Discovery And Validation Of High-Efficiency Large Serine Recombinases For Targeted Gene Integration

By Amy Pooler, Avery Roberts, Kristopher Kieft, Tim Schwochert, Malik Moncalvo, Hannah Wiedner, Allie Crawley, Gavin Ellis, Matt Nethery, David Wiley, Chuck Pepe-Ranney, and Ron Chong

Targeted insertion of large genetic payloads requires editing tools that combine efficiency, precision, and flexibility across cell types. Mining a curated bioinformatics database of more than 10 billion proteins enabled researchers to predict over 150 novel large serine recombinase systems, approximately 80% of which demonstrated activity in mammalian cells.

Testing revealed substantial variation in integration efficiency, with some systems exceeding 80% activity in HEK293 cells. A proprietary recombinase also achieved greater than 25% insertion of a CD19-CAR payload in primary human T cells before protein engineering.

Learn more about the potential to identify and improve gene-insertion tools through bioinformatic discovery, active learning, rational design, directed evolution, and generative AI.