The Authors thank Anna Luchniak and Yin-wei Kuo for critical reading and comments on the protocol.

1. Microscope modification and objective lens
<ol>
	<li>Insert a 50/50 mirror into the filter wheel of the fluorescent microscope using an appropriate filter cube (Figure 1). Handle the 50/50 mirror with care as often they have anti-reflection coating. 
	NOTE: We used a 50/50 mirror in an empty filter cube of the microscope. The 50/50 mirror is inserted where the dichroic mirror is located.</li>
	<li>Use a high magnification/high NA oil objective. 
	NOTE: In this protocol, we used a 100x/1.3 NA objective.</li>
</ol>
2. Chamber preparation to adhere microtubules to the surface
<ol>
	<li>Clean&#160;microscope slides and 22 mm x 22 mm coverslips (for upright microscope) or 22 mm x 22 mm and 18 mm x 18 mm coverslips (for inverted microscopes). Modify the surface as needed. For example, clean the coverslips using an alkaline detergent (see Table of Materials) followed by 100% ethanol with distilled water washes in between and after11.</li>
	<li>Cut 3 mm wide strips of plastic paraffin film (see Table of Materials) using a razor blade and another microscope slide as an edge.</li>
	<li>Place two plastic paraffin film strips 3 mm apart on a clean 22 x 22mm cover slip. Then place an 18 mm x 18 mm coverslip to form a channel. If using an upright microscope, place the strips on top of a clean microscope slide and then place a coverslip on top.</li>
	<li>Place the coverslip (or slide) on a heat block at 100 &#176;C for 10-30 s for the paraffin film to form a sealed channel.</li>
	<li>Flow in 50 &#181;g/mL of antibody (in Brinkley Buffer 1980 (BRB80)) by perfusion using a pipette. Incubate for 10 min. 
	NOTE: We use anti-rhodamine antibodies to bind rhodamine-labeled microtubule seeds to the surface. Alternatively, avidin can be used to bind biotin-labelled microtubule seeds or to biotinylated gold particles. To simply look at microtubules in the absence of tubulin in solution (i.e., a non-dynamic assay), an anti-tubulin antibody can be used.</li>
	<li>Wash five times with BRB80 buffer. It is recommended to filter the solutions using a 0.22 &#181;m filter.</li>
	<li>Flow in 1% poloxamer 407 (a triblock copolymer) in BRB80 to block the surface against non-specific binding. Incubate for 10 min.</li>
	<li>Wash five times with BRB80 buffer.</li>
	<li>The sample is ready to be placed on the microscope. To prevent the sample from drying out, add two droplets of BRB80 buffer at the ends of the channel and replenish when needed.</li>
</ol>
3. Microscope alignment
<ol>
	<li>Place the sample on the microscope stage. Turn on the epi-illumination light source.</li>
	<li>Focus on the sample surface. You will observe multiple surfaces as the objective is moved up and down due to back reflection of light from optics within the optical path. A good method to find the sample surface is to focus on the paraffin film edge. Once the surface is found, set the field of view to the center of the chamber.</li>
	<li>Center the field diaphragm in the field of view by closing it half way and using the adjustment screws. Once aligned, reopen the diaphragm. 
	NOTE: Screw adjustment only needs to be done sporadically, perhaps every 3-6 months or when troubleshooting.</li>
	<li>Slide in the Bertrand lens to view the exit pupil (back focal plane) of the objective.</li>
	<li>Close the aperture diaphragm (AD) beyond the edges of the exit pupil of the objective.</li>
	<li>Use the adjustment screws to center the AD with the exit pupil. Double check by opening the AD and matching its edges with those of the exit pupil. 
	NOTE: This adjustment only needs to be done sporadically.</li>
	<li>Set the aperture diaphragm to about 2/3 of the NA of the objective. See section 7 for detailed procedures for optimizing the aperture diaphragm.</li>
</ol>
4. Imaging stabilized microtubules or 40 nm gold particle
NOTE: Stabilized microtubules and gold nanoparticles serve as good control samples. It is recommended to image surface attached microtubules or gold nanoparticles as a first step to assess IRM performance and help in setting the optimal aperture diaphragm opening (section 7).
<ol>
	<li>Set the exposure time of the camera to 10 ms and adjust the illumination to nearly saturate the camera dynamic range.</li>
	<li>Flow in 10 &#181;L of guanylyl-(alpha, beta)-methylene-diphosphonate (GMPCCP)- or taxol-stabilized microtubules in BRB804,12,13 (or 40 nm gold particles) by perfusion using a pipette to a fresh sample and monitor binding by imaging the surface. Once 10-20 microtubules are bound within the field of view, wash the sample 2x with BRB80. 
	NOTE: With a well aligned microscope, the microtubules should be visible without background subtraction.</li>
	<li>Acquire 10 images by setting a time lapse with 1 second delay period for 10 seconds (at 10 ms exposure).</li>
	<li>Acquire a background image. To do so, move the stage using the stage controller or computer software along the channel long axis while acquiring 100 images with no delay (i.e. streaming close to 100 fps @ 10 ms exposure). 
	NOTE: The background is the median of the 100 images. By taking the median, the illumination profile and other stationary features like dirt on the optics are preserved while everything else is filtered out. There should be no tilt on the sample as this will lead to change in the axial position as the stage is moved and ultimately degrade the background image. If the tilt cannot be avoided, then an alternative method is to acquire averaged background images before flowing the seeds.</li>
	<li>For processing and analyzing the images, go to step 6.</li>
