A coarse-grained NADH redox model enables inference of subcellular metabolic fluxes from fluorescence lifetime imaging

  1. Xingbo Yang
  2. Gloria Ha
  3. Daniel J Needleman

  • Curated by eLife

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    Evaluation Summary:

    This paper will be of interest to scientists who use imaging approaches to study cellular metabolism. It presents a new coarse-grained model for inferring mitochondrial NADH oxidation from NAD(P)H fluorescence lifetime imaging in mouse oocytes. The modeling is thoughtfully and clearly presented, but the validity of some key assumptions of the model and the overall generalizability of the method to other cell types could be strengthened.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 and Reviewer #3 agreed to share their names with the authors.)

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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 fluorescence lifetime imaging microscopy 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.

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  1. eLife

    Author Response

    Reviewer #4 (Public Review):

    Not every single cell is the same in terms of its metabolism. To study the causes of such cell-tocell differences, we need microscopic tools to assess metabolic properties, such as metabolite levels and metabolic fluxes, on the single cell level or even beyond. While sensors exits to visualize certain metabolite levels, we still largely lack methods to assess metabolic fluxes in single cells. The work of Yang and Needleman presents a method that can assess -under certain assumptions- the flux through electron transport chain (ETC) in mitochondria of single mouse oocytes at quasi steady-states with subcellular resolution.

    For their method, the authors use FLIM (fluorescence lifetime imaging microscopy) to determine the concentration of free and unbound NADH in mitochondria, and these measurements are then used in a simple coarse-grained model to infer the flux through the ETC. This coarse-grained steady-state model describes the oxidation of NADH with one oxidase (resembling the ETC) and one NADH reductase (resembling all the 3 TCA cycle NADH dehydrogenases plus pyruvate dehydrogenase, but neglecting the FADH2-dependent succinate dehydrogenase) with only two free model parameters.

    Strikingly, when fed with the FLIM data, this coarse-grained model could describe the outcomes of a number of perturbations, where the oxygen uptake rate (i.e. a proxy for the flux through the ETC) was independently measured with a different method. Applying the method, the authors also suggest that the ETC flux is higher in mitochondria that are rather located at the outside of the oocyte.

    While FLIM measurements of bound and unbound NADH have been done before, the main strength of the paper is that it presents a method to infer metabolic activity in an oocyte, where the novelty resides on the development of the simple coarse-grained model and on showing that the model-based analysis of the FLIM data can allow to obtain quasi-steady-state ETC fluxes. The main weakness of the paper is the following: Unfortunately, the work falls short on the application side. One would have wished that for a novel method like this, if it is indeed relevant, it should have been easy for the authors to add exciting application cases that would indeed generate novel biological insight.

    While the main strength is the paper is the method (i.e. inference of ETC flux of model-based analysis of FLIM data), I feel that the description of the method, its assumptions etc falls short, which made assessment of the method and its potential limitations challenging. I feel that this is due to the fact that the writing of the manuscript is suboptimal. While the biochemistry is described/introduced on a very detailed textbook level, the methods, the measurements, the analyses of the measurement data in the result section and in the method section are described in a very short, condensed, and sometime convoluted, manner. As this is primarily meant to be a method paper, the authors need to do a better job in describing what they have done (i.e. model development, model assumptions, inference procedure, etc) in a clearer manner.

    I felt that a strong point was that the two different versions of how the experimental data is used in the model, i.e. lifetime (tau) and bound ratio (beta), leads to similarly inferred r_ox. However, due to the above criticized too short explanations, I could not tell whether this would be trivial or not. Also, the whole method boils down to this equation J_ox = alpha * (beta - beta_eq) * [NADH_f], describing the full complexity of mitochondrial metabolism (TCA cycle, the electron transport chain, metabolite exchange between mitochondria and cytoplasm) with a single equation with only two free parameters (alpha, beta_eq). For this reviewer, also this part still remains somewhat elusive.

