Modeling the contribution of allosteric regulation for flux control in the central carbon metabolism of E. coli
Modeling metabolism is fundamental for cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM has not been fully unraveled. Recent studies have shown that CCM is mo...
Ausführliche Beschreibung
Autor*in: |
Daniel eMachado [verfasserIn] Markus J Herrgard [verfasserIn] Isabel eRocha [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015 |
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Übergeordnetes Werk: |
In: Frontiers in Bioengineering and Biotechnology - Frontiers Media S.A., 2014, 3(2015) |
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Übergeordnetes Werk: |
volume:3 ; year:2015 |
Links: |
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DOI / URN: |
10.3389/fbioe.2015.00154 |
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Katalog-ID: |
DOAJ066269679 |
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10.3389/fbioe.2015.00154 doi (DE-627)DOAJ066269679 (DE-599)DOAJ73fd36c071c94751b085846820264012 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Daniel eMachado verfasserin aut Modeling the contribution of allosteric regulation for flux control in the central carbon metabolism of E. coli 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Modeling metabolism is fundamental for cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM has not been fully unraveled. Recent studies have shown that CCM is mostly regulated at post-transcriptional levels. To better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand a CCM model of E. coli with allosteric interactions. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite and flux levels. We observe cases where allosteric interactions have a major contribution to the metabolic adjustments. Also, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions accounting for allosteric interactions. This method is used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental flux data. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation. Allosteric Regulation Escherichia coli Metabolism Systems Biology Constraint-based modeling Biotechnology Markus J Herrgard verfasserin aut Isabel eRocha verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 3(2015) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:3 year:2015 https://doi.org/10.3389/fbioe.2015.00154 kostenfrei https://doaj.org/article/73fd36c071c94751b085846820264012 kostenfrei http://journal.frontiersin.org/Journal/10.3389/fbioe.2015.00154/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2015 |
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10.3389/fbioe.2015.00154 doi (DE-627)DOAJ066269679 (DE-599)DOAJ73fd36c071c94751b085846820264012 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Daniel eMachado verfasserin aut Modeling the contribution of allosteric regulation for flux control in the central carbon metabolism of E. coli 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Modeling metabolism is fundamental for cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM has not been fully unraveled. Recent studies have shown that CCM is mostly regulated at post-transcriptional levels. To better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand a CCM model of E. coli with allosteric interactions. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite and flux levels. We observe cases where allosteric interactions have a major contribution to the metabolic adjustments. Also, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions accounting for allosteric interactions. This method is used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental flux data. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation. Allosteric Regulation Escherichia coli Metabolism Systems Biology Constraint-based modeling Biotechnology Markus J Herrgard verfasserin aut Isabel eRocha verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 3(2015) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:3 year:2015 https://doi.org/10.3389/fbioe.2015.00154 kostenfrei https://doaj.org/article/73fd36c071c94751b085846820264012 kostenfrei http://journal.frontiersin.org/Journal/10.3389/fbioe.2015.00154/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2015 |
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10.3389/fbioe.2015.00154 doi (DE-627)DOAJ066269679 (DE-599)DOAJ73fd36c071c94751b085846820264012 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Daniel eMachado verfasserin aut Modeling the contribution of allosteric regulation for flux control in the central carbon metabolism of E. coli 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Modeling metabolism is fundamental for cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM has not been fully unraveled. Recent studies have shown that CCM is mostly regulated at post-transcriptional levels. To better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand a CCM model of E. coli with allosteric interactions. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite and flux levels. We observe cases where allosteric interactions have a major contribution to the metabolic adjustments. Also, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions accounting for allosteric interactions. This method is used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental flux data. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation. Allosteric Regulation Escherichia coli Metabolism Systems Biology Constraint-based modeling Biotechnology Markus J Herrgard verfasserin aut Isabel eRocha verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 3(2015) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:3 year:2015 https://doi.org/10.3389/fbioe.2015.00154 kostenfrei https://doaj.org/article/73fd36c071c94751b085846820264012 kostenfrei http://journal.frontiersin.org/Journal/10.3389/fbioe.2015.00154/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2015 |
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10.3389/fbioe.2015.00154 doi (DE-627)DOAJ066269679 (DE-599)DOAJ73fd36c071c94751b085846820264012 DE-627 ger DE-627 rakwb eng TP248.13-248.65 Daniel eMachado verfasserin aut Modeling the contribution of allosteric regulation for flux control in the central carbon metabolism of E. coli 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Modeling metabolism is fundamental for cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM has not been fully unraveled. Recent studies have shown that CCM is mostly regulated at post-transcriptional levels. To better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand a CCM model of E. coli with allosteric interactions. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite and flux levels. We observe cases where allosteric interactions have a major contribution to the metabolic adjustments. Also, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions accounting for allosteric interactions. This method is used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental flux data. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation. Allosteric Regulation Escherichia coli Metabolism Systems Biology Constraint-based modeling Biotechnology Markus J Herrgard verfasserin aut Isabel eRocha verfasserin aut In Frontiers in Bioengineering and Biotechnology Frontiers Media S.A., 2014 3(2015) (DE-627)74950403X (DE-600)2719493-0 22964185 nnns volume:3 year:2015 https://doi.org/10.3389/fbioe.2015.00154 kostenfrei https://doaj.org/article/73fd36c071c94751b085846820264012 kostenfrei http://journal.frontiersin.org/Journal/10.3389/fbioe.2015.00154/full kostenfrei https://doaj.org/toc/2296-4185 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2015 |
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Modeling the contribution of allosteric regulation for flux control in the central carbon metabolism of E. coli |
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Modeling metabolism is fundamental for cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM has not been fully unraveled. Recent studies have shown that CCM is mostly regulated at post-transcriptional levels. To better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand a CCM model of E. coli with allosteric interactions. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite and flux levels. We observe cases where allosteric interactions have a major contribution to the metabolic adjustments. Also, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions accounting for allosteric interactions. This method is used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental flux data. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation. |
abstractGer |
Modeling metabolism is fundamental for cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM has not been fully unraveled. Recent studies have shown that CCM is mostly regulated at post-transcriptional levels. To better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand a CCM model of E. coli with allosteric interactions. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite and flux levels. We observe cases where allosteric interactions have a major contribution to the metabolic adjustments. Also, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions accounting for allosteric interactions. This method is used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental flux data. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation. |
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Modeling metabolism is fundamental for cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM has not been fully unraveled. Recent studies have shown that CCM is mostly regulated at post-transcriptional levels. To better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand a CCM model of E. coli with allosteric interactions. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite and flux levels. We observe cases where allosteric interactions have a major contribution to the metabolic adjustments. Also, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions accounting for allosteric interactions. This method is used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental flux data. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation. |
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|
score |
7.403063 |