Name: monitoring neuronal survival via longitudinal fluorescence microscopy
Uploaded: 2019-01-19T15:00:00.000+00:00
Duration: 7 min 2 s
Description: Watch this Scientific Journal Video about Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy at JoVE.com

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>

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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 experimental needs. The frequency and duration of imaging can be easily adjusted, and any protein of interest can be co-transfected with the fluorescent marker to model disease states or investigate protein function13,14,15,16,17,18,19. Though this article describes the optimal procedure for transfecting rat cortical neurons, the experimental schema may be applied to any post-mitotic cell type. However, the optimal transfection conditions may need to be optimized on a per-cell line basis, and substrates may need to be adjusted to prevent cells from clumping or moving too much to reliably track.
Image processing and analysis requirements will vary depending on the specific parameters of each longitudinal microscopy experiment. A brief explanation of each critical step is included below to help customize the protocol to better match an experiment&#8217;s demands.
Stitching: If a montage of images is taken, stitching can be performed to create a single, larger image for each field of view. For most applications it is preferable to perform stitching prior to stacking. If only one image is taken per well, there is no need to perform this step.
Stacking: Rather than tracking cells over time across separate image files, stacking can be performed to align consecutive images into a single time series, analogous to a stop frame animation. With successful fiduciary alignment, the individual frames comprising the stacked image will be closely aligned. However, if there are noticeable shifts or rotations between frames, image registration is needed. The Image_Processing macro automatically performs registration using the FIJI plugin &#8220;MultiStackReg.&#8221; This plugin helps reduce small misalignments between imaging runs. However, with significant shifts, manually cropping and realigning images may be required.
Background subtraction (optional): One potential issue that may arise during image acquisition is uneven illumination. This will result in variations in signal intensity across an image that can confound estimates of fluorescence intensity. In these instances, intensity variations can be eliminated by background subtraction techniques. These are particularly relevant with low signal to noise ratios, where intensity shifts due to uneven illumination can be comparable in magnitude to the signal of the fluorophore itself. There are many background subtraction algorithms, several of which have associated FIJI plugins. The choice of which algorithm to use depends on the properties of the image itself and the signal being measured. Within the FIJI macro Image_Processing, the user is given the option to perform &#8220;rolling ball&#8221; background subtraction on a stacked set of images (line 14). In this method, a local background is determined for every pixel based on the average intensity of a circle surrounding that pixel. This value is then subtracted from the pixel&#8217;s initial value. The optimal value for the radius of the circle used for local background estimates will differ based upon the diameter of the largest foreground object in the image.
Scoring cell death: For accurate comparisons between populations, it is essential that the criteria outlined above to identify dead neurons be applied consistently across the entire dataset. Furthermore, blinding the individuals scoring cell death to the experimental groups under investigation eliminates potential sources of bias. Depending on the specific criteria and their generalizability, they may be incorporated into automated algorithms for the unbiased assessment of cellular survival15,16,17,18,19.
In the context of survival analysis and other time-to-event analyses, there are three possible outcomes. First, the event (cell death) has occurred, and the time at which the event occurred is recorded. Second, the event did not occur during the time frame of observation. These observations are censored at the completion of the experiment. Third, the event could not be scored because the cell moved out of the field of view, or was obscured by nearby cells. In this case, the cell is censored when it can no longer be accurately tracked. For the first outcome, the precise timing of cell death may be difficult to determine based on the imaging interval. For instance, a cell that is alive initially but marked as dead 24 h later may have died at any point within that 24 h period. To be conservative, it is good practice to record the time of death as the last time a cell can be confidently identified as alive (left censoring).
Performing Cox proportional hazards analysis and visualizing results: The accompanying Survival.R script enables the comparison of risk of death among populations and their statistical significance using Cox proportional hazards analysis (Figure 4A), and also plot results as either a Kaplan-Meier curve (Figure 4B) or a cumulative risk of death plot (Figure 4C). Survival analysis, Cox proportional hazards analysis, and the &#8220;survival&#8221; package in R are described in more detail by Christensen12 and at https://cran.r-project.org/web/packages/survival/survival.pdf.
By adapting the procedures outlined here, a variety of neuronal features can be related to survival. Generation of an ROI around the cell body and/or nucleus enables the user to longitudinally monitor cell size and morphology, protein expression level and localization, or the formation of subcellular structures such as puncta or protein aggregates13,14,15,16,17,18,19. Importantly, because each of these factors is observed in relation to cell death, it is possible to quantitatively determine how well individual factors predict cellular survival or death during the given time frame. Protein metabolism and cellular pathways may also be assayed by expressing fluorescent reporters that provide real-time measurements of underlying cellular physiology (e.g., gCaMP6f to assay activity). By employing this powerful approach, factors that drive cellular maintenance, function, and dysfunction can be uncovered and studied in detail, thereby inspiring new avenues of inquiry.