    We thank the reviewer for the detailed and in-depth review of our manuscript. We appreciate the reviewer’s suggestion to add application cases to demonstrate the usefulness of our method. We now added two application of our flux inference procedure to the revised manuscript. The first case is the discovery of homeostasis of ETC flux in mouse oocytes: perturbations of nutrient supply and energy demand do not change ETC flux despite significantly impacting NADH metabolic state (Figure 8). The second case is the discovery of the intracellular spatial gradient of ETC flux in mouse oocytes. As suggested by the reviewer, we have used metabolic inhibitors to help reveal the cause of this gradient and found that this gradient is primarily a result of a spatially heterogeneous mitochondrial proton leak (Figure 9). 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.

    We thank the reviewer for their suggestions to improve the presentation of this work. We have significantly rewritten the paper to clearly describe the model development, model assumptions, data analysis procedures and results. Regarding the comparison of the two inference methods, we presented details of the assumptions and derivations in the results section and demonstrated that the agreement between these two methods is not trivial, and is a robust self-consistency check of the method. We also now explained the coarse-graining procedure in detail in the main text and in Appendix 2 and 3 to demonstrate how all the model complexities are coarse-grained into only two free parameters 𝛼 and 𝛽’(. In a nutshell, 𝛼 and 𝛽’( would be functions of the kinetic rates of the model, with the kinetic rates depending on the details of mitochondrial metabolism. However, using the model to infer ETC flux does not require knowing the functional forms of 𝛼 and 𝛽’(, because 𝛼 and 𝛽’( can be experimentally measured with FLIM. The only assumptions required are that 𝛼 remains a constant under perturbations and 𝛽’( can be determined from ETC inhibitions. These assumptions are validated experimentally in mouse oocytes and human tissue culture cells from the agreement between predicted ETC flux and direct measurements of OCR.

    We also validated our model in an additional cell type of human tissue culture cells, demonstrating the generality of our method (Figure 7).

  2. eLife

    Evaluation Summary:

    This paper will be of interest to scientists who use imaging approaches to study cellular metabolism. It presents a new coarse-grained model for inferring mitochondrial NADH oxidation from NAD(P)H fluorescence lifetime imaging in mouse oocytes. The modeling is thoughtfully and clearly presented, but the validity of some key assumptions of the model and the overall generalizability of the method to other cell types could be strengthened.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 and Reviewer #3 agreed to share their names with the authors.)

  3. eLife

    Reviewer #1 (Public Review):

    In this manuscript, the authors present a model to relate FLIM measurements to mitochondrial metabolic fluxes. Using mouse oocytes, which have little NADPH, the authors develop a coarse-grained model to infer mitochondrial NADH oxidation by exploiting NAD(P)H FLIM. Using this approach, the authors uncover regional variation in mitochondrial fluxes in mouse oocytes. The modeled mitochondrial flux shows a strong negative correlation with mitochondrial membrane potential and no correlation with mitochondrial content. While this is not the first paper to use NAD(P)H FLIM to show subcellular metabolic variability, this manuscript does present a model to connect NAD(P)H FLIM to mitochondrial redox cycles. Therefore, the major utility of the model lies in its ability to provide subcellular information about mitochondrial NAD(P)H oxidation. The authors provide a comprehensive and accessible discussion of the assumptions, caveats, and conclusions enabled by their modeling. At present, however, it is not clear to this reviewer how generalizable this method will prove beyond mouse oocytes. This concern stems from the potential difficulty in establishing key parameters of the model in other cell types in which assumptions safely made in mouse oocytes may not be appropriate.

  4. eLife

    Reviewer #2 (Public Review):

    In the manuscript "Coarse-grained model of mitochondrial metabolism enables subcellular flux inference from fluorescence lifetime imaging of NADH", the authors use fluorescence imaging to estimate NADH/NAD turnover flux and electron transfer rate in the mitochondria of mouse oocytes. Because of high spatial resolution of microscopy, the authors could also observe significant subcellular spatial gradient of oxidative flux in oocytes.

