Evidence map›Paper›PMID 40878553›Full record

ArticleJournal of microbiology (Seoul, Korea)2025

Multi-omics to evaluate the protective mechanisms during Akkermansia muciniphila treatment of Candida albicans colonization and subsequent infection.

Qiulin Luo, Huan Zhang, Youming Pu, Yingpu Wei, Jiangkun Yu, Xiaoshen Wang, Qin Cai, Ying Hu, Wenli Yuan

Abstract read
In one paragraph

Article in Journal of microbiology (Seoul, Korea), 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. Microbe on the move:Journal of bacteriology · 2026
    Review
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.

Qiulin LuoDepartment of Clinical Laboratory, The Affiliated Hospital of Yunnan University (The Second People's Hospital of Yunnan Province), Kunming, Yunnan 650021, P. R. China.
Huan ZhangDepartment of Clinical Laboratory, The Affiliated Hospital of Yunnan University (The Second People's Hospital of Yunnan Province), Kunming, Yunnan 650021, P. R. China.
Youming PuDepartment of Clinical Laboratory, People's Hospital of Chuxiong city, Chuxiong, Yunnan 675000, P. R. China.
Yingpu WeiDepartment of Clinical Laboratory, The Affiliated Hospital of Yunnan University (The Second People's Hospital of Yunnan Province), Kunming, Yunnan 650021, P. R. China.
Jiangkun YuState Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming, Yunnan 650500, P. R. China.
Xiaoshen WangDepartment of Clinical Laboratory, The Affiliated Hospital of Yunnan University (The Second People's Hospital of Yunnan Province), Kunming, Yunnan 650021, P. R. China.
Qin CaiDepartment of Clinical Laboratory, People's Hospital of Chuxiong city, Chuxiong, Yunnan 675000, P. R. China.
Ying HuDepartment of Clinical Laboratory, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650101, P. R. China.
Wenli YuanDepartment of Clinical Laboratory, The Affiliated Hospital of Yunnan University (The Second People's Hospital of Yunnan Province), Kunming, Yunnan 650021, P. R. China.

Funding

Association Foundation Program of Yunnan Provincial Science and Technology Department and Kunming Medical University 202001AY070001-255National Natural Science Foundation of China 82360409Top Experts training Project for the Academy and Technology in Yunnan province 202305AC160072Wellcome Trust 202404Yunnan University Medical Research Foundation YDYXJJ2024- 0009Yunnan University Medical Research Foundation YDYXJJ2024-0032
6 · The paper itself

Abstract

Akkermansia muciniphila (AKK, A. muciniphila) fortifies the intestinal barrier, inhibits the colonization of pathogenic bacteria, and protects the host's health. Nevertheless, the existing literature offers inadequate evidence to ascertain whether A. muciniphila can effectively treat Candida albicans (C. albicans) infections in vitro, and the underlying mechanisms remain ambiguous. This study, animal models were established through gavage with clinical isolates of C. albicans to induce gastrointestinal tract colonization and subsequent translocation infection. The models were subsequently administered A. muciniphila. We examined the analysis of 16S rRNA gene sequencing, metabolomics of colonic contents, and transcriptomics of colonic tissue. The intestinal barrier, inflammatory responses, and immune cell infiltration are analyzed. This study revealed that A. muciniphila markedly mitigated C. albicans translocation infection and modified the intestinal microbial community structure and metabolic attributes in model mice. After administering A. muciniphila to the translocation infection group, there was a notable increase in the prevalence of bacteria that produce short-chain fatty acids, including Eubacterium_F. Moreover, there was a significant increase in the levels of specific pathogens, including Faecalibaculum, Turicibacter, and Turicimonas. The study demonstrated that A. muciniphila treatment can improve the composition of intestinal microbiota and metabolites, augment the tight junctions of colonic tissue and diminish systemic inflammatory response. This presents an innovative therapeutic approach for the potential treatment of intestinal C. albicans infection using A. muciniphila.

Indexed as

Candida albicansCandidiasisProbioticsAkkermansiaAnimalsColonDisease Models, AnimalGastrointestinal MicrobiomeMaleMetabolomicsMiceMultiomicsRNA, Ribosomal, 16SVerrucomicrobiaRNA, Ribosomal, 16SAkkermansia muciniphilaCandida albicansgastrointestinal colonizationmulti-omics analysistranslocation infection

Identifiers

PMID40878553
PMCPMC13577117

What OpenQuestion holds

Textmetadata
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.