The authors acknowledge funding from the DFG (EXC-1003 to MG).

1. Cell Culture
<ol>
	<li>Culture HeLa or COS cells in Dulbecco&#39;s Modified Eagle Medium (DMEM) containing 4.5 g/L D-glucose, L-alanine-L-glutamine dipeptide, pyruvate, 10% fetal bovine serum, and 10 units/ml of penicillin/streptomycin. Culture neurons in culture-media without L-glutamine, glutamic acid or aspartic acid, supplemented with 0.5 mM L-alanine-L-glutamine dipeptide, serum-free neuronal supplements and 10 units/ml of penicillin/streptomycin.</li>
	<li>Once 40% confluency is reached, transfect cells with constructs of choice using a transfection reagent as per manufacturer&#39;s instructions. Keep transfected cells in incubator at 37 &#176;C and 5% CO2 for 15-18 h.</li>
	<li>To reduce changes in pH and osmolarity (due to evaporation) during image acquisition, fill the cell culture chambers (prior to imaging) up to 90 % with 37 &#176;C pre-warmed medium containing 20 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES). To seal the lid, apply a thin layer of vacuum grease on the inside of the lid and gently press it on the culture chamber containing the transfected cells.</li>
</ol>
2. Image Acquisition
NOTE: The length of filopodia varies from 2-10 &#181;m 13. Filopodia grow at an average velocity of 0.05-0.1 &#181;m/s 13,14.
<ol>
	<li>Acquire images using a microscope with 60X or 100X objective and no pixel binning (here, a spinning disc confocal microscope). Use acquisition-rates greater than 1 Hertz (Hz) to track filopodial dynamics. To minimize out-of-focus artifacts, image filopodia close to the basal membrane (i.e. substrate surface).</li>
	<li>To assure smooth tracking, adjust the exposure time of the camera and laser intensity such that the signal to noise ratio (SNR) is greater than 4. Avoid saturation of individual channels (i.e. pixel values of 255 for 8-bit images and 65,535 for 16-bit images), as this will preclude subsequent image analysis.</li>
	<li>To avoid bleed-through, only use fluorescence tags compatible with laser lines and filters of the microscope (for details see reference 15).</li>
</ol>
3. Image Pre-processing
NOTE: Use ImageJ or other available software to pre-process images 16,17.
<ol>
	<li>If the sample is moving, correct for lateral drift using available software (e.g. https://github.com/NMSchneider/fixTranslation-Macro_for_ImageJ) prior to analysis. Exclude movies with axial drift (i.e. movement in z-direction).</li>
	<li>Correct background (i.e. grey values of areas outside of the cell), bleaching (i.e. continuous loss if fluorescence intensity due to damage to fluorescence proteins) and possible bleed-trough (i.e. signal from one fluorescence probe in the both channels) using available software (e.g. http://imagej.net/Category:Plugins and 16,17). 
	Note: Fluorescence intensities of individual channels are not altered by the software.</li>
	<li>To ensure subsequent image analysis, save movies corresponding to particular protein channels in grey scale as &#39;.tiff&#39; stacked file format in the work folder. 
	NOTE: The dimensions (i.e. size, length) of the stacks must be same for all channels.</li>
</ol>
4. Image Analysis &#8211; Step 1: Load Images
NOTE: The software described here was written in Matlab (referred to as programming software) and will run only with this program.
<ol>
	<li>Download the zipped folder containing all required files for image analysis from the following site:&#160;https://campus.uni-muenster.de/en/einrichtungen/impb0/nanoscale-forces-in-cells/software/. Unzip and copy files into the work folder.</li>
	<li>Once installed, open the programming software and run &#39;filopodiaAnalysisM3.fig&#39;. GUI Window #1 will open as shown in Figure 2A.</li>
	<li>Load the saved stacked &#39;.tiff&#39; files corresponding to a particular protein of interest in GUI Window #1 using the buttons &#60;1b&#62; for protein A, &#60;1c&#62; for protein B, &#60;1d&#62; for protein C. See Figure 2 and Table 1 for details. 
	NOTE: Protein A shown in GUI Window #1 acts as the reference channel for the final ratiometric analysis.</li>
	<li>Create a superimposed image of the cell from the protein channels by clicking &#60;1a&#62;.</li>
	<li>Click on &#60;2a&#62; to assign the first frame and &#60;2b&#62; for the last frame used for analysis.</li>
	<li>Optionally, crop the region of interest (ROI) containing the filopodium of interest using button &#60;2h&#62;, rotate the image using button &#60;2i&#62;, or delete unwanted regions using the free-hand drawing tool &#60;2j&#62;. 
	NOTE: To streamline image analysis, it is recommended to isolate the ROI (i.e. crop, rotate, delete) together with the other preprocessing steps (background subtraction, bleach corrections, etc.) using ImageJ.</li>
	<li>Move the slider &#60;2c&#62; for each frame for quality control and to check whether the filopodium remains clearly visible throughout the whole movie.</li>
</ol>
5. Image Analysis &#8211; Step 2: Generate Trace
<ol>
	<li>Click on button &#60;3a&#62; in the GUI Window #1 to open GUI Window #2 (see Figure 2B).</li>
	<li>Click on button &#60;4&#62; in the GUI Window #2 to generate the mask of the superimposed cell body (generated in GUI Window #1 after clicking &#60;1a&#62;). The program also generates the boundary of the mask, where the convex hull is implemented to get the vertex points.</li>
	<li>Click button &#60;5&#62;; a cursor will appear. Use the cursor to select the base (from where the distance of the filopodial tip is measured) followed by the tip of the filopodia in the frame where it first appears. To do this, move the slider in Window #2). 
	NOTE: To minimize errors in data output, place the base point vertically below the filopodial tip along the axis. Positioning the base point on other places (e.g. laterally shifted) may introduce a directional bias in fluorescence values within the cell body.</li>
