Image acquisition was performed in the LiM facility of iBiMED, a node of PPBI (Portuguese Platform of BioImaging): POCI-01-0145-FEDER-022122. This work was supported by FCT (EXPL/BTM-SAL/0902/2021) LCF (CI21-00276), a grant to DT from the Funda&#231;&#227;o para a Ci&#234;ncia e Tecnologia of the Minist&#233;rio da Educa&#231;&#227;o e Ci&#234;ncia (2020.02006.CEECIND), a grant from ATG-The Gabba Alumni Association to VP, and the Institute for Biomedicine-iBiMED, University of Aveiro.

NOTE: This protocol has two main steps: a wet lab step, involving cell culture and live confocal microscopy to obtain images of live mitochondria (Figure 1) and an in silico step to analyze obtained images (Figure 2). For automated data analysis of 3D live imaged mitochondria, the MATLAB application Mitometer was used as provided by Lefebvre et al.9. The Routine optimization is written in MATLAB. The software, updated versions and processing ImageJ Macros are freely available online through GitHub, at&#160;https://github.com/JoseJoaoMV/Routine_Optimization_Mitometer_APP_MATLAB.&#160;
1. Live microscopy
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65452/65452fig01.jpg" /> 
Figure 1: Experimental protocol. SH-SY5Y cells were differentiated and treated with retinoids. (A) TMRM was used to live image healthy mitochondria in treated cells using a confocal microscope, capturing a time lapse z-stack of five visual fields. (B) Mitometer application MATLAB automatically segments and analyzes mitochondria images. In addition to analyzing, this software automatically discriminates mitochondria according to nuclear proximity. Blue dots are mitochondrial initial positions; red dots are final positions. Scale bar = 30 &#181;m. Abbreviation: TMRM = tetramethylrhodamine, methyl ester. <a href="https://www.jove.com/files/ftp_upload/65452/65452fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol>
	<li>Cell culture
	<ol>
		<li>Incubate SH-SY5Y cells at 37 &#176;C in a humidified atmosphere of 5% CO2 and 95% air, cultured in equal parts of MEM (Minimal Essential Medium) and F12 (Ham&#39;s F12 Nutrient Mix) Medium, supplemented with 10% fetal bovine serum (FBS).</li>
		<li>Plate SH-SY5Y cells in glass-bottom cell dishes at a density of 15 &#215; 104 cells/mL.</li>
		<li>Differentiate cells with 5 days of treatment with 10 &#181;M all-trans retinoic acid in 1% FBS-containing culture medium, followed by 2 days of treatment with 10 &#414;g/mL brain-derived neurotrophic factor (BDNF).</li>
	</ol>
	</li>
	<li>Cell treatment
	<ol>
		<li>Wash cells with sterile phosphate-buffered saline (PBS) and treat for 72 h with 10-7 M RAR-isoform agonists, in equal parts of MEM (Minimal Essential Medium) and F12 (Ham&#39;s F12 Nutrient Mix) Medium, supplemented with 1% FBS. 
		NOTE: The RAR&#945; agonist used was AM580; RAR&#946; agonist used was CD2314; Ch55 was used as agonist as RAR&#945; and &#946; co-agonist; atRA was used as a positive control; BMS493 was used as a RAR pan-antagonist.</li>
	</ol>
	</li>
	<li>Live confocal imaging
	<ol>
		<li>Replace culture medium with fresh 1% FBS-containing culture medium with 20 nM tetramethylrhodamine, methyl ester (TMRM) for 45 min. 
		NOTE: TMRM is a cell-permeant fluorescent dye, sequestered by active mitochondria, and this incubation period allows TMRM to reach an equilibrium and be taken up by polarized mitochondria11. Imaging should be started before equilibrium is established as TMRM signal intensity could artificially increase during imaging.</li>
		<li>Place the cells in an incubator attached to a laser-scanning confocal microscope at 37 &#176;C.</li>
		<li>Capture images using a 63x oil-immersion apochromat objective, with an image size of 512 x 512 pixels obtained with a pinhole aperture of 1 airy unit, capturing a time series of 15 frames from five different visual fields in each cell plate, and a z-stack of 8 equidistant z-planes. The resulting .lsm file is a time-, position-, and z-stack. 
		NOTE: Settings for gain, contrast, and brightness must be initially optimized using the minimum laser power necessary to use the entire dynamic range of the detector and kept constant throughout the study, ensuring that all imaging is performed under the same conditions. Up to nine different positions can be recorded in this hardware-software combination and the microscope cycles between imaging positions automatically.</li>
	</ol>
	</li>
</ol>
2. Image analysis
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65452/65452fig02.jpg" /> 
Figure 2: Routine optimization. (A) Representative code of the routine optimization. (B) Routine optimization Live-Script. (C) Routine optimization workflow. (D) Routine optimization result validation: representative image of mitochondria in untreated cells (left panel), treated with atRA (10-7&#160;M, 72 h, middle panel), and treated with RAR antagonist BMS493 (10-7 M, 72 h, right panel), imaged after incubation with TMRM (20 nM, 45 min incubation). Scale bar = 30 &#181;m. (E) TMRM Intensity in cell body mitochondria. Significant decrease with all-trans retinoic acid treatment (atRA, 10-7 M, 72 h), compared with control (p=0,0062), not observed when treated with RAR antagonist (BMS493, 10-7&#160;M, 72 hours). Five cells were quantified from each of three repetitions per condition. <a href="https://www.jove.com/files/ftp_upload/65452/65452fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol>
