Dynamic models of metabolism: Review of the cybernetic approach

Abstract

in Wiley Online Library (wileyonlinelibrary.com).The cybernetic approach to metabolic modeling tracing its progress from its early beginnings to its current state with regard to its relationship to other modeling approaches, applications to bioprocess modeling, metabolic engineering, and future prospects are described. The framework is shown to handle large metabolic networks in making dynamic predictions from limited data with looming prospects of extending to genome scale networks. V V C 2012 American Institute of Chemical Engineers AIChE J, 58: 986-997, 2012 Keywords: dynamic metabolic models, the cybernetic approach, metabolic engineering, elementary modes, cellular regulation where W j denotes the species whose concentration is w j . Eq. 1 represents n r reactions of metabolism which subsume both transport and chemical reaction with a ij the stoichiometric coefficient which, as per the usual convention, is positive, negative, or zero, in respective accordance with W j being a product, reactant, or nonparticipant in the ith reaction. The rate associated with the ith reaction is denoted by r i . As each reaction is catalyzed by a specific enzyme, the level of this enzyme and its activity would determine the rate of the reaction besides the concentrations (as dictated by the kinetics) of species participating in the reaction.Predictions (a) based on measurements of glucose alone leads to good predictions of biomass, formate, ethanol but not of lactate and succinate. When measurements of glucose and lactate are both used for model identification (b), all predictions (shown in continuous lines) are considerably improved. Figure 13. Cybernetic model simulations of Namjoshi et al. 52 alongside with experimental data of Europa et al., 50 showing multiple steady states in continuous cultures of hybridoma cells.

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review

“…In many cases, including Reed et al, those patterns are simulated by designing the kinetics of rj's as complex forms and/or additionally considering inhibition terms, but the incorporation of cellular regulatory actions would facilitate model development in a more systematic way. In this regard, while not applied yet, the cybernetic approach developed by Ramkrishna and coworkers [43] is well suited for simulating the community dynamics based on functional gene-centric approach. The cybernetic approach hypothesizes that cellular metabolism is optimally regulated to achieve a certain objective function that is related to actual rates rather than yields.…”

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“…Furthermore, it is important to develop mathematical tools that can effectively incorporate omics-based metabolic pathway information into kinetic functions, which can be used directly in kinetic growth models. The cybernetic approach developed by Song et al sheds some light on future research in this direction, and a review of this approach is given by [81].…”

Complex Nonlinear Behavior in Metabolic Processes: Global Bifurcation Analysis of Escherichia coli Growth on Multiple Substrates

“…For the nonlinear analysis of metabolic systems, therefore, it is essential to employ metabolic models that are able to appropriately account for dynamic regulation. Various modeling ideas have been developed for the analysis of metabolic systems, including metabolic pathway analysis [3,4], constraint-based approaches [5,6], kinetic models [7] and the cybernetic approaches [8]. In the discussion of the conceptual distinctions and commonalities among different modeling frameworks, Song et al [9] highlighted the essential need for dynamic modeling frameworks in a wide range of applications, such as the study of complex nonlinear behavior of metabolic processes.…”

“…Alternatively, the cybernetic approach [8] provides a rational description of regulation based on optimal control theory. The cybernetic description of metabolic regulation is based on the assumption that a cell is frugal in using its resources and optimally allocates them among a subset of enzymes to achieve a certain metabolic objective (such as the carbon uptake rate or growth rate).…”