A coarse-grained NADH redox model enables inference of subcellular metabolic fluxes from fluorescence lifetime imaging
Abstract
Mitochondrial metabolism is of central importance to diverse aspects of cell and developmental biology. Defects in mitochondria are associated with many diseases, including cancer, neuropathology, and infertility. Our understanding of mitochondrial metabolism in situ and dysfunction in diseases are limited by the lack of techniques to measure mitochondrial metabolic fluxes with sufficient spatiotemporal resolution. Herein, we developed a new method to infer mitochondrial metabolic fluxes in living cells with subcellular resolution from fluorescence lifetime imaging of NADH. This result is based on the use of a generic coarse-grained NADH redox model. We tested the model in mouse oocytes and human tissue culture cells subject to a wide variety of perturbations by comparing predicted fluxes through the electron transport chain (ETC) to direct measurements of oxygen consumption rate. Interpreting the FLIM measurements of NADH using this model, we discovered a homeostasis of ETC flux in mouse oocytes: perturbations of nutrient supply and energy demand of the cell do not change ETC flux despite significantly impacting NADH metabolic state. Furthermore, we observed a subcellular spatial gradient of ETC flux in mouse oocytes and found that this gradient is primarily a result of a spatially heterogeneous mitochondrial proton leak. We concluded from these observations that ETC flux in mouse oocytes is not controlled by energy demand or supply, but by the intrinsic rates of mitochondrial respiration.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided for Figures 2, Figure 5, Figure 5-figure supplement 1, Figure 6, Figure 6-figure supplement 1, Figure 7, Figure 8, Figure 8-figure supplement 1.
Article and author information
Author details
Funding
National Institutes of Health (R01HD092550-01)
- Dan Needleman
National Science Foundation (PFI-TT-1827309)
- Dan Needleman
National Science Foundation (PHY-2013874)
- Dan Needleman
National Science Foundation (MCB-2052305)
- Dan Needleman
National Science Foundation (PHY-1748958)
- Xingbo Yang
- Dan Needleman
National Institutes of Health (R25GM067110)
- Xingbo Yang
- Dan Needleman
Gordon and Betty Moore Foundation (2919.02)
- Xingbo Yang
- Dan Needleman
National Science Foundation (1764269)
- Gloria Ha
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Yang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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