The authors are grateful to Keali R&#246;hm, Louisa Frie&#223;, and Heike Menzel for their expert technical assistance; to Helga Br&#252;nner for the animal care; and to Chistopher S. Ward for the generation and distribution of the optical disector grid plugin for the ImageJ software.

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. The protocol was approved by local authorities at the Regierung von Unterfranken, Wuerzburg, Germany.
1. Tissue Processing and Immunohistochemistry
<ol>
	<li>Euthanize mice with CO2 or any other approved method.</li>
	<li>Perfuse six 12-week-old C56Bl/6N male mice transcardially with 10 mL of 0.1 M phosphate-buffered saline (PBS) using a 25-G needle and an infusion pump, followed by 70 mL of 4% paraformaldehyde (PFA) in 0.1 M PBS. 
	CAUTION: PFA is toxic, allergenic, and carcinogenic.</li>
	<li>Dissect the mouse brain in the coronal plane with a brain matrix slicer at the region of +0.74 mm from Bregma (Figure 25, Paxinos and Franklin mouse brain atlas14).</li>
	<li>Put the dorsal part of the brain, including the SN, in 4% PFA in 0.1 M PBS for 1 d at 4 &#176;C for immersion-fixation.</li>
	<li>Exchange the PFA for 30% sucrose/0.1 mol PBS solution for cryo-protection and incubate for another 2 d at 4 &#176;C.</li>
	<li>Put the dorsal part of the brain into a cryomold filled with optimal cutting temperature (OCT) compound and slowly freeze the tissue in liquid dry ice-cooled isopentane. 
	CAUTION: Dry ice is extremely cold (-78 &#176;C); use personal protective equipment (PPE), including gloves, while working with dry ice. Dry ice evaporates in CO2; therefore, work under a fume hood.</li>
	<li>Serially cut 30-&#181;m cryo-sections in the coronal plane and collect the sections, starting at 2.46 mm from Bregma (Figure 51, Paxinos and Franklin mouse brain atlas14) and ending at 4.04 mm from Bregma (Figure 64, Paxinos and Franklin mouse brain atlas14).</li>
	<li>Store four series in tubes that are filled with cryoprotectant (30% glycerol, 30% ethoxyethanol, and 40% PBS) at -20 &#176;C. During the sectioning procedure, mark the right hemisphere by puncturing a small hole into the upper region of the brainstem.</li>
	<li>For immunohistochemical staining, select one series of sections per mouse. Preincubate free-floating sections for 1 h in 10% normal goat serum (NGS)/2% BSA/0.5% detergent in 0.1 mol PBS on a shaker. Incubate the sections with rabbit anti-mouse tyrosine hydroxylase (TH; 1:1,000 dilution) antibody diluted in 2% NGS/2% BSA/0.5% detergent in 0.1 mol PBS overnight at 4 &#176;C.</li>
	<li>Apply secondary antibodies against rabbit Igs (1:100 dilution) for 2 h at room temperature, followed by avidin/biotin reagent (1:100 dilution). Incubate and stain with 3,3-diaminobenzidine-tetrahydrochloride (DAB) and H2O2. Mount the sections after staining them on coated object slides. 
	NOTE: TH+ dopaminergic SN neurons are shown in Figure 1a. By staining one series, an average of 13 SN sections, extending from the rostral to caudal portions of the SN pars compacta (SNpc) and reticulata, are stained per animal (Figure 1b). The sections are separated by 120 &#181;m (1/4 series) (Figure 1c). 
	CAUTION: DAB is a suspected carcinogen. It is toxic by contact and inhalation. Use PPE when working with DAB.</li>
</ol>
2. Acquisition of Images
<ol>
	<li>Capture TH immunohistochemically stained SN sections digitally using imaging software that is coupled to a microscope. Separately analyze each section of one series.</li>
	<li>Use the scan slide option of the imaging software. Save in TIFF format for high-quality images (Figure 2). 
	NOTE: Image resolution is 312 pixels per cm.</li>
	<li>Press &#34;Acquire&#34; to open the acquisition window (Figure 2a).</li>
	<li>Set the binning to &#34;2&#34; for grayscale images. 
	NOTE: The acquisition of grayscale images instead of color pictures reduces the size of the final stack image file (Figure 2a).</li>
	<li>Click on &#34;Show Live&#34; in the acquisition window to open a new window showing the live image of the section (Figure 2a and b).</li>
	<li>Click on &#34;Stage&#34; in the acquisition window. Choose &#34;Scan Slide&#34; in the dropdown menu and check the box (Figure 2c). 
	NOTE: This enables the acquisition and alignment of highly magnified SN images (630X magnification) in the x,y-plane, as well as the acquisition of stack images with a distance between consecutive images of 1 &#181;m in the z-plane, covering a total range of 13 &#181;m.</li>
	<li>Select the 2.5X objective to search for the SN.</li>
	<li>Change the objective to 63x.</li>
	<li>Define the upper left corner (TopLeft) (Figure 2c) and lower right corner (LowRight) (Figure 2d) of the section by clicking on &#34;Set.&#34;</li>
	<li>Click on &#34;Z-Series&#34; and check the &#34;Z-Plane series&#34; box (Figure 2e).</li>
	<li>Determine the actual mounted thickness of the sections at three randomly selected counting sites per section using the imaging software. For this, click on &#34;View Top Offset&#34; to define the top of the section (Figure 2e) and then click on &#34;Stop View Top&#34; (Figure 2f). Thereafter, click on &#34;View Bottom Offset&#34; (Figure 2f) and then click on &#34;Stop View Bottom&#34; (Figure 2g). Write down the thickness of the section.</li>
	<li>Subtract 3 &#181;m (guard zone) from the top offset and type the result into the top offset slot (Figure 2h). Subtract 13 &#181;m (height of the optical disector) from the top offset number and type the result into the bottom offset slot (Figure 2i). Select the following parameters: steps, 14; size, 1.00 (Figure 2i). 
	NOTE: This corresponds to a thickness in the z-plane of 13 &#181;m, with a 1-&#181;m distance between consecutive images.</li>