</ol>
5. Imaging microtubule dynamics
<ol>
	<li>For microtubule dynamics using brain tubulin, set the sample heater temperature to 37 &#176;C.</li>
	<li>Flow in 10 &#181;L of GMPCCP-stabilized microtubule seeds in BRB8011 by perfusion using a pipette to a fresh sample and monitor them binding to the surface by imaging the surface live (i.e., while streaming). Once 10-20 seeds are bound with field of view, wash the sample using 2x channel volume with BRB80 (BRB80 should be prewarmed to 37 &#176;C or at least at room temperature). 
	NOTE: With a well aligned microscope, the seeds should be visible without background subtraction.</li>
	<li>Flow in the polymerization mix (7.5 &#181;M unlabeled tubulin + 1 mM guanosine triphosphate (GTP) + 1 mM Dithiothreitol (DTT) in BRB80 buffer). For measuring microtubule growth, set a time-lapse using the acquisition software to acquire an image every 5 seconds (0.2 frames per second (fps)) for 15 minutes.</li>
	<li>To enhance the contrast, acquire 10 images (instead of one) at each time point and average them. For microtubule shrinkage, acquire images at 100 fps by setting the time delay to 0 and an exposure time of 10ms (higher fps is possible with smaller regions of interest depending on the camera used).</li>
	<li>Acquire a background image as in step 4.4.</li>
</ol>
6. Image processing and analysis
NOTE: For analysis, this protocol uses Fiji14 but the reader is free to use any software she/he find suitable.
<ol>
	<li>Open saved background images.</li>
	<li>Calculate the median image (i.e. background) using Image &#62; Stack &#62; Z project &#62; Median.</li>
	<li>Open microtubule dynamics movie as a stack (same for non-dynamic microtubules) using File &#62; Open.</li>
	<li>Subtract the background image from the stack using Process &#62; Image calculator. Make sure to check the &#8220;32bit (float) result&#8221; option.</li>
	<li>For dynamic microtubules, using the line tool draw a line along the microtubule of interest and add it to the region of interest manager by pressing &#8220;t&#8221;. Repeat for all microtubules of interest.</li>
	<li>For dynamic microtubules, run the Multi-Kymo macro (Supplementary File 1). The macro will generate a video and a kymograph for every microtubule in the ROI manager. Every microtubule will get a unique identifier.</li>
	<li>For dynamic microtubules, run the Kymo-Analysis macro (Supplementary File 2) and follow its steps to measure the growth rates and shrinkage rates of the microtubules.</li>
</ol>
7. Aperture diaphragm size
NOTE: An important factor for acquiring high contrast images of microtubules using IRM is setting the illumination numerical aperture (INA) correctly10,15. The INA can be changed by changing the size of the incoming illumination beam at the objective&#8217;s exit pupil which is controlled by the size of the AD (the AD is located at a conjugate plane with the exit pupil (back focal plane) of the objective, Figure 1): 
<img alt="Equation" src="/files/ftp_upload/59520/59520eq1.jpg" /> 
where DAD is the diameter of the aperture diaphragm, fobjective is the focal length of the objective and Dep is the objective&#8217;s exit pupil diameter. Typically, the AD is left fully open for fluorescence imaging, so the INA equals the objective&#8217;s NA. In a fluorescence microscope, the AD scale does not indicate its diameter, thus the INA can&#8217;t be calculated. It&#8217;s possible to calibrate the AD size with the help of an objective. Yet, it&#8217;s not necessary since the AD size would be fixed to the size that produces the highest contrast.
<ol>
	<li>Prepare a sample of fluorescently labelled stabilized microtubules stuck to the surface (steps 4.1-4.2). 
	NOTE: We used tetramethylrhodamine labeled microtubules16 (Ex: 550 nm, Em: 580 nm).</li>
	<li>Bring microtubules into focus using the microscope focusing knob while fluorescently imaging them (if microtubules are not labelled, image them with IRM15 or DIC5).</li>
	<li>Set camera exposure to 10 ms using the camera software. 
	NOTE: This exposure is arbitrary and an exposure of 100 ms would also work.</li>
	<li>Close down the AD to its smallest opening. Adjust the illumination to nearly saturate the camera&#8217;s dynamic range or to the maximum possible. 
	NOTE: As a guide, use the look up table typically provided by the acquisition software.</li>
	<li>Acquire 10 images (by streaming or taking an image every second) of a field of view containing 10+ microtubules.</li>
	<li>Acquire a background image as in step 4.4.</li>
	<li>Change the size of the AD and repeat steps 7.5-7.6 for the whole AD opening range (from closed to the exit pupil size, Figure 2). Every time the AD size is changed, adjust the illumination intensity to match that of step 7.4.</li>
	<li>For every field of view acquired, subtract the corresponding background using process &#62; image calculator and choosing &#8220;subtract&#8221; from the drop-down menu. Make sure the &#8220;32bit (float) result&#8221; option is checked. Then average the resulting images using image &#62; stack &#62; Z project &#62; average.</li>
	<li>Measure the signal-to-background noise ratio (SBR) of the microtubules defined as the average intensity of the microtubule signal (intensity of the microtubule minus the intensity of the background) divided by the standard deviation of the background (Figure 3).</li>
	<li>Determine the optimal AD size (i.e. optimal INA) by calculating the average SBR&#160;of the microtubules for every opening size and set the AD size to the one producing the highest SBR (Figure 2). It is possible that there is a range of AD sizes that produce comparable contrast15.</li>
</ol>

