Zuo Xinzhe, Chou Tom
Department of Mathematics, UCLA, Los Angeles, CA 90095-1555, United States of America.
Department of Computational Medicine, UCLA, Los Angeles, CA 90095-1766, United States of America.
Phys Biol. 2022 Jan 25;19(2). doi: 10.1088/1478-3975/ac45e2.
Backtracking of RNA polymerase (RNAP) is an important pausing mechanism during DNA transcription that is part of the error correction process that enhances transcription fidelity. We model the backtracking mechanism of RNAP, which usually happens when the polymerase tries to incorporate a noncognate or 'mismatched' nucleotide triphosphate. Previous models have made simplifying assumptions such as neglecting the trailing polymerase behind the backtracking polymerase or assuming that the trailing polymerase is stationary. We derive exact analytic solutions of a stochastic model that includes locally interacting RNAPs by explicitly showing how a trailing RNAP influences the probability that an error is corrected or incorporated by the leading backtracking RNAP. We also provide two related methods for computing the mean times for error correction and incorporation given an initial local RNAP configuration. Using these results, we propose an effective interacting-RNAP lattice that can be readily simulated.
RNA聚合酶(RNAP)回溯是DNA转录过程中的一种重要暂停机制,它是增强转录保真度的纠错过程的一部分。我们对RNAP的回溯机制进行建模,这种情况通常发生在聚合酶试图掺入非同源或“错配”的三磷酸核苷酸时。先前的模型做了一些简化假设,比如忽略回溯聚合酶后面的尾随聚合酶,或者假设尾随聚合酶是静止的。我们通过明确展示尾随RNAP如何影响领先的回溯RNAP纠正或掺入错误的概率,推导出了一个包含局部相互作用RNAP的随机模型的精确解析解。我们还提供了两种相关方法,用于在给定初始局部RNAP构型的情况下计算纠错和掺入的平均时间。利用这些结果,我们提出了一种易于模拟的有效相互作用RNAP晶格。