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

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 time course for 3 representative neurons, two of which die during the course of the experiment (Neurons 1 and 2) while the third survives (Neuron 3).
Survival data were analyzed using the R script provided (survival.R), and the results summarized in Figure 4. The table generated upon running lines 7 and 8 of the survival.R code provides a summary of the Cox proportional hazards analysis. Four particularly important statistics in the table are highlighted in Figure 4A. The number in Box 1 represents the hazard ratio for the group &#34;Mutant&#34; relative to &#34;WT&#34;. Notice that the &#34;WT&#34; group is not listed. This is because the &#34;WT&#34; group serves as the reference population - the risk of death observed in all other groups is compared to that of the reference population to calculate the hazard ratio. Therefore, hazard ratios greater than 1 indicate a faster rate of death in comparison to the reference population, and values less than 1 represent a reduced rate of death. In the example provided, mutant cells display a hazard ratio of 2.2, meaning that they died 2.2x faster than WT cells. By default, R will arrange the groups in alphanumeric order, with the top group serving as the reference population. Placing numbers in front of group names is an easy way to establish the order in which they are evaluated. The values in Boxes 2 and 3 represent the p-values and 95% confidence intervals for the hazard ratios, respectively, calculated by Cox proportional hazards analysis. In Box 4, the results of the log-rank test are reported. This test evaluates whether there is a statistically significant difference in survival among populations being tested, but does not describe which groups are different from the others, and does not calculate a magnitude for the observed difference.
Kaplan-Meier curves (Figure 4B) are widely used in clinical trials for evaluating the effects of an intervention on patient survival. For this reason, many researchers are familiar with interpreting survival data visualized this way. In the context of single-cell survival, these plots depict the fraction of cells alive over time in each group. Rather than plotting cell survival, an alternative approach is to depict the rate of cell death in each group via a cumulative risk of death plot (Figure 4C). In most survival studies, the number of events does not follow a linear progression; rather, for a given rate of death a greater number of events is observed at earlier times. For example, in a population of 100 cells, if 20% of cells die between intervals, then 20 cells will die within the first interval, 16 during the second interval, 13 during the third interval, and so on. This logarithmic trend is conceptually easier to visualize using cumulative risk of death plots, since the y-axis represents the negative log transform of cellular survival. Alternatively, the y-axis of the cumulative risk of death plot can also be presented as % cell death, calculated as 1-1/ecumulative risk of death. These plots also enable straightforward comparisons of the risk of death between populations. The magnitude of the hazard ratio reflects the slope of the cumulative risk of death plot for each population, relative to that of the reference group.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59036/59036fig1.jpg" /> 
Figure 1: Schema for a typical survival experiment. Rat cortical neurons are transfected at DIV4 using the procedure outlined in this article. Beginning 24 h post-transfection, cells are imaged at regularly spaced intervals in accordance with the specific requirements of the experiment. Images are stitched and stacked before cell death is scored, and Cox proportional hazard analysis is used to compare the risk of death between populations. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59036/59036fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59036/59036fig2.jpg" /> 
Figure 2: Required file structure. The provided FIJI&#160;macro requires that the raw data are formatted in a specific way. To utilize Image_Processing, organize the raw data as shown on the left. An example experiment and accompanying file structure is shown on the right. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59036/59036fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59036/59036fig3.jpg" /> 
Figure 3: Scoring cell death in transfected rat cortical neurons. Using the methods described in this article, rat cortical neurons were transfected with a plasmid encoding the fluorescent protein mApple. Cells were then imaged approximately every 24 h, the images were stitched and stacked, and cell death scored using the criteria provided. Cell death is indicated for Neuron 1 at 69 h, as evidenced by loss of fluorescence. Neuron 2 dies at 188 h, as indicated by fragmentation of the processes and rounding of the cell body. Neuron 3 survives for the duration of the experiment. Note that some cells become visible only late in the experiment, as evidenced by the appearance of a new cell at 235 h. Only cells that are visible at the initial time of imaging are included within subsequent analyses. Scale bar = 50 &#181;m. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59036/59036fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/59036/59036fig4.jpg" /> 
Figure 4: Interpretation of Cox proportional hazard analysis. (A) The output summary includes four important statistics that are highlighted in this figure. Box 1 includes the hazard ratio of the experimental group relative to the control group, while Box 2 and Box 3 show the p-values and 95% confidence interval for each hazard ratio, respectively. Box 4 highlights the results of the log-rank test. These data are also depicted via a Kaplan-Meier curve (B) and a cumulative risk of death plot (C). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59036/59036fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental File 1.&#160;<a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59036/Supplemental_File_1_Example_Transfection_Sheet.xlsx">Please click here to download this file.</a>
Supplemental File 2.&#160;<a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59036/Supplemental_File_2_Image_Processing.ijm">Please click here to download this file.</a>
Supplemental File 3.&#160;<a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59036/Supplemental_File_3_Survival_spreadsheet.csv">Please click here to download this file.</a>
Supplemental File 4.&#160;<a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/59036/Supplemental_File_4_survival.R">Please click here to download this file.</a>

