Systematic profiling of conditional degron tag technologies for target validation studies

• Published in: Nature communications Vol. 13; no. 1; p. 5495
• Main Authors: Bondeson, Daniel P., Mullin-Bernstein, Zachary, Oliver, Sydney, Skipper, Thomas A., Atack, Thomas C., Bick, Nolan, Ching, Meilani, Guirguis, Andrew A., Kwon, Jason, Langan, Carly, Millson, Dylan, Paolella, Brenton R., Tran, Kevin, Wie, Sarah J., Vazquez, Francisca, Tothova, Zuzana, Golub, Todd R., Sellers, William R., Ianari, Alessandra
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 20.09.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 13; 13/106; 13/107; 13/44; 38; 38/1; 631/1647; 631/1647/1511; 631/92/469; 631/92/556; Degradation; Design; Fusion protein; Humanities and Social Sciences; multidisciplinary; Proteins; Reagents; Science; Science (multidisciplinary); Tags; Therapeutic targets
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-022-33246-4

Conditional degron tags (CDTs) are a powerful tool for target validation that combines the kinetics and reversible action of pharmacological agents with the generalizability of genetic manipulation. However, successful design of a CDT fusion protein often requires a prolonged, ad hoc cycle of construct design, failure, and re-design. To address this limitation, we report here a system to rapidly compare the activity of five unique CDTs: AID/AID2, IKZF3d, dTAG, HaloTag, and SMASh. We demonstrate the utility of this system against 16 unique protein targets. We find that expression and degradation are highly dependent on the specific CDT, the construct design, and the target. None of the CDTs leads to efficient expression and/or degradation across all targets; however, our systematic approach enables the identification of at least one optimal CDT fusion for each target. To enable the adoption of CDT strategies more broadly, we have made these reagents, and a detailed protocol, available as a community resource. Conditional Degron Tags are a valuable tool to validate and study novel therapeutic targets. Here, the authors compared 5 orthogonal tags across 16 unique proteins and provide a panel of vectors for users to systematically screen the tags with their own protein of interest.