This research was supported in part by AMED under grant number 21gm0810011h0005 (N.I. and Y.S.), JSPS KAKENHI (JP19H03223, N.I.) and JSPS Grants-in-Aid for Early-Career Scientists (JP19K16258, T.M.), the Osaka Medical Research Foundation for Incurable Diseases (T.M.), and NAIST Next Generation Interdisciplinary Research Project (Y.S.).

The authors have nothing to disclose.

The protocols described in this study use commercially available materials and microscopy equipment routinely found in all the laboratories, institutes, and universities. Therefore, investigators can easily adopt the present single speckle imaging and traction force microscopy in their studies.
The speckle imaging can analyze actin polymerization and clutch coupling. In addition, speckle imaging can monitor the retrograde flow of clutch molecules such as shootin1 and cortactin, which interact with F-actin retrograde flow. By using a TIRF microscope, the retrograde flow of the cell adhesion molecule L1-CAM can also be monitored23,41; L1-CAM undergoes grip and slip behaviors that reflect the clutch coupling efficiency23,41. Although the present study employs the TMR-HaloTag system for speckle imaging, other fluorescent proteins, such as EGFP and monomeric red fluorescent protein, are also available in the analysis16,18,20,23,24,27,39. The essentials for visualizing actin speckles are a low expression level of fluorescent actin and the illumination of a minimum area (Figure 2). In this protocol, Lifeact and HaloTag-actin signals are sequentially acquired. Because actin retrograde flow is relatively slow (4.5 &#177; 0.1 &#181;m/min)24, analysis of F-actin retrograde flow and actin polymerization are unaffected by sequential image acquisition of different fluorescent channels (~1 s interval). Lifeact is a widely-used F-actin marker, but can compete with actin binding proteins47. Of further importance, Lifeact can alter actin dynamics, thereby affecting F-actin structures and the cell morphology47,48,49.
Traction force microscopy can detect forces to drive growth cone advance. By mounting the neurons within an extracellular matrix, investigators can also analyze forces generated in a semi-3D environment11. High-magnification imaging is important for accurate quantification of traction force because growth cones generate weak traction forces7. Although other methods with nanopillars or stress-sensitive biosensors are also used to measure traction force50,51, PAA gel-based method is highly adaptable and allows for the adjustment of substrate rigidity by varying the concentrations of acrylamide and bis-acrylamide41,44,52. In this protocol, the PAA gel is prepared at a final concentration of 3.75% acrylamide and 0.03% bis-acrylamide; Young&#39;s modulus is ~270 Pa22 and this stiffness is within the range of brain tissue (100-10,000 Pa)53,54,55. Due to the thickness of the PAA gel (~100 &#181;m), this method limits the use of high-magnification lenses during microscopy. To obtain high-magnification images, investigators should use the zoom function in a laser scanning confocal microscope.
In conclusion, the present speckle imaging and traction force microscopy enable quantitative analyses of the key events in force generations. This information will be invaluable for improving understanding of the mechanisms that underlie growth cone advancement and navigation.

