Macromolecular Architecture Of The Synapse

突触的大分子结构

• 批准号: 10708599
• 负责人: Thomas S Reese
• 金额: $ 190.18万
• 依托单位: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10708599
• 关键词: Address; Architecture; Automation; Binding; Brain; Cells; Collaborations; Collection; Complex; Computer Analysis; Computer software; Computing Methodologies; Cryo-electron tomography; Cryoelectron Microscopy; Data; Data Set; Dendritic Spines; Development; Electrons; Filament; Freeze Substitution; Freezing; Genetic; Glutamate Receptor; Glutamates; Goals; Gold; Hippocampus (Brain); Horseradish Peroxidase; Hour; Hydration status; Hydrogen Peroxide; Image; Imaging Techniques; Individual; Investigation; Ions; Label; Link; Manuals; Maps; Mechanics; Membrane; Memory; Methods; Microscope; Microtomy; Molecular; Molecular Machines; Molecular Probes; Molecular Structure; Morphology; Neurons; Organelles; Pattern; Pattern Recognition; Phosphotransferases; Positioning Attribute; Postsynaptic Membrane; Presynaptic Terminals; Procedures; Process; Proteins; Publications; Rattus; Series; Shapes; Side; Site; Skeleton; Sonication; Specificity; Structure; Subcellular structure; Synapses; Synaptic Cleft; Synaptic Membranes; Synaptic Vesicles; Synaptosomes; System; Techniques; Thick; Tomogram; United States National Institutes of Health; Update; Use of New Techniques; Vertebral column; Vesicle; Visualization; Water; Work; Writing; automated segmentation; calmodulin-dependent protein kinase II; computerized data processing; data exchange; density; electron tomography; improved; information processing; innovation; man; nanobodies; nanocolumn; optical imaging; oxidation; particle; postsynaptic; postsynaptic density protein; preservation; pressure; presynaptic; presynaptic density protein 95; protein complex; receptor; reconstruction; response; scaffold; supercomputer; synaptic function; tomography; trafficking

