Deep molecular diversity of mammalian synapses: why it matters and how to measure it.

Pioneering studies in the middle of the twentieth century revealed substantial diversity among mammalian chemical synapses and led to a widely accepted classification of synapse type on the basis of neurotransmitter molecule identity. Subsequently, powerful new physiological, genetic and structural methods have enabled the discovery of much deeper functional and molecular diversity within each traditional neurotransmitter type. Today, this deep diversity continues to pose both daunting challenges and exciting new opportunities for neuroscience. Our growing understanding of deep synapse diversity may transform how we think about and study neural circuit development, structure and function.

Synaptic molecular imaging in spared and deprived columns of mouse barrel cortex with array tomography.

A major question in neuroscience is how diverse subsets of synaptic connections in neural circuits are affected by experience dependent plasticity to form the basis for behavioral learning and memory. Differences in protein expression patterns at individual synapses could constitute a key to understanding both synaptic diversity and the effects of plasticity at different synapse populations. Our approach to this question leverages the immunohistochemical multiplexing capability of array tomography (ATomo) and the columnar organization of mouse barrel cortex to create a dataset comprising high resolution volumetric images of spared and deprived cortical whisker barrels stained for over a dozen synaptic molecules each. These dataset has been made available through the Open Connectome Project for interactive online viewing, and may also be downloaded for offline analysis using web, Matlab, and other interfaces.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes- neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

Single-synapse analysis of a diverse synapse population: proteomic imaging methods and markers.

A lack of methods for measuring the protein compositions of individual synapses in situ has so far hindered the exploration and exploitation of synapse molecular diversity. Here, we describe the use of array tomography, a new high-resolution proteomic imaging method, to determine the composition of glutamate and GABA synapses in somatosensory cortex of Line-H-YFP Thy-1 transgenic mice. We find that virtually all synapses are recognized by antibodies to the presynaptic phosphoprotein synapsin I, while antibodies to 16 other synaptic proteins discriminate among 4 subtypes of glutamatergic synapses and GABAergic synapses. Cell-specific YFP expression in the YFP-H mouse line allows synapses to be assigned to specific presynaptic and postsynaptic partners and reveals that a subpopulation of spines on layer 5 pyramidal cells receives both VGluT1-subtype glutamatergic and GABAergic synaptic inputs. These results establish a means for the high-throughput acquisition of proteomic data from individual cortical synapses in situ.