Watch this Scientific Journal Video about Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy at JoVE.com

Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy

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 ...

monitoring-neuronal-survival-via-longitudinal-fluorescence-microscopy

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Survival Analysis

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6.1K 조회수.  University of Michigan School of Medicine. Here, we present a protocol to monitor survival on a single-cell basis and identify variables that significantly predict cell death.

비디오: Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy

Long-term Live-cell Imaging to Assess Cell Fate in Response to Paclitaxel

Live-cell imaging is a powerful technique that can be used to directly visualize biological phenomena in single cells over extended periods of time. Over the past decade, new and innovative technologies have greatly enhanced the practicality of live-cell imaging. Cells can now be kept in focus and continuously imaged over several days while maintained under 37 &#176;C and 5% CO2 cell culture conditions. Moreover, multiple fields of view representing different experimental conditions can be acquired simultaneously, thus providing high-throughput experimental data. Live-cell imaging provides a significant advantage over fixed-cell imaging by allowing for the direct visualization and temporal quantitation of dynamic cellular events. Live-cell imaging can also identify variation in the behavior of single cells that would otherwise have been missed using population-based assays. Here, we describe live-cell imaging protocols to assess cell fate decisions following treatment with the anti-mitotic drug paclitaxel. We demonstrate methods to visualize whether mitotically arrested cells die directly from mitosis or slip back into interphase. We also describe how the fluorescent ubiquitination-based cell cycle indicator (FUCCI) system can be used to assess the fraction of interphase cells born from mitotic slippage that are capable of re-entering the cell cycle. Finally, we describe a live-cell imaging method to identify nuclear envelope rupture events.

Live-cell imaging provides a wealth of information on single cells or whole populations that is unattainable by fixed cell imaging alone. Here, live-cell imaging protocols to assess cell fate decisions following treatment with the anti-mitotic drug paclitaxel are described.