  5. eLife

    Reviewer #3 (Public Review):

    This paper describes an analysis of fluorescence lifetime imaging (FLIM) of NADH in mitochondria in intact mouse oocytes, using a mathematical model to interpret the fluorescence data to infer mitochondrial NADH redox fluxes. The authors measure FLIM data for varying oxygen concentrations and using several other perturbations to mitochondrial respiration, in order to infer consequential changes to key mitochondrial metabolic fluxes. One striking observation is of subcellular spatial gradients in the inferred metabolic flux across the oocytes.

  6. eLife

    Reviewer #4 (Public Review):

    Not every single cell is the same in terms of its metabolism. To study the causes of such cell-to-cell differences, we need microscopic tools to assess metabolic properties, such as metabolite levels and metabolic fluxes, on the single cell level or even beyond. While sensors exits to visualize certain metabolite levels, we still largely lack methods to assess metabolic fluxes in single cells. The work of Yang and Needleman presents a method that can assess -under certain assumptions- the flux through electron transport chain (ETC) in mitochondria of single mouse oocytes at quasi steady-states with subcellular resolution. For their method, the authors use FLIM (fluorescence lifetime imaging microscopy) to determine the concentration of free and unbound NADH in mitochondria, and these measurements are then used in a simple coarse-grained model to infer the flux through the ETC. This coarse-grained steady-state model describes the oxidation of NADH with one oxidase (resembling the ETC) and one NADH reductase (resembling all the 3 TCA cycle NADH dehydrogenases plus pyruvate dehydrogenase, but neglecting the FADH2-dependent succinate dehydrogenase) with only two free model parameters.

    Strikingly, when fed with the FLIM data, this coarse-grained model could describe the outcomes of a number of perturbations, where the oxygen uptake rate (i.e. a proxy for the flux through the ETC) was independently measured with a different method. Applying the method, the authors also suggest that the ETC flux is higher in mitochondria that are rather located at the outside of the oocyte. While FLIM measurements of bound and unbound NADH have been done before, the main strength of the paper is that it presents a method to infer metabolic activity in an oocyte, where the novelty resides on the development of the simple coarse-grained model and on showing that the model-based analysis of the FLIM data can allow to obtain quasi-steady-state ETC fluxes. The main weakness of the paper is the following: Unfortunately, the work falls short on the application side. One would have wished that for a novel method like this, if it is indeed relevant, it should have been easy for the authors to add exciting application cases that would indeed generate novel biological insight.

    While the main strength is the paper is the method (i.e. inference of ETC flux of model-based analysis of FLIM data), I feel that the description of the method, its assumptions etc falls short, which made assessment of the method and its potential limitations challenging. I feel that this is due to the fact that the writing of the manuscript is suboptimal. While the biochemistry is described/introduced on a very detailed textbook level, the methods, the measurements, the analyses of the measurement data in the result section and in the method section are described in a very short, condensed, and sometime convoluted, manner. As this is primarily meant to be a method paper, the authors need to do a better job in describing what they have done (i.e. model development, model assumptions, inference procedure, etc) in a clearer manner.

    I felt that a strong point was that the two different versions of how the experimental data is used in the model, i.e. lifetime (tau) and bound ratio (beta), leads to similarly inferred r_ox. However, due to the above criticized too short explanations, I could not tell whether this would be trivial or not. Also, the whole method boils down to this equation J_ox = alpha * (beta - beta_eq) * [NADH_f], describing the full complexity of mitochondrial metabolism (TCA cycle, the electron transport chain, metabolite exchange between mitochondria and cytoplasm) with a single equation with only two free parameters (alpha, beta_eq). For this reviewer, also this part still remains somewhat elusive.

  7. Version published to 10.7554/elife.73808 on eLife
  8. Version published to 10.1101/2020.11.20.392225v3 on bioRxiv
  9. Version published to 10.1101/2020.11.20.392225v2 on bioRxiv
  10. Version published to 10.1101/2020.11.20.392225v1 on bioRxiv