This work is funded by the German Research Foundation (INST 39/969-1) and the European Research Council through the ERC Grant Agreement n. 681891.

1. Setup and Prerequisites
<ol>
	<li>Perform the multi-color smFRET measurements on a prism-type TIRFM. A description of a two-color setup as a JoVE publication is given in reference12.
	<ol>
		<li>Construct a multi-color TIRFM. A general layout is detailed in 9.</li>
		<li>Use switchable, diode pumped solid state continuous wave lasers, which render the use of mechanical shutters in the excitation paths unnecessary.</li>
		<li>Employ an asymmetric, elongated prism that prevents the back reflection of the excitation beam from the rear side to enter the objective.</li>
		<li>Use 2-inch achromatic aspheric fused silica lenses in the detection paths that collect as much light as possible and prevent auto-fluorescence and aberrations, e.g., distortions in off-center regions of the image.</li>
		<li>Focus each detection path on the chip of the EMCCD with a separate lens. This allows optimal focusing of each detection channel. 
		Caution: Class 3B lasers are used in the TIRFM. This means they are hazardous if the eye is exposed directly, but diffuse reflections are not harmful. Ensure compliance with laser safety precautions according to local government regulations before the system is operated.</li>
	</ol>
	</li>
	<li>Determine the correction factors for setup and fluorophore properties beforehand using dsDNA samples.
	<ol>
		<li>Use one high-FRET dsDNA sample for each dye in combination with the acceptor having the longest excitation wavelength (for the presented setup: Atto488-Atto647N, Atto550-Atto647N, Atto594-Atto647N). Make sure that the DNA is additionally modified with a biotin.</li>
		<li>Dilute the sample to 5 nM with TNM buffer (5 mM Tris pH 7.5, 5 mM NaCl, 20 mM MgCl2) and 2 mM Trolox (use this buffer also for measurement).</li>
		<li>Immobilize the dsDNA as described for Hsp90 in steps 2.5 and 2.7.</li>
		<li>Calculate the correction factors for apparent leakage (lk) and apparent gamma (ag) from single-molecule traces that show an acceptor bleaching event.</li>
	</ol>
	</li>
	<li>Construct a flow chamber that is a sandwich of a PEG/biotin-PEG passivated quartz slide, a thin film that is adhesive on both sides, and a cover slip. For detail protocols for the cleaning of the quartz slides and passivation see reference9.
	<ol>
		<li>Use thick (3 mm) quartz slides to geometrically prevent the collection of laser light scattered at the quartz-glycerol-quartz interface between the prism and the functionalized quartz slide.</li>
		<li>Use a thin (40 &#181;m) sealing film that is sprayed with adhesive on the non-adhesive side. The thin film reduces the distance between the surface-attached molecules and objective. Heat to 80 &#176;C and press on.</li>
		<li>Place a cover slip on the top. Heat to 80 &#176;C and press on. Use a drop of glycerol when placing the flow chamber over the prism. 
		NOTE: The materials of the prism and the quartz slides as well as the glycerol are index-matched.</li>
	</ol>
	</li>
	<li>Express Hsp90 from Saccharomyces cerevisiae in the form of two single cysteine point mutants at the positions D61 or Q385. Add a C-terminal coiled-coil motif to prevent dimer dissociation at picomolar concentrations. Label the mutant proteins separately and exchange the monomers to obtain heterodimers labeled with Atto488 at amino acid position 61 and Atto550 at amino acid position 3859.</li>
</ol>
2. Measurement
<ol>
	<li>Start the camera software and set the imaging parameters as specified below:
	<ol>
		<li>Set the temperature for the sensor cooling as low as possible (-95 &#176;C with external water cooling) to decrease the dark current noise.</li>
		<li>Use camera settings that are optimized for single-molecule recording: 3.3 &#181;s vertical shift speed, normal vertical clock voltage, 17 MHz 16-bit horizontal read out, pre-amplification gain 3, gain of electron multiplier 1,000.</li>
		<li>Set the triggering of the acquisition to &#34;External&#34; and the exposure time to 70 ms. Record movies with a length of 750 acquisition cycles. 
		NOTE: Turn off the room light when the camera is acquiring to prevent saturation of the EMCCD sensor.</li>
	</ol>
	</li>
	<li>Create a folder on the local SSD for the measurement. In the software settings go to the &#60;Auto-Save&#62; rider, enable &#60;Auto-save&#62;, and choose file format &#34;Tiff&#34; for movie acquisition. Select the folder on the SSD as auto-save location.</li>
	<li>Start the software that controls the acousto-optical tunable filter (AOTF), the software that controls the operation of the lasers and the trigger software that synchronizes the lasers, AOTF, shutters in the detection path, and cameras. Adjust the laser power with the AOTF (ca. 3 mW before entering the prism) and load the correct triggering pattern.</li>
	<li>Mount the sample holder with the prism and the flow chamber, attach tubing, place the inlet tubing in a microcentrifuge cup, and connect the outlet tubing to a syringe pump. Flush the chamber with approximately 150 &#181;L buffer, align the excitation beam, and focus. Bleach any fluorescent contaminants on the surface by slowly moving along the complete detection range of the slide with a laser power of about 10 mW for all lasers. This takes about 1 h. 
	NOTE: If not stated otherwise, the used buffer contains 40 mM HEPES pH 7.5, 150 mM KCl, and&#160;10 mM MgCl2.</li>
	<li>Flush approximately 300 &#181;L of a NeutrAvidin solution (0.25 mg/mL in buffer) into the chamber and incubate for 1 min. Flush out unbound NeutrAvidin with buffer and flush approximately 300 &#181;L of a BSA solution (0.5 mg/mL in buffer) through the chamber. 
	NOTE: This block remaining surface functionalization defects by unspecific adsorption of BSA to the surface.</li>
	<li>Immobilize the sample by loading the flow chamber with approximately 150 &#181;L of the biotinylated and labeled Hsp90 at rising concentrations (diluted in buffer + 0.5 mg/mL BSA) until a sufficient surface density is reached, which is usually the case at a concentration of 5 - 10 pM. Wash out unbound protein with approximately 300 &#181;L buffer + 0.5 mg/mL BSA.</li>
	<li>Flush in 150 &#181;L of 25 nM AMP-PNP* in buffer + 0.5 mg/mL BSA. Let it incubate for 5 min and repeat this step once to ensure correct nucleotide concentration. 
	NOTE: For experiments in the presence of additional, unlabeled AMP-PNP, also add 250 &#181;M AMP-PNP.</li>
	<li>Begin with the data acquisition. For an appropriate amount of data acquire approximately 20 movies which takes about 1.5 h.
	<ol>
		<li>Move the position of the sample chamber perpendicular to the excitation beam with a piezo stepper to change the field of view.</li>
		<li>Adjust the focus with the z-piezo that controls the height of the objective if needed. This should not be necessary too often when the measurement chamber is mounted without inclination.</li>
		<li>Prepare the recording of the cameras by pressing &#60;Take Signal&#62; in the camera software and start the excitation/acquisition cycles using the &#60;Start&#62; button in the trigger software. This starts the acquisition of the fluorescence intensity.</li>
	</ol>
	</li>
	<li>Perform a channel registration by first recording a movie with fluorescent beads that show fluorescence emission in the spectral range of all detection channels of the setup. Then, detect bead positions in the calibration movie by searching for the brightest spots and determine the central position from a Gaussian fit to the intensity profile. Save the coordinates of beads that are found in all channels and fit both the mapping offset in x- and in y-direction with a 2D polynomial of degree three9.</li>
</ol>
3. Selection of Single-molecule Traces
<ol>
	<li>Data analysis is done with in-house scripts using Igor Pro. Load all necessary scripts by opening &#34;iniTIRF.ipf&#34; and select the correct type of experiment. 
	NOTE: In the following, &#60;Button&#62; specifies clickable elements in the menu or the user interface. Function calls are indicated in quotes, e.g., &#34;Print &#34;Hello World&#34;&#34;. These commands can be pasted to the command line of Igor Pro (without the enclosing quotes).</li>
	<li>Make sure the parameters for the detection channel registration are loaded.</li>
	<li>Start the GUI by clicking &#60;smFRET new|Analysis GUI&#62;.</li>
	<li>Load the movies (i.e., the sequence of frames with 512 x 512 pixels stored as 16 bit TIFF stacks) that hold the intensity in the respective channels. Do this by pressing the &#60;Load Film&#62; button and selecting the files from the so-called &#34;master&#34; and &#34;slave&#34; cameras one after the other.</li>
