Univ Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR5558, Villeurbanne, France.
Mol Biol Evol. 2021 Aug 23;38(9):3938-3952. doi: 10.1093/molbev/msab132.
Enzymes speed up reactions that would otherwise be too slow to sustain the metabolism of selfreplicators. Yet, most enzymes seem only moderately efficient, exhibiting kinetic parameters orders of magnitude lower than their expected physically achievable maxima and spanning over surprisingly large ranges of values. Here, we question how these parameters evolve using a mechanistic model where enzyme efficiency is a key component of individual competition for resources. We show that kinetic parameters are under strong directional selection only up to a point, above which enzymes appear to evolve under near-neutrality, thereby confirming the qualitative observation of other modeling approaches. While the existence of a large fitness plateau could potentially explain the extensive variation in enzyme features reported, we show using a population genetics model that such a widespread distribution is an unlikely outcome of evolution on a common landscape, as mutation-selection-drift balance occupy a narrow area even when very moderate biases towards lower efficiency are considered. Instead, differences in the evolutionary context encountered by each enzyme should be involved, such that each evolves on an individual, unique landscape. Our results point to drift and effective population size playing an important role, along with the kinetics of nutrient transporters, the tolerance to high concentrations of intermediate metabolites, and the reversibility of reactions. Enzyme concentration also shapes selection on kinetic parameters, but we show that the joint evolution of concentration and efficiency does not yield extensive variance in evolutionary outcomes when documented costs to protein expression are applied.
酶能加速反应，否则这些反应的速度太慢，无法维持自我复制者的新陈代谢。然而，大多数酶的效率似乎只是中等水平，表现出的动力学参数比其预期的物理可达最大值低几个数量级，并且跨度相当大。在这里，我们使用一种机制模型来质疑这些参数是如何进化的，在这种模型中，酶的效率是个体竞争资源的关键组成部分。我们表明，动力学参数只在一定程度上受到强烈的定向选择，超过这个程度，酶似乎在近中性条件下进化，从而证实了其他建模方法的定性观察。虽然存在一个很大的适应度高原可能可以解释酶特征的广泛变化，但我们使用群体遗传学模型表明，在共同的景观中，这种广泛的分布不太可能是进化的结果，因为即使考虑到非常温和的低效率偏向，突变-选择-漂变平衡也只占据了一个狭窄的区域。相反，每个酶所遇到的进化背景的差异应该涉及其中，使得每个酶都在一个独特的、独特的景观上进化。我们的研究结果表明，漂变和有效种群大小以及营养物质转运蛋白的动力学、对中间代谢物高浓度的耐受性和反应的可逆性都起着重要作用。酶浓度也会影响对动力学参数的选择，但我们表明，当应用蛋白质表达的成本时，浓度和效率的联合进化不会导致进化结果的广泛变化。