In the developing vertebrate brain, neurons undergo elaborately organized migrations and project axons toward appropriate synaptic partners to establish functional neuronal networks1,2,3. Growth cones, which are sensory and motile structures located at the tip of neurites, determine the speed and direction of neuronal migration and axon outgrowth3,4,5. Since neurons are surrounded by tightly packed environments, growth cones must exert forces against their environment to move forward6,7. To understand the mechanisms underlying neuronal migration and axonal guidance, analyses of the molecular mechanics for growth cone advance are essential.
Decades of analysis have revealed that traction force to drive growth cone advance is generated by the &#39;clutch&#39; mechanism; this mechanism is thought to function not only in the axonal growth cone but also in the leading process growth cone of migrating neurons8,9,10,11,12. Namely, actin filaments (F-actins) in growth cones polymerize at the leading edge and depolymerize proximally, pushing out the leading-edge membrane13,14,15. The resultant force, in conjunction with actomyosin contraction, induces rearward movement of F-actins called retrograde flow7,11,16,17,18,19,20,21. Clutch- and cell adhesion molecules mediate mechanical coupling between F-actin retrograde flow and the adhesive substrate and transmit the force of F-actin flow onto the substrate, thereby generating traction force for growth cone advance7,8,9,11,12,22. Concurrently, the actin-substrate coupling reduces the F-actin flow velocity and converts actin polymerization into the force to protrude the leading-edge membrane9,10.
Axonal growth cones sense local chemical cues and transduce them into a directional driving force for growth cone navigation3,23,24,25. For example, an axon guidance molecule netrin-1 stimulates its receptor deleted in colorectal cancer (DCC), and activates the Rho guanosine triphosphate (GTP)-binding proteins cell division control protein 42 (Cdc42) and Ras-related C3 botulinum toxin substrate 1 (Rac1), and their downstream kinase p21-activated kinase 1 (Pak1)26. Cdc42 and Rac1 promote 1) actin polymerization, and Pak1 phosphorylates a clutch molecule shootin122,26. Shootin1 interacts with F-actin retrograde flow via an actin-binding protein cortactin27. Shootin1 also interacts with L1 cell adhesion molecule (L1-CAM)20,24. Shootin1 phosphorylation increases the binding affinities for cortactin and L1-CAM, and enhances shootin1-mediated 2) clutch coupling24,27. Within the growth cone, asymmetrical activations of actin polymerization and clutch coupling increase 3) traction force on the side of the netrin-1 source, thereby generating directional driving force for growth cone turning (Figure 1)24. Intensive research over the last few decades with respect to neuronal migration and axon guidance has enhanced the understanding of guidance molecules, their receptors, and associated downstream signaling cascades2,10,28,29,30. However, the molecular machineries to generate forces for growth cone advance are just beginning to be elucidated; this may be attributed to the limited usage of the protocols for mechanobiological analyses.
The present study describes a detailed protocol for monitoring F-actin retrograde flow by single speckle imaging16,18. Monitoring of F-actin retrograde flow has been extensively performed using super-resolution microscopy, spinning-disk confocal microscopy and total interference reflection fluorescence (TIRF) microscopy25,31,32,33,34,35,36,37,38. The protocol in the present study, however, uses a standard epifluorescence microscope and is thus readily adoptable11,16,18,20,22,23,24,27,39,40,41,42. When combined with F-actin labelling by Lifeact43,&#160;single speckle imaging allows for quantifications of the actin polymerization rate and the clutch coupling efficiency between F-actin retrograde flow and the adhesive substrate39,42. The present study further describes a detailed protocol of traction force microscopy using a fluorescent bead-embedded polyacrylamide (PAA) gel11,22,23,24,27,39,41,42,44. This method detects and quantifies traction force under the growth cone by monitoring force-induced bead movements44,45. An open-source traction force analysis code is provided, and the method for quantifying traction force during growth cone migration is explained in detail. With the aid of single speckle imaging and traction force microscopy, understanding the molecular mechanics underlying growth cone migration and navigation will be facilitated. These techniques are also applicable for analyzing the molecular mechanics underlying dendritic spine enlargement, which is known to be important in learning and memory42.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>0.5% trypan blue stain solution</td>
			<td>Nacalai</td>
			<td>29853-34</td>
			<td></td>
		</tr>
		<tr>
			<td>3-aminopropyltrimethyoxysilane</td>
			<td>Sigma</td>
			<td>281778-100ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Acrylamide monomer</td>
			<td>Nacalai</td>
			<td>00809-85</td>
			<td></td>
		</tr>
		<tr>
			<td>Ammonium persulphate</td>
			<td>Cytiva</td>
			<td>17-1311-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Axio Observer Z1</td>
			<td>Zeiss</td>
			<td>431007-9902-000</td>
			<td>Epi-fluorescence microscope (single speckle imaging)</td>
