Name: Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy (Video) | JoVE Journal
Uploaded: 2019-01-19T15:00:00.000+00:00
Duration: 7 min 2 s
Description: Learn longitudinal fluorescence microscopy for monitoring neuronal survival in cortical neurons. This method enables single-cell tracking to identify predictors of cell death and advance neurodegenerative disease research.

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5 minutes

We thank Steve Finkbeiner and members of the Finkbeiner lab for pioneering robotic microscopy. We also thank Dan Peisach for building the initial software required for image processing and automated survival analysis. This work was funded by the National Institute for Neurological Disorders and Stroke (NINDS) R01-NS097542, the University of Michigan Protein Folding Disease Initiative, and Ann Arbor Active Against ALS.

All vertebrate animal work was approved by the Committee on the Use and Care of Animals at the University of Michigan (protocol # PRO00007096). Experiments are carefully planned to minimize the number of animals sacrificed. Pregnant female wild-type (WT), non-transgenic Long Evans rats (Rattus norvegicus) are housed singly in chambers equipped with environmental enrichment, and cared for by the Unit for Laboratory Animal Medicine (ULAM) at the University of Michigan, in accordance with the NIH-supported Guide for the Care and Use of Laboratory Animals. All rats were kept in routine housing for as little time as possible prior to euthanasia, consistent with the recommendations of the Guidelines on Euthanasia of the American Veterinary Medical Association and the University of Michigan Methods of Euthanasia by Species Guidelines.
1. Material Preparation
<ol>
	<li>Dissect cortical neurons from embryonic day 19&#8211;20 rat pups and culture rat cortical neurons at 0.5 x 106 cells per milliliter on poly-D-lysine coated plates for 4 days in vitro, as described previously13,14,15,16,17,18,19.</li>
	<li>Prepare the plasmid DNA of interest following the steps outlined by an endotoxin-free plasmid DNA isolation kit (see Table of Materials). Quantify the resultant DNA using a spectrophotometer.</li>
	<li>On in vitro day 4 (DIV4), aliquot, filter sterilize, and incubate the following media at 37 &#176;C: 6 mL reduced serum media (RSM; e.g., OptiMEM), 25 mL neuronal basal media (NBM), 40 mL NBKY (NBM + 1 mM kynurenic acid + 10 mM MgCl2, adjusted to a pH of 7.4), 10 mL NBC (NBM + 1x neuronal cell culture supplement + 1x L-glutamine supplement + 1x Pen Strep). 
	NOTE: Volumes listed are sufficient for transfecting one 96-well plate. Refer to the Table of Materials for specific reagents.</li>
</ol>
2. Transfection of Rat Cortical Neurons
<ol>
	<li>Modify the provided Example transfection sheet (see Supplemental File 1) by adjusting the plate type, plate map, number of DNAs, DNA concentration, and number of wells (green boxes). 
	NOTE: The total DNA sums to 0.2 &#181;g per well, regardless of whether one (e.g., DNA A) or multiple (e.g., DNA B and C) DNA constructs are added to each well.</li>
	<li>Working from the spreadsheet, combine the appropriate amount of RSM and DNA in one tube. Combine the appropriate amount of RSM and transfection reagent (e.g., Lipofectamine) in a separate tube.</li>
	<li>Incubate at room temperature (RT) for 5 min.</li>
	<li>Combine the DNA and transfection reagent RSM mixtures and incubate at RT for 20 min.</li>
	<li>During this incubation step, use a multichannel pipette and sterile plastic troughs to wash cells 2x with 100 &#181;L per well of NBM. Reserve the conditioned media (CM) and store at 37 &#176;C. For this and following steps, take care to minimize the amount of time neurons are exposed to air.</li>
	<li>Remove the NBM media and replace with 100 &#181;L per well of NBKY.</li>
	<li>After 20 min have passed, add 50 &#181;L of the transfection reagent/DNA mixture dropwise to each well.</li>
	<li>Incubate cells with the transfection reagent/DNA complexes for 20 min at 37 &#176;C.</li>
	<li>Rinse 2x with NBKY and replace with 100 &#181;L of CM and 100 &#181;L of NBC per well.</li>
	<li>Successfully transfected cells should be visible by fluorescence microscopy within 16&#8211;24 h of transfection. To gauge efficiency, use a fluorescent microscope to check the transfection after overnight incubation at 37 &#176;C. 
	NOTE: This technique results in an overall transfection efficiency of 5 to 10%.</li>
</ol>
3. Imaging
<ol>
	<li>Place the plate on a fluorescent microscope with a motorized stage, and establish a fiduciary (e.g., a mark on the bottom of the plate) that will allow the user to align the plate each time it is imaged. Save an image of this fiduciary for reference.</li>
	<li>Navigate to a field of interest and note the x-y coordinates relative to the fiduciary.</li>
	<li>Focus on transfected cells expressing a fluorescent label.</li>
	<li>Take fluorescent images in the appropriate channel or channels (e.g., red fluorescent protein [RFP], green fluorescent protein [GFP], 4&#8242;,6-diamidino-2-phenylindole [DAPI]), either manually or in an automated manner. By taking several images at regularly-spaced intervals, a montage of the well can be assembled during image processing (see step 4). 
	NOTE: The spacing depends on several factors, including magnification, the optics of the microscope, and the detector size. In general, the optical spacing between adjacent images will be between 90&#8211;95% of the size of each individual image, to allow for a small degree of image overlap and feature alignment.</li>
