The development of this protocol was supported by grants from the European Research Council (Advanced Grant TOPAS to M.J.L.) and the Deutsche Forschungsgemeinschaft (Grants CA 1014/1-1 to D.C. and SFB487 to M.J.L.). T.S. was supported by the Alexander von Humboldt Foundation.

1. Sample Preparation
<ol>
	<li>Coverslip cleaning 
	NOTE: Work under a fume hood.
	<ol>
		<li>Use clean tweezers to place glass coverslips (24 mm diameter) into a coverslip holder that separates individual coverslips.</li>
		<li>Put the holder with coverslips into a beaker, and add chloroform until the coverslips are covered. Cover the beaker with aluminum foil to reduce evaporation and sonicate in a bath sonicator for 1 hr at RT. Take the coverslip holder out of the beaker and let the coverslips dry.</li>
		<li>Repeat step 1.1.2 with 5M NaOH solution instead of chloroform.</li>
		<li>Take the coverslip holder into a new beaker and wash three times with distilled water. Put cleaned coverslips in a glass cell culture plate filled with 100% ethanol.</li>
	</ol>
	</li>
	<li>Preparation of calibration samples
	<ol>
		<li>Dissolve fluorescent dye in appropriate solvent.</li>
		<li>Prepare a 1:10 serial dilution of the fluorescent dye ranging from 1 pM to 1 nM in filter sterilized (0.22 &#181;m) water.</li>
		<li>Take cleaned coverslips stored in 100% ethanol and wash with filter-sterilized water. Spot 20 &#181;l of each fluorescent dye dilution on a separate cleaned coverslip. Let the coverslips dry under a sterile hood. Protect the coverslips from light and dust until use. Use these samples to estimate the intensity of single fluorescent molecules (see step 3).</li>
	</ol>
	</li>
	<li>Transfection
	<ol>
		<li>Culture CHO cells in 1:1 Dulbecco&#39;s modified Eagle medium/nutrient mixture F-12 (DMEM/F12) supplemented with 10% fetal bovine serum (FBS), 100 U/ml penicillin and 100 &#181;g/ml streptomycin at 37 &#176;C, in 5% CO2. NOTE: Use phenol-red free media throughout the experiment to minimize autofluorescence.</li>
		<li>Take cleaned coverslips from 100% ethanol solution, wash them with sterile phosphate-buffered saline (PBS), and place one coverslip into each well of a 6 well cell culture plate.</li>
		<li>Trypsinize, count and seed CHO cells at a density of 3 x 105 cells/well in the 6-well cell culture plate containing the coverslips. Let the cells grow in an incubator (37 &#176;C, 5% CO2) for 24 hr in order to achieve approx. 80% confluency, which is the optimal cell density for transfection.</li>
		<li>For each well, dilute 2 &#181;g of the desired plasmid DNA (e.g., SNAP-tagged &#946;2-adrenergic receptor) and 6 &#181;l Lipofectamine 2000 in two separate tubes containing 500 &#181;l OptiMem medium. Incubate at RT for 5 min.</li>
		<li>Combine the solutions from step 1.3.4 into one tube and mix to obtain a transfection mixture. Incubate the transfection mixture at RT for 20 min.</li>
		<li>During the incubation (1.3.5), take the CHO cells and wash twice with pre-warmed (37 &#176;C) PBS. Replace PBS with 1 ml/well of phenol red-free DMEM/F12 medium supplemented with 10% FBS but no antibiotics.</li>
		<li>Add the entire transfection mixture (1 ml) from step 1.3.5 dropwise to each well, and gently rock the plate back and forth to ensure complete mixing.</li>
		<li>Incubate for 2 to 4 hr at 37 &#176;C, in 5% CO2 and proceed immediately afterwards to the next step. NOTE: These transfection conditions have been optimized to achieve receptor densities &#60;0.45 particle/&#181;m2, which are suitable for single-molecule imaging. Adjustments might be required when using different cells, constructs or reagents.</li>
	</ol>
	</li>
	<li>Protein labeling
	<ol>
		<li>Dilute 1 &#181;l of fluorophore-BG stock solution in 1 ml DMEM/F12 medium supplemented with 10% FBS to obtain a final concentration of 1 &#181;M. Take the transfected cells from the incubator and wash twice with prewarmed (37 &#176;C) PBS. Replace PBS with 1 ml of 1 &#181;M fluorophore-BG solution and incubate for 20 min at 37 &#176;C 5% CO2 in an incubator.</li>
		<li>After the incubation, wash the cells three times with DMEM/F12 medium supplemented with 10% FBS, each time followed by 5 min incubation at 37 &#176;C. Take a coverslip (with labeled cells) with tweezers and place it into an imaging chamber.</li>
		<li>Wash twice with 300 &#181;l imaging buffer. Add 300 &#181;l of fresh imaging buffer and proceed immediately to imaging (Part 2).</li>
	</ol>
	</li>
</ol>
2. Image Acquisition
NOTE: Use a total internal reflection fluorescence (TIRF) microscope, equipped with an oil-immersion high numerical aperture objective (e.g., 100X magnification/1.46 numerical aperture), suitable lasers (e.g., 405 nm, 488 nm, 561 nm and 645 nm diode lasers), an electron multiplying charge coupled device (EMCCD) camera, an incubator and a temperature control to visualize single fluorescent molecules.
<ol>
	<li>Set the desired microscope parameters, i.e., laser line, TIRF angle (this parameter controls the penetration depth of the evanescent field), exposure time, frame rate and number of images per movie10. Keep the heater/incubator and temperature control always on to avoid temperature drifts and moisture condensation.</li>
	<li>Put a drop of immersion oil on the 100X objective of the microscope. Place the imaging chamber with the labeled cells onto the specimen holder of the microscope, and bring the cells in focus using brightfield illumination.</li>
	<li>Switch to TIRF illumination. Keep laser power as low as possible to allow searching for the desired cell but at the same time minimizing photobleaching.</li>
	<li>Select the desired cell and fine adjust the focus. Set the laser power to a level that allows visualization of single fluorophores. Acquire image sequence and save raw image sequence file as .tiff.</li>
</ol>
3. Calibration (Single Fluorophores on Glass and Monomeric/dimeric Receptor Controls)
<ol>
	<li>Assemble each calibration sample prepared as described in 1.2 in the imaging chamber. Place each sample on the microscope and choose the sample containing well-separated diffraction-limited spots that bleach in a single step. NOTE: These spots represent single molecules of the fluorescent dye.</li>
	<li>Acquire TIRF image sequences as described in step 2. Important: the same imaging parameters must be used for all experiments, including the ones for calibration.</li>