		</tr>
		<tr>
			<td>B-27 supplement (50x)</td>
			<td>Thermo Fisher Scientific</td>
			<td>17504-044</td>
			<td></td>
		</tr>
		<tr>
			<td>Bovine serum albmine</td>
			<td>Sigma</td>
			<td>A7906-10G</td>
			<td></td>
		</tr>
		<tr>
			<td>C-Apochromat 63x/1.2 W Corr</td>
			<td>Zeiss</td>
			<td>421787-9970-799</td>
			<td>Objective lens (traction force microscopy)</td>
		</tr>
		<tr>
			<td>Coverslip (diameter 18 mm)</td>
			<td>Matsunami</td>
			<td>C018001</td>
			<td></td>
		</tr>
		<tr>
			<td>D-glucose</td>
			<td>Nacalai</td>
			<td>16806-25</td>
			<td></td>
		</tr>
		<tr>
			<td>DNaseI</td>
			<td>Sigma</td>
			<td>DN25-100MG</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal bovine serum</td>
			<td>Thermo Fisher Scientific</td>
			<td>10270-106</td>
			<td></td>
		</tr>
		<tr>
			<td>Fiji</td>
			<td>Open source software package</td>
			<td>https://imagej.net/software/fiji/</td>
			<td></td>
		</tr>
		<tr>
			<td>FluoSpheres carboxylate-modified 0.2 mm, red (580/605), 2% solid</td>
			<td>Thermo Fisher Scientific</td>
			<td>F8810</td>
			<td>carboxylate-modified microspheres</td>
		</tr>
		<tr>
			<td>Glass bottom dish (14 mm diameter)</td>
			<td>Matsunami</td>
			<td>D1130H</td>
			<td></td>
		</tr>
		<tr>
			<td>Glass bottom dish (27 mm diameter)</td>
			<td>Matsunami</td>
			<td>D1140H</td>
			<td></td>
		</tr>
		<tr>
			<td>Glutaraldehyde solution</td>
			<td>Sigma</td>
			<td>G5882-10X10ML</td>
			<td></td>
		</tr>
		<tr>
			<td>HaloTag TMR ligand</td>
			<td>Promega</td>
			<td>G8251</td>
			<td></td>
		</tr>
		<tr>
			<td>HBO103 W/2</td>
			<td>Osram</td>
			<td>4050300382128</td>
			<td>Mercury lamp (single speckle imaging)</td>
		</tr>
		<tr>
			<td>Image Processing Toolbox</td>
			<td>MathWork</td>
			<td>https://www.mathworks.com/products/image.html</td>
			<td></td>
		</tr>
		<tr>
			<td>Laminin solution from mouse EHS tumor</td>
			<td>Wako</td>
			<td>120-05751</td>
			<td></td>
		</tr>
		<tr>
			<td>Leibovitz&#8217;s L-15 medium</td>
			<td>Thermo Fisher Scientific</td>
			<td>11415064</td>
			<td></td>
		</tr>
		<tr>
			<td>L-glutamine</td>
			<td>Nacalai</td>
			<td>16919-42</td>
			<td></td>
		</tr>
		<tr>
			<td>LSM710</td>
			<td>Zeiss</td>
			<td>N/A</td>
			<td>Conforcal laser microscope (traction force microscopy)</td>
		</tr>
		<tr>
			<td>MATLAB2018a</td>
			<td>MathWork</td>
			<td>https://www.mathworks.com/products/new_products/release2018a.html</td>
			<td></td>
		</tr>
		<tr>
			<td>Mouse C57BL/6</td>
			<td>Japan SLC</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Mouse neuron nucleofector kit</td>
			<td>Lonza</td>
			<td>VPG-1001</td>
			<td></td>
		</tr>
		<tr>
			<td>N,N,N&#8217;,N&#8217;-tetramethylethylenediamine (TEMED)</td>
			<td>Nacalai</td>
			<td>33401-72</td>
			<td></td>
		</tr>
		<tr>
			<td>N,N&#8217;-methylenebisacrylamide</td>
			<td>Nacalai</td>
			<td>22402-02</td>
			<td></td>
		</tr>
		<tr>
			<td>Neurobasal medium</td>
			<td>Thermo Fisher Scientific</td>
			<td>21103-049</td>
			<td></td>
		</tr>
		<tr>
			<td>Nucleofector I</td>
			<td>Amaxa</td>
			<td>AAD-1001</td>
			<td>Electroporation apparatus</td>
		</tr>
		<tr>
			<td>ORCA Flash 4.0 V2</td>
			<td>Hamamatsu</td>
			<td>C11440-22CU</td>
			<td>CMOS camera (single speckle imaging)</td>
		</tr>
		<tr>
			<td>Papain</td>
			<td>Nacalai</td>
			<td>26036-34</td>
			<td></td>
		</tr>
		<tr>
			<td>Parallel Computing Toolbox</td>
			<td>MathWork</td>
			<td>https://www.mathworks.com/products/parallel-computing.html</td>
			<td></td>
		</tr>
		<tr>
			<td>pEGFP-C1</td>
			<td>Clontech</td>
			<td>1528177</td>
			<td></td>
		</tr>
		<tr>
			<td>Penicillin-streptomycin (100x)</td>
			<td>Nacalai Tesque</td>
			<td>26253-84</td>
			<td></td>
		</tr>
		<tr>
			<td>pFN21A-HaloTag-actin</td>
			<td>(Minegishi et al., 2018)</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate buffered saline (PBS) pH 7.4 (10x)</td>
			<td>Thermo Fisher Scientific</td>
			<td>70011-044</td>
			<td></td>
		</tr>
		<tr>
			<td>Plan-Apochromat 100x/1.4 Oil</td>
			<td>Zeiss</td>
			<td>420790-9901-000</td>
			<td>Objective lens (single speckle imaging)</td>
		</tr>
		<tr>
			<td>pmNeonGreen-N1-Lifeact</td>
			<td>(Kastian et al., 2021)</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Poly-D-lysine hydrobromide</td>
			<td>Sigma</td>
			<td>P6407-5MG</td>
			<td></td>
		</tr>
		<tr>
			<td>Slulfo-SAMPHA</td>
			<td>Thermo Fisher Scientific</td>
			<td>22589</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium dodecyl sulfate</td>
			<td>Nacalai</td>
			<td>08933-05</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium hydrate (NaOH)</td>
			<td>Nacalai</td>
			<td>31511-05</td>
			<td></td>
		</tr>
		<tr>
			<td>Steel ball</td>
			<td>Sako tekkou</td>
			<td>N/A</td>
			<td>Microshpere to determin PAA gel rigidity. 0.6 mm diameter, 7.87 g/cm3.</td>
		</tr>
		<tr>
			<td>ZEN2009</td>
			<td>Zeiss</td>
			<td>https://www.zeiss.com/microscopy/us/products/microscope-software/zen.html#introduction</td>
			<td>Image acquisition software (traction force microscopy)</td>
		</tr>
		<tr>
			<td>ZEN2012</td>
			<td>Zeiss</td>
			<td>https://www.zeiss.com/microscopy/us/products/microscope-software/zen.html#introduction</td>
			<td>Image acquisition software (single speckle imaging)</td>
		</tr>
	</tbody>
</table>

