CdSe quantum dot-based delivery system for CRISPR-Cas9 mediated microglial gene modulation

Abstract

Microglia, the primary immune cells of the central nervous system, play a crucial role in neuroinflammation and homeostasis. They can adopt either M1 or M2 phenotypes, influencing their inflammatory and reparative functions. Modulating microglia phenotypes and functions is a significant area of therapeutic interest. However, the availability of delivery vehicles and gene expression modulation techniques targeting microglia is limited. Fluorescent quantum dots (Qdots) are semiconductor nanoparticles, specifically used to label and modulate microglia functions and offer promising alternatives to traditional genome editing methods. In this study, we developed a cadmium selenide (CdSe) Qdot-mediated delivery system to target the microglial genome. We evaluated streptavidin-coated CdSe Qdots for their ability to deliver clustered regularly interspaced short palindromic repeats-Cas9 to microglia in vivo and in vitro and assessed their distribution, safety, and capacity to deliver Cas9 ribonucleoproteins (RNPs) for gene editing by injecting the Qdots into the frontal white matter of cynomolgus monkeys and Sprague？Dawley rats. Assessing the mechanisms of Qdot uptake and stability revealed that CdSe Qdots were selectively taken up by microglia, with minimal localization in other cell types. Histological and biochemical analyses revealed no significant inflammatory or toxic effects following Qdot injection. The Qdots did not interfere with Cas9 RNP gene editing efficiency and provided enhanced fluorescence signals in microglia. Cas9/Qdot conjugates were stable and effectively delivered CRISPR-Cas9 to microglia, demonstrating higher specificity and lower cytotoxicity when compared to commercial delivery reagents. In conclusion, Qdots offer a promising nonviral method for targeted genome editing in microglia, indicating potential therapeutic applications for neuroinflammatory and neurodegenerative diseases. However, further optimization is needed to improve gene editing efficiency and safety for clinical applications.