The continued expansion in size and resolution of volumetric datasets generated by electron microscopy (3DEM) is making high-performance computing (HPC) an essential component. HPC provides the scalable, parallelized infrastructure required to process and analyze these increasingly large datasets. The Texas Advanced Computing Center’s (TACC) Core Experience Portal (CEP) is a science gateway specialized for leveraging HPC. The CEP can be adapted into customized versions based on a research community’s needs. Here we have constructed 3dem.org as a gateway for the community exploring volumetric data generated by electron microscopy (3DEM). This gateway provides the 3DEM community with user-friendly browser-based access to raw and processed datasets including both private and shared data, image processing tools for alignment and segmentation, and simulation and analysis environments. All this is linked to the underlying HPC environment at TACC with the ability to connect to other data storage and compute systems. 3dem.org bridges advanced electron microscopy with HPC, providing the research community with scalable, accessible infrastructure for discovery.

There is a morphodynamic component to synaptic learning by which changes in dendritic (postsynaptic) spine head size are associated with the strengthening or weakening of the synaptic connection between two neurons. The membrane shape and size dynamics is sculpted by the growth dynamics of the enclosed actin cytoskeleton. We use Dynamical Graph Grammars (DGGs) governing dynamic labelled graphs embedded in two dimensions to model networks of actin filaments and the enclosing membrane in spine head morphology. We demonstrate the flexibility and extensibility of the framework by encoding detailed biophysical as well as biochemical models, obeying constraints of invariance and conservation, in DGG rule sets. From graph-local energy functions for cytoskeleton actin interacting and membrane, we specialize dissipative stochastic dynamics to an exhaustive collection of graph-local neighborhood types for the rule left hand sides. Extensively simulating the resulting model delineates effects of four actin-binding proteins, and their epistatic relationships, on morphology.

Long-term potentiation (LTP) is a lasting form of synaptic plasticity that can persist for hours or even days. It is associated with structural changes in both the presynaptic terminal and the postsynaptic spine. Presynaptically, the number and distribution of synaptic vesicles (SVs) affect synaptic efficacy. How the functional changes in synaptic efficacy after the induction of LTP are mirrored by identifiable structural alterations in the SV cluster is not fully understood. Here, we interrogated presynaptic terminals in 3DEM reconstructions from CA3-to-CA1 synapses in stratum radiatum of adult rats that had undergone control stimulation, or theta-burst stimulation to produce LTP. An increase was observed in the dispersion of SVs at 2 h after LTP induction. This dispersion resulted in greater distances between neighboring SVs, longer distances to the center of the SV cluster, and an increased variance in SV position relative to the cluster's center. Analysis of the SV clusters distinguished terminals that were potentiated based on their degree of dispersion, distances to neighboring SVs, and SV cluster densities. Our analysis demonstrates that the density of SVs is a property independent of the bouton or SV cluster volumes and is subject to strong regulation. Comparing the spatial distribution of SVs to randomized distributions revealed increased SV mobility following LTP induction. Moreover, theoretical calculations informed by the measured SV cluster densities suggest an increase in the mobility of SVs within the cluster during LTP. These findings provide evidence that the SV cluster undergoes a transition from tight to dispersed, making SVs more mobile during LTP.

