Metabolic flux analysis: a comprehensive review on sample preparation, analytical techniques, data analysis, computational modelling, and main application areas

de Falco, Bruna; Giannino, Francesco; Carteni, Fabrizio; Mazzoleni, Stefano; Kim, Dong Hyun

Abstract

Metabolic flux analysis (MFA) quantitatively describes cellular fluxes to understand metabolic phenotypes and functional behaviour after environmental and/or genetic perturbations. In the last decade, the application of stable isotopes became extremely important to determine and integrate in vivo measurements of metabolic reactions in systems biology. 13C-MFA is one of the most informative methods used to study central metabolism of biological systems. This review aims to outline the current experimental procedure adopted in 13C-MFA, starting from the preparation of cell cultures and labelled tracers to the quenching and extraction of metabolites and their subsequent analysis performed with very powerful software. Here, the limitations and advantages of nuclear magnetic resonance spectroscopy and mass spectrometry techniques used in carbon labelled experiments are elucidated by reviewing the most recent published papers. Furthermore, we summarise the most successful approaches used for computational modelling in flux analysis and the main application areas with a particular focus in metabolic engineering.

Citation

de Falco, B., Giannino, F., Carteni, F., Mazzoleni, S., & Kim, D. H. (2022). Metabolic flux analysis: a comprehensive review on sample preparation, analytical techniques, data analysis, computational modelling, and main application areas. RSC Advances, 12(39), 25528-25548. https://doi.org/10.1039/d2ra03326g

• Journal Article Type: Article
• Acceptance Date: Aug 26, 2022
• Online Publication Date: Sep 7, 2022
• Publication Date: Sep 7, 2022
• Deposit Date: Sep 8, 2022
• Publicly Available Date: Sep 12, 2022
• Journal: RSC Advances
• Electronic ISSN: 2046-2069
• Publisher: Royal Society of Chemistry
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 39
• Pages: 25528-25548
• DOI: https://doi.org/10.1039/d2ra03326g
• Public URL: https://nottingham-repository.worktribe.com/output/10915089
• Publisher URL: https://pubs.rsc.org/en/content/articlelanding/2022/RA/D2RA03326G