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Abstract

Cystic fibrosis (CF) is among the most widespread monogenic diseases globally and stands as the most common lethal genetic disorder among Canadian youths and young adults. It arises from single mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. CRISPR-based gene editing offers a groundbreaking opportunity for correcting monogenetic diseases like CF. Nevertheless, the effective delivery of CRISPR-tools through the lung epithelium and its protective mucosal lining poses a significant challenge. Lipid nanoparticles (LNPs) emerged as versatile non-viral gene delivery systems that could potentially overcome this challenge. However, substantial knowledge gaps persist, especially concerning diseases like CF. This thesis delved into the fundamental understanding of interactions between Cas9 mRNA or ribonucleoprotein (RNP)-loaded LNPs and mucus. Notably, LNP-mRNA demonstrated higher mucus diffusivity than LNP-RNP in healthy mucus, likely due to smaller particle sizes. Mucin sialylation significantly impeded LNP diffusivity, along with high mucin concentrations. Conversely, high ionic strength (>100 mM) and moderate acidic conditions enhanced LNP diffusivity. Importantly, increasing LNP’s PEGylation, particularly when employing a mixture of PEG species rather than a single type, significantly improved LNP diffusivity in CF-mucus, while ensuring robust cell transfection in primary normal human bronchial epithelial (NHBE) cells derived from CF patients. Subsequently, the thesis concentrated on devising strategies to enhance gene editing efficacy of Cas9/sgRNA loaded LNPs in both healthy and CF primary NHBE cells, which are notoriously challenging to genetically manipulate. Adjusting sgRNA to Cas9 ratio and incorporating endosomal escape enhancers (saponin) proved fruitful, elevating editing rates to ~15%. Importantly, through screening LNPs, LNP-H (pKa 7.1) demonstrated robust editing, achieving ~30% editing in NHBE cells. Furthermore, when LNP-H was used with highly modified sgRNA, ~50% editing in CF-NHBE cells was achieved. In physiologically relevant 3D NHBE models, LNP-H exhibited high uptake, as confirmed by fluorescence microscopy, yet achieved 7% editing in healthy models and 5% in CF models. The lower editing efficiencies in 3D models were expected because of the ciliated epithelium/mucosal barrier. Various reports indicate that normal lung function requires only 5-10% of normal CFTR, suggesting that the study's LNP-mediated strategies could be effective for CRISPR-based editing as a therapy for CF.