Cheating the Cheater: Suppressing False-Positive Enrichment during Biosensor-Guided Biocatalyst Engineering

生物传感器 定向进化 人口 化学 生物催化 生物化学 计算生物学 突变体 生物 基因 医学 离子液体 催化作用 环境卫生
作者
Vikas D. Trivedi,Karishma Mohan,Todd C. Chappell,Zachary J. S. Mays,Nikhil U. Nair
出处
期刊:ACS Synthetic Biology [American Chemical Society]
卷期号:11 (1): 420-429 被引量:16
标识
DOI:10.1021/acssynbio.1c00506
摘要

Transcription factor (TF)-based biosensors are very desirable reagents for high-throughput enzyme and strain engineering campaigns. Despite their potential, they are often difficult to deploy effectively as the small molecules being detected can leak out of high-producer cells, into low-producer cells, and activate the biosensor therein. This crosstalk leads to the overrepresentation of false-positive/cheater cells in the enriched population. While the host cell can be engineered to minimize crosstalk (e.g., by deleting responsible transporters), this is not easily applicable to all molecules of interest, particularly those that can diffuse passively. One such biosensor recently reported for trans-cinnamic acid (tCA) suffers from crosstalk when used for phenylalanine ammonia-lyase (PAL) enzyme engineering by directed evolution. We report that desensitizing the biosensor (i.e., increasing the limit of detection) suppresses cheater population enrichment. Furthermore, we show that, if we couple the biosensor-based screen with an orthogonal prescreen that eliminates a large fraction of true negatives, we can successfully reduce the cheater population during the fluorescence-activated cell sorting. Using the approach developed here, we were successfully able to isolate PAL variants with ∼70% higher kcat after a single sort. These mutants have tremendous potential in phenylketonuria (PKU) treatment and flavonoid production.
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