Kepp Kasper P, Dasmeh Pouria
Department of Chemistry, Technical University of Denmark, Kongens Lyngby, Denmark.
PLoS One. 2014 Feb 28;9(2):e90504. doi: 10.1371/journal.pone.0090504. eCollection 2014.
A model of proteome-associated chemical energetic costs of cells is derived from protein-turnover kinetics and protein folding. Minimization of the proteostatic maintenance cost can explain a range of trends of proteomes and combines both protein function, stability, size, proteostatic cost, temperature, resource availability, and turnover rates in one simple framework. We then explore the ansatz that the chemical energy remaining after proteostatic maintenance is available for reproduction (or cell division) and thus, proportional to organism fitness. Selection for lower proteostatic costs is then shown to be significant vs. typical effective population sizes of yeast. The model explains and quantifies evolutionary conservation of highly abundant proteins as arising both from functional mutations and from changes in other properties such as stability, cost, or turnover rates. We show that typical hypomorphic mutations can be selected against due to increased cost of compensatory protein expression (both in the mutated gene and in related genes, i.e. epistasis) rather than compromised function itself, although this compensation depends on the protein's importance. Such mutations exhibit larger selective disadvantage in abundant, large, synthetically costly, and/or short-lived proteins. Selection against increased turnover costs of less stable proteins rather than misfolding toxicity per se can explain equilibrium protein stability distributions, in agreement with recent findings in E. coli. The proteostatic selection pressure is stronger at low metabolic rates (i.e. scarce environments) and in hot habitats, explaining proteome adaptations towards rough environments as a question of energy. The model may also explain several trade-offs observed in protein evolution and suggests how protein properties can coevolve to maintain low proteostatic cost.
基于蛋白质周转动力学和蛋白质折叠，推导出了一种细胞蛋白质组相关化学能量成本模型。蛋白质稳态维持成本的最小化能够解释蛋白质组的一系列趋势，并在一个简单的框架内综合了蛋白质功能、稳定性、大小、蛋白质稳态成本、温度、资源可用性和周转率等因素。然后，我们探讨了这样一种假设：蛋白质稳态维持后剩余的化学能量可用于繁殖（或细胞分裂），因此与生物体适应性成正比。结果表明，与酵母典型的有效种群大小相比，选择较低的蛋白质稳态成本具有重要意义。该模型解释并量化了高丰度蛋白质的进化保守性，认为这既源于功能突变，也源于其他特性（如稳定性、成本或周转率）的变化。我们发现，典型的亚效突变可能由于补偿性蛋白质表达成本增加（在突变基因和相关基因中，即上位性）而被选择淘汰，而非功能本身受损，尽管这种补偿取决于蛋白质的重要性。此类突变在丰度高、体积大、合成成本高和/或寿命短的蛋白质中表现出更大的选择劣势。选择淘汰不稳定蛋白质增加的周转成本而非错误折叠毒性本身，可以解释蛋白质稳定性的平衡分布，这与大肠杆菌最近的研究结果一致。在低代谢率（即稀缺环境）和炎热栖息地中，蛋白质稳态选择压力更强，这将蛋白质组对恶劣环境的适应性解释为一个能量问题。该模型还可以解释蛋白质进化中观察到的几种权衡，并提出蛋白质特性如何协同进化以维持较低的蛋白质稳态成本。
