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Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

Sato M, Tsuda K, Wang L, Coller J, Watanabe Y, Glazebrook J, Katagiri F - PLoS Pathog. (2010)

Bottom Line: The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate.Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Biology, Microbial and Plant Genomics Institute, University of Minnesota, St. Paul, Minnesota, United States of America.

ABSTRACT
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. 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 for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the 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 static network model accurately predicted 23 of 25 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; and (ii) negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were 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.

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A hypothesis of sector switching.First, recognition of MAMPs leads to activation of the EMT sectors (A), which then activates the SA sector (B) [30]. If pathogen effectors perturb the EMT sectors, the inhibition of the SA sector by the EMT sectors becomes negligible, and the SA sector becomes highly activated, including signal amplification involving positive feedback [70], and deploys a potent defense response (C). If pathogen effectors perturb the SA sector, the inhibition of the EMT sectors by the SA sector becomes negligible, and the EMT sectors become highly activated and deploy a strong defense response (D). Note that the EMT sectors and the SA sector are not highly activated simultaneously.
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ppat-1001011-g005: A hypothesis of sector switching.First, recognition of MAMPs leads to activation of the EMT sectors (A), which then activates the SA sector (B) [30]. If pathogen effectors perturb the EMT sectors, the inhibition of the SA sector by the EMT sectors becomes negligible, and the SA sector becomes highly activated, including signal amplification involving positive feedback [70], and deploys a potent defense response (C). If pathogen effectors perturb the SA sector, the inhibition of the EMT sectors by the SA sector becomes negligible, and the EMT sectors become highly activated and deploy a strong defense response (D). Note that the EMT sectors and the SA sector are not highly activated simultaneously.

Mentions: The plant immune system must be robust against various perturbations caused by pathogens, which typically evolve much faster than plants. At the same time, not only are immune responses energy-expensive [60] but at least some are also detrimental to the plant fitness [61], [62], [63]. Therefore, ideally immune responses should be contained at the minimally necessary level. We speculate that to balance these apparently conflicting selection pressures, the EMT and SA sectors adjust the level of immune responses according to demand through the positive and negative regulatory relationships between them (Figure 5). When the plant is attacked by a pathogen, the EMT sectors are activated based on recognition of MAMPs. While the activation of the EMT sectors starts the activation of the SA sector with a delay, the SA sector does not become highly activated due to suppression by the strongly-activated EMT sectors. This is probably because detrimental effects of defense components controlled by the EMT sectors are less severe than those of the SA sector: if defense components controlled by the SA sector are not necessary, it is better not to activate them. The delay in activation of the SA sector by the EMT sectors is important in buying time for evaluation of the effect of the EMT sector-mediated defense. However, if the pathogen is to some extent adapted to the plant host and its effectors interfere with the EMT sectors, the resulting weakened activity of the EMT sectors could release the SA sector from suppression. In fact, several P. syringae effectors, such as HopAI1 [10], target components of the EMT sectors. Using the SA sector-controlled defense components against more virulent pathogens is reasonable, as the SA sector-controlled defenses are known to be potent in defense against biotrophic and hemi-biotrophic pathogens [39]. Thus, an elaborate combination of positive and negative regulatory relationships between the EMT and the SA sectors may enable shifting the balance between the EMT sectors for defense against less virulent pathogens to keep negative impacts of the immune response on plant fitness low and to reserve the SA sector for defense against more virulent biotrophic and hemi-biotrophic pathogens.


Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

Sato M, Tsuda K, Wang L, Coller J, Watanabe Y, Glazebrook J, Katagiri F - PLoS Pathog. (2010)

A hypothesis of sector switching.First, recognition of MAMPs leads to activation of the EMT sectors (A), which then activates the SA sector (B) [30]. If pathogen effectors perturb the EMT sectors, the inhibition of the SA sector by the EMT sectors becomes negligible, and the SA sector becomes highly activated, including signal amplification involving positive feedback [70], and deploys a potent defense response (C). If pathogen effectors perturb the SA sector, the inhibition of the EMT sectors by the SA sector becomes negligible, and the EMT sectors become highly activated and deploy a strong defense response (D). Note that the EMT sectors and the SA sector are not highly activated simultaneously.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2908620&req=5

ppat-1001011-g005: A hypothesis of sector switching.First, recognition of MAMPs leads to activation of the EMT sectors (A), which then activates the SA sector (B) [30]. If pathogen effectors perturb the EMT sectors, the inhibition of the SA sector by the EMT sectors becomes negligible, and the SA sector becomes highly activated, including signal amplification involving positive feedback [70], and deploys a potent defense response (C). If pathogen effectors perturb the SA sector, the inhibition of the EMT sectors by the SA sector becomes negligible, and the EMT sectors become highly activated and deploy a strong defense response (D). Note that the EMT sectors and the SA sector are not highly activated simultaneously.
Mentions: The plant immune system must be robust against various perturbations caused by pathogens, which typically evolve much faster than plants. At the same time, not only are immune responses energy-expensive [60] but at least some are also detrimental to the plant fitness [61], [62], [63]. Therefore, ideally immune responses should be contained at the minimally necessary level. We speculate that to balance these apparently conflicting selection pressures, the EMT and SA sectors adjust the level of immune responses according to demand through the positive and negative regulatory relationships between them (Figure 5). When the plant is attacked by a pathogen, the EMT sectors are activated based on recognition of MAMPs. While the activation of the EMT sectors starts the activation of the SA sector with a delay, the SA sector does not become highly activated due to suppression by the strongly-activated EMT sectors. This is probably because detrimental effects of defense components controlled by the EMT sectors are less severe than those of the SA sector: if defense components controlled by the SA sector are not necessary, it is better not to activate them. The delay in activation of the SA sector by the EMT sectors is important in buying time for evaluation of the effect of the EMT sector-mediated defense. However, if the pathogen is to some extent adapted to the plant host and its effectors interfere with the EMT sectors, the resulting weakened activity of the EMT sectors could release the SA sector from suppression. In fact, several P. syringae effectors, such as HopAI1 [10], target components of the EMT sectors. Using the SA sector-controlled defense components against more virulent pathogens is reasonable, as the SA sector-controlled defenses are known to be potent in defense against biotrophic and hemi-biotrophic pathogens [39]. Thus, an elaborate combination of positive and negative regulatory relationships between the EMT and the SA sectors may enable shifting the balance between the EMT sectors for defense against less virulent pathogens to keep negative impacts of the immune response on plant fitness low and to reserve the SA sector for defense against more virulent biotrophic and hemi-biotrophic pathogens.

Bottom Line: The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate.Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Biology, Microbial and Plant Genomics Institute, University of Minnesota, St. Paul, Minnesota, United States of America.

ABSTRACT
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. 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 for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the 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 static network model accurately predicted 23 of 25 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; and (ii) negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were 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.

Show MeSH
Related in: MedlinePlus