Department of Chemistry, University of Illinois, Urbana, IL, 61801, United States of America. National Center for Supercomputing Applications, University of Illinois, Urbana, IL, 61801, United States of America.
Rep Prog Phys. 2018 May;81(5):052601. doi: 10.1088/1361-6633/aaae2c. Epub 2018 Feb 9.
The last few decades have revealed the living cell to be a crowded spatially heterogeneous space teeming with biomolecules whose concentrations and activities are governed by intrinsically random forces. It is from this randomness, however, that a vast array of precisely timed and intricately coordinated biological functions emerge that give rise to the complex forms and behaviors we see in the biosphere around us. This seemingly paradoxical nature of life has drawn the interest of an increasing number of physicists, and recent years have seen stochastic modeling grow into a major subdiscipline within biological physics. Here we review some of the major advances that have shaped our understanding of stochasticity in biology. We begin with some historical context, outlining a string of important experimental results that motivated the development of stochastic modeling. We then embark upon a fairly rigorous treatment of the simulation methods that are currently available for the treatment of stochastic biological models, with an eye toward comparing and contrasting their realms of applicability, and the care that must be taken when parameterizing them. Following that, we describe how stochasticity impacts several key biological functions, including transcription, translation, ribosome biogenesis, chromosome replication, and metabolism, before considering how the functions may be coupled into a comprehensive model of a 'minimal cell'. Finally, we close with our expectation for the future of the field, focusing on how mesoscopic stochastic methods may be augmented with atomic-scale molecular modeling approaches in order to understand life across a range of length and time scales.
过去几十年的研究揭示了活细胞是一个拥挤的、空间不均匀的环境，充满了生物分子，其浓度和活性受内在随机力的控制。然而，正是这种随机性产生了大量精确定时和错综复杂协调的生物功能，这些功能产生了我们在周围生物圈中看到的复杂形态和行为。生命的这种看似矛盾的本质引起了越来越多物理学家的兴趣，近年来，随机建模已发展成为生物物理中的一个主要分支。在这里，我们回顾了一些重大进展，这些进展塑造了我们对生物学中随机性的理解。我们首先介绍一些历史背景，概述了一系列重要的实验结果，这些结果激发了随机建模的发展。然后，我们对当前可用于处理随机生物模型的模拟方法进行了相当严格的处理，着眼于比较和对比它们的适用范围，以及在对其进行参数化时必须注意的事项。之后，我们描述了随机性如何影响转录、翻译、核糖体生物发生、染色体复制和代谢等几个关键的生物学功能，然后考虑如何将这些功能耦合到一个“最小细胞”的综合模型中。最后，我们对该领域的未来进行了展望，重点介绍了如何通过原子尺度的分子建模方法来增强介观随机方法，以便在各种长度和时间尺度上理解生命。
