Development of microRNA-guided neuron tags (mAGNETs) to target and classify neural subtypes in the living brain

Boston University (Charles River Campus), Boston MA

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Abstract

? DESCRIPTION (provided by applicant): The ability to genetically modify specific neural subsets is essential in elucidating their contributions to brain computation and disease. Recently, we developed a novel strategy for targeting transgene expression to neuronal subtypes by exploiting endogenous microRNA (miRNA) regulation, which we call miRNA-guided neuron tags (mAGNETs). miRNAs are small (~20 nt), non-coding RNAs that inhibit gene expression by hybridizing to complementary recognition sites within mRNA transcripts. Because different miRNAs are upregulated in specific cell types, we are able to target gene expression by including signature miRNA recognition sites at the end of mAGNET transcripts. Exploiting miRNA regulation to target gene expression is an attractive technique for brain research due to the small footprint of miRNA sites (which facilitates viral packaging), the potential to engineer combinations of miRNA sites to tune selectivity, and the possibility to target and classify novel neuron subtypes based upon physiological function. As a proof of principle demonstration, we designed mAGNETs to target EGFP expression to cortical inhibitory (GABA) neurons in the mouse brain, and achieved up to 91% targeting specificity. The goal of this proposal is to overcome some of the viral gene targeting challenges in basic neuroscience research and human gene therapy by further developing and testing the application of this promising, novel neurotechnology platform. First, I aim to build upon our previous work and develop a mAGNET to selectively target transgene expression to an even more specific subset of inhibitory neurons, parvalbumin (PV+) cells. Second, because miRNAs are inhibitory, our gene targeting designs have relied upon recognition sites for signature miRNAs strongly upregulated in off-target cells, therefore to improve the ease of mAGNET design and use, I aim to test a repressor system that would allow mAGNETs to employ signature miRNAs positively correlated to target cell populations. Finally, I aim to demonstrate how mAGNETs can be used to classify novel neural subsets by applying simple mAGNETs to characterize a potential subset of functionally distinct CamKII neurons relevant for Parkinson's disease and epilepsy.This work could provide a new method of gene delivery for neuroscience research and human gene therapy.