	<li>Image processing
	<ol>
		<li>Open files in ImageJ 2.1.0 and separate position stacks by visual field: Open ImageJ and click Menu Bar | Image | Duplicate | Input slices/frame number | OK. 
		NOTE: To decrease repetitive inputs to the software, an ImageJ Macro was developed to facilitate duplication and saving of visual field images.</li>
	</ol>
	</li>
	<li>Macro protocol
	<ol>
		<li>Draw a region of interest (ROI) around the cell with the free selection tool.</li>
		<li>Run the macro by opening ImageJ and navigating to Menu Bar | Plugins | Macros | Run Clear the background and save images macro. 
		NOTE: Images can be randomized in this process, storing the solution key according to optimization requirements.</li>
		<li>Determine pixel size and voxel-depth: Open ImageJ | the Image and navigate to Menu Bar | Image | Properties.</li>
	</ol>
	</li>
	<li>Alternative direct protocol 
	NOTE: This alternative does not use Macro to process images
	<ol>
		<li>Find the pixel size and voxel depth: Open ImageJ | Open Image and navigate to Menu Bar | Image | Properties.</li>
		<li>Draw an ROI around the cell with the free selection tool, ensuring it encompasses the whole cell throughout the 15&#160;frames.</li>
		<li>Navigate to Menu Bar | Edit | Clear Outside.</li>
		<li>Navigate to Menu Bar | File | Save-as | Select Tiff.</li>
		<li>Select Saving Folder and click on Save. 
		NOTE: Images can be blinded/randomized manually at this point before continuing to analysis.</li>
	</ol>
	</li>
	<li>Automated image analysis
	<ol>
		<li>Prepare the folders for analysis files.
		<ol>
			<li>Create three main folders, titled &#34;All tracks&#34;, &#34;Perinuclear tracks&#34;, and &#34;Telenuclear tracks&#34;. 
			NOTE: These match the main automated track options.</li>
			<li>In each main folder, create a sub-folder for each image to process, identified numerically from 1 upwards.</li>
			<li>Add a copy of the two routine optimization supplementary files (mitometer2table.m and getTXTfiles.m) to each image folder. 
			NOTE: These files help in data analysis and final format arrangement. The number of folders must match the number of elements in the randomized spreadsheet (.xlsx). After creating all numbered subfolders with supplementary files for one dataset, they can be batch-copied and pasted to the remaining datasets.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Use the MATLAB application Mitometer to analyze images. 
	NOTE: This protocol was run on a mitometer, installed on MATLAB R2022a. Load images in batches of 30 for optimal time-running and output balance. Maximum MAT-file size is imposed by the native file system: by default, &#34;save&#34; operations can create a file &#60; 231 bytes (~2 GB); save format MAT-Files Version 7.3 can be used instead, as it allows maximum variable sizes larger than 2 GB.
	<ol>
		<li>Identify/alter the default MAT-file version: On the Home tab in the Environment section, click Preferences and select MATLAB | General | MAT-Files.</li>
		<li>Use MATLAB tool Mitometer to analyze: Open MATLAB and navigate to Menu Bar | APPS | Open Mitometer | Select Start 3D | Input data (Pixel Size (&#181;m): 0.1395089/Time between frames (s): 2/Number z-planes: 8/Axial distance between z-planes (&#181;m): 0.418809 | Select images to input.</li>
		<li>Go to Mitometer Side Menu, select Image, click on Select Highlighted, navigate to the mitometer Menu Bar | Select Tracks | Track views | select All-Tracks, Telenuclear or Perinuclear | mitometer Menu Bar | Select Analysis | Choose an element (i.e., Length) | select Save to &#34;.txt&#34;. 
		NOTE: More than one parameter can be downloaded at once, if selected concomitantly.</li>
		<li>Extract result files to the created folders (2.2.1).</li>
	</ol>
	</li>
	<li>Routine optimization and data analysis
	<ol>
		<li>Prepare/adapt the &#34;Randomization.xlsx&#34; file containing the key for image encoding.
		<ol>
			<li>Insert a list of consecutive integers, from 1 upwards, in column A. 
			NOTE: It is advisable to keep a duplicated folder with originally named images.</li>
			<li>Place the analytic variables in column B, composed of alphanumeric characters. 
			NOTE: The number of lines in the document must be consistent with the number of folders present in the main dataset. Copy and paste this &#34;Randomization.xlsx&#34; file into the other two main datasets.</li>
		</ol>
		</li>
		<li>Optimized data analysis
		<ol>
			<li>Double-click &#34;executable.mlx&#34;, input the number of folders, specify the folders directory (copy the directory from the top of the folder) | the save directory (copy the directory from the top of the folder) | the spreadsheet name in the output file and click Run.</li>
			<li>Perform statistical analysis as necessary. 
			NOTE: Optional creation of a .xlsx file in each folder with the .txt data and sound alert to the end of analysis may be selected. Live Script outputs a single spreadsheet file in a table format. In this output, columns represent analyzed parameters (e.g., &#34;Major Axis Length&#34;; &#34;Intensity&#34;) and lines represent visual fields of analytic variables (e.g., &#34;Control&#34;).</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>