	<li>Select the directory to save the file (Figure 2j).</li>
	<li>Click on &#34;Sequence&#34; to start the acquisition (Figure 2j).</li>
	<li>Click on &#34;Processing&#34; and select the following parameters: &#34;All Planes,&#34; from &#34;Sequence;&#34; &#34;Montage;&#34; and the &#34;Fast&#34; and &#34;Stitching&#34; boxes, with an image overlap of 10% (Figure 2k). Start to stitch the images by clicking on &#34;start&#34;. 
	NOTE: This will generate stack images for analysis (Figure 2l, Figure 3a-e).</li>
</ol>
3. Sequence of Stereological Assessment
<ol>
	<li>Perform the analysis of SN stack images using the NIH ImageJ software version 4.7.</li>
	<li>Download the two plugins that are needed from the ImageJ.nih.gov website: the &#34;Grid Overlay&#34; plugin15 and the &#34;Cell Counter&#34; plugin16. Install both plugins as described.</li>
	<li>For unbiased stereological assessment, define the counting parameters as follows: grid size, 130 x 130 &#181;m; counting frame, 50 x 50 &#181;m; and optical disector height, 13 &#181;m.</li>
	<li>Open the image by clicking on &#34;File&#34;&#160;&#8594; &#34;Open&#34; (Figure 4a) Set the image scale by using the &#34;Analyze&#34;&#160;&#8594; &#34;Set Scale&#34; command (Figure 4b). For this step, change the defined size from pixels to &#181;m (Figure 4c). 
	NOTE: For the analyzed images, 425 pixels corresponds to 100 &#181;m.</li>
	<li>Select the &#34;Plugins&#34;&#160;&#8594; &#34;Grid&#34;&#160;&#8594; &#34;Grid Type: Lines&#34; command to randomly insert a grid. Check the &#34;Random Offset&#34; box. Define the size of one square within the grid (grid-square) as 130 &#181;m x 130 &#181;m = 16,900 &#181;m2 (Figure 3b and Figure 4d and e).</li>
	<li>Change image type from 16-bit to RGB Color (Click on &#34;Image&#34;&#160;&#8594; &#34;Type&#34;&#160;&#8594; &#34;RGB Color&#34;) (Figure 4f). Locate the SNpc, as described by Baquet et al.17. Encircle the SNpc with the &#34;Paintbrush Tool&#34; (brush width: 11) (Figure 3c and Figure 4g-i).</li>
	<li>Undo the &#34;Set Scale&#34; command by clicking &#34;Analyze&#34; &#8594; &#34;Set Scale&#34; &#8594; &#34;Click to Remove Scale&#34; (Figure 4j-l) to enable the performance of the calculations in pixels rather than &#181;m.</li>
	<li>Make a screenshot (Figure 4m), save the image file, and open the new file with ImageJ (Figure 4n). Select &#34;Point&#34; (Figure 4o) and a brush width of 25 (Figure 4p). Mark every grid-square that contacts the SN for placement of an optical disector (Figure 4q). Perform analysis of the cell number in all optical disectors that are localized fully or partially within the outlined SN.</li>
	<li>Select one grid-square that includes parts of the SN. Measure the upper left corner of this square with the cursor in ImageJ to define the x and y coordinates to start with (Figure 4r). 
	NOTE: Coordinates will be inserted for optical disector positioning using the &#34;optical disector position&#34; (Figure 4s), as described in step 4.</li>
	<li>Calculate the optical disector position by using the spreadsheet template entitled, &#34;Optical disector position,&#34; as described in step 4.</li>
	<li>Calibrate the optical disector (macro written by Christopher S. Ward, Supplemental File) by clicking on &#34;Plugins&#34; &#8594; &#34;Macros&#34; &#8594; &#34;Edit&#34; (Figure 4t), open the &#34;opt_dis_grid.txt&#34; file (Figure 4u), and define the size of the &#34;usergrid&#34; in pixels that corresponds with the x,y dimension of the optical disector (Figure 4v). Select a size of 50 &#181;m x 50 &#181;m, so that the size of one side of the usergrid is defined as 212.5 pixels (50 x 4.25 pixels).</li>
	<li>Determine the position of the optical disector in the stack image by inserting the ImageX and ImageY coordinates that define the center of the optical disector (Figure 4v). Run the macro (&#34;Macros&#34; &#8594; &#34;Run Macro&#34;) (Figure 4w). 
	NOTE: The grid will vanish from the stack image (Figure 3d and Figure 4x). The optical disector will persist when moving down in the z-plane (Figure 3e and Figure 4x).</li>
	<li>Select &#34;Plugins&#34;&#160;&#8594; &#34;Cell Counter&#34; to start the Cell Counter plugin (Figure 4y). Initialize the Cell Counter and select a marker type (Figure 4z). Zoom in on the image (click on &#34;+&#34;) and perform the stereological assessment of the cell numbers at a magnification of 200%.</li>
	<li>Identify dopaminergic neuronal perikarya by their rounded or ovoid shape and cell size (Figure 1a). Quantify the number of cells using stereological rules. 
	NOTE: Since the optical disector is a 3-dimensional cube (Figure 5a), define the exclusion sides as the front, left, and top sides of the cube (red). Therefore, don&#39;t count TH+ cells that come into contact with either the red line (left and front) or the top side. Add the results of the cell counts to the prepared spreadsheet file entitled, &#34;Calculation of cell count&#34; (step 5).</li>
	<li>According to the SN image, calculate the next grid-square in which to place the optical disector for the next cell count, using x,y steps the size of the overlying grid (Figure 5b) and the &#34;Optical disector position&#34; spreadsheet template, as described in step 4.</li>
	<li>Perform an estimation of the cell number using the &#34;Calculation of cell count&#34; spreadsheet (step 5).</li>
</ol>
4. Calculation of Optical Disector Position Using the &#34;Optical Disector Position&#34; Spreadsheet Template
<ol>
	<li>Calculate the size and position of each optical disector to be placed into the overlying grid within the outline of the SN (Figure 5b) using the &#34;Optical disector position.xlsx&#34; spreadsheet file (Supplemental File).</li>