	<li>Repeat this process as often as required, aligning to the original fiduciary each time. For survival analysis, imaging takes place every 6&#8211;24 h, depending on the cell type and the purpose of the experiment.</li>
</ol>
4. Image Processing
NOTE: Following image acquisition, a series of processing steps are required prior to image analysis. These include, but are not limited to, stitching, stacking, and background subtraction (Figure 1). The goal of these steps is to produce an image stack, or time series, in which cells are clearly discernible from their background and easy to follow over multiple time points. A dedicated FIJI macro (Image_Processing.ijm, see Supplemental File 2), performs basic stitching, stacking, and background subtraction. An explanation of each step and the parameters to consider when performing image processing is provided in the discussion section.
<ol>
	<li>Adjust the raw data or input directory to match the formatting shown in Figure 2.</li>
	<li>If time points are not contiguous (i.e., T1, T2, T3), rename these folders so that they are. This step is critical to ensure that the Image_Processing macro does not crash during stacking.</li>
	<li>Double-click on the Fiji icon to open the program, then click and drag the Image_Processing macro onto the Fiji bar. This will open the macro within Fiji.</li>
	<li>Adjust lines 2-7 of the Image_Processing macro to specify the input directory containing images, the desired output directory for stitched and stacked images, the number of imaging timepoints, number of fluorescent channels and plate format.</li>
	<li>Determine the order in which the images were acquired. To test this, manually stitch a montage of images in FIJI by maneuvering to the Plugins drop down menu | Stitching | Grid/Collection stitching. Adjust the settings within the dropdown menus Type and Order until an accurately stitched image is produced.</li>
	<li>Adjust the GRID_TYPE and STITCH_ORDER variables in lines 8 and 9 of the Image_Processing macro to match these selections.</li>
	<li>Specify the number of images per well by adjusting line 10 in the Image_Processing macro. 
	NOTE: For a 2 x 2 montage of images, this line would read DIM = 2.</li>
	<li>If background subtraction is required, adjust line 14 in the Image_Processing macro to BGSUB = true.</li>
	<li>Set the rolling ball radius by adjusting line 15 in the Image_Processing macro. 
	NOTE: For optimal results, set the radius to at least the diameter of the largest foreground object in the image.</li>
	<li>Click Run to start the Image_Processing macro. Once started, Image_Processing will automatically advance through stitching, stacking, and background subtraction.</li>
</ol>
5. Scoring Cell Death
NOTE: See the Discussion section for more information on scoring cell death and censoring data.
<ol>
	<li>Locate the image stacks produced by the Image_Processing script. Open these in FIJI.</li>
	<li>Use the point tool within FIJI to individually label each cell with a number. Pressing t after each point will add the cell identifier to the ROI (region-of-interest) Manager. 
	NOTE: The identifiers can be visualized by clicking the labels and show all checkboxes in the ROI Manager.</li>
	<li>Progress through the timepoints in each image stack and record the timepoint when each cell either dies or needs to be censored in the file Survival_spreadsheet.csv (see Supplemental File 3).
	<ol>
		<li>Each cell occupies a single row in the spreadsheet, where a unique identifier (ID) for each cell consists of its corresponding well and ROI number within that well. tp_death is the last time point a cell is observed to be alive, while time_death represents the actual time of death in hours. For each cell, input these data. It is critical to maintain this structure for subsequent analysis using survival.R (see Supplemental File 4). 
		NOTE: The criteria for determining cell death are crucial and may vary depending on cell type. Three main criteria are used in the identification of dead neurons11,20 (Figure 3): loss of fluorescence intensity (e.g., Neuron 1 at 69 h), rounding of the cell body (e.g., Neuron 2 at 188 h), and the loss of neurite integrity or blebbing (e.g., Neuron 2 at 188 h).</li>
	</ol>
	</li>
	<li>Record the censor status of the cell in the last column. 
	NOTE: Here, due to the peculiar way censoring is handled by R, censored cells are marked by 0, while uncensored cells are marked by 1. Note that all cells that live to the last time point are censored, and therefore marked as 0.</li>
</ol>
6. Performing Cox Proportional Hazards Analysis and Visualizing Results
<ol>
	<li>If necessary, download R studio at https://cran.r-project.org/mirrors.html.</li>
	<li>Open R studio and double-click the icon for the survival.R script.</li>
	<li>Place the cursor on line 2 of survival.R and click the run button in the main R studio window in order to load the survival library.</li>
	<li>Change line 5 of the survival.R script to match the location of the file Survival_spreadsheet.csv. Click on run to load the survival data as a dataframe.</li>
	<li>Highlight lines 8 and 9 and click the run button in the R studio console window in order to perform Cox proportional hazards analysis. Results and output statistics appear in the console window of R studio.</li>
	<li>Highlight lines 12-16 of survival.R and hit the run button in order to produce a cumulative risk of death plot, which will appear in the plots tab in R studio. This file can be saved by clicking on the export button above the plot.</li>
	<li>If it is desirable to plot the survival data as a Kaplan-Meier curve, highlight lines 19-24 of survival.R and hit the run button.</li>
</ol>

