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Tracing metabolic flux in vivo: motion pictures differ from snapshots

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주제분류생화학

초록

Since Rudolf Schoenheimer’s pioneering metabolic tracing work in the 1930s1, it is currently well appreciated that all constituents of living matter (e.g., DNAs, RNAs, proteins, lipids, and metabolites) are in a constant state of turnover at varying rates to achieve overall “dynamic” homeostasis. Furthermore, metabolic systems are highly complex, connected, and interactive, and consequently, one’s metabolic fluxes (“motion pictures”) should not be understood as individual components but as a whole system2. Unfortunately, most modern metabolic studies heavily depend on the measurements of static, snapshot information, so-called “statomics” (e.g., transcriptomics, proteomics, metabolomics, and cellular signaling cascades) of individual components of the whole system, which often fail to reflect actual metabolic status3,4. Without simultaneous considerations of metabolic flux, sole dependence on “statomics” can lead to incorrect conclusions regarding metabolic status. In this Special Feature, experts in the field of tracer methodology or fluxomics provide the basic principles and applications of the methodologies determining metabolic fluxes to various metabolic conditions. The incorporation of these state-of-the-art methodologies into metabolic research will guide researchers to a better understanding of dynamic metabolic systems with which to better dissect underlying molecular mechanisms of physiology or pathophysiology.

Abstract

Since Rudolf Schoenheimer’s pioneering metabolic tracing work in the 1930s1, it is currently well appreciated that all constituents of living matter (e.g., DNAs, RNAs, proteins, lipids, and metabolites) are in a constant state of turnover at varying rates to achieve overall “dynamic” homeostasis. Furthermore, metabolic systems are highly complex, connected, and interactive, and consequently, one’s metabolic fluxes (“motion pictures”) should not be understood as individual components but as a whole system2. Unfortunately, most modern metabolic studies heavily depend on the measurements of static, snapshot information, so-called “statomics” (e.g., transcriptomics, proteomics, metabolomics, and cellular signaling cascades) of individual components of the whole system, which often fail to reflect actual metabolic status3,4. Without simultaneous considerations of metabolic flux, sole dependence on “statomics” can lead to incorrect conclusions regarding metabolic status. In this Special Feature, experts in the field of tracer methodology or fluxomics provide the basic principles and applications of the methodologies determining metabolic fluxes to various metabolic conditions. The incorporation of these state-of-the-art methodologies into metabolic research will guide researchers to a better understanding of dynamic metabolic systems with which to better dissect underlying molecular mechanisms of physiology or pathophysiology.

참고문헌 (11)

  1. Schoenheimer, R., "Deuterium as an indicator in the study of intermediary metabolism: VI. Synthesis and destruction of fatty acids in the organism", J. Biol. Chem, 114, pp.381~396 (1937)
  2. Hellerstein, M. K., "In vivo measurement of fluxes through metabolic pathways : the missing link in functional genomics and pharmaceutical research", Annu. Rev. Nutr, 23, pp.379~402 (2003)
  3. Neinast, M. D., "Quantitative analysis of the whole-body metabolic fate of branched-chain amino acids", Cell Metab, 29, pp.417~429.e4 (2019)
  4. Perry, R. J., "Leptin mediates a glucose-fatty acid cycle to maintain glucose homeostasis in starvation", Cell, 172, pp.234~248.e17 (2018)
  5. Wolfe, R. R., "Isotope Tracers in Metabolic Research: Principles and Practice of Kinetic Analysis" (2005), Wiley-Liss
  6. 김일영, "Applications of stable, nonradioactive isotope tracers in in vivo human metabolic research", Experimental and Molecular Medicine, 48, pp.1~10 (2016), 생화학분자생물학회
  7. Kim, I. Y., "Update on maximal anabolic response to dietary protein", Clin. Nutr, 37, pp.411~418 (2018)
  8. Brooks, G. A., "The science and translation of lactate shuttle theory", Cell Metab, 27, pp.757~785 (2018)
  9. Brooks, G. A., "Lactate as a major myokine and exerkine", Nat. Rev. Endocrinol (2022)[DOI]
  10. Biolo, G., "Physiologic hyperinsulinemia stimulates protein synthesis and enhances transport of selected amino acids in human skeletal muscle", J. Clin. Invest, 95, pp.811~819 (1995)
  11. Murashige, D., "Comprehensive quantification of fuel use by the failing and nonfailing human heart", Science, 370, pp.364~368 (2020)

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