	<li>Select the threshold length (above which the filopodia will bend) using &#60;6c&#62;. 
	Note: This length is defined as the distance between the base point (selected using &#60;5&#62;) and the boundary of the cell body (i.e. the region from where the filopodia starts growing). The distance is measured is in pixels.</li>
	<li>Specify the number of segments used to approximate the shape of the filopodia in box &#60;6a&#62;. 
	NOTE: The minimum number of segments depends on the maximal length reached by the filopodium, but also how the filopodium bends. Do not select a number of segments larger than the number of pixel between the base and the tip (i.e. the threshold length). Selecting more segments than the threshold length defined in step 5.4. (i.e. number of pixels between base and tip) will result in an overestimation of the length of the filopodium.</li>
	<li>Specify the scan width, which acts as horizontal scanner to place the nodes, in &#60;6b&#62;. 
	NOTE: These nodes are used by the program to fit the line joining the base and the tip with the body of the filopodium (i.e. to create the backbone). As a starting point, put a value in pixels equal to the maximum length multiplied by a factor of <img alt="Equation" src="/files/ftp_upload/55653/55653eq1.jpg" />.</li>
	<li>Specify the scan radius (in pixels) in box &#60;6d&#62;. Use a value that is approximately 50% larger than the observed inter-frame tip displacement. 
	NOTE: Using a very large scan radius might grab unwanted convex-hull points in frames where no real filopodial tip is present (e.g. out of plane movement or low SNR).</li>
	<li>Specify the bending angle in box &#60;6e&#62;. 
	NOTE: The angle threshold is determined by the maximum angle the filopodium is bending during the whole analysis. Specifying the angle threshold helps the software to exclude tracking of unwanted structures growing from the side of the filopodia when the filopodia bends towards the cell body. The program works reliably for filopodia with tilting angles less than 45 degrees from the vertical axis.</li>
	<li>To start tracking, click the &#60;Track&#38;Analyze&#62; button in GUI Window #2. Click the &#39;History trace&#39; box in GUI Window #2 to save the whole tracking protocol for future reference. 
	NOTE: After the tracking procedure is complete, the length of the filopodium in each frame is stored in the sheet named &#39;length_vel&#39; of &#39;dynamics.xlsx&#39; for future references. Likewise, all other tracking parameters are stored in the sheet named &#39;parameters&#39; of &#39;dynamics.xlsx&#39;.</li>
	<li>Optionally, if the filopodia is not automatically detected in all frames, use the following steps to manually correct for it.
	<ol>
		<li>Visit the respective frame using the slider in Window #2 and manually select the tip of the filopodium. 
		Note: Frames, where no convex hull points are detected will be represented by a blue region in the tracking window of GUI Window #2. It is mandatory to check the &#39;History trace&#39; button before the tracking program was initiated for accessing the nodal coordinates in that frame.</li>
		<li>Select the reference points (base followed by tip) using &#60;6f&#62; in GUI Window #2. Specify the other parameters such as &#39;scan length&#39;, &#39;Accurate Measurement after&#39;, and &#39;maximum bending angle&#39; for that frame as described in steps 5.4-5.8.</li>
		<li>Click button &#60;6i&#62; to save the new parameters (specific to that one frame). The steps are to be repeated for all frames indicated by the blue region.</li>
		<li>When finished, re-initialize the tracking procedure using &#60;7&#62;. 
		NOTE: This correction can also be used if the program suddenly switches from one filopodial to another within a movie. As an alternative, consider cropping movies that contain multiple filopodia.</li>
	</ol>
	</li>
</ol>
6. Image Analysis &#8211; Step 3: Spatio-temporal Protein Analysis
<ol>
	<li>For spatio-temporal analysis, select the box represented by &#60;8b&#62; followed by the protein channel of interest (&#60;8c&#62; and/or &#60;8d&#62; and/or &#60;8e&#62;). 
	Note: It is mandatory to select Protein A prior to ratiometric analysis (&#60;9a&#62;, &#60;9b&#62; and/or &#60;9c&#62;) since Protein A is used as reference.</li>
	<li>Click on &#60;8a&#62; to initiate protein tracking along the filopodial length using the trace generated in step 5.9.</li>
</ol>
7. Image Analysis &#8211; Step 4: Ratio-metric Protein Analysis
<ol>
	<li>Check box &#60;9b&#62; or &#60;9c&#62; and click on the button &#60;9a&#62; to get the spatio-temporal ratiometric plot. 
	NOTE: To avoid misrepresentation of relative protein concentration, the ratiometric image is not plotted as X/Y but as log(X/Y). For future use, the ratiometric plot is exported in &#39;.png&#39; and &#39;.fig&#39; format files, and raw plot data is stored within the &#39;dynamics.xlsx&#39; file.</li>
</ol>
8. Image Analysis &#8211; Step 5: Filopodial Tip Analysis
<ol>
	<li>Check box &#60;8f&#62; and specify the tip length and threshold length from the base using &#60;8g&#62; and &#60;8h&#62;. Click on &#60;push button&#62; to save data to file &#39;dynamics.xlsx&#39;. Click on &#60;Analyze Protein Intensities&#62; to generate the trace of protein intensities of the filopodial tip and to save for ratiometric analysis. 
	NOTE: Tip length determines the number of pixels at the tip used for the analysis. The software will return the average intensity value of the pixels at the tip over each frame. The threshold length determines the minimum distance from the base to tip above which the filopodium (filopodial tip) starts growing (and when the program starts tracking the intensity value of the tip). So the tip length must be smaller than the threshold length.</li>
	<li>Click on the desired ratio to be analyzed using &#60;9d&#62; or &#60;9e&#62;.</li>
	<li>Click on the compare button &#60;9a&#62; to generate the ratiometric data.</li>
</ol>

