Inference of dynamic macroscopic models of cell metabolism based on elementary flux modes analysis

Abbate, Thomas; Sousa, Sofia Fernandes de; Dewasme, Laurent; Bastin, Georges; Wouwer, Alain Vande

doi:10.1016/j.bej.2019.107325

Cited by 10 publications

(5 citation statements)

References 26 publications

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“…[77,78] select reduced sets of EFMs via a geometrical reduction (excluding EFMs with a cosine-similarity algorithm) followed by a multi-objective genetic algorithm that minimizes the prediction error and the size of the EFMs subset. A linear optimization problem has been formulated in [79] for selecting the best subset of EFMs based on a relaxation criterion. The methodology is extended in [80] and includes a more efficient selection procedure for the minimal subset of EFMs.…”

Section: Model Reduction To Macroscopic Scalementioning

confidence: 99%

How to Tackle Underdeterminacy in Metabolic Flux Analysis? A Tutorial and Critical Review

Bogaerts

Wouwer

2021

Processes

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Metabolic flux analysis is often (not to say almost always) faced with system underdeterminacy. Indeed, the linear algebraic system formed by the steady-state mass balance equations around the intracellular metabolites and the equality constraints related to the measurements of extracellular fluxes do not define a unique solution for the distribution of intracellular fluxes, but instead a set of solutions belonging to a convex polytope. Various methods have been proposed to tackle this underdeterminacy, including flux pathway analysis, flux balance analysis, flux variability analysis and sampling. These approaches are reviewed in this article and a toy example supports the discussion with illustrative numerical results.

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Section: Model Reduction To Macroscopic Scalementioning

confidence: 99%

How to Tackle Underdeterminacy in Metabolic Flux Analysis? A Tutorial and Critical Review

Bogaerts

Wouwer

2021

Processes

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“…In connection with this, Hebing et al [22] used an EFM reduction procedure based on a geometrical collinearity criterion. More recently, several procedures of EFM reduction have been developed by our research group, i.e., Abbate [23] selected the best EFM candidates based on the formulation of a linear optimization problem and Maton [24] developed a reduction methodology based on a combination of several criteria based on collinearity and a series of constrained least-square problems.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Dynamic Models of Bioprocesses Based on Elementary Flux Modes and Multilayer Perceptrons

2022

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The derivation of minimal bioreaction models is of primary importance to develop monitoring and control strategies of cell/microorganism culture production. These minimal bioreaction models can be obtained based on the selection of a basis of elementary flux modes (EFMs) using an algorithm starting from a relatively large set of EFMs and progressively reducing their numbers based on geometric and least-squares residual criteria. The reaction rates associated with the selected EFMs usually have complex features resulting from the combination of different activation, inhibition and saturation effects from several culture species. Multilayer perceptrons (MLPs) are used in order to undertake the representation of these rates, resulting in a hybrid dynamic model combining the mass-balance equations provided by the EFMs to the rate equations described by the MLPs. To further reduce the number of kinetic parameters of the model, pruning algorithms for the MLPs are also considered. The whole procedure ends up with reduced-order macroscopic models that show promising prediction results, as illustrated with data of perfusion cultures of hybridoma cell line HB-58.

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“…Recently, [21,27] have applied column generation techniques to determine subsets of elementary flux modes in metabolic networks and [28] introduces the poly-pathway model approach to account for the metabolic behavior of multiple experimental conditions. Recently, our research group has developed two procedures, e.g., [29] picks the best EFMs candidates based on a linear optimization problem, and [30] uses a two-step reduction based on cosine-linearity and optimization, to identify and retain the most informative EFMs to develop macroscopic models.…”

Section: Introductionmentioning

confidence: 99%

A systematic elementary flux mode selection procedure for deriving macroscopic bioreaction models from metabolic networks

Maton

Bogaerts

Wouwer

2022

Journal of Process Control

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Inference of dynamic macroscopic models of cell metabolism based on elementary flux modes analysis

Cited by 10 publications

References 26 publications

How to Tackle Underdeterminacy in Metabolic Flux Analysis? A Tutorial and Critical Review

How to Tackle Underdeterminacy in Metabolic Flux Analysis? A Tutorial and Critical Review

Hybrid Dynamic Models of Bioprocesses Based on Elementary Flux Modes and Multilayer Perceptrons

A systematic elementary flux mode selection procedure for deriving macroscopic bioreaction models from metabolic networks

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