This work was supported in part by the Sao Paulo State Science Foundation (FAPESP) grant #2015/50122-0 and IRTG-GRTK 1740/2, by the IBM/FAPESP grant #2016/18825-4, and by the FAPESP grant #2018/06504-4.

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The authors declare that they have no competing financial interests.

This article presents a method for the construction of 3D meshes for modeling reaction-diffusion synaptic plasticity processes in a dendritic segment with dendritic spines. The developed model contains a dendritic segment with few dendritic spines. The lateral diffusion and reaction of AMPARs with synaptic anchors allow the simulation of the basal dynamics. The critical steps in the protocol are cutting the sphere for the creation of the top of the spine head (Figure 1, Figure 2, Figure 3), the extrusion to create the spine neck (Figure 4), and the joining of the dendrite and the spines into a single mesh (Figure 5). It is critical to have a complete overlap between the spine necks and the dendrite; otherwise, the mesh will not be watertight. Other critical steps are the selection of the membrane regions and the definition of the surface classes (Figure 6, Figure 7). Save the files for each critical step with a different name.
Use the mesh analyze tool to ensure that the mesh is watertight, manifold, and outward-facing normal after creating the single spine and after creating the combined dendrite with the spine. If&#160;the mesh fails this analysis, return to the last correct version saved. Some steps may be slightly different depending on the version of the software installed, the operating system, and the type of keyboard.
This protocol simulates the trafficking of AMPAR molecules in the 3D mesh (Figure 8, Figure 9, Figure 10, Figure 11), which is key for neuronal excitatory transmission and synaptic plasticity. The trafficking of single molecules in a 3D mesh is an valuable feature of this model with respect to existing methods based on well-mixed volumes with homogeneous distributions of molecules21,22, which is not the physiological condition at the synapses27. A limitation of this technique is the high computational cost and the slow velocity of simulations that use a high number of copies of each molecule and a high number of chemical reactions between them. This constraint can be overcome by reducing the number of copies of each species.
The construction of a system with a realistic 3D mesh and spatiotemporal tracking of molecules is a powerful tool to test mechanical scenarios that can give great insights about the functioning of systems with a high number of nonlinear variables.