	<li>Identify the positions of potential single molecules by searching for the brightest spots in the sum of the first five frames in a certain detection channel. Calculate the corresponding positions in all other detection channels from the channel mapping. To obtain the fluorescence intensity trace, sum the intensity of a pixel square around the central position for each frame. Do this by pressing the button &#60;Find Traces&#62; in the GUI. 
	NOTE: The side length of the square (in pixel) is given by: 2 * &#60;Sum Pxs&#62; + 1.</li>
	<li>For each molecule, calculate a joint raw intensity trace as the sum of all traces of this spot with the same excitation color. Evaluate the intensity profile of the molecule in all channels for the following criteria:
	<ol>
		<li>A roughly flat plateau in the joint raw intensity and a single bleaching step for all excitation colors, anticorrelated behavior in the appropriate detection channels, detection of red fluorescence (indicating FRET to a bound AMP-PNP*) at least once within the trace, and no multiple steps in the red fluorescence, which would indicate the presence of two AMP-PNP* bound to one Hsp90 dimer.</li>
	</ol>
	</li>
	<li>Save the fluorescence traces of the spot for further analysis if these criteria are fulfilled. Do this by selecting the trace with the cursor and then pressing the &#60;Save&#62; button in the &#34;timelines&#34; graph. Manually inspect the intensity traces in all three detection channels after blue excitation for about 200 molecules per movie.</li>
</ol>
4. Calculation of the Partial Fluorescence Traces
<ol>
	<li>Display all fluorescence intensity traces for one of the saved molecules. Use the cursors in the graph to select time ranges.</li>
	<li>Select a time interval where all fluorophores are bleached already. The mean background intensity is calculated from this range and subtracted from the intensity trace in each channel. Do this by pressing the &#60;Background&#62; button.</li>
	<li>Select the FRET efficiency range, where at least both the dyes attached to Hsp90 (Atto488 and Atto550) are present. Make sure to exclude traces that contain a blinking event (see Figure 3B). These events are characterized by a drop-in fluorescence intensity in one channel without an accompanying increase in any other channel.</li>
	<li>Calculate the PF traces. Do this by pressing the &#60;PF Calc&#62; button. The predefined correction factors for apparent leakage (lk) and apparent gamma (ag) are applied to the raw intensity in order to correct for photo-physical and setup properties.</li>
</ol>
5. Population Selection and 3D Histogram Fitting
<ol>
	<li>Remove molecules that show a low signal-to-noise ratio in the PF traces. Molecules that exceed the interval [-1;2] in any PF trace for more than 10% of the frames are removed from the data set. Do this by executing &#34;RemoveTracesLowSNR()&#34; from the Command Window.</li>
	<li>Calculate binned 2D projections of the PF data. Plot <img alt="Equation 12" src="/files/ftp_upload/56896/56896eq12.jpg" />over&#160;<img alt="Equation 13" src="/files/ftp_upload/56896/56896eq13v2.jpg" /> and <img alt="Equation 14" src="/files/ftp_upload/56896/56896eq14.jpg" /> over <img alt="Equation 13" src="/files/ftp_upload/56896/56896eq13v2.jpg" /> in the range [-0.5; 1.5] with a resolution of 100 x 100 bins. To do so, execute:
	<ol>
		<li>&#34;HistFret2D(&#34;r_b&#34;, &#34;r_g&#34;, binHist=100)&#34;</li>
		<li>&#34;HistFret2D(&#34;r_b&#34;, &#34;g_b&#34;, binHist=100); MoveWindow 553.5, 42.5, 1055.25, 508.25&#34;</li>
	</ol>
	</li>
	<li>Determine the relative population of each distinguishable state in the 2D projections.
	<ol>
		<li>Bring the appropriate graph to the front and execute &#34;panelHist2DCount()&#34;.</li>
		<li>Press the &#60;Init&#62; button and draw a free-hand polygon around the peak.</li>
		<li>Click the &#60;Count&#62; button. The number of data points in the polygon and the total number of data points in the projection are printed in the Command Window.</li>
	</ol>
	</li>
	<li>Prepare a 3D histogram of the PF data by executing &#34;HistFret3D(&#34;g_b&#34;, &#34;r_b&#34;, &#34;r_g&#34;)&#34;.</li>
	<li>Normalize the 3D histogram to an integral of 1. Execute the following:
	<ol>
		<li>&#34;NewDataFolder/S fit0&#34;</li>
		<li>&#34;Duplicate/O ::FRET:Hist3D, Hist3D&#34;</li>
		<li>&#34;Variable /G div = sum(Hist3D)*(DimDelta(Hist3D,0))^3&#34;</li>
		<li>&#34;Hist3D /= div; Print div&#34;</li>
	</ol>
	</li>
	<li>Provide initial parameters for the 3D Gaussian fit and prepare necessary data structures.
	<ol>
		<li>Execute &#34;Gauss3D_initParam(); edit W_coef_old.&#34;</li>
		<li>Add the state populations to the end of the parameter vector.</li>
		<li>Execute &#34;Gauss3D_prepareFit().&#34; 
		Note: W_coef_old is a vector that holds the initial parameters for the fit. Per state this means <img alt="Equation 15" src="/files/ftp_upload/56896/56896eq15.jpg" /> and the state population, which is concatenated at the end of the vector. Make sure that the covariance matrix is symmetric.</li>
	</ol>
	</li>
	<li>Fit the sum of S 3D Gaussian functions to the 3D PF histogram, with S being the number of distinguishable states.
	<ol>
		<li>Execute &#34;do3D().&#34;&#160;This may take an hour or more on a normal office PC, depending on the quality of the initial parameters.</li>
		<li>Execute &#34;postprocessFitMultiGauss3D(); evalFitMultiGauss3D(); edit W_coef.&#34;</li>
	</ol>
	</li>
	<li>Display the fit result. For each of the two 2D projections, use the following commands:
	<ol>
		<li>&#34;contourPF3D_new(0); contourPF3D_new(1); contourPF3D_new(2); contourPF3D_new(3); contourPF3D_new(4)&#34;</li>
		<li>&#34;contourPF3D_colorize()&#34;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;</li>
	</ol>
	</li>
</ol>
6. Kinetic Analysis with 3D Ensemble HMM
<ol>
	<li>Prepare an ensemble HMM run to extract the kinetic information. One HMM is optimized from all molecules in the data set. Use the information obtained in the previous step to define the position and width of each state in the 3D PF space.
	<ol>
		<li>Initialize the HMM user interface (&#60;HMM|Init HMM&#62;) and choose the appropriate number of states (in the case of the Hsp90 data this means &#60;NumStates&#62; = 5), number of dimensions of the input signal (&#60;NumDims&#62; = 3), and the type of the input (&#60;Input Type&#62; = &#34;FRET 3D bgr&#34;).</li>
	</ol>
	</li>
	<li>Optimize the parameters of the HMM by letting the software converge the likelihood of the HMM (execute &#34;prepENS_CONVERGE_gB(GetDataFolder(1), -14)&#34;) until the change in the transition matrix compared to the previous iteration falls below a threshold (10-14 for the sum of the absolute change for each transition probability). This yields the MLE for the transition probabilities in about an hour on a normal office PC.</li>
	<li>Repeat the population selection, Gaussian fitting, and the HMM optimization for subsets of the data (e.g., 75% of the full data set). If the full data set was merged from different experiments, repeat the optimization also for each of the single experiments. Analysis of subsets permits to estimate the uncertainty of the manual population selection and the variability within the data set.</li>
	<li>Calculate the CI for the transition probabilities, which report on the data set heterogeneity and the precision of the HMM.
	<ol>
		<li>Get a rough estimate of the CI bounds by executing &#34;cd $(root:path3Dimport + &#34;HMM&#34;); loop_getCI_estimate_limits().&#34;</li>
		<li>Calculate the exact limits of the CI by executing:</li>
		<li>&#34;loop_getCI_HMM_converge(1)&#34;</li>
		<li>&#34;CIresults_conv_new()&#34;</li>
		<li>&#34;cd ::HMM_CIresult; reportCI_conv()&#34;</li>
		<li>&#34;cd ::cmp_CI_conv; CI_plot2(&#34;HMM&#34;, doAppend=0)&#34;</li>
	</ol>
	</li>
	<li>Condense the available kinetic information to simplify the interpretation.
	<ol>
		<li>Collect information about the time a labeled nucleotide stays bound to Hsp90. Do this by collapsing the states that are bound to AMP-PNP* (i.e., S1, S2 and S3, see also Figure 2) and compile the dwell time histogram. Execute &#34;cd $(root:path3Dimport +&#34;HMM&#34;); collapse_states_get_DT({0,1,1,1,0})&#34;, which combines dwells of states S0 and S4 as well as S1, S2, and S3.</li>
		<li>Extract the dwell times from the Viterbi path for each state of interest and compare the resulting dwell time histogram for different experimental conditions. Execute &#34;plot_collapsed_DT_Hist (wDTo_01110_record1).&#34;</li>
		<li>For a more detailed picture, collapse states that have distinct PF but are functionally identical to ease the further data analysis, e.g., in the case of a three-color experiment with labeled Hsp90 and nucleotide, states S2 and S3 can be collapsed. Execute &#34;collapse_states_get_DT({0,1,2,2,4}).&#34;</li>
	</ol>
	</li>
</ol>