analyses of actin dynamics, clutch coupling and traction force for growth cone advance

To establish functional networks, neurons must migrate to their appropriate destinations and then extend axons toward their target cells. These processes depend on the advances of growth cones that located at the tips of neurites. Axonal growth cones generate driving forces by sensing their local microenvironment and modulating cytoskeletal dynamics and actin-adhesion coupling (clutch coupling). Decades of research have led to the identification of guidance molecules, their receptors, and downstream signaling cascades for regulating neuronal migration and axonal guidance; however, the molecular machineries required for generating forces to drive growth cone advance and navigation are just beginning to be elucidated. At the leading edge of neuronal growth cones, actin filaments undergo retrograde flow, which is powered by actin polymerization and actomyosin contraction. A clutch coupling between F-actin retrograde flow and adhesive substrate generates traction forces for growth cone advance. The present study describes a detailed protocol for monitoring F-actin retrograde flow by single speckle imaging. Importantly, when combined with an F-actin marker Lifeact, this technique can quantify 1) the F-actin polymerization rate and 2) the clutch coupling efficiency between F-actin retrograde flow and the adhesive substrate. Both are critical variables for generating forces for growth cone advance and navigation. In addition, the present study describes a detailed protocol of traction force microscopy, which can quantify 3) traction force generated by growth cones. Thus, by coupling the analyses of&#160;single speckle imaging and traction force microscopy, investigators can monitor the molecular mechanics underlying growth cone advance and navigation.

