TY - JOUR
T1 - Simultaneous tracers and a unified model of positional and mass isotopomers for quantification of metabolic flux in liver
AU - Deja, Stanislaw
AU - Fu, Xiaorong
AU - Fletcher, Justin A.
AU - Kucejova, Blanka
AU - Browning, Jeffrey D.
AU - Young, Jamey D.
AU - Burgess, Shawn C.
N1 - Funding Information:
JDY was supported by NIH R01 DK106348 . SCB was supported by NIH R01-DK078184 . SD and SCB were supported by NIH P41-EB-015908 , the Robert A. Welch Foundation Grant I-1804 and the UT Southwestern Center for Human Nutrition. Appendix A
Funding Information:
JDY was supported by NIH R01 DK106348. SCB was supported by NIH R01-DK078184. SD and SCB were supported by NIH P41-EB-015908, the Robert A. Welch Foundation Grant I-1804 and the UT Southwestern Center for Human Nutrition.
Publisher Copyright:
© 2020 The Authors
PY - 2020/5
Y1 - 2020/5
N2 - 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 2H and 13C tracers, yielding complex glucose isotopomers that were assigned by NMR and fit to a newly developed metabolic model. Fluxes regressed from 2H and 13C 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 2H or 13C NMR.
AB - 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 2H and 13C tracers, yielding complex glucose isotopomers that were assigned by NMR and fit to a newly developed metabolic model. Fluxes regressed from 2H and 13C 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 2H or 13C NMR.
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U2 - 10.1016/j.ymben.2019.12.005
DO - 10.1016/j.ymben.2019.12.005
M3 - Article
C2 - 31891762
AN - SCOPUS:85077504985
SN - 1096-7176
VL - 59
SP - 1
EP - 14
JO - Metabolic Engineering
JF - Metabolic Engineering
ER -