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J., Lilley, D. M. J., Ha, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Vesicle+encapsulation+studies+reveal+that+single+molecule+ribozyme+heterogeneities+are+intrinsic.">Vesicle encapsulation studies reveal that single molecule ribozyme heterogeneities are intrinsic.</a> Biophys J. 87 (4), 2798-2806 (2004).</li><li>Boukobza, E., Sonnenfeld, A., Haran, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immobilization+in+Surface-Tethered+Lipid+Vesicles+as+a+New+Tool+for+Single+Biomolecule+Spectroscopy.">Immobilization in Surface-Tethered Lipid Vesicles as a New Tool for Single Biomolecule Spectroscopy.</a> J Phys Chem B. 105 (48), 12165-12170 (2001).</li><li>Levene, M. J., Korlach, J., Turner, S. W., Foquet, M., Craighead, H. G., Webb, W. 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The authors declare no conflicts of interest.

We present the experimental procedure to obtain three-color smFRET data for a complex protein system and a step-by-step description of the analysis of these measurements. This approach offers the unique possibility to directly assess the correlation between multiple interaction sites or conformational changes.
In order to obtain suitable multi-color single-molecule data on proteins it is important to perform reproducible measurements at a low noise level. This can be achieved by using an efficient and reliable surface passivation protocol for the flow chamber9. A sufficient density of molecules immobilized to the surface should be used to increase the yield of molecules per recorded movie. This means that fluorescence light from single molecules should fall on about 5 - 10% of the pixels in the recorded images. At the same time overloading should be prevented, because it would result in an overlap of neighboring molecules. When a labeled species is free in solution (AMP-PNP* in the presented study), make sure the concentration is low enough to not interfere with the measurement by direct excitation from lasers with shorter wavelength (i.e., typically well below a micromolar concentration). Also, ensure that the concentration of these compounds is not lower than intended due to unspecific binding to interfaces. Additionally, the optimal excitation power represents a trade-off between the signal-to-noise ratio and the photobleaching of the fluorophores.
No oxygen scavenging system is employed in the presented protocol. The used Atto-Tec dyes do not show significant blinking on the time scale of the experiment (70 ms illumination per excitation cycle) and no decrease of the photo bleach rate was observed by a scavenger system consisting of glucose oxidase, catalase, and Trolox33,34. Also, absence of oxygen scavenger avoids artifacts due to unspecific protein interactions, as oxygen scavenging systems usually contain protein components up to a micromolar concentration35.
Another critical step is the trace selection. The size of the area for summing the intensity of a single fluorophore is chosen to be as small as possible but still larger than the point spread function of the setup. Be aware that a flat plateau in the joint intensity traces can only be expected if the detection channels have similar apparent gamma factors, since the traces are not corrected at this stage of the analysis. Only molecules that meet well-defined criteria for the fluorescence intensity traces are included in the analysis (Section 3). Molecules with a poor signal-to-noise ratio in the PF traces are excluded from further analysis and do not affect data evaluation as clear selection criteria are used.
Depending on the data quality, alternative approaches provide optimal state allocation. A free multi-dimensional ensemble HMM based either on the fluorescence intensity traces27 or the PF traces could be applied to allocate the underlying states by optimizing the corresponding emission probabilities (e.g., Gaussian PDFs) while at the same time optimizing the kinetic model. Both approaches have their advantages and disadvantages. PF traces may contain unfavorable spikes while fluorescence intensity levels vary from molecule to molecule. The presented protocol solves this issue by preventing artificial transitions when spikes occur and by estimating the emission probabilities from a 3D Gaussian fit to the PF histogram and only optimizing the transition probabilities in the subsequent ensemble HMM run.
The presented approach is limited by the need for a labeled interaction partner that binds with a comparably high affinity in order to be compatible with the low concentrations necessary for conventional single-molecule measurements. This may be overcome by strategies to increase the local concentration (tethering of the interaction partners36, encapsulation in vesicles37,38) or methods to decrease the excited volume (e.g., zero-mode waveguides39). In addition, labeling positions have to be chosen with care and control experiments are necessary to exclude severe side-effects of the fluorophores. In case of Hsp90, this is usually checked by an ATPase assay, which proves the enzymatic activity40. If available, structural information from crystal or NMR structure should be considered. Preferred positions are in surface-exposed loops, away from interaction interfaces and not buried in a protein surface pocket. This ensures a large accessible volume for the dye.
The framework is suited for a multi-color smFRET experiment with an arbitrary number of colors. We focus on three-color measurements here, as these already provide the feature that renders them distinct from other single-molecule experiments, namely the possibility to directly observe correlation between two processes (e.g., binding of an interaction partner and conformational changes). This information is inaccessible in a standard two-color smFRET experiment but is of fundamental interest for understanding the function of any molecular machine.
The presented experiment and analysis is capable of characterizing protein systems, which might display dynamics on a wide range of time scales between states that are highly flexible themselves3. This contrasts previously published multi-color smFRET experiments, which focused on DNA or RNA model systems, such as Holliday junctions4, exhibiting transitions between (mostly two) well-defined states. In protein systems, the signal-to-noise ratio is lower and extracting the complete set of transition probabilities is difficult because of the limited temporal bandwidth in smFRET experiments due to photobleaching. Here, we show that - if applied carefully and with reasonable constraints - the obstacles in measuring protein systems can be overcome with multi-color smFRET using multi-dimensional state allocation and ensemble hidden Markov analysis9.

