A Direct Comparison of in Vitro and in Vivo Nucleic Acid Delivery Mediated by Hundreds of Nanoparticles Reveals a Weak Correlation.
Kalina PaunovskaCory D SagoChristopher M MonacoWilliam H HudsonMarielena Gamboa CastroTobi G RudoltzSujay KalathoorDaryll A VanoverPhilip J SantangeloRafi AhmedAnton V BryksinJames E DahlmanPublished in: Nano letters (2018)
Endothelial cells and macrophages play active roles in disease and as a result are important targets for nucleic acid therapies. While thousands of chemically distinct lipid nanoparticles (LNPs) can be synthesized to deliver nucleic acids, studying more than a few LNPs in vivo is challenging. As a result, it is difficult to understand how nanoparticles target these cells in vivo. Using high throughput LNP barcoding, we quantified how well LNPs delivered DNA barcodes to endothelial cells and macrophages in vitro, as well as endothelial cells and macrophages isolated from the lung, heart, and bone marrow in vivo. We focused on two fundamental questions in drug delivery. First, does in vitro LNP delivery predict in vivo LNP delivery? By comparing how 281 LNPs delivered barcodes to endothelial cells and macrophages in vitro and in vivo, we found in vitro delivery did not predict in vivo delivery. Second, does LNP delivery change within the microenvironment of a tissue? We quantified how 85 LNPs delivered barcodes to eight splenic cell populations, and found that cell types derived from myeloid progenitors tended to be targeted by similar LNPs, relative to cell types derived from lymphoid progenitors. These data demonstrate that barcoded LNPs can elucidate fundamental questions about in vivo nanoparticle delivery.
Keyphrases
- endothelial cells
- nucleic acid
- bone marrow
- single cell
- drug delivery
- high throughput
- high glucose
- heart failure
- stem cells
- induced apoptosis
- mesenchymal stem cells
- acute myeloid leukemia
- vascular endothelial growth factor
- machine learning
- atrial fibrillation
- cancer therapy
- cell proliferation
- artificial intelligence
- endoplasmic reticulum stress
- deep learning
- single molecule
- cell cycle arrest
- drug release