Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Dash, Satyakam, Mueller, Thomas J, Venkataramanan, Keerthi P, Papoutsakis, Eleftherios T, Maranas, Costas D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
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
_version_ 1782340953481150464
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
work_keys_str_mv AT dashsatyakam capturingtheresponseofclostridiumacetobutylicumtochemicalstressorsusingaregulatedgenomescalemetabolicmodel
AT muellerthomasj capturingtheresponseofclostridiumacetobutylicumtochemicalstressorsusingaregulatedgenomescalemetabolicmodel
AT venkataramanankeerthip capturingtheresponseofclostridiumacetobutylicumtochemicalstressorsusingaregulatedgenomescalemetabolicmodel
AT papoutsakiseleftheriost capturingtheresponseofclostridiumacetobutylicumtochemicalstressorsusingaregulatedgenomescalemetabolicmodel
AT maranascostasd capturingtheresponseofclostridiumacetobutylicumtochemicalstressorsusingaregulatedgenomescalemetabolicmodel