Single speckle imaging to quantify actin polymerization rate and clutch coupling efficiency 
A high Lifeact expression permits F-actin visualization within the growth cone; a low HaloTag-actin expression allows the monitoring of F-actin retrograde flow (Figure 3, Supplemental File 2). Tracing of the actin speckles allows measurement of F-actin flow velocity (Figure 3C,D). Since the mechanical coupling of F-actin retrograde flow and the adhesive substrate reduces the F-actin flow velocity, the clutch coupling efficiency can be estimated from the velocity. Furthermore, F-actin labeling with Lifeact aids visualization of F-actin extension and is useful for quantifying the actin polymerization rate (Figure 3E,F).
Quantitative analysis of traction force 
Strict adherence to the methodology presented here will reveal the movements of fluorescent beads under the growth cone (Figure 6C, Supplemental File 4). F-actin retrograde flow onto the substrate generates traction force causing the fluorescent beads to move rearward under the growth cone. The traction force analysis code estimates traction force from fluorescent bead displacement, and expresses the calculated traction force as a force vector. The direction and magnitude of the traction force are determined from the x- and y-components of the force vector (Figure 8C,D). The red box in Figure 8D represents the x- and y-components of a force vector; Figure 8C depicts the corresponding growth cone. In terms of x-y coordinates, the vector points to -93.8&#176; against the x-axis; this orientation is directed toward the rear of the growth cone (Figure 8C). The magnitude of the traction force F was calculated as follows:
<img alt="Equation 2" src="/files/ftp_upload/63227/63227eq02.jpg" />
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63227/63227fig01.jpg" /> 
Figure 1: A growth cone machinery for force generation and growth cone navigation. A netrin-1 chemoattractant gradient induces asymmetrical stimulation of its receptor DCC on an axonal growth cone. This activates Rac1 and Cdc42, and their downstream kinase Pak1. Rac1 and Cdc42 promote (1) actin polymerization, whereas Pak1 phosphorylates shootin1, enhancing shootin1-mediated (2) clutch coupling. The asymmetric activation of actin dynamics and the clutch coupling within the growth cone increases (3) traction force on the side of the netrin-1 source, thereby generating a directional driving force for growth cone attraction. The protocols presented here allow for the quantification of the key variables (1)-(3) for growth cone navigation. <a href="https://www.jove.com/files/ftp_upload/63227/63227fig01large.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/63227/63227fig02.jpg" /> 
Figure 2: Fluorescence images of a neuronal growth cone under a fully opened and narrowed diaphragm. The growth cone expresses Lifeact and HaloTag-actin. (A) A high Lifeact expression permits visualization of growth cone morphology. On the other hand, HaloTag-actin expression levels are very low, with dim signals when the diaphragm is fully opened. (B) When the diaphragm is appropriately narrowed, background signals diminish, and single actin speckles appear in the growth cone. Scale bars: 5 &#181;m. <a href="https://www.jove.com/files/ftp_upload/63227/63227fig02large.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/63227/63227fig3v2.jpg" /> 
Figure 3: Steps for quantifying F-actin flow velocity and actin polymerization rate using an image processing and analysis software Fiji. (A) Adjust the angle of the image for analysis. (1) Find and select an actin speckle (arrowhead) that flows in an F-actin bundle. (2) Select Image &#62; Transform &#62; Rotate. (3) Set the angle so that the F-actin bundle is directed upward. (4) The angle of the image will be changed. (B) Demarcate the region, including the actin speckle and the F-actin bundle. (1) Click on Rectangle on the toolbar. (2) Delineate a region on the image. The brightness and contrast of the image are increased to allow clear visualization of the actin speckle and the tip of the F-actin bundle. (3) Select Image &#62; Duplicate. (4) Input the five time-frames that show actin speckle flow in the F-actin bundle. (5) The selected stack image will appear on the screen. (C) Overlay circles on the actin speckle. (1) Click on Oval on the toolbar. (2) Draw a circle on an actin speckle. (3) Select Image &#62; Overlay &#62; Add Selection. (4) The circle is overlaid. 5) Repeat overlaying the circles on the remaining actin speckles. (D) Measure the translocation distance of actin speckles during the five time-frames. (1) Click on Straight on the toolbar. (2) Draw a line which links the centers of the circles. (3) Select Analyze &#62; Measure. The result, indicated by the parameter Height (red box), relaying the actin speckle translocation distance. (E) Measure the change in the length of F-actin protrusion during the five time-frames. (1) Draw a line which links the tips of the F-actin protrusion. (2) Select Analyze &#62; Measure. The result (red box), Height, indicates the extension length of the F-actin bundle. (F) The actin polymerization rate is calculated from the sum of the F-actin flow velocity and the extension rate.&#160;See also Supplemental File 2. Supplemental File 3 assists investigators to practice the methodology described above. <a href="https://www.jove.com/files/ftp_upload/63227/63227fig3v2large.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/63227/63227fig04.jpg" /> 
Figure 4: Steps for the PAA gel preparation. Please see step 7.1 for a detailed description. <a href="https://www.jove.com/files/ftp_upload/63227/63227fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/63227/63227fig05.jpg" /> 
Figure 5: Determination of PAA gel rigidity. (A) A microsphere indentation method. When a microsphere is placed on a fluorescent bead-embedded PAA gel, the weight of the microsphere causes an indentation in the gel. The indentation depth is calculated by subtracting the z-positions of the PAA gel surface from the bottom of the microsphere (B,C) Fluorescence images of a PAA gel indented by a microsphere and containing fluorescent beads. A laser scanning confocal microscope was used to capture images of the gel surface (B) and the bottom of the microsphere (C). Signals from the fluorescent&#160;beads are not visible at the gel surface in the indented region (B, circle). They can, however, be observed at the bottom of the microsphere. Scale bars: 50 &#181;m. <a href="https://www.jove.com/files/ftp_upload/63227/63227fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/63227/63227fig06.jpg" /> 
Figure 6: Force mapping of a neuronal growth cone. (A-C) Fluorescence images of beads embedded in a PAA gel and a neural growth cone visualized with EGFP. Following the acquisition of time-lapse images (A), the neuron was released from the gel substrate by applying SDS solution, and an image of the beads in the unstrained substrate was captured (B). (C) The image of the beads in the unstrained substrate shows the beads in their original (green) and displaced (red) positions. The EGFP signal of the growth cone is shown in blue. Kymographs (right) show the movements of beads at 3 s intervals for a duration of 147 s, indicated by the arrows in boxed areas 1 and 2. The bead in area 2 is a reference bead. Scale bars: 2 &#181;m for (A), (B) and (C, left), and 1 &#181;m for (C, middle). See also Supplemental File 4. <a href="https://www.jove.com/files/ftp_upload/63227/63227fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/63227/63227fig07.jpg" /> 
Figure 7: Steps for the correcting x-y position of the bead image in unstrained substrate using Fiji. (A) Concatenate the bead image in unstrained substrate with the time-lapse stack image of fluorescent beads. (1) Select Image &#62; Stacks &#62; Tools &#62; Concatenate. (2) Select the beads image in unstrained substrate and the time-lapse stack image of fluorescent beads in Image1 and Image2, respectively. Click on&#160;OK. (3) The bead image in the unstrained substrate is added to the time-lapse stack image. (B) Correct the x-y position of the fluorescent bead image. (1) Use the scroll bar (red frame) to select the second frame (red arrow) in the image stack. (2) Select Plugins &#62; StackReg. (3) Select Rigid Body from the drop-down list (red frame) and click on OK. The correction of the x-y position will begin. (C) Save the x-y position-corrected bead image. After selecting the first frame of the x-y position-corrected stack image, (1) select Image &#62; Duplicate. (2) input 1 into the Range and deselect Duplicate stack. Then click on OK. (3) the x-y position-corrected bead image in the unstrained substrate will appear on the screen. Save this image as a tiff file. Supplemental File 6 assists investigators to practice the methodology described above. <a href="https://www.jove.com/files/ftp_upload/63227/63227fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/63227/63227fig08.jpg" /> 
Figure 8: Analysis of traction force under a neuronal growth cone using an open-source traction force analysis code. (A) GUI for analyzing traction force. Time-lapse images selected on the GUI can be confirmed from the drop-down list and with the slider indicated (red box). (B) Select a region that includes the growth cone. (1) Click on ROI on the GUI. With the mouse cursor, specify two points (arrowheads) on the cell image. (2) A red box will appear on the cell image. Two clicks determine the locations of two corners. (C) Select the detected beads (white dots) under the growth cone. (1) On the GUI, click on Select beads, and demarcate a polygonal region that includes the growth cone by clicking. Press the Enter key. (2) The white dots within the polygonal region will change into a red color. (D) Calculated results of the direction and magnitude of the traction force. The red box in the spreadsheet represents the x- and y-components of the force vector, estimated by traction force analysis. On the x-y coordinate in the right panel, the force vector generated by the growth cone points to -93.8&#176; against the x-axis; this orientation is directed toward the rear of the growth cone in (C). Supplemental File 6 assists investigators to practice the methodology described above. <a href="https://www.jove.com/files/ftp_upload/63227/63227fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental File 1: Recipes of solutions and media used in this study. See text for detailed usage. <a href="https://www.jove.com/files/ftp_upload/63227/JoVE Review - Supplemental File 1-63227R1.xlsx" target="_blank">Please click here to download this File.</a>
Supplemental File 2: Fluorescence imaging of Lifeact and fluorescent speckle imaging of HaloTag-actin in a nerve growth cone. Lifeact (green) and HaloTag-actin (magenta). Images were acquired every 3 s for a total duration of 147 s. Scale bar: 2 &#181;m. See also Figure 3. <a href="https://www.jove.com/files/ftp_upload/63227/JoVE Review - Supplemental File 2.mp4" target="_blank">Please click here to download this File.</a>
Supplemental File 3: Practice data for quantifying F-actin flow velocity and the actin polymerization rate. A multichannel time-lapse stack image of Lifeact (green) and HaloTag-actin (magenta). See also Figure 3. <a href="https://www.jove.com/files/ftp_upload/63227/Supplemental file 3.zip" target="_blank">Please click here to download this File.</a>
Supplemental File 4: A force-mapping video detecting traction force at a neuronal growth cone. The original (green) and displaced (red) positions of the beads. The EGFP signal in the growth cone is shown in blue. Images were acquired every 3 s for 147 s. Scale bar: 2 &#181;m. See also Figure 6. <a href="https://www.jove.com/files/ftp_upload/63227/JoVE Review - Supplemental File 4.mp4" target="_blank">Please click here to download this File.</a>
Supplemental File 5: Traction force analysis code. Please see Step 8.12 for detailed usage. <a href="https://www.jove.com/files/ftp_upload/63227/JoVE Review - Supplemental file 5.zip" target="_blank">Please click here to download this File.</a>
Supplemental File 6: Practice data for quantifying traction force. A single-channel RGB image of the beads in unstrained substrate and single-channel time-lapse stack RGB images of fluorescent beads under a growth cone, EGFP, and bright-field. See also Figures 7 and 8. <a href="https://www.jove.com/files/ftp_upload/63227/JoVE Review - Supplemental file 6.zip" target="_blank">Please click here to download this File.</a>