The postsynaptic density (PSD) at excitatory glutamatergic synapses is an extensive molecular machine and a key site of memory, information processing, and storage. To investigate the structure of PSD, we developed a method to freeze-substitute dissociated rat hippocampal cultures. We examine thin sections of the result by EM tomography, and they reveal individual protein complexes within the PSD. Our EM tomography revealed that the core of the PSD is an array of membrane-associated scaffolding with a latticework of filaments. Two major types of glutamate receptors, namely NMDARs and AMPARs cluster within the PSD. NMDARs cluster in the central region of the PSD with AMPARs at the periphery. The latticework of scaffold filaments appears to support the distribution of these receptors. We now have adapted two techniques for identifying proteins in EM tomography. First, we developed a new technique using nanobody labeling for tomograms. A nanobody binds directly to the target protein with high specificity which allows us to use gold particle labels on synaptic proteins and identify them directly in tomograms. We have data on PSD-95 and CaMKII, and we are expanding to Homer and Shank. We plan to finish this work and prepare it for publication. Second, we succeeded in fine-tuning a genetic labeling procedure for EM tomography using APEX2, a cloneable horseradish peroxidase, which catalyzes the oxidation of DAB into electron-dense material in the presence of hydrogen peroxide. CaMKII is a kinase required for LTP and is the most abundant protein in the brain. Using this APEX2 method in rat hippocampal neurons imaged by dark-field STEM tomography, individual APEX2 labeled CaMKII are readily identified in tomographic reconstructions of dendritic spines. As a result, we are beginning to understand the distribution of CaMKII in spines and on the membrane, their self-interactions, and their response to synaptic activity. We are preparing this work for publication. In addition, both labeling methods are being expanded for use in labeling other PSD proteins. Also in the past year, we made significant progress on several ground-breaking cryo-EM tomography projects in collaboration with NIH cryo-EM facilities (NICE and MICEF). We acquired over 150 cryo-EM tomograms on the NCI 300 kV Krios cryo-EM microscope, specifically on frozen-hydrated isolated PSDs from rat brains or sonicated PSD fragments. We are processing these tomograms with a self-developed segmentation method called automatic segmentation optimization method (ASOM), discussed below. We are making very good progress on collecting many cryo-EM tomography series of synapses, as we have overcome challenges related to preserving cells that contain more water than protein. We are further refining our collection with the use cryo focused ion beam (FIB) milling. With FIB milling we can shave neuronal processes and synapses to obtain 200 nm thick lamellar for cryo-EM tomography. Finally, we are freezing synaptosomes isolated from the brain for cryo-EM tomography. This method preserves synaptic terminals, membranes, and PSDs while being easier to freeze. This is an attractive method for cryo-EM tomography of PSD. In all these efforts, we are helped by access to the NIH-HCP supercomputer cluster for data transfer and processing. We expect that the combination of our current EM techniques with cryo-EM will result in more new discoveries. Our transsynaptic assembly project investigates the recently discovered synaptic nanocolumns, domains of pre-and postsynaptic molecules that align across the cleft. In this project, transcleft structures and all connected transmembrane and intracellular structures are segmented and analyzed in tomograms of synapses from high-pressure frozen, freeze-substituted neuronal cultures. In renderings, structures are not aligned, so much as they make continuous connections from one intracellular compartment to the other to make transsynaptic assemblies. We have analyzed patterns of assembly connectivity and distribution, but we continue to work to identify their constituent components to better understand which synaptic systems use assemblies and how. So far, this project has yielded three clear findings. First, nearly all transcleft objects have some intracellular component. Second, transsynaptic assemblies with large intracellular volumes and more than one intracellular component are very likely to be associated with synaptic vesicles. Third, transsynaptic assemblies share intracellular components and produce large domains of associated assemblies, or just association domains. We believe association domains explain the underpinnings of the nanodomain phenomena and reveal a more complex picture of their composition and function, as our results show that less than half of assemblies associate with synaptic vesicles. Currently, we are writing up these findings for publication but intend to continue delving deeper by integrating ASOM, discussed below, with an updated annotation and computational analysis process. This will increase the number of synapses and assemblies we must analyze and give us the ability to better identify common assembly components. With more objects to compare, computational methods can be used to better identify common structures, and we will be able to further parse out assembly types and perhaps prescribe assembly functions. Analysis of electron tomographic data requires painstaking effort and many man-hours. With this project, our goal is to accelerate the segmentation and visualization of synaptic structures with automation. To achieve this goal, we developed an automatic segmentation optimization method (ASOM). With ASOM, we are processing many vast tomograms. For one project, ASOM segmented detailed structures of fragments isolated from sonicated and control PSDs imaged by cryo-EM. We recently improved ASOM further by adding watershed segmentation, widely used to separate connected structures automatically. This enabled automatic segmentation of hundreds of tightly packed granular structures in intact PSDs into individual modules. More than 40% of the modules from both sonicated and control PSDs ranged from 40 nm to 90 nm in size suggesting that the fragments are generated by mechanical separation of loosely connected modular structures within the PSD rather than mere degradation of the synapse due to sonication. Last, ASOM was efficient for automatic segmentation of individual structures, but it did not allow us to easily automate the segmentation of structures that belong to one class or criteria set, like filaments connected to the synaptic membrane like PSD-95 filaments or those connected to both sides of the synaptic cleft, for example. To address this, we improved ASOM by adding skeletonization, which has proven important for pattern recognition. The improved ASOM now allows us to automatically segment filaments connected to only the postsynaptic membrane in one step, revealing that PSD-95-like filaments can be segmented by automation. Furthermore, the improved ASOM automatically segmented other distinct classes such as those connected to the presynaptic membrane, postsynaptic membranes, and/or vesicle membranes. We found that some of the automatically segmented filaments were linked to each other across the synaptic cleft forming complete tripartite assemblies including incomplete ones. The findings are consistent with those assemblies obtained by painstaking manual segmentation, demonstrating that this approach will contribute to expediting the segmentation of the assemblies, thus expanding the scope of our investigation to include more datasets and experimental conditions.