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Rationally Designed MicroRNA-Based Genetic Classifiers Target Specific Neurons in the Brain
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Details:
  • Pubmed ID:
    25848814
  • Pubmed Central ID:
    PMC4547530
  • Funding:
    1DP2CA186574/CA/NCI NIH HHS/United States
    1DP2NS082126/DP/NCCDPHP CDC HHS/United States
    1R01NS081716/NS/NINDS NIH HHS/United States
    1R01NS087950/NS/NINDS NIH HHS/United States
    1R21NS078660/NS/NINDS NIH HHS/United States
    5R00MH085944/MH/NIMH NIH HHS/United States
    DP2 NS082126/NS/NINDS NIH HHS/United States
    R00 MH085944/MH/NIMH NIH HHS/United States
    R01 NS087950/NS/NINDS NIH HHS/United States
    R21 NS078660/NS/NINDS NIH HHS/United States
  • Document Type:
  • Collection(s):
  • Description:
    Targeting transgene expression to specific cell types in vivo has proven instrumental in characterizing the functional role of defined cell populations. Genetic classifiers, synthetic transgene constructs designed to restrict expression to particular classes of cells, commonly rely on transcriptional promoters to define cellular specificity. However, the large size of many natural promoters complicates their use in viral vectors, an important mode of transgene delivery in the brain and in human gene therapy. Here, we expanded upon an emerging classifier platform, orthogonal to promoter-based strategies, that exploits endogenous microRNA regulation to target gene expression. Such classifiers have been extensively explored in other tissues; however, their use in the nervous system has thus far been limited to targeting gene expression between neurons and supporting cells. Here, we tested the possibility of using combinatory microRNA regulation to specify gene targeting between neuronal subtypes, and successfully targeted inhibitory cells in the neocortex. These classifiers demonstrate the feasibility of designing a new generation of microRNA-based neuron-type- and brain-region-specific gene expression targeting neurotechnologies.