장기 라이브 셀 이미징 셀 운명 Paclitaxel에 대 한 응답에서을 평가 하

Live-cell imaging is a powerful technique that can be used to directly visualize biological phenomena in single cells over extended periods of time. Over ...

연구

암 연구학

Neuromodulation and Mitochondrial Transport: Live Imaging in Hippocampal Neurons over Long Durations

To understand the relationship between mitochondrial transport and neuronal function, it is critical to observe mitochondrial behavior in live cultured neurons for extended durations1-3. This is now possible through the use of vital dyes and fluorescent proteins with which cytoskeletal components, organelles, and other structures in living cells can be labeled and then visualized via dynamic fluorescence microscopy. For example, in embryonic chicken sympathetic neurons, mitochondrial movement was characterized using the vital dye rhodamine 1234. In another study, mitochondria were visualized in rat forebrain neurons by transfection of mitochondrially targeted eYFP5. However, imaging of primary neurons over minutes, hours, or even days presents a number of issues. Foremost among these are: 1) maintenance of culture conditions such as temperature, humidity, and pH during long imaging sessions; 2) a strong, stable fluorescent signal to assure both the quality of acquired images and accurate measurement of signal intensity during image analysis; and 3) limiting exposure times during image acquisition to minimize photobleaching and avoid phototoxicity.
Here, we describe a protocol that permits the observation, visualization, and analysis of mitochondrial movement in cultured hippocampal neurons with high temporal resolution and under optimal life support conditions. We have constructed an affordable stage-top incubator that provides good temperature regulation and atmospheric gas flow, and also limits the degree of media evaporation, assuring stable pH and osmolarity. This incubator is connected, via inlet and outlet hoses, to a standard tissue culture incubator, which provides constant humidity levels and an atmosphere of 5-10% CO2/air. This design offers a cost-effective alternative to significantly more expensive microscope incubators that don't necessarily assure the viability of cells over many hours or even days. To visualize mitochondria, we infect cells with a lentivirus encoding a red fluorescent protein that is targeted to the mitochondrion. This assures a strong and persistent signal, which, in conjunction with the use of a stable xenon light source, allows us to limit exposure times during image acquisition and all but precludes photobleaching and phototoxicity. Two injection ports on the top of the stage-top incubator allow the acute administration of neurotransmitters and other reagents intended to modulate mitochondrial movement. In sum, lentivirus-mediated expression of an organelle-targeted red fluorescent protein and the combination of our stage-top incubator, a conventional inverted fluorescence microscope, CCD camera, and xenon light source allow us to acquire time-lapse images of mitochondrial transport in living neurons over longer durations than those possible in studies deploying conventional vital dyes and off-the-shelf life support systems.

We describe a protocol that allows imaging of mitochondria in living neurons via fluorescence microscopy over long durations. Imaging over extended periods is accomplished through lentivirus-mediated expression of a mitochondrially targeted fluorescent protein and use of an inexpensive stage-top incubator that was designed and built in our laboratory.

Neuromodulation 및 Mitochondrial 교통 : 긴 기간이 이상 Hippocampal 뉴런의 라이브 영상

To understand the relationship between mitochondrial transport and neuronal function, it is critical to observe mitochondrial behavior in live cultured ...

신경과학

Light Sheet-based Fluorescence Microscopy of Living or Fixed and Stained Tribolium castaneum Embryos

