A systematic elementary flux mode selection procedure for deriving macroscopic bioreaction models from metabolic networks. (October 2022)

• Record Type: Journal Article
• Authors: Maton, M.; Bogaerts, Ph.; Vande Wouwer, A.
• Is Part Of: Journal of process control. Volume 118(2022)
• Page Start: 170
• Page End: 184
• Publication Date: 2022-10
• Subjects: Model reduction -- Dynamic models -- Metabolic network -- Elementary flux modes -- Biotechnology -- Reaction scheme; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2022.09.002
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: Elementary flux modes (EFMs) are an important concept in metabolic pathway analysis and for the derivation of macroscopic dynamic models. However, the computation of elementary flux vectors is facing combinatorial explosion with the size of the metabolic network, which hinders widespread application. This study proposes a systematic elementary flux mode reduction procedure to derive reduced-order dynamic models starting from an initial set of EFMs either generated by complete enumeration or subset selection. The procedure proceeds in several steps, including geometric and optimization-based criteria. The methodology ends up with a macroscopic bioreaction scheme with a reaction number smaller than that of the measured species, and shows very satisfactory prediction results, as illustrated with data of batch cultures of CHO-320 cells. Highlights: Detailed metabolic networks can be used to generate macroscopic models. A systematic procedure to reduce the number of elementary flux modes is proposed. When EFMs enumeration becomes intractable, minimal generation algorithms are exploited. The reduction procedure is modular with steps that can be activated or bypassed. CHO batch cultures can be efficiently represented by a few elementary flux vectors.