Metabolic flux analysis reaching genome wide coverage: lessons learned and future perspectives. (December 2020)

• Record Type: Journal Article
• Authors: Hendry, John I; Dinh, Hoang V; Foster, Charles; Gopalakrishnan, Saratram; Wang, Lin; Maranas, Costas D
• Is Part Of: Current opinion in chemical engineering. Volume 30(2020)
• Page Start: 17
• Page End: 25
• Publication Date: 2020-12
• Subjects: Chemical engineering -- Periodicals; Chemical engineering; Periodicals; 660.05
• DOI: 10.1016/j.coche.2020.05.008
• Languages: English
• ISSNs: 2211-3398

Abstract

Highlights: Use of simplified metabolic network in 13 C-MFA causes loss of information. Genome scale 13 C-MFA provides more accurate flux distribution. Computational tools are already in place for genome scale 13 C-MFA. Construction of genome scale atom mapping model is no more an impossible task. Non-stationary genome scale 13 C-MFA still remains computationally expensive. Abstract : 13 C-MFA is currently the only technique capable of elucidating intracellular metabolic fluxes. Generally, in 13 C-MFA studies the reactions that can carry flux are mostly pre-specified by only considering canonical pathways and ignoring alternate ones. This may bias flux elucidation and cause labeling data to erroneously confirm implied assumptions. By expanding the scope of the metabolic mapping models to match known genome-scale metabolism such estimation biases can be eliminated. However, this model expansion to genome-scale requires the construction of expanded atom mapping models, more efficient flux estimation algorithms, and formal estimation of confidence levels. Even though significant progress has been made in this direction, a number of challenges remain before widespread adoption by the community.