Survival of the cheapest: how proteome cost minimization drives evolution.

IF 7.2 2区 生物学 Q1 BIOPHYSICS Quarterly Reviews of Biophysics Pub Date : 2020-06-23 DOI:10.1017/S0033583520000037
Kasper P Kepp
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引用次数: 9

Abstract

Darwin's theory of evolution emphasized that positive selection of functional proficiency provides the fitness that ultimately determines the structure of life, a view that has dominated biochemical thinking of enzymes as perfectly optimized for their specific functions. The 20th-century modern synthesis, structural biology, and the central dogma explained the machinery of evolution, and nearly neutral theory explained how selection competes with random fixation dynamics that produce molecular clocks essential e.g. for dating evolutionary histories. However, quantitative proteomics revealed that selection pressures not relating to optimal function play much larger roles than previously thought, acting perhaps most importantly via protein expression levels. This paper first summarizes recent progress in the 21st century toward recovering this universal selection pressure. Then, the paper argues that proteome cost minimization is the dominant, underlying 'non-function' selection pressure controlling most of the evolution of already functionally adapted living systems. A theory of proteome cost minimization is described and argued to have consequences for understanding evolutionary trade-offs, aging, cancer, and neurodegenerative protein-misfolding diseases.

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最便宜的生存:蛋白质组成本最小化如何驱动进化。
达尔文的进化论强调,功能熟练度的积极选择提供了最终决定生命结构的适应性,这一观点主导了酶的生化思想,认为酶是其特定功能的完美优化。20世纪的现代合成、结构生物学和中心教条解释了进化的机制,而近乎中性的理论解释了选择如何与产生分子钟的随机固定动力学竞争,这些分子钟对于确定进化史的年代至关重要。然而,定量蛋白质组学揭示了与最佳功能无关的选择压力比以前认为的要大得多,可能最重要的是通过蛋白质表达水平起作用。本文首先总结了21世纪在恢复这种普遍选择压力方面的最新进展。然后,本文认为蛋白质组成本最小化是主导的,潜在的“非功能”选择压力,控制着已经功能适应的生命系统的大部分进化。一种蛋白质组成本最小化理论被描述和论证为理解进化权衡、衰老、癌症和神经退行性蛋白质错误折叠疾病的后果。
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来源期刊
Quarterly Reviews of Biophysics
Quarterly Reviews of Biophysics 生物-生物物理
CiteScore
12.90
自引率
1.60%
发文量
16
期刊介绍: Quarterly Reviews of Biophysics covers the field of experimental and computational biophysics. Experimental biophysics span across different physics-based measurements such as optical microscopy, super-resolution imaging, electron microscopy, X-ray and neutron diffraction, spectroscopy, calorimetry, thermodynamics and their integrated uses. Computational biophysics includes theory, simulations, bioinformatics and system analysis. These biophysical methodologies are used to discover the structure, function and physiology of biological systems in varying complexities from cells, organelles, membranes, protein-nucleic acid complexes, molecular machines to molecules. The majority of reviews published are invited from authors who have made significant contributions to the field, who give critical, readable and sometimes controversial accounts of recent progress and problems in their specialty. The journal has long-standing, worldwide reputation, demonstrated by its high ranking in the ISI Science Citation Index, as a forum for general and specialized communication between biophysicists working in different areas. Thematic issues are occasionally published.
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