细胞中的线粒体群体通过分裂和融合事件的循环来维持。在几种疾病如癌症和神经变性中已经观察到这种平衡的扰动。在裂殖酵母细胞中,线粒体与微管的关联抑制线粒体裂变[Mehta等人。,J、生物。Chem.,2019,294,3385],说明线粒体和细胞内微管的动态群体之间的复杂耦合。为了理解这种耦合,我们进行了动力学蒙特卡罗(KMC)模拟,以预测不同情况下线粒体大小分布的演变;野生型细胞,具有短和长微管的细胞,和没有微管的细胞。与裂殖酵母细胞实验中报道的线粒体分布进行了比较。利用实验确定的线粒体裂变和融合频率,在没有微管动力学耦合的情况下实施的模拟预测线粒体平均数量的增加,在50s内平衡。这些模型中的线粒体长度分布也显示出较短线粒体的较高发生率,暗示裂变的更大趋势,类似于在没有微管和具有短微管的细胞的情况下观察到的情况。有趣的是,这导致在具有野生型和长微管的细胞中高估了线粒体的平均数量,而低估了线粒体的长度.然而,将线粒体的裂变和融合事件与微管动力学耦合,有效地捕获了野生型和长微管细胞中的线粒体数量和大小分布。因此,该模型为不同微管环境中线粒体种群的时间演变提供了更多的物理见解,允许人们研究实验中观察到的短时演化(<5分钟)以及它们向稳态(>15分钟)的过渡。我们的研究说明了微管在线粒体动力学和耦合微管生长和收缩动力学中的关键作用对于预测细胞内线粒体群体的进化至关重要。
Mitochondrial populations in cells are maintained by cycles of fission and fusion events. Perturbation of this balance has been observed in several diseases such as cancer and neurodegeneration. In fission yeast cells, the association of mitochondria with microtubules inhibits mitochondrial fission [Mehta et al., J. Biol. Chem., 2019, 294, 3385], illustrating the intricate coupling between mitochondria and the dynamic population of microtubules within the cell. In order to understand this coupling, we carried out kinetic Monte Carlo (KMC) simulations to predict the evolution of mitochondrial size distributions for different cases; wild-type cells, cells with short and long microtubules, and cells without microtubules. Comparisons are made with mitochondrial distributions reported in experiments with fission yeast cells. Using experimentally determined mitochondrial fission and fusion frequencies, simulations implemented without the coupling of microtubule dynamics predicted an increase in the mean number of mitochondria, equilibrating within 50 s. The mitochondrial length distribution in these models also showed a higher occurrence of shorter mitochondria, implying a greater tendency for fission, similar to the scenario observed in the absence of microtubules and cells with short microtubules. Interestingly, this resulted in overestimating the mean number of mitochondria and underestimating mitochondrial lengths in cells with wild-type and long microtubules. However, coupling mitochondria\'s fission and fusion events to the microtubule dynamics effectively captured the mitochondrial number and size distributions in wild-type and cells with long microtubules. Thus, the model provides greater physical insight into the temporal evolution of mitochondrial populations in different microtubule environments, allowing one to
study both the short-time evolution as observed in the experiments (<5 minutes) as well as their transition towards a steady-state (>15 minutes). Our
study illustrates the critical role of microtubules in mitochondrial dynamics and coupling microtubule growth and shrinkage dynamics is critical to predicting the evolution of mitochondrial populations within the cell.