A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.

The Type III secretion system (TTSS) is a protein secretion machinery used by certain gram-negative bacterial pathogens of plants and animals to deliver effector molecules to the host and is at the core of the ability to cause disease. Extensive molecular and biochemical study has revealed the compo...

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Main Authors: Daniel MacLean, David J Studholme
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2010-02-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20169167/pdf/?tool=EBI
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spelling doaj-61f93204f91f4880849d6577c15531372021-03-03T22:30:34ZengPublic Library of Science (PLoS)PLoS ONE1932-62032010-02-0152e910110.1371/journal.pone.0009101A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.Daniel MacLeanDavid J StudholmeThe Type III secretion system (TTSS) is a protein secretion machinery used by certain gram-negative bacterial pathogens of plants and animals to deliver effector molecules to the host and is at the core of the ability to cause disease. Extensive molecular and biochemical study has revealed the components and their interactions within this system but reductive approaches do not consider the dynamical properties of the system as a whole. In order to gain a better understanding of these dynamical behaviours and to create a basis for the refinement of the experimentally derived knowledge we created a Boolean model of the regulatory interactions within the hrp regulon of Pseudomonas syringae pathovar tomato strain DC3000 Pseudomonas syringae. We compared simulations of the model with experimental data and found them to be largely in accordance, though the hrpV node shows some differences in state changes to that expected. Our simulations also revealed interesting dynamical properties not previously predicted. The model predicts that the hrp regulon is a biologically stable two-state system, with each of the stable states being strongly attractive, a feature indicative of selection for a tightly regulated and responsive system. The model predicts that the state of the GacS/GacA node confers control, a prediction that is consistent with experimental observations that the protein has a role as master regulator. Simulated gene "knock out" experiments with the model predict that HrpL is a central information processing point within the network.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20169167/pdf/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Daniel MacLean
David J Studholme
spellingShingle Daniel MacLean
David J Studholme
A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.
PLoS ONE
author_facet Daniel MacLean
David J Studholme
author_sort Daniel MacLean
title A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.
title_short A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.
title_full A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.
title_fullStr A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.
title_full_unstemmed A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.
title_sort boolean model of the pseudomonas syringae hrp regulon predicts a tightly regulated system.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2010-02-01
description The Type III secretion system (TTSS) is a protein secretion machinery used by certain gram-negative bacterial pathogens of plants and animals to deliver effector molecules to the host and is at the core of the ability to cause disease. Extensive molecular and biochemical study has revealed the components and their interactions within this system but reductive approaches do not consider the dynamical properties of the system as a whole. In order to gain a better understanding of these dynamical behaviours and to create a basis for the refinement of the experimentally derived knowledge we created a Boolean model of the regulatory interactions within the hrp regulon of Pseudomonas syringae pathovar tomato strain DC3000 Pseudomonas syringae. We compared simulations of the model with experimental data and found them to be largely in accordance, though the hrpV node shows some differences in state changes to that expected. Our simulations also revealed interesting dynamical properties not previously predicted. The model predicts that the hrp regulon is a biologically stable two-state system, with each of the stable states being strongly attractive, a feature indicative of selection for a tightly regulated and responsive system. The model predicts that the state of the GacS/GacA node confers control, a prediction that is consistent with experimental observations that the protein has a role as master regulator. Simulated gene "knock out" experiments with the model predict that HrpL is a central information processing point within the network.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20169167/pdf/?tool=EBI
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