Evidence map›Paper›PMID 38695733›Full record

ArticleMolecular plant pathology2024

An effector SsCVNH promotes the virulence of Sclerotinia sclerotiorum through targeting class III peroxidase AtPRX71.

Ming Ma, Liguang Tang, Rui Sun, Xueliang Lyu, Jiatao Xie, Yanping Fu, Bo Li, Tao Chen, Yang Lin, Xiao Yu and 3 more

Open access · goldAbstract read
In one paragraph

Article in Molecular plant pathology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
6.6field-weighted citation impact, top 4% of its field
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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. The Guanine Exchange FactorJournal of fungi (Basel, Switzerland) · 2025
    Article
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  6. Trans-Kingdom sRNA Silencing inPathogens (Basel, Switzerland) · 2025
    Review
  7. A Novel Effector FoUpe9 Enhances the Virulence ofJournal of fungi (Basel, Switzerland) · 2025
    Article
  8. Article
  9. 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

13 authors at 3 institutions in 2 countries.

Ming MaNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.
Liguang TangWuhan Vegetable Research Institute, Wuhan Academy of Agricultural Science, Wuhan, Hubei, China.
Rui SunNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.
Xueliang LyuNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.
Jiatao XieNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.
Yanping FuThe Provincial Key Lab of Plant Pathology of Hubei Province, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
Bo LiNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.ORCID 0000-0002-7337-0112
Tao ChenNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.ORCID 0000-0003-4614-4440
Yang LinThe Provincial Key Lab of Plant Pathology of Hubei Province, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.ORCID 0000-0003-3942-7063
Xiao YuNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.
Weidong ChenUnited States Department of Agriculture, Agricultural Research Service, Washington State University, Pullman, Washington, USA.
Daohong JiangNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.
Jiasen ChengNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, Hubei, China.ORCID 0000-0003-0040-2360
Huazhong Agricultural University · CNUnited States Department of Agriculture · USWuhan Academy of Agricultural Sciences · CN

Funding

Huazhong Agricultural University Scientific and Technological Self-innovation Foundation 2021ZKPY014National Natural Science Foundation of China 31701735National Natural Science Foundation of China 32130087National Natural Science Foundation of China 32172368The earmarked fund of China Agriculture Research System CARS-12
6 · The paper itself

Abstract

Many plant pathogens secrete effector proteins into the host plant to suppress host immunity and facilitate pathogen colonization. The necrotrophic pathogen Sclerotinia sclerotiorum causes severe plant diseases and results in enormous economic losses, in which secreted proteins play a crucial role. SsCVNH was previously reported as a secreted protein, and its expression is significantly upregulated at 3 h after inoculation on the host plant. Here, we further demonstrated that deletion of SsCVNH leads to attenuated virulence. Heterologous expression of SsCVNH in Arabidopsis enhanced pathogen infection, inhibited the host PAMP-triggered immunity (PTI) response and increased plant susceptibility to S. sclerotiorum. SsCVNH interacted with class III peroxidase AtPRX71, a positive regulator of innate immunity against plant pathogens. SsCVNH could also interact with other class III peroxidases, thus reducing peroxidase activity and suppressing plant immunity. Our results reveal a new infection strategy employed by S. sclerotiorum in which the fungus suppresses the function of class III peroxidases, the major component of PTI to promote its own infection.

Indexed as

ArabidopsisAscomycotaFungal ProteinsPlant DiseasesPlant ImmunityPeroxidasesVirulenceFungal ProteinsPeroxidasesAtPRX71peroxidaseSclerotinia sclerotiorumSsCVNH

Identifiers

PMID38695733
PMCPMC11064801
OpenAlexW4396579552

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.