Two major glutamate decarboxylase isoforms (i.e., GAD65 and GAD67) together synthesize the majority of γ-aminobutyric acid (GABA) in our nervous system. However, the subcellular distribution of these enzymes and their relative impacts on synaptic GABA release remain unclear. To address this important question, here we monitored their synaptic trafficking in male and female mouse brains and dissociated neuronal cultures. We noticed that, unlike some major glutamate-biosynthesizing enzymes, e.g., glutaminase and glutamate dehydrogenase, which were primarily associated with perisomatic mitochondria, both GADs together were highly enriched at GABAergic presynapses. Nevertheless, when expressed separately in GAD-deficient human neurons derived from a male stem cell line, GAD65 exhibited preferential distribution at presynapses over GAD67. Despite these differences in subcellular localization, both GADs produced equivalent levels of intracellular GABA, which adequately diffused to axon terminals, and triggered robust GABAergic activities. These findings raised the question of whether the presynaptic recruitment of GADs is, after all, necessary for reliable GABAergic transmission. To examine this hypothesis, we further swapped or removed the trafficking signals from both GAD isoforms and even artificially restricted them at nonsynaptic compartments, including the cell nucleus. Despite our attempts, the chimeric and mutant GAD variants continued to produce sufficient amount of intracellular GABA for vesicular loading and presynaptic release. These results indicate that GAD65 and GAD67 are functionally redundant in GABA production, if expressed equitably in neurons, and irrespective of GADs’ subcellular trafficking profile, diffusion of GABA molecules from distant sources can effectively supply and replenish the presynaptic terminals for functional activities.

Synapses of retinal rod photoreceptors involve deep invaginations occupied by second-order rod bipolar cell (RBP) and horizontal cell (HC) dendrites. Synaptic vesicles are released into this invagination at multiple sites beneath an elongated presynaptic ribbon. To study the impact of this architecture on glutamate diffusion and receptor activity, we reconstructed four rod terminals and their postsynaptic dendrites from serial electron micrographs of the mouse retina. We incorporated these structures into anatomically realistic Monte Carlo simulations of neurotransmitter diffusion and receptor activation. By comparing passive diffusion of glutamate in realistic structures with geometrically simplified models, we found that glutamate exits anatomically realistic synapses 10-fold more slowly than previously predicted. Constraining simulations with physiological data, we modeled activity of EAAT5 glutamate transporters in rods, AMPA receptors on HC dendrites, and metabotropic glutamate receptors (mGluR6) on RBP dendrites. Simulations suggested that ∼3,000 EAAT5 populate rod membranes. While uptake by surrounding glial Müller cells retrieves most glutamate released by rods, binding and uptake by EAAT5 influence RBP kinetics. Glutamate persistence allows mGluR6 on RBP dendrites to integrate the stream of vesicles released by rods in darkness. Glutamate's tortuous diffusional path confers quantal variability, as release from nearby ribbon sites exerts larger effects on RBP and HC receptors than release from more distant sites. Temporal integration supports slower sustained release rates, but additional quantal variability can impede postsynaptic detection of changes in release produced by rod light responses. These results show an example of the profound impact that synaptic architecture can have on postsynaptic responses.

Activation of N-methyl-D-aspartate-type glutamate receptors (NMDARs) at synapses in the CNS triggers changes in synaptic strength that underlie memory formation in response to strong synaptic stimuli. The primary target of Ca2+ flowing through NMDARs is Ca2+/calmodulin-dependent protein kinase II (CaMKII) which forms dodecameric holoenzymes that are highly concentrated at the postsynaptic site. Activation of CaMKII is necessary to trigger long-term potentiation of synaptic strength (LTP), and is prolonged by autophosphorylation of subunits within the holoenzyme. Here we use MCell4, an agent-based, stochastic, modeling platform to model CaMKII holoenzymes placed within a realistic spine geometry. We show how two mechanisms of regulation of CaMKII, ‘Ca2+-calmodulin-trapping (CaM-trapping)’ and dephosphorylation by protein phosphatase-1 (PP1) shape the autophosphorylation response during a repeated high-frequency stimulus. Our simulation results suggest that autophosphorylation of CaMKII does not constitute a bistable switch. Instead, prolonged but temporary, autophosphorylation of CaMKII may contribute to a biochemical-network-based ‘kinetic proof-reading” mechanism that controls induction of synaptic plasticity. ### Competing Interest Statement The authors have declared no competing interest.

