A study of a diauxic growth experiment using an expanded dynamic flux balance framework.

Flux balance analysis (FBA) remains one of the most used methods for modeling the entirety of cellular metabolism, and a range of applications and extensions based on the FBA framework have been generated. Dynamic flux balance analysis (dFBA), the expansion of FBA into the time domain, still has iss...

Full description

Bibliographic Details
Main Authors: Emil Karlsen, Marianne Gylseth, Christian Schulz, Eivind Almaas
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0280077
_version_ 1797866058368942080
author Emil Karlsen
Marianne Gylseth
Christian Schulz
Eivind Almaas
author_facet Emil Karlsen
Marianne Gylseth
Christian Schulz
Eivind Almaas
author_sort Emil Karlsen
collection DOAJ
description Flux balance analysis (FBA) remains one of the most used methods for modeling the entirety of cellular metabolism, and a range of applications and extensions based on the FBA framework have been generated. Dynamic flux balance analysis (dFBA), the expansion of FBA into the time domain, still has issues regarding accessibility limiting its widespread adoption and application, such as a lack of a consistently rigid formalism and tools that can be applied without expert knowledge. Recent work has combined dFBA with enzyme-constrained flux balance analysis (decFBA), which has been shown to greatly improve accuracy in the comparison of computational simulations and experimental data, but such approaches generally do not take into account the fact that altering the enzyme composition of a cell is not an instantaneous process. Here, we have developed a decFBA method that explicitly takes enzyme change constraints (ecc) into account, decFBAecc. The resulting software is a simple yet flexible framework for using genome-scale metabolic modeling for simulations in the time domain that has full interoperability with the COBRA Toolbox 3.0. To assess the quality of the computational predictions of decFBAecc, we conducted a diauxic growth fermentation experiment with Escherichia coli BW25113 in glucose minimal M9 medium. The comparison of experimental data with dFBA, decFBA and decFBAecc predictions demonstrates how systematic analyses within a fixed constraint-based framework can aid the study of model parameters. Finally, in explaining experimentally observed phenotypes, our computational analysis demonstrates the importance of non-linear dependence of exchange fluxes on medium metabolite concentrations and the non-instantaneous change in enzyme composition, effects of which have not previously been accounted for in constraint-based analysis.
first_indexed 2024-04-09T23:17:58Z
format Article
id doaj.art-dccd396aac494d56997d46c1a08cf209
institution Directory Open Access Journal
issn 1932-6203
language English
last_indexed 2024-04-09T23:17:58Z
publishDate 2023-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj.art-dccd396aac494d56997d46c1a08cf2092023-03-22T05:31:25ZengPublic Library of Science (PLoS)PLoS ONE1932-62032023-01-01181e028007710.1371/journal.pone.0280077A study of a diauxic growth experiment using an expanded dynamic flux balance framework.Emil KarlsenMarianne GylsethChristian SchulzEivind AlmaasFlux balance analysis (FBA) remains one of the most used methods for modeling the entirety of cellular metabolism, and a range of applications and extensions based on the FBA framework have been generated. Dynamic flux balance analysis (dFBA), the expansion of FBA into the time domain, still has issues regarding accessibility limiting its widespread adoption and application, such as a lack of a consistently rigid formalism and tools that can be applied without expert knowledge. Recent work has combined dFBA with enzyme-constrained flux balance analysis (decFBA), which has been shown to greatly improve accuracy in the comparison of computational simulations and experimental data, but such approaches generally do not take into account the fact that altering the enzyme composition of a cell is not an instantaneous process. Here, we have developed a decFBA method that explicitly takes enzyme change constraints (ecc) into account, decFBAecc. The resulting software is a simple yet flexible framework for using genome-scale metabolic modeling for simulations in the time domain that has full interoperability with the COBRA Toolbox 3.0. To assess the quality of the computational predictions of decFBAecc, we conducted a diauxic growth fermentation experiment with Escherichia coli BW25113 in glucose minimal M9 medium. The comparison of experimental data with dFBA, decFBA and decFBAecc predictions demonstrates how systematic analyses within a fixed constraint-based framework can aid the study of model parameters. Finally, in explaining experimentally observed phenotypes, our computational analysis demonstrates the importance of non-linear dependence of exchange fluxes on medium metabolite concentrations and the non-instantaneous change in enzyme composition, effects of which have not previously been accounted for in constraint-based analysis.https://doi.org/10.1371/journal.pone.0280077
spellingShingle Emil Karlsen
Marianne Gylseth
Christian Schulz
Eivind Almaas
A study of a diauxic growth experiment using an expanded dynamic flux balance framework.
PLoS ONE
title A study of a diauxic growth experiment using an expanded dynamic flux balance framework.
title_full A study of a diauxic growth experiment using an expanded dynamic flux balance framework.
title_fullStr A study of a diauxic growth experiment using an expanded dynamic flux balance framework.
title_full_unstemmed A study of a diauxic growth experiment using an expanded dynamic flux balance framework.
title_short A study of a diauxic growth experiment using an expanded dynamic flux balance framework.
title_sort study of a diauxic growth experiment using an expanded dynamic flux balance framework
url https://doi.org/10.1371/journal.pone.0280077
work_keys_str_mv AT emilkarlsen astudyofadiauxicgrowthexperimentusinganexpandeddynamicfluxbalanceframework
AT mariannegylseth astudyofadiauxicgrowthexperimentusinganexpandeddynamicfluxbalanceframework
AT christianschulz astudyofadiauxicgrowthexperimentusinganexpandeddynamicfluxbalanceframework
AT eivindalmaas astudyofadiauxicgrowthexperimentusinganexpandeddynamicfluxbalanceframework
AT emilkarlsen studyofadiauxicgrowthexperimentusinganexpandeddynamicfluxbalanceframework
AT mariannegylseth studyofadiauxicgrowthexperimentusinganexpandeddynamicfluxbalanceframework
AT christianschulz studyofadiauxicgrowthexperimentusinganexpandeddynamicfluxbalanceframework
AT eivindalmaas studyofadiauxicgrowthexperimentusinganexpandeddynamicfluxbalanceframework