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Quantifying the Performance of Micro-Compartmentalized Directed Evolution Protocols

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 t...

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Detalles Bibliográficos
Autores principales: Dramé-Maigné, Adèle, Zadorin, Anton S., Golovkova, Iaroslava, Rondelez, Yannick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7175308/
https://www.ncbi.nlm.nih.gov/pubmed/32069848
http://dx.doi.org/10.3390/life10020017
Descripción
Sumario: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.