Name: Author Spotlight: Optimizing Dendritic Spine Analysis for Balanced Manual and Automated Assessment in the Hippocampus CA1 Apical Dendrites
Uploaded: 2024-09-27T12:50:00
Description: Synaptic connections allow for the exchange and processing of information between neurons. The post-synaptic site of excitatory synapses is often formed ...

We would like to acknowledge Carolyn Smith, Sarah Williams Avram, Ted Usdin, and the NIMH SNIR for technical assistance. We would additionally like to acknowledge the Colgate University Bethesda Biomedical Research Study Group. This work is supported by the NIMH Intramural Program (1ZIAMH002881 to Z.L.).

All animal procedures followed the US National Institutes of Health Guidelines Using Animals in Intramural Research and were approved by the National Institute of Mental Health Animal Care and Use Committee.
1. Preparation of fixed hippocampal slices
<ol>
	<li>Anesthetize mice with an intraperitoneal injection of Ketamine/Xylazine (Ketamine: 100 mg/kg; Xylazine: 8 mg/kg). Validate anesthesia via tail pinch and affix mouse to perfusion plate.</li>
	<li>Using large surgical sc...

Protocol for Dendritic Spine Analysis Using Neurolucida 360

<ol>
	<li>Gray, E. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electron+microscopy+of+synaptic+contacts+on+dendrite+spines+of+the+cerebral+cortex.">Electron microscopy of synaptic contacts on dendrite spines of the cerebral cortex.</a> Nature. 183, 1592-1593 (1959).</li><li>Ram&#243;n Y Cajal, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sobre+la+fibras+nerviosas+de+la+capa+molecular+del+cerebelo.">Sobre la fibras nerviosas de la capa molecular del cerebelo.</a> Rev Trim Histol Norm. 1, 33-49 (1888).</li><li>Desmond, N. 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R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+small+pyramidal+neuron+of+the+rat+cerebral+cortex.+The+perikaryon,+dendrites+and+spines.">The small pyramidal neuron of the rat cerebral cortex. The perikaryon, dendrites and spines.</a> Am J Anat. 127 (4), 321-356 (1970).</li><li>Pfeiffer, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chronic+2p-sted+imaging+reveals+high+turnover+of+dendritic+spines+in+the+hippocampus+in+vivo.">Chronic 2p-sted imaging reveals high turnover of dendritic spines in the hippocampus in vivo.</a> Elife. 7, e34700 (2018).</li><li>Harris, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structure,+development,+and+plasticity+of+dendritic+spines.">Structure, development, and plasticity of dendritic spines.</a> Curr Opin Neurobiol. 9 (3), 343-348 (1999).</li><li>Hering, H., Sheng, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dendritic+spines:+Structure,+dynamics,+and+regulation.">Dendritic spines: Structure, dynamics, and regulation.</a> Nat Rev Neurosci. 2 (12), 880-888 (2001).</li><li>Jontes, J. D., Smith, S. 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This protocol details the specific steps of sample preparation, imaging, and the process of dendritic spine quantification and classification using three-dimensional reconstruction software. This software is a powerful tool capable of producing robust structural data that contributes to a diverse array of investigations. Throughout the process, there are some critical steps that make this protocol less of a methodological burden and enhance the overall output of the data. The method for labeling dendritic spines is one o...

