Evidence map›Paper›PMID 27784266›Full record

ArticleBMC genomics2016

Transcriptomic responses of a simplified soil microcosm to a plant pathogen and its biocontrol agent reveal a complex reaction to harsh habitat.

Michele Perazzolli, Noemí Herrero, Lieven Sterck, Luisa Lenzi, Alberto Pellegrini, Gerardo Puopolo, Yves Van de Peer, Ilaria Pertot

Abstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Molecular Tools for MonitoringFrontiers in microbiology · 2018
    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

8 authors.

Michele PerazzolliDepartment of Sustainable Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, 38010 S, Michele all'Adige, Italy. michele.perazzolli@fmach.it.ORCID 0000-0001-7218-9963
Noemí HerreroDepartment of Sustainable Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, 38010 S, Michele all'Adige, Italy.
Lieven SterckDepartment of Plant Systems Biology, VIB, 9052, Ghent, Belgium.
Luisa LenziDepartment of Sustainable Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, 38010 S, Michele all'Adige, Italy.
Alberto PellegriniDepartment of Sustainable Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, 38010 S, Michele all'Adige, Italy.
Gerardo PuopoloDepartment of Sustainable Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, 38010 S, Michele all'Adige, Italy.
Yves Van de PeerDepartment of Plant Systems Biology, VIB, 9052, Ghent, Belgium.
Ilaria PertotDepartment of Sustainable Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, 38010 S, Michele all'Adige, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSoil microorganisms are key determinants of soil fertility and plant health. Soil phytopathogenic fungi are one of the most important causes of crop losses worldwide. Microbial biocontrol agents have been extensively studied as alternatives for controlling phytopathogenic soil microorganisms, but molecular interactions between them have mainly been characterised in dual cultures, without taking into account the soil microbial community. We used an RNA sequencing approach to elucidate the molecular interplay of a soil microbial community in response to a plant pathogen and its biocontrol agent, in order to examine the molecular patterns activated by the microorganisms.

resultsA simplified soil microcosm containing 11 soil microorganisms was incubated with a plant root pathogen (Armillaria mellea) and its biocontrol agent (Trichoderma atroviride) for 24 h under controlled conditions. More than 46 million paired-end reads were obtained for each replicate and 28,309 differentially expressed genes were identified in total. Pathway analysis revealed complex adaptations of soil microorganisms to the harsh conditions of the soil matrix and to reciprocal microbial competition/cooperation relationships. Both the phytopathogen and its biocontrol agent were specifically recognised by the simplified soil microcosm: defence reaction mechanisms and neutral adaptation processes were activated in response to competitive (T. atroviride) or non-competitive (A. mellea) microorganisms, respectively. Moreover, activation of resistance mechanisms dominated in the simplified soil microcosm in the presence of both A. mellea and T. atroviride. Biocontrol processes of T. atroviride were already activated during incubation in the simplified soil microcosm, possibly to occupy niches in a competitive ecosystem, and they were not further enhanced by the introduction of A. mellea.

conclusionsThis work represents an additional step towards understanding molecular interactions between plant pathogens and biocontrol agents within a soil ecosystem. Global transcriptional analysis of the simplified soil microcosm revealed complex metabolic adaptation in the soil environment and specific responses to antagonistic or neutral intruders.

Indexed as

EcosystemSoil MicrobiologyTranscriptomeCluster AnalysisComputational BiologyGene ExpressionGene Expression ProfilingHigh-Throughput Nucleotide SequencingHost-Pathogen InteractionsMetagenomeMetagenomicsMolecular Sequence AnnotationPlant RootsBiological controlGene expressionMicrobial interactionPlant pathogenRNA-SeqSoil microbial communitySoil transcriptomeTranscriptomics

Identifiers

PMID27784266
PMCPMC5081961

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Registered trials

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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.