MATLAB Optimization for Analyzing Mitochondrial Networks in Neuroscience

<ol>
	<li>Trigo, D., Avelar, C., Fernandes, M., Sa, J., da Cruz, E. S. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mitochondria,+energy,+and+metabolism+in+neuronal+health+and+disease.">Mitochondria, energy, and metabolism in neuronal health and disease.</a> FEBS Letters. 596 (9), 1095-1110 (2022).</li><li>Zong, W. X., Rabinowitz, J. D., White, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mitochondria+and+cancer.">Mitochondria and cancer.</a> Molecular Cell. 61 (5), 667-676 (2016).</li><li>Clare, D. K., Saibil, H. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ATP-driven+molecular+chaperone+machines.">ATP-driven molecular chaperone machines.</a> Biopolymers. 99 (11), 846-859 (2013).</li><li>Tourniaire, F., 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=All-trans+retinoic+acid+induces+oxidative+phosphorylation+and+mitochondria+biogenesis+in+adipocytes.">All-trans retinoic acid induces oxidative phosphorylation and mitochondria biogenesis in adipocytes.</a> Journal of Lipid Research. 56 (6), 1100-1109 (2015).</li><li>Psarra, A. M., Sekeris, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nuclear+receptors+and+other+nuclear+transcription+factors+in+mitochondria:+regulatory+molecules+in+a+new+environment.">Nuclear receptors and other nuclear transcription factors in mitochondria: regulatory molecules in a new environment.</a> Biochimica et Biophysica Acta. 1783 (1), 1-11 (2008).</li><li>Trigo, D., Goncalves, M. B., Corcoran, J. P. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+regulation+of+mitochondrial+dynamics+in+neurite+outgrowth+by+retinoic+acid+receptor+beta+signaling.">The regulation of mitochondrial dynamics in neurite outgrowth by retinoic acid receptor beta signaling.</a> FASEB Journal. 33 (6), 7225-7235 (2019).</li><li>Mitra, K., Lippincott-Schwartz, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+mitochondrial+dynamics+and+functions+using+imaging+approaches.">Analysis of mitochondrial dynamics and functions using imaging approaches.</a> Current Protocols in Cell Biology. Chapter 4 (Unit 4), 1-21 (2010).</li><li>Sajic, M., 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=Impulse+conduction+increases+mitochondrial+transport+in+adult+mammalian+peripheral+nerves+in+vivo.">Impulse conduction increases mitochondrial transport in adult mammalian peripheral nerves in vivo.</a> PLoS Biology. 11 (12), e1001754 (2013).</li><li>Lefebvre, A., Ma, D., Kessenbrock, K., Lawson, D. A., Digman, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+segmentation+and+tracking+of+mitochondria+in+live-cell+time-lapse+images.">Automated segmentation and tracking of mitochondria in live-cell time-lapse images.</a> Nature Methods. 18 (9), 1091-1102 (2021).</li><li>Chu, C. -. H., Tseng, W. -. W., Hsu, C. -. M., Wei, A. -. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Image+analysis+of+the+mitochondrial+network+morphology+with+applications+in+cancer+research.">Image analysis of the mitochondrial network morphology with applications in cancer research.</a> Frontiers in Physics. 10, 855775 (2022).</li><li>Creed, S., McKenzie, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+mitochondrial+membrane+potential+with+the+fluorescent+dye+tetramethylrhodamine+methyl+ester+(TMRM).">Measurement of mitochondrial membrane potential with the fluorescent dye tetramethylrhodamine methyl ester (TMRM).</a> Methods in Molecular Biology. 1928, 69-76 (2019).</li><li>Kovalevich, J., Langford, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Considerations+for+the+use+of+SH-SY5Y+neuroblastoma+cells+in+neurobiology.">Considerations for the use of SH-SY5Y neuroblastoma cells in neurobiology.</a> Methods in Molecular Biology. 1078, 9-21 (2013).</li><li>Sahin, M., Oncu, G., Yilmaz, M. A., Ozkan, D., Saybasili, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transformation+of+SH-SY5Y+cell+line+into+neuron-like+cells:+Investigation+of+electrophysiological+and+biomechanical+changes.">Transformation of SH-SY5Y cell line into neuron-like cells: Investigation of electrophysiological and biomechanical changes.</a> Neuroscience Letters. 745, 135628 (2021).</li><li>Trigo, D., 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=Mitochondria+dysfunction+and+impaired+response+to+oxidative+stress+promotes+proteostasis+disruption+in+aged+human+cells.">Mitochondria dysfunction and impaired response to oxidative stress promotes proteostasis disruption in aged human cells.</a> Mitochondrion. 69, 1-9 (2022).</li></ol>

The authors have no conflicts of interest to declare.

Live cell imaging produces large files that require serious computing processing, but even the most recent tools require extensive manual input to process. This routine optimization is focused on simplifying the process of mitochondria analysis on the Mitometer because this tool presents a very good balance between user input and data output. A comprehensive comparison between different tools for mitochondria image analysis has previously been reviewed10. While other pipelines are more focused on ...

