Plant-microbial association networks
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB36623 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3895420.fastq.gz | Fastqsanger.gz | |||
| ERR3895430.fastq.gz | Fastqsanger.gz | |||
| ERR3895440.fastq.gz | Fastqsanger.gz | |||
| ERR3895450.fastq.gz | Fastqsanger.gz | |||
| ERR3895421.fastq.gz | Fastqsanger.gz |
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Project description:Plants in their natural and agricultural environments are continuously exposed to a plethora of diverse microorganisms resulting in microbial colonization of plants in the rhizosphere. This process is believed to be accompanied by an intricate network of ongoing simultaneous interactions. In this study, we compared transcriptional patterns of Arabidopsis thaliana roots and shoots in the presence and absence of whole microbial communities extracted from compost soil. The results show a clear growth promoting effect of Arabidopsis shoots in the presence of soil microbes compared to axenically grown plants under identical conditions. Element analyses showed that iron uptake was facilitated by these mixed microbial communities which also lead to transcriptional downregulation of genes required for iron transport. In addition, soil microbial communities suppressed the expression of marker genes involved in oxidative stress/redox signalling, cell wall modification and plant defense. While most previous studies have focussed on individual plant-microbe interactions, our data suggest that multi-species transcriptional profiling, using simultaneous plant and metatranscriptomics coupled to metagenomics may be required to further increase our understanding of the intricate networks underlying plant-microbe interactions in their diverse environments.
2013-03-09 | GSE44984 | GEO
Project description:Plants in their natural and agricultural environments are continuously exposed to a plethora of diverse microorganisms resulting in microbial colonization of plants in the rhizosphere. This process is believed to be accompanied by an intricate network of ongoing simultaneous interactions. In this study, we compared transcriptional patterns of Arabidopsis thaliana roots and shoots in the presence and absence of whole microbial communities extracted from compost soil. The results show a clear growth promoting effect of Arabidopsis shoots in the presence of soil microbes compared to axenically grown plants under identical conditions. Element analyses showed that iron uptake was facilitated by these mixed microbial communities which also lead to transcriptional downregulation of genes required for iron transport. In addition, soil microbial communities suppressed the expression of marker genes involved in oxidative stress/redox signalling, cell wall modification and plant defense. While most previous studies have focussed on individual plant-microbe interactions, our data suggest that multi-species transcriptional profiling, using simultaneous plant and metatranscriptomics coupled to metagenomics may be required to further increase our understanding of the intricate networks underlying plant-microbe interactions in their diverse environments. Four samples were analysed in total. One corresponded to a pooled sample of RNA extracted from root tissues of 60 plants. The other three were biological replicates from shoot tissues, each of which contained 20 plants. Controls were used as reference and corresponded to tissues of plants grown in sterile conditions.
2013-03-09 | E-GEOD-44984 | biostudies-arrayexpress
Project description:Although some mechanisms are known how plant growth beneficial bacteria help plants to grow under stressful conditions, we still know little how the metabolism of host plants and bacteria is coordinated during the establishment of functional interaction. In the present work, using single and dual transcriptomics, we studied the reprograming of metabolic and signaling pathways of Enterobacter sp. SA187 with Arabidopsis thaliana during the change from free-living to endophytic host-microbe interaction. We could identify major changes in primary and secondary metabolic pathways in both the host and bacteria upon interaction, with an important role of the sulfur metabolism and retrograde signaling in mediating plant resistance to salt stress. Also, we studied the effect of SA187 endogenous compounds and its role on sulfur metabolism and consequently salt tolerance. These data should help future research in the field of beneficial plant-microbe interactions for developing sophisticated strategies to improve agriculture of crops under adverse environmental conditions. transcriptome of Arabidopsis thaliana organs with beneficial microbe, beneficial microbe endogenous compound, and ethylene precursor
2021-02-25 | GSE145884 | GEO
Project description:Pritchard2014 - plant-microbe
interaction
This
model is an abstraction of a generic interaction between microbes,
and a plant host. The reactions are generally intended to be
representative of processes, not specific molecular mechanisms
(except where indicated, eg. for activation of receptors). The
model is intended to be of a similar level of abstraction as the
Zig-Zag model proposed in Jones and Dangl (2006) [PMID:
17108957
],
but
to represent a dynamic system. Jones and Dangl (2006) model is
used here to illustrate the advantages of dynamic representations
of systems over expository models such as the Zig-Zag
model.
