Name: a fluorescence fluctuation spectroscopy assay of protein-protein interactions at cell-cell contacts
Uploaded: 2018-12-01T13:00:00
Description: Watch this Scientific Journal Video about A Fluorescence Fluctuation Spectroscopy Assay of Protein-Protein Interactions at Cell-Cell Contacts at JoVE.com

This work was partially supported by the Deutsche Forschungsgemeinschaft (DFG) grant 254850309. The authors thank Madlen Luckner for critical reading of the manuscript.

1. Sample Preparation: Cell-Cell Mixing Assay
NOTE: The following protocol describes the mixing procedure for adherent cells. It may be modified for cells cultured in suspension.
<ol>
	<li>Seed an appropriate number of cells on a 6-well plate, e.g., 800,000 HEK 293T cells (counted with a Neubauer counting chamber), a day before transfection. The number can be modified depending on the time between seeding and transfection and adjusted for other cell types. To perform a basic experim...

The experimental procedure described here allows the investigation of protein-protein trans interactions at cell-cell contacts, employing fluorescence fluctuation spectroscopy techniques, namely sFCCS and ccN&#38;B. These methods involve a statistical analysis of fluorescence fluctuations emitted by two spectrally separated FPs fused to the protein(s) of interest at a contact of two neighboring cells, each expressing one or the other fusion protein. The presence of trans complexes is quantified by probi...