	<li>Insert the conversion of pixel per &#181;m, as defined by the &#34;Set Scale&#34; command, into the yellow marked positions of the &#34;Optical disector position.xlsx&#34; file (Figure 6a and Supplemental File).</li>
	<li>Insert the planned size of the optical disector and the size of the grid-square of the overlying grid, defined by the length of one side (in &#181;m), into the orange marked positions. 
	NOTE: Results are depicted in the red boxes next to the orange boxes.</li>
	<li>Start with the grid-square within the SN outline that was determined as the starting point (one grid-square was selected to begin with, as in step 3.9, above).</li>
	<li>Insert the x and y coordinates, as measured in step 3.9, into the green boxes of the file (by using these values, the x,y coordinates for the center of the optical disector within this first square are calculated, and the results are depicted in the blue boxes). Run the opt_dis_grid.txt macro (Supplemental File).</li>
	<li>Calculate the x,y coordinates of the consecutive optical disectors by inserting the grid-square distance (measured in number of squares) relative to the first grid-square (brown boxes). 
	NOTE: +x: grid-square is located to the right; -x: grid-square is located to the left; +y: grid-square is located to the bottom; -y: grid-square is located to the top. Results are shown in the gray boxes.</li>
</ol>
5. Estimation of Cell Number Using the &#34;Calculation of Cell Count&#34; Spreadsheet
<ol>
	<li>Calculate the estimated number of TH+ SN cells per animal (N) using the formula published by West et al., 19913, where &#8721;Q- is defined as the total number of TH+ neurons counted in all optical disectors of one brain section. 
	NOTE: The height of the optical disector (h) in relation to the measured thickness of the section (t) is included in the equation. The area sampling fraction (asf) is defined as the proportion of the area (A) of the optical disector (A optical disector) frame size within the square size of the grid (A x,y step) (A optical disector/A x,y step) (Figure 3b), and the section sampling fraction (ssf) is defined as the proportion of sections of the whole serially cut brain: 
	<img alt="Equation 1" src="/files/ftp_upload/56103/56103eq1.jpg" /> 
	To ensure high-quality quantitative estimates, the coefficient of error (CE) should be lower than 0.10. Determine the CE using the formula by Keuker et al., 200110: 
	<img alt="Equation 2" src="/files/ftp_upload/56103/56103eq2.jpg" /></li>
	<li>For the stereological estimation of the cell number within the SN of each mouse, insert the indicated information regarding the total number of generated series per mouse, the height of the optical disector, the x,y area of the optical disector (A optical disector, in &#181;m2), the x,y area of the grid-square (A x,y step, in &#181;m2), and the mean measured thickness of the section (in &#181;m) in the yellow boxes using the &#34;Calculation of cell count.xlsx&#34; spreadsheet file (Figure 6b and Supplemental File).</li>
	<li>Analyze each SN section from the same animal, as described in step 5.</li>
	<li>Insert cell counts for each optical disector in the gray boxes, each line referring to one SN section, using the &#34;Calculation of cell count.xlsx&#34; spreadsheet file (Supplemental File). 
	NOTE: The estimated cell number and the calculated CE are depicted in the blue boxes (Figure 6b).</li>
</ol>
6. Estimation of Cell Number Using a Commercially Available Stereology System
<ol>
	<li>Start the estimation of dopaminergic SNpc cell number by clicking on &#34;Probes&#34; &#8594; &#34;Optical Fractionator Workflow&#34; to open the Optical Fractionator Workflow window. 
	NOTE: A new window will pop-up to determine if a new series of SN is going to be counted.</li>
	<li>Start a new series of TH+ SN sections by clicking &#34;Start a new subject&#34; in the pop-up window.</li>
	<li>Go through the different steps of the Optical Fractionator Workflow. Set up the subject in the first step. For this, insert the investigator&#39;s name, the subject&#39;s name (SN group), and other helpful information. Insert the numbers of sections to count for this SN. Insert the thickness of the cut tissue sections. Insert the section interval, which is four in this case. Insert the randomly determined section number to start with.</li>
	<li>In the second step, set the microscope to low magnification (2X objective) and select &#34;2X Mag Lens&#34; from the menu.</li>
	<li>In step 3, trace the region of interest with the left mouse button, which is the SNpc, as described by Baquet et al., 200917.</li>
	<li>Set the microscope to high magnification in step 4. For this, change the objective to 100X and select &#34;100X Mag lens&#34; from the dropdown menu.</li>
	<li>Measure the mounted thickness in step 5 by focusing to the top and to the bottom of the section.</li>
	<li>In step 6, define the counting frame size as 50 x 50 &#181;m; this is the size of the optical disector (x,y).</li>
	<li>In step 7, set the size of the systematic random sampling (SRS) grid as 130 x 130 &#181;m.</li>
	<li>Enter a 3-&#181;m guard zone in step 8.</li>
	<li>Save the settings in step 9.</li>
	<li>Finally, count the TH+ dopaminergic cells in each of the optical disectors within the SRS grid in step 10 of the Optical Fractionator Workflow. For this, start by clicking on the &#34;Counting&#34; button.</li>
	<li>After finishing one section, click on the &#34;Begin Next Section&#34; button to start the Optical Fractionator Workflow of the next SN section of the same SN series.</li>
	<li>When the last SN section of one SN series has been quantified, click on &#34;I&#39;ve Finished Counting.&#34;</li>
	<li>Click on the &#34;View Results&#34; button to display the results of the stereology sampling.</li>
</ol>

