Project description:Plant-parasitic cyst nematodes induce the formation of hypermetabolic feeding sites, termed syncytia, as their sole source of nutrients. The formation of the syncytium is orchestrated by the nematode in part by modulation of phytohormone responses, including cytokinin. In response to infection by the nematode H. schachtii, cytokinin signaling is transiently induced at the site of infection and in the developing syncytium. Arabidopsis lines with reduced cytokinin sensitivity show reduced susceptibility to nematode infection, indicating that cytokinin signaling is required for optimal nematode development. Furthermore, lines with increased cytokinin sensitivity also exhibit reduced nematode susceptibility. To ascertain why cytokinin hypersensitivity reduces nematode parasitism, we examined the transcriptomes in wild-type and a cytokinin-hypersensitive type-A arr Arabidopsis mutant in response to H. schachtii infection. Genes involved in the response to biotic stress and defense response were elevated in the type-A arr mutant in the absence of nematodes and were hyper-induced following H. schachtii infection, which suggests that the Arabidopsis type-A arr mutants impede nematode development because they are primed to respond to pathogen infection. These results suggest that cytokinin signaling is required for optimal H. schachtii parasitism of Arabidopsis, but that elevated cytokinin signaling triggers a heightened immune response to nematode infection.
Project description:Expression profiles of 22 reference Arabidopsis immunity mutants were collected using the Arabidopsis Pathoarray 464_001 (GPL3638) in order to build a network model predicting the Arabidopsis immune signaling network. Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. Here, we demonstrate that use of mRNA profiling to collect and analyze detailed descriptions of changes in the network state resulting from specific network perturbations is a powerful and economical strategy to elucidate regulatory relationships among the components of a complex signaling network. Specifically, we studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with the Pto DC3000 AvrRpt2 and used as detailed descriptions of the network states resulting from specific genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting network model accurately predicted 22 of 23 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; (ii) negative regulatory relationships are common between signaling sectors. One case of a novel negative regulatory relationship, between the early microbe-associated molecular pattern (MAMP)-activated sector and the salicylic acid (SA)-mediated sector, was further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector-switching" network, which effectively balances two apparently conflicting demands, robustness against pathogenic perturbations and moderation of negative impacts of immune responses on plant fitness. Keywords: Responses of reference Arabidopsis immunity mutants to Pseudomonas syringae pv. tomato DC3000 carrying avrRpt2 This experiment consists of two (group00) or three (group01-04) biological replicates of each genotype (total 25 genotypes [3 are multiple mutants, which were removed for the network modeling, but were used for normalization]). For each genotype, two leaves per plant were pooled from three pots to prepare total RNA.
Project description:A major part of plant immune response is mediated by signaling pathways controlled by three hormnes, jasmonate, ethylene, and salicylate. The involvement of each of these hormone signaling pathways in Arabidopsis thaliana was investigated in response to infection of a necrotrophic fungal pathogen, A. brassicicola. Arabideopsis mutants deficient in these hormone signaling pathways were compared to wild type.
Project description:Recognition of microbial patterns and host derived damage signals by host pattern recognition receptors is a key step in immune activation in multicellular eukaryotes. Here we show how mutations in ethylene signaling and the coreceptor bak1 affect host immune responses triggered by elicitors. A 51 DNA microarray study using total RNA from Arabidopsis mutants (ein2-1, bak1-3, efr-1 and pepr1-1 pepr2-3) as well as wild type treated with elf18 or Pep2 with three biological replicates.
