Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.
PLoS Comput Biol. 2020 Sep 14;16(9):e1008202. doi: 10.1371/journal.pcbi.1008202. eCollection 2020 Sep.
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.
过氧化氢（H2O2）根据其细胞内浓度和给药动力学促进一系列表型，包括细胞死亡。虽然这种定性关系已经得到很好的证实，但 H2O2 信号的定量和机制方面仍在阐明中。线粒体，细胞内 H2O2 的潜在来源，最近被证明特别容易受到局部 H2O2 干扰，与类似的细胞质干扰相比，会引起剧烈的细胞死亡反应。我们试图通过创建该系统的动力学模型并使用该模型来探索基础和受扰条件，来提高我们对 Hela 细胞中线粒体 H2O2 反应网络的动态和机制理解。该模型使用最新的定量蛋白质组学和动力学数据来预测单个线粒体中 H2O2 及其反应伙伴的反应速率和稳态浓度。模拟时间范围从毫秒到一小时。我们预测基础、稳态线粒体 H2O2 将处于低 nM 范围（2-4 nM），并将与过氧化物酶 3（Prx3）的总池呈反比。忽略 H2O2 向细胞质的流出，线粒体反应网络预计将很好地控制干扰，直到 H2O2 产生率达到~50 μM/s（0.25 nmol/mg-蛋白/s），超过该点，Prx3 系统预计会崩溃。将这些结果与 Prx3 和 Prx2 氧化态的还原 Western blot 进行比较，在一系列实验性干扰 H2O2 产生率的情况下，在短时间（≤15 分钟）内表现出合理的趋势一致性。在较长时间内，通过过氧化物酶 2（Prx2）的氧化证明了 H2O2 从线粒体向细胞质的大量流出，并且没有观察到 Prx3 的崩溃。使用蒙特卡罗参数采样的改进模型用于探索 H2O2 流出率，该模型可以使 Prx3 氧化态的模型预测与实验观察结果相一致。