Long-term potentiation (LTP) is a biochemical process that underlies learning in excitatory glutamatergic synapses in the Central Nervous System (CNS). A critical early driver of LTP is autophosphorylation of the abundant postsynaptic enzyme, Ca2+/calmodulin-dependent protein kinase II (CaMKII). Autophosphorylation is initiated by Ca2+ flowing through NMDA receptors activated by strong synaptic activity. Its lifetime is ultimately determined by the balance of the rates of autophosphorylation and of dephosphorylation by protein phosphatase 1 (PP1). Here we have modeled the autophosphorylation and dephosphorylation of CaMKII during synaptic activity in a spine synapse using MCell4, an open source computer program for creating particle-based stochastic, and spatially realistic models of cellular microchemistry. The model integrates four earlier detailed models of separate aspects of regulation of spine Ca2+ and CaMKII activity, each of which incorporate experimentally measured biochemical parameters and have been validated against experimental data. We validate the composite model by showing that it accurately predicts previous experimental measurements of effects of NMDA receptor activation, including high sensitivity of induction of LTP to phosphatase activity in vivo, and persistence of autophosphorylation for a period of minutes after the end of synaptic stimulation. We then use the model to probe aspects of the mechanism of regulation of autophosphorylation of CaMKII that are difficult to measure in vivo. We examine the effects of “CaM-trapping,” a process in which the affinity for Ca2+/CaM increases several hundred-fold after autophosphorylation. We find that CaM-trapping does not increase the proportion of autophosphorylated subunits in holoenzymes after a complex stimulus, as previously hypothesized. Instead, CaM-trapping may dramatically prolong the lifetime of autophosphorylated CaMKII through steric hindrance of dephosphorylation by protein phosphatase 1. The results provide motivation for experimental measurement of the extent of suppression of dephosphorylation of CaMKII by bound Ca2+/CaM. The composite MCell4 model of biochemical effects of complex stimuli in synaptic spines is a powerful new tool for realistic, detailed dissection of mechanisms of synaptic plasticity.

Variation in the strength of synapses can be quantified by measuring the anatomical properties of synapses. Quantifying precision of synaptic plasticity is fundamental to understanding information storage and retrieval in neural circuits. Synapses from the same axon onto the same dendrite have a common history of coactivation, making them ideal candidates for determining the precision of synaptic plasticity based on the similarity of their physical dimensions. Here, the precision and amount of information stored in synapse dimensions were quantified with Shannon information theory, expanding prior analysis that used signal detection theory (Bartol et al., 2015). The two methods were compared using dendritic spine head volumes in the middle of the stratum radiatum of hippocampal area CA1 as well-defined measures of synaptic strength. Information theory delineated the number of distinguishable synaptic strengths based on nonoverlapping bins of dendritic spine head volumes. Shannon entropy was applied to measure synaptic information storage capacity (SISC) and resulted in a lower bound of 4.1 bits and upper bound of 4.59 bits of information based on 24 distinguishable sizes. We further compared the distribution of distinguishable sizes and a uniform distribution using Kullback-Leibler divergence and discovered that there was a nearly uniform distribution of spine head volumes across the sizes, suggesting optimal use of the distinguishable values. Thus, SISC provides a new analytical measure that can be generalized to probe synaptic strengths and capacity for plasticity in different brain regions of different species and among animals raised in different conditions or during learning. How brain diseases and disorders affect the precision of synaptic plasticity can also be probed.

We present the first-ever, fully discrete, stochastic model of triggered cardiac Ca2+ dynamics. Using anatomically accurate subcellular cardiac myocyte geometries, we simulate the molecular players involved in Ca2+ handling using high-resolution stochastic and explicit-particle methods at the level of an individual cardiac dyadic junction. Integrating data from multiple experimental sources, the model not only replicates the findings of traditional in silico studies and complements in vitro experimental data but also reveals new insights into the molecular mechanisms driving cardiac dysfunction under stress and disease conditions. We improve upon older, nondiscrete models using the same realistic geometry by incorporating molecular mechanisms for spontaneous, as well as triggered calcium-induced calcium release (CICR). Action potentials are used to activate L-type calcium channels (LTCC), triggering CICR through ryanodine receptors (RyRs) on the surface of the sarcoplasmic reticulum. These improvements allow for the specific focus on the couplon: the structure-function relationship between LTCC and RyR. We investigate the electrophysical effects of normal and diseased action potentials on CICR and interrogate the effects of dyadic junction deformation through detubulation and orphaning of RyR. Our work demonstrates the importance of the electrophysical integrity of the calcium release unit on CICR fidelity, giving insights into the molecular basis of heart disease. Finally, we provide a unique, detailed, molecular view of the CICR process using advanced rendering techniques. This easy-to-use model comes complete with tutorials and the necessary software for use and analysis to maximize usability and reproducibility. Our work focuses on quantifying, qualifying, and visualizing the behavior of the molecular species that underlie the function and dysfunction of subcellular cardiomyocyte systems.

