Kinetic modeling of H2O2 dynamics in the mitochondria of HeLa cells

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Abstract
Hydrogen peroxide (H2O2) promotes a range of phenotypes depending on its intracellular concentration and dosing kinetics, including cell death. While this qualitative relationship has been well established, the quantitative and mechanistic aspects of H2O2 signaling are still being elucidated. Mitochondria, a putative source of intracellular H2O2, have recently been demonstrated to be particularly vulnerable to localized H2O2 perturbations, eliciting a dramatic cell death response in comparison to similar cytosolic perturbations. We sought to improve our dynamic and mechanistic understanding of the mitochondrial H2O2 reaction network in HeLa cells by creating a kinetic model of this system and using it to explore basal and perturbed conditions. The model uses the most current quantitative proteomic and kinetic data available to predict reaction rates and steady-state concentrations of H2O2 and its reaction partners within individual mitochondria. Time scales ranging from milliseconds to one hour were simulated. We predict that basal, steady-state mitochondrial H2O2 will be in the low nM range (2–4 nM) and will be inversely dependent on the total pool of peroxiredoxin-3 (Prx3). Neglecting efflux of H2O2 to the cytosol, the mitochondrial reaction network is expected to control perturbations well up to H2O2 generation rates ~50 μM/s (0.25 nmol/mg-protein/s), above which point the Prx3 system would be expected to collapse. Comparison of these results with redox Western blots of Prx3 and Prx2 oxidation states demonstrated reasonable trend agreement at short times (≤ 15 min) for a range of experimentally perturbed H2O2 generation rates. At longer times, substantial efflux of H2O2 from the mitochondria to the cytosol was evidenced by peroxiredoxin-2 (Prx2) oxidation, and Prx3 collapse was not observed. A refined model using Monte Carlo parameter sampling was used to explore rates of H2O2 efflux that could reconcile model predictions of Prx3 oxidation states with the experimental observations. Cancer is a complex disease that caused the deaths of over 9 million people worldwide in 2018, according to the WHO. While great strides have been made in treating many cancers, effective chemotherapies still carry difficult side effects, motivating the search for more targeted and selective treatments that act minimally in healthy cells. The Selective Cancer Killing Hypothesis is based on the idea that some cancers exist at endogenous levels of reactive oxygen species that are higher than healthy cells, so if a patient were systemically treated with a redox-based chemotherapeutic that raises all cells’ levels of reactive oxygen species, only the cancer cells would cross a toxicity threshold. This hypothesis is attractive because it would minimize side effects in healthy cells, but the quantitative knowledge of endogenous oxidant concentrations that would be helpful in refining and testing this hypothesis is not widely established. Our model predicts the range of relevant hydrogen peroxide concentrations in the mitochondria of the HeLa model cancer cell line and suggests experimental measurements of tumor cells and tissues that may be useful in quantifying steady state concentrations of this oxidant.

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