<ol>
	<li>Widlund, P. O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=One-step+purification+of+assembly-competent+tubulin+from+diverse+eukaryotic+sources.">One-step purification of assembly-competent tubulin from diverse eukaryotic sources.</a> Molecular Biology of the Cell. 23 (22), 4393-4401 (2012).</li><li>Walker, R. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+instability+of+individual+microtubules+analyzed+by+video+light+microscopy:+rate+constants+and+transition+frequencies.">Dynamic instability of individual microtubules analyzed by video light microscopy: rate constants and transition frequencies.</a> The Journal of Cell Biology. 107 (4), 1437-1448 (1988).</li><li>Hotani, H., Horio, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamics+of+microtubules+visualized+by+darkfield+microscopy:+Treadmilling+and+dynamic+instability.">Dynamics of microtubules visualized by darkfield microscopy: Treadmilling and dynamic instability.</a> Cell Motility and the Cytoskeleton. 10 (1-2), 229-236 (1988).</li><li>Gittes, F., Mickey, B., Nettleton, J., Howard, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flexural+rigidity+of+microtubules+and+actin+filaments+measured+from+thermal+fluctuations+in+shape.">Flexural rigidity of microtubules and actin filaments measured from thermal fluctuations in shape.</a> The Journal of Cell Biology. 120 (4), 923-934 (1993).</li><li>Bormuth, V., Howard, J., Sch&#228;ffer, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LED+illumination+for+video-enhanced+DIC+imaging+of+single+microtubules.">LED illumination for video-enhanced DIC imaging of single microtubules.</a> J Microsc. 226 (Pt 1), 1-5 (2007).</li><li>Andrecka, J., Ortega Arroyo, J., Lewis, K., Cross, R. A., Kukura, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Label-free+Imaging+of+Microtubules+with+Sub-nm+Precision+Using+Interferometric+Scattering+Microscopy.">Label-free Imaging of Microtubules with Sub-nm Precision Using Interferometric Scattering Microscopy.</a> Biophysical Journal. 110 (1), 214-217 (2016).</li><li>Koch, M. D., Rohrbach, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Label-free+Imaging+and+Bending+Analysis+of+Microtubules+by+ROCS+Microscopy+and+Optical+Trapping.">Label-free Imaging and Bending Analysis of Microtubules by ROCS Microscopy and Optical Trapping.</a> Biophysical Journal. 114 (1), 168-177 (2018).</li><li>Kandel, M. E., Teng, K. W., Selvin, P. R., Popescu, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Label-Free+Imaging+of+Single+Microtubule+Dynamics+Using+Spatial+Light+Interference+Microscopy.">Label-Free Imaging of Single Microtubule Dynamics Using Spatial Light Interference Microscopy.</a> ACS Nano. 11 (1), 647-655 (2017).</li><li>Curtis, A. S. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Mechanism+of+Adhesion+of+Cells+to+Glass.">The Mechanism of Adhesion of Cells to Glass.</a> The Journal of Cell Biology. 20 (2), 199-215 (1964).</li><li>Weber, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=[2]+Reflection+interference+contrast+microscopy.">[2] Reflection interference contrast microscopy.</a> Methods in Enzymology. 361, 34-47 (2003).</li><li>Gell, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+13+-+Microtubule+Dynamics+Reconstituted+In+Vitro+and+Imaged+by+Single-Molecule+Fluorescence+Microscopy.">Chapter 13 - Microtubule Dynamics Reconstituted In Vitro and Imaged by Single-Molecule Fluorescence Microscopy.</a> Methods in Cell Biology. 95, 221-245 (2010).</li><li>Nitzsche, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+14+-+Studying+Kinesin+Motors+by+Optical+3D-Nanometry+in+Gliding+Motility+Assays.">Chapter 14 - Studying Kinesin Motors by Optical 3D-Nanometry in Gliding Motility Assays.</a> Methods in Cell Biology. 95, 247-271 (2010).</li><li>Schiff, P. B., Fant, J., Horwitz, S. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Promotion+of+microtubule+assembly+in+vitro+by+taxol.">Promotion of microtubule assembly in vitro by taxol.</a> Nature. 277 (5698), 665-667 (1979).</li><li>Schindelin, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fiji:+an+open-source+platform+for+biological-image+analysis.">Fiji: an open-source platform for biological-image analysis.</a> Nature Methods. 9 (7), 676-682 (2012).</li><li>Mahamdeh, M., Simmert, S., Luchniak, A., Sch&#228;ffer, E., Howard, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Label-free+high-speed+wide-field+imaging+of+single+microtubules+using+interference+reflection+microscopy.">Label-free high-speed wide-field imaging of single microtubules using interference reflection microscopy.</a> Journal of Microscopy. 272 (1), 60-66 (2018).</li><li>Hyman, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=[39]+Preparation+of+modified+tubulins.">[39] Preparation of modified tubulins.</a> Methods in Enzymology. 196, 478-485 (1991).</li><li>Ruhnow, F., Zwicker, D., Diez, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tracking+Single+Particles+and+Elongated+Filaments+with+Nanometer+Precision.">Tracking Single Particles and Elongated Filaments with Nanometer Precision.</a> Biophysical Journal. 100 (11), 2820-2828 (2011).</li><li>Mahamdeh, M., Sch&#228;ffer, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optical+tweezers+with+millikelvin+precision+of+temperature-controlled+objectives+and+base-pair+resolution.">Optical tweezers with millikelvin precision of temperature-controlled objectives and base-pair resolution.</a> Optics Express. 17 (19), 17190-17199 (2009).</li><li>Kim, K., Saleh, O. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stabilizing+method+for+reflection+interference+contrast+microscopy.">Stabilizing method for reflection interference contrast microscopy.</a> Applied Optics. 47 (12), 2070-2075 (2008).</li><li>Ortega Arroyo, J., Cole, D., Kukura, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interferometric+scattering+microscopy+and+its+combination+with+single-molecule+fluorescence+imaging.">Interferometric scattering microscopy and its combination with single-molecule fluorescence imaging.</a> Nature Protocols. 11 (4), 617-633 (2016).</li><li>Carter, A. R., King, G. M., Ulrich, T. A., Halsey, W., Alchenberger, D., Perkins, T. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stabilization+of+an+optical+microscope+to+0.1+nm+in+three+dimensions.">Stabilization of an optical microscope to 0.1 nm in three dimensions.</a> Appl Opt. 46 (3), 421-427 (2007).</li><li>Limozin, L., Sengupta, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+Reflection+Interference+Contrast+Microscopy+(RICM)+in+Soft+Matter+and+Cell+Adhesion.">Quantitative Reflection Interference Contrast Microscopy (RICM) in Soft Matter and Cell Adhesion.</a> ChemPhysChem. 10 (16), 2752-2768 (2009).</li></ol>

