Model reduction of genome-scale metabolic models as a basis for targeted kinetic models.
DBTL cycle
Metabolic engineering
Model optimisation
Model reduction
Model-driven design
Synthetic biology
Journal
Metabolic engineering
ISSN: 1096-7184
Titre abrégé: Metab Eng
Pays: Belgium
ID NLM: 9815657
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
received:
26
08
2020
revised:
05
01
2021
accepted:
15
01
2021
pubmed:
25
1
2021
medline:
25
11
2021
entrez:
24
1
2021
Statut:
ppublish
Résumé
Constraint-based, genome-scale metabolic models are an essential tool to guide metabolic engineering. However, they lack the detail and time dimension that kinetic models with enzyme dynamics offer. Model reduction can be used to bridge the gap between the two methods and allow for the integration of kinetic models into the Design-Built-Test-Learn cycle. Here we show that these reduced size models can be representative of the dynamics of the original model and demonstrate the automated generation and parameterisation of such models. Using these minimal models of metabolism could allow for further exploration of dynamic responses in metabolic networks.
Identifiants
pubmed: 33486094
pii: S1096-7176(21)00016-1
doi: 10.1016/j.ymben.2021.01.008
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
74-84Informations de copyright
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.