Synaptic plasticity has been associated with learning and memory1. Synaptic plasticity, such as long-term potentiation (LTP) and long-term depression (LTD), is associated respectively with the insertion and removal of AMPA receptors (AMPARs) in and out of the synaptic membrane2. The AMPAR synapses are located on top of the small volume structures called dendritic spines3. Each spine contains a protein dense region in the postsynaptic membrane called the postsynaptic density (PSD). Anchor proteins at the PSD trap AMPARs in the synaptic region. There are few copies of AMPARs within a single synapse and the trafficking and reaction of AMPARs with other species in dendritic spines is a stochastic process2,4. There are several compartmental models of synaptic receptor trafficking at dendritic spines5,6,7,8. However, there is a lack of stochastic computational models of the trafficking of AMPARs associated with synaptic plasticity at the 3D structures of the dendrites and their dendritic spines.
Computational modeling is a useful tool to investigate the mechanisms underlying the dynamics of complex systems such as the reaction-diffusion of AMPARs in dendritic spines during the occurrence of synaptic plasticity9,10,11,12. The model can be used to visualize complex scenarios, varying sensitive parameters and making important predictions in scientific conditions involving many variables that are difficult or impossible to control experimental12,13. Defining the level of detail of a computational model is a fundamental step in obtaining accurate information about the modeled phenomenon. An ideal computational model is a delicate balance between complexity and simplicity to capture the essential characteristics of the natural phenomena without being computationally prohibitive. Computational models that are too detailed can be expensive to compute. On the other hand, systems that are poorly detailed can lack the fundamental components that are essential to capture the dynamics of the phenomenon. Although 3D modeling of dendritic spines is computationally more expensive than 2D and 1D, there are conditions, such as in complex systems with many nonlinear variables reacting and diffusing in time and 3D space, for which modeling at a 3D level is essential to obtain insights about the functioning of the system. Further, the complexity can be reduced carefully to preserve the essential characteristics of a lower-dimensional model.
In a stochastic system with few copies of a given species within a small volume, the average dynamics of the system deviates from the average dynamics of a large population. In this case, the stochastic computational modeling of reaction-diffusing particles is required. This work introduces a method for stochastic modeling reaction-diffusion of a few copies of AMPARs in 3D dendritic spines. The purpose of this method is to develop a 3D computational model of a dendritic segment with dendritic spines and their synapses for modeling synaptic plasticity.
The method uses the software&#160;MCell to solve the model numerically, Blender for constructing 3D meshes, and CellBlender to create and visualize the MCell simulations, including the spatiotemporal reaction-diffusion of molecules in 3D meshes14,15,16. Blender is a suite for the creation of meshes and CellBlender is an add-on for the base software Blender. MCell is a Monte Carlo simulator for the reaction-diffusion of single molecules17.
The rationale behind the use of this method consists of modeling synaptic plasticity to achieve a better understanding of this phenomenon in the microphysiological environment of the dendritic spines14. Particularly, this method allows the simulation of homosynaptic potentiation, homosynaptic depression, and heterosynaptic plasticity between dendritic spines14.
The features of this method include modeling the 3D geometric structure of the dendrite and its synapses, the diffusion by random walk, and the chemical reactions of the molecules involved with synaptic plasticity. This method provides the advantage of creating rich environments to test hypotheses and make predictions about the functioning of a complex nonlinear system with a large number of variables. In addition, this method can be applied not only for studying synaptic plasticity but also for studying stochastic reaction-diffusion of molecules in 3D mesh structures in general.
Alternatively, 3D meshes of dendritic structures can be constructed directly in Blender from electron microscope serial reconstructions18. Although meshes based on serial reconstructions provide 3D structures, access to the experimental data is not always available. Thus, the construction of meshes adapted from basic geometric structures, as described in the present protocol, provides flexibility to develop customized dendritic segments with dendritic spines.
Another alternative computational method is the bulk simulation of well-mixed reactions in a regular volume9,10,11,19,20,21,22. The bulk simulations are very efficient in solving the reactions of many species within a single well-mixed volume23, but the bulk approach is extremely slow to solve the reaction-diffusion of molecules within many well-mixed voxels in a high-resolution 3D mesh. On the other hand, the present method using MCell simulations of reaction-diffusion of individual particles works efficiently in high-resolution 3D meshes15.
Before using this method, one should ask whether the phenomenon studied requires a stochastic reaction-diffusion approach in a 3D mesh. If the phenomenon has few copies (less than 1,000) of at least one of the reacting species diffusing in a complex geometric structure with small volume compartments such as dendritic spines, then stochastic modeling of reaction-diffusion in 3D meshes is appropriate for the application.
There are several steps required to construct a 3D computational model of a dendritic segment containing dendritic spines with synaptic plasticity. The main steps are the installation of the proper software for the construction of the model, the construction of a single dendritic spine to be used as a template to create multiple spines, and the creation of a dendritic segment that is connected with multiple dendritic spines. The step for modeling synaptic plasticity consists of inserting anchors at&#160;the PSD region and AMPARs in the dendritic segment and dendritic spines. Then, kinetic reactions between the anchors located at&#160;the PSD and AMPARs are defined to produce complexed anchor-AMPAR species that trap the AMPARs at&#160;the synaptic region. Respectively, the increase and decrease of the affinity between the anchors and the synaptic AMPARs create the process of LTP and LTD.

<table><tbody><tr><td>Blender</td><td>Blender Foundation</td><td></td><td>https://www.blender.org/</td></tr><tr><td>CellBlender</td><td>University of Pittsburgh</td><td></td><td>https://mcell.org/</td></tr><tr><td>Mcell</td><td>University of Pittsburgh</td><td></td><td>https://mcell.org/</td></tr></tbody></table>

3d modeling of dendritic spines with synaptic plasticity

Computational modeling of diffusion and reaction of chemical species in a three-dimensional (3D) geometry is a fundamental method to understand the mechanisms of synaptic plasticity in dendritic spines. In this protocol, the detailed 3D structure of the dendrites and dendritic spines is modeled with meshes on the software Blender with CellBlender. The synaptic and extrasynaptic regions are defined on the mesh. Next, the synaptic receptor and synaptic anchor molecules are defined with their diffusion constants. Finally, the chemical reactions between synaptic receptors and synaptic anchors are included and the computational model is solved numerically with the software MCell. This method describes the spatiotemporal path of every single molecule in a 3D geometrical structure. Thus, it is very useful to study the trafficking of synaptic receptors in and out of the dendritic spines during the occurrence of synaptic plasticity. A limitation of this method is that the high number of molecules slows the speed of the simulations. Modeling of dendritic spines with this method allows the study of homosynaptic potentiation and depression within single spines and heterosynaptic plasticity between neighbor dendritic spines.