	<li>Perform the detection and tracking analysis as detailed in 4.1 - 4.2. Extract the intensity of each particle as described in 4.2.6. From these data, calculate the mean (&#181;) and standard deviation (&#963;) of the intensity of single fluorophores.</li>
	<li>Optional: perform the same analysis on cells transfected with a monomeric cell-surface receptor (e.g., CD86), N-terminally tagged with either one or two copies of SNAP10 and labeled with the fluorophore-BG derivative. Follow the procedure described above for the single fluorophore on glass. Estimate the labeling efficiency as described in Calebiro, D. et al.10</li>
</ol>
4. Image Analysis
<ol>
	<li>Image sequence preparation
	<ol>
		<li>Use an image processing software (e.g.,&#160;ImageJ) to crop the images.</li>
		<li>Save individual frames as separate .tiff images in a new folder, indicating on each image the frame number.</li>
		<li>Measure the cell surface area by drawing a region of interest (ROI) along the contour of a cell and using the measure tool in ImageJ or a similar tool in another software. Use this value to calculate particle density by dividing the total number of particles at the beginning of the movie by the cell surface area.</li>
	</ol>
	</li>
	<li>Particle detection and tracking 
	NOTE: Use noncommercial software such as u-track13, working in Matlab environment, to automatically detect and track single receptor particles. 
	NOTE: The u-track algorithm is based on the multiple-hypothesis tracking approach. This approach links particles between frames by building cost matrices, where the individual probabilities that a given particle in one frame corresponds to a given particle in the next frame, appears, disappears or merges/splits with/from other particles are assigned. The solution that globally minimizes the costs, i.e., the one with the highest probability, is finally selected. This also allows tracking a temporarily disappearing particle, a typical phenomenon caused by fluorophore blinking. The latest version of u-track (2.1.0) has graphic user interfaces that facilitate the execution of these analyses.
	<ol>
		<li>From the Matlab command prompt, type &#8220;movieSelectorGUI&#8221; to open the movie selection interface. Follow the instructions to create a new movie database starting from the previously saved separate images (see 4.1.2).</li>
		<li>Provide the pixel size in nm, time interval in seconds, numerical aperture, camera bit depth and emission wavelength of the fluorophore, required for particle detection and tracking. Save the movie database.</li>
		<li>From the movie selection interface, run the analysis, choosing &#8220;single-particles&#8221; as type of objects. A new window will appear where the parameters used for particle detection and tracking can be defined. Begin with the default parameters. Later, adjust these parameters if the quality of the detection and/or tracking is not satisfactory (e.g., some particles are not detected or tracks are fragmented). Optional: under the tracking settings, check &#8220;Export tracking results to matrix format&#8221; to store the coordinates and amplitudes of all particles in a single matrix (field called &#8220;trackedFeaturedInfo&#8221;). For a detailed description of these parameters, refer to the u-track documentation.</li>
		<li>Run the detection algorithm. This algorithm automatically determine the location and intensity above background of each diffraction-limited spot (i.e., single receptors/receptor complexes) by fitting a two-dimensional Gaussian function with standard deviation equal to the point spread function of the microscope around local intensity maxima. Then, run the tracking algorithm. Store the results of the analyses in a .mat file.</li>
		<li>Use the &#8220;movieViewer&#8221; routine, contained in the u-track package, or similar custom ones to visualize the tracks and check the quality of the detection and tracking.</li>
		<li>Open the .mat file to see the position and amplitude (i.e., intensity) of the tracked particles at each frame. Data generated in step 4.2.4 are contained in the tracksCoordAmpCG field of the tracksFinal array and/or in trackedFeaturedInfo. From the total number of particles detected calculate the particle density dividing this value by the cell surface area measured at 4.1.3.</li>
		<li>Optional: Use the particle coordinates over time (see 4.2.6) to analyze the motion of the receptor particles. Calculate the mean square displacements (MSD) and diffusion coefficients (D) using Matlab or similar software. For each particle and every time interval (&#916;t) considered, calculate the mean square displacement (MSD) using the following formula: 
		<img align="middle" alt="Equation 1" fo:content-width="4in" src="/files/ftp_upload/51784/51784eq1.jpg" /> 
		where &#916;t is the time interval in frames, N is the number of steps analyzed, x and y are the particle&#8217;s x and y coordinates at the frame indicated by the index. Use the MSD over time plots to evaluate the type of motion of a given particle: Linear relationships indicate free diffusion (i.e., Brownian motion), a positive curvature (i.e., the curve looks like a parabola) suggests directed motion, a negative curvature is indicative of confined motion14. In case of freely diffusing particles, calculate the diffusion coefficient (D) of each particle by fitting the obtained MSD data with the following equation: 
		<img align="middle" alt="Equation 2" src="/files/ftp_upload/51784/51784eq2.jpg" /></li>
	</ol>
	</li>
	<li>Calculation of particle size with Gaussian fitting method 
	NOTE: Once the intensity distribution of calibration samples (single fluorophores on glass and/or fluorescently labeled monomeric receptors) is known, perform a mixed Gaussian fit on the distribution of particle intensities at the beginning of an image sequence to determine the size of receptor complexes (i.e., the number of receptors per particle)10. Perform these analyses using Matlab or similar software.
	<ol>
		<li>Calculate the intensity of each particle by averaging the intensity of the particle from the first frame to the frame before the first change in intensity occurred (in most cases a decrease due to photobleaching).</li>
