Evidence map›Paper›PMID 42804574›Full record

ReviewVirulence2026

Coordination of quorum sensing with T3SS and T6SS: Bacterial strategies for combating fungal pathogens.

Yuanyuan Ma, Anmin Ren, Xiaolei Ji, Yihua Sun, Peng Xue, Liang Yang

Abstract readReview
In one paragraph

Review in Virulence, 2026. 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.

Yuanyuan MaInstitute for Applied Research in Public Health, School of Public Health, Nantong University, Nantong, China.
Anmin RenSchool of Medicine, Southern University of Science and Technology, Shenzhen, China.
Xiaolei JiInstitute for Applied Research in Public Health, School of Public Health, Nantong University, Nantong, China.
Yihua SunInstitute for Applied Research in Public Health, School of Public Health, Nantong University, Nantong, China.
Peng XueInstitute for Applied Research in Public Health, School of Public Health, Nantong University, Nantong, China.ORCID 0000-0003-2755-7987
Liang YangSchool of Medicine, Southern University of Science and Technology, Shenzhen, China.ORCID 0000-0002-2362-0128

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial-fungal interactions are essential for ecosystem balance, where secretion systems like the Type III Secretion System (T3SS) and Type VI Secretion System (T6SS) play crucial roles. T6SS acts as a multifunctional weapon by delivering antifungal effectors that disrupt fungal cell integrity and metabolism, while T3SS mediates both mutualistic and antagonistic interactions, with mutualistic roles documented primarily in plant-associated bacteria-fungi systems. Quorum sensing (QS) facilitates these interactions by allowing bacteria to adjust their secretion responses based on fungal signals. This review delves into the antifungal mechanisms of T6SS and T3SS and emphasizes QS as a regulatory framework that influences microbial community dynamics. Understanding these relationships can lead to innovative strategies for combating fungal pathogens, contributing to agricultural sustainability and paving the way for future clinical and environmental research.

Indexed as

BacteriaBacterial Secretion SystemsFungiQuorum SensingType VI Secretion SystemsAntifungal AgentsMicrobial InteractionsPlantsSymbiosisAntifungal AgentsBacterial Secretion SystemsType VI Secretion Systemsantifungal mechanismsbacterial-fungal interactionsquorum sensingT3SST6SS

Identifiers

PMID42804574
PMCPMC13625719

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.