Watch this Scientific Journal Video about Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance at JoVE.com

Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance

To advance, growth cones must exert traction forces against the external environment. The generation of traction forces is dependent on actin dynamics and clutch coupling. The present study describes methods for analyzing actin dynamics, clutch coupling and traction forces for growth cone advance.

To establish functional networks, neurons must migrate to their appropriate destinations and then extend axons toward their target cells. These processes ...

analyses-actin-dynamics-clutch-coupling-traction-force-for-growth

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JoVE Journal

Neuroscience

3.2K Views.  Nara Institute of Science and Technology. To advance, growth cones must exert traction forces against the external environment. The generation of traction forces is dependent on actin dynamics and clutch coupling. The present study describes methods for analyzing actin dynamics, clutch coupling and traction forces for growth cone advance. 

Video: Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance

Labeling F-actin Barbed Ends with Rhodamine-actin in Permeabilized Neuronal Growth Cones

The motile tips of growing axons are called growth cones. Growth cones lead navigating axons through developing tissues by interacting with locally expressed molecular guidance cues that bind growth cone receptors and regulate the dynamics and organization of the growth cone cytoskeleton3-6. The main target of these navigational signals is the actin filament meshwork that fills the growth cone periphery and that drives growth cone motility through continual actin polymerization and dynamic remodeling7. Positive or attractive guidance cues induce growth cone turning by stimulating actin filament (F-actin) polymerization in the region of the growth cone periphery that is nearer the source of the attractant cue. This actin polymerization drives local growth cone protrusion, adhesion of the leading margin and axonal elongation toward the attractant.
Actin filament polymerization depends on the availability of sufficient actin monomer and on polymerization nuclei or actin filament barbed ends for the addition of monomer. Actin monomer is abundantly available in chick retinal and dorsal root ganglion (DRG) growth cones. Consequently, polymerization increases rapidly when free F-actin barbed ends become available for monomer addition. This occurs in chick DRG and retinal growth cones via the local activation of the F-actin severing protein actin depolymerizing factor (ADF/cofilin) in the growth cone region closer to an attractant8-10. This heightened ADF/cofilin activity severs actin filaments to create new F-actin barbed ends for polymerization. The following method demonstrates this mechanism. Total content of F-actin is visualized by staining with fluorescent phalloidin. F-actin barbed ends are visualized by the incorporation of rhodamine-actin within growth cones that are permeabilized with the procedure described in the following, which is adapted from previous studies of other motile cells11, 12. When rhodamine-actin is added at a concentration above the critical concentration for actin monomer addition to barbed ends, rhodamine-actin assembles onto free barbed ends. If the attractive cue is presented in a gradient, such as being released from a micropipette positioned to one side of a growth cone, the incorporation of rhodamine-actin onto F-actin barbed ends will be greater in the growth cone side toward the micropipette10.
Growth cones are small and delicate cell structures. The procedures of permeabilization, rhodamine-actin incorporation, fixation and fluorescence visualization are all carefully done and can be conducted on the stage of an inverted microscope. These methods can be applied to studying local actin polymerization in migrating neurons, other primary tissue cells or cell lines.

A method to visualize and quantify F-actin barbed ends in neuronal growth cones is described. After culturing neurons on glass coverslips, cells are permeabilized with a saponin-containing solution. Then, a short incubation with the saponin buffer containing rhodamine-actin incorporates fluorescent actin onto free actin barbed ends.

The motile tips of growing axons are called growth cones. Growth cones lead navigating axons through developing tissues by interacting with locally ...

Morphometric Analyses of Retinal Sections

Morphometric analyses of retinal sections have been used in examining retinal diseases. For examples, neuronal cells were significantly lost in the retinal ganglion cell layer (RGCL) in rat models with N-methyl-D-aspartate (NMDA)&#x2013;induced excitotoxicity1, retinal ischemia-reperfusion injury2 and glaucoma3. Reduction of INL and inner plexiform layer (IPL) thicknesses were reversed with citicoline treatment in rats' eyes subjected to kainic acid-mediated glutamate excitotoxicity4. Alteration of RGC density and soma sizes were observed with different drug treatments in eyes with elevated intraocular pressure3,5,6. Therefore, having objective methods of analyzing the retinal morphometries may be of great significance in evaluating retinal pathologies and the effectiveness of therapeutic strategies.
The retinal structure is multi-layers and several different kinds of neurons exist in the retina. The morphometric parameters of retina such as cell number, cell size and thickness of different layers are more complex than the cell culture system. Early on, these parameters can be detected using other commercial imaging software. The values are normally of relative value, and changing to the precise value may need further accurate calculation. Also, the tracing of the cell size and morphology may not be accurate and sensitive enough for statistic analysis, especially in the chronic glaucoma model. The measurements used in this protocol provided a more precise and easy way. And the absolute length of the line and size of the cell can be reported directly and easy to be copied to other files. For example, we traced the margin of the inner and outer most nuclei in the INL and formed a line then using the software to draw a 90 degree angle to measure the thickness. While without the help of the software, the line maybe oblique and the changing of retinal thickness may not be repeatable among individual observers. In addition, the number and density of RGCs can also be quantified. This protocol successfully decreases the variability in quantitating features of the retina, increases the sensitivity in detecting minimal changes.
 	This video will demonstrate three types of morphometric analyses of the retinal sections. They include measuring the INL thickness, quantifying the number of RGCs and measuring the sizes of RGCs in absolute value. These three analyses are carried out with Stereo Investigator (MBF Bioscience &mdash; MicroBrightField, Inc.). The technique can offer a simple but scientific platform for morphometric analyses.

This video demonstrates three types of morphometric analyses of the retina, which include measuring the inner nuclear layer thickness, quantifying the number of retinal ganglion cells (RGCs) and measuring the sizes of RGCs. The technique can offer a simple but scientific platform for morphometric analyses.

Morphometric analyses of retinal sections have been used in examining retinal diseases. For examples, neuronal cells were significantly lost in the ...

Transretinal ERG Recordings from Mouse Retina: Rod and Cone Photoresponses

There are two distinct classes of image-forming photoreceptors in the vertebrate retina: rods and cones. Rods are able to detect single photons of light whereas cones operate continuously under rapidly changing bright light conditions. Absorption of light by rod- and cone-specific visual pigments in the outer segments of photoreceptors triggers a phototransduction cascade that eventually leads to closure of cyclic nucleotide-gated channels on the plasma membrane and cell hyperpolarization. This light-induced change in membrane current and potential can be registered as a photoresponse, by either classical suction electrode recording technique1,2 or by transretinal electroretinogram recordings (ERG) from isolated retinas with pharmacologically blocked postsynaptic response components3-5. The latter method allows drug-accessible long-lasting recordings from mouse photoreceptors and is particularly useful for obtaining stable photoresponses from the scarce and fragile mouse cones. In the case of cones, such experiments can be performed both in dark-adapted conditions and following intense illumination that bleaches essentially all visual pigment, to monitor the process of cone photosensitivity recovery during dark adaptation6,7. In this video, we will show how to perform rod- and M/L-cone-driven transretinal recordings from dark-adapted mouse retina. Rod recordings will be carried out using retina of wild type (C57Bl/6) mice. For simplicity, cone recordings will be obtained from genetically modified rod transducin &alpha;-subunit knockout (T&alpha;-/-) mice which lack rod signaling8.