		<li>Perform a mixed Gaussian fitting according the following equation: 
		<img align="middle" alt="Equation 3" fo:content-width="3in" src="/files/ftp_upload/51784/51784eq3.jpg" /> 
		where &#966;(i) is the frequency of particles having intensity i, n is the component number, &#945;n is a parameter that contributes to the height of component n, &#956; and &#963; are the mean and standard deviation of the intensity of reference single fluorophores (calculated as described in step 3). NOTE: Determine the maximal number of components (nmax) for each image sequence by progressively increasing nmax until the addition of a component does no longer produce a statistically better fitting, as judged by an F-test.</li>
		<li>Optional: Perform a mixed Gaussian fit on the intensity distribution obtained on the last frames of the movie (e.g., the last 60 frames of a 400 frame sequence). Replace &#956; and &#963; with the values obtained after this fitting, which provide refined estimates for those parameters, and repeat step 4.3.2.</li>
		<li>Calculate the area under the curve (AUC) of each component of the mixed Gaussian fit. Calculate the relative abundance of receptor particles of different size (i.e., monomer, dimer, trimer, etc.) by dividing the AUC value of each component by the AUC of the entire distribution.</li>
		<li>Optional: Use data from different cells and the corresponding particle densities (calculated as described in 4.2.6) to generate plots where the distribution of particles with different size is correlated with particle density10.</li>
	</ol>
	</li>
	<li>Calculation of particle size with step fitting method 
	NOTE: Use a step-fitting analysis as an alternative method to determine the size of receptor complexes10. The basis for this analysis is that the light-induced destruction (photobleaching) of a single fluorophore results in its instantaneous disappearance &#8211; thus particles containing n fluorophores are expected to progressively bleach producing an intensity profile with n steps.
	<ol>
		<li>Extract intensity profiles of each particle from the .mat file generated by u-track or similar detection/tracking software (see 4.2.6).</li>
		<li>Use a step-fitting algorithm, such as the one presented in ref. 10, to count the number of bleaching steps for each particle.</li>
		<li>Optional: use the results to generate distributions showing the relative abundance of receptor particles of different size and correlate them with particle density as previously described for the results of the mixed Gaussian fitting (see 4.3).</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Pierce, K. L., Premont, R. T., Lefkowitz, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Seven-transmembrane+receptors.">Seven-transmembrane receptors.</a> Nat Rev Mol Cell Biol. 3, 639-650 (2002).</li><li>Angers, S., Salahpour, A., Bouvier, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dimerization:+an+emerging+concept+for+G+protein-coupled+receptor+ontogeny+and+function.">Dimerization: an emerging concept for G protein-coupled receptor ontogeny and function.</a> Annu Rev Pharmacol Toxicol. 42, 409-435 (2002).</li><li>Ferr&#233;, S., 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=Building+a+new+conceptual+framework+for+receptor+heteromers.">Building a new conceptual framework for receptor heteromers.</a> Nat Chem Biol. 5, 131-134 (2009).</li><li>Milligan, G. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=protein-coupled+receptor+hetero-dimerization:+contribution+to+pharmacology+and+function.">protein-coupled receptor hetero-dimerization: contribution to pharmacology and function.</a> Br J Pharmacol. 158, 5-14 (2009).</li><li>Lohse, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dimerization+in+GPCR+mobility+and+signaling.">Dimerization in GPCR mobility and signaling.</a> Curr Opin Pharmacol. 10, 53-58 (2010).</li><li>Ulbrich, M. H., Isacoff, E. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Subunit+counting+in+membrane-bound+proteins.">Subunit counting in membrane-bound proteins.</a> Nat Methods. 4, 319-321 (2007).</li><li>Triller, A., Choquet, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=New+concepts+in+synaptic+biology+derived+from+single-molecule+imaging.">New concepts in synaptic biology derived from single-molecule imaging.</a> Neuron. 59, 359-374 (2008).</li><li>Hern, J. 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=Formation+and+dissociation+of+M1+muscarinic+receptor+dimers+seen+by+total+internal+reflection+fluorescence+imaging+of+single+molecules.">Formation and dissociation of M1 muscarinic receptor dimers seen by total internal reflection fluorescence imaging of single molecules.</a> Proc Natl Acad Sci U S A. 107, 2693-2698 (2010).</li><li>Kasai, R. S., 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=Full+characterization+of+GPCR+monomer-dimer+dynamic+equilibrium+by+single+molecule+imaging.">Full characterization of GPCR monomer-dimer dynamic equilibrium by single molecule imaging.</a> J Cell Biol. 192, 463-480 (2011).</li><li>Calebiro, D., 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=Single-molecule+analysis+of+fluorescently+labeled+G-protein-coupled+receptors+reveals+complexes+with+distinct+dynamics+and+organization.">Single-molecule analysis of fluorescently labeled G-protein-coupled receptors reveals complexes with distinct dynamics and organization.</a> Proc Natl Acad Sci U S A. 110, 743-748 (2013).</li><li>Keppler, 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=A+general+method+for+the+covalent+labeling+of+fusion+proteins+with+small+molecules+in+vivo.">A general method for the covalent labeling of fusion proteins with small molecules in vivo.</a> Nat Biotechnol. 21, 86-89 (2003).</li><li>Gautier, 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=An+engineered+protein+tag+for+multiprotein+labeling+in+living+cells.">An engineered protein tag for multiprotein labeling in living cells.</a> Chem Biol. 15, 128-136 (2008).</li><li>Jaqaman, K., 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=Robust+single-particle+tracking+in+live-cell+time-lapse+sequences.">Robust single-particle tracking in live-cell time-lapse sequences.</a> Nat Methods. 5, 695-702 (2008).</li><li>Saxton, M. 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The authors declare that they have no competing financial interests.

