Nonviral delivery techniques for in vivo prime editing

Gene editing is a promising strategy for treating or even permanently curing genetic diseases. In
particular, a new technique called prime editing has the potential to make small targeted
insertions, deletions, and substitutions with very high potential coverage of known disease-
causing mutations, and while minimizing dangerous double-stranded breaks in DNA. In order to
realize this potential, robust delivery strategies must be developed to deliver prime editing tools
efficiently to disease-relevant organs. One such delivery strategy is lipid nanoparticle delivery of
RNA and/or protein-based prime editing components. LNPs are nonviral, nontoxic, and clinically
validated delivery tools. However, there is an extremely diverse space of possible LNPs, with
tens of thousands of potential lipid structures that may be useful for LNP delivery. Selecting the
best possible LNP for a prime editing application, therefore, is challenging because in vitro
testing is often unreliable and in vivo testing of one LNP at a time is extremely low throughput.
Here, we propose to combine two scalable techniques to generate and test safe, potent LNP
formulations for performing prime editing. First, we will employ combinatorial chemistry
techniques to generate large libraries of biodegradable lipids for inclusion into LNPs. Second,
we will introduce a new technique which we term pegRNA barcoding to screen dozens to
hundreds of LNPs for successful prime editing in a single mouse. We will employ this technique
to identify the best biodegradable LNPs for editing of multiple organs, including in particular the
lung and the liver. Having identified the top candidates, we will proceed to use our LNPs to
apply prime editing to treat mouse models of two different inherited genetic diseases: hereditary
tyrosinemia type I (HTI), a liver disease, and cystic fibrosis (CF), primarily a lung disease. We
will evaluate the efficiency of prime editing, the levels of undesired editing events, and
phenotypic correction of these mice. The results may identify promising preclinical candidates
for the treatment of HTI, CF, and many other lung and liver diseases.

Grant Number: 5R01HL162564-05
NIH Institute/Center: NIH
Principal Investigator: DANIEL ANDERSON