Automating the High-Throughput Screening of Protein-Based Optical Indicators and Actuators

Authors

Jihwan Lee
Beatriz Campillo
Shaminta Hamidian
Zhuohe Liu
Matthew Shorey
François St-Pierre

Publication Date

1-17-2023

Journal

Biochemistry

DOI

10.1021/acs.biochem.2c00357

PMID

36315460

PMCID

PMC9852035

PubMedCentral® Posted Date

1-17-2024

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes

Keywords

Humans, High-Throughput Screening Assays, Proteins, Mutagenesis

Abstract

Over the last 25 years, protein engineers have developed an impressive collection of optical tools to interface with biological systems: indicators to eavesdrop on cellular activity and actuators to poke and prod native processes. To reach the performance level required for their downstream applications, protein-based tools are usually sculpted by iterative rounds of mutagenesis. In each round, libraries of variants are made and evaluated, and the most promising hits are then retrieved, sequenced, and further characterized. Early efforts to engineer protein-based optical tools were largely manual, suffering from low throughput, human error, and tedium. Here, we describe approaches to automating the screening of libraries generated as colonies on agar, multiwell plates, and pooled populations of single-cell variants. We also briefly discuss emerging approaches for screening, including cell-free systems and machine learning.