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The authors have nothing to disclose.

Here we present a detailed protocol for tracking filopodial growth dynamics and analysis of relative protein concentrations in these dynamic structures via the convex-hull algorithm. Using the software, up to 3 channels can be compared pair-wise in a single run, whereby the relative concentrations of two channels (i.e. proteins) is determined throughout the extension/retraction cycle and stored as image and data files in separate folders. In addition to the routine operations, the software also provides a number...

Spatio-temporal control of actin regulatory proteins is associated with filopodium dynamics 1,2. Tracking spatially resolved protein concentration along the whole filopodial length through time is thus crucial to advance our understanding of the mechanisms underlying initiation, elongation, stabilization or collapse of these dynamic structures 3,4. Unlike protein analysis in the cytosol, where many cell shape changes occur at a larger scale, filopodia are dynamic micro structures that constantly buckle 5 and bend, thus precluding analysis using a simple approach such as a line-scan.
Different software solutions for tracking filopodial shape are available 6,7,8,9. Likewise, software for ratiometric tracking of protein dynamics within the cell body has been developed 10,11. To combine automated tracking of filopodial shape and spatio-temporal protein analysis, we recently developed an image analysis software based on the convex-hull algorithm 12. This novel analysis method, which is operated via a graphical user interface (GUI), combines for the first time, relative protein concentration along the filopodial length and growth velocity, thus allowing the accurate measurement of spatio-temporal protein distribution independent of movement of these dynamic structures 12.
The idea behind the software (source code is freely available, see below) is that one of the vertices of the convex hull will coincide with the tip of the filopodium (Figure 1A). By looking in the subsequent frame for the nearest vertex of the convex-hull, the moving tip can be tracked throughout the whole movie. Once the tip is detected in each frame, its position is used to draw an axis by joining the tip with a reference point at the base of the filopodium (Figure 1B). Finally, using equidistant nodal points, whose positions are determined by the median pixel with maximum intensity along the line orthogonal to the axis, are used to determine a backbone that follows the filopodial shape. Taking advantage of this adaptive backbone, a kymograph is generated to trace filopodial growth and protein concentrations for up to three channels along the filopodial length (Figure 1C).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55653/55653fig1.jpg" /> 
Figure 1: Working Principle of the Image Analysis Software. (A) The algorithm behind the software. In Step1 the user specifies the reference (base) and the vertex (the tip) of the filopodium. In Step 2-1 the backbone of the filopodium is obtained using the median pixel with maximum intensity value. In Step 3 the backbone is used for spatial protein intensity profile. In Step 2-2 the software automatically tracks the tip in the subsequent frame. The whole procedure iterates. (B) Snapshot of the algorithm with real filopodium introducing important elements such as the convex hull that is being used for tracking. (C) Overview of parameters that can be measured with the algorithm. This figure has been modified from reference 12. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55653/55653fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The image analysis software is operated in Matlab (referred to as programming software) via a graphical user interface. To maximize flexibility and robustness for the particular experimental setting, the user can adjust a series of tracking parameters (e.g. permitted bending angle and inter-frame movement) and also make some corrections to the movies (e.g. cropping, rotation, removal of unwanted objects) (Figure 2A and Table 1).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>GUI</td>
			<td>No.</td>
			<td>Mandatory</td>
			<td colspan="5">Description</td>
			<td>Name (in GUI)</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>1a</td>
			<td>Y</td>
			<td colspan="5">Loading stacked .tiff file representing cell body (with box checked in) or create superimposed cell body from channels</td>
			<td>CellBody</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>1b</td>
			<td>Y</td>
			<td colspan="5">Loading stacked image file corresponding to protein 1</td>
			<td>Protein 1</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>1c</td>
			<td>Y</td>
			<td colspan="5">Loading stacked image file corresponding to protein 2</td>
			<td>Protein 2</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>1d</td>
			<td>Y</td>
			<td colspan="5">Loading stacked image file corresponding to protein 3</td>
			<td>Protein 3</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>1e</td>
			<td>N</td>
			<td colspan="5">Resets everything to preloaded stacked image files</td>
			<td>Reset</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2a</td>
			<td>Y</td>
			<td colspan="5">Scroll bar to determine the initial frame for analysis in GUI window #2</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2b</td>
			<td>Y</td>
			<td colspan="5">Scroll bar to determine the final frame for analysis in GUI window #2</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2c</td>
			<td>Y</td>
			<td colspan="5">Scroll bar representing current frame</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2d</td>
			<td>N</td>
			<td colspan="5">The grey value of the pixels below which all pixels will be set to zero</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2e</td>
			<td>N</td>
			<td colspan="5">The grey value of the pixels above which all pixels will be set to maximum values</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2f</td>
			<td>N</td>
			<td colspan="5">Set the intensity values of the pixels specified by &#60;2e&#62; &#38; &#60;2f&#62;</td>
			<td>Set</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2g</td>
			<td>N</td>
			<td colspan="5">Play the intensity-adjusted movie</td>
			<td>Play</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2h</td>
			<td>N</td>
			<td colspan="5">Crop Image</td>
			<td>Crop</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2i</td>
			<td>N</td>
			<td colspan="5">Rotate Image</td>
			<td>Rotate</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>2j</td>
			<td>N</td>
			<td colspan="5">Delete regions in the whole stack</td>
			<td>Delete regions</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>3a</td>
			<td>Y</td>
			<td colspan="5">Click to open the &#8216;Analysis Window&#8217; (GUI window #2)</td>
			<td>Tracking Window</td>
		</tr>
		<tr>
			<td>#1</td>
			<td>3b</td>
			<td>Y</td>
			<td colspan="5">Enter the size of a pixel in microns</td>
			<td>Enter Pixel size</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>4</td>
			<td>Y</td>
			<td colspan="5">Click to generate the boundary/edge image of the superimposed cell body</td>
			<td>Boundary</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>5</td>