Many biological processes occur at the sites of cell-cell interactions, e.g., cell-cell adhesion1,2,3, cell-cell fusion4 and cellular recognition5. Such events are particularly important during the development of multicellular organisms and for cell-cell communication, e.g., during immune responses. These processes are typically mediated by proteins that are localized at the surface, i.e., at the plasma membrane (PM) of neighboring cells and undergo specific interactions at the cell-cell contact that are precisely regulated in space and time. In many cases, these interactions are direct homo- or heterotypic protein-protein trans interactions, but may also involve ions or ligands acting as extracellular linkers1. Although of fundamental importance, there is a lack of assays probing these specific protein-protein interactions directly in the native environment of living cells. Many methods either require cell disruption (e.g., biochemical assays such as co-immunoprecipitation6), fixation (e.g., some of the super-resolution optical microscopy techniques and electron microscopy of cell-cell contacts7), or are non-specific, e.g., aggregation/ adhesion assays8,9. To overcome this issue, fluorescence techniques have been implemented based on fluorescence resonance energy transfer (FRET)10 or fluorescence complementation11. However, to achieve sufficiently small distances between fluorophores, these methods require fluorescent labels on the extracellular side of the proteins10, potentially interfering with trans interactions.
Here, we present an alternative fluorescence-based assay for protein-protein interactions at cell-cell contacts. This approach combines fluorescence cross-correlation approaches (scanning fluorescence cross-correlation spectroscopy (sFCCS), cross-correlation number and brightness (ccN&#38;B)) and mixing of cells expressing a fusion construct of the protein of interest, e.g., an adhesion receptor. The investigated receptors in the two interacting cells are labeled with two spectrally separated fluorescent proteins (FPs), from the intracellular side (see Figure 1A).
The employed methods are based on the statistical analysis of fluorescence fluctuations induced by the diffusive motion of fluorescent fusion proteins through the focal volume of a confocal laser scanning microscope. More in detail, the assay probes the co-diffusion of the proteins of interest in both neighboring PMs at cell-cell contacts. If the proteins undergo trans interactions, these trans complexes will carry fluorescent proteins emitting in both spectral channels, causing correlated fluorescence fluctuations of both emitters. On the other hand, if no binding occurs, the number fluctuations of proteins in facing PMs will be independent, causing no correlated fluctuations. The acquisition can be performed in two ways: 1) sFCCS is based on a line-shaped scan across the cell-cell contact and effectively probes the interactions in a spot located in the contact region. Through a temporal analysis of fluorescence fluctuations, sFCCS provides also dynamics information, i.e., the diffusion coefficients of protein complexes; 2) ccN&#38;B is based on a pixel-wise analysis of a sequence of images acquired at the cell-cell contact regions. It has capability to probe and map interactions along the whole contact region (in one focal plane), but does not provide information on dynamics. Both methods can be combined with an analysis of the molecular brightness, i.e., the average fluorescence signal emitted in the time unit by single diffusing protein complexes and, thus, provide estimates of the stoichiometry of protein complexes at cell-cell contacts.
In this article, we provide detailed protocols for sample preparation, instrument calibration, data acquisition and analysis to perform the presented assay on a commercial confocal laser scanning microscope. The experiments can be performed on any instrument equipped with photon counting or analog detectors and an objective with high numerical aperture. We further discuss critical steps of the protocol and provide correction schemes for several processes causing artefactual signal fluctuations, e.g., detector noise, photobleaching or cell movement. Originally developed to probe interactions between adherent cells, the assay may be modified for suspension cells, or adapted to model membrane systems, e.g., giant unilamellar vesicles (GUVs) or giant plasma membrane vesicles (GPMVs), allowing the quantification of interactions in different lipid environments or in the absence of an organized cytoskeleton12,13.
Scanning fluorescence cross-correlation spectroscopy is a modified version of fluorescence cross-correlation spectroscopy14 and was specifically designed to probe slow diffusive dynamics in lipid membranes15. It is based on a line scan acquisition perpendicular to the PM containing the fluorescent proteins of interest. To probe interactions of two differently labeled protein species, the acquisition is performed in two spectral channels using two laser lines and two detection windows for&#160;spectrally separated fluorophores. Due to the slow diffusion dynamics of proteins in the PM (D&#8804;~1 &#181;m2/s), a cross-talk-free measurement can be performed by alternating the excitation scheme from line to line15. The analysis starts with: 1) an alignment algorithm correcting for lateral cell movement based on block-wise averaging of ~1000 lines, 2) determination of the position with maximum fluorescence signal, i.e., the PM position, in each block and 3) shifting of all blocks to a common origin12,15, separately in each channel. Then, an automatic selection of pixels corresponding to the PM is performed by selecting the central region from a Gaussian fit of the sum of all aligned lines (i.e., center &#177; 2.5&#963;). Integration of the signal in each line yields the membrane fluorescence time series F(t) in each channel (g = green channel, r = red channel). Note that the pixel size has to be small enough, e.g., &#60;200 nm, to reconstruct the shape of the point spread function and find its center, corresponding to the position of the PM. In the presence of substantial photobleaching, the fluorescence time series in each channel may be modeled&#160;with a double-exponential function and then corrected with the following formula:16
<img alt="Equation 1" src="/files/ftp_upload/58582/58582eq2.jpg" />.&#160; &#160; (1)
