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Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis
BACKGROUND: Bacterial spores are important contaminants in food, and the spore forming bacteria are often implicated in food safety and food quality considerations. Spore formation is a complex developmental process involving the expression of more than 500 genes over the course of 6 to 8 hrs. The p...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4213463/ https://www.ncbi.nlm.nih.gov/pubmed/25341802 http://dx.doi.org/10.1186/s12918-014-0119-x |
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author | Ihekwaba, Adaoha EC Mura, Ivan Barker, Gary C |
author_facet | Ihekwaba, Adaoha EC Mura, Ivan Barker, Gary C |
author_sort | Ihekwaba, Adaoha EC |
collection | PubMed |
description | BACKGROUND: Bacterial spores are important contaminants in food, and the spore forming bacteria are often implicated in food safety and food quality considerations. Spore formation is a complex developmental process involving the expression of more than 500 genes over the course of 6 to 8 hrs. The process culminates in the formation of resting cells capable of resisting environmental extremes and remaining dormant for long periods of time, germinating when conditions promote further vegetative growth. Experimental observations of sporulation and germination are problematic and time consuming so that reliable models are an invaluable asset in terms of prediction and risk assessment. In this report we develop a model which assists in the interpretation of sporulation dynamics. RESULTS: This paper defines and analyses a mathematical model for the network regulating Bacillus subtilis sporulation initiation, from sensing of sporulation signals down to the activation of the early genes under control of the master regulator Spo0A. Our model summarises and extends other published modelling studies, by allowing the user to execute sporulation initiation in a scenario where Isopropyl β-D-1-thiogalactopyranoside (IPTG) is used as an artificial sporulation initiator as well as in modelling the induction of sporulation in wild-type cells. The analysis of the model results and the comparison with experimental data indicate that the model is good at predicting inducible responses to sporulation signals. However, the model is unable to reproduce experimentally observed accumulation of phosphorelay sporulation proteins in wild type B. subtilis. This model also highlights that the phosphorelay sub-component, which relays the signals detected by the sensor kinases to the master regulator Spo0A, is crucial in determining the response dynamics of the system. CONCLUSION: We show that there is a complex connectivity between the phosphorelay features and the master regulatory Spo0A. Additional we discovered that the experimentally observed regulation of the phosphotransferase Spo0B for wild-type B. subtilis may be playing an important role in the network which suggests that modelling of sporulation initiation may require additional experimental support. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-014-0119-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4213463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42134632014-11-06 Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis Ihekwaba, Adaoha EC Mura, Ivan Barker, Gary C BMC Syst Biol Research Article BACKGROUND: Bacterial spores are important contaminants in food, and the spore forming bacteria are often implicated in food safety and food quality considerations. Spore formation is a complex developmental process involving the expression of more than 500 genes over the course of 6 to 8 hrs. The process culminates in the formation of resting cells capable of resisting environmental extremes and remaining dormant for long periods of time, germinating when conditions promote further vegetative growth. Experimental observations of sporulation and germination are problematic and time consuming so that reliable models are an invaluable asset in terms of prediction and risk assessment. In this report we develop a model which assists in the interpretation of sporulation dynamics. RESULTS: This paper defines and analyses a mathematical model for the network regulating Bacillus subtilis sporulation initiation, from sensing of sporulation signals down to the activation of the early genes under control of the master regulator Spo0A. Our model summarises and extends other published modelling studies, by allowing the user to execute sporulation initiation in a scenario where Isopropyl β-D-1-thiogalactopyranoside (IPTG) is used as an artificial sporulation initiator as well as in modelling the induction of sporulation in wild-type cells. The analysis of the model results and the comparison with experimental data indicate that the model is good at predicting inducible responses to sporulation signals. However, the model is unable to reproduce experimentally observed accumulation of phosphorelay sporulation proteins in wild type B. subtilis. This model also highlights that the phosphorelay sub-component, which relays the signals detected by the sensor kinases to the master regulator Spo0A, is crucial in determining the response dynamics of the system. CONCLUSION: We show that there is a complex connectivity between the phosphorelay features and the master regulatory Spo0A. Additional we discovered that the experimentally observed regulation of the phosphotransferase Spo0B for wild-type B. subtilis may be playing an important role in the network which suggests that modelling of sporulation initiation may require additional experimental support. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-014-0119-x) contains supplementary material, which is available to authorized users. BioMed Central 2014-10-24 /pmc/articles/PMC4213463/ /pubmed/25341802 http://dx.doi.org/10.1186/s12918-014-0119-x Text en © Ihekwaba et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Ihekwaba, Adaoha EC Mura, Ivan Barker, Gary C Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis |
title | Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis |
title_full | Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis |
title_fullStr | Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis |
title_full_unstemmed | Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis |
title_short | Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis |
title_sort | computational modelling and analysis of the molecular network regulating sporulation initiation in bacillus subtilis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4213463/ https://www.ncbi.nlm.nih.gov/pubmed/25341802 http://dx.doi.org/10.1186/s12918-014-0119-x |
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