Department of Chemical Engineering, Indian Institute of Science, Bangalore, Karnataka, India.
Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, Karnataka, India.
Soft Matter. 2022 Jun 15;18(23):4483-4492. doi: 10.1039/d2sm00155a.
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 , , 2019, , 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.
细胞中的线粒体群体是通过分裂和融合事件的循环来维持的。在癌症和神经退行性疾病等几种疾病中观察到这种平衡的破坏。在裂殖酵母细胞中，线粒体与微管的结合抑制了线粒体的分裂[Mehta,, 2019,, 3385]，说明了线粒体与细胞内动态微管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、微管短和长的细胞以及没有微管的细胞。将这些模拟与裂殖酵母细胞的实验中报告的线粒体分布进行了比较。使用实验确定的线粒体分裂和融合频率，在没有微管动力学耦合的情况下进行的模拟预测，线粒体的平均数量会增加，在 50 秒内达到平衡。这些模型中的线粒体长度分布也显示出较短线粒体的出现频率更高，这意味着分裂的趋势更大，类似于没有微管和微管较短的细胞中观察到的情况。有趣的是，这导致在野生型和微管较长的细胞中高估了线粒体的平均数量和低估了线粒体的长度。然而，将线粒体的分裂和融合事件与微管动力学耦合有效地捕捉到了野生型和微管较长的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群体的时间演变提供了更深入的物理理解，使人们能够研究实验中观察到的（<5 分钟）短时间演变以及它们向稳态（>15 分钟）的转变。我们的研究说明了微管在线粒体动力学中的关键作用，并且耦合微管的生长和收缩动力学对于预测细胞内线粒体群体的演变至关重要。