It is important to note that this formula effectively corrects both the amplitudes and diffusion times obtained from correlation analysis of F(t)c, compared to parameter estimates that would be obtained from the uncorrected F(t). Then, the auto- and cross-correlation functions (ACFs/ CCFs) of the fluorescence signals are calculated:
<img alt="Equation 2" src="/files/ftp_upload/58582/58582eq3v2.jpg" />, (2)
<img alt="Equation 3" src="/files/ftp_upload/58582/58582eq4v2.jpg" />, (3)
where &#948;Fi = Fi(t) - <img alt="Image 1" src="/files/ftp_upload/58582/58582img1.jpg" />Fi(t)<img alt="Image 2" src="/files/ftp_upload/58582/58582img2.jpg" /> and i&#160;=&#160;g,r.
A two-dimensional diffusion model is then fitted to all correlation functions (CFs):
<img alt="Equation 4" src="/files/ftp_upload/58582/58582eq7.jpg" />.&#160; &#160;(4)
Here, N denotes the number of fluorescent proteins in the observation volume and &#964;d the diffusion time for each channel. This model takes into account that in the described experimental setting, diffusion of proteins in the PM occurs in the x-z plane, in contrast to the commonly used configuration of fluorescence correlation spectroscopy (FCS) experiments on membranes probing diffusion in the x-y plane of the confocal volume17. The waist w0 and the structure factor S, describing the elongation wz of the focal volume in z, S = wz/w0, are obtained from a point FCS calibration measurement performed with spectrally similar dyes and same optical settings using already available values for the diffusion coefficient Ddye:
<img alt="Equation 5" src="/files/ftp_upload/58582/58582eq8.jpg" />,&#160; &#160; (5)
where &#964;d,dye is the measured average diffusion time of the dye molecules, obtained from fitting a model for three-dimensional diffusion to the data, taking into account transitions of a fraction T of all N molecules to a triplet state with a time constant &#964;&#964;:
<img alt="Equation 6" src="/files/ftp_upload/58582/58582eq9.jpg" />.&#160; &#160;(6)
Finally, diffusion coefficients (D), molecular brightness values (&#949;) and the relative cross-correlation of sFCCS data (rel.cc.) are calculated as follows:
<img alt="Equation 7" src="/files/ftp_upload/58582/58582eq10.jpg" />,&#160; &#160; (7)
<img alt="Equation 8" src="/files/ftp_upload/58582/58582eq11.jpg" />&#160;,&#160; &#160;(8)
<img alt="Equation 9" src="/files/ftp_upload/58582/58582eq12.jpg" />,&#160; &#160;(9)
where Gcross(0) is the amplitude of the cross-correlation function and <img alt="Equation 14" src="/files/ftp_upload/58582/58582eq14.jpg" /> is the amplitude of the autocorrelation function in the i-th channel.
This definition of the relative cross-correlation, i.e. using max instead of mean in Equation 9, takes into account that the maximum number of complexes of two protein species present at different concentrations is limited by the species present in a lower number.
Cross-correlation number and brightness is based on a moment analysis of the fluorescence intensity for each pixel of an image stack acquired over time at a fixed position in the sample, typically consisting of ~100-200 frames, with two spectral channels (g = green channel, r = red channel). From the temporal mean <img alt="Image 1" src="/files/ftp_upload/58582/58582img1.jpg" />I<img alt="Image 2" src="/files/ftp_upload/58582/58582img2.jpg" />i and variance&#160; <img alt="Equation 16" src="/files/ftp_upload/58582/58582eq16.jpg" />, the molecular brightness&#160;&#949;i and number ni are calculated in each pixel and spectral channel (i = g, r)18:
<img alt="Equation 10" src="/files/ftp_upload/58582/58582eq20.jpg" />,&#160; &#160;(10)
<img alt="Equation 11" src="/files/ftp_upload/58582/58582eq21.jpg" />. (11)
It is important to note that the given equations apply to the ideal case of a true photon-counting detector. For analog detection systems, the following equations apply19,20:
<img alt="Equation 12" src="/files/ftp_upload/58582/58582eq22.jpg" />,&#160; &#160;(12)
<img alt="Equation 13" src="/files/ftp_upload/58582/58582eq23.jpg" />.&#160; &#160;(13)
Here, S is the conversion factor between detected photons and the recorded digital counts, <img alt="Equation 24" src="/files/ftp_upload/58582/58582eq24.jpg" /> is the readout noise and offset refers to the detector intensity offset. Generally, these quantities should be calibrated, for any detector type, based on measuring the detector variance as a function of intensity for steady illumination19, e.g., a reflective metal surface or dried dye solution. The offset can be determined by measuring the count rate for a sample without excitation light. By performing a linear regression of the detector-associated variance <img alt="Equation 25" src="/files/ftp_upload/58582/58582eq25.jpg" /> versus intensity (I) plot, S and <img alt="Equation 24" src="/files/ftp_upload/58582/58582eq24.jpg" /> can be determined19:
<img alt="Equation 14" src="/files/ftp_upload/58582/58582eq27.jpg" />.&#160; &#160;(14)
Finally, the cross-correlation brightness is calculated in each pixel and is defined in general as21
<img alt="Equation 15" src="/files/ftp_upload/58582/58582eq28.jpg" />,&#160; &#160;(15)
where <img alt="Equation 29" src="/files/ftp_upload/58582/58582eq29.jpg" /> is the cross-variance <img alt="Equation 30" src="/files/ftp_upload/58582/58582eq30.jpg" />.
In order to filter long-lived fluctuations, all ccN&#38;B calculations are performed following a boxcar filtering, independently for each pixel22. Briefly, ni, &#949;i (i = g, r) and Bcc are calculated in sliding segments of e.g., 8-15 frames. The values thus obtained can be then averaged to obtain the final pixel number and brightness values.
Stoichiometry analysis 
In order to estimate the stoichiometry of protein complexes at cell-cell contacts, the molecular brightness can be separately analyzed in each spectral channel for the sFCCS or ccN&#38;B data. In sFCCS, one brightness value is obtained per measurement in each channel. In ccN&#38;B, a brightness histogram of all pixels corresponding to the cell-cell contact is obtained and the average (or median) value can be used as representative brightness for the measurement. By performing the same analysis on a monomeric reference, all brightness values can be normalized to directly obtain the average oligomeric state of the detected protein complexes. At this point, it is important to correct for the presence of non-fluorescent FPs that may result in an underestimation of the oligomeric state. This is typically performed by measuring the brightness of a homo-dimeric reference protein23,24 using one-color sFCS or number and brightness (N&#38;B).