At the first synapse in the vertebrate retina, rod photoreceptor terminals form deep invaginations occupied by multiple second-order rod bipolar and horizontal cell (RBP and HC) dendrites. Synaptic vesicles are released into this invagination at multiple sites beneath an elongated presynaptic ribbon. We investigated the impact of this complex architecture on the diffusion of synaptic glutamate and activity of postsynaptic receptors. We obtained serial electron micrographs of mouse retina and reconstructed four rod terminals along with their postsynaptic RBP and HC dendrites. We incorporated these structures into an anatomically realistic Monte Carlo simulation of neurotransmitter diffusion and receptor activation. We compared passive diffusion of glutamate in these realistic structures to existing, geometrically simplified models of the synapse and found that glutamate exits anatomically realistic synapses ten times more slowly than previously predicted. By comparing simulations with electrophysiological recordings, we modeled synaptic activation of EAAT5 glutamate transporters in rods, AMPA receptors on HC dendrites, and metabotropic glutamate receptors (mGluR6) on RRBP dendrites. Our simulations suggested that ~3,000 EAAT5 transporters populate the rod presynaptic membrane and that, while uptake by surrounding glial Müller cells retrieves much of the glutamate released by rods, binding and uptake by EAAT5 influences RBP response kinetics. The long lifetime of glutamate within the cleft allows mGluR6 on RBP dendrites to temporally integrate the steady stream of vesicles released at this synapse in darkness. Glutamate's tortuous diffusional path through realistic synaptic geometry confers quantal variability, as release from nearby ribbon sites exerts larger effects on RBP and HC receptors than release from more distant sites. While greater integration may allow slower sustained release rates, added quantal variability complicates the challenging task of detecting brief decreases in release produced by rod light responses at scotopic threshold.

Long-term potentiation (LTP) has become a standard model for investigating synaptic mechanisms of learning and memory. Increasingly, it is of interest to understand how LTP affects the synaptic information storage capacity of the targeted population of synapses. Here, structural synaptic plasticity during LTP was explored using three-dimensional reconstruction from serial section electron microscopy. Storage capacity was assessed by applying a new analytical approach, Shannon information theory, to delineate the number of functionally distinguishable synaptic strengths. LTP was induced by delta-burst stimulation of perforant pathway inputs to the middle molecular layer of hippocampal dentate granule cells in adult rats. Spine head volumes were measured as predictors of synaptic strength and compared between LTP and control hemispheres at 30 min and 2 hr after the induction of LTP. Synapses from the same axon onto the same dendrite were used to determine the precision of synaptic plasticity based on the similarity of their physical dimensions. Shannon entropy was measured by exploiting the frequency of spine heads in functionally distinguishable sizes to assess the degree to which LTP altered the number of bits of information storage. Outcomes from these analyses reveal that LTP expanded storage capacity; the distribution of spine head volumes was increased from 2 bits in controls to 3 bits at 30 min and 2.7 bits at 2 hr after the induction of LTP. Furthermore, the distribution of spine head volumes was more uniform across the increased number of functionally distinguishable sizes following LTP, thus achieving more efficient use of coding space across the population of synapses.