These results provide the steps for the construction of a 3D mesh that simulates a dendritic spine with a spine head and spine neck (Figure 1 to Figure 4). In addition, multiple dendritic spines can be inserted in a single dendritic segment (Figure 5) to study heterosynaptic plasticity of AMPARs14. The PSD on the top of the spine head (Figure 6) is the place where synaptic anchors bind to AMPARs and trap them temporarily at the synapse (Figure 7, Figure 8).
Synaptic plasticity could be verified roughly through changes in the number of species of anchor_AMPAR, anchor_AMPAR_LTP, and anchor_AMPAR_LTD at each spine. For the exact calculation of the occurrence of synaptic plasticity, it is recommended to calculate the variation in the total number of anchored and free AMPARs at the synapse. This can be performed using third-party programs to open the saved data of the simulation to summate the time series of the free AMPARs and the anchored AMPARs at each PSD (Figure 8).
The release of AMPARs on the mesh allowed the observation of their diffusion by a stochastic random walk along the dendrite and dendritic spines. Factors that modify the affinity of AMPARs for the anchors, such as posttranslational modifications and alterations of the rates of endocytosis and exocytosis, can trap the AMPARs at the PSD24,25,26. The binding of AMPARs with the anchors located at the PSD trapped a high density of AMPARs at the synapse. Homosynaptic potentiation (Figure 9) and depression (Figure 10) could be verified respectively through increases and decreases in the number of anchored AMPARs caused by changes in the affinity of AMPARs by anchors in comparison to the basal condition (Figure 11). Factors that reduced the affinity of AMPARs with the anchors released multiple AMPARs from one dendritic spine (i.e., homosynaptic depression) and induced heterosynaptic potentiation at the neighboring spines. Also, factors that increased the affinity of AMPARs for the anchors at one spine induced homosynaptic potentiation at that spine and heterosynaptic depression at the neighboring spines14. In this way, heterosynaptic plasticity was observed as the opposite effect at the neighboring spines of the homosynaptic plasticity induced at a given spine. For instance, homosynaptic LTP induction at a single spine created a heterosynaptic LTD effect at the neighboring spines (Figure 8E,F,G).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/60896/60896fig01.jpg" /> 
Figure 1: Creation of the dendritic spine head using a spherical mesh.&#160;(A) Adding the UV sphere. (B) Setting up the sphere dimensions. (C) Observing the created sphere. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/60896/60896fig02.jpg" /> 
Figure 2: Construction of the top region.&#160;(A) Selecting the top region of the sphere. (B) Removing the selected region to make it flat. (C) Sealing the flat top. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/60896/60896fig03.jpg" /> 
Figure 3: Creating concentric areas on the top of the spine.&#160;(A) Visualizing the top. (B) Using a knife to define a concentric region. (C) Creating multiple concentric regions. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/60896/60896fig04.jpg" /> 
Figure 4: Creating the dendritic spine neck.&#160;(A) Selecting the bottom of the modified sphere. (B) Deleting the selected vertices. (C) Selecting the bottom. (D) Extrusion of the bottom to create the spine neck. (E) Sealing the bottom of the spine neck. (F) Analyzing the created spine. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/60896/60896fig05.jpg" /> 
Figure 5: Creation of the dendrite with multiple spines.&#160;(A) Using the cylindrical mesh to create a dendrite. (B) Aligning the dendritic spine with the cylinder. (C) Joining the cylinder with the spine. (D) The Boolean operation to join the meshes. (E) The new combined mesh. (F) Adding the second spine. (G) Adding the third spine. (H) Adding the fourth spine. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/60896/60896fig06.jpg" /> 
Figure 6: Defining the PSD region and the perisynaptic zone.&#160;(A) Selecting the PSD region. (B) Detailed view of the created PSD. (C) Defining the PSD surface region. (D) Selecting and defining the perisynaptic zone around the PSD. (E) Selecting and defining the lateral surface of the dendrite. (F) Defined surface regions. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/60896/60896fig07.jpg" /> 
Figure 7: Defining the surface molecules.&#160;(A) Defining AMPAR, anchor, and AMPAR bound to anchor. (B) Defining the location and quantity of AMPAR copies. (C) Defining the Surface Classes. (D) Assigning the Surface Classes. (E) Creating the chemical reactions between the molecules. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/60896/60896fig08.jpg" /> 
Figure 8: Representative results of synaptic plasticity.&#160;(A) Different meshes of a dendritic segment with two, four, or eight spines. (B) A different view of the dendritic segment with eight spines. (C) Detailed view of a dendritic spine with AMPARs and anchors at the PSD. (D) Diagram of the trafficking of AMPARs in and out of the PSD through their interactions with the anchors. (E-G) The curves show the number of synaptic AMPARs at each PSD for the basal condition and during LTP and LTD. The induction of homosynaptic LTP or LTD at a single spine created a heterosynaptic effect in the nearby spines for the mesh with two spines (E), four spines (F), and eight spines (G). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/60896/60896fig09.jpg" /> 
Figure 9: Representative result of the LTP condition.&#160;(A) The x-axis is the time and the y-axis is the number of the complex anchor_LTP_AMPAR at PSD1. There was a release of 200 free anchor_LTP at the beginning of the simulation. A higher number of bonds with anchors was formed in comparison to the basal condition (Figure 11) <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig09large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/60896/60896fig10.jpg" /> 
Figure 10: Representative result of the LTD condition.&#160;(A) The x-axis is the time and the y-axis is the number of the complex anchor_LTD_AMPAR at PSD1. There was a release of 200 free anchor_LTD at the beginning of the simulation. A lower number of bonds with anchors was&#160;formed in comparison to the basal condition (Figure 11). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 11" class="xfigimg" src="/files/ftp_upload/60896/60896fig11.jpg" /> 
Figure 11: Representative result during basal condition.&#160;(A) The x-axis is the time and the y-axis is the number of the complex anchor_AMPAR at PSD1. There was a release of 200 free anchors at the beginning of the simulation. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/60896fig11large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary File 1. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/60896/Supplementary_File_1.xlsx" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about 3D Modeling of Dendritic Spines with Synaptic Plasticity at JoVE.com