<ol><li>Lockshin, R. A., Zakeri, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cell+death+in+health+and+disease%5BTitle%5D)+AND+%22Journal+of+Cellular+and+Molecular+Medicine%22%5BJournal%5D)">Cell death in health and disease.</a> Journal of Cellular and Molecular Medicine. 11, 1214-1224 (2007).</li>
<li>Kepp, O., Galluzzi, L., Lipinski, M., Yuan, J., Kroemer, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cell+death+assays+for+drug+discovery%5BTitle%5D)+AND+%22Nature+Reviews+Drug+Discovery%22%5BJournal%5D)">Cell death assays for drug discovery.</a> Nature Reviews Drug Discovery. 10, 221-237 (2011).</li>
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<li>Mitchell, D. B., Santone, K. S., Acosta, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Evaluation+of+cytotoxicity+in+cultured+cells+by+enzyme+leakage%5BTitle%5D)+AND+%22Journal+of+Tissue+Culture+Methods%22%5BJournal%5D)">Evaluation of cytotoxicity in cultured cells by enzyme leakage.</a> Journal of Tissue Culture Methods. 6, 113-116 (1980).</li>
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<li>Mossman, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Rapid+colorimetric+assay+for+cellular+growth+and+survival%3A+Application+to+proliferation+and+cytotoxicity+assays%5BTitle%5D)+AND+%22Journal+of+Immunological+Methods%22%5BJournal%5D)">Rapid colorimetric assay for cellular growth and survival: Application to proliferation and cytotoxicity assays.</a> Journal of Immunological Methods. 65 (1-2), 55-63 (1983).</li>
<li>Guerzoni, L. P. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((In+Vitro+Modulation+of+TrkB+Receptor+Signaling+upon+Sequential+Delivery+of+Curcumin-DHA+Loaded+Carriers+Towards+Promoting+Neuronal+Survival%5BTitle%5D)+AND+%22Pharmaceutical+Research%22%5BJournal%5D)">In Vitro Modulation of TrkB Receptor Signaling upon Sequential Delivery of Curcumin-DHA Loaded Carriers Towards Promoting Neuronal Survival.</a> Pharmaceutical Research. 34 (2), 492-505 (2017).</li>
<li>Arrasate, M., Finkbeiner, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Automated+microscope+system+for+determining+factors+that+predict+neuronal+fate%5BTitle%5D)+AND+%22Proceedings+of+the+National+Academy+of+Science+of+the+United+States+of+America%22%5BJournal%5D)">Automated microscope system for determining factors that predict neuronal fate.</a> Proceedings of the National Academy of Science of the United States of America. 102, 3840-3845 (2005).</li>
<li>Christensen, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multivariate+survival+analysis+using+Cox%E2%80%99s+regression+model%5BTitle%5D)+AND+%22Hepatology%22%5BJournal%5D)">Multivariate survival analysis using Cox’s regression model.</a> Hepatology. 7, 1346-1358 (1987).</li>
<li>Barmada, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Autophagy+induction+enhances+TDP43+turnover+and+survival+in+neuronal+ALS+models%5BTitle%5D)+AND+%22Nature+Chemical+Biology%22%5BJournal%5D)">Autophagy induction enhances TDP43 turnover and survival in neuronal ALS models.</a> Nature Chemical Biology. 10, 677-685 (2014).</li>
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</ol>