			<td>Y</td>
			<td colspan="5">Click to select the base and tip of the filopodia</td>
			<td>Referernce</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6a</td>
			<td>Y</td>
			<td colspan="5">Enter the number of segments or nodes</td>
			<td>No of segments</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6b</td>
			<td>Y</td>
			<td colspan="5">Enter the scan length (perpendicular to axis)</td>
			<td>Scan Width</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6c</td>
			<td>Y</td>
			<td colspan="5">Enter the length above which filopodia starts bending</td>
			<td>Accurate Meas after</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6d</td>
			<td>Y</td>
			<td colspan="5">Enter the radius of the tip detection circle (i.e. area where the vertex can be localized in the next frame)</td>
			<td>Radius of tip detection</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6e</td>
			<td>Y</td>
			<td colspan="5">Enter the maximum angle the filopodium can bend from the vertical axis</td>
			<td>Angle Threshold</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6f</td>
			<td>N</td>
			<td colspan="5">Add reference points for base and tip for that specific frame</td>
			<td>Select reference</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6g</td>
			<td>N</td>
			<td colspan="5">Enter the length above which filopodia starts bending for that specific frame</td>
			<td>Accurate Meas after</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6h</td>
			<td>N</td>
			<td colspan="5">Enter the radius of the detection circle for that specific frame</td>
			<td>Radius of tip detection</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6i</td>
			<td>N</td>
			<td colspan="5">After entering all the parameters for the specific frame click to store the values to memory and file for further reference</td>
			<td>Add</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6j</td>
			<td>N</td>
			<td colspan="5">Click to delete the set manually parameters for that frame</td>
			<td>Delete</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6k</td>
			<td>N</td>
			<td colspan="5">Click to delete all parameters stored manually using the &#8216;optional features panel&#8217; for all frames</td>
			<td>Reset</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>6l</td>
			<td>N</td>
			<td colspan="5">Check in before tracking to store all tracking results in memory for future reference</td>
			<td>History trace</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>7</td>
			<td>Y</td>
			<td colspan="5">Click to start tracking</td>
			<td>Track&#38;Analyze</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8a</td>
			<td>N</td>
			<td colspan="5">Click to start tracking protein channel intensity</td>
			<td>Analyze Protein Intensities</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8b</td>
			<td>N</td>
			<td colspan="5">Check in to track protein channel intensity along the filopodial length</td>
			<td>Whole filopodia</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8c</td>
			<td>N</td>
			<td colspan="5">Check in for tracking the reference protein or protein A</td>
			<td>ProteinA</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8d</td>
			<td>N</td>
			<td colspan="5">Check in for tracking the protein B</td>
			<td>ProteinB</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8e</td>
			<td>N</td>
			<td colspan="5">Check in for tracking the protein C</td>
			<td>ProteinC</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8f</td>
			<td>N</td>
			<td colspan="5">Check in to track average protein intensity in the tip</td>
			<td>Leading tip</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8g</td>
			<td>N</td>
			<td colspan="5">Enter the length of the tip</td>
			<td>Tip Length</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8h</td>
			<td>N</td>
			<td colspan="5">Enter the minimum distance from base above which the tip starts forming</td>
			<td>threshold</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>8i</td>
			<td>N</td>
			<td colspan="5">Click to save the leading tip analysis results to file</td>
			<td>Push Button</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>9a</td>
			<td>N</td>
			<td colspan="5">Click to initiate ratiometric protein analysis</td>
			<td>Compare</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>9b</td>
			<td>N</td>
			<td colspan="5">Check in to compare protein B with respect to A</td>
			<td>log10(B/A)</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>9c</td>
			<td>N</td>
			<td colspan="5">Check in to compare protein C with respect to A</td>
			<td>log10(C/A)</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>9d</td>
			<td>N</td>
			<td colspan="5">Check in to compare protein B with respect to A at the tip</td>
			<td>log10(B/A)</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>9e</td>
			<td>N</td>
			<td colspan="5">Check in to compare protein C with respect to A at the tip</td>
			<td>log10(C/A)</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>10a</td>
			<td>N</td>
			<td colspan="5">Choose other color-map (default: Jetplot)</td>
			<td>Color Map</td>
		</tr>
		<tr>
			<td>#2</td>
			<td>10b</td>
			<td>N</td>
			<td colspan="5">Edit the colormap</td>
			<td>Edit colormap</td>
		</tr>
	</tbody>
</table>
Table 1: Overview of All Functions Present in the GUI Windows #1 and #2.
Once this is accomplished, the program creates a convex hull and automatically tracks the tip throughout the movie. Parameters extracted from the movie, such as a ratiometric kymograph, growth velocity, and filopodial length are displayed and also stored in the work folder as images and as data files. Other parameters such as filopodial lifetime, growth rate and retraction rate can then be extracted and further analyzed from the stored data files (Figure 2B).
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55653/55653fig2.jpg" /> 
Figure 2: Graphical User Interface for using the Image Analysis Software. (A) GUI Window #1 is used for loading and processing images. The program can load up to 3 protein channels, whereby 2 channels are compared pair-wise. The window comes with mandatory (blue) and optional features (green) for pre-processing the images prior to tracking (B) GUI Window #2 is used for tracking the filopodium as well as spatio-temporal and ratio-metric protein analysis. Again, optional features are marked in green. This figure has been modified from reference 12. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55653/55653fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Here, we present a detailed protocol for sample preparation and software handling. We start with detailed instructions on culturing cells and acquiring movies optimized for image analysis. This section on data acquisition is followed by a detailed description for operating the image analysis software. Throughout the protocol, we introduce critical steps and optional features that should be considered when collecting and processing data. Finally, we analyze filopodia from different model systems with the image analysis software, before closing with a comparison of the described image analysis software with other programs available for filopodial quantification and a discussion on limitations and future direction.