Cellular mitochondria sit at the center of all physiological states, and a thorough understanding of their homeostasis (mitostasis) and behavior is paramount to assist in identifying pharmacological treatment for a wide range of illnesses, including cancer and Alzheimer&#39;s disease1,2.
Mitochondria play crucial cellular roles in energy homeostasis, ATP generation, calcium buffering, and ROS regulation, and mitostasis is essential for maintaining protein homeostasis as molecular chaperones are energy-dependent3. These require a constant and dynamic network modulation and adaptation to efficiently meet cellular needs, and mitochondria transport is regulated by different signaling pathways; previous work has described one such pathway, that of retinoic acid receptors (RARs)4,5. Retinoic acid (RA) promotes axonal and neurite outgrowth via RAR activation. In mouse primary cortical neurons, activation of RAR-&#946; encourages mitochondrial growth, speed, and mobility in the neurite6.
Considering the mitochondrial network adaptability and dynamics, the possibility of assessing mitostasis in &#34;real time&#34; is essential not only for investigating energy homeostasis, but also for proteostasis, cellular health, proliferation, or signaling. A commonly used method for evaluating mitostasis relies on confocal microscopy after highlighting mitochondria using a fluorescent dye or marker, as well as a specific microscopy setup allowing temperature and/or CO2 regulation7. This type of experimental setup entails that one experimental replicate be performed at a time. In addition to experimental repetition of different treatments, it should be considered that most experiments should have their technical replicates (where more than one position is imaged per plate), with a series of focal planes (z-stacks) being recorded in a series of time points. Thus, an experimental design with three repetitions of one control and two treatments, with five imaging positions per plate, and 15 time points, results in 225 stacks to be processed. Classically, videos of live mitochondria were analyzed by plotting kymographs, which would be individually analyzed8, in a time-consuming process requiring extensive manual input, even when relying on computer tools.
An algorithm was recently described9 that allows automated segmentation and tracking of mitochondria in live-cell 2-D and 3-D time-lapse files. Other quantification techniques are available, and all have their limitations10. Mitometer, an automated open-source application, is particularly adequate for time lapse and mitochondria dynamics analysis, requiring low user input. This application has a series of advantages over other existing MATLAB-based tools, namely allowing the automatic processing of individual TIF stacks, using up to 13 different parameters, particularly interesting for neurosciences, as it differentiates between peri- and tele-nuclear mitochondria.
However, for an experiment such as the above described, these 13 parameters applied to 225 stacks result in 2,925 individual output files. These require four individual computer inputs, which sum up to over 10,000 manual inputs being required to download all output files. For large experimental designs, this results in a needlessly extremely time-consuming analysis of each file and data integration. Herein we present a routine optimization that allows swift file analysis, greatly reducing document reading and data processing, analyzing data in a defined manner, consistent with the output from existing tools.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>AM580</td>
			<td>Sigma-Aldrich</td>
			<td>A8843</td>
			<td></td>
		</tr>
		<tr>
			<td>BDNF&#160;</td>
			<td>Thermo-Fisher</td>
			<td>RP8642</td>
			<td></td>
		</tr>
		<tr>
			<td>BMS493</td>
			<td>Tocris Bioscience&#160;</td>
			<td>3409</td>
			<td></td>
		</tr>
		<tr>
			<td>CD2314</td>
			<td>Tocris Bioscience</td>
			<td>3824</td>
			<td></td>
		</tr>
		<tr>
			<td>Ch55</td>
			<td>Tocris Bioscience&#160;</td>
			<td>2020</td>
			<td></td>
		</tr>
		<tr>
			<td>Foetal Bovine Serum</td>
			<td>Thermo-Fisher</td>
			<td>10270106</td>
			<td></td>
		</tr>
		<tr>
			<td>GraphPad Prism v4.0</td>
			<td>GraphPad Software, La Jolla</td>
			<td>n/a</td>
			<td></td>
		</tr>
		<tr>
			<td>Ham&#8217;s F12 Nutrient Mix</td>
			<td>Thermo-Fisher</td>
			<td>21765029</td>
			<td></td>
		</tr>
		<tr>
			<td>MATLAB R2022a&#160;</td>
			<td>MathWorks</td>
			<td>n/a</td>
			<td></td>
		</tr>
		<tr>
			<td>Minimal Essential Medium</td>
			<td>Thermo-Fisher</td>
			<td>31095</td>
			<td></td>
		</tr>
		<tr>
			<td>Nunc Glass Bottom Dishes</td>
			<td>Thermo-Fisher</td>
			<td>150680</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate Buffer Saline Solution</td>
			<td>Thermo-Fisher</td>
			<td>28372</td>
			<td></td>
		</tr>
		<tr>
			<td>Retinoic acid</td>
			<td>Sigma-Aldrich</td>
			<td>&#160;R2625</td>
			<td></td>
		</tr>
		<tr>
			<td>TMRM&#160;</td>
			<td>Thermo-Fisher</td>
			<td>T668</td>
			<td></td>
		</tr>
		<tr>
			<td>Zeiss LSM 510</td>
			<td>Carl Zeiss</td>
			<td>n/a</td>
			<td>Equiped with live-cell imaging culture chamber and 63x oil immersion objective&#160;</td>
		</tr>
	</tbody>
</table>

optimized automated analysis of live neuronal mitochondria homeostasis modulation by isoform-specific retinoic acid receptors

The complex mitochondrial network makes it very challenging to segment, follow, and analyze live cells. MATLAB tools allow the analysis of mitochondria in timelapse files, considerably simplifying and speeding up the process of image processing. Nonetheless, existing tools produce a large output volume, requiring individual manual attention, and basic experimental setups have an output of thousands of files, each requiring extensive and time-consuming handling. 
To address these issues, a routine optimization was developed, in both MATLAB code and live-script forms, allowing for swift file analysis and significantly reducing document reading and data processing. With a speed of 100 files/min, the optimization allows an overall rapid analysis. The optimization achieves the results output by averaging frame-specific data for individual mitochondria throughout time frames, analyzing data in a defined manner, consistent with those output from existing tools. Live confocal imaging was performed using the dye tetramethylrhodamine methyl ester, and the routine optimization was validated by treating neuronal cells with retinoic acid receptor (RAR) agonists, whose effects on neuronal mitochondria are established in the literature. The results were consistent with the literature and allowed further characterization of mitochondrial network behavior in response to isoform-specific RAR modulation. 
This new methodology allowed rapid and validated characterization of whole-neuron mitochondria network, but it also allows for differentiation between axon and cell body mitochondria, an essential feature to apply in the neuroscience field. Moreover, this protocol can be applied to experiments using fast-acting treatments, allowing the imaging of the same cells before and after treatments, transcending the field of neuroscience.