The described protocol allows analysis of the spatial arrangement, mobility and size of cell-surface receptor complexes at single-molecule level. Compared to the use of fluorescent proteins, labeling with small organic fluorophores, which are brighter and more photostable, has the advantage of permitting extended visualization of single receptor particles. Since extremely low expression levels are achieved (&#60;0.45 receptor particles/&#181;m2), the properties of receptors and other membrane proteins can be a...

Receptors located on the cell surface sense the extracellular environment and respond to a variety of stimuli, such as odorants, ions, small neurotransmitters and large protein hormones. The fluid nature of cellular membranes allows movements of receptors and other membrane proteins. This is essential for the formation of protein complexes and the occurrence of transient protein-protein interactions, such as those used by receptors to assemble into functional units and transduce signals into the cell interior. For instance, G-protein-coupled receptors (GPCRs), which constitute the largest family of cell-surface receptors1, have been suggested to form di-/oligomers, which appears to be involved in the fine-tuned regulation of signal transduction and might have important physiological and pharmacological consequences2-5.
Single-molecule microscopy has the great potential of directly visualizing with high spatiotemporal resolution the dynamic behavior of individual receptors located on the surface of living cells, including their association to form dimers and higher order molecular complexes6-10. This offers several advantages compared to standard biochemical and microscopy methods, which usually report the average behavior of thousands or millions of molecules.
Protein labeling with a sufficiently bright and photostable fluorophore is essential for single-molecule microscopy. This protocol takes advantage of the recently introduced SNAP tag11 to covalently attach small and bright organic fluorophores to cell-surface receptors. SNAP is a 20 kD protein tag derived from the human DNA repair enzyme O6-alkylguanine-DNA alkyltransferase, which can be irreversibly labeled with fluorophore-conjugated benzylguanine (fluorophore-BG) derivatives. CLIP, a further engineered tag derived from SNAP, can be instead labeled with fluorophore-conjugated benzylcytosine derivatives12.
The protocol reported in this manuscript explains how to transfect and label SNAP-tagged11 receptors with small organic fluorophores and use total internal reflection fluorescence (TIRF) microscopy to visualize single receptors or receptor complexes on the surface of living cells10. The reported protocol results in &#62;90% labeling efficiency of an extracellularly SNAP-tagged cell-surface protein10. Further information on how to use single-molecule data to analyze the size and mobility of receptor complexes, as well as to capture transient receptor-receptor interactions, is provided. A schematic workflow of the entire protocol is given in Figure 1. As an example, the transfection of Chinese Hamster Ovary (CHO) cells with SNAP-tagged G-protein-coupled receptors (GPCRs) followed by labeling with a fluorophore-BG derivative as well as its application to quantify and monitor receptor di-/oligomerization are described. This protocol can be extended to other cell-surface proteins and fluorescent tags (e.g., CLIP), as well as to other transfection and labeling methods.