3D Modeling of Dendritic Spines with Synaptic Plasticity

The protocol develops a three-dimensional (3D) model of a dendritic segment with dendritic spines for modeling synaptic plasticity. The constructed mesh can be used for computational modeling of AMPA receptor trafficking in the long-term synaptic plasticity using the software program Blender with CellBlender and MCell.

Computational modeling of diffusion and reaction of chemical species in a three-dimensional (3D) geometry is a fundamental method to understand the ...

3d-modeling-of-dendritic-spines-with-synaptic-plasticity

Universidad San Sebastian

Research

JoVE Journal

Neuroscience

6.7K Views.  Federal University of ABC. The protocol develops a three-dimensional (3D) model of a dendritic segment with dendritic spines for modeling synaptic plasticity. The constructed mesh can be used for computational modeling of AMPA receptor trafficking in the long-term synaptic plasticity using the software program Blender with CellBlender and MCell.

Video: 3D Modeling of Dendritic Spines with Synaptic Plasticity

Preparation of Oligomeric &beta;-amyloid1-42 and Induction of Synaptic Plasticity Impairment on Hippocampal Slices

Impairment of synaptic connections is likely to underlie the subtle amnesic changes occurring at the early stages of Alzheimer s Disease (AD). &beta;-amyloid (A&beta;), a peptide produced in high amounts in AD, is known to reduce Long-Term Potentiation (LTP), a cellular correlate of learning and memory. Indeed, LTP impairment caused by A&beta; is a useful experimental paradigm for studying synaptic dysfunctions in AD models and for screening drugs capable of mitigating or reverting such synaptic impairments. Studies have shown that A&beta; produces the LTP disruption preferentially via its oligomeric form. Here we provide a detailed protocol for impairing LTP by perfusion of oligomerized synthetic A&beta;1-42 peptide onto acute hippocampal slices. In this video, we outline a step-by-step procedure for the preparation of oligomeric A&beta;1-42. Then, we follow an individual experiment in which LTP is reduced in hippocampal slices exposed to oligomerized A&beta;1-42 compared to slices in a control experiment where no A&beta;1-42 exposure had occurred.

Preparation of Oligomeric &#946;-amyloid1-42 and Induction of Synaptic Plasticity Impairment on Hippocampal Slices

One feature of Alzheimer's Disease is the elevation of A&beta;1-42 peptide. Here we provide a protocol for preparing synthetic A&beta;1-42 oligomers, which impairs hippocampal Long-Term Potentiation, a cellular correlate of memory. This procedure is useful for investigating mechanisms of A&beta;-induced pathology and drug screening.