To enhance and accelerate the analysis of output files in .txt format, a routine optimization was coded that reads data consistent with Mitometer .txt output files, with columns representing a frame and lines representing identified mitochondria. The routine optimization produces data in a single value per parameter by averaging the frames for each identified mitochondria and then averaging the results of all mitochondria per visual field. The developed routine reads files from folders numbered from 1 upwards. The Live S...

Watch this Scientific Journal Video about Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria at JoVE.com

Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria

The mitochondrial network is extremely complex, making it very challenging to analyze. A novel MATLAB tool analyzes live confocal imaged mitochondria in timelapse images but results in a large output volume requiring individual manual attention. To address this issue, a routine optimization was developed, allowing for speedy file analysis.

Optimized Automated Analysis of Live Neuronal Mitochondria Homeostasis Modulation by Isoform-Specific Retinoic Acid Receptors

The complex mitochondrial network makes it very challenging to segment, follow, and analyze live cells. MATLAB tools allow the analysis of mitochondria in ...

optimized-automated-analysis-live-neuronal-mitochondria-homeostasis

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507 Views.  University of Aveiro. The mitochondrial network is extremely complex, making it very challenging to analyze. A novel MATLAB tool analyzes live confocal imaged mitochondria in timelapse images but results in a large output volume requiring individual manual attention. To address this issue, a routine optimization was developed, allowing for speedy file analysis.

Video: Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria

Automated Sholl Analysis of Digitized Neuronal Morphology at Multiple Scales

Neuronal morphology plays a significant role in determining how neurons function and communicate1-3. Specifically, it affects the ability of neurons to receive inputs from other cells2 and contributes to the propagation of action potentials4,5. The morphology of the neurites also affects how information is processed. The diversity of dendrite morphologies facilitate local and long range signaling and allow individual neurons or groups of neurons to carry out specialized functions within the neuronal network6,7. Alterations in dendrite morphology, including fragmentation of dendrites and changes in branching patterns, have been observed in a number of disease states, including Alzheimer's disease8, schizophrenia9,10, and mental retardation11. The ability to both understand the factors that shape dendrite morphologies and to identify changes in dendrite morphologies is essential in the understanding of nervous system function and dysfunction.
Neurite morphology is often analyzed by Sholl analysis and by counting the number of neurites and the number of branch tips. This analysis is generally applied to dendrites, but it can also be applied to axons. Performing this analysis by hand is both time consuming and inevitably introduces variability due to experimenter bias and inconsistency. The Bonfire program is a semi-automated approach to the analysis of dendrite and axon morphology that builds upon available open-source morphological analysis tools. Our program enables the detection of local changes in dendrite and axon branching behaviors by performing Sholl analysis on subregions of the neuritic arbor. For example, Sholl analysis is performed on both the neuron as a whole as well as on each subset of processes (primary, secondary, terminal, root, etc.) Dendrite and axon patterning is influenced by a number of intracellular and extracellular factors, many acting locally. Thus, the resulting arbor morphology is a result of specific processes acting on specific neurites, making it necessary to perform morphological analysis on a smaller scale in order to observe these local variations12.
The Bonfire program requires the use of two open-source analysis tools, the NeuronJ plugin to ImageJ and NeuronStudio. Neurons are traced in ImageJ, and NeuronStudio is used to define the connectivity between neurites. Bonfire contains a number of custom scripts written in MATLAB (MathWorks) that are used to convert the data into the appropriate format for further analysis, check for user errors, and ultimately perform Sholl analysis. Finally, data are exported into Excel for statistical analysis. A flow chart of the Bonfire program is shown in Figure 1.

We have developed a computer program to analyze neuronal morphology. In combination with two existing open source analysis tools, our program performs Sholl analysis and determines the number of neurites, branch points, and neurite tips. The analyses are performed so that local changes in neurite morphology can be observed.

Neuronal morphology plays a significant role in determining how neurons function and communicate1-3.  Specifically, it affects the ability of neurons to ...