Many proteins fulfill their function in dynamic complexes with other molecules, mediated by conformational changes and transient associations on a broad range of timescales1,2,3. Coupled to an external energy source (e.g., ATP) these dynamic interactions can lead to directionality in a functional cycle and ultimately maintain the non-equilibrium steady-state in a cell, the prerequisite for life.
In order to fully understand these molecular machines, a static description guided by structural studies is not sufficient. In addition, it is essential to have knowledge of the underlying kinetic model and to determine the kinetic rate constants. Several existing methods allow researchers to study the dynamics of binary interactions between two molecules of interest, e.g., surface plasmon resonance, relaxation methods with a spectroscopic readout (e.g., jump or stopped-flow techniques), and nuclear magnetic resonance. However, their applicability is in most cases limited to simple two-state systems (e.g., one bound and one unbound state) due to the averaging inherent to bulk experiments. In cases where more states or intermediates are involved, they yield only a complex mixture of the rate constants. Single-molecule methods such as optical or magnetic tweezers or two-color smFRET, i.e., one donor and one acceptor fluorophore, with a surface-immobilized sample can recover the rate constants for all observed conformational changes. However, when it comes to interactions affecting more than one binding site, these methods remain limited and the information on the possible correlation of the two (or more) interactions will only be accessible via indirect conclusions from a set of experiments.
Multi-color smFRET4,5,6,7,8,9 offers the opportunity to study the interaction between these components directly, at real time and under near-physiological conditions10. This permits one to investigate for example, the conformation-dependent binding of a ligand or another protein8,9,11. The overall approach presented here is to label the protein(s) of interest at specific positions, to attach one protein to the surface of the measurement chamber, and to track the fluorescence intensity over time on a prism-type TIRFM (for details see 9,12). The spatial proximity of the different dyes can then be determined from the energy transfer between them. Labeling strategies may vary from protein to protein (reviewed in 13) and guidelines to avoid artifacts in smFRET measurements exist14.
Since a donor dye may transfer energy to different acceptor dyes in a multi-color smFRET experiment, the relative position of all dyes is not accessible from excitation of one dye alone15,16. But in combination with alternating laser excitation (ALEX17, and reviewed in 18) this method provides all spatio-temporal information at sub-second and sub-nanometer resolution.
In principal, high resolution structural information can be achieved by using the inter-dye distances calculated from the combination of all fluorescence intensities in a multi-color smFRET experiment with ALEX. However, here we focus on state identification and separation as well as the extraction of kinetic models, where multi-color smFRET is indispensable. When &#34;only&#34; structure determination by triangulation is desired, a set of simpler two-color smFRET experiments with high signal-to-noise ratio can be performed12,19.
We use the partial fluorescence (<img alt="Equation 1" src="/files/ftp_upload/56896/56896eq1.jpg" />) as a proxy for the energy transfer between two fluorophores7. The PF is calculated from the fluorescence intensity analogous to the FRET efficiency of a two-color experiment:
<img alt="Equation 2" src="/files/ftp_upload/56896/56896eq2.jpg" />
Where, <img alt="Equation 3" src="/files/ftp_upload/56896/56896eq3v2.jpg" /> is the intensity in emission channel em after excitation with color ex, and c is the acceptor with the longest wavelength. Detection channels represent the same position in the sample chamber but record different spectral ranges of the fluorescence light. The same identifier for excitation and emission are used in this protocol (i.e., &#34;blue,&#34;&#160;&#34;green,&#34;&#160;and &#34;red&#34;).
Because of experimental shortcomings the measured fluorescence intensities depend not only on the energy transfer but also on fluorophore and setup properties. In order to obtain the true energy transfer efficiency between two fluorophores, the measured intensities have to be corrected. The following procedure is based on reference9. Correction factors for apparent leakage (lk, i.e., the detection of photons from a fluorophore in a channel designated for another dye) and apparent gamma (ag, i.e., the fluorescence quantum yield of the dye and the detection efficiency of the channel) are obtained from single-molecule traces that show an acceptor bleaching event.
The leakage of the donor dye into every possible acceptor channel is calculated from all data points in the recorded fluorescence traces where the acceptor dye bleached but the donor is still fluorescent (<img alt="Equation 4" src="/files/ftp_upload/56896/56896eq4.jpg" />):
<img alt="Equation 5" src="/files/ftp_upload/56896/56896eq5.jpg" />
The median of the leakage histogram is used as the apparent leakage factor. After correction for leakage, the apparent gamma factor is determined from the same set of traces. It is calculated by dividing the change of fluorescence in the acceptor channel by the change of fluorescence in the donor channel upon bleaching of the acceptor dye:
<img alt="Equation 6" src="/files/ftp_upload/56896/56896eq6.jpg" />
Where c again is the detection channel for the acceptor with the longest wavelength. The median of the resulting distribution is used as the apparent correction factor.
The corrected intensities in each channel are obtained by:
<img alt="Equation 7" src="/files/ftp_upload/56896/56896eq7.jpg" />
The PF is then calculated according to:
<img alt="Equation 8" src="/files/ftp_upload/56896/56896eq8.jpg" />
Different populations can be separated in the multi-dimensional space spanned by the PFs. The position and width of each state is determined by fitting the data with multi-dimensional Gaussian functions. Subsequent optimization of one global HMM based on all PF traces provides a quantitative description of the observed kinetics. Even small changes of the rates are detectable.
HMMs provide a way of inferring a state model from a collection of noisy time traces. The system is considered to be in one of a set of discrete, hidden states at any given time and the actual observation (i.e., the emission) is a probabilistic function of this hidden state20. In the case of TIRFM smFRET data, the emission probabilities bi per state i can be modeled by continuous Gaussian probability density functions. At regularly spaced discrete time points, transitions from one to another state can occur according to the transition probability that is time-invariant and only depends on the current state. The transition matrix A contains these transition probabilities aij between all hidden states. The initial state distribution <img alt="Equation 9" src="/files/ftp_upload/56896/56896eq9.jpg" /> gives the state-specific probabilities <img alt="Equation 10" src="/files/ftp_upload/56896/56896eq10.jpg" /> for the first time point of a time trace. Using a maximum-likelihood approach, these parameters can be optimized to best describe the data with the Forward-Backward and Baum-Welch algorithms20,21. This yields the maximum likelihood estimators (MLE). Finally, the state sequence that most likely produced the trajectory of observations can be inferred with the Viterbi algorithm. In contrast to other HMM analyses of smFRET data24,25,26 we do not use the HMM as a mere &#34;smoothing&#34; of the data but extract the kinetic state model from the data set without the need for fitting dwell time histograms27. HMM analysis is done with in-house scripts using Igor Pro. Implementation of the code is based on reference21. We provide a software kit and exemplary data on our webpage in order to follow sections 5 and 6 of this protocol (https://www.singlemolecule.uni-freiburg.de/software/3d-fret). Full software is available upon request.
Time points in the data with PF &#60;-1 or PF &#62;2 in any detection channel are assigned the minimal emission probability for all states (10-200). This prevents artificial transitions at these data points.
The parameters for the emission probabilities are obtained from the fit of the 3D PF histogram with Gaussian functions as described in step 5.7. These parameters are kept fixed during the optimization of the HMM.
In the presented approach, the initial state distribution vector and the transition matrix are used globally to describe the entire ensemble of traces. They are updated based on all N molecules from the data set according to reference27.
Start parameters for the initial state distribution are determined from 2D projections of the PF histogram (step 5.3) and the transition probabilities are set to 0.05 with the exception of the probabilities to stay in the same state, which are chosen such that the probability to leave a certain state is normalized to unity.
A likelihood profiling method is used to give confidence intervals (CIs) for all transition rates21,22, which serve as meaningful estimates for their uncertainty. To calculate the bounds of the CI for a specific rate, the transition probability of interest is fixed to a value other than the MLE. This yields the test model &#955;&#39;. A likelihood ratio (LR) test of the likelihood <img alt="Equation 16" src="/files/ftp_upload/56896/56896eq16.jpg" /> given the data set 0 is performed according to:
<img alt="Equation 11" src="/files/ftp_upload/56896/56896eq11.jpg" />
The 95% confidence bound for the parameter is reached when LR exceeds 3.841, the 95% quantile of a x2-distribution with one degree of freedom22,23.
The power of the method is demonstrated using the Hsp90. This abundant protein is found in bacteria and eukaryotes and is part of the cellular stress response28. It is a promising drug target in cancer treatment29. Hsp90 is a homodimer with one nucleotide binding pocket in the N-terminal domain of each subunit30. It can undergo transitions between at least two globally distinct conformations, one closed and one N-terminal open, V-shaped conformation19,31,32. The dimeric nature directly raises the question of the interplay between the two nucleotide binding sites in Hsp90.
In the following, we provide a step-by-step protocol for the data acquisition and analysis of a three-color smFRET experiment on yeast Hsp90 and nucleotide. The conformation-dependent binding of fluorescently labeled AMP-PNP (AMP-PNP*, a non-hydrolyzable analog of ATP) is analyzed. The application of the described procedure permits the study of the nucleotide binding and at the same time the conformational changes of Hsp90 and thereby reveals the cooperativity between the two nucleotide binding pockets of Hsp90.

