A versatile viral toolkit for functional discovery in the nervous system.
A versatile viral toolkit for functional discovery in the nervous system.
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DOI:
10.1016/j.crmeth.2022.100225
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发表时间:
2022-06-20
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The ability to precisely control transgene expression is essential for basic research and clinical applications. Adeno-associated viruses (AAVs) are non-pathogenic and can be used to drive stable expression in virtually any tissue, cell type, or species, but their limited genomic payload results in a trade-off between the transgenes that can be incorporated and the complexity of the regulatory elements controlling their expression. Resolving these competing imperatives in complex experiments inevitably results in compromises. Here, we assemble an optimized viral toolkit (VTK) that addresses these limitations and allows for efficient combinatorial targeting of cell types. Moreover, their modular design explicitly enables further refinements. We achieve this in compact vectors by integrating structural improvements of AAV vectors with innovative molecular tools. We illustrate the potential of this approach through a systematic demonstration of their utility for targeting cell types and querying their biology using a wide array of genetically encoded tools. Cell-type-specific targeting is required to study circuits and behaviors Factors such as transgene size limit the AAV payload available VTK is a set of optimized AAV backbones that overcomes these limitations The diversity of transgenes allowing for precise labeling and manipulation of neurons is ever evolving, but the evolution of viral vectors capable of restricting their expression to specific and functionally defined subtypes lags behind. Here, we present an optimized viral toolkit (VTK) that aims at simplifying the experimental design by increasing the modularity of AAV vectors for the targeting of specific types of neurons. Pouchelon et al. develop an optimized and modular viral toolkit (VTK) that addresses key AAV limitations and allows for efficient combinatorial targeting of neuronal cell types. This approach allows efficient querying of neuronal biology using a wide array of genetically encoded tools.