Maitra Arijit, Dill Ken A
Laufer Center for Physical and Quantitative Biology and the Departments of Chemistry and Physics, Stony Brook University, Stony Brook, NY 11794
Proc Natl Acad Sci U S A. 2015 Jan 13;112(2):406-11. doi: 10.1073/pnas.1421138111. Epub 2014 Dec 29.
We are interested in the balance of energy and protein synthesis in bacterial growth. How has evolution optimized this balance? We describe an analytical model that leverages extensive literature data on growth laws to infer the underlying fitness landscape and to draw inferences about what evolution has optimized in Escherichia coli. Is E. coli optimized for growth speed, energy efficiency, or some other property? Experimental data show that at its replication speed limit, E. coli produces about four mass equivalents of nonribosomal proteins for every mass equivalent of ribosomes. This ratio can be explained if the cell's fitness function is the the energy efficiency of cells under fast growth conditions, indicating a tradeoff between the high energy costs of ribosomes under fast growth and the high energy costs of turning over nonribosomal proteins under slow growth. This model gives insight into some of the complex nonlinear relationships between energy utilization and ribosomal and nonribosomal production as a function of cell growth conditions.
我们对细菌生长过程中能量与蛋白质合成的平衡感兴趣。进化是如何优化这种平衡的呢？我们描述了一个分析模型，该模型利用关于生长规律的大量文献数据来推断潜在的适应度景观，并对大肠杆菌中进化所优化的内容进行推断。大肠杆菌是针对生长速度、能量效率还是其他某种特性进行了优化呢？实验数据表明，在其复制速度极限下，大肠杆菌每产生一个质量当量的核糖体，就会产生大约四个质量当量的非核糖体蛋白。如果细胞的适应度函数是快速生长条件下细胞的能量效率，那么这个比例就可以得到解释，这表明在快速生长时核糖体的高能量成本与缓慢生长时非核糖体蛋白周转的高能量成本之间存在权衡。该模型揭示了能量利用与核糖体及非核糖体产生之间一些复杂的非线性关系，这些关系是细胞生长条件的函数。
