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Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model
BACKGROUND: Clostridia are anaerobic Gram-positive Firmicutes containing broad and flexible systems for substrate utilization, which have been used successfully to produce a range of industrial compounds. In particular, Clostridium acetobutylicum has been used to produce butanol on an industrial sca...
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/PMC4207355/ https://www.ncbi.nlm.nih.gov/pubmed/25379054 http://dx.doi.org/10.1186/s13068-014-0144-4 |
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author | Dash, Satyakam Mueller, Thomas J Venkataramanan, Keerthi P Papoutsakis, Eleftherios T Maranas, Costas D |
author_facet | Dash, Satyakam Mueller, Thomas J Venkataramanan, Keerthi P Papoutsakis, Eleftherios T Maranas, Costas D |
author_sort | Dash, Satyakam |
collection | PubMed |
description | BACKGROUND: Clostridia are anaerobic Gram-positive Firmicutes containing broad and flexible systems for substrate utilization, which have been used successfully to produce a range of industrial compounds. In particular, Clostridium acetobutylicum has been used to produce butanol on an industrial scale through acetone-butanol-ethanol (ABE) fermentation. A genome-scale metabolic (GSM) model is a powerful tool for understanding the metabolic capacities of an organism and developing metabolic engineering strategies for strain development. The integration of stress-related specific transcriptomics information with the GSM model provides opportunities for elucidating the focal points of regulation. RESULTS: We describe here the construction and validation of a GSM model for C. acetobutylicum ATCC 824, iCac802. iCac802 spans 802 genes and includes 1,137 metabolites and 1,462 reactions, along with gene-protein-reaction associations. Both (13)C-MFA and gene deletion data in the ABE fermentation pathway were used to test the predicted flux ranges allowed by the model. We also describe the CoreReg method, introduced in this paper, to integrate transcriptomic data and identify core sets of reactions that, when their flux was selectively restricted, reproduced flux and biomass-formation ranges seen under all regulatory constraints. CoreReg was used in response to butanol and butyrate stress to tighten bounds for 50 reactions within the iCac802 model. These bounds affected the flux of tens of reactions in core metabolism. The model, incorporating the regulatory restrictions from CoreReg under chemical stress, exhibited an approximate 70% reduction in biomass yield for most stress conditions. CONCLUSIONS: The regulation placed on the model for the two stresses using CoreReg identified differences in the respective responses, including distinct core sets and the restriction of biomass production similar to experimental observations. Given the core sets predicted by the CoreReg method, remedial actions can be taken to counteract the effect of stress on metabolism. For less well-known systems, plausible regulatory loops can be suggested around the affected metabolic reactions, and the hypotheses can be tested experimentally. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13068-014-0144-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4207355 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42073552014-11-06 Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model Dash, Satyakam Mueller, Thomas J Venkataramanan, Keerthi P Papoutsakis, Eleftherios T Maranas, Costas D Biotechnol Biofuels Research Article BACKGROUND: Clostridia are anaerobic Gram-positive Firmicutes containing broad and flexible systems for substrate utilization, which have been used successfully to produce a range of industrial compounds. In particular, Clostridium acetobutylicum has been used to produce butanol on an industrial scale through acetone-butanol-ethanol (ABE) fermentation. A genome-scale metabolic (GSM) model is a powerful tool for understanding the metabolic capacities of an organism and developing metabolic engineering strategies for strain development. The integration of stress-related specific transcriptomics information with the GSM model provides opportunities for elucidating the focal points of regulation. RESULTS: We describe here the construction and validation of a GSM model for C. acetobutylicum ATCC 824, iCac802. iCac802 spans 802 genes and includes 1,137 metabolites and 1,462 reactions, along with gene-protein-reaction associations. Both (13)C-MFA and gene deletion data in the ABE fermentation pathway were used to test the predicted flux ranges allowed by the model. We also describe the CoreReg method, introduced in this paper, to integrate transcriptomic data and identify core sets of reactions that, when their flux was selectively restricted, reproduced flux and biomass-formation ranges seen under all regulatory constraints. CoreReg was used in response to butanol and butyrate stress to tighten bounds for 50 reactions within the iCac802 model. These bounds affected the flux of tens of reactions in core metabolism. The model, incorporating the regulatory restrictions from CoreReg under chemical stress, exhibited an approximate 70% reduction in biomass yield for most stress conditions. CONCLUSIONS: The regulation placed on the model for the two stresses using CoreReg identified differences in the respective responses, including distinct core sets and the restriction of biomass production similar to experimental observations. Given the core sets predicted by the CoreReg method, remedial actions can be taken to counteract the effect of stress on metabolism. For less well-known systems, plausible regulatory loops can be suggested around the affected metabolic reactions, and the hypotheses can be tested experimentally. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13068-014-0144-4) contains supplementary material, which is available to authorized users. BioMed Central 2014-10-14 /pmc/articles/PMC4207355/ /pubmed/25379054 http://dx.doi.org/10.1186/s13068-014-0144-4 Text en © Dash 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 Dash, Satyakam Mueller, Thomas J Venkataramanan, Keerthi P Papoutsakis, Eleftherios T Maranas, Costas D Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model |
title | Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model |
title_full | Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model |
title_fullStr | Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model |
title_full_unstemmed | Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model |
title_short | Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model |
title_sort | capturing the response of clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4207355/ https://www.ncbi.nlm.nih.gov/pubmed/25379054 http://dx.doi.org/10.1186/s13068-014-0144-4 |
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