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Equation-free analysis of two-component system signalling model reveals the emergence of co-existing phenotypes in the absence of multistationarity

Equation-free analysis of two-component system signalling model reveals the emergence of co-existing phenotypes in the absence of multistationarity
Equation-free analysis of two-component system signalling model reveals the emergence of co-existing phenotypes in the absence of multistationarity
Phenotypic differences of genetically identical cells under the same environmental conditions have been attributed to the inherent stochasticity of biochemical processes. Various mechanisms have been suggested, including the existence of alternative steady states in regulatory networks that are reached by means of stochastic fluctuations, long transient excursions from a stable state to an unstable excited state, and the switching on and off of a reaction network according to the availability of a constituent chemical species. Here we analyse a detailed stochastic kinetic model of two-component system signalling in bacteria, and show that alternative phenotypes emerge in the absence of these features. We perform a bifurcation analysis of deterministic reaction rate equations derived from the model, and find that they cannot reproduce the whole range of qualitative responses to external signals demonstrated by direct stochastic simulations. In particular, the mixed mode, where stochastic switching and a graded response are seen simultaneously, is absent. However, probabilistic and equation-free analyses of the stochastic model that calculate stationary states for the mean of an ensemble of stochastic trajectories reveal that slow transcription of either response regulator or histidine kinase leads to the coexistence of an approximate basal solution and a graded response that combine to produce the mixed mode, thus establishing its essential stochastic nature. The same techniques also show that stochasticity results in the observation of an all-or-none bistable response over a much wider range of external signals than would be expected on deterministic grounds. Thus we demonstrate the application of numerical equation-free methods to a detailed biochemical reaction network model, and show that it can provide new insight into the role of stochasticity in the emergence of phenotypic diversity
1553-734X
e1002396
Hoyle, Rebecca B.
e980d6a8-b750-491b-be13-84d695f8b8a1
Avitabile, Daniele
048f5fc9-dd44-483f-8e28-343d1f6e0af7
Kierzek, Andrzej M.
ef018cb1-de53-48e3-a27b-c10d5e51ca14
Hoyle, Rebecca B.
e980d6a8-b750-491b-be13-84d695f8b8a1
Avitabile, Daniele
048f5fc9-dd44-483f-8e28-343d1f6e0af7
Kierzek, Andrzej M.
ef018cb1-de53-48e3-a27b-c10d5e51ca14

Hoyle, Rebecca B., Avitabile, Daniele and Kierzek, Andrzej M. (2012) Equation-free analysis of two-component system signalling model reveals the emergence of co-existing phenotypes in the absence of multistationarity. PLoS Computational Biology, 8 (6), e1002396. (doi:10.1371/journal.pcbi.1002396).

Record type: Article

Abstract

Phenotypic differences of genetically identical cells under the same environmental conditions have been attributed to the inherent stochasticity of biochemical processes. Various mechanisms have been suggested, including the existence of alternative steady states in regulatory networks that are reached by means of stochastic fluctuations, long transient excursions from a stable state to an unstable excited state, and the switching on and off of a reaction network according to the availability of a constituent chemical species. Here we analyse a detailed stochastic kinetic model of two-component system signalling in bacteria, and show that alternative phenotypes emerge in the absence of these features. We perform a bifurcation analysis of deterministic reaction rate equations derived from the model, and find that they cannot reproduce the whole range of qualitative responses to external signals demonstrated by direct stochastic simulations. In particular, the mixed mode, where stochastic switching and a graded response are seen simultaneously, is absent. However, probabilistic and equation-free analyses of the stochastic model that calculate stationary states for the mean of an ensemble of stochastic trajectories reveal that slow transcription of either response regulator or histidine kinase leads to the coexistence of an approximate basal solution and a graded response that combine to produce the mixed mode, thus establishing its essential stochastic nature. The same techniques also show that stochasticity results in the observation of an all-or-none bistable response over a much wider range of external signals than would be expected on deterministic grounds. Thus we demonstrate the application of numerical equation-free methods to a detailed biochemical reaction network model, and show that it can provide new insight into the role of stochasticity in the emergence of phenotypic diversity

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Accepted/In Press date: 17 May 2012
Published date: 28 June 2012
Organisations: Mathematical Sciences

Identifiers

Local EPrints ID: 380225
URI: http://eprints.soton.ac.uk/id/eprint/380225
ISSN: 1553-734X
PURE UUID: f64eabea-e9ca-4392-9c88-ed2d1913e10e
ORCID for Rebecca B. Hoyle: ORCID iD orcid.org/0000-0002-1645-1071

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Date deposited: 10 Aug 2015 10:16
Last modified: 15 Mar 2024 03:36

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Contributors

Author: Daniele Avitabile
Author: Andrzej M. Kierzek

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