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C. W. I. has served on scientific boards for Merz Pharmaceuticals, LLC and TEVA; has received funding for travel from Ipsen, Merz Pharmaceuticals, LLC, and Allergan, Inc.; and has received speaker honoraria from Merz, TEVA, and Allergan, Inc. outside the submitted work. J. V. has served as a consultant for Boston Scientific, Medtronic, and AbbVie and has received honoraria from Medtronic, Boston Scientific, AbbVie, Bial, Allergan, and GlobalKinetics outside the submitted work.

Stereology starts with tissue processing. The serial cutting of SN tissue must be performed carefully to prevent the loss of sections during stereological analysis. Additionally, one essential step is to mark one hemisphere in order to distinguish the right from the left SN when performing stereology. Placing a tiny hole at the upper part of the brainstem generated the best results in the presented study. Moreover, since working with the optical fractionator method demands that the tissue is cut in thick sections of abou...

The quantification of neuronal cell number is pivotal in pre-clinical Parkinson&#39;s disease research to determine the level of neurodegeneration within the substantia nigra (SN)1,2. The unbiased stereological estimation of cell number in a region of interest is considered the gold standard3,4,5.
Before the advent of unbiased stereology, the number of neurons in sections was assessed by manipulating counted cell profiles to correct for the variable probabilities that neurons come into sight in a section. One of the most commonly used methods was the correction of quantified cell counts described by Abercrombie6. This method attempted to take into account that cells can be quantified more than once if fragments of the same cell are found in adjacent thin sections. Therefore, Abercrombie and other authors generated equations that required assumptions about the shape, size, and orientation of the counted cells7,8. However, these assumptions were usually not realized and therefore led to systematic errors and divergence from the actual cell number (i.e., bias). Moreover, the bias could not be reduced by additional sampling3.
For the stereological estimation of cell numbers using the optical fractionator, mathematical principles are applied to directly estimate the cell numbers directly in a defined, 3-dimensional volume. The advantage of this method is that it does not involve assumptions about the shape, size, and orientation of the cells being counted. Thus, the estimated cell numbers are closer to the true values and get closer as the sample size increases (i.e., unbiased)3. Because many rules must be followed when using stereology to keep the method unbiased, ready-to-use commercial stereology systems have been developed (for review, see Schmitz and Hof, 20054). Specialized stereology systems implement design-based stereological methods with a priori defined probes and sampling schemes for stereological assessments that lead to independence from shape, size, spatial distribution, and orientation of the cells to be analyzed4,9. However, commercially available stereology systems are expensive; this may limit implementation in new research.
The aim of this study was to develop a usable technique for the design-based stereological estimation of dopaminergic cell counts in the mouse SN, employing the optical fractionator method and using standard microscopy equipment (i.e., light microscope, standard microscope software, and a motorized x, y, z stage). For this, a step-by-step guide on how to process mouse brain tissue and how to estimate SN cell numbers using design-based unbiased stereology is presented. Moreover, templates for the calculation of the estimated cell numbers and coefficients of error (CE) are provided.
The method described here is not limited to the analysis of the SN, but can be adapted for use in other anatomically defined regions of the mouse or rat brain. For instance, unbiased stereology has been used to estimate neuronal cell numbers in the hippocampus10 and the locus coeruleus11. Additionally, cell types other than neurons, such as astrocytes12 and microglia13, can be assessed as well. Therefore, this method can be useful to scientists who intend to implement unbiased stereology in their research but are not willing to spend a lot of money to purchase a stereology system.

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			<td style="width:467px;">The Mouse Brain George Paxinos Keith B.J.FranklinCopyright @2001 by Academic Press CD Rom designet &#38; created by Paul Halasz</td>
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			<td>Standard Ultra Sensitive ABC Staining Kit, 1:100</td>
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			<td height="42" style="height:42px;width:216px;">biotinylated goat-anti-rabbit IgG H+L</td>
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			<td>1:100</td>
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			<td height="21" style="height:21px;width:216px;">grid overlay plugin</td>
			<td style="width:217px;">Wayne Rasband</td>
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			<td>https://imagej.nih.gov/ij/plugins/graphic-overlay.html</td>
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			<td style="width:217px;">Kurt de Vos</td>
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			<td>https://imagej.nih.gov/ij/plugins/cell-counter.html).&#160;</td>
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			<td style="width:217px;">Charles River, Germany</td>
			<td style="width:119px;"></td>
			<td></td>
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			<td height="42" style="height:42px;width:216px;">SuperFrost Plus coated object slides</td>
			<td style="width:217px;">Langenbrinck, Germany</td>
			<td style="width:119px;"></td>
			<td></td>
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		<tr height="21">
			<td height="21" style="height:21px;width:216px;">25G needle Microlance 3</td>
			<td style="width:217px;">BD&#160;</td>
			<td align="right" style="width:119px;">300400</td>
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			<td height="21" style="height:21px;width:216px;">REGLO Analog Infusion pump</td>
			<td style="width:217px;">Ismatec</td>
			<td style="width:119px;">ISM 829</td>
			<td></td>
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		<tr height="21">
			<td height="21" style="height:21px;width:216px;">StereoInvestigator system</td>
			<td style="width:217px;"></td>
			<td style="width:119px;"></td>
			<td style="width:467px;">StereoInvestigator version 11.07</td>
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			<td style="width:119px;"></td>
			<td style="width:467px;">BX53 microscope</td>
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			<td style="width:467px;">Visiview</td>
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			<td height="21" style="height:21px;width:216px;">Axiophot2</td>
			<td style="width:217px;"></td>
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			<td style="width:467px;">Axiophot2</td>
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stereological estimation of dopaminergic neuron number in the mouse substantia nigra using the optical fractionator and standard microscopy equipment