Dendritic spines are protrusions of dendrites often comprising the post-synaptic site of glutamatergic synapses1,2. Dendritic spines are of particular interest in the field of synaptic plasticity. Spines are often altered when synaptic strength changes, becoming larger and stronger in long-term synaptic potentiation or smaller and weaker in long-term synaptic depression3,4,5,6,7. Beyond synaptic plasticity, the profile of dendritic spines changes throughout the lifespan. In early development, there is a period of dendritic spine formation and growth, followed by dendritic spine pruning until reaching a steady state8,9,10. In the aging brain, spine loss accompanies brain shrinkage and cognitive decline11. Additionally, many neurological, neurodegenerative, and psychiatric disorders are characterized by aberrant dendritic spines. Multiple brain regions in individuals affected with schizophrenia have fewer dendritic spines, likely resulting from altered synaptic pruning12. Autism spectrum disorders are also characterized by dendritic spine pathologies13. Dendritic spine loss is a hallmark of both Alzheimer&#39;s and Parkinson&#39;s disease14,15. Given the wide array of research topics encompassing investigations into dendritic spine properties, techniques for accurate spine quantification are of paramount importance.
Staining, i.e., the Golgi method, or labeling neurons via dye filling or expressing fluorescent proteins are common methods for dendritic spine visualization16,17,18. Once visualized, spines can be analyzed with a variety of free and commercially available software clients. The desired output of the analysis is an important factor in determining which software will be of the most use. Fiji is a viable software option for questions centered around dendritic spine density. However, this technique largely relies on time consuming manual counting that can introduce the potential for bias. New plugins such as SpineJ allow for automatic quantification, additionally allowing for more accurate spine neck analysis19. A drawback of these approaches is the loss of a three-dimensional analysis for determining spine volume, as SpineJ is limited to two-dimensional image stacks. Additionally, obtaining spine subtype information becomes challenging via these processes. The four predominant spine subtypes, thin, mushroom, stubby, and filopodia, all connote individual functions and are largely classified via morphology20. Thin spines are characterized by an elongated neck and defined head21. Mushroom spines have a much larger and pronounced spine head22. Stubby spines are short and have little variance between head and neck23. Filopodia are immature spines with a long, thin neck and no obviously observable head24. While classification provides valuable information, spines exist on a continuum of dimensions. Classification into categories is based on ranges of morphological measurements25,26. Manually measuring spines for classification compounds the logistical burden for researchers in this approach.
Other software options focusing specifically on three-dimensional dendritic spine analysis are better suited for investigations into spine volume and subtype properties27,28,29,30,31. Despite the difficulty presented by three-dimensional analysis, such as poor z-plane resolution and smear, these software options allow for reliable three-dimensional reconstruction of dendrites and dendritic spines in a user-guided semi-automated fashion. Automatic classification of identified spines into their subtypes is also a feature present in some of these spine analysis software packages. This can ameliorate concerns of potential workload and experimental bias. Neurolucida 360 is one commercially available software allowing for reliable and reproducible three-dimensional dendritic spine identification and classification32. Here, we present a comprehensive protocol to effectively prepare fixed tissue, acquire images, and ultimately quantify and classify dendritic spines using this software.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>518F Immersion Oil</td>
			<td>Zeiss</td>
			<td>444960-0000-000</td>
			<td></td>
		</tr>
		<tr>
			<td>Cryostat</td>
			<td>Leica</td>
			<td>CM3050S</td>
			<td>For slice preparation</td>
		</tr>
		<tr>
			<td>Fine Forceps</td>
			<td>FST</td>
			<td>11150-10</td>
			<td></td>
		</tr>
		<tr>
			<td>Hemostat Forceps</td>
			<td>FST</td>
			<td>13020-12</td>
			<td></td>
		</tr>
		<tr>
			<td>Large Surgical Scissors</td>
			<td>FST</td>
			<td>14002-16</td>
			<td></td>
		</tr>
		<tr>
			<td>LSM 880 Confocal Microscope</td>
			<td>Zeiss</td>
			<td>LSM 880</td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope Cover Glass</td>
			<td>Fisherbrand</td>
			<td>12-541-035</td>
			<td></td>
		</tr>
		<tr>
			<td>Mini-Peristaltic Pump II</td>
			<td>Harvard Apparatus</td>
			<td>70-2027</td>
			<td>For perfusions</td>
		</tr>
		<tr>
			<td>Neurolucida 360</td>
			<td>MBF Bioscience</td>
			<td>v2022.1.1</td>
			<td>Spine Analysis Software</td>
		</tr>
		<tr>
			<td>Neurolucida Explorer</td>
			<td>MBF Bioscience</td>
			<td>v2022.1.1</td>
			<td>Spine Analysis Software</td>
		</tr>
		<tr>
			<td>OCT Compound</td>
			<td>Sakura Finetek</td>
			<td>4583</td>
			<td>For cryostat sectioning</td>
		</tr>
		<tr>
			<td>Paraformaldehyde (37%)</td>
			<td>Fisherbrand</td>
			<td>F79-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Plan-Apochromat 63x/1.40 Oil DIC</td>
			<td>Zeiss</td>
			<td>440762-9904-000</td>
			<td></td>
		</tr>
		<tr>
			<td>Scalpel Blade</td>
			<td>FST</td>
			<td>10022-00</td>
			<td></td>
		</tr>
		<tr>
			<td>Small Surgical Scissors</td>
			<td>FST</td>
			<td>14060-09</td>
			<td></td>
		</tr>
		<tr>
			<td>Spatula&#160;</td>
			<td>FST</td>
			<td>10091-12</td>
			<td></td>
		</tr>
		<tr>
			<td>Sucrose</td>
			<td>FIsherbrand</td>
			<td>S5-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Superfrost Plus Microslides</td>
			<td>Diagger</td>
			<td>ES4951+</td>
			<td></td>
		</tr>
		<tr>
			<td>Vectashield HardSet Mounting Medium</td>
			<td>Vector Laboratories</td>
			<td>H-1400-10</td>
			<td></td>
		</tr>
	</tbody>
</table>

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 Spine Quantification Using an Automatic Three-Dimensional Neuron Reconstruction Software

The scope of our research is to examine the structural profile of dendritic spines in the hippocampus, specifically the CA-one apical dendrite. Through this, we're trying to answer questions centered around how different inputs to different parts of the same dendrite can be encoded at the cellular level. One challenge is obtaining high resolution images of dendritic spines for spine analysis.Once you have these images, the method to most accurately and reliably analyze spines in a fashion that isn't overly burdensome for the researcher presents an additional challenge. A balance must be struck between the two components. This protocol offers a happy medium between fully manual and fully automated dendritic spine analysis.Our protocol reduces the burden of manually counting individual spines. Additionally, the 3D reconstruction makes it possible to obtain spine volume. Classify the spines at the subtypes automatically.

