Biology subjects

Bartol, T. M.

Publications and source records attributed to Bartol, T. M..

18 recordsLinked to original sources

bioRxiv2025

Presynaptic vesicles supply membrane for axonal bouton enlargement during LTP

Long-term potentiation (LTP) induces presynaptic bouton enlargement and a reduction in the number of synaptic vesicles. To understand the relationship between these events, we performed 3D analysis of serial section electron micrographs in rat hippocampal area CA1, 2 hours after LTP induction. We observed a high vesicle packing density in control boutons, contrasting with a lower density in most LTP boutons. Notably, the summed membrane area of the vesicles lost in low-density LTP boutons is comparable to the surface membrane required for the observed bouton enlargement when compared to high-density control boutons. These novel findings suggest that presynaptic vesicle density provides a new structural indicator of LTP that supports a local mechanism of bouton enlargement.

neuroscience↗

bioRxiv2024

The presynaptic vesicle cluster transitions from a compact to loose organization during long-term potentiation

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.

neuroscience↗

bioRxiv2024

Geometric tortuosity at invaginating rod synapses slows glutamate diffusion and shapes synaptic responses: insights from anatomically realistic Monte Carlo simulations

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 Muller 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. Glutamates 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.

neuroscience↗

bioRxiv2024

A spatial model of autophosphorylation of CaMKII in a glutamatergic spine suggests a network-driven kinetic mechanism for bistable changes in synaptic strength.

Long-term potentiation (LTP) is a biochemical process that underlies learning in excitatory glutamatergic synapses in the Central Nervous System (CNS). The 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.

neuroscience↗

bioRxiv2024

Long-Term Potentiation Produces a Sustained Expansion of Synaptic Information Storage Capacity in Adult Rat Hippocampus

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. SignificanceEstablishing relationships between structure, function, and information storage capacity provides a new approach to assessing network strength from structural measurements. Long term potentiation (LTP) is a standard model for investigating synaptic mechanisms of learning and memory. Information is a retrievable quantity that is being stored in synapses as synaptic strength and is correlated with multiple structural components of synaptic strength. Structural synaptic plasticity was measured in 3D reconstructions from serial section electron microscopy of spine head volume, as a proxy for synapse strength, at 30 min and 2 hr after LTP induction. Outcomes indicate that LTP enhances information storage capacity for at least 2 hr by increasing the precision of the synaptic structure and expanding the range of synapse sizes.

neuroscience↗

bioRxiv2022

Regional and LTP-Dependent Variation of Synaptic Information Storage Capacity in Rat Hippocampus

Connectomics is generating an ever-increasing deluge of data, which challenges us to develop new methods for analyzing and extracting insights from these data. We introduce here a powerful method for analyzing three-dimensional reconstruction from serial section electron microscopy (3DEM) to measure synaptic information storage capacity (SISC) and apply it to data following in vivo long-term potentiation (LTP). Connectomic researchers have focused on the pattern of connectivity between neurons. The strengths of synapses have also been studied by quantifying the sizes of synapses. Importantly, synapses from the same axon onto the same dendrite have a common history of coactivation, making them a candidate for measuring the precision of synaptic plasticity based on the similarity of their dimensions. Quantifying precision is fundamental to understanding information storage and retrieval in neural circuits. We quantify this precision with Shannon information theory, which is a more reliable estimate than prior analyses based on signal detection theory because there is no overlap between states, and outliers do not artificially bias the outcome. Spine head volumes are well correlated with other measures of synaptic weight, thus SISC can be determined by identifying the non-overlapping clusters of dendritic spine head volumes to determine the number of distinguishable synaptic weights. SISC analysis of spine head volumes in the stratum radiatum of hippocampal area CA1 revealed 24 distinguishable states (4.1 bits). In contrast, spine head volumes in the middle molecular layer of control dentate gyrus occupied only 5 distinguishable states (2 bits). Thus, synapses in different hippocampal regions had significantly different SISCs. Moreover, these were not fixed properties but increased by 30 min following induction of LTP in the dentate gyrus to occupy 10 distinguishable states (3 bits), and this increase lasted for at least 2 hours. We also observed a broader and nearly uniform distribution of spine head volumes across the increased number of states, suggesting the distribution evolved towards the theoretical upper bound of SISC following LTP. For dentate granule cells these findings show that the spine size range was broadened by the interplay among synaptic plasticity mechanisms. SISC provides a new analytical measure to probe these mechanisms in normal and diseased brains.

