Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism

Abstract Background Several computational methods have been developed that integrate transcriptomics data with genome-scale metabolic reconstructions to increase accuracy of inferences of intracellular metabolic flux distributions. Even though existing methods use transcript abundances as a proxy fo...

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Autores principales:	Neeraj Sinha, Evert M. van Schothorst, Guido J. E. J. Hooiveld, Jaap Keijer, Vitor A. P. Martins dos Santos, Maria Suarez-Diez
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	E-Flux Gene expression integration Transcriptomics Constraint-based models Proportionality constant Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/6f4431891a6e4a50b5861b087c64c3c3
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spelling	oai:doaj.org-article:6f4431891a6e4a50b5861b087c64c3c32021-12-05T12:08:43ZExploring the associations between transcript levels and fluxes in constraint-based models of metabolism10.1186/s12859-021-04488-81471-2105https://doaj.org/article/6f4431891a6e4a50b5861b087c64c3c32021-11-01T00:00:00Zhttps://doi.org/10.1186/s12859-021-04488-8https://doaj.org/toc/1471-2105Abstract Background Several computational methods have been developed that integrate transcriptomics data with genome-scale metabolic reconstructions to increase accuracy of inferences of intracellular metabolic flux distributions. Even though existing methods use transcript abundances as a proxy for enzyme activity, each method uses a different hypothesis and assumptions. Most methods implicitly assume a proportionality between transcript levels and flux through the corresponding function, although these proportionality constant(s) are often not explicitly mentioned nor discussed in any of the published methods. E-Flux is one such method and, in this algorithm, flux bounds are related to expression data, so that reactions associated with highly expressed genes are allowed to carry higher flux values. Results Here, we extended E-Flux and systematically evaluated the impact of an assumed proportionality constant on model predictions. We used data from published experiments with Escherichia coli and Saccharomyces cerevisiae and we compared the predictions of the algorithm to measured extracellular and intracellular fluxes. Conclusion We showed that detailed modelling using a proportionality constant can greatly impact the outcome of the analysis. This increases accuracy and allows for extraction of better physiological information.Neeraj SinhaEvert M. van SchothorstGuido J. E. J. HooiveldJaap KeijerVitor A. P. Martins dos SantosMaria Suarez-DiezBMCarticleE-FluxGene expression integrationTranscriptomicsConstraint-based modelsProportionality constantComputer applications to medicine. Medical informaticsR858-859.7Biology (General)QH301-705.5ENBMC Bioinformatics, Vol 22, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	E-Flux Gene expression integration Transcriptomics Constraint-based models Proportionality constant Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5
spellingShingle	E-Flux Gene expression integration Transcriptomics Constraint-based models Proportionality constant Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5 Neeraj Sinha Evert M. van Schothorst Guido J. E. J. Hooiveld Jaap Keijer Vitor A. P. Martins dos Santos Maria Suarez-Diez Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism
description	Abstract Background Several computational methods have been developed that integrate transcriptomics data with genome-scale metabolic reconstructions to increase accuracy of inferences of intracellular metabolic flux distributions. Even though existing methods use transcript abundances as a proxy for enzyme activity, each method uses a different hypothesis and assumptions. Most methods implicitly assume a proportionality between transcript levels and flux through the corresponding function, although these proportionality constant(s) are often not explicitly mentioned nor discussed in any of the published methods. E-Flux is one such method and, in this algorithm, flux bounds are related to expression data, so that reactions associated with highly expressed genes are allowed to carry higher flux values. Results Here, we extended E-Flux and systematically evaluated the impact of an assumed proportionality constant on model predictions. We used data from published experiments with Escherichia coli and Saccharomyces cerevisiae and we compared the predictions of the algorithm to measured extracellular and intracellular fluxes. Conclusion We showed that detailed modelling using a proportionality constant can greatly impact the outcome of the analysis. This increases accuracy and allows for extraction of better physiological information.
format	article
author	Neeraj Sinha Evert M. van Schothorst Guido J. E. J. Hooiveld Jaap Keijer Vitor A. P. Martins dos Santos Maria Suarez-Diez
author_facet	Neeraj Sinha Evert M. van Schothorst Guido J. E. J. Hooiveld Jaap Keijer Vitor A. P. Martins dos Santos Maria Suarez-Diez
author_sort	Neeraj Sinha
title	Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism
title_short	Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism
title_full	Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism
title_fullStr	Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism
title_full_unstemmed	Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism
title_sort	exploring the associations between transcript levels and fluxes in constraint-based models of metabolism
publisher	BMC
publishDate	2021
url	https://doaj.org/article/6f4431891a6e4a50b5861b087c64c3c3
work_keys_str_mv	AT neerajsinha exploringtheassociationsbetweentranscriptlevelsandfluxesinconstraintbasedmodelsofmetabolism AT evertmvanschothorst exploringtheassociationsbetweentranscriptlevelsandfluxesinconstraintbasedmodelsofmetabolism AT guidojejhooiveld exploringtheassociationsbetweentranscriptlevelsandfluxesinconstraintbasedmodelsofmetabolism AT jaapkeijer exploringtheassociationsbetweentranscriptlevelsandfluxesinconstraintbasedmodelsofmetabolism AT vitorapmartinsdossantos exploringtheassociationsbetweentranscriptlevelsandfluxesinconstraintbasedmodelsofmetabolism AT mariasuarezdiez exploringtheassociationsbetweentranscriptlevelsandfluxesinconstraintbasedmodelsofmetabolism
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Exploring the associations between transcript levels and fluxes in constraint-based models of metabolism

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