<table border="0" cellpadding="0" cellspacing="0" width="882">
	<tbody>
		<tr height="69">
			<td height="69" style="height:69px;width:259px;">Chloroform</td>
			<td style="width:248px;">AppliChem GmbH</td>
			<td style="width:115px;">A1585</td>
			<td style="width:261px;">CAUTION: toxic and irritating substance as well as a possible carcinogen</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:259px;">NaOH</td>
			<td style="width:248px;">Sigma-Aldrich</td>
			<td style="width:115px;">S8045</td>
			<td style="width:261px;">CAUTION: strong base and highly corrosive reagent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Absolute ethanol</td>
			<td style="width:248px;">Sigma-Aldrich</td>
			<td style="width:115px;">32205</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:259px;">Glass coverslip&#160;</td>
			<td style="width:248px;">Marienfeld-Superior</td>
			<td style="width:115px;">111640</td>
			<td style="width:261px;">24 mm diameter, 0.13-0.16 mm thickness</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">0.2 mm sterile filter</td>
			<td style="width:248px;">Sarstedt</td>
			<td style="width:115px;">83.1826.001</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">CHO cells</td>
			<td style="width:248px;">ATCC, USA</td>
			<td style="width:115px;">ATCC CCL-61</td>
			<td style="width:261px;">Chinese hamster ovary cell line</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">6-well cell culture plare</td>
			<td style="width:248px;">Nunc</td>
			<td style="width:115px;">140675</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">DMEM/F-12 medium</td>
			<td style="width:248px;">GIBCO, Life Technologies</td>
			<td style="width:115px;">11039-021</td>
			<td style="width:261px;">Phenol-red free medium</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Fetal bovine serum&#160;</td>
			<td style="width:248px;">Biochrom</td>
			<td style="width:115px;">S 0115</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Penicillin - streptomycin&#160;</td>
			<td style="width:248px;">Pan Biotech GmbH</td>
			<td style="width:115px;">P06-07 100</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Trypsin-EDTA</td>
			<td style="width:248px;">Pan Biotech GmbH</td>
			<td style="width:115px;">P10-23100</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Lipofectamine 2000</td>
			<td style="width:248px;">Invitrogen, Life Technologies</td>
			<td style="width:115px;">11668-019</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Opti-MEM I Reduced Serum Medium</td>
			<td style="width:248px;">Invitrogen, Life Technologies</td>
			<td style="width:115px;">31985-047</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;">Fluorophore-conjugated benzylguanine&#160;</td>
			<td style="width:248px;">New England BioLabs</td>
			<td style="width:115px;">S9136S</td>
			<td style="width:261px;">SNAP-Surface Alexa Fluor 647. Make a 1 mM stock solution in DMSO. Store at -20&#176;C.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">DMSO</td>
			<td style="width:248px;">AppliChem GmbH</td>
			<td style="width:115px;">A1584</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="67">
			<td height="67" style="height:67px;width:259px;">Imaging buffer:</td>
			<td style="width:248px;"></td>
			<td style="width:115px;"></td>
			<td style="width:261px;">137 mM NaCl, 5.4 mM KCl, 2 mM CaCl2, 1 mM MgCl2, 10 mM HEPES, pH 7.3, sterile-filtered</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">&#160;&#160;&#160; NaCl</td>
			<td style="width:248px;">AppliChem GmbH</td>
			<td style="width:115px;">A1371</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">&#160;&#160;&#160; KCl</td>
			<td style="width:248px;">AppliChem GmbH</td>
			<td style="width:115px;">A3582</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:259px;">&#160;&#160;&#160; CaCl2</td>
			<td style="width:248px;">AppliChem GmbH</td>
			<td style="width:115px;">A2303</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:259px;">&#160;&#160;&#160; MgCl2</td>
			<td style="width:248px;">AppliChem GmbH</td>
			<td style="width:115px;">A3618</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">&#160;&#160;&#160; HEPES</td>
			<td style="width:248px;">AppliChem GmbH</td>
			<td style="width:115px;">A3724</td>
			<td style="width:261px;"></td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:259px;">Imaging chamber</td>
			<td style="width:248px;">Molecular Probes, Life Technologies</td>
			<td style="width:115px;">A-7816</td>
			<td style="width:261px;">Attofluor Cell Chamber, for microscopy</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">TIRF-M</td>
			<td style="width:248px;">Leica</td>
			<td style="width:115px;"></td>
			<td style="width:261px;">Model: DMI6000B</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">TIRF objective</td>
			<td style="width:248px;">Leica</td>
			<td style="width:115px;">11 506 249&#160;</td>
			<td style="width:261px;">HCX PL Apo 100x/1.46 Oil CORR&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">EM-CCD camera&#160;</td>
			<td style="width:248px;">Roper Scientific</td>
			<td style="width:115px;"></td>
			<td style="width:261px;">Photometrics Cascade 512B</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Temperature controller</td>
			<td style="width:248px;">Pecon</td>
			<td style="width:115px;"></td>
			<td style="width:261px;">Tempcontrol 37-2 digital</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">ImageJ software</td>
			<td style="width:248px;">NIH, USA</td>
			<td style="width:115px;"></td>
			<td style="width:261px;">http://rsbweb.nih.gov/ij</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:259px;">u-track software</td>
			<td style="width:248px;">Laboratory for computational cell biology, Dept. of Cell Biology, Harvard Medical School, USA</td>
			<td style="width:115px;"></td>
			<td style="width:261px;">http://lccb.hms.harvard.edu/software.html</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:259px;">Matlab software</td>
			<td style="width:248px;">The MathWorks, USA</td>
			<td style="width:115px;"></td>
			<td style="width:261px;"></td>
		</tr>
	</tbody>
</table>

high-resolution spatiotemporal analysis of receptor dynamics by single-molecule fluorescence microscopy