Biochemical signaling pathways in living cells are often highly organized into spatially segregated volumes, membranes, scaffolds, subcellular compartments, and organelles comprising small numbers of interacting molecules. At this level of granularity stochastic behavior dominates, well-mixed continuum approximations based on concentrations break down and a particle-based approach is more accurate and more efficient. We describe and validate a new version of the open-source MCell simulation program (MCell4), which supports generalized 3D Monte Carlo modeling of diffusion and chemical reaction of discrete molecules and macromolecular complexes in solution, on surfaces representing membranes, and combinations thereof. The main improvements in MCell4 compared to the previous versions, MCell3 and MCell3-R, include a Python interface and native BioNetGen reaction language (BNGL) support. MCell4’s Python interface opens up completely new possibilities for interfacing with external simulators to allow creation of sophisticated event-driven multiscale/multiphysics simulations. The native BNGL support, implemented through a new open-source library libBNG (also introduced in this paper), provides the capability to run a given BNGL model spatially resolved in MCell4 and, with appropriate simplifying assumptions, also in the BioNetGen simulation environment, greatly accelerating and simplifying model validation and comparison.

Functional and structural elements of synaptic plasticity are tightly coupled, as has been extensively shown for dendritic spines. Here, we interrogated structural features of presynaptic terminals in 3DEM reconstructions from CA1 hippocampal axons that had undergone control stimulation or theta-burst stimulation (TBS) to produce long-term potentiation (LTP). We reveal that after LTP induction, the synaptic vesicle (SV) cluster is less dense, and SVs are more dispersed. The distances between neighboring SVs are greater in less dense terminals and have more SV-associated volume. We characterized the changes to the SV cluster by measuring distances between neighboring SVs, distances to the active zone, and the dispersion of the SV cluster. Furthermore, we compared the distribution of SVs with randomized ones and provided evidence that SVs gained mobility after LTP induction. With a computational model, we can predict the increment of the diffusion coefficient of the SVs in the cluster. Moreover, using a machine learning approach, we identify presynaptic terminals that were potentiated after LTP induction. Lastly, we show that the local SV density is a volume-independent property under strong regulation. Altogether, these results provide evidence that the SV cluster is undergoing a transition during LTP. ### Competing Interest Statement The authors have declared no competing interest.

There is a morphodynamic component to synaptic learning by which dendritic (postsynaptic) spine head size changes can strengthen or weaken the synaptic connection between two neurons, in response to signals from the axon of a presynaptic neuron. These morphological factors are in turn sculpted by the graph-like dynamics of the actin cytoskeleton. In this project, we seek to use Dynamical Graph Grammars (DGGs) [1,2] implemented within a computer algebra system to model how networks of actin filaments can dynamically grow or shrink and reshape the spine head. We designed and implemented several DGG sub-grammar mathematical models including actin network growth, isotropic/anisotropic filament forces, filament-membrane mechanical interaction, and Hessian Boltzmann sampling of random molecular displacements, to regulate the generation and deletion of graph objects. From first principles expressed in about a dozen DGG rules we simulate emergent biomechanics of a simplified network of actin polymers and its interaction with membrane, using very rough parameter estimates, all in two dimensions. We refined this model by incorporating rate constants used in previous models (e.g. [3,4,5]) in each sector, and we are currently recapitulating the previously observed sub-grammar behaviors.

Life is based on energy conversion. In particular, in the nervous system, significant amounts of energy are needed to maintain synaptic transmission and homeostasis. To a large extent, neurons depend on oxidative phosphorylation in mitochondria to meet their high energy demand. For a comprehensive understanding of the metabolic demands in neuronal signaling, accurate models of ATP production in mitochondria are required. Here, we present a thermodynamically consistent model of ATP production in mitochondria based on previous work. The significant improvement of the model is that the reaction rate constants are set such that detailed balance is satisfied. Moreover, using thermodynamic considerations, the dependence of the reaction rate constants on membrane potential, pH, and substrate concentrations are explicitly provided. These constraints assure that the model is physically plausible. Furthermore, we explore different parameter regimes to understand in which conditions ATP production or its export are the limiting steps in making ATP available in the cytosol. The outcomes reveal that, under the conditions used in our simulations, ATP production is the limiting step and not its export. Finally, we performed spatial simulations with nine 3-D realistic mitochondrial reconstructions and linked the ATP production rate in the cytosol with morphological features of the organelles.

