Dynamic estimations of metabolic fluxes with constraint-based models and possibility theory

Abstract

ElsevierLlaneras Estrada, F.; Sala, A.; Picó Marco, JA. (2012). Dynamic estimations of metabolic fluxes with constraint-based models and possibility theory. Journal of Process Control. 22(10):1946Control. 22(10): -1955Control. 22(10): . doi:10.1016Control. 22(10): /j.jprocont.2012 it is easy to take extracellular dynamics into account. This work explores the benefits of using possibility theory to get these dynamic predictions. It will be shown that the possibilistic methods (a) provide rich estimates for time-varying fluxes and metabolite concentrations, (b) account for uncertainty and data scarcity, and (c) give predictions relaxing the optimality assumption of FBA. On the other hand, these methods could serve as basis for monitoring and fault detection systems in industrial bioprocesses. Highlights-Possibility theory is used to get dynamic estimates of fluxes and metabolites. -The approach handles measurements errors, uncertainty, and data scarcity. -Predictions can be obtained relaxing the assumption of cells evolved optimality. KeywordsConstraint satisfaction problems, possibility theory, constraint-based model, metabolic flux analysis, flux balance analysis.

Metabolic Network Modelling of Chinese Hamster Ovary (CHO) Culture Bioreactors Operated as Microbial Cell Factories

“…These methods originally provide static insights into metabolic routes, what allows to study cell cultures at a state of particular interest. Even though several extensions were proposed to include extracellular dynamics in the framework of MFA and FBA, 81 precise mathematical representation of reaction kinetics and regulation mechanisms remains a challenge. See the review for a concise overview of metabolic models.…”

Adaptive flux variability analysis of HEK cell cultures

“…In addition to traditional MPA methods, extreme admissible values of individual internal fluxes can be determined through computation of flux variability analysis (FVA) which consists in solving a simple linear programming problem ( Leighty and Antoniewicz, 2011;Llaneras et al, 2012;Vercammen et al, 2014 ). While the usual analysis provides an insight into the cell activity under specific growth conditions, in the course of the exponential phase or the stationary phase for example, several studies provide a dynamic overview over the whole experiment using FBA ( Mahadevan et al, 2002 ), MPA ( Fernandes et al, 2016;Zamorano et al, 2013 ) or FVA ( Richelle et al, 2016;Bogaerts et al, 2017 ).…”

Dynamic metabolic flux analysis using a convex analysis approach: Application to hybridoma cell cultures in perfusion

“…When the environmental conditions of a culture change, dynamics should be considered to investigate cellular metabolism. To this end, the development of dynamic metabolic flux analysis (DMFA) techniques has been addressed (Leighty and Antoniewicz, 2011;Lequeux et al, 2010;Llaneras et al, 2012;Niklas et al, 2010;Vercammen et al, 2014). For instance, Lequeux et al (2010) extended MFA based on the transformation of time series of concentration measurements into flux values.…”

“…This method was illustrated with a fed‐batch fermentation of E. coli , but is presented by the authors as a generic method (e.g., useful for microbial, mammalian and plant cells). In the work of Llaneras et al (), dynamic extracellular concentration measurements are taken into account into a possibilistic MFA strategy by approximating the derivatives of the concentrations. This approach provides solution intervals, where the ranges of possible solutions are obtained by solving a set of minimum‐maximum linear programming problems.…”