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., kinetics, coexistence of different states and populations, transient interactions), which are typically hidden in ensemble measurements, such as those obtained with standard biochemical or microscopy methods. Thus, dynamic events, such as receptor-receptor interactions, can be followed in real time in a living cell with high spatiotemporal resolution. This protocol describes a method based on labeling with small and bright organic fluorophores and total internal reflection fluorescence (TIRF) microscopy to directly visualize single receptors on the surface of living cells. This approach allows one to precisely localize receptors, measure the size of receptor complexes, and capture dynamic events such as transient receptor-receptor interactions. The protocol provides a detailed description of how to perform a single-molecule experiment, including sample preparation, image acquisition and image analysis. As an example, the application of this method to analyze two G-protein-coupled receptors, i.e., &#946;2-adrenergic and &#947;-aminobutyric acid type B (GABAB) receptor, is reported. The protocol can be adapted to other membrane proteins and different cell models, transfection methods and labeling strategies.

The described protocol can be applied to a variety of different membrane proteins. As an example, representative results obtained with &#946;2-adrenergic and GABAB receptors are reported10. Since fluorescent signals from single molecules are weak, minimization of background fluorescence is the first key step to successful results. Thus, it is important to use extensively cleaned coverslips (Figure 2A) as well as to minimize sample autofluorescence (e.g., by using...

Watch this Scientific Journal Video about High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy at JoVE.com

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

This protocol describes how to use total internal reflection fluorescence microscopy to visualize and track single receptors on the surface of living cells and thereby analyze receptor lateral mobility, size of receptor complexes as well as to visualize transient receptor-receptor interactions. This protocol can be extended to other membrane proteins.

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., ...

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Research

JoVE Journal

Bioengineering

11.3K Views.  University of Würzburg, Germany. This protocol describes how to use total internal reflection fluorescence microscopy to visualize and track single receptors on the surface of living cells and thereby analyze receptor lateral mobility, size of receptor complexes as well as to visualize transient receptor-receptor interactions. This protocol can be extended to other membrane proteins. 

Video: High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT

Non-destructive volume visualization can be achieved only by tomographic techniques, of which the most efficient is the x-ray micro computerized tomography (&mu;CT).
High resolution &mu;CT is a very versatile yet accurate (1-2 microns of resolution) technique for 3D examination of ex-vivo biological samples1, 2. As opposed to electron tomography, the &mu;CT allows the examination of up to 4 cm thick samples. This technique requires only few hours of measurement as compared to weeks in histology. In addition, &mu;CT does not rely on 2D stereologic models, thus it may complement and in some cases can even replace histological methods3, 4, which are both time consuming and destructive. Sample conditioning and positioning in &mu;CT is straightforward and does not require high vacuum or low temperatures, which may adversely affect the structure. The sample is positioned and rotated 180&deg; or 360&deg;between a microfocused x-ray source and a detector, which includes a scintillator and an accurate CCD camera, For each angle a 2D image is taken, and then the entire volume is reconstructed using one of the different available algorithms5-7. The 3D resolution increases with the decrease of the rotation step. The present video protocol shows the main steps in preparation, immobilization and positioning of the sample followed by imaging at high resolution.

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT

Non-destructive volume visualization can be achieved only by tomographic techniques, of which the most efficient is the x-ray micro computerized tomography ( CT).

Non-destructive volume visualization can be achieved only by tomographic techniques, of which the most efficient is the x-ray micro computerized ...

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. ...

Investigating Receptor-ligand Systems of the Cellulosome with AFM-based Single-molecule Force Spectroscopy

Cellulosomes are discrete multienzyme complexes used by a subset of anaerobic bacteria and fungi to digest lignocellulosic substrates. Assembly of the enzymes onto the noncatalytic scaffold protein is directed by interactions among a family of related receptor-ligand pairs comprising interacting cohesin and dockerin modules. The extremely strong binding between cohesin and dockerin modules results in dissociation constants in the low picomolar to nanomolar range, which may hamper accurate off-rate measurements with conventional bulk methods. Single-molecule force spectroscopy (SMFS) with the atomic force microscope measures the response of individual biomolecules to force, and in contrast to other single-molecule manipulation methods (i.e.&#160;optical tweezers), is optimal for studying high-affinity receptor-ligand interactions because of its ability to probe the high-force regime (&#62;120 pN). Here we present our complete protocol for studying cellulosomal protein assemblies at the single-molecule level. Using a protein topology derived from the native cellulosome, we worked with enzyme-dockerin and carbohydrate binding module-cohesin (CBM-cohesin) fusion proteins, each with an accessible free thiol group at an engineered cysteine residue. We present our site-specific surface immobilization protocol, along with our measurement and data analysis procedure for obtaining detailed binding parameters for the high-affinity complex. We demonstrate how to quantify single subdomain unfolding forces, complex rupture forces, kinetic off-rates, and potential widths of the binding well. The successful application of these methods in characterizing the cohesin-dockerin interaction responsible for assembly of multidomain cellulolytic complexes is further described.

