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Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ

BACKGROUND: Gene regulatory networks can be modelled in various ways depending on the level of detail required and biological questions addressed. One of the earliest formalisms used for modeling is a Boolean network, although these models cannot describe most temporal aspects of a biological system...

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Autores principales: Ruklisa, Dace, Brazma, Alvis, Cerans, Karlis, Schlitt, Thomas, Viksna, Juris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544977/
https://www.ncbi.nlm.nih.gov/pubmed/31151381
http://dx.doi.org/10.1186/s12859-019-2909-z
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author Ruklisa, Dace
Brazma, Alvis
Cerans, Karlis
Schlitt, Thomas
Viksna, Juris
author_facet Ruklisa, Dace
Brazma, Alvis
Cerans, Karlis
Schlitt, Thomas
Viksna, Juris
author_sort Ruklisa, Dace
collection PubMed
description BACKGROUND: Gene regulatory networks can be modelled in various ways depending on the level of detail required and biological questions addressed. One of the earliest formalisms used for modeling is a Boolean network, although these models cannot describe most temporal aspects of a biological system. Differential equation models have also been used to model gene regulatory networks, but these frameworks tend to be too detailed for large models and many quantitative parameters might not be deducible in practice. Hybrid models bridge the gap between these two model classes – these are useful when concentration changes are important while the information about precise concentrations and binding site affinities is partial. RESULTS: In this paper we study the stable behaviours of phage λ via a hybrid system based model. We identify wild type and mutant behaviours that arise for various orderings of binding site affinities. We propose experiments for detecting these behaviours: we suggest several ways of altering binding affinities with either mutations or genome rearrangements to achieve modified behaviours. The feasibility of these experiments is assessed. The interplay between the qualitative aspects of a network, e.g. network topology, and quantitative parameters, e.g. growth and degradation rates of proteins, is demonstrated. We also provide a software for exploring all feasible states of a hybrid system model and identifying all attractors. CONCLUSIONS: The behaviours of phage λ are determined mainly by the topology of this network and by the mutual order of binding affinities. Exact affinities and growth and degradation rates of proteins fine tune the system. We show that only two stable behaviours are possible for phage λ if the main constraints of λ switch are preserved – these behaviours correspond to lysis and lysogeny. We identify several variants of both lysis and lysogeny – one wild type and one modified behaviour for each. We elucidate the necessary constraints for binding site affinities to achieve both wild type lysis and lysogeny. Our software is applicable to a wide range of biological models described as a hybrid system. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2909-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-65449772019-06-04 Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ Ruklisa, Dace Brazma, Alvis Cerans, Karlis Schlitt, Thomas Viksna, Juris BMC Bioinformatics Research Article BACKGROUND: Gene regulatory networks can be modelled in various ways depending on the level of detail required and biological questions addressed. One of the earliest formalisms used for modeling is a Boolean network, although these models cannot describe most temporal aspects of a biological system. Differential equation models have also been used to model gene regulatory networks, but these frameworks tend to be too detailed for large models and many quantitative parameters might not be deducible in practice. Hybrid models bridge the gap between these two model classes – these are useful when concentration changes are important while the information about precise concentrations and binding site affinities is partial. RESULTS: In this paper we study the stable behaviours of phage λ via a hybrid system based model. We identify wild type and mutant behaviours that arise for various orderings of binding site affinities. We propose experiments for detecting these behaviours: we suggest several ways of altering binding affinities with either mutations or genome rearrangements to achieve modified behaviours. The feasibility of these experiments is assessed. The interplay between the qualitative aspects of a network, e.g. network topology, and quantitative parameters, e.g. growth and degradation rates of proteins, is demonstrated. We also provide a software for exploring all feasible states of a hybrid system model and identifying all attractors. CONCLUSIONS: The behaviours of phage λ are determined mainly by the topology of this network and by the mutual order of binding affinities. Exact affinities and growth and degradation rates of proteins fine tune the system. We show that only two stable behaviours are possible for phage λ if the main constraints of λ switch are preserved – these behaviours correspond to lysis and lysogeny. We identify several variants of both lysis and lysogeny – one wild type and one modified behaviour for each. We elucidate the necessary constraints for binding site affinities to achieve both wild type lysis and lysogeny. Our software is applicable to a wide range of biological models described as a hybrid system. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2909-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-31 /pmc/articles/PMC6544977/ /pubmed/31151381 http://dx.doi.org/10.1186/s12859-019-2909-z Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Ruklisa, Dace
Brazma, Alvis
Cerans, Karlis
Schlitt, Thomas
Viksna, Juris
Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ
title Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ
title_full Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ
title_fullStr Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ
title_full_unstemmed Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ
title_short Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ
title_sort dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544977/
https://www.ncbi.nlm.nih.gov/pubmed/31151381
http://dx.doi.org/10.1186/s12859-019-2909-z
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