Chair of Computational Science, ETH Zurich, Zurich, Switzerland.
PLoS Comput Biol. 2009 Dec;5(12):e1000623. doi: 10.1371/journal.pcbi.1000623. Epub 2009 Dec 24.
Cytoplasmic transport of organelles, nucleic acids and proteins on microtubules is usually bidirectional with dynein and kinesin motors mediating the delivery of cargoes in the cytoplasm. Here we combine live cell microscopy, single virus tracking and trajectory segmentation to systematically identify the parameters of a stochastic computational model of cargo transport by molecular motors on microtubules. The model parameters are identified using an evolutionary optimization algorithm to minimize the Kullback-Leibler divergence between the in silico and the in vivo run length and velocity distributions of the viruses on microtubules. The present stochastic model suggests that bidirectional transport of human adenoviruses can be explained without explicit motor coordination. The model enables the prediction of the number of motors active on the viral cargo during microtubule-dependent motions as well as the number of motor binding sites, with the protein hexon as the binding site for the motors.
细胞质中的细胞器、核酸和蛋白质在微管上的运输通常是双向的，动力蛋白和驱动蛋白介导细胞质中货物的运输。在这里，我们将活细胞显微镜、单病毒跟踪和轨迹分割相结合，系统地确定了微管上分子马达运输货物的随机计算模型的参数。使用进化优化算法来最小化 Kullback-Leibler 散度，以确定模型参数，该散度是在计算机模拟和病毒在微管上的体内运行长度和速度分布之间的差异。本随机模型表明，不需要明确的马达协调就可以解释人类腺病毒的双向运输。该模型能够预测在微管依赖性运动过程中，病毒货物上的活跃马达数量以及马达结合位点的数量，其中蛋白六邻体是马达的结合位点。