Cellulosomes are multienzyme complexes designed for digesting cellulose. AFM-based SMFS was used to study the mechanical properties and folding configuration of cellulosome-associated protein assemblies. We present a complete workflow for protein immobilization, data acquisition, and data analysis to study the interactions of individual receptor-ligand complexes involved in cellulosome assembly.

Cellulosomes are discrete multienzyme complexes used by a subset of anaerobic bacteria and fungi to digest lignocellulosic substrates. Assembly of the ...

3D Orbital Tracking in a Modified Two-photon Microscope: An Application to the Tracking of Intracellular Vesicles

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a modified two-photon microscope1. As opposed to conventional approaches (raster scan or wide field based on a stack of frames), the 3D orbital tracking allows to localize and follow with a high spatial (10 nm accuracy) and temporal resolution (50 Hz frequency response) the 3D displacement of a moving fluorescent particle on length-scales of hundreds of microns2. The method is based on a feedback algorithm that controls the hardware of a two-photon laser scanning microscope in order to perform a circular orbit around the object to be tracked: the feedback mechanism will maintain the fluorescent object in the center by controlling the displacement of the scanning beam3-5. To demonstrate the advantages of this technique, we followed a fast moving organelle, the lysosome, within a living cell6,7. Cells were plated according to standard protocols, and stained using a commercially lysosome dye. We discuss briefly the hardware configuration and in more detail the control software, to perform a 3D orbital tracking experiment inside living cells. We discuss in detail the parameters required in order to control the scanning microscope and enable the motion of the beam in a closed orbit around the particle. We conclude by demonstrating how this method can be effectively used to track the fast motion of a labeled lysosome along microtubules in 3D within a live cell. Lysosomes can move with speeds in the range of 0.4-0.5 &#181;m/sec, typically displaying a directed motion along the microtubule network8.

In this video protocol we track - at high speed and in three dimensions - fluorescently labeled lysosomes within living cells, using the orbital tracking method in a modified two-photon microscope.

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a ...

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn&#8217;t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on &#181;m-sized membrane regions in the micro-to-milli-second time range.

Spatial distribution and temporal dynamics of plasma membrane proteins and lipids is a hot topic in biology. Here this issue is addressed by a spatio-temporal image fluctuation analysis that provides conceptually the same physical quantities of single particle tracking, but it uses small molecular labels and standard microscopy setups.

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the ...

Preparation of Mica Supported Lipid Bilayers for High Resolution Optical Microscopy Imaging

Supported lipid bilayers (SLBs) are widely used as a model for studying membrane properties (phase separation, clustering, dynamics) and its interaction with other compounds, such as drugs or peptides. However SLB characteristics differ depending on the support used. 
Commonly used techniques for SLB imaging and measurements are single molecule fluorescence microscopy, FCS and atomic force microscopy (AFM). Because most optical imaging studies are carried out on a glass support, while AFM requires an extremely flat surface (generally mica), results from these techniques cannot be compared directly, since the charge and smoothness properties of these materials strongly influence diffusion. Unfortunately, the high level of manual dexterity required for the cutting and gluing thin slices of mica to the glass slide presents a hurdle to routine use of mica for SLB preparation. Although this would be the method of choice, such prepared mica surfaces often end up being uneven (wavy) and difficult to image, especially with small working distance, high numerical aperture lenses. Here we present a simple and reproducible method for preparing thin, flat mica surfaces for lipid vesicle deposition and SLB preparation. Additionally, our custom made chamber requires only very small volumes of vesicles for SLB formation. The overall procedure results in the efficient, simple and inexpensive production of high quality lipid bilayer surfaces that are directly comparable to those used in AFM studies.

We present a method of preparing mica supported lipid bilayers for high resolution microscopy. Mica is transparent and flat on an atomic scale, but rarely used in imaging because of handling difficulties; our preparation results in even deposition of the mica sheet, and reduces the material used in bilayer preparation.

Supported lipid bilayers (SLBs) are widely used as a model for studying membrane properties (phase separation, clustering, dynamics) and its interaction ...

Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

In the course of a single decade single molecule microscopy has changed from being a secluded domain shared merely by physicists with a strong background in optics and laser physics to a discipline that is now enjoying vivid attention by life-scientists of all venues 1. This is because single molecule imaging has the unique potential to reveal protein behavior in situ in living cells and uncover cellular organization with unprecedented resolution below the diffraction limit of visible light 2. Glass-supported planar lipid bilayers (SLBs) are a powerful tool to bring cells otherwise growing in suspension in close enough proximity to the glass slide so that they can be readily imaged in noise-reduced Total Internal Reflection illumination mode 3,4. They are very useful to study the protein dynamics in plasma membrane-associated events as diverse as cell-cell contact formation, endocytosis, exocytosis and immune recognition. Simple procedures are presented how to generate highly mobile protein-functionalized SLBs in a reproducible manner, how to determine protein mobility within and how to measure protein densities with the use of single molecule detection. It is shown how to construct a cost-efficient single molecule microscopy system with TIRF illumination capabilities and how to operate it in the experiment.

