Dramé-Maigné Adèle, Zadorin Anton S, Golovkova Iaroslava, Rondelez Yannick
Laboratoire Gulliver, ESPCI Paris, PSL Research University, 10 rue Vauquelin, 75005 Paris, France.
Laboratoire CBI, ESPCI Paris, PSL Research University, 10 rue Vauquelin, 75005 Paris, France.
Life (Basel). 2020 Feb 13;10(2):17. doi: 10.3390/life10020017.
High-throughput, in vitro approaches for the evolution of enzymes rely on a random micro-encapsulation to link phenotypes to genotypes, followed by screening or selection steps. In order to optimise these approaches, or compare one to another, one needs a measure of their performance at extracting the best variants of a library. Here, we introduce a new metric, the Selection Quality Index (SQI), which can be computed from a simple mock experiment, performed with a known initial fraction of active variants. In contrast to previous approaches, our index integrates the effect of random co-encapsulation, and comes with a straightforward experimental interpretation. We further show how this new metric can be used to extract general protocol efficiency trends or reveal hidden selection mechanisms such as a counterintuitive form of beneficial poisoning in the compartmentalized self-replication protocol.
用于酶进化的高通量体外方法依赖于随机微囊化将表型与基因型联系起来，随后进行筛选或选择步骤。为了优化这些方法或相互比较，需要一种衡量它们在从文库中提取最佳变体方面性能的指标。在此，我们引入了一种新的指标，即选择质量指数（SQI），它可以通过一个简单的模拟实验计算得出，该实验使用已知初始比例的活性变体进行。与先前的方法不同，我们的指标整合了随机共包封的影响，并且具有直接的实验解释。我们进一步展示了如何使用这个新指标来提取通用方案效率趋势或揭示隐藏的选择机制，例如在区室化自我复制方案中一种违反直觉的有益中毒形式。