This model is described in the article:
The zigzag model of
plant-microbe interactions: is it time to move on?
Pritchard L, Birch PR.
Mol. Plant Pathol. 2014 Dec; 15(9):
865-870
Abstract:
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000563.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000563 | BioModels
Project description:plant-microbial synergism Metagenome
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Project description:Flavonoids are stress-inducible metabolites important for plant-microbe interactions. In contrast to their well-known function in initiating rhizobia nodulation in legumes, it is unclear whether and how flavonoids may contribute to plant stress resistance through affecting non-nodulating bacteria in the root microbiome. Here we show how flavonoids preferentially attracts Aeromonadaceae in Arabidopsis thaliana root microbiome and how flavonoid-dependent recruitment of an Aeromona spp. results in enhanced plant Na_H1 resistance.
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Project description:Flavonoids are stress-inducible metabolites important for plant-microbe interactions. In contrast to their well-known function in initiating rhizobia nodulation in legumes, it is unclear whether and how flavonoids may contribute to plant stress resistance through affecting non-nodulating bacteria in the root microbiome. Here we show how flavonoids preferentially attracts Aeromonadaceae in Arabidopsis thaliana root microbiome and how flavonoid-dependent recruitment of an Aeromona spp. results in enhanced plant drought resistance.
2022-10-19 | GSE184872 | GEO
Project description:Due to the recent advances in high-throughput sequencing technologies, it becomes possible to directly analyze microbial communities in human body and environment. To understand how microbial communities adapt, develop, and interact with the human body and the surrounding environment, one of the fundamental challenges is to infer the interactions among different microbes. However, due to the compositional and high-dimensional nature of microbial data, statistical inference cannot offer reliable results. Consequently, new approaches that can accurately and robustly estimate the associations (putative interactions) among microbes are needed to analyze such compositional and high-dimensional data. We propose a novel framework called Microbial Prior Lasso (MPLasso) which integrates graph learning algorithm with microbial co-occurrences and associations obtained from scientific literature by using automated text mining. We show that MPLasso outperforms existing models in terms of accuracy, microbial network recovery rate, and reproducibility. Furthermore, the association networks we obtain from the Human Microbiome Project datasets show credible results when compared against laboratory data.
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Project description:Plants deploy pattern recognition receptors to detect microbe- and damage-associated molecular patterns. Arabidopsis thaliana receptor-like protein RLP30 contributes to innate immunity to the necrotrophic fungus Sclerotinia sclerotiorum by recognizing SCLEROTINIA CULTURE FILTRATE ELICITOR 1 (SCFE1). Here we show that the S. sclerotiorum small cysteine-rich protein SCP1 accounts for elicitor activity of SCFE1. RLP30 recognizes SCP1 and its homologs from divergent fungi and oomycetes, as well as an SCP1-unrelated and conserved pattern from bacterial Pseudomonads. Stable expression of RLP30 in Nicotiana tabacum confers enhanced immunity to bacterial, fungal, and oomycete pathogens. Unlike Arabidopsis, which requires intact SCP1 for RLP30-mediated immunity, other Brassicaceae and Solanaceae respond to smaller immunogenic SCP1 epitopes. We conclude that Arabidopsis RLP30 recognizes immunogenic patterns from three microbial kingdoms and that mechanistically different SCP1 perception has evolved in other plant species, likely as a result of convergent evolution.
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