Preparation of protein-functionalized planar glass-supported lipid bilayers, determination of protein mobility within and measurement of protein densities is shown here. A roadmap to building a noise-reduced Total Internal Reflection microscope is outlined, which allows visualizing single bilayer-resident fluorochromes with high spatiotemporal resolution.

In the course of a single decade single molecule microscopy has changed from being a secluded domain shared merely by physicists with a strong background ...

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 ...

Engineering 'Golden' Fluorescence by Selective Pressure Incorporation of Non-canonical Amino Acids and Protein Analysis by Mass Spectrometry and Fluorescence

Fluorescent proteins are fundamental tools for the life sciences, in particular for fluorescence microscopy of living cells. While wild-type and engineered variants of the green fluorescent protein from Aequorea victoria (avGFP) as well as homologs from other species already cover large parts of the optical spectrum, a spectral gap remains in the near-infrared region, for which avGFP-based fluorophores are not available. Red-shifted fluorescent protein (FP) variants would substantially expand the toolkit for spectral unmixing of multiple molecular species, but the naturally occurring red-shifted FPs derived from corals or sea anemones have lower fluorescence quantum yield and inferior photo-stability compared to the avGFP variants. Further manipulation and possible expansion of the chromophore&#39;s conjugated system towards the far-red spectral region is also limited by the repertoire of 20 canonical amino acids prescribed by the genetic code. To overcome these limitations, synthetic biology can achieve further spectral red-shifting via insertion of non-canonical amino acids into the chromophore triad. We describe the application of SPI to engineer avGFP variants with novel spectral properties. Protein expression is performed in a tryptophan-auxotrophic E. coli strain and by supplementing growth media with suitable indole precursors. Inside the cells, these precursors are converted to the corresponding tryptophan analogs and incorporated into proteins by the ribosomal machinery in response to UGG codons. The replacement of Trp-66 in the enhanced &#34;cyan&#34; variant of avGFP (ECFP) by an electron-donating 4-aminotryptophan results in GdFP featuring a 108 nm Stokes shift and a strongly red-shifted emission maximum (574 nm), while being thermodynamically more stable than its predecessor ECFP. Residue-specific incorporation of the non-canonical amino acid is analyzed by mass spectrometry. The spectroscopic properties of GdFP are characterized by time-resolved fluorescence spectroscopy as one of the valuable applications of genetically encoded FPs in life sciences.

Engineering &#039;Golden&#039; Fluorescence by Selective Pressure Incorporation of Non-canonical Amino Acids and Protein Analysis by Mass Spectrometry and Fluorescence

Synthetic biology enables the engineering of proteins with unprecedented properties using the co-translational insertion of non-canonical amino acids. Here, we presented how a spectrally red-shifted variant of a GFP-type fluorophore with novel fluorescence spectroscopic properties, termed &#34;gold&#34; fluorescent protein (GdFP), is produced in E. coli via selective pressure incorporation (SPI).

Fluorescent proteins are fundamental tools for the life sciences, in particular for fluorescence microscopy of living cells. While wild-type and ...

Visualizing Adhesion Formation in Cells by Means of Advanced Spinning Disk-Total Internal Reflection Fluorescence Microscopy

In living cells, processes such as adhesion formation involve extensive structural changes in the plasma membrane and the cell interior. In order to visualize these highly dynamic events, two complementary light microscopy techniques that allow fast imaging of live samples were combined: spinning disk microscopy (SD) for fast and high-resolution volume recording and total internal reflection fluorescence (TIRF) microscopy for precise localization and visualization of the plasma membrane. A comprehensive and complete imaging protocol will be shown for guiding through sample preparation, microscope calibration, image formation and acquisition, resulting in multi-color SD-TIRF live imaging series with high spatio-temporal resolution. All necessary image post-processing steps to generate multi-dimensional live imaging datasets, i.e. registration and combination of the individual channels, are provided in a self-written macro for the open source software ImageJ. The imaging of fluorescent proteins during initiation and maturation of adhesion complexes, as well as the formation of the actin cytoskeletal network, was used as a proof of principle for this novel approach. The combination of high resolution 3D microscopy and TIRF provided a detailed description of these complex processes within the cellular environment and, at the same time, precise localization of the membrane-associated molecules detected with a high signal-to-background ratio.

An advanced microscope that permit fast and high-resolution imaging of both, the isolated plasma membrane and the surrounding intracellular volume, will be presented. The integration of spinning disk and total internal reflection fluorescence microscopy in one setup allows live imaging experiments at high acquisition rates up to 3.5 s per image stack.

In living cells, processes such as adhesion formation involve extensive structural changes in the plasma membrane and the cell interior. In order to ...