neuroscience↗

bioRxiv2022

A thermodynamically-consistent model for ATP production in mitochondria

AO_SCPLOWBSTRACTC_SCPLOWLife 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 (Pekkurnaz and Wang, 2022). 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 (Pietrobon and Caplan, 1985; Magnus and Keizer, 1997; Metelkin et al., 2006; Garcia et al., 2019). 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 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 3D realistic mitochondrial reconstructions and linked the ATP production rate in the cytosol with morphological features of the organelles. 1. SO_SCPLOWUMMARYC_SCPLOWIn this work, Garcia et al present a thermodynamically consistent model for ATP production in mitochondria, in which reaction rate constants are set such that detailed balance is satisfied. Simulations revealed that ATP production, but not its export, is the limiting step, and simulations with 3D mitochondrial reconstructions linked the ATP production rate in the cytosol with the morphological features of the organelles.

cell biology↗

bioRxiv2022

MCell4 with BioNetGen: A Monte Carlo Simulator of Rule-Based Reaction-Diffusion Systems with Python Interface

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. MCell4s 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.

biophysics↗

bioRxiv2021

Multiscale modeling of presynaptic dynamics from molecular to mesoscale

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 mossy fiber 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. Author SummaryMost information transmission between neurons in the brain occurs via release of neurotransmitter from synaptic vesicles. In response to a presynaptic spike, calcium influx at the active zone of a synapse can trigger the release of neurotransmitter with a certain probability. These stochastic release events may occur immediately after a spike or with some delay. As calcium accumulates from one spike to the next, the probability of release may increase (facilitate) for subsequent spikes. This process, known as short-term plasticity, transforms the spiking code to a release code, underlying much of the brains information processing. In this paper, we use an accurate, detailed model of presynaptic molecular physiology to characterize these processes at high precision in response to various spike trains. We then apply model reduction to the results to obtain a phenomenological model of release timing, probability, and facilitation, which can perform as accurately as the molecular model but with far less computational cost. This mesoscale model of spike-evoked release and facilitation helps to bridge the gap between microscale molecular dynamics and macroscale information processing in neural circuits. It can thus benefit large scale modelling of neural circuits, biologically inspired machine learning models, and the design of neuromorphic chips.

neuroscience↗

bioRxiv2021

Morphological principles of neuronal mitochondria

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.

neuroscience↗

bioRxiv2020

Towards Biophysically-Based Neuromorphic Computing at Scale: Markov Abstractions of Electrochemical Reaction-Diffusion in Synaptic Transmission

Progress in computational neuroscience towards understanding brain function is challenged both by the complexity of molecular-scale electrochemical interactions at the level of individual neurons and synapses and the dimensionality of network dynamics across the brain covering a vast range of spatial and temporal scales. Our work abstracts an existing highly detailed, biophysically realistic 3D reaction-diffusion model of a chemical synapse to a compact internal state space representation that maps onto parallel neuromorphic hardware for efficient emulation at a very large scale and offers near-equivalence in input-output dynamics while preserving biologically interpretable tunable parameters.

neuroscience↗

bioRxiv2020

Release sites are positioned to activate NMDA receptors

Neurotransmitter is released synchronously and asynchronously following an action potential. The release sites of these two phases are segregated within an active zone, with asynchronous release sites enriched near the center. Here we demonstrate that synchronous and asynchronous release sites are aligned with AMPA receptor and NMDA receptor clusters, respectively. Computational simulations indicate that this spatial and temporal arrangement of release ensures maximal membrane depolarization through AMPA receptors, alleviating the pore-blocking magnesium leading to greater activation of NMDA receptors. Together, these results suggest that release sites are organized to efficiently activate NMDA receptors.

neuroscience↗

bioRxiv2019

Interactions between calmodulin and neurogranin govern the dynamics of CaMKII as a leaky integrator