The authors have nothing to disclose.

Here, methodology to directly monitor neuronal survival on a single-cell basis is presented. In contrast to traditional assays for cell death that are limited to discrete time points and entire populations of cells, this method allows for the continuous assessment of a variety of factors such as cellular morphology, protein expression, or localization, and can determine how each factor influences cellular survival in a prospective manner.
This methodology can be modified to fit a wide array of...

Abnormal cell death is a driving factor in many diseases, including cancer, neurodegeneration, and stroke1. Robust and sensitive assays for cell death are essential to the characterization of these disorders, as well as the development of therapeutic strategies for extending or reducing cellular survival. There are currently dozens of techniques for measuring cell death, either directly or through surrogate markers2. For example, cell death can be assessed visually with the help of vital dyes that selectively stain dead or living cells3, or by monitoring the appearance of specific phospholipids on the plasma membrane4,5,6. Measurements of intracellular components or cellular metabolites released into the media upon cellular dissolution can also be used as proxies for cell death7,8. Alternatively, cellular viability can be approximated by assessing metabolic activity9,10. Though these methods provide rapid means of assessing cell survival, they are not without caveats. Each technique observes the culture as a single population, rendering it impossible to distinguish between individual cells and their unique rates of survival. Furthermore, such population-based assays are unable to measure factors that may be important for cell death, including cellular morphology, protein expression, or localization. In many cases, these assays are limited to discrete time points, and do not allow for the continuous observation of cells over time.
&#160;In contrast, longitudinal fluorescence microscopy is a highly flexible methodology that directly and continuously monitors the risk of death on a single-cell basis11. In brief, longitudinal fluorescence microscopy enables thousands of individual cells to be tracked at regular intervals for extended periods of time, allowing precise determinations of cell death and the factors that enhance or suppress cell death. At its base, the method involves the transient transfection or transduction of cells with vectors encoding fluorescent proteins. A unique fiduciary is then established, and the position of each transfected cell in relation to this landmark allows the user to image and track individual cells over the course of hours, days, or weeks. When these images are viewed sequentially, cell death is marked by characteristic changes in fluorescence, morphology, and fragmentation of the cell body, enabling the assignment of a time of death for each cell. The calculated rate of death, determined by the hazard function, can then be quantitatively compared between conditions, or related to select cellular characteristics using univariate or multivariate Cox proportional hazards analysis12. Together, these approaches enable the accurate and objective discrimination of rates of cell death among cellular populations, and the identification of variables that significantly predict cell death and/or survival (Figure 1).
Although this method can be used to monitor survival in any post-mitotic cell type in a variety of plating formats, this protocol will describe conditions for transfecting and imaging rat cortical neurons cultured in a 96-well plate.

