, Institute of Zoology Chinese Academy of Sciences Beijing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pigs are increasingly recognized as promising candidates for clinical xenotransplantation and as large-animal models for biomedical research; however, interspecies differences in gut microbiota, immune function, and metabolism remain major barriers. To address this, we established gut microbiota-humanized (GMH) pigs by transplanting human fecal microbiota into antibiotic-treated pigs. We systemically evaluated alterations in microbiota composition, serum metabolites, and immune cell profiles using integrated metagenomic, quasi-targeted metabolomic and single-cell transcriptomic (scRNA-seq) analyses. Metagenomic profiling revealed a shift in the intestinal microbiota of GMH pigs toward a human-like composition, characterized by enrichment of

Indexed as

gut microbiotahumanized pigshuman microbiota transplantationimmune cellsmetabolismpigs

Identifiers

PMID41674575
PMCPMC12806034

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.