Facile, high‐throughput protein purification enabled by high‐efficiency protease elution

Abstract

While advances in artificial intelligence have made protein design widely accessible, protein production and characterization remain a bottleneck. Protease‐cleavable affinity tags are commonly used to improve yield and purity of recombinant proteins, but tag removal adds labor and complexity. Previous attempts to use a selective protease to elute cleaved fusion protein during affinity chromatography have suffered from poor digestion efficiency that greatly diminishes yield, or protease contamination in the eluate. Here, we describe a novel SUMO protease construct that supports rapid, high‐yield protease elution. This is the keystone of an end‐to‐end DNA‐to‐protein workflow that we optimized for speed, parallelizability, and generalizability. While our workflow is intended for an automated liquid‐handler, it can easily be performed manually, making it broadly accessible. We demonstrate the method by producing and characterizing 96 disparate proteins derived from mesophilic organisms. This provides a benchmark for methods development and a curated dataset useful for machine learning.