<table><tbody><tr><td>Neurobasal Medium</td><td>GIBCO</td><td>21103-049</td><td></td></tr><tr><td>Opti-MEM</td><td>GIBCO</td><td>31985-070</td><td></td></tr><tr><td>CompactPrep Plasmid Maxi Kit</td><td>Qiagen</td><td>12863</td><td></td></tr><tr><td>Magnesium chloride Hexahydrate</td><td>Sigma</td><td>M9272</td><td></td></tr><tr><td>Kynurenic Acid Hydrate</td><td>TCI</td><td>H0303</td><td></td></tr><tr><td>Poly D-Lysine</td><td>Millipore</td><td>A-003-E</td><td></td></tr><tr><td>Glutamax</td><td>GIBCO</td><td>35050-061</td><td></td></tr><tr><td>Lipofectamine 2000</td><td>Invitrogen</td><td>52887</td><td></td></tr><tr><td>B27 supplement</td><td>Thermo Fisher</td><td>A3582801</td><td></td></tr><tr><td>Penicillin/Streptomycin</td><td>GIBCO</td><td>15140122</td><td></td></tr><tr><td>96 well plates</td><td>TPP</td><td>0876</td><td></td></tr></tbody></table>

monitoring neuronal survival via longitudinal fluorescence microscopy

Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy

Standard cytotoxicity assays, which require the collection of lysates or fixed cells at multiple time points, have limited sensitivity and capacity to assess factors that influence neuronal fate. These assays require the observation of separate populations of cells at discrete time points. As a result, individual cells cannot be followed prospectively over time, severely limiting the ability to discriminate whether subcellular events, such as puncta formation or protein mislocalization, are pathogenic drivers of disease, homeostatic responses, or merely coincidental phenomena. Single-cell longitudinal microscopy overcomes these limitations, allowing the researcher to determine differences in survival between populations and draw causal relationships with enhanced sensitivity. This video guide will outline a representative workflow for experiments measuring single-cell survival of rat primary cortical neurons expressing a fluorescent protein marker. The viewer will learn how to achieve high-efficiency transfections, collect and process images enabling the prospective tracking of individual cells, and compare the relative survival of neuronal populations using Cox proportional hazards analysis.

Using the transfection procedure described here, DIV4 rat cortical neurons were transfected with a plasmid encoding the fluorescent protein mApple. Beginning 24 h post-transfection, cells were imaged by fluorescence microscopy every 24 h for 10 consecutive days. The resultant images were organized as indicated in Figure 2, then stitched, stacked, and scored for cell death (Figure 1). Figure 3 shows a...

Here, we present a protocol to monitor survival on a single-cell basis and identify variables that significantly predict cell death.

Standard cytotoxicity assays, which require the collection of lysates or fixed cells at multiple time points, have limited sensitivity and capacity to ...

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Neural stem/progenitor cells exhibit various expression dynamics of Notch signaling components that lead to different outcomes of cellular events. Such dynamic expression can be revealed by real-time monitoring, not by static analysis, using a highly sensitive bioluminescence imaging system that enables visualization of rapid changes in gene expressions.

Real-time Bioluminescence Imaging of Notch Signaling Dynamics during Murine Neurogenesis

Two related methods are described to visualize subcellular events required for synaptic transmission. These protocols enable the real-time monitoring of the dynamics of presynaptic calcium influx and synaptic vesicle membrane fusion using live-cell imaging of in vitro cultured neurons.

Real-Time Fluorescent Measurement of Synaptic Functions in Models of Amyotrophic Lateral Sclerosis

Learn longitudinal fluorescence microscopy for monitoring neuronal survival in cortical neurons. This method enables single-cell tracking to identify predictors of cell death and advance neurodegenerative disease research.

Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy

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