VisioTracker, an Innovative Automated Approach to Oculomotor Analysis

Investigations into the visual system development and function necessitate quantifiable behavioral models of visual performance that are easy to elicit, robust, and simple to manipulate. A suitable model has been found in the optokinetic response (OKR), a reflexive behavior present in all vertebrates due to its high selection value. The OKR involves slow stimulus-following movements of eyes alternated with rapid resetting saccades. The measurement of this behavior is easily carried out in zebrafish larvae, due to its early and stable onset (fully developed after 96 hours post fertilization (hpf)), and benefitting from the thorough knowledge about zebrafish genetics, for decades one of the favored model organisms in this field. Meanwhile the analysis of similar mechanisms in adult fish has gained importance, particularly for pharmacological and toxicological applications.
Here we describe VisioTracker, a fully automated, high-throughput system for quantitative analysis of visual performance. The system is based on research carried out in the group of Prof. Stephan Neuhauss and was re-designed by TSE Systems. It consists of an immobilizing device for small fish monitored by a high-quality video camera equipped with a high-resolution zoom lens. The fish container is surrounded by a drum screen, upon which computer-generated stimulus patterns can be projected. Eye movements are recorded and automatically analyzed by the VisioTracker software package in real time.
Data analysis enables immediate recognition of parameters such as slow and fast phase duration, movement cycle frequency, slow-phase gain, visual acuity, and contrast sensitivity.
Typical results allow for example the rapid identification of visual system mutants that show no apparent alteration in wild type morphology, or the determination of quantitative effects of pharmacological or toxic and mutagenic agents on visual system performance.

The VisioTracker is an automated system for the quantitative analysis of visual performance of larval and small adult fish based on the recording of eye movements. It features full control over visual stimulus properties and real-time analysis, enabling high-throughput research in fields such as visual system development and function, pharmacology, neural circuit studies and sensorimotor integration.

Investigations into the visual system development and function necessitate quantifiable behavioral models of visual performance that are easy to elicit, ...

Methods for the Modulation and Analysis of NF-&#954;B-dependent Adult Neurogenesis

The hippocampus plays a pivotal role in the formation and consolidation of episodic memories, and in spatial orientation. Historically, the adult hippocampus has been viewed as a very static anatomical region of the mammalian brain. However, recent findings have demonstrated that the dentate gyrus of the hippocampus is an area of tremendous plasticity in adults, involving not only modifications of existing neuronal circuits, but also adult neurogenesis. This plasticity is regulated by complex transcriptional networks, in which the transcription factor NF-&#954;B plays a prominent role. To study and manipulate adult neurogenesis, a transgenic mouse model for forebrain-specific neuronal inhibition of NF-&#954;B activity can be used.
In this study, methods are described for the analysis of NF-&#954;B-dependent neurogenesis, including its structural aspects, neuronal apoptosis and progenitor proliferation, and cognitive significance, which was specifically assessed via a dentate gyrus (DG)-dependent behavioral test, the spatial pattern separation-Barnes maze (SPS-BM). The SPS-BM protocol could be simply adapted for use with other transgenic animal models designed to assess the influence of particular genes on adult hippocampal neurogenesis. Furthermore, SPS-BM could be used in other experimental settings aimed at investigating and manipulating DG-dependent learning, for example, using pharmacological agents.

Methods for the manipulation and analysis of NF-&#954;B-dependent adult hippocampal neurogenesis are described. A detailed protocol is presented for a dentate gyrus-dependent behavioral test (termed the spatial pattern separation-Barnes maze) for the investigation of cognitive outcome in mice. This technique should also help enable investigations in other experimental settings.

The hippocampus plays a pivotal role in the formation and consolidation of episodic memories, and in spatial orientation. Historically, the adult ...

Inducing Plasticity of Astrocytic Receptors by Manipulation of Neuronal Firing Rates

Close to two decades of research has established that astrocytes in situ and in vivo express numerous G protein-coupled receptors (GPCRs) that can be stimulated by neuronally-released transmitter. However, the ability of astrocytic receptors to exhibit plasticity in response to changes in neuronal activity has received little attention. Here we describe a model system that can be used to globally scale up or down astrocytic group I metabotropic glutamate receptors (mGluRs) in acute brain slices. Included are methods on how to prepare parasagittal hippocampal slices, construct chambers suitable for long-term slice incubation, bidirectionally manipulate neuronal action potential frequency, load astrocytes and astrocyte processes with fluorescent Ca2+ indicator, and measure changes in astrocytic Gq GPCR activity by recording spontaneous and evoked astrocyte Ca2+ events using confocal microscopy. In essence, a &#8220;calcium roadmap&#8221; is provided for how to measure plasticity of astrocytic Gq GPCRs. Applications of the technique for study of astrocytes are discussed. Having an understanding of how astrocytic receptor signaling is affected by changes in neuronal activity has important implications for both normal synaptic function as well as processes underlying neurological disorders and neurodegenerative disease.

Here we describe an adaptation of protocols used to induce homeostatic plasticity in neurons for the study of plasticity of astrocytic G protein-coupled receptors. Recently used to examine changes in astrocytic group I mGluRs in juvenile mice, the method can be applied to measure scaling of various astrocytic GPCRs, in tissue from adult mice in situ and in vivo, and to gain a better appreciation of the sensitivity of astrocytic receptors to changes in neuronal activity.

Close to two decades of research has established that astrocytes in situ and in vivo express numerous G protein-coupled receptors (GPCRs) that can be ...

High-throughput Analysis of Mammalian Olfactory Receptors: Measurement of Receptor Activation via Luciferase Activity

Odorants create unique and overlapping patterns of olfactory receptor activation, allowing a family of approximately 1,000 murine and 400 human receptors to recognize thousands of odorants. Odorant ligands have been published for fewer than 6% of human receptors1-11. This lack of data is due in part to difficulties functionally expressing these receptors in heterologous systems. Here, we describe a method for expressing the majority of the olfactory receptor family in Hana3A cells, followed by high-throughput assessment of olfactory receptor activation using a luciferase reporter assay. This assay can be used to (1) screen panels of odorants against panels of olfactory receptors; (2) confirm odorant/receptor interaction via dose response curves; and (3) compare receptor activation levels among receptor variants. In our sample data, 328 olfactory receptors were screened against 26 odorants. Odorant/receptor pairs with varying response scores were selected and tested in dose response. These data indicate that a screen is an effective method to enrich for odorant/receptor pairs that will pass a dose response experiment, i.e. receptors that have a bona fide response to an odorant. Therefore, this high-throughput luciferase assay is an effective method to characterize olfactory receptors&#8212;an essential step toward a model of odor coding in the mammalian olfactory system.