<table border="0" cellpadding="0" cellspacing="0" width="1301">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Setup</td>
			<td style="width:445px;"></td>
			<td style="width:167px;"></td>
			<td style="width:347px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">vibration-damped optical table&#160;&#160;</td>
			<td style="width:445px;">Newport, Irvine, CA, USA</td>
			<td style="width:167px;">RS2000</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">OBIS 473nm LX 75mW LASER</td>
			<td style="width:445px;">Coherent Inc, Santa Clara, CA, USA</td>
			<td style="width:167px;">1185052</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">OBIS 532nm LS 50mW LASER</td>
			<td style="width:445px;">Coherent Inc, Santa Clara, CA, USA</td>
			<td style="width:167px;">1261779</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">OBIS 594nm LS 60mW LASER</td>
			<td style="width:445px;">Coherent Inc, Santa Clara, CA, USA</td>
			<td style="width:167px;">1233470</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">OBIS 637nm LX 140mW LASER</td>
			<td style="width:445px;">Coherent Inc, Santa Clara, CA, USA</td>
			<td style="width:167px;">1196625</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">laser control unit</td>
			<td style="width:445px;">Coherent Inc, Santa Clara, CA, USA</td>
			<td style="width:167px;">1234465</td>
			<td style="width:347px;">Scientific Remote</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">aspheric telescope lenses</td>
			<td style="width:445px;">Thorlabs Inc, Newton, New Jersey, USA</td>
			<td style="width:167px;"></td>
			<td>d=25.4mm, f=50mm and f=100mm</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">CF ex1</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">ZET 473/10</td>
			<td>cleanup filter excitation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">CF ex2</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">ZET 532/10</td>
			<td>cleanup filter excitation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">CF ex3</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">ZET 594/10</td>
			<td>cleanup filter excitation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">CF ex4</td>
			<td style="width:445px;">Thorlabs Inc, Newton, New Jersey, USA</td>
			<td>FL635-10</td>
			<td>cleanup filter excitation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">DM ex1</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">ZQ594RDC</td>
			<td>dichroic mirror excitation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">DM ex2</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">570DCXR</td>
			<td>dichroic mirror excitation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">DM ex3</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">ZQ491RDC</td>
			<td>dichroic mirror excitation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">AOTFnC-Vis</td>
			<td style="width:445px;">AA Opto-Electronic, Orsay, France</td>
			<td style="width:167px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">&#955;/4 plate</td>
			<td style="width:445px;">Thorlabs Inc, Newton, New Jersey, USA</td>
			<td style="width:167px;">AQWP05M-600</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">CFI Apo TIRF 100x</td>
			<td style="width:445px;">Nikon Instruments Inc, Melville, NY, USA</td>
			<td style="width:167px;"></td>
			<td>high-NA objective</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">piezo focus positioner MIPOS 250 CAP</td>
			<td style="width:445px;">piezosystem jena GmbH, Jena, Germany</td>
			<td style="width:167px;"></td>
			<td>Piezo Controller NV 40/1 CLE</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">piezo stepper</td>
			<td style="width:445px;">Newport, Irvine, CA, USA</td>
			<td>PZA12</td>
			<td>PZC200-KT NanoPZ Actuator Kit</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">achromatic aspheric lenses</td>
			<td style="width:445px;">Qioptiq Photonics GmbH &#38; Co. KG, G&#246;ttingen, Germany</td>
			<td style="width:167px;">G322-304-000</td>
			<td>d=50mm, f=200mm</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">adjustable optical slit</td>
			<td style="width:445px;">Owis GmbH, Staufen i. Br., Germany</td>
			<td>27.160.1212</td>
			<td>max. aperture 12 x 12 mm</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">DM det1</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">T 600 LPXR</td>
			<td>dichroic mirror detection</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">DM det2</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">H 560 LPXR superflat</td>
			<td>dichroic mirror detection</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">DM det3</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">HC BS R635</td>
			<td>dichroic mirror detection</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">BP det1</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">525/40 BrightLine HC</td>
			<td>bandpass filter detection</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">BP det2</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">586/20 BrightLine HC</td>
			<td>bandpass filter detection</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">BP det3</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">631/36 BrightLine HC</td>
			<td>bandpass filter detection</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">BP det4</td>
			<td style="width:445px;">AHF analysentechnik AG, T&#252;bingen, Germany</td>
			<td style="width:167px;">700/75 ET Bandpass</td>
			<td>bandpass filter detection</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">optical shutters detection</td>
			<td style="width:445px;">Vincent Associates, Rochester, NY, USA</td>
			<td style="width:167px;">Uniblitz VS25S2T0&#160;</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">EMCCD iXon Ultra 897</td>
			<td style="width:445px;">Andor Technology Ltd, Belfast, Northern Ireland</td>
			<td style="width:167px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">digital I/O card, PCIe-6535</td>
			<td style="width:445px;">National Instruments, Austin, Texas, USA</td>
			<td style="width:167px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">syringe pump</td>
			<td style="width:445px;">Harvard Apparatus, Holliston, MA, USA</td>
			<td style="width:167px;">PHD22/2000</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Name</td>
			<td style="width:445px;">Company</td>
			<td style="width:167px;">Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Flow chamber</td>
			<td style="width:445px;"></td>
			<td style="width:167px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">quartz slides</td>
			<td style="width:445px;">G. Finkenbeiner Inc, Waltham, MA, USA</td>
			<td style="width:167px;"></td>
			<td>Spectrosil2000, h=3mm</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">TEGADERM film</td>
			<td style="width:445px;">3M Deutschland GmbH, Neuss, Germany</td>
			<td style="width:167px;">1626W</td>
			<td>10 x 12cm</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">spray adhesive</td>
			<td style="width:445px;">3M Deutschland GmbH, Neuss, Germany</td>
			<td style="width:167px;">Photo Mount 050777</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">glycerol</td>
			<td style="width:445px;">Carl Zeiss AG, Oberkochen, Germany</td>
			<td style="width:167px;">Immersol G</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">immersion oil</td>
			<td style="width:445px;">OLYMPUS EUROPA SE &#38; CO. KG, Hamburg, Germany</td>
			<td>IMMOIL-F30CC</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">prism</td>
			<td style="width:445px;">Vogelsberger Quarzglastechnik GmbH, Hauzenberg, Germany</td>
			<td style="width:167px;"></td>
			<td>Suprasil1</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">aluminium prism holder</td>
			<td style="width:445px;"></td>
			<td style="width:167px;"></td>
			<td>custom built</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">hollow setscrews</td>
			<td style="width:445px;">Thorlabs Inc, Newton, New Jersey, USA</td>
			<td style="width:167px;"></td>
			<td>with custom drilling</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Tygon S3 E-3603 tubing</td>
			<td style="width:445px;">neoLab Migge GmbH, Heidelberg, Germany</td>
			<td style="width:167px;">2-4450</td>
			<td>ACF00001</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">PTFE tubing</td>
			<td style="width:445px;">Bohlender GmbH, Gr&#252;nsfeld, Germany</td>
			<td style="width:167px;">S1810-08</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Name</td>
			<td style="width:445px;">Company</td>
			<td style="width:167px;">Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Sample</td>
			<td style="width:445px;"></td>
			<td style="width:167px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">yeast Hsp90 D61C, Q385C_biotin</td>
			<td style="width:445px;"></td>
			<td style="width:167px;"></td>
			<td>UniProt ID P02829</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Maleimide derivatives of Atto488, Atto550</td>
			<td style="width:445px;">ATTO-TEC GmbH, Siegen, Germany</td>
			<td style="width:167px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">AMP-PNP*</td>
			<td style="width:445px;">Jena Bioscience, Jena, Germany</td>
			<td style="width:167px;"></td>
			<td style="width:347px;">&#947;-[(6-Aminohexyl)-imido]-AMP-PNP-Atto647N</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Fluospheres</td>
			<td style="width:445px;">Thermo Fisher Scientific, Waltham, MA, USA</td>
			<td style="width:167px;">F8764</td>
			<td>amine-modified, 0.2 &#956;m, yellow-green fluorescent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Name</td>
			<td style="width:445px;">Company</td>
			<td style="width:167px;">Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Software</td>
			<td style="width:445px;"></td>
			<td style="width:167px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Andor Solis</td>
			<td style="width:445px;">Andor Technology Ltd, Belfast, Northern Ireland</td>
			<td style="width:167px;"></td>
			<td>version 4.30</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">LabVIEW</td>
			<td style="width:445px;">National Instruments, Austin, Texas, USA</td>
			<td style="width:167px;"></td>
			<td>version 2012, 32bit; misc. hardware control</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">MDS control software</td>
			<td style="width:445px;">AA Opto-Electronic, Orsay, France</td>
			<td style="width:167px;"></td>
			<td>version 2.03a</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Coherent Connection</td>
			<td style="width:445px;">Coherent Inc, Santa Clara, CA, USA</td>
			<td style="width:167px;"></td>
			<td>version 3</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Igor Pro</td>
			<td style="width:445px;">WaveMetrics Inc, Portland, OR, USA</td>
			<td style="width:167px;"></td>
			<td>version 6.37</td>
		</tr>
	</tbody>
</table>

using three-color single-molecule fret to study the correlation of protein interactions

Single-molecule F&#246;rster resonance energy transfer (smFRET) has become a widely used biophysical technique to study the dynamics of biomolecules. For many molecular machines in a cell proteins have to act together&#160;with interaction partners in a functional cycle to fulfill their task. The extension of two-color to multi-color smFRET makes it possible to simultaneously probe more than one interaction or conformational change. This not only adds a new dimension to smFRET experiments but it also offers the unique possibility to directly study the sequence of events and to detect correlated interactions when using an immobilized sample and a total internal reflection fluorescence microscope (TIRFM). Therefore, multi-color smFRET is a versatile tool for studying biomolecular complexes in a quantitative manner and in a previously unachievable detail.
Here, we demonstrate how to overcome the special challenges of multi-color smFRET experiments on proteins. We present detailed protocols for obtaining the data and for extracting kinetic information. This includes trace selection criteria, state separation, and the recovery of state trajectories from the noisy data using a 3D ensemble Hidden Markov Model (HMM). Compared to other methods, the kinetic information is not recovered from dwell time histograms but directly from the HMM. The maximum likelihood framework allows us to critically evaluate the kinetic model and to provide meaningful uncertainties for the rates.
By applying our method to the heat shock protein 90 (Hsp90), we are able to disentangle the nucleotide binding and the global conformational changes of the protein. This allows us to directly observe the cooperativity between the two nucleotide binding pockets of the Hsp90 dimer.

