Russo Christopher Joel, Husain Kabir, Murugan Arvind
James Franck Institute, University of Chicago, Chicago, United States.
Program in Biophysical Sciences, University of Chicago, Chicago, United States.
ArXiv. 2024 Dec 18:arXiv:2412.13637v1.
All biological systems are subject to perturbations: due to thermal fluctuations, external environments, or mutations. Yet, while biological systems are composed of thousands of interacting components, recent high-throughput experiments show that their response to perturbations is surprisingly low-dimensional: confined to only a few stereotyped changes out of the many possible. Here, we explore a unifying dynamical systems framework - soft modes - to explain and analyze low-dimensionality in biology, from molecules to eco-systems. We argue that this one framework of soft modes makes non-trivial predictions that generalize classic ideas from developmental biology to disparate systems, namely: phenocopying, dual buffering, and global epistasis. While some of these predictions have been borne out in experiments, we discuss how soft modes allow for a surprisingly far-reaching and unifying framework in which to analyze data from protein biophysics to microbial ecology.
这是由热涨落、外部环境或突变引起的。然而，尽管生物系统由数千个相互作用的组件组成，但最近的高通量实验表明，它们对干扰的响应惊人地低维：在众多可能的变化中，仅局限于少数几种固定模式的变化。在这里，我们探索一个统一的动力系统框架——软模式，以解释和分析从分子到生态系统的生物学中的低维性。我们认为，这个软模式框架做出了不平凡的预测，将发育生物学中的经典概念推广到了不同的系统，即：表型模拟、双重缓冲和全局上位性。虽然其中一些预测已在实验中得到证实，但我们讨论了软模式如何提供一个惊人地具有深远意义且统一的框架，用于分析从蛋白质生物物理学到微生物生态学的数据。
