Extracting dwell time sequences from processive molecular motor data
Extracting dwell time sequences from processive molecular motor data
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DOI：
10.1529/biophysj.105.079517
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发表时间：
2006-11-01
影响因子：
3.4
通讯作者：
Sachs, Frederick
中科院分区：
文献类型：
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作者：
Milescu, Lorin S.;Yildiz, Ahmet;Sachs, Frederick
过程性分子马达，如驱动蛋白、肌球蛋白或动力蛋白，通过水解ATP将化学能转化为机械能。机械能用于沿着细胞骨架以离散步骤移动并携带分子载荷。单分子记录电机位置沿着基板聚合物出现作为一个随机的阶梯。其他单分子的记录，如F1-ATP酶、RNA聚合酶或拓扑异构酶，具有相同的外观。我们提出了一个最大似然算法，从噪声数据中提取停留时间序列，并估计状态转移概率和电机步长的分布。该算法可以处理具有均匀或交替步长以及可逆或不可逆动力学的模型。周期性马尔可夫模型描述了电机的重复化学反应，卡尔曼滤波器允许包括具有可变步长的模型并校正基线漂移。数据在单个或多个数据集上进行递归和全局优化，使结果在数据的整个范围内都是客观的。局部二进制算法，如t检验，不能代表整个数据集的行为。我们的方法是基于模型的，并允许快速测试不同的模型通过比较的可能性得分。从目前的技术获得的数据，小到8纳米的步骤可以解决和分析与我们的方法。可以进一步详细分析提取的停留序列的动力学后果。我们展示了从分析模拟和实验驱动蛋白和肌球蛋白电机数据的结果。该算法在免费的QuB软件中实现。
Processive molecular motors, such as kinesin, myosin, or dynein, convert chemical energy into mechanical energy by hydrolyzing ATP. The mechanical energy is used for moving in discrete steps along the cytoskeleton and carrying a molecular load. Single-molecule recordings of motor position along a substrate polymer appear as a stochastic staircase. Recordings of other single molecules, such as F1-ATPase, RNA polymerase, or topoisomerase, have the same appearance. We present a maximum likelihood algorithm that extracts the dwell time sequence from noisy data, and estimates state transition probabilities and the distribution of the motor step size. The algorithm can handle models with uniform or alternating step sizes, and reversible or irreversible kinetics. A periodic Markov model describes the repetitive chemistry of the motor, and a Kalman filter allows one to include models with variable step size and to correct for baseline drift. The data are optimized recursively and globally over single or multiple data sets, making the results objective over the full scale of the data. Local binary algorithms, such as the t-test, do not represent the behavior of the whole data set. Our method is model-based, and allows rapid testing of different models by comparing the likelihood scores. From data obtained with current technology, steps as small as 8 nm can be resolved and analyzed with our method. The kinetic consequences of the extracted dwell sequence can be further analyzed in detail. We show results from analyzing simulated and experimental kinesin and myosin motor data. The algorithm is implemented in the free QuB software.