Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism.
An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2015-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0139507 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850162265819447296 |
|---|---|
| author | Ahmad A Mannan Yoshihiro Toya Kazuyuki Shimizu Johnjoe McFadden Andrzej M Kierzek Andrea Rocco |
| author_facet | Ahmad A Mannan Yoshihiro Toya Kazuyuki Shimizu Johnjoe McFadden Andrzej M Kierzek Andrea Rocco |
| author_sort | Ahmad A Mannan |
| collection | DOAJ |
| description | An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-'omics' steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population. |
| format | Article |
| id | doaj-art-14335af2d81848c3b34e36cd4ec0b69d |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-14335af2d81848c3b34e36cd4ec0b69d2025-08-20T02:22:37ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011010e013950710.1371/journal.pone.0139507Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism.Ahmad A MannanYoshihiro ToyaKazuyuki ShimizuJohnjoe McFaddenAndrzej M KierzekAndrea RoccoAn understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-'omics' steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population.https://doi.org/10.1371/journal.pone.0139507 |
| spellingShingle | Ahmad A Mannan Yoshihiro Toya Kazuyuki Shimizu Johnjoe McFadden Andrzej M Kierzek Andrea Rocco Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism. PLoS ONE |
| title | Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism. |
| title_full | Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism. |
| title_fullStr | Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism. |
| title_full_unstemmed | Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism. |
| title_short | Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism. |
| title_sort | integrating kinetic model of e coli with genome scale metabolic fluxes overcomes its open system problem and reveals bistability in central metabolism |
| url | https://doi.org/10.1371/journal.pone.0139507 |
| work_keys_str_mv | AT ahmadamannan integratingkineticmodelofecoliwithgenomescalemetabolicfluxesovercomesitsopensystemproblemandrevealsbistabilityincentralmetabolism AT yoshihirotoya integratingkineticmodelofecoliwithgenomescalemetabolicfluxesovercomesitsopensystemproblemandrevealsbistabilityincentralmetabolism AT kazuyukishimizu integratingkineticmodelofecoliwithgenomescalemetabolicfluxesovercomesitsopensystemproblemandrevealsbistabilityincentralmetabolism AT johnjoemcfadden integratingkineticmodelofecoliwithgenomescalemetabolicfluxesovercomesitsopensystemproblemandrevealsbistabilityincentralmetabolism AT andrzejmkierzek integratingkineticmodelofecoliwithgenomescalemetabolicfluxesovercomesitsopensystemproblemandrevealsbistabilityincentralmetabolism AT andrearocco integratingkineticmodelofecoliwithgenomescalemetabolicfluxesovercomesitsopensystemproblemandrevealsbistabilityincentralmetabolism |