Corri Hickson

Corri, a sophomore studying Chemistry at Amherst College, optimized prime editing for targeted protein degradation.

Degron tags are small amino acid sequences that can be recognized by intracellular proteases, leading to the degradation of a protein of interest. Degron tags have shown to be valuable tools in several fields as they can degrade previously undruggable proteins by being inserted in the N- or C-terminus of the protein of interest. Participating in BSRP was a life-changing experience in all aspects of life. I gained so much knowledge about being a scientist in and out of the lab and the importance of mentorship. For once, I felt like I belonged, and I feel confident that I can thrive and accomplish so much in the scientific world thanks to BSRP. However, most tags are too large for insertion using gene editing tools. The Liu lab recently evolved their degron tag, SD40, which is small enough for insertion via twin prime editing (twinPE). TwinPE uses two prime editors to insert double-stranded DNA fragments like SD40 in the genome without causing unwanted mutations. Using twin PE to insert SD40 into proteins of interest requires careful optimization of its prime editing guide RNAs (PegRNAs). Here, we optimized the insertion of SD40 into MAT2A and SHOC2, two undruggable proteins involved in cancer. We perform two PegRNAs screens to find (1) the optimal spacer combination and (2) the optimal primer binding site (PBS) and reverse transcriptase template (RTT) lengths for twin PE. Our results from the spacer screen show SD40 insertion into MAT2A with .5% and SHOC2 with 2% editing. With these spacer combinations, ongoing work will focus on screening optimal PBS/RTT lengths to obtain a high insertion of SD40. Together, this work will show the effectiveness of TwinPE in installing SD40 as a powerful degron tag for targeting undruggable proteins for degradation.

Project: Optimizing Prime Editing Insertion of Degron Tags for Targeted Protein Degradation

Mentors: Kiara Berríos-Adorno & Jaron Mercer

PI: David Liu Lab