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	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">DMEM growth medium</td>
			<td style="width:95px;">PAN-Biotech</td>
			<td style="width:119px;">P04-01548</td>
			<td style="width:167px;"></td>
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		<tr height="21">
			<td height="21" style="height:21px;width:216px;">DPBS w/o: Ca2+ and Mg2+</td>
			<td style="width:95px;">PAN-Biotech</td>
			<td style="width:119px;">P04-36500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">DPBS w: Ca2+ and Mg2+</td>
			<td style="width:95px;">PAN-Biotech</td>
			<td style="width:119px;">P04-35500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Trypsin EDTA</td>
			<td style="width:95px;">PAN-Biotech</td>
			<td style="width:119px;">P10-023100</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">TurboFect Transfection Reagent</td>
			<td style="width:95px;">Thermo Fisher Scientific</td>
			<td style="width:119px;">R0531</td>
			<td></td>
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		<tr height="21">
			<td height="21" style="height:21px;width:216px;">HEK 293T cells</td>
			<td style="width:95px;">DSMZ</td>
			<td style="width:119px;">ACC 635</td>
			<td></td>
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			<td height="63" style="height:63px;width:216px;">Alexa Fluor 488 NHS Ester</td>
			<td style="width:95px;">Thermo Fisher Scientific</td>
			<td style="width:119px;">A20000</td>
			<td></td>
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			<td height="42" style="height:42px;width:216px;">Rhodamine B</td>
			<td style="width:95px;">Sigma-Alderich</td>
			<td style="width:119px;">83689-1G</td>
			<td></td>
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		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Plasmid DNA</td>
			<td style="width:95px;">Addgene</td>
			<td style="width:119px;">NA</td>
			<td>See reference 12 (Dunsing et. al., MBoC 2017),for a detailed description of all plasmids</td>
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		<tr height="21">
			<td height="21" style="height:21px;width:216px;">6-well plate</td>
			<td style="width:95px;">Starlab</td>
			<td style="width:119px;">CC7672-7506</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">35-mm glass bottom dishes</td>
			<td style="width:95px;">CellVis</td>
			<td style="width:119px;">D35-14-1.5-N</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Zeiss LSM780 confocal</td>
			<td style="width:95px;">Carl Zeiss</td>
			<td style="width:119px;">NA</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">MATLAB software package</td>
			<td style="width:95px;">MathWorks</td>
			<td style="width:119px;">&#160;2015b&#160;</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Neubauer cell counting chamber</td>
			<td style="width:95px;">Marienfeld</td>
			<td align="right" style="width:119px;">640110</td>
			<td></td>
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a fluorescence fluctuation spectroscopy assay of protein-protein interactions at cell-cell contacts