Project description:Expression profiles of 22 reference Arabidopsis immunity mutants were collected using the Arabidopsis Pathoarray 464_001 (GPL3638) in order to build a network model predicting the Arabidopsis immune signaling network. Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. Here, we demonstrate that use of mRNA profiling to collect and analyze detailed descriptions of changes in the network state resulting from specific network perturbations is a powerful and economical strategy to elucidate regulatory relationships among the components of a complex signaling network. Specifically, we studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with the Pto DC3000 AvrRpt2 and used as detailed descriptions of the network states resulting from specific genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting network model accurately predicted 22 of 23 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; (ii) negative regulatory relationships are common between signaling sectors. One case of a novel negative regulatory relationship, between the early microbe-associated molecular pattern (MAMP)-activated sector and the salicylic acid (SA)-mediated sector, was further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector-switching" network, which effectively balances two apparently conflicting demands, robustness against pathogenic perturbations and moderation of negative impacts of immune responses on plant fitness. Keywords: Responses of reference Arabidopsis immunity mutants to Pseudomonas syringae pv. tomato DC3000 carrying avrRpt2
Project description:<p>Rapid metabolic responses to pathogens are essential for plant survival and depend on numerous transcription factors. Mediator is the major transcriptional co-regulator for integration and transmission of signals from transcriptional regulators to RNA polymerase II. Using four Arabidopsis Mediator mutants, med16, med18, med25 and cdk8, we studied how differences in regulation of their transcript and metabolite levels correlate to their responses to Pseudomonas syringae infection. We found that med16 and cdk8 were susceptible, while med25 showed increased resistance. Glucosinolates, phytoalexins and carbohydrates were reduced already before infection in med16 and cdk8, but increased in med25, which also display increased benzenoids levels. Early after infection, wild type plants showed reduced glucosinolate and nucleoside levels, but increases in amino acids, benzeniods, oxylipins and the phytoalexin Camalexin. The Mediator mutants showed altered levels of these metabolites and in regulation of genes encoding key enzymes for their metabolism. At later stage, mutants displayed defective levels of specific amino acids, carbohydrates, lipids and jasmonates which correlates to their infection response phenotypes. Our results reveal that MED16, MED25 and CDK8 are required for a proper, coordinated transcriptional response of genes which encode enzymes involved in important metabolic pathways for Arabidopsis responses to Pseudomonas syringae infection.</p>
Project description:Zhou2015 - Circadian clock with immune
regulator NPR1
Arabidopsis clock model modified from
P2012 (Pokhilko et al., 2013 -
BIOMD0000000445)
model to include the master immune regulator NPR1 coupling to LHY,
TOC1 and PRR7.
Triggers: The Global Quantities contain triggers that allow
one to change coupling settings, Salicyclic acid (SA) treatment and
npr1 mutants.
LHY_on: true->NPR1 couples to LHY
PRR7_on: true->NPR1 couples to PRR7
WT: true->WT plants, false->npr1 mutant plants
SA: true->SA treated plants, false->no treatment
This model has L=1, i.e. operates only under constant light
conditions and is not aiming to make preditions under diurnal
conditions. Due to period overshoot only time points after 28h are
relevant.
This model is described in the article:
Redox rhythm reinforces the
circadian clock to gate immune response.
Zhou M, Wang W, Karapetyan S, Mwimba
M, Marqués J, Buchler NE, Dong X.
Nature 2015 Jun;
Abstract:
Recent studies have shown that in addition to the
transcriptional circadian clock, many organisms, including
Arabidopsis, have a circadian redox rhythm driven by the
organism's metabolic activities. It has been hypothesized that
the redox rhythm is linked to the circadian clock, but the
mechanism and the biological significance of this link have
only begun to be investigated. Here we report that the master
immune regulator NPR1 (non-expressor of pathogenesis-related
gene 1) of Arabidopsis is a sensor of the plant's redox state
and regulates transcription of core circadian clock genes even
in the absence of pathogen challenge. Surprisingly, acute
perturbation in the redox status triggered by the immune signal
salicylic acid does not compromise the circadian clock but
rather leads to its reinforcement. Mathematical modelling and
subsequent experiments show that NPR1 reinforces the circadian
clock without changing the period by regulating both the
morning and the evening clock genes. This balanced network
architecture helps plants gate their immune responses towards
the morning and minimize costs on growth at night. Our study
demonstrates how a sensitive redox rhythm interacts with a
robust circadian clock to ensure proper responsiveness to
environmental stimuli without compromising fitness of the
organism.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000577.
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To the extent possible under law, all copyright and related or
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Project description:Goal of the study is the identification of transcriptome deregulation of smg7 pad4 mutants, which are deficient in nonsense-mediated mRNA decay and are blocked in immune signaling, which should avoid secondary responses from immune signaling