<table border="0" cellpadding="0" cellspacing="0" width="816">
	<tbody>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">DMEM</td>
			<td style="width:204px;">Life Technologies</td>
			<td style="width:204px;">31966-021</td>
			<td style="width:204px;"></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">10% Fetal bovine serum</td>
			<td style="width:204px;">Biochrom AG</td>
			<td style="width:204px;">L11-044</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Lipofectamine 2000</td>
			<td style="width:204px;">Life Technologies</td>
			<td style="width:204px;">11668-027</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">1% penicillin/streptomycin</td>
			<td style="width:204px;">Biochrom AG</td>
			<td style="width:204px;">12212</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Neurobasal Medium</td>
			<td style="width:204px;">Life Technologies</td>
			<td style="width:204px;">21103-049</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">B27</td>
			<td style="width:204px;">Life Technologies</td>
			<td style="width:204px;">17504-044</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">HEPES (1M stock solution)</td>
			<td style="width:204px;">Life Technologies</td>
			<td style="width:204px;">15630</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Citrine-N1</td>
			<td style="width:204px;">Addgene</td>
			<td style="width:204px;">54593</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;">Labtech</td>
			<td>Thermo</td>
			<td>155411</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Glutamax-I</td>
			<td>Thermo</td>
			<td>35050-061</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Hela</td>
			<td>Leibniz Institute DSMZ</td>
			<td>ACC-57</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">COS 7</td>
			<td>Leibniz Institute DSMZ</td>
			<td>ACC-60</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">3T3 cells</td>
			<td>Leibniz Institute DSMZ</td>
			<td>ACC-59</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Microscope</td>
			<td>Nicon Eclipse</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Camera</td>
			<td>Andor</td>
			<td>DU888 Ultra</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Confocal Unit</td>
			<td>Yokagawa</td>
			<td>CSU-X1</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:204px;">Pyruvate</td>
			<td>Gibco</td>
			<td>31966-021</td>
			<td></td>
		</tr>
	</tbody>
</table>

a graphical user interface for software-assisted tracking of protein concentration in dynamic cellular protrusions

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

Using COS cells transfected with a marker for filamentous actin (f-tractin18, red) and a cytosolic reference (green), we found actin-rich filopodial protrusions (Figure 3A, top panel). Time series showed that filopodia rapidly extend and retract (Figure 3A, middle panel). Using the image analysis software, we then traced individual filopodia. Comparison of filopodial length measured by hand vs. the image a...

