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

Area of Science:

• Biochemistry
• Molecular Biology
• Protein Engineering

Background:

• Protein design is advancing rapidly due to AI, but protein production and characterization remain challenging bottlenecks.
• Protease-cleavable affinity tags aid recombinant protein yield and purity but require additional labor for tag removal.
• Previous methods for protease-mediated tag removal during affinity chromatography suffered from low efficiency or protease contamination.

Purpose of the Study:

• To develop a novel, efficient, and broadly accessible end-to-end DNA-to-protein workflow.
• To overcome limitations of existing methods for recombinant protein purification and tag removal.
• To establish a benchmark for protein production methods and generate a dataset for machine learning.

Main Methods:

• Development of a novel SUMO protease construct for rapid, high-yield protease elution.
• Optimization of an end-to-end DNA-to-protein workflow for speed, parallelization, and generalizability.
• Demonstration of the workflow through the production and characterization of 96 diverse proteins.

Main Results:

• The novel SUMO protease construct enables rapid and high-yield elution of cleaved fusion proteins.
• The optimized workflow significantly improves speed and efficiency in recombinant protein production.
• Successful production and characterization of 96 disparate proteins were achieved, validating the method's broad applicability.

Conclusions:

• A novel protease-based workflow significantly enhances recombinant protein production and purification efficiency.
• The developed method is broadly accessible, adaptable for both automated and manual execution.
• The study provides a valuable benchmark and dataset for future protein engineering and machine learning applications.