Compound Delivery of eVLPs Enhances Prime Editing for Targeted Genome Engineering and High-Throughput Screening

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Engineered virus-like particles (eVLPs) enable transgene-free ribonucleoprotein delivery for genome editing applications, yet optimized delivery strategies for high-throughput applications remain unexplored. Prime editing enables precise genomic modifications but suffers from limited efficiency that constrains its widespread adoption. Here, we present PRIME-VLP (Progressive Repeated Infections for Maximized Editing via Virus-Like Particles), a delivery strategy that enhances prime editing efficiency for both targeted genome engineering and high-throughput prime editing screening. PRIME-VLP leverages the temporal dynamics of eVLP-mediated editing through multiple sequential transductions with sub-saturating eVLP doses delivered at optimal intervals. This approach achieves 1.5 to 2.8-fold improvements in editing efficiency across diverse genomic targets and cell types. PRIME-VLP maintains high specificity without increasing off-target effects, compromising cellular viability or causing transcriptional perturbations. By decoupling pegRNA and editor delivery through pegRNA-free eVLPs, PRIME-VLP enables pooled prime editing screens, circumventing transgene silencing limitations of conventional lentiviral-based screens. Using a 6,000-pegRNA library targeting TP53 , PRIME-VLP achieved 2.8-fold higher editing efficiency and improved reproducibility compared to conventional lentiviral delivery. An eVLP-based screen identified functional TP53 loss-of-function variants that confer resistance to MDM2 inhibition by Nutlin-3. This work expands the versatility of eVLPs beyond their current in vivo therapeutic applications, demonstrating their promise for high-throughput functional genomics by overcoming the delivery limitations of lentiviral systems.

Article activity feed