A variety of biological processes involves cell-cell interactions, typically mediated by proteins that interact at the interface between neighboring cells. Of interest, only few assays are capable of specifically probing such interactions directly in living cells. Here, we present an assay to measure the binding of proteins expressed at the surfaces of neighboring cells, at cell-cell contacts. This assay consists of two steps: mixing of cells expressing the proteins of interest fused to different fluorescent proteins, followed by fluorescence fluctuation spectroscopy measurements at cell-cell contacts using a confocal laser scanning microscope. We demonstrate the feasibility of this assay in a biologically relevant context by measuring the interactions of the amyloid precursor-like protein 1 (APLP1) across cell-cell junctions. We provide detailed protocols on the data acquisition using fluorescence-based techniques (scanning fluorescence cross-correlation spectroscopy, cross-correlation number and brightness analysis) and the required instrument calibrations. Further, we discuss critical steps in the data analysis and how to identify and correct external, spurious signal variations, such as those due to photobleaching or cell movement.
In general, the presented assay is applicable to any homo- or heterotypic protein-protein interaction at cell-cell contacts, between cells of the same or different types and can be implemented on a commercial confocal laser scanning microscope. An important requirement is the stability of the system, which needs to be sufficient to probe diffusive dynamics of the proteins of interest over several minutes.