Impairment of synaptic connections is likely to underlie the subtle amnesic changes occurring at the early stages of Alzheimer s Disease (AD). ...

Three-dimensional Quantification of Dendritic Spines from Pyramidal Neurons Derived from Human Induced Pluripotent Stem Cells

Dendritic spines are small protrusions that correspond to the post-synaptic compartments of excitatory synapses in the central nervous system. They are distributed along the dendrites. Their morphology is largely dependent on neuronal activity, and they are dynamic. Dendritic spines express glutamatergic receptors (AMPA and NMDA receptors) on their surface and at the levels of postsynaptic densities. Each spine allows the neuron to control its state and local activity independently. Spine morphologies have been extensively studied in glutamatergic pyramidal cells of the brain cortex, using both in vivo approaches and neuronal cultures obtained from rodent tissues. Neuropathological conditions can be associated to altered spine induction and maturation, as shown in rodent cultured neurons and one-dimensional quantitative analysis 1. The present study describes a protocol for the 3D quantitative analysis of spine morphologies using human cortical neurons derived from neural stem cells (late cortical progenitors). These cells were initially obtained from induced&#160;pluripotent stem cells. This protocol allows the analysis of spine morphologies at different culture periods, and with possible comparison between induced&#160;pluripotent stem cells obtained from control individuals with those obtained from patients with psychiatric diseases.

Dendritic spines of pyramidal neurons are the sites of most excitatory synapses in mammalian brain cortex. This method describes a 3D quantitative analysis of spine morphologies in human cortical pyramidal glutamatergic neurons derived from induced&#160;pluripotent stem cells.

Dendritic spines are small protrusions that correspond to the post-synaptic compartments of excitatory synapses in the central nervous system. They are ...

Developmental Biology

Fluorescence Recovery After Photobleaching (FRAP) of Fluorescence Tagged Proteins in Dendritic Spines of Cultured Hippocampal Neurons

FRAP has been used to quantify the mobility of GFP-tagged proteins. Using a strong excitation laser, the fluorescence of a GFP-tagged protein is bleached in the region of interest. The fluorescence of the region recovers when the unbleached GFP-tagged protein from outside of the region diffuses into the region of interest. The mobility of the protein is then analyzed by measuring the fluorescence recovery rate. This technique could be used to characterize protein mobility and turnover rate.
In this study, we express the (enhanced green fluorescent protein) EGFP vector in cultured hippocampal neurons. Using the Zeiss 710 confocal microscope, we photobleach the fluorescence signal of the GFP protein in a single spine, and then take time lapse images to record the fluorescence recovery after photobleaching. Finally, we estimate the percentage of mobile and immobile fractions of the GFP in spines, by analyzing the imaging data using ImageJ and Graphpad softwares.
This FRAP protocol shows how to perform a basic FRAP experiment as well as how to analyze the data.

Fluorescence Recovery After Photobleaching FRAP of Fluorescence Tagged Proteins in Dendritic Spines of Cultured Hippocampal Neurons

FRAP has been used to quantify the mobility of Green Fluorescence Protein (GFP)-tagged proteins in cultured cells. We examined the mobile/immobile fractions of the GFP by analyzing the fluorescence recovery percentage after photobleaching. In this study, FRAP was performed at spines of hippocampal neurons.

FRAP has been used to quantify the mobility of GFP-tagged proteins. Using a strong excitation laser, the fluorescence of a GFP-tagged protein is bleached ...

Analysis of Dendritic Spine Morphology in Cultured CNS Neurons

Dendritic spines are the sites of the majority of excitatory connections within the brain, and form the post-synaptic 
compartment of synapses. These structures are rich in actin and have been shown to be highly dynamic. In response to classical Hebbian plasticity 
as well as neuromodulatory signals, dendritic spines can change shape and number, which is thought to be critical for the refinement of neural 
circuits and the processing and storage of information within the brain. Within dendritic spines, a complex network of proteins link extracellular 
signals with the actin cyctoskeleton allowing for control of dendritic spine morphology and number. Neuropathological studies have demonstrated that 
a number of disease states, ranging from schizophrenia to autism spectrum disorders, display abnormal dendritic spine morphology or numbers. 
Moreover, recent genetic studies have identified mutations in numerous genes that encode synaptic proteins, leading to suggestions that these 
proteins may contribute to aberrant spine plasticity that, in part, underlie the pathophysiology of these disorders. In order to study the potential 
role of these proteins in controlling dendritic spine morphologies/number, the use of cultured cortical neurons offers several advantages. Firstly, 
this system allows for high-resolution imaging of dendritic spines in fixed cells as well as time-lapse imaging of live cells. Secondly, this in 
vitro system allows for easy manipulation of protein function by expression of mutant proteins, knockdown by shRNA constructs, or pharmacological 
treatments. These techniques allow researchers to begin to dissect the role of disease-associated proteins and to predict how mutations of these 
proteins may function in vivo.

