Accelerating the development and application of genetic medicines

Abstract

Precision gene editing offers the promise of permanently correcting alleles that cause disease in the genomes of living individuals with one-time treatments. Making this promise a reality has been a major objective of molecular biology and genetics since the descriptions of the mutations that cause cystic fibrosis—the first for any genetic disease—were reported in 1989. My doctoral work has focused on developing and applying precision gene editing technologies to correct cystic fibrosis-causing pathogenic mutations at ever increasing scales. In Chapter 1, I discuss cystic fibrosis, an autosomal recessive disease arising from loss-of-function mutations in the CFTR gene. I summarize the pathogenesis and genetic epidemiology of the disease, and I describe the profound need for highly effective medicines that correct cystic fibrosis-causing alleles in the age of highly effective CFTR modulator therapies. I also illustrate how recent advances in gene editing technologies enable us to explore the development of genetic medicines at scale in different ways. In Chapter 2, I describe the systematic optimization of prime editing to efficiently correct CFTR.F508∆, a three-nucleotide deletion that is the predominant cause of cystic fibrosis. By combining six recent advances in prime editing—epegRNAs, the PEmax architecture, MLH1dn, strategic silent edits, PE6, and dsgRNAs—we increased CFTR.F508∆ correction efficiency from .5% in model HEK293T cell lines to 58% in therapeutically relevant immortalized bronchial epithelial cells. In primary airway epithelial cells derived from people with cystic fibrosis, the optimized prime editing strategy enabled 25% precise correction of CFTR.F508∆, a 140-fold improvement over initial prime editing systems, with a 3.4-fold higher edit-to-indel ratio than nuclease-mediated homology directed repair approaches, and minimal off-target editing. Editing primary airway cell cultures restored CFTR ion channel function to >50% of wild-type levels, comparable to treatment with the modulator drug combination elexacaftor/tezacaftor/ivacaftor. Direct and efficient correction of CFTR.F508∆ suggests a durable one-time treatment for cystic fibrosis and provides a blueprint for optimizing prime editing to correct other pathogenic gene variants, including the >1000 other cystic fibrosis-causing alleles that have been described to date. In Chapter 3, I present work that explores a variety of therapeutically viable viral and nonviral strategies for the efficient delivery of CFTR-correcting prime editors to the airway. Building on the high-potency CFTR.F508∆ gene editing strategies we devised in Chapter 2, we formulate helper-dependent adenoviral vectors (HD-Ad), engineered virus-like particles (eVLPs), and lipid nanoparticles (LNPs) for the delivery of prime editors to both differentiated and undifferentiated primary airway cells as well as to human bronchial epithelial cell lines. We demonstrate functional restoration of CFTR-mediated channel currents that approaches the efficacy of existing small molecule modulator drugs by delivering CFTR.F508∆-correcting prime editors via HD-Ad and eVLPs. We also develop a prime editing formulation for the modulator-ineligible allele CFTR.G542X that achieves 40% correction efficiency when delivered to 16HBEge cells via LNPs. To enable efficient packaging of CFTR-correcting prime editors into dual adeno-associated viral (AAV) vectors, we assess the ability of size-minimized SpCas9 domains to support prime editing. Our work provides insight into the relationship between editing efficiency and functional correction for CFTR, suggesting that modest (~3%) editing efficiencies can restore CFTR function to therapeutic levels but that 15-20% correction is likely needed to match the functional levels of current standard-of-care modulators. These proof-of-concept in vitro experiments lay a foundation for the evaluation of diverse delivery modalities to correct CFTR via prime editing in the airways of animal models. In Chapter 4, I summarize efforts to leverage self-targeting lentiviral screens to accelerate the optimization of prime editing formulations for therapeutic applications. We describe LVPrime, a computational toolkit that facilitates the design and analysis of self-targeting lentiviral screens for optimizing therapeutic pegRNAs. We use these tools to screen thousands of pegRNAs for 17 cystic fibrosis-causing alleles that do not respond to modulator therapies in multiple cell types, including ~3200 pegRNAs to correct W1282X, ~2300 pegRNAs to correct c.489+1G>T, and ~1100 pegRNAs to correct R1162X. We also describe adaptive triaging, an active learning method that enables iterative optimization of pegRNA silent edit strategies in an allele- and cell type-agnostic manner. Adaptive triaging facilitates identification of high efficiency pegRNAs without the need to comprehensively screen multiple pegRNA parameters simultaneously and shows efficacy across a diversity of experimental scales. The tools and findings from this work could be applied in future translational studies that endeavor to correct disease-causing alleles via prime editing in preclinical settings. In Chapter 5, I describe a series of studies to evolve and characterize botulinum neurotoxin (BoNT) proteases to cleave therapeutically relevant protein targets. We used phage-assisted evolution to reprogram BoNTs to cleave procaspase-1, a mediator of programmed inflammatory cell death, and NaV1.7, a voltage-gated sodium channel implicated in the sensation of acute pain. We also developed an efficient platform to broadly characterize the substrate specificity of both wild-type and evolved BoNT protease variants. Substrate profiling of evolved procaspase-1 cleaving BoNT/X variants demonstrated that evolved proteases acquired enhanced substrate sequence specificity over their wild-type BoNT/X starting point and enabled the nomination of proteome-wide off-target cleavage activity. We leveraged substrate profiling to inform evolutionary trajectories for a NaV1.7-cleaving BoNT/E, demonstrating that information on the substrate preferences of proteases can be used for the forward design of reprogrammed proteases. Together, these results expand the repertoire of experimental tools available for therapeutic protease development.