The authors have no conflicts of interest to disclose.

This protocol demonstrated the successful use of IRM for imaging and measurement of the microtubule dynamics. Care should be given to correctly set the illumination numerical aperture as it has the strongest impact on image contrast. Also, using high numerical aperture (NA) objectives is important for getting high resolution/high contrast images, as higher NA objective have higher light collecting power compared to low NA objectives. The cleaner the surface and solutions used the lower the noise as dirt ends up attaching to the surface and adding (over the course of the experiment) speckle like noise to the images. Acquisition of a background image is important as well as it removes illumination inhomogeneities, static noise and surface irregularities.
A recommended modification is to introduce a long pass filter (&#62;600 nm) in the illumination path. The spectrum of white light sources typically contains wavelengths in the UV which can damage microtubules. In addition, using long wave length for IRM comes in handy when combining IRM with fluorescence (e.g., when studying the effect of microtubule associated proteins (MAPs) on microtubule dynamics). Be aware that when imaging for expended period of times, sample drift (especially along the optical axis) decreases image contrast due to the deviation of the image plane from the background plane. Modern microscopes are often equipped with stabilization mechanisms (e.g., perfect focus (Nikon), Definite focus.2 (Zeiss), IX3-ZDC2 (Olympus)). An alternative solution is to thermally stabilize the setup either passively or actively18 or by correcting for drift19,20,21. Finally, microtubule contrast can be increased by reducing the size of field diaphragm (a 70% opening is good choice as it is a balance between increasing contrast and field of view size)15.
While IRM is suitable for imaging microtubules it is not sensitive enough to detect single proteins. For such application, iSCAT is a more suitable technique. Similarly, fluorescence and iSCAT are better suited if tracking precision of less than 10 nm is needed. For IRM, the measured length tracking precision is ~20 nm as shown in Figure 7.
Use of IRM in surface assays can go beyond microtubules; for example, molecular motors can be labelled with gold nanoparticles and tracked as they interact with microtubules. In addition a more advanced form of IRM known as reflective interference contrast microscopy (RICM)22 can, in principle, be used to further enhance microtubules contrast and obtain higher tracking precision.

Label-free imaging of microtubules is of interest as it circumvents the need for fluorescent labeling of tubulin to generate contrast in the images. Fluorescent labeling has several drawbacks: it not feasible if the protein concentration is low1 and photobleaching and photodamage limit the observation time. Several techniques have been used to image label-free microtubules, including video-enhanced differential interference contrast microscopy (DIC) and darkfield microscopy2,3,4,5. Recently, interferometric scattering microscopy (iSCAT)6, rotating-coherent-scattering microscopy (ROCS)7 and spatial light interference microscopy (SLIM)8, have also been used. All these techniques are capable of imaging microtubules and have proved to be valuable for studying microtubule dynamics. However, each have their own limitations. In DIC the contrast depends on the angle between the microtubule and the Nomarski prism axis. &#160;In darkfield, the microtubule signal is degraded by scattered light from impurities or surfaces defects. Though iSCAT exhibits extraordinary sensitivity (down to single proteins) and ROCS can image microtubules deeper into the sample, both methods are technically demanding, requiring laser scanners.
This protocol demonstrates how interference reflection microscopy (IRM)9, 10 can be set up as an alternative technique for label-free imaging of microtubules. IRM is easy to implement as it requires only the addition of an inexpensive 50/50 mirror to a standard fluorescent microscope. When used in conjunction with the software described here, IRM produces high contrast microtubule images, can image large fields of view at high speed, requires a onetime alignment, and can easily be combined with other techniques such as fluorescence imaging.

<table>
	<tbody>
		<tr>
			<td>Microscope</td>
			<td>Nikon</td>
			<td>Ti-Eclipse</td>
			<td>An inverted microscope used for perfoming the expriments</td>
		</tr>
		<tr>
			<td>50/50 beam splitter</td>
			<td>Chroma</td>
			<td>21000</td>
			<td>When buying make sure to choose the splitter dimensions that fit the cube used in the microscope</td>
		</tr>
		<tr>
			<td>NIKON PLAN FLUOR 100X/0.5-1.3 Iris objective</td>
			<td>Nikon</td>
			<td>MRH02902</td>
			<td>Imaging objective. This objective has a NA adjusting iris that was opened to NA 1.3</td>
		</tr>
		<tr>
			<td>Mucasol universal detergent</td>
			<td>Sigma-aAldrich</td>
			<td>Z637181-2L</td>
			<td>Used for cleaning coverslips and slides</td>
		</tr>
		<tr>
			<td>plastic paraffin film (commerical name Parafilm M)</td>
			<td>Sigma-aAldrich</td>
			<td>P7793</td>
			<td>Used for constructing flow channels</td>
		</tr>
		<tr>
			<td>Anti-TAMRA antibody</td>
			<td>Invitrogen</td>
			<td>A-6397</td>
			<td>Used to bind TAMRA labeled molecules (e.g. microtubules) to the sample surface. RRID (AB_2536196)</td>
		</tr>
		<tr>
			<td>Poloxamer 407 (commercial name Pluronic F-127)</td>
			<td>Sigma-aAldrich</td>
			<td></td>
			<td>Used for blocking the channel surface to prevent nonspecific binding</td>
		</tr>
		<tr>
			<td>40 nm gold nanoparticles</td>
			<td>Sigma-aAldrich</td>
			<td>753637</td>
			<td>Used as a control sample</td>
		</tr>
		<tr>
			<td>20 nm gold nanoparticles</td>
			<td>Sigma-aAldrich</td>
			<td>753610</td>
			<td>Used as a control sample</td>
		</tr>
		<tr>
			<td>Zyla 4.2 Camera</td>
			<td>Andor</td>
			<td>Zyla 4.2</td>
			<td>2048x2048 pixles (6.5&#181;m pixel size) with quantum efficiency of 72% and 16bit dynamic range</td>
		</tr>
		<tr>
			<td>Feista tracking software</td>
			<td></td>
			<td></td>
			<td>https://www.bcube-dresden.de/fiesta/wiki/FIESTA</td>
		</tr>
		<tr>
			<td>Stabilized microtubles</td>
			<td></td>
			<td></td>
			<td>prepared in house (see references in text)</td>
		</tr>
	</tbody>
</table>

implementation of interference reflection microscopy for label-free, high-speed imaging of microtubules