Watch this Scientific Journal Video about A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions at JoVE.com

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

We present a software solution for semi-automated tracking of relative protein concentration along the length of dynamic cellular protrusions.

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex ...

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Biology

7.3K Views.  University of Muenster. We present a software solution for semi-automated tracking of relative protein concentration along the length of dynamic cellular protrusions.

Video: A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

Application of Light-cured Dental Adhesive Resin for Mounting Electrodes or Microdialysis Probes in Chronic Experiments

In chronic recording experiments, self-curing dental acrylic resins have been used as a mounting base of electrodes or microdialysis-probes. Since these acrylics do not bond to the bone, screws have been used as anchors. However, in small experimental animals like finches or mouse, their craniums are very fragile and can not successfully hold the anchors. In this report, we propose a new application of light-curing dental resins for mounting base of electrodes or microdialysis probes in chronic experiments. This material allows direct bonding to the cranium. Therefore, anchor screws are not required and surgical field can be reduced considerably. Past experiences show that the bonding effect maintains more than 2 months. Conventional resin's window of time when the materials are pliable and workable is a few minutes. However, the window of working time for these dental adhesives is significantly wider and adjustable.

In this report, we propose a new application of light-curing dental resins for mounting base of electrodes or microdialysis probes in chronic experiments. This material allows direct bonding to the cranium.

In chronic recording experiments, self-curing dental acrylic resins have been used as a mounting base of electrodes or microdialysis-probes. Since these ...

Visually Mediated Odor Tracking During Flight in Drosophila

Flying insects use visual cues to stabilize their heading in a wind stream. Many animals additionally track odors carried in the wind. As such, visual stabilization of upwind tracking directly aids in odor tracking. But do olfactory signals directly influence visual tracking behavior independently from wind cues? Additionally, recent advances in olfactory molecular genetics and neurophysiology have motivated novel quantitative behavioral analyses to assess the behavioral influence of (e.g.) genetically inactivating specific olfactory activation circuits. We modified a magnetic tether system originally devised for vision experiments by equipping the arena with narrow laminar flow odor plumes. Here we focus on experiments that can be performed after a fly is tethered and is able to navigate in the magnetic arena. We show how to acquire video images optimized for measuring body angle, how to judge stable odor tracking, and we illustrate two experiments to examine the influence of visual cues on odor tracking.

Here we describe how to optimize the acquired video image for an olfactory magnetic-tether (OMT) apparatus. We also describe two sample experimental protocols for studying visuo-olfactory fusion.

Flying insects use visual cues to stabilize their heading in a wind stream. Many animals additionally track odors carried in the wind. As such, visual ...

Microvolume Protein Concentration Determination using the NanoDrop 2000c Spectrophotometer

Traditional spectrophotometry requires placing samples into cuvettes or capillaries. This is often impractical due to the limited sample volumes often used for protein analysis. The Thermo Scientific NanoDrop 2000c Spectrophotometer solves this issue with an innovative sample retention system that holds microvolume samples between two measurement surfaces using the surface tension properties of liquids, enabling the quantification of samples in volumes as low as 0.5-2 &mu;L. The elimination of cuvettes or capillaries allows real time changes in path length, which reduces the measurement time while greatly increasing the dynamic range of protein concentrations that can be measured. The need for dilutions is also eliminated, and preparations for sample quantification are relatively easy as the measurement surfaces can be simply wiped with laboratory wipe. This video article presents modifications to traditional protein concentration determination methods for quantification of microvolume amounts of protein using A280 absorbance readings or the BCA colorimetric assay.

Microvolume samples are quantified by a spectrophotometer system that uses natural surface tension to retain samples without the use of cuvettes or capillaries. The dynamic range of protein concentrations and speed by which they can be measured are greatly increased with this method.

Traditional spectrophotometry requires placing samples into cuvettes or capillaries. This is often impractical due to the limited sample volumes often ...

Split-Ubiquitin Based Membrane Yeast Two-Hybrid (MYTH) System: A Powerful Tool For Identifying Protein-Protein Interactions

The fundamental biological and clinical importance of integral membrane proteins prompted the development of a yeast-based system for the high-throughput identification of protein-protein interactions (PPI) for full-length transmembrane proteins. To this end, our lab developed the split-ubiquitin based Membrane Yeast Two-Hybrid (MYTH) system. This technology allows for the sensitive detection of transient and stable protein interactions using Saccharomyces cerevisiae as a host organism. MYTH takes advantage of the observation that ubiquitin can be separated into two stable moieties: the C-terminal half of yeast ubiquitin (Cub) and the N-terminal half of the ubiquitin moiety (Nub). In MYTH, this principle is adapted for use as a 'sensor' of protein-protein interactions. Briefly, the integral membrane bait protein is fused to Cub which is linked to an artificial transcription factor. Prey proteins, either in individual or library format, are fused to the Nub moiety. Protein interaction between the bait and prey leads to reconstitution of the ubiquitin moieties, forming a full-length 'pseudo-ubiquitin' molecule. This molecule is in turn recognized by cytosolic deubiquitinating enzymes, resulting in cleavage of the transcription factor, and subsequent induction of reporter gene expression. The system is highly adaptable, and is particularly well-suited to high-throughput screening. It has been successfully employed to investigate interactions using integral membrane proteins from both yeast and other organisms.