Multi-color smFRET measurements allow the direct detection of correlation between two or more distinct interaction sites. This renders the technique unique to investigate multi-component systems, such as protein complexes. We focus on the presentation of a three-color smFRET experiment here, which serves as an illustrative example.
The general workflow of the method is shown in Figure 1. The first part comprises the recording of multi-color smFRET data on a prism-type TIRF microscope. The surface attachment strategy and the schematics of the setup are depicted in Figure 2A. For a more detailed description of the setup, refer to reference9. The second part of the presented method focuses on the data analysis. Exemplary fluorescence intensity traces are shown in Figure 2B. Suitable time traces show: (i) a clear bleaching step for both fluorophores attached to Hsp90, (ii) flat intensity plateaus, (iii) anti-correlated behavior in the corresponding channels, and (iv) at least one binding event of AMP-PNP* (Figure 3). More than 400 molecules that meet the selection criteria were selected to yield reliable statistics. In the studied system, five states can be distinguished by the fluorescence intensities, with four states being functionally distinct (Figure 2C).
From the fluorescence intensity traces the partial fluorescence (PF, the extension of the FRET efficiency for multi-color smFRET experiments) can be calculated (Figure 4A). The PF is related to the proximity of the dyes. In a three-color smFRET experiment, the data spans a 3D space (Figure 5B). 2D projections of the 3D histogram have proven to be useful for state separation (Figure 4B, C). In a successful experiment, all states that are theoretically expected under the applied experimental conditions are distinguishable by their PF in the 2D projections.
The relative populations of the states are determined from the 2D projections by drawing free-hand polygons that enclose the peak (Figure 5C). This approach was found to be accurate and reliable9. The emission probabilities for the HMM are obtained by fitting the 3D PF histogram with the sum of 3D Gaussian functions, where S is the number of distinguishable states (five in the presented case; Figure 5D). For this fit to converge properly, only the relative population pi of each state i has to be held constant while the position and width of the Gaussians are free.
One ensemble HMM is optimized over the full data set with the emission probabilities fixed to the parameters obtained from the Gaussian fit (Figure 6). In order to get a measure for the uncertainty of the extracted transition probabilities, the 95% CI for each transition is determined (Figure 7).
In addition, the average time that the labeled reporter nucleotide AMP-PNP* remains bound to Hsp90 can be extracted under different experimental conditions (Figure 8A). This helps to further reduce the complexity of the results. To do so, states that represent AMP-PNP* bound and unbound conformations are collapsed in the state trajectories, respectively. From this the average dwell time for the AMP-PNP* dissociation can be calculated (Figure 8B).
By comparing the kinetics observed in the absence and the presence of additional, unlabeled AMP-PNP, unique information on the correlation between the conformational changes of Hsp90 and the nucleotide state can be gained. This makes it possible to directly study the cooperativity between the two nucleotide binding pockets of Hsp90. Besides, it circumvents the need for titration experiments that measure the binding site occupation as a function of the substrate concentration (e.g., Hill plots). For highly dynamic protein systems such as Hsp90, this approach is also sensitive to small changes in the rates11.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56896/56896fig1.jpg" /> 
Figure 1: General workflow of the data acquisition and analysis. Data is acquired on a multi-color smFRET total internal reflection fluorescence microscope (TIRFM). After trace selection and calculation of the partial fluorescence (PF), the 3D PF histogram and 2D projections thereof are compiled. Using the 2D projections, the population of all distinguishable states can be determined. These are used as a constraint for a 3D Gaussian fit to the PF histogram. The Gaussian probability density functions serve as emission probabilities for the subsequent 3D ensemble Hidden Markov Modeling (HMM). This yields the kinetic description of the system. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56896/56896fig1large.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/56896/56896fig2.jpg" /> 
Figure 2: Scheme of the data acquisition. (A) Pictogram of the studied system consisting of an Hsp90 dimer (yellow ovals represent the domain structure) attached to the surface with the labels Atto488 (blue) and Atto550 (green) and the reporter nucleotide AMP-PNP* in solution, labeled with Atto647N (red). Data are recorded on a prism-type TIRF microscope with alternating laser excitation (ALEX). (B) Exemplary fluorescence intensity (Fl. Int.) traces after blue and green excitation. (C) Pictograms of the distinguishable conformational states of Hsp90 (S0, S1, S2, S3, S4) and their respective identifier for the functional state (O, C, O*, C*) used in this work. Fluorophore positions are indicated in blue, green, and red. Two populations represent the same functional state, namely open Hsp90 with AMP-PNP* bound (S2 and S3). <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56896/56896fig2large.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/56896/56896fig3.jpg" /> 
Figure 3: Selection criteria. (A) A molecule selected for further analysis. (B, C) Molecules not selected for further analysis. (B) No flat plateaus and Atto550 is in a dark state around 30 s after green excitation (indicated by arrows). (C) Multiple bleaching steps after green excitation (indicated by arrows). Fl. Int.: fluorescence intensity, blue: Atto488, green: Atto550, red Atto647N, ex: excitation. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56896/56896fig3large.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/56896/56896fig4.jpg" /> 
Figure 4: Calculation of the PF traces and representative histograms. (A) Representative fluorescence intensity (Fl. Int.) traces and the corresponding partial fluorescence (PF) traces. (B) Two 2D projections of the 3D PF histogram for the measurement in absence of additional, unlabeled nucleotide. (C) The same projections for the experiment in the presence of additional 250 &#181;M AMP-PNP. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56896/56896fig4large.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/56896/56896fig5.jpg" /> 
Figure 5: Population selection process. (A) The position of the five distinguishable populations in the two 2D projections. (B) Copy of the pictograms in Figure 2C. (C) Representative 3D scatter plot of the PF data. Coloration of the data points is only for visualization. The same color code as in B is used. (D) Determination of the relative populations is done by drawing free-hand polygons around the peaks in the 2D histogram. Using a combination of the two projections depicted in Figure 3, all five populations can be distinguished. (E) Results of the 3D Gaussian fit to the histogram of the PF data shown in A. Depicted are the isosurfaces at FWHM, which represent the five different populations. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56896/56896fig5large.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/56896/56896fig6.jpg" /> 
Figure 6: Flow chart of the ensemble 3D HMM optimization. One model is optimized for all molecules from the data set. The start values are given by the input model (with a pre-defined number of states). The likelihood of the model given the data (the 3D&#160;PF traces) is rated with the Forward-Backward (FB) algorithm. The Baum-Welch (BW) algorithm yields a local maximum likelihood estimate (MLE) of the parameters. The global MLE then can be found iteratively. The Viterbi algorithm computes the most likely state trajectory given a model. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56896/56896fig6large.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/56896/56896fig7.jpg" /> 
Figure 7: Meaningful uncertainty estimation with CI. (A) Determination of the CI for one exemplary rate constant. The likelihood ratio (LR) of the test model compared to the maximum likelihood estimator (MLE) model is calculated in the region around the MLE for the rate constant. The 95% confidence bound is reached when the LR exceeds 3.841 (horizontal dark grey line). (B) The extracted rate constants without additional nucleotide (red) and with AMP-PNP (blue) and their 95% CI. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56896/56896fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/56896/56896fig8.jpg" /> 
Figure 8: The average dwell time of the reporter nucleotide AMP-PNP* bound to Hsp90 is prolonged in presence of additional nucleotide. (A) Pictogram of the observed dissociation of labeled AMP-PNP* from the Hsp90 dimer, averaging over all conformations of Hsp90. The domain structure of Hsp90 is depicted by yellow ovals and the conformational flexibility is indicated by overlaying an open and closed dimer. (B) Average dwell time of AMP-PNP* bound to Hsp90 in absence of additional nucleotide (red) and in presence of 250 &#181;M unlabeled AMP-PNP (blue). <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56896/56896fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions at JoVE.com

Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions

Here, we present a protocol to obtain three-color smFRET data and its analysis with a 3D ensemble Hidden Markov Model. With this approach, scientists can extract kinetic information from complex protein systems, including cooperativity or correlated interactions.

Single-molecule F&#246;rster resonance energy transfer (smFRET) has become a widely used biophysical technique to study the dynamics of biomolecules. For ...

using-three-color-single-molecule-fret-to-study-correlation-protein

Nanyang Technological University

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JoVE Journal

Biochemistry

10.0K Views.  University of Freiburg. Here, we present a protocol to obtain three-color smFRET data and its analysis with a 3D ensemble Hidden Markov Model. With this approach, scientists can extract kinetic information from complex protein systems, including cooperativity or correlated interactions.