Numerous recent studies have identified mutations in synaptic proteins associated with brain pathologies. Primary cultured cortical neurons offer great flexibility in examining the effects of these disease-associated proteins on dendritic spine morphology and motility.

Dendritic spines are the sites of the majority of excitatory connections within the brain, and form the post-synaptic 
compartment of synapses. These ...

Lateral Diffusion and Exocytosis of Membrane Proteins in Cultured Neurons Assessed using Fluorescence Recovery and Fluorescence-loss Photobleaching

Membrane proteins such as receptors and ion channels undergo active trafficking in neurons, which are highly polarised and morphologically complex. This directed trafficking is of fundamental importance to deliver, maintain or remove synaptic proteins.
Super-ecliptic pHluorin (SEP) is a pH-sensitive derivative of eGFP that has been extensively used for live cell imaging of plasma membrane proteins1-2. At low pH, protonation of SEP decreases photon absorption and eliminates fluorescence emission. As most intracellular trafficking events occur in compartments with low pH, where SEP fluorescence is eclipsed, the fluorescence signal from SEP-tagged proteins is predominantly from the plasma membrane where the SEP is exposed to a neutral pH extracellular environment. When illuminated at high intensity SEP, like every fluorescent dye, is irreversibly photodamaged (photobleached)3-5. Importantly, because low pH quenches photon absorption, only surface expressed SEP can be photobleached whereas intracellular SEP is unaffected by the high intensity illumination6-10. 
FRAP (fluorescence recovery after photobleaching) of SEP-tagged proteins is a convenient and powerful technique for assessing protein dynamics at the plasma membrane. When fluorescently tagged proteins are photobleached in a region of interest (ROI) the recovery in fluorescence occurs due to the movement of unbleached SEP-tagged proteins into the bleached region. This can occur via lateral diffusion and/or from exocytosis of non-photobleached receptors supplied either by de novo synthesis or recycling (see Fig. 1). The fraction of immobile and mobile protein can be determined and the mobility and kinetics of the diffusible fraction can be interrogated under basal and stimulated conditions such as agonist application or neuronal activation stimuli such as NMDA or KCl application8,10. 
We describe photobleaching techniques designed to selectively visualize the recovery of fluorescence attributable to exocytosis. Briefly, an ROI is photobleached once as with standard FRAP protocols, followed, after a brief recovery, by repetitive bleaching of the flanking regions. This 'FRAP-FLIP' protocol, developed in our lab, has been used to characterize AMPA receptor trafficking at dendritic spines10, and is applicable to a wide range of trafficking studies to evaluate the intracellular trafficking and exocytosis.

This report describes the use of live cell imaging and photobleach techniques to determine the surface expression, transport pathways and trafficking kinetics of exogenously expressed, pH-sensitive GFP-tagged proteins at the plasma membrane of neurons.

Membrane proteins such as receptors and ion channels undergo active trafficking in neurons, which are highly polarised and morphologically complex. This ...

Fast Micro-iontophoresis of Glutamate and GABA: A Useful Tool to Investigate Synaptic Integration

One of the fundamental interests in neuroscience is to understand the integration of excitatory and inhibitory inputs along the very complex structure of the dendritic tree, which eventually leads to neuronal output of action potentials at the axon. The influence of diverse spatial and temporal parameters of specific synaptic input on neuronal output is currently under investigation, e.g. the distance-dependent attenuation of dendritic inputs, the location-dependent interaction of spatially segregated inputs, the influence of GABAergig inhibition on excitatory integration, linear and non-linear integration modes, and many more.
With fast micro-iontophoresis of glutamate and GABA it is possible to precisely investigate the spatial and temporal integration of glutamatergic excitation and GABAergic inhibition. Critical technical requirements are either a triggered fluorescent lamp, light-emitting diode (LED), or a two-photon scanning microscope to visualize dendritic branches without introducing significant photo-damage of the tissue. Furthermore, it is very important to have a micro-iontophoresis amplifier that allows for fast capacitance compensation of high resistance pipettes. Another crucial point is that no transmitter is involuntarily released by the pipette during the experiment.
Once established, this technique will give reliable and reproducible signals with a high neurotransmitter and location specificity. Compared to glutamate and GABA uncaging, fast iontophoresis allows using both transmitters at the same time but at very distant locations without limitation to the field of view. There are also advantages compared to focal electrical stimulation of axons: with micro-iontophoresis the location of the input site is definitely known and it is sure that only the neurotransmitter of interest is released. However it has to be considered that with micro-iontophoresis only the postsynapse is activated and presynaptic aspects of neurotransmitter release are not resolved. In this article we demonstrate how to set up micro-iontophoresis in brain slice experiments.