A first test for the protein-protein interaction assay, i.e., mixing of cells expressing spectrally distinct fluorescent proteins followed by sFCCS/ccN&#38;B measurements (Figure 1), should be performed on proteins that are not expected to interact at the cell-cell contact (i.e., a negative control). Therefore, HEK 293T cells expressing myristoylated-palmitoylated-mEYFP (myr-palm-mEYFP) or -mCardinal were mixed and sFCCS was performed across...

Watch this Scientific Journal Video about A Fluorescence Fluctuation Spectroscopy Assay of Protein-Protein Interactions at Cell-Cell Contacts at JoVE.com

A Fluorescence Fluctuation Spectroscopy Assay of Protein-Protein Interactions at Cell-Cell Contacts

This protocol describes a fluorescence fluctuation spectroscopy-based approach to investigate interactions among proteins mediating cell-cell interactions, i.e. proteins localized in cell junctions, directly in living cells. We provide detailed guidelines on instrument calibration, data acquisition and analysis, including corrections to possible artefact sources.

A variety of biological processes involves cell-cell interactions, typically mediated by proteins that interact at the interface between neighboring ...

This method can help to understand key questions in the cell-to-cell interaction field such as which receptors mediate adhesion or recognition in cell-to-cell contacts and whether specific ligands trigger their interactions. The main advantage of this technique is that it allows one to investigate such interactions directly in living cells with no need for cell fixation or disruption. Though this method is used to investigate interactions between cultured cells, it can also be applied to other systems mono-membrane vesicles or even small model organisms.Generally individuals new to this method should check that their sample is stable enough to allow acquisition over a few minutes by carefully inspecting cell movement and slow signal variations. First, seed the appropriate number of cells in at least four wells of a six-well plate a day before transfection. Culture the cells at 37 degrees Celsius 5%carbon dioxide in DMEM medium supplemented with 10%FBS and 1%L-glutamine.To perform a basic experiment transfect plasmids for the protein of interest fused to a green or a yellow fluorescent protein and a red fluorescent protein in separate wells. After four hours remove the growth medium and wash each well gently with one milliliter of PBS supplemented with magnesium and calcium dropping PBS on the well edge to prevent detachment of the cells during washing. Then remove the PBS.Add approximately 50 microliters of EDTA solution drop wise to each well to facilitate detachment of the cells. After incubating at 37 degrees Celsius for two minutes, slowly shake the six-well plate laterally to detach the cells. Next, add 950 microliters of growth medium to each well and resuspend the cells by pipetting a few times up and down thereby detaching all cells from the well bottom.Ensure that cells are resuspended properly and detached from each other by visually checking for the absence of large cell aggregates after resuspension. Transfer the cell solution of one well to the corresponding well. Mix gently by pipetting a few times up and down.Then seed the mixed cells on a 35-millimeter glass bottom dish and culture the seeded cells at 37 degrees Celsius in 5%carbon dioxide for one day. In the laser scanning confocal microscope software set up the optical path. To avoid spectral crosstalk select two separate tracks to excite and detect mEGFP or mEYFP and mCherry or mCardinal sequentially and select Switch tracks every Line.For the detection use appropriate filters for both channels. Place the dish containing the mixed cells on the sample holder. After waiting 10 minutes to ensure temperature equilibration and to reduce focus drift, focus on the cells using the transmission light in the Locate menu.Search for a pair of red and green cells in contact with each other. Next, select a scan path perpendicular to cell-to-cell contact using the Crop button. Zoom to achieve a pixel size of 50 to 200 nanometers and select Line in Scan mode.Set frame size to 128 by one pixels. Set scan speed to the maximum allowed value. Then set cycles to 100, 000 to 500, 000.Following this, choose the appropriate laser powers. Set the detectors to Photon Counting mode. Press Start Experiment to start the acquisition.Export the raw data files to an RGB TIF image in raw data format. This file will contain a kymograph with the green and red channel data in the channel termed G and R of the image, respectively. Next, import the TIF file with the appropriate analysis software and proceed to perform the analysis.Align the lines by performing a segment-wise time average with blocks of 500 to 1000 lines. Determine the membrane position in each block. Then shift all blocks to the same lateral position.Sum up all aligned lines along the time axis and fit the average intensity profile using a Gaussian function. Define the pixels corresponding to the membrane as all pixels within plus or minus 2.5 sigma of the membrane position, and sum up the intensity of these pixels in each line obtaining a single fluorescent signal value for each time point. If photo bleaching is observed, apply a bleaching correction by fitting the membrane fluorescence time series with a double exponential function and applying the appropriate correction formula.Calculate the auto and cross-correlation functions according to the appropriate equations. To improve the reliability of the analysis and avoid artifacts perform the calculations for 10 to 20 equal segments of the total measurement. Inspect the fluorescence time series and correlation functions in each segment and remove clearly distorted segments.Finally, average all non-distorted segments. While analyzing your data, carefully inspect the intensity time series and correlation functions from each segment to avoid distortions, for instance, due to intracellular vesicles in the membrane periphery. An intensity image of HEK 293T cells expressing myristolyated-palmitoylated-mEYFP or mCardinal is shown here.A relative cross-correlation close to zero was observed while the autocorrelation functions show characteristic decay times of 10 to 20 milliseconds for the diffusion of myristolyated-palmitoylated-mEYFP and mCardinal in the plasma membrane. The cross-correlation functions of the sFCCS measurements of HEK 293T cells expressing membrane-anchored heterodimer myristolyated-palmitoylated-mCardinal-mEYFP had positive amplitudes and showed similar decay times as the autocorrelation function. sFCCS measurements on cell-to-cell contacts between APLP1-mEYFP and APLP1-mCardinal-expressing cells resulted in a positive relative cross-correlation of 0.45.The sFCCS correlation functions obtained from measurements across APLP1 clusters at cell-cell contacts showed strongly reduced dynamics as evident from large decay times in the oscillations at large lag times. Upon zinc ion addition, the relative cross-correlation increased to an average value of 0.8. Further the molecular brightness significantly increased from small oligomers to larger multimers consisting of 10 to 50 monomers on each cell.Transient instabilities may result in a cross-correlation function having negative values or a high false positive cross-correlation. The corresponding correlation functions typically deviate strongly from those of the majority of segments. As a complementary approach to sFCCS cross-correlation number and brightness can be used to detect protein-protein interactions.While attempting this procedure it's important to remember that mixing of transfected cells is a critical step. Gently mix the cells and optimize transfection efficiencies to increase the chance of finding red and green cells in contact. After its development this technique has been used by researchers in the field of immunology to explore the interactions of signaling molecules in immunological synapses.

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