There are several methods for visualizing purified biomolecules near surfaces. Total-internal reflection fluorescence (TIRF) microscopy is a commonly used method, but has the drawback that it requires fluorescent labeling, which can interfere with the activity of the molecules. Also, photobleaching and photodamage are concerns. In the case of microtubules, we have found that images of similar quality to TIRF can be obtained using interference reflection microscopy (IRM). This suggests that IRM might be a general technique for visualizing the dynamics of large biomolecules and oligomers in vitro. In this paper, we show how a fluorescence microscope can be modified simply to obtain IRM images. IRM is easier and considerably cheaper to implement than other contrast techniques such as differential interference contrast microcopy or interferometric scattering microscopy. It is also less susceptible to surface defects and solution impurities than darkfield microscopy. Using IRM, together with the image analysis software described in this paper, the field of view and the frame rate is limited only by the camera; with a sCMOS camera and&#160;wide-field&#160;illumination&#160;microtubule length can be measured with precision up to 20 nm with a bandwidth of 10 Hz.&#160;

As mentioned above, with a well aligned microscope, microtubules should be visible without background subtraction (Figure 4A). Subtracting the background (Figure 4B) enhances the contrast of microtubule (Figure 4C). To further enhance the contrast, averaging or Fourier filtering or a combination of both can be used (Figure 4D,F,E). The line scans in Figure 4G shows the incremental improvement of image quality. Notice the reduction of background noise with each processing step.
Examples of kymographs of microtubule dynamics generated from time-lapse movies are shown in Figure 5. The videos were acquired at two frame rates: 0.2 fps (slow) and 100 fps (fast). The former is suitable for measuring growth rates while the latter is more suitable for measuring shrinkage rate that is an order of magnitude faster than the growth rate.
For the case where gold nanoparticles are used for setting up the microscope, an example image is shown in Figure 6. Gold nanoparticles were passively attached to the surface. While 40 nm particles are recommended, it is also possible to image 20 nm particles, yet at a lower contrast.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59520/59520fig1.jpg" /> 
Figure 1. Schematic representation of IRM. (A) Epi-illumination from the light source passes through the aperture diaphragm before reaching the 50/50 mirror. The aperture diaphragm sets the beam width thus the illumination NA. The 50/50 mirror partially reflects the light up to the objective to illuminate the sample. Light reflected from the sample is collected and then projected onto the camera chip (by the tube lens) where it interferes to generate the image. Image contrast is the result of the interference between the light reflected from the glass/water interface (I1) and the light reflected from the water/microtubule interface (I2). Depending on the microtubule/surface distance (h), the optical path difference between I1 and I2 will result in a constructive (bright signal) or destructive (dark signal) or anything in between. For example, if light with a wavelength of 600 nm is used for imaging, the contrast will switch between dark and bright when the microtubule height changes by about 100 nm. The asterisk indicate conjugate planes &#160;(modified from15). (B) Example of the 50/50 mirror installation. A suitable filter cube was opened and the mirror was inserted where a dichroic mirror usually sits. The mirror was oriented as per manufacturer instructions. Then the cube was inserted in the filter wheel which was inserted back to the microscope (not shown). During the installation, gloves were used, and the mirror was only held by the edges. <a href="https://www.jove.com/files/ftp_upload/59520/59520fig1large.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/59520/59520fig2.jpg" /> 
Figure 2. Optimal Aperture diaphragm setting. (A) Same field of view was imaged at different aperture diaphragm openings without background subtraction. Visually, the contrast increased as the size of the aperture diaphragm increased till it reached a plateau and started to degrade afterwards. This was confirmed by (B) SBR measurements of background subtracted images. Error bars are standard deviation. &#160;Scale bars are 500 &#181;m (AD) and 3 &#181;m (microtubules). <a href="https://www.jove.com/files/ftp_upload/59520/59520fig2large.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/59520/59520fig3.jpg" /> 
Figure 3. Measuring signal-to-background noise ratio. Microtubules were isolated in regions of interest. Each region of interest was thresholded to separate the microtubule from the background. The average microtubule signal was obtained from a line scan across the microtubule. The scan line width was set to equal the microtubule length. This way, every point on the scan is an average of the signals of all pixels along the microtubule axis that are parallel to that point. The background noise is the standard deviation of all the pixels below threshold cut off.&#160; <a href="https://www.jove.com/files/ftp_upload/59520/59520fig3large.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/59520/59520fig4.jpg" /> 
Figure 4. Image processing. After acquiring raw images (A), the background (B) was subtracted (C) to enhance the microtubule contrast. To further improve the contrast the images were either averaged (D) or Fourier filtered (E) or both (F). The line scans (G), whose location is indicated by the dashed red line in (A) are color matched to the various images in (A) to (F). The numbers at the lower corner are average SBRs measured for the whole field of view. The scale bar is 5 &#181;m (modified from15) . <a href="https://www.jove.com/files/ftp_upload/59520/59520fig4large.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/59520/59520fig5.jpg" /> 
Figure 5. Examples of kymographs. (A) Kymograph examples of microtubule dynamics generated from time-lapse movies acquired at 0.2 fps. (B) Kymograph depicting an example of a shrinkage event generated from a movie acquired at 100 fps. Dashed lines mark the seeds. <a href="https://www.jove.com/files/ftp_upload/59520/59520fig5large.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/59520/59520fig6.jpg" /> 
Figure 6. Example of gold nanoparticles imaged with IRM. Gold nanoparticles of sizes 20 and 40 nm were passively attached to the surface. 10 images were acquired. After background subtraction, the images were averaged to enhance contrast. <a href="https://www.jove.com/files/ftp_upload/59520/59520fig6large.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/59520/59520fig7.jpg" /> 
Figure 7. Microtubule length Tracking precision in IRM images. Stabilized microtubules (i.e., fixed lengths) were imaged 200x at 100 fps then averaged to 10 fps to enhance contrast. Next, the microtubules&#8217; lengths were measured using Fiesta17 tracking software. For every microtubule the mean length and standard deviation were calculated as shown in the figure (dashed line represents the mean and solid red lines represents the standard deviation, length = 3971 &#177; 20 nm. The overall tracking precision was the average of the standard deviation of all tracked &#160;microtubules (n = 6 microtubules x 20 data points = 120 data points).&#160;<a href="https://www.jove.com/files/ftp_upload/59520/59520fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary&#160;File 1.&#160;<a href="https://www.jove.com/files/ftp_upload/59520/Multi_Kymo.ijm" target="_blank">Please click here to download this file.</a>
Supplementary&#160;File 2.&#160;<a href="https://www.jove.com/files/ftp_upload/59520/Kymo_Analysis.ijm" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about Implementation of Interference Reflection Microscopy for Label-free, High-speed Imaging of Microtubules at JoVE.com

