Quantifying the performance of high-throughput directed evolution protocols

TL;DR

This paper introduces the Selection Quality Index (SQI), a new metric for evaluating high-throughput directed evolution protocols, accounting for random encapsulation effects and enabling better comparison and optimization.

Contribution

The paper presents the SQI metric, which provides a straightforward, interpretable measure of protocol performance that considers random co-encapsulation effects in directed evolution.

Findings

SQI effectively measures protocol efficiency.

The metric reveals hidden mechanisms like beneficial poisoning.

It enables comparison and optimization of different protocols.

Abstract

Most protocols for the high-throughput directed evolution of enzymes rely on random encapsulation to link phenotype and genotype. In order to optimize these approaches, or compare one to another, one needs a measure of their performance at extracting the best variants. We introduce here a new metric named the Selection Quality Index (SQI), which can be computed from a simple mock experiment with a known initial fraction of active variants. As opposed to previous approaches, our index integrates the random co-encapsulation of entities in compartments and comes with a straightforward experimental interpretation. We further show how this new metric can be used to extract general trends of protocol efficiency, or reveal hidden mechanisms such as a counterintuitive form of beneficial poisoning in the Compartmentalized Self-Replication protocol.