Strategy to map electrical synaptic connectivity in neural networks

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SUMMARY Electrical synapses, also known as gap junctions, occur frequently in all nervous systems, including the human brain. They are composed of connexins, arranged to form intercellular channels between adjacent, coupled cells. Connexin36 (Cx36) is the predominant connexin in the CNS. In many brain and retinal circuits, gap junctions provide direct and specific connections between cells. In addition, electrical synapses mediate network properties such as signal averaging, noise reduction and synchronization. However, because of their small size, gap junctions are not visible in large-scale serial EM data sets. For these reasons, gap junctions tend to be under-reported or simply ignored. The objective of this proposal is to develop a combined approach to image gap junction connectivity in EM datasets and, in addition, to estimate the size, strength, and plasticity of gap junctions. We will study regions of the retina that contain gap junctions of dramatically different sizes and shapes, to allow us to correlate structure and function. Aim 1 will use high-resolution confocal microscopy to determine connexon number at large and small gap junctions. Analyses will determine the number of connexons per gap junction. These methods will provide a general-purpose tool to determine the size of gap junctions for use in all brain regions. Aim 2 will use 3D-EM imaging to allow unambiguous identification of gap junctions in FIB-SEM images, which will follow with first-ever immunogold quantification of a membrane-bound protein in 3D-EM structures. These studies will allow high-resolution quantification of gap junctions and proteins in identified neurons. Aim 3 will use electrophysiological measures to determine coupling conductance and then develop models to calculate the maximal potential coupling conductance from the morphological data by multiplying the number of channels/gap junction [Specific Aim 1] times the connectivity (the number of gap junctions between coupled cells) [Specific Aim 2], times the unitary conductance of Cx36. Using paired recordings, we will obtain direct physiological measures of the junctional conductance between coupled cells. Then, by comparison with the potential maximum calculated from the morphological data, we can calculate the open channel probability and place realistic limits on the operating range. These are the fundamental properties required to understand the function of gap junctions in neuronal microcircuits. This program is an exact match for one of the listed areas, “Tools to identify gap junctions and characterize electrical synapses” in the Funding Opportunity Announcement, RFA-MH-20-135.