Modeling the metabolic dynamics at the genome-scale by optimized yield analysis
Journal article, 2023

The hybrid cybernetic model (HCM) approach is a dynamic modeling framework that integrates enzyme synthesis and activity regulation. It has been widely applied in bioreaction engineering, particularly in the simulation of microbial growth in different mixtures of carbon sources. In a HCM, the metabolic network is decomposed into elementary flux modes (EFMs), whereby the network can be reduced into a few pathways by yield analysis. However, applying the HCM approach on conventional genome-scale metabolic models (GEMs) is still a challenge due to the high computational demands. Here, we present a HCM strategy that introduced an optimized yield analysis algorithm (opt-yield-FBA) to simulate metabolic dynamics at the genome-scale without the need for EFMs calculation. The opt-yield-FBA is a flux-balance analysis (FBA) based method that can calculate optimal yield solutions and yield space for GEM. With the opt-yield-FBA algorithm, the HCM strategy can be applied to get the yield spaces and avoid the computational burden of EFMs, and it can therefore be applied for developing dynamic models for genome-scale metabolic networks. Here, we illustrate the strategy by applying the concept to simulate the dynamics of microbial communities.

Genome-scale metabolic model

Cybernetic modeling

Elementary flux mode

Yield space

Flux-balance analysis

Optimize yield

Author

Hao Luo

Chalmers, Life Sciences, Systems and Synthetic Biology

Peishun Li

Chalmers, Life Sciences, Systems and Synthetic Biology

Boyang Ji

BioInnovation Institute

Chalmers, Life Sciences, Systems and Synthetic Biology

Jens B Nielsen

BioInnovation Institute

Chalmers, Life Sciences, Systems and Synthetic Biology

Metabolic Engineering

1096-7176 (ISSN) 1096-7184 (eISSN)

Vol. 75 119-130

Subject Categories

Bioinformatics (Computational Biology)

Computer Science

Computer Systems

DOI

10.1016/j.ymben.2022.12.001

PubMed

36503050

More information

Latest update

1/2/2023 2