Simple biological controllers drive the evolution of soft modes.

ArXiv Pub Date : 2025-07-16
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Abstract

Biological systems, with many interacting components, face high-dimensional environmental fluctuations, ranging from diverse nutrient deprivations to toxins, drugs, and physical stresses. Yet, many biological control mechanisms are `simple' -- they restore homeostasis through low-dimensional representations of the system's high-dimensional state. How do low-dimensional controllers maintain homeostasis in high-dimensional systems? We develop an analytically tractable model of integral feedback for complex systems in fluctuating environments. We find that selection for homeostasis leads to the emergence of a soft mode that provides the dimensionality reduction required for the functioning of simple controllers. Our theory predicts that simple controllers that buffer environmental perturbations (e.g., stress response pathways) will also buffer mutational perturbation, an equivalence we test using experimental data across ~5000 strains in the yeast knockout collection. We also predict, counterintuitively, that knocking out a simple controller will \emph{decrease} the dimensionality of the response to environmental change; we outline transcriptomics tests to validate this. Our work suggests an evolutionary origin of soft modes whose function is for dimensionality reduction in and of itself rather than direct function like allostery, with implications ranging from cryptic genetic variation to global epistasis.

简单的生物控制器驱动着软模式的进化。
生物系统有许多相互作用的组成部分,面临着高维的环境波动,从各种营养物质的剥夺到毒素、药物和物理压力。然而,许多生物控制机制是“简单的”——它们通过系统高维状态的低维表示来恢复体内平衡。低维控制器如何在高维系统中维持稳态?本文建立了复杂系统在波动环境下积分反馈的解析可处理模型。我们发现,对稳态的选择导致了一种软模式的出现,这种模式提供了简单控制器功能所需的降维。我们的理论预测,缓冲环境扰动(例如,应激反应途径)的简单控制器也将缓冲突变扰动,我们使用酵母敲除收集的5000株的实验数据来测试等效性。我们还预测,与直觉相反,取消一个简单的控制器将\emph{降低}对环境变化的响应维度;我们概述了转录组学测试来验证这一点。我们的研究表明,软模式的进化起源,其功能是自身的维数降低,而不是像变构这样的直接功能,其含义从隐遗传变异到全局上位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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