Olfactory receptor activation patterns encode odor identity, but the lack of published data identifying odorant ligands for mammalian olfactory receptors hinders the development of a comprehensive model of odor coding. This protocol describes a method to facilitate high-throughput identification of olfactory receptor ligands and quantification of receptor activation.

Odorants create unique and overlapping patterns of olfactory receptor activation, allowing a family of approximately 1,000 murine and 400 human receptors ...

Three-dimensional Imaging and Analysis of Mitochondria within Human Intraepidermal Nerve Fibers

The goal of this protocol is to study mitochondria within intraepidermal nerve fibers. Therefore, 3D imaging and analysis techniques were developed to isolate nerve-specific mitochondria and evaluate disease-induced alterations of mitochondria in the distal tip of sensory nerves. The protocol combines fluorescence immunohistochemistry, confocal microscopy and 3D image analysis techniques to visualize and quantify nerve-specific mitochondria. Detailed parameters are defined throughout the procedures in order to provide a concrete example of how to use these techniques to isolate nerve-specific mitochondria. Antibodies were used to label nerve and mitochondrial signals within tissue sections of skin punch biopsies, which was followed by indirect immunofluorescence to visualize nerves and mitochondria with a green and red fluorescent signal respectively. Z-series images were acquired with confocal microscopy and 3D analysis software was used to process and analyze the signals. It is not necessary to follow the exact parameters described within, but it is important to be consistent with the ones chosen throughout the staining, acquisition and analysis steps. The strength of this protocol is that it is applicable to a wide variety of circumstances where one fluorescent signal is used to isolate other signals that would otherwise be impossible to study alone.

This protocol uses three-dimensional (3D) imaging and analysis techniques to visualize and quantify nerve-specific mitochondria. The techniques are applicable to other situations where one fluorescent signal is used to isolate a subset of data from another fluorescent signal.

The goal of this protocol is to study mitochondria within intraepidermal nerve fibers. Therefore, 3D imaging and analysis techniques were developed to ...

Analysis of Brain Mitochondria Using Serial Block-Face Scanning Electron Microscopy

Human brain is a high energy consuming organ that mainly relies on glucose as a fuel source. Glucose is catabolized by brain mitochondria via glycolysis, tri-carboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS) pathways to produce cellular energy in the form of adenosine triphosphate (ATP). Impairment of mitochondrial ATP production causes mitochondrial disorders, which present clinically with prominent neurological and myopathic symptoms. Mitochondrial defects are also present in neurodevelopmental disorders (e.g. autism spectrum disorder) and neurodegenerative disorders (e.g. amyotrophic lateral sclerosis, Alzheimer&#39;s and Parkinson&#39;s diseases). Thus, there is an increased interest in the field for performing 3D analysis of mitochondrial morphology, structure and distribution under both healthy and disease states. The brain mitochondrial morphology is extremely diverse, with some mitochondria especially those in the synaptic region being in the range of &#60;200 nm diameter, which is below the resolution limit of traditional light microscopy. Expressing a mitochondrially-targeted green fluorescent protein (GFP) in the brain significantly enhances the organellar detection by confocal microscopy. However, it does not overcome the constraints on the sensitivity of detection of relatively small sized mitochondria without oversaturating the images of large sized mitochondria. While serial transmission electron microscopy has been successfully used to characterize mitochondria at the neuronal synapse, this technique is extremely time-consuming especially when comparing multiple samples. The serial block-face scanning electron microscopy (SBFSEM) technique involves an automated process of sectioning, imaging blocks of tissue and data acquisition. Here, we provide a protocol to perform SBFSEM of a defined region from rodent brain to rapidly reconstruct and visualize mitochondrial morphology. This technique could also be used to provide accurate information on mitochondrial number, volume, size and distribution in a defined brain region. Since the obtained image resolution is high (typically under 10 nm) any gross mitochondrial morphological defects may also be detected.

Mitochondrial visualization and analysis from mammalian brain tissue is a challenging task. Here, we describe how three dimensional (3D) reconstruction analysis from the serial block-face scanning electron microscopy (SBFSEM) can be used to gain insights on the morphological and volumetric analysis of this critical energy generating organelle.

Human brain is a high energy consuming organ that mainly relies on glucose as a fuel source. Glucose is catabolized by brain mitochondria via glycolysis, ...