In pre-clinical Parkinson&#39;s disease research, analysis of the nigrostriatal tract, including quantification of dopaminergic neuron loss within the substantia nigra, is essential. To estimate the total dopaminergic neuron number, unbiased stereology using the optical fractionator method is currently considered the gold standard. Because the theory behind the optical fractionator method is complex and because stereology is difficult to achieve without specialized equipment, several commercially available complete stereology systems that include the necessary software do exist, purely for cell counting reasons. Since purchasing a specialized stereology setup is not always feasible, for many reasons, this report describes a method for the stereological estimation of dopaminergic neuronal cell counts using standard microscopy equipment, including a light microscope, a motorized object table (x, y, z plane) with imaging software, and a computer for analysis. A step-by-step explanation is given on how to perform stereological quantification using the optical fractionator method, and pre-programmed files for the calculation of estimated cell counts are provided. To assess the accuracy of this method, a comparison to data obtained from a commercially available stereology apparatus was performed. Comparable cell numbers were found using this protocol and the stereology device, thus demonstrating the precision of this protocol for unbiased stereology.

Using the presented method, the estimated number of TH+ dopaminergic neurons in the right SN ranged between 7,363 and 7,987 cells and, in the left SN, between 7,446 and 7,904 cells. Thus, the mean number of dopaminergic neurons (&#177; SEM) was 7,647 &#177; 83 cells for the right SN and 7,675 &#177; 66 for the left SN. The calculated CE for each animal was lower than 0.08 (range: 0.073-0.079) (Figure 7). To ascertain the comparability of this method with comm...

Watch this Scientific Journal Video about Stereological Estimation of Dopaminergic Neuron Number in the Mouse Substantia Nigra Using the Optical Fractionator and Standard Microscopy Equipment at JoVE.

Stereological Estimation of Dopaminergic Neuron Number in the Mouse Substantia Nigra Using the Optical Fractionator and Standard Microscopy Equipment

This work presents a step-by-step protocol for the unbiased stereological estimation of dopaminergic neuronal cell numbers in the mouse substantia nigra using standard microscopy equipment (i.e., a light microscope, a motorized object table (x, y, z plane), and public domain software for digital image analysis.

In pre-clinical Parkinson&#39;s disease research, analysis of the nigrostriatal tract, including quantification of dopaminergic neuron loss within the ...

stereological-estimation-dopaminergic-neuron-number-mouse-substantia

Research

JoVE Journal

Neuroscience

17.8K Views.  University Hospital of Würzburg. This work presents a step-by-step protocol for the unbiased stereological estimation of dopaminergic neuronal cell numbers in the mouse substantia nigra using standard microscopy equipment (i.e., a light microscope, a motorized object table (x, y, z plane), and public domain software for digital image analysis.

Video: Stereological Estimation of Dopaminergic Neuron Number in the Mouse Substantia Nigra Using the Optical Fractionator and Standard Microscopy Equipment

In vivo Imaging of the Mouse Spinal Cord Using Two-photon Microscopy

In vivo imaging using two-photon microscopy 1 in mice that have been genetically engineered to express fluorescent proteins in specific cell types 2-3 has significantly broadened our knowledge of physiological and pathological processes in numerous tissues in vivo 4-7. In studies of the central nervous system (CNS), there has been a broad application of in vivo imaging in the brain, which has produced a plethora of novel and often unexpected findings about the behavior of cells such as neurons, astrocytes, microglia, under physiological or pathological conditions 8-17. However, mostly technical complications have limited the implementation of in vivo imaging in studies of the living mouse spinal cord. In particular, the anatomical proximity of the spinal cord to the lungs and heart generates significant movement artifact that makes imaging the living spinal cord a challenging task.
We developed a novel method that overcomes the inherent limitations of spinal cord imaging by stabilizing the spinal column, reducing respiratory-induced movements and thereby facilitating the use of two-photon microscopy to image the mouse spinal cord in vivo. This is achieved by combining a customized spinal stabilization device with a method of deep anesthesia, resulting in a significant reduction of respiratory-induced movements. This video protocol shows how to expose a small area of the living spinal cord that can be maintained under stable physiological conditions over extended periods of time by keeping tissue injury and bleeding to a minimum. Representative raw images acquired in vivo detail in high resolution the close relationship between microglia and the vasculature. A timelapse sequence shows the dynamic behavior of microglial processes in the living mouse spinal cord. Moreover, a continuous scan of the same z-frame demonstrates the outstanding stability that this method can achieve to generate stacks of images and/or timelapse movies that do not require image alignment post-acquisition. Finally, we show how this method can be used to revisit and reimage the same area of the spinal cord at later timepoints, allowing for longitudinal studies of ongoing physiological or pathological processes in vivo.

In vivo Imaging of the Mouse Spinal Cord Using Two-photon Microscopy

A minimally invasive protocol to stabilize the mouse spinal column and perform repetitive in vivo spinal cord imaging using two-photon microscopy is described. This method combines a spinal stabilization device and an anesthetic regimen to minimize respiratory-induced movements and produce raw imaging data that require no alignment or other post-processing.

