Evidence map›Paper›PMID 27507961›Full record

ArticleFrontiers in microbiology2016

Comparison of Fusarium graminearum Transcriptomes on Living or Dead Wheat Differentiates Substrate-Responsive and Defense-Responsive Genes.

Stefan Boedi, Harald Berger, Christian Sieber, Martin Münsterkötter, Imer Maloku, Benedikt Warth, Michael Sulyok, Marc Lemmens, Rainer Schuhmacher, Ulrich Güldener and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
5.5field-weighted citation impact, top 5% 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

27 citing papers in PubMed, 54 citations in OpenAlex.

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  15. Genetic Diversity ofMycobiology · 2022
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  18. The Influence of ArtificialMicroorganisms · 2021
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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

11 authors at 4 institutions in 3 countries.

Stefan BoediFungal Genetics and Genomics Unit, Division of Microbial Genetics and Pathogen Interactions, Department of Applied Genetics and Cell Biology, BOKU University, University and Research Centre Tulln Tulln, Austria.
Harald BergerFungal Genetics and Genomics Unit, Division of Microbial Genetics and Pathogen Interactions, Department of Applied Genetics and Cell Biology, BOKU University, University and Research Centre TullnTulln, Austria; Bioresources, Austrian Institute of Technology GmbHTulln, Austria.
Christian SieberDepartment of Earth and Planetary Sciences, University of California, Berkeley Berkeley, CA, USA.
Martin MünsterkötterHelmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt Neuherberg, Germany.
Imer MalokuDepartment for Agrobiotechnology (IFA-Tulln), BOKU University Tulln, Austria.
Benedikt WarthDepartment for Agrobiotechnology (IFA-Tulln), BOKU University Tulln, Austria.
Michael SulyokDepartment for Agrobiotechnology (IFA-Tulln), BOKU University Tulln, Austria.
Marc LemmensDepartment for Agrobiotechnology (IFA-Tulln), BOKU University Tulln, Austria.
Rainer SchuhmacherDepartment for Agrobiotechnology (IFA-Tulln), BOKU University Tulln, Austria.
Ulrich GüldenerDepartment of Genome-oriented Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München München, Germany.
Joseph StraussFungal Genetics and Genomics Unit, Division of Microbial Genetics and Pathogen Interactions, Department of Applied Genetics and Cell Biology, BOKU University, University and Research Centre TullnTulln, Austria; Bioresources, Austrian Institute of Technology GmbHTulln, Austria.
Austrian Institute of Technology · ATHelmholtz Zentrum München · DETechnical University of Munich · DEUniversity of California, Berkeley · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fusarium graminearum is an opportunistic pathogen of cereals where it causes severe yield losses and concomitant mycotoxin contamination of the grains. The pathogen has mixed biotrophic and necrotrophic (saprophytic) growth phases during infection and the regulatory networks associated with these phases have so far always been analyzed together. In this study we compared the transcriptomes of fungal cells infecting a living, actively defending plant representing the mixed live style (pathogenic growth on living flowering wheat heads) to the response of the fungus infecting identical, but dead plant tissues (cold-killed flowering wheat heads) representing strictly saprophytic conditions. We found that the living plant actively suppressed fungal growth and promoted much higher toxin production in comparison to the identical plant tissue without metabolism suggesting that molecules signaling secondary metabolite induction are not pre-existing or not stable in the plant in sufficient amounts before infection. Differential gene expression analysis was used to define gene sets responding to the active or the passive plant as main impact factor and driver for gene expression. We correlated our results to the published F. graminearum transcriptomes, proteomes, and secretomes and found that only a limited number of in planta- expressed genes require the living plant for induction but the majority uses simply the plant tissue as signal. Many secondary metabolite (SM) gene clusters show a heterogeneous expression pattern within the cluster indicating that different genetic or epigenetic signals govern the expression of individual genes within a physically linked cluster. Our bioinformatic approach also identified fungal genes which were actively repressed by signals derived from the active plant and may thus represent direct targets of the plant defense against the invading pathogen.

Indexed as

active plantdefense genesFusariumpassive plantpathogenicity factorssecondary metabolism

Identifiers

PMID27507961
PMCPMC4960244
OpenAlexW2495157372

What OpenQuestion holds

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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.