We describe a relatively simple method of transretinal electroretinogram (ERG) recordings for obtaining rod and cone photoresponses from intact mouse retina. This approach takes advantage of the block of synaptic transmission from photoreceptors to isolate their light responses and record them using field electrodes placed across the isolated flat-mounted retina.

There are two distinct classes of image-forming photoreceptors in the vertebrate retina: rods and cones. Rods are able to detect single photons of light ...

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Long-term behavioral tracking can capture and quantify natural animal behaviors, including those occurring infrequently. Behaviors such as exploration and social interactions can be best studied by observing unrestrained, freely behaving animals. Weakly electric fish (WEF) display readily observable exploratory and social behaviors by emitting electric organ discharge (EOD). Here, we describe three effective techniques to synchronously measure the EOD, body position, and posture of a free-swimming WEF for an extended period of time. First, we describe the construction of an experimental tank inside of an isolation chamber designed to block external sources of sensory stimuli such as light, sound, and vibration. The aquarium was partitioned to accommodate four test specimens, and automated gates remotely control the animals&#39; access to the central arena. Second, we describe a precise and reliable real-time EOD timing measurement method from freely swimming WEF. Signal distortions caused by the animal&#39;s body movements are corrected by spatial averaging and temporal processing stages. Third, we describe an underwater near-infrared imaging setup to observe unperturbed nocturnal animal behaviors. Infrared light pulses were used to synchronize the timing between the video and the physiological signal over a long recording duration. Our automated tracking software measures the animal&#39;s body position and posture reliably in an aquatic scene. In combination, these techniques enable long term observation of spontaneous behavior of freely swimming weakly electric fish in a reliable and precise manner. We believe our method can be similarly applied to the study of other aquatic animals by relating their physiological signals with exploratory or social behaviors.

We describe a set of techniques for studying spontaneous behavior of freely swimming weakly electric fish over an extended period of time, by synchronously measuring the animal&#39;s electric organ discharge timing, body position and posture both accurately and reliably in a specially designed aquarium tank inside a sensory isolation chamber.

Long-term behavioral tracking can capture and quantify natural animal behaviors, including those occurring infrequently. Behaviors such as exploration and ...

Flow Cytometry Protocols for Surface and Intracellular Antigen Analyses of Neural Cell Types

Flow cytometry has been extensively used to define cell populations in immunology, hematology and oncology. Here, we provide a detailed description of protocols for flow cytometric analysis of the cluster of differentiation (CD) surface antigens and intracellular antigens in neural cell types. Our step-by-step description of the methodological procedures include: the harvesting of neural in vitro cultures, an optional carboxyfluorescein succinimidyl ester (CFSE)-labeling step, followed by surface antigen staining with conjugated CD antibodies (e.g., CD24, CD54), and subsequent intracellar antigen detection via primary/secondary antibodies or fluorescently labeled Fab fragments (Zenon labeling). The video demonstrates the most critical steps. Moreover, principles of experimental planning, the inclusion of critical controls, and fundamentals of flow cytometric analysis (identification of target population and exclusion of debris; gating strategy; compensation for spectral overlap) are briefly explained in order to enable neurobiologists with limited prior knowledge or specific training in flow cytometry to assess its utility and to better exploit this powerful methodology.

We provide a detailed description of a protocol for flow cytometric analysis of surface antigens and/or intracellular antigens in neural cell types. Critical aspects of experimental planning, step-by-step methodological procedures, and fundamental principles of flow cytometry are explained in order to enable neurobiologists to exploit this powerful technology.

Flow cytometry has been extensively used to define cell populations in immunology, hematology and oncology. Here, we provide a detailed description of ...

Imaging Ca2+ Dynamics in Cone Photoreceptor Axon Terminals of the Mouse Retina

Retinal cone photoreceptors (cones) serve daylight vision and are the basis of color discrimination. They are subject to degeneration, often leading to blindness in many retinal diseases. Calcium (Ca2+), a key second messenger in photoreceptor signaling and metabolism, has been proposed to be indirectly linked with photoreceptor degeneration in various animal models. Systematically studying these aspects of cone physiology and pathophysiology has been hampered by the difficulties of electrically recording from these small cells, in particular in the mouse where the retina is dominated by rod photoreceptors. To circumvent this issue, we established a two-photon Ca2+ imaging protocol using a transgenic mouse line that expresses the genetically encoded Ca2+ biosensor TN-XL exclusively in cones and can be crossbred with mouse models for photoreceptor degeneration. The protocol described here involves preparing vertical sections (&#8220;slices&#8221;) of retinas from mice and optical imaging of light stimulus-evoked changes in cone Ca2+ level. The protocol also allows &#8220;in-slice measurement&#8221; of absolute Ca2+ concentrations; as the recordings can be followed by calibration. This protocol enables studies into functional cone properties and is expected to contribute to the understanding of cone Ca2+ signaling as well as the potential involvement of Ca2+ in photoreceptor death and retinal degeneration.

Imaging Ca2+ Dynamics in Cone Photoreceptor Axon Terminals of the Mouse Retina

We describe a protocol to monitor Ca2+ dynamics in the axon terminals of cone photoreceptors using an ex-vivo&#160;slice preparation of the mouse retina. This protocol allows comprehensive studies of cone Ca2+ signaling in an important mammalian model system, the mouse.