The red flour beetle Tribolium castaneum has become an important insect model organism in developmental genetics and evolutionary developmental biology. The observation of Tribolium embryos with light sheet-based fluorescence microscopy has multiple advantages over conventional widefield and confocal fluorescence microscopy. Due to the unique properties of a light sheet-based microscope, three dimensional images of living specimens can be recorded with high signal-to-noise ratios and significantly reduced photo-bleaching as well as photo-toxicity along multiple directions over periods that last several days. With more than four years of methodological development and a continuous increase of data, the time seems appropriate to establish standard operating procedures for the usage of light sheet technology in the Tribolium community as well as in the insect community at large. This protocol describes three mounting techniques suitable for different purposes, presents two novel custom-made transgenic Tribolium lines appropriate for long-term live imaging, suggests five fluorescent dyes to label intracellular structures of fixed embryos and provides information on data post-processing for the timely evaluation of the recorded data. Representative results concentrate on long-term live imaging, optical sectioning and the observation of the same embryo along multiple directions. The respective datasets are provided as a downloadable resource. Finally, the protocol discusses quality controls for live imaging assays, current limitations and the applicability of the outlined procedures to other insect species.
This protocol is primarily intended for developmental biologists who seek imaging solutions that outperform standard laboratory equipment. It promotes the continuous attempt to close the gap between the technically orientated laboratories/communities, which develop and refine microscopy methodologically, and the life science laboratories/communities, which require 'plug-and-play' solutions to technical challenges. Furthermore, it supports an axiomatic approach that moves the biological questions into the center of attention.

Light Sheet-based Fluorescence Microscopy of Living or Fixed and Stained Tribolium castaneum Embryos

Imaging the morphogenesis of insect embryos with light sheet-based fluorescence microscopy has become state of the art. This protocol outlines and compares three mounting techniques appropriate for Tribolium castaneum embryos, introduces two novel custom-made transgenic lines well suited for live imaging, discusses essential quality controls and indicates current experimental limitations.

라이트 시트 기반의 형광 생활의 현미경 또는 고정 및 스테인드<em&gt; Tribolium castaneum</em&gt; 배아

The red flour beetle Tribolium castaneum has become an important insect model organism in developmental genetics and evolutionary developmental biology. ...

발생학

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

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

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

교양 뉴런의 막 단백질의 측면 보급과 Exocytosis은 형광 복구 및 형광 손실 Photobleaching를 사용하여 평가

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

High-resolution Live Imaging of Cell Behavior in the Developing Neuroepithelium

The embryonic spinal cord consists of cycling neural progenitor cells that give rise to a large percentage of the neuronal and glial cells of the central nervous system (CNS). Although much is known about the molecular mechanisms that pattern the spinal cord and elicit neuronal differentiation1, 2, we lack a deep understanding of these early events at the level of cell behavior. It is thus critical to study the behavior of neural progenitors in real time as they undergo neurogenesis.
In the past, real-time imaging of early embryonic tissue has been limited by cell/tissue viability in culture as well as the phototoxic effects of fluorescent imaging. Here we present a novel assay for imaging such tissue for long periods of time, utilizing a novel ex vivo slice culture protocol and wide-field fluorescence microscopy (Fig. 1). This approach achieves long-term time-lapse monitoring of chick embryonic spinal cord progenitor cells with high spatial and temporal resolution.
This assay may be modified to image a range of embryonic tissues3, 4 In addition to the observation of cellular and sub-cellular behaviors, the development of novel and highly sensitive reporters for gene activity (for example, Notch signaling5) makes this assay a powerful tool with which to understand how signaling regulates cell behavior during embryonic development.

Imaging embryonic tissue in real-time is challenging over long periods of time. Here we present an assay for monitoring cellular and sub-cellular changes in chick spinal cord for long periods with high spatial and temporal resolution. This technique can be adapted for other regions of the nervous system and developing embryo.

개발 Neuroepithelium의 세포 문제의 고해상도 라이브 영상

The embryonic spinal cord consists of cycling neural progenitor cells that give rise to a large percentage of the neuronal and glial cells of the central ...