Split-Ubiquitin Based Membrane Yeast Two-Hybrid MYTH System: A Powerful Tool For Identifying Protein-Protein Interactions

MYTH allows the sensitive detection of transient and stable interactions between proteins that are expressed in the model organism Saccharomyces cerevisiae. It has been successfully applied to study exogenous and yeast integral membrane proteins in order to identify their interacting partners in a high throughput manner.

The fundamental biological and clinical importance of integral membrane proteins prompted the development of a yeast-based system for the high-throughput ...

The Importance of Correct Protein Concentration for Kinetics and Affinity Determination in Structure-function Analysis 

In this study, we explore the interaction between the bovine cysteine protease inhibitor cystatin B and a catalytically inactive form of papain (Fig. 1), a plant cysteine protease, by real-time label-free analysis using Biacore X100. Several cystatin B variants with point mutations in areas of interaction with papain, are produced. For each cystatin B variant we determine its specific binding concentration using calibration-free concentration analysis (CFCA) and compare the values obtained with total protein concentration as determined by A280. After that, the kinetics of each cystatin B variant binding to papain is measured using single-cycle kinetics (SCK). We show that one of the four cystatin B variants we examine is only partially active for binding. This partial activity, revealed by CFCA, translates to a significant difference in the association rate constant (ka) and affinity (KD), compared to the values calculated using total protein concentration. Using CFCA in combination with kinetic analysis in a structure-function study contributes to obtaining reliable results, and helps to make the right interpretation of the interaction mechanism.

The Importance of Correct Protein Concentration for Kinetics and Affinity Determination in Structure-function Analysis

We apply label-free protein interaction analysis using Biacore X100 for structure-function analysis of the binding of several cystatin B mutants to papain through kinetic characterization. Calibration-free concentration analysis (CFCA) measures the concentration of protein with retained binding activity without the need for a standard curve. We show that confirmation of concentrations using CFCA increases the reliability of the kinetic analysis and that kinetic constants can reliably be determined even if the activity of a recombinant protein is reduced.

In this study, we explore the interaction between the bovine cysteine protease inhibitor cystatin B and a catalytically inactive form of papain (Fig. 1), ...

A Microfluidic Device for Quantifying Bacterial Chemotaxis in Stable Concentration Gradients

Chemotaxis allows bacteria to approach sources of attractant chemicals or to avoid sources of repellent chemicals. Bacteria constantly monitor the concentration of specific chemoeffectors by comparing the current concentration to the concentration detected a few seconds earlier. This comparison determines the net direction of movement. Although multiple, competing gradients often coexist in nature, conventional approaches for investigating bacterial chemotaxis are suboptimal for quantifying migration in response to concentration gradients of attractants and repellents. Here, we describe the development of a microfluidic chemotaxis model for presenting precise and stable concentration gradients of chemoeffectors to bacteria and quantitatively investigating their response to the applied gradient. The device is versatile in that concentration gradients of any desired absolute concentration and gradient strength can be easily generated by diffusive mixing. The device is demonstrated using the response of Escherichia coli RP437 to gradients of amino acids and nickel ions.

This protocol describes the development of a microfluidic device for investigating bacterial chemotaxis in stable concentration gradients of chemoeffectors.

Chemotaxis allows bacteria to approach sources of attractant chemicals or to avoid sources of repellent chemicals. Bacteria constantly monitor the ...

Isolation of Labile Multi-protein Complexes by in vivo Controlled Cellular Cross-Linking and Immuno-magnetic Affinity Chromatography

The dynamic nature of cellular machineries is frequently built on transient and/or weak protein associations. These low affinity interactions preclude stringent methods for the isolation and identification of protein networks around a protein of interest. The use of chemical crosslinkers allows the selective stabilization of labile interactions, thus bypassing biochemical limitations for purification. Here we present a protocol amenable for cells in culture that uses a homobifunctional crosslinker with a spacer arm of 12 &Aring;, dithiobis-(succinimidyl proprionate) (DSP). DSP is cleaved by reduction of a disulphide bond present in the molecule. Cross-linking combined with immunoaffinity chromatography of proteins of interest with magnetic beads allows the isolation of protein complexes that otherwise would not withstand purification. This protocol is compatible with regular western blot techniques and it can be scaled up for protein identification by mass spectrometry1.
Stephanie A. Zlatic and Pearl V. Ryder contributed equally to this work.