Implementation of Interference Reflection Microscopy for Label-free, High-speed Imaging of Microtubules

This protocol is a guide for implementing interference reflection microscopy on a standard fluorescence microscope for label-free, high-contrast, high-speed imaging of microtubules using in vitro surfaces assays.

There are several methods for visualizing purified biomolecules near surfaces. Total-internal reflection fluorescence (TIRF) microscopy is a commonly used ...

implementation-interference-reflection-microscopy-for-label-free-high

Research

Education

JoVE Journal

JoVE Core

Cell Biology

Bioengineering

Unit 1

The Cytoskeleton II: Microtubules and Intermediate Filaments

SCIENTISTS IN ACTION

9.8K Views.  Yale University. This protocol is a guide for implementing interference reflection microscopy on a standard fluorescence microscope for label-free, high-contrast, high-speed imaging of microtubules using in vitro surfaces assays.

Video: Implementation of Interference Reflection Microscopy for Label-free, High-speed Imaging of Microtubules

Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy

Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, currently available routine methods require processing steps and alter sample integrity. Raman spectroscopy is a fast method that enables the measurement of biological samples without the need for further processing steps. This laser-based technology detects the inelastic scattering of monochromatic light.6 As every chemical vibration is assigned to a specific Raman band (wavenumber in cm-1), each biological sample features a typical spectral pattern due to their inherent biochemical composition.7-9 Within Raman spectra, the peak intensities correlate with the amount of the present molecular bonds.1 Similarities and differences of the spectral data sets can be detected by employing a multivariate analysis (e.g. principal component analysis (PCA)).10
Here, we perform Raman spectroscopy of living cells and native tissues. Cells are either seeded on glass bottom dishes or kept in suspension under normal cell culture conditions (37 &deg;C, 5% CO2) before measurement. Native tissues are dissected and stored in phosphate buffered saline (PBS) at 4 &deg;C prior measurements. Depending on our experimental set up, we then either focused on the cell nucleus or extracellular matrix (ECM) proteins such as elastin and collagen. For all studies, a minimum of 30 cells or 30 random points of interest within the ECM are measured. Data processing steps included background subtraction and normalization.

Raman spectroscopy is a suitable technique for the non-contact, label-free analysis of living cells, tissue-engineered constructs and native tissues. Source-specific spectral fingerprints can be generated and analyzed using multivariate analysis.

Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, ...

Visualization of Cortex Organization and Dynamics in Microorganisms, using Total Internal Reflection Fluorescence Microscopy

TIRF microscopy has emerged as a powerful imaging technology to study spatio-temporal dynamics of fluorescent molecules in vitro and in living cells1. The optical phenomenon of total internal reflection occurs when light passes from a medium with high refractive index into a medium with low refractive index at an angle larger than a characteristic critical angle (i.e. closer to being parallel with the boundary). Although all light is reflected back under such conditions, an evanescent wave is created that propagates across and along the boundary, which decays exponentially with distance, and only penetrates sample areas that are 100-200 nm near the interface2. In addition to providing superior axial resolution, the reduced excitation of out of focus fluorophores creates a very high signal to noise ratios and minimizes damaging effects of photobleaching2,3. Being a widefield technique, TIRF also allows faster image acquisition than most scanning based confocal setups.
At first glance, the low penetration depth of TIRF seems to be incompatible with imaging of bacterial and fungal cells, which are often surrounded by thick cell walls. On the contrary, we have found that the cell walls of yeast and bacterial cells actually improve the usability of TIRF and increase the range of observable structures4-8. Many cellular processes can therefore be directly accessed by TIRF in small, single-cell microorganisms, which often offer powerful genetic manipulation techniques. This allows us to perform in vivo biochemistry experiments, where kinetics of protein interactions and activities can be directly assessed in living cells.
We describe here the individual steps required to obtain high quality TIRF images for Saccharomyces cerevisiae or Bacillus subtilis cells. We point out various problems that can affect TIRF visualization of fluorescent probes in cells and illustrate the procedure with several application examples. Finally, we demonstrate how TIRF images can be further improved using established image restoration techniques.

Total Internal Reflection Fluorescence (TIRF) microscopy is a powerful approach to observe structures close to the cell surface at high contrast and temporal resolution. We demonstrate how TIRF can be employed to study protein dynamics at the cortex of cell wall-enclosed bacterial and fungal cells.

TIRF microscopy has emerged as  a powerful imaging technology to study spatio-temporal dynamics of fluorescent molecules  in vitro and in living cells1. ...