In this article we introduce fast micro-iontophoresis of neurotransmitters as a technique to investigate integration of postsynaptic signals with high spatial and temporal precision.

One of the fundamental interests in neuroscience is to understand the integration of excitatory and inhibitory inputs along the very complex structure of ...

Deriving the Time Course of Glutamate Clearance with a Deconvolution Analysis of Astrocytic Transporter Currents

The highest density of glutamate transporters in the brain is found in astrocytes. Glutamate transporters couple the movement of glutamate across the membrane with the co-transport of 3 Na+ and 1 H+ and the counter-transport of 1 K+. The stoichiometric current generated by the transport process can be monitored with whole-cell patch-clamp recordings from astrocytes. The time course of the recorded current is shaped by the time course of the glutamate concentration profile to which astrocytes are exposed, the kinetics of glutamate transporters, and the passive electrotonic properties of astrocytic membranes. Here we describe the experimental and analytical methods that can be used to record glutamate transporter currents in astrocytes and isolate the time course of glutamate clearance from all other factors that shape the waveform of astrocytic transporter currents. The methods described here can be used to estimate the lifetime of flash-uncaged and synaptically-released glutamate at astrocytic membranes in any region of the central nervous system during health and disease.

We describe an analytical method to estimate the lifetime of glutamate at astrocytic membranes from electrophysiological recordings of glutamate transporter currents in astrocytes.

The highest density of glutamate transporters in the brain is found in astrocytes. Glutamate transporters couple the movement of glutamate across the ...

Imaging Dendritic Spines of Rat Primary Hippocampal Neurons using Structured Illumination Microscopy

Dendritic spines are protrusions emerging from the dendrite of a neuron and represent the primary postsynaptic targets of excitatory inputs in the brain. Technological advances have identified these structures as key elements in neuron connectivity and synaptic plasticity. The quantitative analysis of spine morphology using light microscopy remains an essential problem due to technical limitations associated with light's intrinsic refraction limit. Dendritic spines can be readily identified by confocal laser-scanning fluorescence microscopy. However, measuring subtle changes in the shape and size of spines is difficult because spine dimensions other than length are usually smaller than conventional optical resolution fixed by light microscopy's theoretical resolution limit of 200 nm.
Several recently developed super resolution techniques have been used to image cellular structures smaller than the 200 nm, including dendritic spines. These techniques are based on classical far-field operations and therefore allow the use of existing sample preparation methods and to image beyond the surface of a specimen. Described here is a working protocol to apply super resolution structured illumination microscopy (SIM) to the imaging of dendritic spines in primary hippocampal neuron cultures. Possible applications of SIM overlap with those of confocal microscopy. However, the two techniques present different applicability. SIM offers higher effective lateral resolution, while confocal microscopy, due to the usage of a physical pinhole, achieves resolution improvement at the expense of removal of out of focus light. In this protocol, primary neurons are cultured on glass coverslips using a standard protocol, transfected with DNA plasmids encoding fluorescent proteins and imaged using SIM. The whole protocol described herein takes approximately 2 weeks, because dendritic spines are imaged after 16-17 days in vitro, when dendritic development is optimal. After completion of the protocol, dendritic spines can be reconstructed in 3D from series of SIM image stacks using specialized software.

This article describes a working protocol to image dendritic spines from hippocampal neurons in vitro using Structured Illumination Microscopy (SIM). Super-resolution microscopy using SIM provides image resolution significantly beyond the light diffraction limit in all three spatial dimensions, allowing the imaging of individual dendritic spines with improved detail.

Dendritic spines are protrusions emerging from the dendrite of a neuron and represent the primary postsynaptic targets of excitatory inputs in the brain. ...

