journal article·2026-04-01

Amino acid-derived ionizable lipids enable inhaled base editing for therapeutic gene correction in the lung

Fanglin Gong, Yue Xu, Jingan Chen, Shun Zhang, Songtao Dong, Lauren Healy, Breanna Seto, Muye Zhou, Rick Xing Ze Lu, Gen Li, Tyler Thomson, Yinghua Tang, Ziyan Chen, Krista Antonio, Andrew Varley, David X. W. Chen, Craig A. Hodges, Amy P. Wong, Jim Hu, Basil P. Hubbard, John F. Engelhardt, Ziying Yan, Bowen Li

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Abstract

CRISPR-based gene editing holds promise for treating genetic diseases, yet its application to lung disorders has been hindered by the challenges of pulmonary delivery. Inspired by the modularity and biocompatibility of amino acid-derived chemistries, we report the combinatorial synthesis of 960 ionizable lipids incorporating chemically diverse backbones from both proteinogenic and non-proteinogenic α-amino acids. Through high-throughput screening and structure-function analysis, we identify CHCha-10, a cyclohexyl amino acid-derived lipid that forms biodegradable nanoparticles capable of efficiently delivering mRNA-based gene editors to lung epithelial cells. Following intratracheal administration, CHCha-10 nanoparticles exhibit enhanced mucus penetration and epithelial-specific transfection in both mice and ferrets. Here, as a functional application, we demonstrate in vivo base editing in the lung via inhalation. Delivery of adenine base editor mRNA and guide RNA targeting the CFTR G542X mutation restores CFTR expression and chloride channel function in G542X human airway epithelial cells, mouse-derived intestinal organoids and the lungs of cystic fibrosis mice. This work establishes a chemically modular design framework for ionizable lipids and a translatable platform for RNA-based pulmonary gene correction.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: RNA Interference and Gene Delivery · CRISPR and Genetic Engineering · RNA and protein synthesis mechanisms

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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