Calmodulin-dependent kinase II (CaMKII) has long been known to play an important role in learning and memory as well as long term potentiation (LTP). More recently it has been suggested that it might be involved in the time averaging of synaptic signals, which can then lead to the high precision of information stored at a single synapse. However, the role of the scaffolding molecule, neurogranin (Ng), in governing the dynamics of CaMKII is not yet fully understood. In this work, we adopt a rule-based modeling approach through the Monte Carlo method to study the effect of Ca2+ signals on the dynamics of CaMKII phosphorylation in the postsynaptic density (PSD). Calcium surges are observed in synaptic spines during an EPSP and back-propagating action potential due to the opening of NMDA receptors and voltage dependent calcium channels. We study the differences between the dynamics of phosphorylation of CaMKII monomers and dodecameric holoenzymes. The scaffolding molecule Ng, when present in significant concentration, limits the availability of free calmodulin (CaM), the protein which activates CaMKII in the presence of calcium. We show that it plays an important modulatory role in CaMKII phosphorylation following a surge of high calcium concentration. We find a non-intuitive dependence of this effect on CaM concentration that results from the different affinities of CaM for CaMKII depending on the number of calcium ions bound to the former. It has been shown previously that in the absence of phosphatase CaMKII monomers integrate over Ca2+ signals of certain frequencies through autophosphorylation (Pepke et al, Plos Comp. Bio., 2010). We also study the effect of multiple calcium spikes on CaMKII holoenzyme autophosphorylation, and show that in the presence of phosphatase CaMKII behaves as a leaky integrator of calcium signals, a result that has been recently observed in vivo. Our models predict that the parameters of this leaky integrator are finely tuned through the interactions of Ng, CaM, CaMKII, and PP1. This is a possible mechanism to precisely control the sensitivity of synapses to calcium signals.

neuroscience↗

bioRxiv2019

Specific nanoscale synaptic reshuffling and control of short-term plasticity following NMDAR- and P2XR-dependent Long-Term Depression

Long-Term Potentiation (LTP) and Long-Term Depression (LTD) of excitatory synaptic transmission are considered as cellular basis of learning and memory. These two forms of synaptic plasticity have been mainly attributed to global changes in the number of synaptic AMPA-type glutamate receptor (AMPAR) through a regulation of the diffusion/trapping balance at the PSD, exocytosis and endocytosis. While the precise molecular mechanisms at the base of LTP have been intensively investigated, the ones involved in LTD remains elusive. Here we combined super-resolution imaging technique, electrophysiology and modeling to describe the various modifications of AMPAR nanoscale organization and their effect on synaptic transmission in response to two different LTD protocols, based on the activation of either NMDA receptors or P2X receptors. While both type of LTD are associated with a decrease in synaptic AMPAR clustering, only NMDAR-dependent LTD is associated with a reorganization of PSD-95 at the nanoscale. This change increases the pool of diffusive AMPAR improving synaptic short-term facilitation through a post-synaptic mechanism. These results demonstrate that specific dynamic reorganization of synapses at the nanoscale during specific LTD paradigm allows to improve the responsiveness of depressed synapses.

neuroscience↗

bioRxiv2019

Mitochondrial morphology provides a mechanism for energy buffering at synapses

Mitochondria as the main energy suppliers of eukaryotic cells are highly dynamic organelles that fuse, divide and are transported along the cytoskeleton to ensure cellular energy homeostasis. While these processes are well established, substantial evidence indicates that the internal structure is also highly variable in dependence on metabolic conditions. However, a quantitative mechanistic understanding of how mitochondrial morphology affects energetic states is still elusive. To address this question, we here present an agent-based dynamic model using three-dimensional morphologies from electron microscopy tomography which considers the molecular dynamics of the main ATP production components. We apply our modeling approach to mitochondria at the synapse which is the largest energy consumer within the brain. Interestingly, comparing the spatiotemporal simulations with a corresponding space-independent approach, we find minor space dependence when the system relaxes toward equilibrium but a qualitative difference in fluctuating environments. These results suggest that internal mitochondrial morphology is not only optimized for ATP production but also provides a mechanism for energy buffering and may represent a mechanism for cellular robustness.

biophysics↗

bioRxiv2019

A multi-state model of the CaMKII dodecamer suggests a role for calmodulin in maintenance of autophosphorylation