In vivo imaging using two-photon microscopy 1 in mice that have been genetically engineered to express fluorescent proteins in specific cell types 2-3 has ...

Imaging Odor-Evoked Activities in the Mouse Olfactory Bulb using Optical Reflectance and Autofluorescence Signals

In the brain, sensory stimulation activates distributed populations of neurons among functional modules which participate to the coding of the stimulus. Functional optical imaging techniques are advantageous to visualize the activation of these modules in sensory cortices with high spatial resolution. In this context, endogenous optical signals that arise from molecular mechanisms linked to neuroenergetics are valuable sources of contrast to record spatial maps of sensory stimuli over wide fields in the rodent brain.
Here, we present two techniques based on changes of endogenous optical properties of the brain tissue during activation. First the intrinsic optical signals (IOS) are produced by a local alteration in red light reflectance due to: (i) absorption by changes in blood oxygenation level and blood volume (ii) photon scattering. The use of in vivo IOS to record spatial maps started in the mid 1980's with the observation of optical maps of whisker barrels in the rat and the orientation columns in the cat visual cortex1. IOS imaging of the surface of the rodent main olfactory bulb (OB) in response to odorants was later demonstrated by Larry Katz's group2. The second approach relies on flavoprotein autofluorescence signals (FAS) due to changes in the redox state of these mitochondrial metabolic intermediates. More precisely, the technique is based on the green fluorescence due to oxidized state of flavoproteins when the tissue is excited with blue light. Although such signals were probably among the first fluorescent molecules recorded for the study of brain activity by the pioneer studies of Britton Chances and colleagues3, it was not until recently that they have been used for mapping of brain activation in vivo. FAS imaging was first applied to the somatosensory cortex in rodents in response to hindpaw stimulation by Katsuei Shibuki's group4.
The olfactory system is of central importance for the survival of the vast majority of living species because it allows efficient detection and identification of chemical substances in the environment (food, predators). The OB is the first relay of olfactory information processing in the brain. It receives afferent projections from the olfactory primary sensory neurons that detect volatile odorant molecules. Each sensory neuron expresses only one type of odorant receptor and neurons carrying the same type of receptor send their nerve processes to the same well-defined microregions of &tilde;100&mu;m3 constituted of discrete neuropil, the olfactory glomerulus (Fig. 1). In the last decade, IOS imaging has fostered the functional exploration of the OB5, 6, 7 which has become one of the most studied sensory structures. The mapping of OB activity with FAS imaging has not been performed yet.
Here, we show the successive steps of an efficient protocol for IOS and FAS imaging to map odor-evoked activities in the mouse OB.

This article presents the protocols of intrinsic optical signals and flavoproteins autofluorescence signals imaging to map odor-evoked activities at the surface of the olfactory bulb in mice.

In the brain, sensory stimulation activates distributed populations of neurons among functional modules which participate to the coding of the stimulus. ...

Comprehensive Profiling of Dopamine Regulation in Substantia Nigra and Ventral Tegmental Area

Dopamine is a vigorously studied neurotransmitter in the CNS. Indeed, its involvement in locomotor activity and reward-related behaviour has fostered five decades of inquiry into the molecular deficiencies associated with dopamine regulation. The majority of these inquiries of dopamine regulation in the brain focus upon the molecular basis for its regulation in the terminal field regions of the nigrostriatal and mesoaccumbens pathways; striatum and nucleus accumbens. Furthermore, such studies have concentrated on analysis of dopamine tissue content with normalization to only wet tissue weight. Investigation of the proteins that regulate dopamine, such as tyrosine hydroxylase (TH) protein, TH phosphorylation, dopamine transporter (DAT), and vesicular monoamine transporter 2 (VMAT2) protein often do not include analysis of dopamine tissue content in the same sample. The ability to analyze both dopamine tissue content and its regulating proteins (including post-translational modifications) not only gives inherent power to interpreting the relationship of dopamine with the protein level and function of TH, DAT, or VMAT2, but also extends sample economy. This translates into less cost, and yet produces insights into the molecular regulation of dopamine in virtually any paradigm of the investigators' choice.
We focus the analyses in the midbrain. Although the SN and VTA are typically neglected in most studies of dopamine regulation, these nuclei are easily dissected with practice. A comprehensive readout of dopamine tissue content and TH, DAT, or VMAT2 can be conducted. There is burgeoning literature on the impact of dopamine function in the SN and VTA on behavior, and the impingements of exogenous substances or disease processes therein 1-5. Furthermore, compounds such as growth factors have a profound effect on dopamine and dopamine-regulating proteins, to a comparatively greater extent in the SN or VTA 6-8. Therefore, this methodology is presented for reference to laboratories that want to extend their inquiries on how specific treatments modulate behaviour and dopamine regulation. Here, a multi-step method is presented for the analyses of dopamine tissue content, the protein levels of TH, DAT, or VMAT2, and TH phosphorylation from the substantia nigra and VTA from rodent midbrain. The analysis of TH phosphorylation can yield significant insights into not only how TH activity is regulated, but also the signaling cascades affected in the somatodendritic nuclei in a given paradigm.
We will illustrate the dissection technique to segregate these two nuclei and the sample processing of dissected tissue that produces a profile revealing molecular mechanisms of dopamine regulation in vivo, specific for each nuclei (Figure 1).

Dopamine is distinctly regulated in the midbrain nuclei, which contain the cell bodies and dendrites of the dopamine neurons. Here we describe a dissection and sample-handling approach to maximize results, and thus conclusions and insights, on dopamine regulation in the midbrain nuclei of the substantia nigra (SN) and ventral tegmental area (VTA) in rodents.

Dopamine is a vigorously studied neurotransmitter in the CNS. Indeed, its involvement in locomotor activity and reward-related behaviour has fostered five ...