Two-Photon in vivo Imaging of Dendritic Spines in the Mouse Cortex Using a Thinned-skull Preparation

In the mammalian cortex, neurons form extremely complicated networks and exchange information at synapses. Changes in synaptic strength, as well as addition/removal of synapses, occur in an experience-dependent manner, providing the structural foundation of neuronal plasticity. As postsynaptic components of the most excitatory synapses in the cortex, dendritic spines are considered to be a good proxy of synapses. Taking advantages of mouse genetics and fluorescent labeling techniques, individual neurons and their synaptic structures can be labeled in the intact brain. Here we introduce a transcranial imaging protocol using two-photon laser scanning microscopy to follow fluorescently labeled postsynaptic dendritic spines over time in vivo. This protocol utilizes a thinned-skull preparation, which keeps the skull intact and avoids inflammatory effects caused by exposure of the meninges and the cortex. Therefore, images can be acquired immediately after surgery is performed. The experimental procedure can be performed repetitively over various time intervals ranging from hours to years. The application of this preparation can also be expanded to investigate different cortical regions and layers, as well as other cell types, under physiological and pathological conditions.

Two-Photon in vivo Imaging of Dendritic Spines in the Mouse Cortex Using a Thinned-skull Preparation

Time-lapse imaging in the living animal provides valuable information on structural reorganization in the intact brain. Here, we introduce a thinned-skull preparation that allows transcranial imaging of fluorescently labeled synaptic structures in the living mouse cortex by two-photon microscopy.

In the mammalian cortex, neurons form extremely complicated networks and exchange information at synapses. Changes in synaptic strength, as well as ...

Protocol for Dendritic Spine Analysis Using Neurolucida 360

Dendritic Spine Quantification Using an Automatic Three-Dimensional Neuron Reconstruction Software

Synaptic connections allow for the exchange and processing of information between neurons. The post-synaptic site of excitatory synapses is often formed on dendritic spines. Dendritic spines are structures of great interest in research centered around synaptic plasticity, neurodevelopment, and neurological and psychiatric disorders. Dendritic spines undergo structural modifications during their lifespan, with properties such as total spine number, dendritic spine size, and morphologically defined subtype altering in response to different processes. Delineating the molecular mechanisms regulating these structural alterations of dendritic spines relies on morphological measurement. This mandates accurate and reproducible dendritic spine analysis to provide experimental evidence. The present study outlines a detailed protocol for dendritic spine quantification and classification using Neurolucida 360 (automatic three-dimensional neuron reconstruction software). This protocol allows for the determination of key dendritic spine properties such as total spine density, spine head volume, and classification into spine subtypes thus enabling effective analysis of dendritic spine structural phenotypes.

Author Spotlight: Optimizing Dendritic Spine Analysis for Balanced Manual and Automated Assessment in the Hippocampus CA1 Apical Dendrites

Dendritic spines are post-synaptic compartments of most excitatory synapses. Alterations to dendritic spine morphology occur during neurodevelopment, aging, learning, and many neurological and psychiatric disorders, underscoring the importance of reliable dendritic spine analysis. This protocol describes quantifying dendritic spine morphology accurately and reproducibly using automatic three-dimensional neuron reconstruction software.

Synaptic connections allow for the exchange and processing of information between neurons. The post-synaptic site of excitatory synapses is often formed ...

3D Modeling of Dendritic Spines with Synaptic Plasticity

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Preparation of Oligomeric β-amyloid_1-42 and Induction of Synaptic Plasticity Impairment on Hippocampal Slices

Three-dimensional Quantification of Dendritic Spines from Pyramidal Neurons Derived from Human Induced Pluripotent Stem Cells

Fluorescence Recovery After Photobleaching (FRAP) of Fluorescence Tagged Proteins in Dendritic Spines of Cultured Hippocampal Neurons

Analysis of Dendritic Spine Morphology in Cultured CNS Neurons

Lateral Diffusion and Exocytosis of Membrane Proteins in Cultured Neurons Assessed using Fluorescence Recovery and Fluorescence-loss Photobleaching

Fast Micro-iontophoresis of Glutamate and GABA: A Useful Tool to Investigate Synaptic Integration

Deriving the Time Course of Glutamate Clearance with a Deconvolution Analysis of Astrocytic Transporter Currents

Imaging Dendritic Spines of Rat Primary Hippocampal Neurons using Structured Illumination Microscopy

Two-Photon in vivo Imaging of Dendritic Spines in the Mouse Cortex Using a Thinned-skull Preparation

Dendritic Spine Quantification Using an Automatic Three-Dimensional Neuron Reconstruction Software