Isolation of Labile Multi-protein Complexes by in vivo Controlled Cellular Cross-Linking and Immuno-magnetic Affinity Chromatography

The cell permeable crosslinker DSP [dithiobis-(succinimidyl propionate)] stabilizes transient and labile interactions in vivo, which allows their isolation using stringent protein complex purification techniques. Here we present a technique for crosslinking cells grown in culture followed by isolation of protein complexes by immunoprecipitation.

The dynamic nature of cellular machineries is frequently built on transient and/or weak protein associations. These low affinity interactions preclude ...

Analysis of the Development of a Morphological Phenotype as a Function of Protein Concentration in Budding Yeast

Gene deletion and protein overexpression are common methods for studying functions of proteins. In this article, we describe a protocol for analysis of phenotype development as a function of protein concentration at population and single-cell levels in Saccharomyces cerevisiae. Although this protocol is based on the overexpression of a protein, it can easily be adapted for morphological phenotypes dependent on suppression of protein expression. Our lab is interested in studying the signaling properties of the endocytic adaptor protein epsin. To that purpose we used a dominant negative approach in which we over-expressed the conserved Epsin N-Terminal Homology (ENTH) domain in order to interfere with the functions of endogenous epsin-2 (Ent2 or YLR206W). We observed that overexpression of the ENTH domain of Ent2 (ENTH2) in wild type cells led to a cell division defect that is dependent on the mislocalization of a family of scaffolding proteins, septins.

Gene deletion and protein overexpression are common methods for studying functions of proteins. In this article, we describe a protocol for analysis of phenotype development as a function of protein concentration at population and single-cell levels in Saccharomyces cerevisiae.

Gene deletion and protein overexpression are common methods for studying functions of proteins. In this article, we describe a protocol for analysis of ...

Tracking Morphogenetic Tissue Deformations in the Early Chick Embryo

Embryonic epithelia undergo complex deformations (e.g. bending, twisting, folding, and stretching) to form the primitive organs of the early embryo. Tracking fiducial markers on the surfaces of these cellular sheets is a well-established method for estimating morphogenetic quantities such as growth, contraction, and shear. However, not all surface labeling techniques are readily adaptable to conventional imaging modalities and possess different advantages and limitations. Here, we describe two labeling methods and illustrate the utility of each technique. In the first method, hundreds of fluorescent labels are applied simultaneously to the embryo using magnetic iron particles. These labels are then used to quantity 2-D tissue deformations during morphogenesis. In the second method, polystyrene microspheres are used as contrast agents in non-invasive optical coherence tomography (OCT) imaging to track 3-D tissue deformations. These techniques have been successfully implemented in our lab to studythe physical mechanisms of early head fold, heart, and brain development, and should be adaptable to a wide range morphogenetic processes.

This article describes surface labeling and ex ovo tissue culture in the early chick embryo. Techniques amenable to time-lapse bright field, fluorescence, and optical coherence tomography imaging are presented. Tracking surface labels with high spatiotemporal resolution enables kinematic quantities such as morphogenetic strains (deformations) to be calculated in both two and three dimensions.

Embryonic epithelia undergo complex deformations (e.g. bending, twisting, folding, and stretching) to form the primitive organs of the early embryo. ...

Cell Tracking Using Photoconvertible Proteins During Zebrafish Development

Embryogenesis is a dynamic process that is best studied by using techniques that allow the documentation of developmental changes in vivo. The use of genetically-encoded fluorescent proteins has proven a valuable strategy for elucidating dynamic morphogenetic processes as they occur in the intact organism. During the past decade, the development of photoactivatable and photoconvertible fluorescent proteins has opened the possibility to investigate the fate of discrete subpopulations of tagged proteins1. Unlike photoactivatable proteins, photoconvertible fluorescent proteins (PCFPs) are readily tracked and imaged in their native emission state prior to photoconversion, making it easier to identify and select regions by optical inspection. PCFPs, such as Kaede2, KikGR3, Dendra4 and EosFP5, can be shifted from green to red upon exposure to UV or blue light due to a His-Tyr-Gly tripeptide sequence which forms a green chromophore that can be photoconverted to a red one by a light-catalyzed &beta;-elimination and subsequent extension of a &pi;-conjugated system3. PCFPs and their monomeric variants are useful tools for tracking cells6-10 and studying protein dynamics11-14, respectively. During recent years, PCFPs have been expressed in different animal model, such as zebrafish6, chicken7,8 and mouse9,10 for cell fate tracking. Here we report a protocol for cell-specific photoconversion of PCFPs in the living zebrafish embryo and further tracking of photoconverted proteins at later developmental stages. This methodology allows studying, in a tissue-specific manner, cell biological events underlying morphogenesis in the zebrafish animal model.

Here, we present a method for the photoactivated switch of photoconvertible fluorescent proteins (PCFPs) in the living zebrafish embryo and further tracking of photoconverted protein at specific time points during development. This methodology allows monitoring of cell biological events underlying different developmental processes in a live vertebrate organism.

Embryogenesis is a dynamic process that is best studied by using techniques that allow the documentation of developmental changes in vivo. The use of ...