An Enhanced Green Fluorescence Protein-based Assay for Studying Neurite Outgrowth in Primary Neurons

Neurite outgrowth is a fundamental event in the formation of the neural circuits during nervous system development. Severe neurite damage and synaptic dysfunction occur in various neurodegenerative diseases and age-related degeneration. Investigation of the mechanisms that regulate neurite outgrowth would not only shed valuable light on brain developmental processes but also on such neurological disorders. Due to the low transfection efficiency, it is currently challenging to study the effect of a specific protein on neurite outgrowth in primary mammalian neurons. Here, we describe a simple method for the investigation of neurite outgrowth by the co-transfection of primary rat cortical neurons with EGFP and a protein of interest (POI). This method allows the identification of POI transfected neurons through the EGFP signal, and thus the effect of the POI on neurite outgrowth can be determined precisely. This EGFP-based assay provides a convenient approach for the investigation of pathways regulating neurite outgrowth.

In this report, we describe a simple protocol for studying neurite outgrowth in embryonic rat cortical neurons by co-transfecting with EGFP and the protein of interest.

1 차적인 뉴런에 있는 Neurite 파생을 공부를 위한 향상된 녹색 형광 단백질 기지를 둔 분석

Neurite outgrowth is a fundamental event in the formation of the neural circuits during nervous system development. Severe neurite damage and synaptic ...

Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations

Understanding the mechanisms that control critical biological events of neural cell populations, such as proliferation, differentiation, or cell fate decisions, will be crucial to design therapeutic strategies for many diseases affecting the nervous system. Current methods to track cell populations rely on their final outcomes in still images and they generally fail to provide sufficient temporal resolution to identify behavioral features in single cells. Moreover, variations in cell death, behavioral heterogeneity within a cell population, dilution, spreading, or the low efficiency of the markers used to analyze cells are all important handicaps that will lead to incomplete or incorrect read-outs of the results. Conversely, performing live imaging and single cell tracking under appropriate conditions represents a powerful tool to monitor each of these events. Here, a time-lapse video-microscopy protocol, followed by post-processing, is described to track neural populations with single cell resolution, employing specific software. The methods described enable researchers to address essential questions regarding the cell biology and lineage progression of distinct neural populations.

A robust protocol to monitor neural populations by time-lapse video-microscopy followed by software-based post-processing is described. This method represents a powerful tool to identify biological events in a selected population during live imaging experiments.

영상 모니터 세포 생물학과 여러 신경 인구의 계보 진행을 추적 하는 단일 셀 다음 라이브

Understanding the mechanisms that control critical biological events of neural cell populations, such as proliferation, differentiation, or cell fate ...

Modified Roller Tube Method for Precisely Localized and Repetitive Intermittent Imaging During Long-term Culture of Brain Slices in an Enclosed System

Cultured rodent brain slices are useful for studying the cellular and molecular behavior of neurons and glia in an environment that maintains many of their normal in vivo interactions. Slices obtained from a variety of transgenic mouse lines or use of viral vectors for expression of fluorescently tagged proteins or reporters in wild type brain slices allow for high-resolution imaging by fluorescence microscopy. Although several methods have been developed for imaging brain slices, combining slice culture with the ability to perform repetitive high-resolution imaging of specific cells in live slices over long time periods has posed problems. This is especially true when viral vectors are used for expression of exogenous proteins since this is best done in a closed system to protect users and prevent cross contamination. Simple modifications made to the roller tube brain slice culture method that allow for repetitive high-resolution imaging of slices over many weeks in an enclosed system are reported. Culturing slices on photoetched coverslips permits the use of fiducial marks to rapidly and precisely reposition the stage to image the identical field over time before and after different treatments. Examples are shown for the use of this method combined with specific neuronal staining and expression to observe changes in hippocampal slice architecture, viral-mediated neuronal expression of fluorescent proteins, and the development of cofilin pathology, which was previously observed in the hippocampus of Alzheimer's disease (AD) in response to slice treatment with oligomers of amyloid-&#946; (A&#946;) peptide.

Presented here is a modified roller tube method for culturing and intermittent high-resolution imaging of rodent brain slices over many weeks with precise repositioning on photoetched coverslips. Neuronal viability and slice morphology are well maintained. Applications of this fully enclosed system using viruses for cell-type specific expression are provided.

