TY - JOUR
T1 - Systems-level computational modeling demonstrates fuel selection switching in high capacity running and low capacity running rats
AU - Moxley, Michael A.
AU - Vinnakota, Kalyan C.
AU - Bazil, Jason N.
AU - Qi, Nathan R.
AU - Beard, Daniel A.
N1 - Funding Information:
This work was funded by the National Institute of Diabetes and Digestive and Kidney Diseases (R01-DK095210), the National Heart, Lung, and Blood institute (R01-HL072011 and R00-HL121160). The funders had no role in study design, data analysis, decision to publish, or preparation of the manuscript. We would like to acknowledge Dr. Charles Burant, at the University of Michigan-Ann Arbor, for his help in providing the data, previously published in Cell Metab. 2015;21(3):468–78.
Publisher Copyright:
© 2018 Moxley et al.
PY - 2018/2
Y1 - 2018/2
N2 - High capacity and low capacity running rats, HCR and LCR respectively, have been bred to represent two extremes of running endurance and have recently demonstrated disparities in fuel usage during transient aerobic exercise. HCR rats can maintain fatty acid (FA) utilization throughout the course of transient aerobic exercise whereas LCR rats rely predominantly on glucose utilization. We hypothesized that the difference between HCR and LCR fuel utilization could be explained by a difference in mitochondrial density. To test this hypothesis and to investigate mechanisms of fuel selection, we used a constraint-based kinetic analysis of whole-body metabolism to analyze transient exercise data from these rats. Our model analysis used a thermodynamically constrained kinetic framework that accounts for glycolysis, the TCA cycle, and mitochondrial FA transport and oxidation. The model can effectively match the observed relative rates of oxidation of glucose versus FA, as a function of ATP demand. In searching for the minimal differences required to explain metabolic function in HCR versus LCR rats, it was determined that the whole-body metabolic phenotype of LCR, compared to the HCR, could be explained by a ~50% reduction in total mitochondrial activity with an additional 5-fold reduction in mitochondrial FA transport activity. Finally, we postulate that over sustained periods of exercise that LCR can partly overcome the initial deficit in FA catabolic activity by upregulating FA transport and/or oxidation processes.
AB - High capacity and low capacity running rats, HCR and LCR respectively, have been bred to represent two extremes of running endurance and have recently demonstrated disparities in fuel usage during transient aerobic exercise. HCR rats can maintain fatty acid (FA) utilization throughout the course of transient aerobic exercise whereas LCR rats rely predominantly on glucose utilization. We hypothesized that the difference between HCR and LCR fuel utilization could be explained by a difference in mitochondrial density. To test this hypothesis and to investigate mechanisms of fuel selection, we used a constraint-based kinetic analysis of whole-body metabolism to analyze transient exercise data from these rats. Our model analysis used a thermodynamically constrained kinetic framework that accounts for glycolysis, the TCA cycle, and mitochondrial FA transport and oxidation. The model can effectively match the observed relative rates of oxidation of glucose versus FA, as a function of ATP demand. In searching for the minimal differences required to explain metabolic function in HCR versus LCR rats, it was determined that the whole-body metabolic phenotype of LCR, compared to the HCR, could be explained by a ~50% reduction in total mitochondrial activity with an additional 5-fold reduction in mitochondrial FA transport activity. Finally, we postulate that over sustained periods of exercise that LCR can partly overcome the initial deficit in FA catabolic activity by upregulating FA transport and/or oxidation processes.
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U2 - 10.1371/journal.pcbi.1005982
DO - 10.1371/journal.pcbi.1005982
M3 - Article
C2 - 29474500
AN - SCOPUS:85042684354
SN - 1553-734X
VL - 14
JO - PLoS computational biology
JF - PLoS computational biology
IS - 2
M1 - e1005982
ER -