Drug DeliveryMolecular BiologyPeer-reviewed journal article
Lipid Nanoparticles with Aptamers Enable Targeted mRNA Delivery to CD4⁺ T Cells
Shrey ShahiD, Meenakshi RanasingheiD, John Decker, Keith FraseriD, Ying WangiD, Sarah Kinlaw, Morgan Barker, Sawan PateliD, Adam Friedman, Sherwood YaoiD
- Citations
- 6
- FWCI
- 12.31
- Field percentile
- top 1%
Abstract
In vivo genetic engineering of T cells could overcome the logistical, biological, and safety challenges of ex vivo modification, but effective and safe delivery systems remain limited by a lack of cellular specificity. Here, we developed aptamer-functionalized lipid nanoparticles (LNPs) for targeted mRNA delivery to CD4+ T cells, employing both a validated CD4-binding aptamer (Apt62) and novel aptamers generated using our proprietary transformer-based AI language model, AptaBLE. LNPs formulated with ionizable lipid SM102 or MC3 and conjugated with aptamers at controlled densities were physiochemically characterized and assessed for binding, in vitro transfection, in vivo biodistribution, and safety evaluation. Aptamer-functionalized LNPs demonstrated selective nanomolar binding to recombinant CD4, achieved enhanced transfection of CD4+ versus CD4- T cells in vitro, and significantly enriched mRNA delivery to immune-rich tissues in vivo, achieving up to 70-fold spleen signal enhancement with SM102 formulations compared to non-targeted controls, while maintaining suitable safety profiles. Overall, these findings demonstrate aptamer-functionalized LNPs, augmented by AI-guided aptamer design, as a tunable, non-immunogenic platform for in vivo T cell engineering. HighlightsO_LIAptamer-functionalized LNPs enable selective mRNA delivery to CD4+ immune cells rich organs. C_LIO_LIAptamer-functionalized LNPs maintain a favorable systemic safety profile in vivo. C_LIO_LIAI-guided AptaBLE platform generated functional aptamers validated in nanoparticle delivery. C_LI
- organism: human
- assay: multiome
- research focus: drug response / drug discovery
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: experimental assay
- approach: machine learning (classical)
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