정확 하 게 지역화 하 고 반복적인 뇌 조각 동봉 된 시스템에서의 장기적인 문화 중 간헐적인 이미징 수정된 롤러 튜브 메서드

Cultured rodent brain slices are useful for studying the cellular and molecular behavior of neurons and glia in an environment that maintains many of ...

Imaging and Analysis of Neurofilament Transport in Excised Mouse Tibial Nerve

Neurofilament protein polymers move along axons in the slow component of axonal transport at average speeds of ~0.35-3.5 mm/day. Until recently the study of this movement in situ was only possible using radioisotopic pulse-labeling, which permits analysis of axonal transport in whole nerves with a temporal resolution of days and a spatial resolution of millimeters. To study neurofilament transport in situ with higher temporal and spatial resolution, we developed a hThy1-paGFP-NFM transgenic mouse that expresses neurofilament protein M tagged with photoactivatable GFP in neurons. Here we describe fluorescence photoactivation pulse-escape and pulse-spread methods to analyze neurofilament transport in single myelinated axons of tibial nerves from these mice ex vivo. Isolated nerve segments are maintained on the microscope stage by perfusion with oxygenated saline and imaged by spinning disk confocal fluorescence microscopy. Violet light is used to activate the fluorescence in a short axonal window. The fluorescence in the activated and flanking regions is analyzed over time, permitting the study of neurofilament transport with temporal and spatial resolution on the order of minutes&#160;and microns, respectively. Mathematical modeling can be used to extract kinetic parameters of neurofilament transport including the velocity, directional bias and pausing behavior from the resulting data. The pulse-escape and pulse-spread methods can also be adapted to visualize neurofilament transport in other nerves. With the development of additional transgenic mice, these methods could also be used to image and analyze the axonal transport of other cytoskeletal and cytosolic proteins in axons.

We describe fluorescence photoactivation methods to analyze the axonal transport of neurofilaments in single myelinated axons of peripheral nerves from transgenic mice that express a photoactivatable neurofilament protein.

절제된 마우스 티비알 신경에 있는 신경필라멘트 수송의 화상 진찰 그리고 분석

Neurofilament protein polymers move along axons in the slow component of axonal transport at average speeds of ~0.35-3.5 mm/day. Until recently the study ...

A Scalable Method to Study Neuronal Survival in Primary Neuronal Culture with Single-cell and Real-Time Resolution

Neuronal loss is at the core of many neuropathologies, including stroke, Alzheimer's disease, and Parkinson's disease. Different methods were developed to study the process of neuronal survival upon cytotoxic stress. Most methods are based on biochemical approaches that do not allow single-cell resolution or involve complex and costly methodologies. Presented here is a versatile, inexpensive, and effective experimental paradigm to study neuronal survival. This method takes advantage of sparse fluorescent labeling of the neurons followed by live imaging and automated quantification. To this aim, the neurons are electroporated to express fluorescent markers and co-cultured with non-electroporated neurons to easily regulate cell density and increase survival. 
Sparse labeling by electroporation allows a simple and robust automated quantification. In addition, fluorescent labeling can be combined with the co-expression of a gene of interest to study specific molecular pathways. Here, we present a model of stroke as a neurotoxic model, namely, the oxygen-glucose deprivation (OGD) assay, which was performed in an affordable and robust homemade hypoxic chamber. Finally, two different workflows are described using IN Cell Analyzer 2200 or the open-source ImageJ for image analysis for semi-automatic data processing. This workflow can be easily adapted to different experimental models of toxicity and scaled up for high-throughput screening. In conclusion, the described protocol provides an approachable, affordable, and effective in vitro model of neurotoxicity, which can be suitable for testing the roles of specific genes and pathways in live imaging and for high-throughput drug screening.

Here, we present a simple, potent, and versatile methodology to investigate neuronal survival upon cytotoxic stress in primary cortical neurons with cellular resolution in real time or in fixed material.

Neuronal loss is at the core of many neuropathologies, including stroke, Alzheimer's disease, and Parkinson's disease. Different methods were developed to ...