Genetically-encoded voltage integrators for stable tagging of activated or inhibited neural ensembles in vivo

A major goal in systems neuroscience is to discover the neural circuit basis of behavior, including the cell types involved and their connectivity patterns. Existing methods are limited to tagging activated neurons but not the inhibited neuronal populations, which are equally crucial for producing behavior. Here we propose to develop first-in-class genetically encoded voltage integrators (GEVIns), which will be used to provide stable genetic access to either transiently activated or inhibited neuronal ensembles. We will use a combination of rational engineering and directed evolution to develop and optimize GEVIns, and then apply them to identify neural subpopulations in the spinal cord that are inhibited in chronic pain.