A Microfluidic-based Electrochemical Biochip for Label-free DNA Hybridization Analysis

Miniaturization of analytical benchtop procedures into the micro-scale provides significant advantages in regards to reaction time, cost, and integration of pre-processing steps. Utilizing these devices towards the analysis of DNA hybridization events is important because it offers a technology for real time assessment of biomarkers at the point-of-care for various diseases. However, when the device footprint decreases the dominance of various physical phenomena increases. These phenomena influence the fabrication precision and operation reliability of the device. Therefore, there is a great need to accurately fabricate and operate these devices in a reproducible manner in order to improve the overall performance. Here, we describe the protocols and the methods used for the fabrication and the operation of a microfluidic-based electrochemical biochip for accurate analysis of DNA hybridization events. The biochip is composed of two parts: a microfluidic chip with three parallel micro-channels made of polydimethylsiloxane (PDMS), and a 3 x 3 arrayed electrochemical micro-chip. The DNA hybridization events are detected using electrochemical impedance spectroscopy (EIS) analysis. The EIS analysis enables monitoring variations of the properties of the electrochemical system that are dominant at these length scales. With the ability to monitor changes of both charge transfer and diffusional resistance with the biosensor, we demonstrate the selectivity to complementary ssDNA targets, a calculated detection limit of 3.8 nM, and a 13% cross-reactivity with other non-complementary ssDNA following 20 min&#160;of incubation. This methodology can improve the performance of miniaturized devices by elucidating on the behavior of diffusion at the micro-scale regime and by enabling the study of DNA hybridization events.

We present a microfluidic-based electrochemical biochip for DNA hybridization detection. Following ssDNA probe functionalization, the specificity, sensitivity, and detection limit are studied with complementary and non-complementary ssDNA targets. Results illustrate the influence of the DNA hybridization events on the electrochemical system, with a detection limit of 3.8 nM.

Miniaturization of analytical benchtop procedures into the micro-scale provides significant advantages in regards to reaction time, cost, and integration ...

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning of such signaling can lead to many disorders. To understand cell-to-cell signaling, it is essential to study the spatial and temporal nature of the secreted molecules from the cell without disturbing the local environment. Various assays have been developed to study protein secretion, however, these methods are typically based on fluorescent probes which disrupt the relevant signaling pathways. To overcome this limitation, a label-free technique is required.
In this paper, we describe the fabrication and application of a label-free localized surface plasmon resonance imaging (LSPRi) technology capable of detecting protein secretions from a single cell. The plasmonic nanostructures are lithographically patterned onto a standard glass coverslip and can be excited using visible light on commercially available light microscopes. Only a small fraction of the coverslip is covered by the nanostructures and hence this technique is well suited for combining common techniques such as fluorescence and bright-field imaging.
A multidisciplinary approach is used in this protocol which incorporates sensor nanofabrication and subsequent biofunctionalization, binding kinetics characterization of ligand and analyte, the integration of the chip and live cells, and the analysis of the measured signal. As a whole, this technology enables a general label-free approach towards mapping cellular secretions and correlating them with the responses of nearby cells.

Inter-cellular communication is critical for controlling various physiological activities within and outside the cell. This paper describes a protocol for measuring the spatio-temporal nature of single cell secretions. To achieve this, a multidisciplinary approach is used which integrates label-free nanoplasmonic sensing with live cell imaging.

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning ...

Label-free Single Molecule Detection Using Microtoroid Optical Resonators

Detecting small concentrations of molecules down to the single molecule limit has impact on areas such as early detection of disease, and fundamental studies on the behavior of molecules. Single molecule detection techniques commonly utilize labels such as fluorescent tags or quantum dots, however, labels are not always available, increase cost and complexity, and can perturb the events being studied. Optical resonators have emerged as a promising means to detect single molecules without the use of labels. Currently the smallest particle detected by a non-plasmonically-enhanced bare optical resonator system in solution is a 25 nm polystyrene sphere1. We have developed a technique known as Frequency Locking Optical Whispering Evanescent Resonator (FLOWER) that can surpass this limit and achieve label-free single molecule detection in aqueous solution2. As signal strength scales with particle volume, our work represents a &#62; 100x improvement in the signal to noise ratio (SNR) over the current state of the art. Here the procedures behind FLOWER are presented in an effort to increase its usage in the field.

We have developed a label-free biosensing system based on optical resonator technology known as Frequency Locking Optical Whispering Evanescent Resonator (FLOWER) that is capable of detecting single molecules in solution. Here the procedures behind this work are described and presented.

Detecting small concentrations of molecules down to the single molecule limit has impact on areas such as early detection of disease, and fundamental ...

High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis

The goal of this protocol is to build a parallel high-extinction and high-resolution optical Brillouin spectrometer. Brillouin spectroscopy is a non-contact measurement method that can be used to obtain direct readouts of viscoelastic material properties. It has been a useful tool in material characterization, structural monitoring and environmental sensing. In the past, Brillouin spectroscopy has usually employed scanning Fabry-Perot etalons to perform spectral analysis. This process requires high illumination power and long acquisition times, making the technique unsuitable for biomedical applications. A recently introduced novel spectrometer overcomes this challenge by employing two VIPAs in a cross-axis configuration. This innovation enables sub-Gigahertz (GHz) resolution spectral analysis with sub-second acquisition time and illumination power within the safety limits of biological tissue. The multiple new applications facilitated by this improvement are currently being explored in biological research and clinical application.

Here we present a protocol to build a rapid Brillouin spectrometer. Cascading virtually imaged phase array (VIPA) etalons achieve a measurement speed more than 1,000 times faster than traditional scanning Fabry-Perot spectrometers. This improvement provides the means for Brillouin analysis of tissue and biomaterials at low power levels in vivo.

The goal of this protocol is to build a parallel high-extinction and high-resolution optical Brillouin spectrometer. Brillouin spectroscopy is a ...

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Optical super-resolution imaging with structured illumination microscopy (SIM) is a key technology for the visualization of processes at the molecular level in the chemical and biomedical sciences. Although commercial SIM systems are available, systems that are custom designed in the laboratory can outperform commercial systems, the latter typically designed for ease of use and general purpose applications, both in terms of imaging fidelity and speed. This article presents an in-depth guide to building a SIM system that uses total internal reflection (TIR) illumination and is capable of imaging at up to 10 Hz in three colors at a resolution reaching 100 nm. Due to the combination of SIM and TIRF, the system provides better image contrast than rival technologies. To achieve these specifications, several optical elements are used to enable automated control over the polarization state and spatial structure of the illumination light for all available excitation wavelengths. Full details on hardware implementation and control are given to achieve synchronization between excitation light pattern generation, wavelength, polarization state, and camera control with an emphasis on achieving maximum acquisition frame rate. A step-by-step protocol for system alignment and calibration is presented and the achievable resolution improvement is validated on ideal test samples. The capability for video-rate super-resolution imaging is demonstrated with living cells.

