Computational Modeling of In Vitro Swelling of Mitochondria: A Biophysical Approach.
Computational Modeling of In Vitro Swelling of Mitochondria: A Biophysical Approach.
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DOI：
10.3390/molecules23040783
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发表时间：
2018-03-28
期刊：
影响因子：
--
通讯作者：
Javadov S
中科院分区：
文献类型：
--
作者：
Makarov VI;Khmelinskii I;Javadov S
线粒体肿胀通过凋亡、坏死和自噬刺激线粒体介导的细胞死亡，在人类疾病的发病机制中起着重要作用。离子和其他物质的线粒体内膜（IMM）通透性变化导致胶体渗透压升高，进而引起基质肿胀。线粒体肿胀的建模对于模拟和预测细胞在氧化和能量应激期间体内发生的事件非常重要。在本研究中，我们开发了一个计算模型，该模型基于渗透作用、线粒体内膜的刚性以及离子/中性物质的动力学来描述线粒体肿胀的机制。该模型描述了一种新的肿胀动力学的生物物理方法，即基质中产生的渗透压由线粒体内膜的刚性来补偿，也就是说，渗透压引起膜变形，从而补偿渗透压的影响。因此，在膜变形较小时，这种影响是线性且可逆的，使得膜能够恢复其正常形态。另一方面，在大变形时，膜的刚性降为零，肿胀变得不可逆。结果，功能失调的线粒体数量增加会激活线粒体自噬并引发细胞死亡。数值模拟分析得出的结果合理地描述了先前报道的实验数据。
Swelling of mitochondria plays an important role in the pathogenesis of human diseases by stimulating mitochondria-mediated cell death through apoptosis, necrosis, and autophagy. Changes in the permeability of the inner mitochondrial membrane (IMM) of ions and other substances induce an increase in the colloid osmotic pressure, leading to matrix swelling. Modeling of mitochondrial swelling is important for simulation and prediction of in vivo events in the cell during oxidative and energy stress. In the present study, we developed a computational model that describes the mechanism of mitochondrial swelling based on osmosis, the rigidity of the IMM, and dynamics of ionic/neutral species. The model describes a new biophysical approach to swelling dynamics, where osmotic pressure created in the matrix is compensated for by the rigidity of the IMM, i.e., osmotic pressure induces membrane deformation, which compensates for the osmotic pressure effect. Thus, the effect is linear and reversible at small membrane deformations, allowing the membrane to restore its normal form. On the other hand, the membrane rigidity drops to zero at large deformations, and the swelling becomes irreversible. As a result, an increased number of dysfunctional mitochondria can activate mitophagy and initiate cell death. Numerical modeling analysis produced results that reasonably describe the experimental data reported earlier.
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影响因子：
3
作者：
Bernardi, P;Petronilli, V
通讯作者：
Petronilli, V
影响因子：
5
作者：
Dedkova EN;Blatter LA
通讯作者：
Blatter LA
影响因子：
4.3
作者：
Bazil, Jason N.;Buzzard, Gregery T.;Rundell, Ann E.
通讯作者：
Rundell, Ann E.
影响因子：
5
作者：
Bernardi, Paolo;Di Lisa, Fabio
通讯作者：
Di Lisa, Fabio
DOI：
10.1073/pnas.1401591111
发表时间：
2014-07-22
影响因子：
11.1
作者：
Alavian, Kambiz N.;Beutner, Gisela;Jonas, Elizabeth A.
通讯作者：
Jonas, Elizabeth A.