Video: Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions

Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions

Protein-protein interactions play an essential role in the function of a living organism. Once an interaction has been identified and validated it is necessary to characterize it at the structural and mechanistic level. Several biochemical and biophysical methods exist for such purpose. Among them, fluorescence anisotropy is a powerful technique particularly used when the fluorescence intensity of a fluorophore-labeled protein remains constant upon protein-protein interaction. In this technique, a fluorophore-labeled protein is excited with vertically polarized light of an appropriate wavelength that selectively excites a subset of the fluorophores according to their relative orientation with the incoming beam. The resulting emission also has a directionality whose relationship in the vertical and horizontal planes defines anisotropy (r) as follows: r=(IVV-IVH)/(IVV+2IVH), where IVV and IVH are the fluorescence intensities of the vertical and horizontal components, respectively. Fluorescence anisotropy is sensitive to the rotational diffusion of a fluorophore, namely the apparent molecular size of a fluorophore attached to a protein, which is altered upon protein-protein interaction. In the present text, the use of fluorescence anisotropy as a tool to study protein-protein interactions was exemplified to address the binding between the protein mutated in the Shwachman-Diamond Syndrome (SBDS) and the Elongation factor like-1 GTPase (EFL1). Conventionally, labeling of a protein with a fluorophore is carried out on the thiol groups (cysteine) or in the amino groups (the N-terminal amine or lysine) of the protein. However, SBDS possesses several cysteines and lysines that did not allow site directed labeling of it. As an alternative technique, the dye 4&#39;,5&#39;-bis(1,3,2 dithioarsolan-2-yl) fluorescein was used to specifically label a tetracysteine motif, Cys-Cys-Pro-Gly-Cys-Cys, genetically engineered in the C-terminus of the recombinant SBDS protein. Fitting of the experimental data provided quantitative and mechanistic information on the binding mode between these proteins.

Protein interactions are at the heart of a cell&#39;s function. Calorimetric and spectroscopic techniques are commonly used to characterize them. Here we describe fluorescence anisotropy as a tool to study the interaction between the protein mutated in the Shwachman-Diamond Syndrome (SBDS) and the Elongation factor-like 1 GTPase (EFL1).

Protein-protein interactions play an essential role in the function of a living organism. Once an interaction has been identified and validated it is ...

Structural Information from Single-molecule FRET Experiments Using the Fast Nano-positioning System

Single-molecule F&#246;rster Resonance Energy Transfer (smFRET) can be used to obtain structural information on biomolecular complexes in real-time. Thereby, multiple smFRET measurements are used to localize an unknown dye position inside a protein complex by means of trilateration. In order to obtain quantitative information, the Nano-Positioning System (NPS) uses probabilistic data analysis to combine structural information from X-ray crystallography with single-molecule fluorescence data to calculate not only the most probable position but the complete three-dimensional probability distribution, termed posterior, which indicates the experimental uncertainty. The concept was generalized for the analysis of smFRET networks containing numerous dye molecules. The latest version of NPS, Fast-NPS, features a new algorithm using Bayesian parameter estimation based on Markov Chain Monte Carlo sampling and parallel tempering that allows for the analysis of large smFRET networks in a comparably short time. Moreover, Fast-NPS allows the calculation of the posterior by choosing one of five different models for each dye, that account for the different spatial and orientational behavior exhibited by the dye molecules due to their local environment.
Here we present a detailed protocol for obtaining smFRET data and applying the Fast-NPS. We provide detailed instructions for the acquisition of the three input parameters of Fast-NPS: the smFRET values, as well as the quantum yield and anisotropy of the dye molecules. Recently, the NPS has been used to elucidate the architecture of an archaeal open promotor complex. This data is used to demonstrate the influence of the five different dye models on the posterior distribution.

We present the setup and experimental procedure to obtain smFRET data from large donor-acceptor networks with a TIRF microscope. The step-by-step analysis of these measurements with the Bayesian inference software Fast-NPS yields high-resolved structural information via the application of adapted dye models.

Single-molecule F&#246;rster Resonance Energy Transfer (smFRET) can be used to obtain structural information on biomolecular complexes in real-time. ...

Using Scaffold Liposomes to Reconstitute Lipid-proximal Protein-protein Interactions In Vitro

Studies of integral membrane proteins in vitro are frequently complicated by the presence of a hydrophobic transmembrane domain. Further complicating these studies, reincorporation of detergent-solubilized membrane proteins into liposomes is a stochastic process where protein topology is impossible to enforce. This paper offers an alternative method to these challenging techniques that utilizes a liposome-based scaffold. Protein solubility is enhanced by deletion of the transmembrane domain, and these amino acids are replaced with a tethering moiety, such as a His-tag. This tether interacts with an anchoring group (Ni2+ coordinated by nitrilotriacetic acid (NTA(Ni2+)) for His-tagged proteins), which enforces a uniform protein topology at the surface of the liposome. An example is presented wherein the interaction between Dynamin-related protein 1 (Drp1) with an integral membrane protein, Mitochondrial Fission Factor (Mff), was investigated using this scaffold liposome method. In this work, we have demonstrated the ability of Mff to efficiently recruit soluble Drp1 to the surface of liposomes, which stimulated its GTPase activity. Moreover, Drp1 was able to tubulate the Mff-decorated lipid template in the presence of specific lipids. This example demonstrates the effectiveness of scaffold liposomes using structural and functional assays and highlights the role of Mff in regulating Drp1 activity.

Using Scaffold Liposomes to Reconstitute Lipid-proximal Protein-protein Interactions In Vitro

This paper describes a method for assessing the interactions and assemblies of integral membrane proteins in vitro with various partner factors in a lipid-proximal environment.

Studies of integral membrane proteins in vitro are frequently complicated by the presence of a hydrophobic transmembrane domain. Further complicating ...

High Precision FRET at Single-molecule Level for Biomolecule Structure Determination

A protocol on how to perform high-precision interdye distance measurements using F&#246;rster resonance energy transfer (FRET) at the single-molecule level in multiparameter fluorescence detection (MFD) mode is presented here. MFD maximizes the usage of all &#34;dimensions&#34; of fluorescence to reduce photophysical and experimental artifacts and allows for the measurement of interdye distance with an accuracy up to ~1 &#197; in rigid biomolecules. This method was used to identify three conformational states of the ligand-binding domain of the N-methyl-D-aspartate (NMDA) receptor to explain the activation of the receptor upon ligand binding. When comparing the known crystallographic structures with experimental measurements, they agreed within less than 3 &#197; for more dynamic biomolecules. Gathering a set of distance restraints that covers the entire dimensionality of the biomolecules would make it possible to provide a structural model of dynamic biomolecules.

A protocol for high-precision FRET experiments at the single molecule level is presented here. Additionally, this methodology can be used to identify three conformational states in the ligand-binding domain of the N-methyl-D-aspartate (NMDA) receptor. Determining precise distances is the first step towards building structural models based on FRET experiments.

A protocol on how to perform high-precision interdye distance measurements using F&#246;rster resonance energy transfer (FRET) at the single-molecule ...

Biotinylated Cell-penetrating Peptides to Study Intracellular Protein-protein Interactions

Here we present a protocol to study intracellular protein-protein interactions that is based on the widely used biotin-avidin pull-down system. The modification presented includes the combination of this technique with cell-penetrating sequences. We propose to design cell-penetrating baits that can be incubated with living cells instead of cell lysates and therefore the interactions found will reflect those that occur within the intracellular context. Connexin43 (Cx43), a protein that forms gap junction channels and hemichannels is down-regulated in high-grade gliomas. The Cx43 region comprising amino acids 266-283 is responsible for the inhibition of the oncogenic activity of c-Src in glioma cells. Here we use TAT as the cell-penetrating sequence, biotin as the pull-down tag and the region of Cx43 comprised between amino acids 266-283 as the target to find intracellular interactions in the hard-to-transfect human glioma stem cells. One of the limitations of the proposed method is that the molecule used as bait could fail to fold properly and, consequently, the interactions found could not be associated with the effect. However, this method can be especially interesting for the interactions involved in signal transduction pathways because they are usually carried out by intrinsically disordered regions and, therefore, they do not require an ordered folding. In addition, one of the advantages of the proposed method is that the relevance of each residue on the interaction can be easily studied. This is a modular system; therefore, other cell-penetrating sequences, other tags, and other intracellular targets can be employed. Finally, the scope of this protocol is far beyond protein-protein interaction because this system can be applied to other bioactive cargoes such as RNA sequences, nanoparticles, viruses or any molecule that can be transduced with cell-penetrating sequences and fused to pull-down tags to study their intracellular mechanism of action.

This is a protocol to study intracellular protein-protein interactions based on the biotin-avidin pull-down system with the novelty of combining cell-penetrating sequences. The main advantage is that the target sequence is incubated with living cells instead of cell lysates and therefore the interactions will occur within the cellular context.