Directed Dopaminergic Neuron Differentiation from Human Pluripotent Stem Cells

Dopaminergic (DA) neurons in the substantia nigra pars compacta (also known as A9 DA neurons) are the specific cell type that is lost in Parkinson&#8217;s disease (PD). There is great interest in deriving A9 DA neurons from human pluripotent stem cells (hPSCs) for regenerative cell replacement therapy for PD. During neural development, A9 DA neurons originate from the floor plate (FP) precursors located at the ventral midline of the central nervous system. Here, we optimized the culture conditions for the stepwise differentiation of hPSCs to A9 DA neurons, which mimics embryonic DA neuron development. In our protocol, we first describe the efficient generation of FP precursor cells from hPSCs using a small molecule method, and then convert the FP cells to A9 DA neurons, which could be maintained in vitro for several months. This efficient, repeatable and controllable protocol works well in human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) from normal persons and PD patients, in which one could derive A9 DA neurons to perform in vitro disease modeling and drug screening and in vivo cell transplantation therapy for PD.

We, based on knowledge from developmental biology and published research, developed an optimized protocol to efficiently generate A9 midbrain dopaminergic neurons from both human embryonic stem cells and human induced pluripotent stem cells, which would be useful for disease modeling and cell replacement therapy for Parkinson&#8217;s disease.

Dopaminergic (DA) neurons in the substantia nigra pars compacta  (also known as A9 DA neurons) are the specific cell type that is lost in ...

The Neuromuscular Junction: Measuring Synapse Size, Fragmentation and Changes in Synaptic Protein Density Using Confocal Fluorescence Microscopy

The neuromuscular junction (NMJ) is the large, cholinergic relay synapse through which mammalian motor neurons control voluntary muscle contraction. Structural changes at the NMJ can result in neurotransmission failure, resulting in weakness, atrophy and even death of the muscle fiber. Many studies have investigated how genetic modifications or disease can alter the structure of the mouse NMJ. Unfortunately, it can be difficult to directly compare findings from these studies because they often employed different parameters and analytical methods. Three protocols are described here. The first uses maximum intensity projection confocal images to measure the area of acetylcholine receptor (AChR)-rich postsynaptic membrane domains at the endplate and the area of synaptic vesicle staining in the overlying presynaptic nerve terminal. The second protocol compares the relative intensities of immunostaining for synaptic proteins in the postsynaptic membrane. The third protocol uses Fluorescence Resonance Energy Transfer (FRET) to detect changes in the packing of postsynaptic AChRs at the endplate. The protocols have been developed and refined over a series of studies. Factors that influence the quality and consistency of results are discussed and normative data are provided for NMJs in healthy young adult mice.

The neuromuscular junction (NMJ) is altered in a variety of conditions that can sometimes culminate in synaptic failure. This report describes fluorescence microscope-based methods to quantify such structural changes.

The neuromuscular junction (NMJ) is the large, cholinergic relay synapse through which mammalian motor neurons control voluntary muscle contraction. ...

Optical Control of a Neuronal Protein Using a Genetically Encoded Unnatural Amino Acid in Neurons

Photostimulation is a noninvasive way to control biological events with excellent spatial and temporal resolution. New methods are desired to photo-regulate endogenous proteins expressed in their native environment. Here, we present an approach to optically control the function of a neuronal protein directly in neurons using a genetically encoded unnatural amino acid (Uaa). By using an orthogonal tRNA/aminoacyl-tRNA synthetase pair to suppress the amber codon, a photo-reactive Uaa 4,5-dimethoxy-2-nitrobenzyl-cysteine (Cmn) is site-specifically incorporated in the pore of a neuronal protein Kir2.1, an inwardly rectifying potassium channel. The bulky Cmn physically blocks the channel pore, rendering Kir2.1 non-conducting. Light illumination instantaneously converts Cmn into a smaller natural amino acid Cys, activating Kir2.1 channel function. We express these photo-inducible inwardly rectifying potassium (PIRK) channels in rat hippocampal primary neurons, and demonstrate that light-activation of PIRK ceases the neuronal firing due to the outflux of K+ current through the activated Kir2.1 channels. Using in utero electroporation, we also express PIRK in the embryonic mouse neocortex in vivo, showing the light-activation of PIRK in neocortical neurons. Genetically encoding Uaa imposes no restrictions on target protein type or cellular location, and a family of photoreactive Uaas is available for modulating different natural amino acid residues. This technique thus has the potential to be generally applied to many neuronal proteins to achieve optical regulation of different processes in brains. The current protocol presents an accessible procedure for intricate Uaa incorporation in neurons in vitro and in vivo to achieve photo control of neuronal protein activity on the molecular level.

Here, a procedure to selectively activate a neuronal protein with a short pulse of light by genetically encoding a photo-reactive unnatural amino acid into a target neuronal protein expressed in neurons in culture or in vivo is presented.

Photostimulation is a noninvasive way to control biological events with excellent spatial and temporal resolution. New methods are desired to ...

Optical Clearing of the Mouse Central Nervous System Using Passive CLARITY

Traditionally, tissue visualization has required that the tissue of interest be serially sectioned and imaged, subjecting each tissue section to unique non-linear deformations, dramatically hampering one's ability to evaluate cellular morphology, distribution and connectivity in the central nervous system (CNS). However, optical clearing techniques are changing the way tissues are visualized. These approaches permit one to probe deeply into intact organ preparations, providing tremendous insight into the structural organization of tissues in health and disease. Techniques such as Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging-compatible Tissue-hYdrogel (CLARITY) achieve this goal by providing a matrix that binds important biomolecules while permitting light-scattering lipids to freely diffuse out. Lipid removal, followed by refractive index matching, renders the tissue transparent and readily imaged in 3 dimensions (3D). Nevertheless, the electrophoretic tissue clearing (ETC) used in the original CLARITY protocol can be challenging to implement successfully and the use of a proprietary refraction index matching solution makes it expensive to use the technique routinely. This report demonstrates the implementation of a simple and inexpensive optical clearing protocol that combines passive CLARITY for improved tissue integrity and 2,2&#8242;-thiodiethanol (TDE), a previously described refractive index matching solution.

