蛋白质过剩是生长稳健性的驱动因素

H. James Choi, Teresa W. Lo, Kevin J. Cutler, Dean Huang, W. Ryan Will, Paul A. Wiggins
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引用次数: 0

摘要

蛋白质表达水平可优化细胞的适应性:必需蛋白表达量过低,会影响基本过程,从而减缓生长速度;而表达量过大,则会增加代谢负荷,从而减缓生长速度。这种权衡天真地预测,细胞会通过表达足够的每种必需蛋白来实现其功能的最大化。在这些实验中,当目标蛋白水平从内源水平稀释时,细胞会增殖多代。在这些实验中,细胞会增殖多代,目标蛋白水平会从内源水平被稀释。这种方法有助于在蛋白质组范围内分析蛋白质过量。正如稳健性-负载权衡(RLTO)模型所预测的那样,我们发现大约 70% 的重要蛋白质过量表达,而且随着表达水平的降低,过量表达的程度也在增加,这正是该模型的特征性预测。这些结果表明,稳健性在决定重要基因的表达水平方面起着根本性的作用,而过量表达是确保稳健生长的关键机制。
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Protein overabundance is driven by growth robustness
Protein expression levels optimize cell fitness: Too low an expression level of essential proteins will slow growth by compromising essential processes; whereas overexpression slows growth by increasing the metabolic load. This trade-off naively predicts that cells maximize their fitness by sufficiency, expressing just enough of each essential protein for function. We test this prediction in the naturally-competent bacterium Acinetobacter baylyi by characterizing the proliferation dynamics of essential-gene knockouts at a single-cell scale (by imaging) as well as at a genome-wide scale (by TFNseq). In these experiments, cells proliferate for multiple generations as target protein levels are diluted from their endogenous levels. This approach facilitates a proteome-scale analysis of protein overabundance. As predicted by the Robustness-Load Trade-Off (RLTO) model, we find that roughly 70% of essential proteins are overabundant and that overabundance increases as the expression level decreases, the signature prediction of the model. These results reveal that robustness plays a fundamental role in determining the expression levels of essential genes and that overabundance is a key mechanism for ensuring robust growth.
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