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Simultaneous tracers and a unified model of positional and mass isotopomers for quantification of metabolic flux in liver.

Authors :
Deja S
Fu X
Fletcher JA
Kucejova B
Browning JD
Young JD
Burgess SC
Source :
Metabolic engineering [Metab Eng] 2020 May; Vol. 59, pp. 1-14. Date of Electronic Publication: 2019 Dec 28.
Publication Year :
2020

Abstract

Computational models based on the metabolism of stable isotope tracers can yield valuable insight into the metabolic basis of disease. The complexity of these models is limited by the number of tracers and the ability to characterize tracer labeling in downstream metabolites. NMR spectroscopy is ideal for multiple tracer experiments since it precisely detects the position of tracer nuclei in molecules, but it lacks sensitivity for detecting low-concentration metabolites. GC-MS detects stable isotope mass enrichment in low-concentration metabolites, but lacks nuclei and positional specificity. We performed liver perfusions and in vivo infusions of <superscript>2</superscript> H and <superscript>13</superscript> C tracers, yielding complex glucose isotopomers that were assigned by NMR and fit to a newly developed metabolic model. Fluxes regressed from <superscript>2</superscript> H and <superscript>13</superscript> C NMR positional isotopomer enrichments served to validate GC-MS-based flux estimates obtained from the same experimental samples. NMR-derived fluxes were largely recapitulated by modeling the mass isotopomer distributions of six glucose fragment ions measured by GC-MS. Modest differences related to limited fragmentation coverage of glucose C1-C3 were identified, but fluxes such as gluconeogenesis, glycogenolysis, cataplerosis and TCA cycle flux were tightly correlated between the methods. Most importantly, modeling of GC-MS data could assign fluxes in primary mouse hepatocytes, an experiment that is impractical by <superscript>2</superscript> H or <superscript>13</superscript> C NMR.<br /> (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1096-7184
Volume :
59
Database :
MEDLINE
Journal :
Metabolic engineering
Publication Type :
Academic Journal
Accession number :
31891762
Full Text :
https://doi.org/10.1016/j.ymben.2019.12.005