Evidence map›Paper›PMID 41675707›Full record

ArticleiMetaOmics2025

Systematic characterization of horizontally transferred biosynthetic gene clusters in the human gut microbiota using HTBGC-Finder.

Jiacheng Wu, Xiao Yang, Lanlan Zhao, Ziyun Li, Guoping Zhao, Lei Zhang

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jiacheng WuMicrobiome-X, School of Public Health, Cheeloo College of Medicine Shandong University Jinan China.
Xiao YangMicrobiome-X, School of Public Health, Cheeloo College of Medicine Shandong University Jinan China.
Lanlan ZhaoMicrobiome-X, School of Public Health, Cheeloo College of Medicine Shandong University Jinan China.
Ziyun LiMicrobiome-X, School of Public Health, Cheeloo College of Medicine Shandong University Jinan China.
Guoping ZhaoMicrobiome-X, School of Public Health, Cheeloo College of Medicine Shandong University Jinan China.
Lei ZhangMicrobiome-X, School of Public Health, Cheeloo College of Medicine Shandong University Jinan China.ORCID 0000-0003-4284-2604

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human gut microbiota contains biosynthetic gene clusters (BGCs) that encode bioactive secondary metabolites, which play pivotal roles in microbe-microbe and host-microbe interactions and serve as a rich source of pharmaceutical lead compounds. Understanding the horizontal transfer of BGCs can reveal insights into microbial adaptation, resource utilization, and evolutionary mechanisms, thereby advancing biotechnological applications. Despite its importance, horizontal transfer of BGCs within the gut microbiota remains poorly understood. In this study, we introduce a novel tool, the Horizontally Transferred Biosynthetic Gene Clusters Finder (HTBGC-Finder), designed to systematically identify potential horizontally transferred BGCs (HTBGCs) within the extensive human gut microbiota. Using HTBGC-Finder, we identified 81 potential HTBGCs, underscoring the prevalence and significance of horizontal gene transfer in shaping the genetic landscape of the gut microbiome. Remarkably, ribosomally synthesized and post-translationally modified peptides (RiPPs) constituted the majority of these HTBGCs (76 out of 81, 93.83%), exhibiting a significantly higher transfer rate compared to non-RiPPs (Chi-squared test,

Indexed as

biosynthetic gene clustersgut microbiomehorizontal gene transfermetagenomicsquorum sensing

Identifiers

PMID41675707
PMCPMC12806405

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.