Ca2+/calmodulin-dependent protein kinase II (CaMKII) accounts for up to 2 percent of all brain protein and is essential to memory function. CaMKII activity is known to regulate dynamic shifts in the size and signaling strength of neuronal connections, a process known as synaptic plasticity. Increasingly, computational models are used to explore synaptic plasticity and the mechanisms regulating CaMKII activity. Conventional modeling approaches may exclude biophysical detail due to the impractical number of state combinations that arise when explicitly monitoring the conformational changes, ligand binding, and phosphorylation events that occur on each of the CaMKII holoenzymes twelve subunits. To manage the combinatorial explosion without necessitating bias or loss in biological accuracy, we use a specialized syntax in the software MCell to create a rule-based model of the twelve-subunit CaMKII holoenzyme. Here we validate the rule-based model against previous measures of CaMKII activity and investigate molecular mechanisms of CaMKII regulation. Specifically, we explore how Ca2+/CaM-binding may both stabilize CaMKII subunit activation and regulate maintenance of CaMKII autophosphorylation. Noting that Ca2+/CaM and protein phosphatases bind CaMKII at nearby or overlapping sites, we compare model scenarios in which Ca2+/CaM and protein phosphatase do or do not structurally exclude each others binding to CaMKII. Our results suggest a functional mechanism for the so-called \"CaM trapping\" phenomenon, such that Ca2+/CaM structurally excludes phosphatase binding and thereby prolongs CaMKII autophosphorylation. We conclude that structural protection of autophosphorylated CaMKII by Ca2+/CaM may be an important mechanism for regulation of synaptic plasticity.\n\nAuthor summaryIn the hippocampus, the dynamic fluctuation in size and strength of neuronal connections is thought to underlie learning and memory processes. These fluctuations, called synaptic plasticity, are in-part regulated by the protein calcium/calmodulin-dependent kinase II (CaMKII). During synaptic plasticity, CaMKII becomes activated in the presence of calcium ions (Ca2+) and calmodulin (CaM), allowing it to interact enzymatically with downstream binding partners. Interestingly, activated CaMKII can phosphorylate itself, resulting in state changes that allow CaMKII to be functionally active independent of Ca2+/CaM. Phosphorylation of CaMKII at Thr-286/287 has been shown to be a critical component of learning and memory. To explore the molecular mechanisms that regulate the activity of CaMKII holoenzymes, we use a rule-based approach that reduces computational complexity normally associated with representing the wide variety of functional states that a CaMKII holoenzyme can adopt. Using this approach we observe regulatory mechanisms that might be obscured by reductive approaches. Our results newly suggest that CaMKII phosphorylation at Thr-286/287 is stabilized by a mechanism in which CaM structurally excludes phosphatase binding at that site.

neuroscience↗

bioRxiv2018

Geometric principles of second messenger dynamics in dendritic spines.

Dendritic spines are small, bulbous protrusions along dendrites in neurons and play a critical role in synaptic transmission. Dendritic spines come in a variety of shapes that depend on their developmental state. Additionally, roughly 14-19% of mature spines have a specialized endoplasmic reticulum called the spine apparatus. How does the shape of a postsynaptic spine and its internal organization affect the spatio-temporal dynamics of short timescale signaling? Answers to this question are central to our understanding the initiation of synaptic transmission, learning, and memory formation. In this work, we investigated the effect of spine and spine apparatus size and shape on the spatio-temporal dynamics of second messengers using mathematical modeling using reaction-diffusion equations in idealized geometries (ellipsoids, spheres, and mushroom-shaped). Our analyses and simulations showed that in the short timescale, spine size and shape coupled with the spine apparatus geometries govern the spatiotemporal dynamics of second messengers. We show that the curvature of the geometries gives rise to pseudo-harmonic functions, which predict the locations of maximum and minimum concentrations along the spine head. Furthermore, we showed that the lifetime of the concentration gradient can be fine-tuned by localization of fluxes on the spine head and varying the relative curvatures and distances between the spine apparatus and the spine head. Thus, we have identified several key geometric determinants of how the spine head and spine apparatus may regulate the short timescale chemical dynamics of small molecules that control synaptic plasticity.

biophysics↗

bioRxiv2017

Pre-post synaptic alignment through neuroligin tunes synaptic transmission efficiency

The nanoscale organization of neurotransmitter receptors relative to pre-synaptic release sites is a fundamental determinant of both the amplitude and reliability of synaptic transmission. How modifications in the alignment between pre- and post-synaptic machineries affect synaptic current properties has only been addressed with computer modeling, and therefore remains hypothetical. Using dual-color single molecule based super-resolution microscopy, we found a strong spatial correlation between AMPA receptor (AMPAR) nanodomains and the post-synaptic adhesion protein neuroligin-1 (NLG1). Expression of a C-terminal truncated form of NLG1 disrupted this correlation without affecting the intrinsic organization of AMPAR nanodomains. Moreover, this NLG1 dominant-negative mutant significantly shifted the pre-synaptic release machinery from AMPAR synaptic clusters. Electrophysiology and computer modeling show that this physical shift is sufficient to induce a significant decrease in synaptic transmission. Thus, our results suggest the necessity for synapses to release glutamate in front of AMPAR nanodomains, to maintain a high efficiency of synaptic responses.

neuroscience↗