Retinal cone photoreceptors (cones) serve daylight vision and are the basis of color discrimination. They are subject to degeneration, often leading to ...

Quantification of Filamentous Actin (F-actin) Puncta in Rat Cortical Neurons

Filamentous actin protein (F-actin) plays a major role in spinogenesis, synaptic plasticity, and synaptic stability. Changes in dendritic F-actin rich structures suggest alterations in synaptic integrity and connectivity. Here we provide a detailed protocol for culturing primary rat cortical neurons, Phalloidin staining for F-actin puncta, and subsequent quantification techniques. First, the frontal cortex of E18 rat embryos are dissociated into low-density cell culture, then the neurons grown in vitro for at least 12-14 days. Following experimental treatment, the cortical neurons are stained with AlexaFluor 488 Phalloidin (to label the dendritic F-actin puncta) and microtubule-associated protein 2 (MAP2; to validate the neuronal cells and dendritic integrity). Finally, specialized software is used to analyze and quantify randomly selected neuronal dendrites. F-actin rich structures are identified on second order dendritic branches (length range 25-75 &#181;m) with continuous MAP2 immunofluorescence. The protocol presented here will be a useful method for investigating changes in dendritic synapse structures subsequent to experimental treatments.

Quantification of Filamentous Actin F-actin Puncta in Rat Cortical Neurons

Filamentous actin (F-actin) plays an important role in spinogenesis, synaptic plasticity, and synaptic stability. Quantification of F-actin puncta is therefore a useful tool to study the integrity of synaptic structures. This protocol describes the procedures of quantifying F-actin puncta labeled with Phalloidin in low-density primary cortical neuronal cultures.

Filamentous actin protein (F-actin) plays a major role in spinogenesis, synaptic plasticity, and synaptic stability. Changes in dendritic F-actin rich ...

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Microstate and omega complexity are two reference-free electroencephalography (EEG) measures that can represent the temporal and spatial complexities of EEG data and have been widely used to investigate the neural mechanisms in some brain disorders. The goal of this article is to describe the protocol underlying EEG microstate and omega complexity analyses step by step. The main advantage of these two measures is that they could eliminate the reference-dependent problem inherent to traditional spectrum analysis. In addition, microstate analysis makes good use of high time resolution of resting-state EEG, and the four obtained microstate classes could match the corresponding resting-state networks respectively. The omega complexity characterizes the spatial complexity of the whole brain or specific brain regions, which has obvious advantage compared with traditional complexity measures focusing on the signal complexity in a single channel. These two EEG measures could complement each other to investigate the brain complexity from the temporal and spatial domain respectively.

This article describes the protocol underlying electroencephalography (EEG) microstate analysis and omega complexity analysis, which are two reference-free EEG measures and highly valuable to explore the neural mechanisms of brain disorders.

Microstate and omega complexity are two reference-free electroencephalography (EEG) measures that can represent the temporal and spatial complexities of ...

Visualizing Axonal Growth Cone Collapse and Early Amyloid &#946; Effects in Cultured Mouse Neurons

Amyloid-&#946; (A&#946;) causes memory impairments in Alzheimer's disease (AD). Although therapeutics have been shown to reduce A&#946; levels in the brains of AD patients, these do not improve memory functions. Since A&#946; aggregates in the brain before the appearance of memory impairments, targeting A&#946; may be inefficient for treating AD patients who already exhibit memory deficits. Therefore, downstream signaling due to A&#946; deposition should be blocked before AD development. A&#946; induces axonal degeneration, leading to the disruption of neuronal networks and memory impairments. Although there are many studies on the mechanisms of A&#946; toxicity, the source of A&#946; toxicity remains unknown. To help identify the source, we propose a novel protocol that uses microscopy, gene transfection, and live cell imaging to investigate early changes caused by A&#946; in axonal growth cones of cultured neurons. This protocol revealed that A&#946; induced clathrin-mediated endocytosis in axonal growth cones followed by growth cone collapse, demonstrating that inhibition of endocytosis prevents A&#946; toxicity. This protocol will be useful in studying the early effects of A&#946; and may lead to more efficient and preventative AD treatment.

Here a protocol to investigate the early effects of amyloid-&#946; (A&#946;) in the brain is presented. This shows that A&#946; induces clathrin-mediated endocytosis and collapse of axonal growth cones. The protocol is useful in studying early effects of A&#946; on axonal growth cones and may facilitate prevention of Alzheimer's disease.

Amyloid-&#946; (A&#946;) causes memory impairments in Alzheimer's disease (AD). Although therapeutics have been shown to reduce A&#946; levels in the ...

Collection of Frozen Rodent Brain Regions for Downstream Analyses

As our understanding of neurobiology has progressed, molecular analyses are often performed on small brain areas such as the medial prefrontal cortex (mPFC) or nucleus accumbens. The challenge in this work is to dissect the correct area while preserving the microenvironment to be examined. In this paper, we describe a simple, low-cost method using resources readily available in most labs. This method preserves nucleic acid and proteins by keeping the tissue frozen throughout the process. Brains are cut into 0.5&#8211;1.0 mm sections using a brain matrix and arranged on a frozen glass plate. Landmarks within each section are compared to a reference, such as the Allen Mouse Brain Atlas, and regions are dissected using a cold scalpel or biopsy punch. Tissue is then stored at -80 &#176;C until use. Through this process rat and mouse mPFC, nucleus accumbens, dorsal and ventral hippocampus and other regions have been successfully analyzed using qRT-PCR and Western assays. This method is limited to brain regions that can be identified by clear landmarks.

This procedure describes the collection of discrete frozen brain regions to obtain high-quality protein and RNA using inexpensive and commonly available tools.

As our understanding of neurobiology has progressed, molecular analyses are often performed on small brain areas such as the medial prefrontal cortex ...

Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance

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