High-throughput barcoding of nanoparticles identifies cationic, degradable lipid-like materials for mRNA delivery to the lungs in female preclinical models.
Lulu XueAlex G HamiltonGan ZhaoZebin XiaoRakan El-MaytaXuexiang HanNingqiang GongXinhong XiongJunchao XuChristian G Figueroa-EspadaSarah J ShepherdAlvin J MukalelMohamad Gabriel AlamehJiaxi CuiKarin WangAndrew E VaughanDrew WeissmanMichael J MitchellPublished in: Nature communications (2024)
Lipid nanoparticles for delivering mRNA therapeutics hold immense promise for the treatment of a wide range of lung-associated diseases. However, the lack of effective methodologies capable of identifying the pulmonary delivery profile of chemically distinct lipid libraries poses a significant obstacle to the advancement of mRNA therapeutics. Here we report the implementation of a barcoded high-throughput screening system as a means to identify the lung-targeting efficacy of cationic, degradable lipid-like materials. We combinatorially synthesize 180 cationic, degradable lipids which are initially screened in vitro. We then use barcoding technology to quantify how the selected 96 distinct lipid nanoparticles deliver DNA barcodes in vivo. The top-performing nanoparticle formulation delivering Cas9-based genetic editors exhibits therapeutic potential for antiangiogenic cancer therapy within a lung tumor model in female mice. These data demonstrate that employing high-throughput barcoding technology as a screening tool for identifying nanoparticles with lung tropism holds potential for the development of next-generation extrahepatic delivery platforms.
Keyphrases
- high throughput
- cancer therapy
- fatty acid
- drug delivery
- primary care
- genome wide
- single cell
- big data
- type diabetes
- binding protein
- healthcare
- electronic health record
- crispr cas
- metabolic syndrome
- single molecule
- mesenchymal stem cells
- machine learning
- deep learning
- risk assessment
- adipose tissue
- artificial intelligence
- copy number
- cell therapy
- iron oxide