Optical clearing techniques are revolutionizing the way tissues are visualized. In this report we describe modifications of the original Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging-compatible Tissue-hYdrogel (CLARITY) protocol that yields more consistent and less expensive results.

Traditionally, tissue visualization has required that the tissue of interest be serially sectioned and imaged, subjecting each tissue section to unique ...

The Optical Fractionator Technique to Estimate Cell Numbers in a Rat Model of Electroconvulsive Therapy

Stereological methods are designed to describe quantitative parameters without making assumptions about size, shape, orientation and distribution of cells or structures. These methods have been revolutionary for quantitative analysis of the mammalian brain, in which volumetric cell populations are too high to count manually, and stereology is now the technique of choice whenever estimates of three-dimensional quantities need to be extracted from measurements on two-dimensional sections. All stereological methods are in principle unbiased; however, they rely on proper knowledge about the structure of interest and the characteristics of the tissue. Stereology is based on Systematic Uniformly Random Sampling (SURS), with adjustment of sampling to the most efficient level in respect to precision, providing reliable, quantitative information about the whole structure of interest. Here we present the optical fractionator in conjunction with BrdU immunohistochemistry to estimate the production and survival of newly-formed neurons in the granule cell layer (including the sub-granular zone) of the rat hippocampus following electroconvulsive stimulation, which is among the most potent stimulators of neurogenesis. The optical fractionator technique is designed to provide estimates of the total number of cells from thick sections sampled from the full structure. Thick sections provide the opportunity to observe cells in their full 3-D extent and thus, allow for easy and robust cell classification based on morphological criteria. When correctly implemented, the sensitivity and efficiency of the optical fractionator provides accurate estimates with a fixed and predetermined precision.

Here, we present a stereological method, the optical fractionator, used to quantify the formation of new neurons, and their survival, in the rat hippocampus following electroconvulsive stimulation. When correctly implemented, the sensitivity and efficiency of stereological methods ensures accurate estimates with a fixed and predetermined precision.

Stereological methods are designed to describe quantitative parameters without making assumptions about size, shape, orientation and distribution of cells ...

Live Images of GLUT4 Protein Trafficking in Mouse Primary Hypothalamic Neurons Using Deconvolution Microscopy

Type 2 diabetes mellitus (T2DM) is a global health crisis which is characterized by insulin signaling impairment and chronic inflammation in peripheral tissues. The hypothalamus in the central nervous system (CNS) is the control center for energy and insulin signal response regulation. Chronic inflammation in peripheral tissues and imbalances of certain chemokines (such as CCL5, TNF&#945;, and IL-6) contribute to diabetes and obesity. However, the functional mechanism(s) connecting chemokines and hypothalamic insulin signal regulation still remain unclear.
In vitro primary neuron culture models are convenient and simple models which can be used to investigate insulin signal regulation in hypothalamic neurons. In this study, we introduced exogeneous GLUT4 protein conjugated with GFP (GFP-GLUT4) into primary hypothalamic neurons to track GLUT4 membrane translocation upon insulin stimulation. Time-lapse images of GFP-GLUT4 protein trafficking were recorded by deconvolution microscopy, which allowed users to generate high-speed, high-resolution images without damaging the neurons significantly while conducting the experiment. The contribution of CCR5 in insulin regulated GLUT4 translocation was observed in CCR5 deficient hypothalamic neurons, which were isolated and cultured from CCR5 knockout mice. Our results demonstrated that the GLUT4 membrane translocation efficiency was reduced in CCR5 deficient hypothalamic neurons after insulin stimulation.

This protocol describes a technique for observation of real-time Green Fluorescence Protein (GFP) tagged Glucose Transporter 4 (GLUT4) protein trafficking upon insulin stimulation and characterization of the biological role of CCR5 in the insulin&#8211;GLUT4 signaling pathway with Deconvolution Microscopy.

Type 2 diabetes mellitus (T2DM) is a global health crisis which is characterized by insulin signaling impairment and chronic inflammation in peripheral ...

Stereological Estimation of Cholinergic Fiber Length in the Nucleus Basalis of Meynert of the Mouse Brain

The length of cholinergic or other neuronal axons in various brain regions are often correlated with the specific function of the region. Stereology is a useful method to quantify neuronal profiles of various brain structures. Here we provide a software-based stereology protocol to estimate the total length of cholinergic fibers in the nucleus basalis of Meynert (NBM) of the basal forebrain. The method uses a space ball probe for length estimates. The cholinergic fibers are visualized by choline acetyltransferase (ChAT) immunostaining with the horseradish peroxidase-diaminobenzidine (HRP-DAB) detection system. The staining protocol is also valid for fiber and cell number estimation in various brain regions using stereology software. The stereology protocol can be used for estimation of any linear profiles such as cholinoceptive fibers, dopaminergic/catecholaminergic fibers, serotonergic fibers, astrocyte processes, or even vascular profiles.

Neuronal fiber length within a three-dimensional structure of a brain region is a reliable parameter to quantify specific neuronal structural integrity or degeneration. This article details a stereological quantification method to measure cholinergic fiber length within the nucleus basalis of Meynert in mice as an example.

The length of cholinergic or other neuronal axons in various brain regions are often correlated with the specific function of the region. Stereology is a ...