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Moiz B, Sriram G, Clyne AM. Interpreting metabolic complexity via isotope-assisted metabolic flux analysis. Trends Biochem Sci 2023; 48:553-567. [PMID: 36863894 PMCID: PMC10182253 DOI: 10.1016/j.tibs.2023.02.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 01/22/2023] [Accepted: 02/03/2023] [Indexed: 03/04/2023]
Abstract
Isotope-assisted metabolic flux analysis (iMFA) is a powerful method to mathematically determine the metabolic fluxome from experimental isotope labeling data and a metabolic network model. While iMFA was originally developed for industrial biotechnological applications, it is increasingly used to analyze eukaryotic cell metabolism in physiological and pathological states. In this review, we explain how iMFA estimates the intracellular fluxome, including data and network model (inputs), the optimization-based data fitting (process), and the flux map (output). We then describe how iMFA enables analysis of metabolic complexities and discovery of metabolic pathways. Our goal is to expand the use of iMFA in metabolism research, which is essential to maximizing the impact of metabolic experiments and continuing to advance iMFA and biocomputational techniques.
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Affiliation(s)
- Bilal Moiz
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA
| | - Ganesh Sriram
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD 20742, USA
| | - Alisa Morss Clyne
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
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Moiz B, Li A, Padmanabhan S, Sriram G, Clyne AM. Isotope-Assisted Metabolic Flux Analysis: A Powerful Technique to Gain New Insights into the Human Metabolome in Health and Disease. Metabolites 2022; 12:1066. [PMID: 36355149 PMCID: PMC9694183 DOI: 10.3390/metabo12111066] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 10/25/2022] [Accepted: 10/27/2022] [Indexed: 04/28/2024] Open
Abstract
Cell metabolism represents the coordinated changes in genes, proteins, and metabolites that occur in health and disease. The metabolic fluxome, which includes both intracellular and extracellular metabolic reaction rates (fluxes), therefore provides a powerful, integrated description of cellular phenotype. However, intracellular fluxes cannot be directly measured. Instead, flux quantification requires sophisticated mathematical and computational analysis of data from isotope labeling experiments. In this review, we describe isotope-assisted metabolic flux analysis (iMFA), a rigorous computational approach to fluxome quantification that integrates metabolic network models and experimental data to generate quantitative metabolic flux maps. We highlight practical considerations for implementing iMFA in mammalian models, as well as iMFA applications in in vitro and in vivo studies of physiology and disease. Finally, we identify promising new frontiers in iMFA which may enable us to fully unlock the potential of iMFA in biomedical research.
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Affiliation(s)
- Bilal Moiz
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA
| | - Andrew Li
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA
| | - Surya Padmanabhan
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA
| | - Ganesh Sriram
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD 20742, USA
| | - Alisa Morss Clyne
- Department of Bioengineering, University of Maryland, College Park, MD 20742, USA
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Salon C, Avice JC, Colombié S, Dieuaide-Noubhani M, Gallardo K, Jeudy C, Ourry A, Prudent M, Voisin AS, Rolin D. Fluxomics links cellular functional analyses to whole-plant phenotyping. JOURNAL OF EXPERIMENTAL BOTANY 2017; 68:2083-2098. [PMID: 28444347 DOI: 10.1093/jxb/erx126] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Fluxes through metabolic pathways reflect the integration of genetic and metabolic regulations. While it is attractive to measure all the mRNAs (transcriptome), all the proteins (proteome), and a large number of the metabolites (metabolome) in a given cellular system, linking and integrating this information remains difficult. Measurement of metabolome-wide fluxes (termed the fluxome) provides an integrated functional output of the cell machinery and a better tool to link functional analyses to plant phenotyping. This review presents and discusses sets of methodologies that have been developed to measure the fluxome. First, the principles of metabolic flux analysis (MFA), its 'short time interval' version Inst-MFA, and of constraints-based methods, such as flux balance analysis and kinetic analysis, are briefly described. The use of these powerful methods for flux characterization at the cellular scale up to the organ (fruits, seeds) and whole-plant level is illustrated. The added value given by fluxomics methods for unravelling how the abiotic environment affects flux, the process, and key metabolic steps are also described. Challenges associated with the development of fluxomics and its integration with 'omics' for thorough plant and organ functional phenotyping are discussed. Taken together, these will ultimately provide crucial clues for identifying appropriate target plant phenotypes for breeding.
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Affiliation(s)
- Christophe Salon
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, 17 Rue Sully, BP 86510, 21065 Dijon Cedex, France
| | - Jean-Christophe Avice
- UNICAEN, UMR INRA 950 Ecophysiologie Végétale, Agronomie et nutritions N, C, S, Esplanade de la Paix, Université Caen Normandie, 14032 Caen Cedex 5, France
| | - Sophie Colombié
- UMR 1332 Biologie du Fruit et Pathologie, INRA, Université de Bordeaux, 33882 Villenave d'Ornon, France
| | - Martine Dieuaide-Noubhani
- UMR 1332 Biologie du Fruit et Pathologie, INRA, Université de Bordeaux, 33882 Villenave d'Ornon, France
| | - Karine Gallardo
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, 17 Rue Sully, BP 86510, 21065 Dijon Cedex, France
| | - Christian Jeudy
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, 17 Rue Sully, BP 86510, 21065 Dijon Cedex, France
| | - Alain Ourry
- UNICAEN, UMR INRA 950 Ecophysiologie Végétale, Agronomie et nutritions N, C, S, Esplanade de la Paix, Université Caen Normandie, 14032 Caen Cedex 5, France
| | - Marion Prudent
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, 17 Rue Sully, BP 86510, 21065 Dijon Cedex, France
| | - Anne-Sophie Voisin
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, 17 Rue Sully, BP 86510, 21065 Dijon Cedex, France
| | - Dominique Rolin
- UMR 1332 Biologie du Fruit et Pathologie, INRA, Université de Bordeaux, 33882 Villenave d'Ornon, France
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