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light

The nervous system has the remarkable ability to adapt and respond to various stimuli. This neural adjustment is largely achieved through plasticity at the synaptic level. The Active Zone (AZ) is the region at the presynaptic membrane that mediates neurotransmitter release and is composed of a dense collection of scaffold proteins. AZs of Drosophila melanogaster (Drosophila) photoreceptors undergo molecular remodeling after prolonged exposure to natural ambient light. Thus the level of neuronal activity can rearrange the molecular composition of the AZ and contribute to the regulation of the functional output.
Starting from the light exposure set-up preparation to the immunohistochemistry, this protocol details how to quantify the number, the spatial distribution, and the delocalization level of synaptic molecules at AZs in Drosophila photoreceptors. Using image analysis software, clusters of the GFP-fused AZ component Bruchpilot were identified for each R8 photoreceptor (R8) axon terminal. Detected Bruchpilot spots were automatically assigned to individual R8 axons. To calculate the distribution of spot frequency along the axon, we implemented a customized software plugin. Each axon&#39;s start-point and end-point were manually defined and the position of each Bruchpilot spot was projected onto the connecting line between start and end-point. Besides the number of Bruchpilot clusters, we also quantified the delocalization level of Bruchpilot-GFP within the clusters. These measurements reflect in detail the spatially resolved synaptic dynamics in a single neuron under different environmental conditions to stimuli.

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light

Here we show how to quantify the number and spatial distribution of synaptic active zones in Drosophila melanogaster&#160;photoreceptors, highlighted with a genetically encoded molecular marker, and their modulation after prolonged exposure to light.

The nervous system has the remarkable ability to adapt and respond to various stimuli. This neural adjustment is largely achieved through plasticity at ...

Assessment of Dopaminergic Homeostasis in Mice by Use of High-performance Liquid Chromatography Analysis and Synaptosomal Dopamine Uptake

Dopamine (DA) is a modulatory neurotransmitter controlling motor activity, reward processes and cognitive function. Impairment of dopaminergic (DAergic) neurotransmission is strongly associated with several central nervous system-associated diseases such as Parkinson&#39;s disease, attention-deficit-hyperactivity disorder and drug addiction1,2,3,4. Delineating disease mechanisms involving DA imbalance is critically dependent on animal models to mimic aspects of the diseases, and thus protocols that assess specific parts of the DA homeostasis are important to provide novel insights and possible therapeutic targets for these diseases.
Here, we present two useful experimental protocols that when combined provide a functional read-out of the DAergic system in mice. Biochemical and functional parameters on DA homeostasis are obtained through assessment of DA levels and dopamine transporter (DAT) functionality5. When investigating the DA system, the ability to reliably measure endogenous levels of DA from adult brain is essential. Therefore, we present how to perform high-performance liquid chromatography (HPLC) on brain tissue from mice to determine levels of DA. We perform the experiment on tissue from dorsal striatum (dStr) and nucleus accumbens (NAc), but the method is also suitable for other DA-innervated brain areas.
DAT is essential for reuptake of DA into the presynaptic terminal, thereby controlling the temporal and spatial activity of released DA. Knowing the levels and functionality of DAT in the striatum is of major importance when assessing DA homeostasis. Here, we provide a protocol that allows to simultaneously deduce information on surface levels and function using a synaptosomal6 DA uptake assay.
Current methods combined with standard immunoblotting protocols provide the researcher with relevant tools to characterize the DAergic system.

Synaptosomal dopamine uptake and high-performance liquid chromatography analysis represent experimental tools to investigate dopamine homeostasis in mice by assessing the function of the dopamine transporter and levels of dopamine in striatal tissue, respectively. Here we present protocols to measure dopamine tissue content and assess the functionality of the dopamine transporter.

Dopamine (DA) is a modulatory neurotransmitter controlling motor activity, reward processes and cognitive function. Impairment of dopaminergic (DAergic) ...

Molecular Modulation by Lentivirus-Delivered Specific shRNAs in Endoplasmic Reticulum Stressed Neurons

The accumulation of unfolded proteins within the endoplasmic reticulum (ER), caused by any stress condition, triggers the unfolded protein response (UPR) through the activation of specialized sensors. UPR attempts first to restore homeostasis; but if damage persists the signaling induces apoptosis.
There is increasing evidence that sustained and unresolved ER stress contributes to many pathological conditions including neurodegenerative diseases. Because the UPR controls cell fate by switching between cytoprotective and apoptotic processes, it is essential to understand the events defining this transition, as well as the elements involved in its modulation.
Recently, we demonstrated that abnormal GM2 ganglioside accumulation causes depletion of ER Ca2+ content, which in turn activates PERK (PKR-like-ER kinase), one of the UPR sensors. Furthermore, PERK signaling participates in the neurite atrophy and apoptosis induced by GM2 accumulation. In this respect, we have established an experimental system that allows us to molecularly modulate the expression of downstream PERK components and thus change vulnerability of neurons to undergo neuritic atrophy.
We performed knockdown of calcineurin (cytoprotective) and CHOP (pro-apoptotic) expression in rat cortical neuronal cultures. Cells were infected with lentivirus-delivered specific shRNA and then treated with GM2 at different times, fixed and immunostained with anti-MAP2 (microtube-associated protein 2) antibody. Later, cell images were recorded using a fluorescence microscope and total neurite outgrowth was evaluated by using the public domain image processing software ImageJ. The inhibition of expression of those PERK signaling components clearly made it possible to either accelerate or delay the neuritic atrophy induced by ER stress.
This approach might be used in cell system models of ER stress to evaluate the vulnerability of neurons to neurite atrophy.

In the present study, the expression is knocked down of two downstream signaling components of the PERK pathway, the cytoprotective calcineurin and the pro-apoptotic CHOP, by using specific shRNAs. In opposite ways, these modulate the susceptibility of primary cortical neurons to neurite atrophy after induction of endoplasmic reticulum stress.

The accumulation of unfolded proteins within the endoplasmic reticulum (ER), caused by any stress condition, triggers the unfolded protein response (UPR) ...