Here we present a protocol to study intracellular protein-protein interactions that is based on the widely used biotin-avidin pull-down system. The ...

Covalent Immobilization of Proteins for the Single Molecule Force Spectroscopy

In recent years, atomic force microscopy (AFM) based single molecule force spectroscopy (SMFS) extended our understanding of molecular properties and functions. It gave us the opportunity to explore a multiplicity of biophysical mechanisms, e.g., how bacterial adhesins bind to host surface receptors in more detail. Among other factors, the success of SMFS experiments depends on the functional and native immobilization of the biomolecules of interest on solid surfaces and AFM tips. Here, we describe a straightforward protocol for the covalent coupling of proteins to silicon surfaces using silane-PEG-carboxyls and the well-established N-hydroxysuccinimid/1-ethyl-3-(3-dimethyl-aminopropyl)carbodiimid (EDC/NHS) chemistry in order to explore the interaction of pilus-1 adhesin RrgA from the Gram-positive bacterium Streptococcus pneumoniae (S. pneumoniae) with the extracellular matrix protein fibronectin (Fn). Our results show that the surface functionalization leads to a homogenous distribution of Fn on the glass surface and to an appropriate concentration of RrgA on the AFM cantilever tip, apparent by the target value of up to 20% of interaction events during SMFS measurements and revealed that RrgA binds to Fn with a mean force of 52 pN. The protocol can be adjusted to couple via site specific free thiol groups. This results in a predefined protein or molecule orientation and is suitable for other biophysical applications besides the SMFS.

This protocol describes the covalent immobilization of proteins with a heterobifunctional silane coupling agent to silicon-oxide surfaces designed for the atomic force microscopy based single molecule force spectroscopy which is exemplified by the interaction of RrgA (pilus-1 tip adhesin of S. pneumoniae) with fibronectin.

In recent years, atomic force microscopy (AFM) based single molecule force spectroscopy (SMFS) extended our understanding of molecular properties and ...

Making Precise and Accurate Single-Molecule FRET Measurements using the Open-Source smfBox

The smfBox is a recently developed cost-effective, open-source instrument for single-molecule F&#246;rster Resonance Energy Transfer (smFRET), which makes measurements on freely diffusing biomolecules more accessible. This overview includes a step-by-step protocol for using this instrument to make measurements of precise FRET efficiencies in duplex DNA samples, including details of the sample preparation, instrument setup and alignment, data acquisition, and complete analysis routines. The presented approach, which includes how to determine all the correction factors required for accurate FRET-derived distance measurements, builds on a large body of recent collaborative work across the FRET Community, which aims to establish standard protocols and analysis approaches. This protocol, which is easily adaptable to a range of biomolecular systems, adds to the growing efforts in democratising smFRET for the wider scientific community.

This article provides step-by-step instructions for making fully-corrected accurate FRET measurements on individual, freely diffusing biomolecules using the open-source, inexpensive smfBox, from switch on, through alignment and focusing, to data collection and analysis.

The smfBox is a recently developed cost-effective, open-source instrument for single-molecule F&#246;rster Resonance Energy Transfer (smFRET), which makes ...

Optical Tweezers to Study RNA-Protein Interactions in Translation Regulation

RNA adopts diverse structural folds, which are essential for its functions and thereby can impact diverse processes in the cell. In addition, the structure and function of an RNA can be modulated by various trans-acting factors, such as proteins, metabolites or other RNAs. Frameshifting RNA molecules, for instance, are regulatory RNAs located in coding regions, which direct translating ribosomes into an alternative open reading frame, and thereby act as gene switches. They may also adopt different folds after binding to proteins or other trans-factors. To dissect the role of RNA-binding proteins in translation and how they modulate RNA structure and stability, it is crucial to study the interplay and mechanical features of these RNA-protein complexes simultaneously.&#160;This work illustrates how to employ single-molecule-fluorescence-coupled optical tweezers to explore the conformational and thermodynamic landscape of RNA-protein complexes at a high resolution. As an example, the interaction of the SARS-CoV-2 programmed ribosomal frameshifting element with the trans-acting factor short isoform of zinc-finger antiviral protein is elaborated. In addition, fluorescence-labeled ribosomes were monitored using the confocal unit, which would ultimately enable the study of translation elongation. The fluorescence coupled OT assay can be widely applied to explore diverse RNA-protein complexes or trans-acting factors regulating translation and could facilitate studies of RNA-based gene regulation.

This protocol presents a complete experimental workflow for studying RNA-protein interactions using optical tweezers. Several possible experimental setups are outlined including the combination of optical tweezers with confocal microscopy.

RNA adopts diverse structural folds, which are essential for its functions and thereby can impact diverse processes in the cell. In addition, the ...

Single Molecule Fluorescence Energy Transfer Study of Ribosome Protein Synthesis

The ribosome is a large ribonucleoprotein complex that assembles proteins processively along mRNA templates. The diameter of the ribosome is approximately 20 nm to accommodate large tRNA substrates at the A-, P- and E-sites. Consequently, the ribosome dynamics are naturally de-phased quickly. Single molecule method can detect each ribosome separately and distinguish inhomogeneous populations, which is essential to reveal the complicated mechanisms of multi-component systems. We report the details of a smFRET method based on the Nikon Ti2 inverted microscope to probe the ribosome dynamics between the ribosomal protein L27 and tRNAs. The L27 is labeled at its unique Cys 53 position and reconstituted into a ribosome that is engineered to lack L27. The tRNA is labeled at its elbow region. As the tRNA moves to different locations inside the ribosome during the elongation cycle, such as pre- and post- translocation, the FRET efficiencies and dynamics exhibit differences, which have suggested multiple subpopulations. These subpopulations are not detectable by ensemble methods. The TIRF-based smFRET microscope is built on a manual or motorized inverted microscope, with home-built laser illumination. The ribosome samples are purified by ultracentrifugation, loaded into a home-built multi-channel sample cell and then illuminated via an evanescent laser field. The reflection laser spot can be used to achieve feedback control of perfect focus. The fluorescence signals are separated by a motorized filter-turret and collected by two digital CMOS cameras. The intensities are retrieved via the NIS-Elements software.

Single molecule fluorescence energy transfer is a method that tracks the tRNA dynamics during ribosomal protein synthesis. By tracking individual ribosomes, inhomogeneous populations are identified, which shed light on mechanisms. This method can be used to track biological conformational changes in general to reveal dynamic-function relationships in many other complexed biosystems. Single molecule methods can observe non-rate limiting steps and low-populated key intermediates, which are not accessible by conventional ensemble methods due to the average effect.

The ribosome is a large ribonucleoprotein complex that assembles proteins processively along mRNA templates. The diameter of the ribosome is approximately ...

Dual-Color Fluorescence Cross-Correlation Spectroscopy to Study Protein-Protein Interaction and Protein Dynamics in Live Cells

We present a protocol and workflow to perform live cell dual-color fluorescence cross-correlation spectroscopy (FCCS) combined with F&#246;rster Resonance Energy transfer (FRET) to study membrane receptor dynamics in live cells using modern fluorescence labeling techniques. In dual-color FCCS, where the fluctuations in fluorescence intensity represent the dynamic &#34;fingerprint&#34; of the respective fluorescent biomolecule, we can probe co-diffusion or binding of the receptors. FRET, with its high sensitivity to molecular distances, serves as a well-known &#34;nanoruler&#34; to monitor intramolecular changes. Taken together, conformational changes and key parameters such as local receptor concentrations and mobility constants become accessible in cellular settings.
Quantitative fluorescence approaches are challenging in cells due to high noise levels and the vulnerability of the sample. Here we show how to perform this experiment, including the calibration steps using dual-color labeled &#946;2-adrenergic receptor (&#946;2AR) labeled with eGFP and SNAP-tag-TAMRA. A step-by-step data analysis procedure is provided using open-source software and templates that are easy to customize.
Our guideline enables researchers to unravel molecular interactions of biomolecules in live cells in situ with high reliability despite the limited signal-to-noise levels in live cell experiments. The operational window of FRET and particularly FCCS at low concentrations allows quantitative analysis at near-physiological conditions.

We present an experimental protocol and data analysis workflow to perform live cell dual-color fluorescence cross correlation spectroscopy (FCCS) combined with F&#246;rster Resonance Energy transfer (FRET) to study membrane receptor dynamics in live cells using modern fluorescence labeling techniques.

We present a protocol and workflow to perform live cell dual-color fluorescence cross-correlation spectroscopy (FCCS) combined with F&#246;rster Resonance ...