This article provides an in depth guide for the assembly and operation of a structured illumination microscope operating with total internal reflection fluorescence illumination (TIRF-SIM) to image dynamic biological processes with optical super-resolution in multiple colors.

Optical super-resolution imaging with structured illumination microscopy (SIM) is a key technology for the visualization of processes at the molecular ...

PIP-on-a-chip: A Label-free Study of Protein-phosphoinositide Interactions

Numerous cellular proteins interact with membrane surfaces to affect essential cellular processes. These interactions can be directed towards a specific lipid component within a membrane, as in the case of phosphoinositides (PIPs), to ensure specific subcellular localization and/or activation. PIPs and cellular PIP-binding domains have been studied extensively to better understand their role in cellular physiology. We applied a pH modulation assay on supported lipid bilayers (SLBs) as a tool to study protein-PIP interactions. In these studies, pH sensitive ortho-Sulforhodamine B conjugated phosphatidylethanolamine is used to detect protein-PIP interactions. Upon binding of a protein to a PIP-containing membrane surface, the interfacial potential is modulated (i.e. change in local pH), shifting the protonation state of the probe. A case study of the successful usage of the pH modulation assay is presented by using phospholipase C delta1 Pleckstrin Homology (PLC-&#948;1 PH) domain and phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) interaction as an example. The apparent dissociation constant (Kd,app) for this interaction was 0.39 &#177; 0.05 &#181;M, similar to Kd,app values obtained by others. As previously observed, the PLC-&#948;1 PH domain is PI(4,5)P2 specific, shows weaker binding towards phosphatidylinositol 4-phosphate, and no binding to pure phosphatidylcholine SLBs. The PIP-on-a-chip assay is advantageous over traditional PIP-binding assays, including but not limited to low sample volume and no ligand/receptor labeling requirements, the ability to test high- and low-affinity membrane interactions with both small and large molecules, and improved signal to noise ratio. Accordingly, the usage of the PIP-on-a-chip approach will facilitate the elucidation of mechanisms of a wide range of membrane interactions. Furthermore, this method could potentially be used in identifying therapeutics that modulate protein&#39;s capacity to interact with membranes.

Here we present a supported lipid bilayer in the context of a microfluidic platform to study protein-phosphoinositide interactions using a label-free method based on pH modulation.

Numerous cellular proteins interact with membrane surfaces to affect essential cellular processes. These interactions can be directed towards a specific ...

Mammalian Cell Division in 3D Matrices via Quantitative Confocal Reflection Microscopy

The study of how mammalian cell division is regulated in a 3D environment remains largely unexplored despite its physiological relevance and therapeutic significance. Possible reasons for the lack of exploration are the experimental limitations and technical challenges that render the study of cell division in 3D culture inefficient. Here, we describe an imaging-based method to efficiently study mammalian cell division and cell-matrix interactions in 3D collagen matrices. Cells labeled with fluorescent H2B are synchronized using the combination of thymidine blocking and nocodazole treatment, followed by a mechanical shake-off technique. Synchronized cells are then embedded into a 3D collagen matrix. Cell division is monitored using live-cell microscopy. The deformation of collagen fibers during and after cell division, which is an indicator of cell-matrix interaction, can be monitored and quantified using quantitative confocal reflection microscopy. The method provides an efficient and general approach to study mammalian cell division and cell-matrix interactions in a physiologically relevant 3D environment. This approach not only provides novel insights into the molecular basis of the development of normal tissue and diseases, but also allows for the design of novel diagnostic and therapeutic approaches.

This protocol efficiently studies mammalian cell division in 3D collagen matrices by integrating synchronization of cell division, monitoring of division events in 3D matrices using live-cell imaging technique, time-resolved confocal reflection microscopy and quantitative imaging analysis.

The study of how mammalian cell division is regulated in a 3D environment remains largely unexplored despite its physiological relevance and therapeutic ...

Assessing Collagen and Elastin Pressure-dependent Microarchitectures in Live, Human Resistance Arteries by Label-free Fluorescence Microscopy

The pathogenic contribution of resistance artery remodeling is documented in essential hypertension, diabetes and the metabolic syndrome. Investigations and development of microstructurally motivated mathematical models for understanding the mechanical properties of human resistance arteries in health and disease have the potential to aid understanding how disease and medical treatments affect the human microcirculation. To develop these mathematical models, it is essential to decipher the relationship between the mechanical and microarchitectural properties of the microvascular wall. In this work, we describe an ex vivo method for passive mechanical testing and simultaneous label-free three-dimensional imaging of the microarchitecture of elastin and collagen in the arterial wall of isolated human resistance arteries. The imaging protocol can be applied to resistance arteries of any species of interest. Image analyses are described for quantifying i) pressure-induced changes in internal elastic lamina branching angles and adventitial collagen straightness using Fiji and ii) collagen and elastin volume densities determined using Ilastik software. Preferably all mechanical and imaging measurements are performed on live, perfused arteries, however, an alternative approach using standard video-microscopy pressure myography in combination with post-fixation imaging of re-pressurized vessels is discussed. This alternative method provides users with different options for analysis approaches. The inclusion of the mechanical and imaging data in mathematical models of the arterial wall mechanics is discussed, and future development and additions to the protocol are proposed.

We describe simultaneous mechanical testing and 3D-imaging of the arterial wall of isolated, live human resistance arteries, and Fiji and Ilastik image analyses for the quantification of elastin and collagen spatial organization and volume densities. We discuss the use of these data in mathematical models of arterial wall mechanics.

The pathogenic contribution of resistance artery remodeling is documented in essential hypertension, diabetes and the metabolic syndrome. Investigations ...