Postsynaptic plasticity is not accessible as a selection criterion for molecular identification of neurons by single-cell RNA-sequencing (scRNA-seq). The currently available methods to find specific connection plasticity ex vivo have inherently low throughput. To overcome these limitations and pre-select neurons based on short-term postsynaptic plasticity for soma harvesting and subsequent scRNA-seq we created Voltage-Seq. First, we established all-optical voltage imaging and recorded the short-term postsynaptic plasticity of 6911 periaqueductal gray (PAG) neurons evoked by optogenetic activation of the ventromedial hypothalamic (VMH) input. Postsynaptic response-types were classified and spatially resolved in the entire innervated PAG. Next, to browse and identify all-optical responses, we built a quick on-site analysis named VoltView which incorporated the a priori VMH-PAG connectome database as a classifier. VoltView targetedly identifies postsynaptic neurons for somatic harvesting. We demonstrated the agility of Voltage-Seq in locating GABAergic PAG neurons, guided by an all-optical connectivity map and on-site classification in VoltView.
Understanding the routing of neuronal information requires the functional characterization of connections. Neuronal projections recruit large postsynaptic ensembles with distinct postsynaptic response types (PRTs). PRT is typically probed by low-throughput whole-cell electrophysiology and is not a selection criterion for single-cell RNA-sequencing (scRNA-seq). To overcome these limitations and target neurons based on specific PRTs for soma harvesting and subsequent scRNA-seq, we created Voltage-Seq. We established all-optical voltage imaging and recorded the PRT of 8,347 neurons in the mouse periaqueductal gray (PAG) evoked by the optogenetic activation of ventromedial hypothalamic (VMH) terminals. PRTs were classified and spatially resolved in the entire VMH-PAG connectome. We built an onsite analysis tool named VoltView to navigate soma harvesting towards target PRTs guided by a classifier that used the VMH-PAG connectome database as a reference. We demonstrated Voltage-seq by locating VMH-driven γ-aminobutyric acid-ergic neurons in the PAG, guided solely by the onsite classification in VoltView.
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