Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
Departamento de Sanidad Animal and VISAVET Health Surveillance Centre, Universidad Complutense de Madrid, Madrid, Spain.
Science. 2023 Nov 24;382(6673):eadh3860. doi: 10.1126/science.adh3860.
Fitness landscape theory predicts that rugged landscapes with multiple peaks impair Darwinian evolution, but experimental evidence is limited. In this study, we used genome editing to map the fitness of >260,000 genotypes of the key metabolic enzyme dihydrofolate reductase in the presence of the antibiotic trimethoprim, which targets this enzyme. The resulting landscape is highly rugged and harbors 514 fitness peaks. However, its highest peaks are accessible to evolving populations via abundant fitness-increasing paths. Different peaks share large basins of attraction that render the outcome of adaptive evolution highly contingent on chance events. Our work shows that ruggedness need not be an obstacle to Darwinian evolution but can reduce its predictability. If true in general, the complexity of optimization problems on realistic landscapes may require reappraisal.
适应景观理论预测,具有多个峰值的崎岖景观会损害达尔文式进化,但实验证据有限。在这项研究中,我们使用基因组编辑来绘制关键代谢酶二氢叶酸还原酶在抗生素甲氧苄啶存在下超过 260,000 种基因型的适应性,该抗生素靶向这种酶。得到的景观非常崎岖,有 514 个适应峰。然而,其最高的峰可以通过丰富的适应性增加途径被进化种群到达。不同的峰共享大量的吸引盆地,使得适应性进化的结果高度依赖于偶然事件。我们的工作表明,崎岖不平不一定是达尔文式进化的障碍,但可以降低其可预测性。如果普遍如此,那么在现实景观上的优化问题的复杂性可能需要重新评估。