Effectively utilizing this analysis method begins with the selection of dendritic segments for tracing. As described in Figure 1, the ideal dendrites for tracing are not in close proximity to other dendrites. Dendrites running in parallel can result in improperly identifying spines from a neighboring dendrite. Dendrites directly intersecting or running perpendicular in a different z-plane add significant difficulty to accurate dendritic tracing as well. It is also important to note the diffe...

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 ...

dendritic-spine-quantification-using-an-automatic-three-dimensional

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Research

JoVE Journal

Neuroscience

Quantifying Dendritic Spine Morphology Accurately and Reproducibly Using a Neuron Reconstruction Software

To begin, acquire the confocal images of mouse hippocampal slices. After opening the image file in Neurolucida 360 software, left-click the move/pivot point tool located in the top toolbar of the 3D environment window. Then, left-click on the desired dendrite to establish the new pivot point.After that, left-click the reset orientation icon to restore the original view. Then, click the move/pivot point tool again to continue tracing the dendrite. Left-click the tree tab within the 3D environment window.Select User Guided"for the tracing mode and directional kernels, as the method under User Guided"tracing options. For initiating dendrite tracing, left-click on the dendrite as soon as a circular kernel appears. Then, move the cursor along the dendritic segment.To ensure continuous kernel population, gently move the cursor back and forth over the dendrite. Then, left-click to secure any kernels that have been detected. If the kernels seize populating, left-click where a kernel appears further along the dendrite to place it manually, and right-click to stop tracing.Left-click and drag within the 3D environment window to check the precision of the dendritic tracing in all three dimensions, pitch, yaw, and roll. Locate any points where the dendrite tracing deviates from the intended path. For correcting any inaccuracies in the dendrite tracing, navigate to the edit tab located within the tree menu.Left-click on the dendrite of interest and then click on points to make necessary adjustments. Then, move improperly placed points back onto the dendrite segment, via click and drag. Left-click on the extraneous point to remove it and then click the delete button.If the points do not adequately cover the dendrite segment, adjust their size by left-clicking on them and modifying the thickness using the slider. After that, navigate to the spine tab within the 3D environment window. Set the detection settings for outer range, minimum height, and minimum voxel count.Adjust the detector sensitivity to 70%and then left-click Detect All"to identify spines on all dendrites according to the set sensitivity level. For a dendrite specific selection, take the option Click Image"to detect all on nearest branch, and manually left-click on each dendrite to apply different detector sensitivities. After detecting spines, click and drag the dendrite in all three directions to exam the coverage.If the detected spines are underfilled, increment the detector sensitivity by 5%to 10%and click Detect All"again to replace them at a higher sensitivity level. If overfilled spines are detected, reduce the detector sensitivity by 5%to 10%and select Detect All"once more to update the spine detection with a lower sensitivity. Then, left-click Keep Existing Spines"in the spine tab of the 3D environment.If the option, Click image to detect all on nearest branch"is active, make sure to deselect it. To focus on a specific dendrite for further spine analysis, left-click Move Pivot Point"and then click on the desired dendrite to set the pivot point. Once the pivot point is set, deselect Move Pivot Point"Identify a dendritic spine that appears unfilled.Increase the detector sensitivity by 10%to 20%beyond the previous setting, and left-click directly on the spine. If the spine does not populate, the message, Unable to detect a spine at the selected location"will appear. Increase the detector sensitivity incrementally, potentially exceeding 100%until a spine is detected and adequately filled.To correct an underfilled spine, go to the edit tab and left-click on it. Choose Remove"then deselect the edit tab. Increase the sensitivity by 5%to 10%and left-click on the spine again.For an overfilled spine, navigate to the edit tab and select it. Click Remove"then deselect the edit tab. Reduce the sensitivity by 5%to 10%and left-click on the spine.Inspect the dendrite for any spines that may belong to neighboring dendrites, false positives, or dendritic segments incorrectly identified as spines. Utilize Remove"to delete these inaccuracies. Then, access the spines identified on the dendrite.In cases where multiple spines might appear merged into a single conglomerate, access the edit tab, select the conglomerate spine, and click Hide Selection"to evaluate. If confirmed, within the edit tab, choose Show Selection"and then split to separate the spines. With all spines visually identified and correctly depicted, move to the spine tab and select Classify All"to categorize them into thin, mushroom, stubby, and filopodia.After completing all spine detections and classifications, in the top toolbar of the 3D environment window, select Save and View"in Neurolucida Explorer to save the data gathered from the tracings. Within the Explorer window, navigate to the view tab and left-click Select all"to highlight all dendrites and spines. Then, proceed to the analyze tab located in the upper toolbar.Left-click the structure dropdown menu and select Branch Structure Analysis"to initiate a detailed structural analysis of the highlighted elements. For spine density and average spine volume analysis, select each tree and each dendrite. Then, click Spines"followed by Spine Details"Click Okay"to execute the analysis and the results will be displayed in two distinct windows.