One of the early hallmarks of Huntington's disease (HD) is neuronal cell atrophy, especially in the striatum, underlying motor dysfunction in HD. Here using a computer model, we have predicted the impact of cell shrinkage on calcium dynamics at the cellular level. Our model indicates that as cytosolic volume decreases, the amplitude of calcium transients increases and the endoplasmic reticulum (ER) becomes more leaky due to calcium-induced calcium release and a "toxic" positive feedback mechanism mediated by ryanodine receptors that greatly increases calcium release into the cytosol. The excessive calcium release from ER saturates the calcium buffering capacity of calbindin and forces further accumulation of free calcium in the cytosol and cellular compartments including mitochondria. This leads to imbalance of calcium in both cytosol and ER regions. Excessive calcium accumulation in the cytosol can damage the mitochondria resulting in metabolic dysfunction in the cell consistent with the pathology of HD. Our computational model points toward potential drug targets and can accelerate and greatly help the experimental studies of HD paving the way for treatments of patients suffering from HD.

In the highly dynamic metabolic landscape of a neuron, mitochondrial membrane architectures can provide critical insight into the unique energy balance of the cell. Current theoretical calculations of functional outputs like ATP and heat often represent mitochondria as idealized geometries and therefore can miscalculate the metabolic fluxes. To analyze mitochondrial morphology in neurons of mouse cerebellum neuropil, 3D tracings of complete synaptic and axonal mitochondria were constructed using a database of serial TEM tomography images and converted to watertight meshes with minimal distortion of the original microscopy volumes with a granularity of 1.6 nanometer isotropic voxels. The resulting in silico representations were subsequently quantified by differential geometry methods in terms of the mean and Gaussian curvatures, surface areas, volumes, and membrane motifs, all of which can alter the metabolic output of the organelle. Finally, we identify structural motifs that are present across this population of mitochondria; observations which may contribute to future modeling studies of mitochondrial physiology and metabolism in neurons.

Chemical synapses exhibit a diverse array of internal mechanisms that affect the dynamics of transmission efficacy. Many of these processes, such as release of neurotransmitter and vesicle recycling, depend strongly on activity-dependent influx and accumulation of Ca2+. To model how each of these processes may affect the processing of information in neural circuits, and how their dysfunction may lead to disease states, requires a computationally efficient modelling framework, capable of generating accurate phenomenology without incurring a heavy computational cost per synapse. Constructing a phenomenologically realistic model requires the precise characterization of the timing and probability of neurotransmitter release. Difficulties arise in that functional forms of instantaneous release rate can be difficult to extract from noisy data without running many thousands of trials, and in biophysical synapses, facilitation of per-vesicle release probability is confounded by depletion. To overcome this, we obtained traces of free Ca2+ concentration in response to various action potential stimulus trains from a molecular MCell model of a hippocampal Schaffer collateral axon. Ca2+ sensors were placed at varying distance from a voltage-dependent calcium channel (VDCC) cluster, and Ca2+ was buffered by calbindin. Then, using the calcium traces to drive deterministic state vector models of synaptotagmin 1 and 7 (Syt-1/7), which respectively mediate synchronous and asynchronous release in excitatory hippocampal synapses, we obtained high-resolution profiles of instantaneous release rate, to which we applied functional fits. Synchronous vesicle release occurred predominantly within half a micron of the source of spike-evoked Ca2+ influx, while asynchronous release occurred more consistently at all distances. Both fast and slow mechanisms exhibited multi-exponential release rate curves, whose magnitudes decayed exponentially with distance from the Ca2+ source. Profile parameters facilitate on different time scales according to a single, general facilitation function. These functional descriptions lay the groundwork for efficient mesoscale modelling of vesicular release dynamics.