AI Article Synopsis

  • The "Supernova" series of vector systems enables precise single-cell labeling and targeted gene manipulation through techniques like in utero electroporation (IUE) and adeno-associated virus (AAV) delivery.
  • This system uses low TRE leakage for sparse labeling, which can be enhanced by feedback mechanisms and site-specific recombination tools, allowing clear visualization of individual neurons even in densely populated brain regions.
  • Additionally, it allows for adjustable labeling levels and facilitates gene knockout and editing with tools like RNAi, TALEN, and CRISPR/Cas9, making it versatile for studying complex organs such as the mammalian brain.

Article Abstract

Here we describe "Supernova" series of vector systems that enable single-cell labeling and labeled cell-specific gene manipulation, when introduced by in utero electroporation (IUE) or adeno-associated virus (AAV)-mediated gene delivery. In Supernova, sparse labeling relies on low TRE leakage. In a small population of cells with over-threshold leakage, initial tTA-independent weak expression is enhanced by tTA/TRE-positive feedback along with a site-specific recombination system (e.g., Cre/loxP, Flpe/FRT). Sparse and bright labeling by Supernova with little background enables the visualization of the morphological details of individual neurons in densely packed brain areas such as the cortex and hippocampus, both during development and in adulthood. Sparseness levels are adjustable. Labeled cell-specific gene knockout was accomplished by introducing Cre/loxP-based Supernova vectors into floxed mice. Furthermore, by combining with RNAi, TALEN, and CRISPR/Cas9 technologies, IUE-based Supernova achieved labeled cell-specific gene knockdown and editing/knockout without requiring genetically altered mice. Thus, Supernova system is highly extensible and widely applicable for single-cell analyses in complex organs, such as the mammalian brain.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5075795PMC
http://dx.doi.org/10.1038/srep35747DOI Listing

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