We would like to acknowledge the advice and guidance from Dr. Vytas Bindokas at the University of Chicago. We thank the Integrated Light Microscopy Core Facility at the University of Chicago for supporting and maintaining the lattice light-sheet microscope. This work was supported by NIH New Innovator Award 1DP2AI144245 and NSF Career Award 1653782 (To J.H.). J.R. is supported by the NSF Graduate Research Fellowships Program.

5C.C7 TCR-transgenic RAG2 knockout mice in B10.A background were used in this study according to a protocol approved by the Institutional Animal Care and Use Committee of the University of Chicago.
1. Harvest and Activate T Cells
NOTE: This part of the protocol is based on previous protocols. See citations for further detail20,21.
<ol>
	<li>Euthanize a 10-12 week-old 5C.C7 transgenic mouse of either sex (~20-25 g) according to the approved IACUC protocol (i.e., CO2 chamber followed by cervical dislocation).</li>
	<li>Spray mouse carcass thoroughly with 70% ethanol to soak down the fur and bring into a BSL-2 safety cabinet.</li>
	<li>Turn mouse onto its right side and make a small incision in the body cavity with surgical scissors. Remove the spleen using surgical forceps. Cut away connective tissue as needed with surgical scissors.</li>
	<li>Place the spleen in a 70 &#181;m-pore mesh cell strainer and mash with the back of a 1 mL syringe plunger. Wash through the strainer thoroughly with complete RPMI (RPMI with 10% fetal bovine serum [FBS], 2 mM L-glutamine, 1% penicillin/streptomycin, 50 &#181;M 2-mercaptoethanol).</li>
	<li>Centrifuge the single cell suspension of splenocytes at 300 x g for 5 min. Discard the supernatant. 
	NOTE: The pellet at this point will be red.</li>
	<li>Resuspend the splenocytes in 5 mL RBC lysis buffer. Incubate for 5 min, then quench with 5 mL of complete RPMI.</li>
	<li>Centrifuge the single cell suspension of splenocytes at 300 x g for 5 min. Discard the supernatant. 
	NOTE: The pellet at this point should be white, not red.</li>
	<li>Resuspend the pellet in 5 mL of complete RPMI.</li>
	<li>Transfer to a T-25 flask and add 10 &#181;M moth cytochrome-C (MCC, sequence ANERADLIAYLKQATK). Put the cells in a cell culture incubator at 37 &#176;C, 5% CO2 overnight.</li>
	<li>On the next day, add recombinant mouse IL-2 to a final concentration of 100 U/mL.</li>
	<li>Observe for the following days, adding fresh media as the current media turns yellow. T cells will die if left in yellow media unattended for over 48 h. Cells are ready to use 6-10 days after harvest.</li>
</ol>
2. Prepare Cells
<ol>
	<li>Incubate 5 mm round coverslips with 0.1% poly-L-lysine for 10 min. Aspirate off and let dry naturally.</li>
	<li>Use a density gradient reagent (see the Table of Materials) to separate out dead cells and to obtain 1 x 106 T cells and 1 x 106 APCs (CH27 cells21,22 transduced with cytosolic mCherry) separately. 
	NOTE: Cells are counted using a hemocytometer.
	<ol>
		<li>Add 3 mL of density gradient reagent to a 15 mL conical tube and add cells dropwise to the edge of the tube carefully. Do not mix. Centrifuge at 930 x g for 10 min at 4 &#176;C; use acceleration/deceleration: SLOW/SLOW. Remove the thin middle layer of cells between the complete media and the density gradient reagent carefully, putting each cell type into separate conical tubes. 
		NOTE: It is necessary to prepare more cells than needed for imaging, as we find that 50% is lost on average during the process. The more cells used for the process, the easier it is to harvest them from the density gradient. We use 4-8 mL of both cell types to ensure excess cells. If desired, cells can be counted before this step to ensure volume needed. Any extra cells are put back into their respective flasks.</li>
		<li>Wash both tubes of T cells and CH27 cells three times with 5 mL complete RPMI (300 x g for 5 min). Discard the supernatant each time during the wash. Resuspend each tube in 1 mL complete RPMI and count cells by a hemocytometer.</li>
	</ol>
	</li>
	<li>Resuspend 1 x 106 APCs in 500 &#181;L complete RPMI and add 10 &#181;M MCC. Incubate for 3 h at 37 &#176;C, 5% CO2. Wash cells three times with 500 &#181;L complete RPMI (300 x g for 5 min). Discard the supernatants.</li>
	<li>Resuspend 1 x 106 T cells in 500 &#181;L complete RPMI. Add 2 &#181;g of anti-TCR&#946; Alexa488-labeled Fab (clone H57) to 500 &#181;L of cells. Incubate for 30 min at 37 &#176;C, 5% CO2. Wash cells three times with 500 &#181;L of complete RPMI (300 x g for 5 min). Discard supernatant after each wash. 
	NOTE: The divalent anti-TCR antibody was cut into monovalent Fab using a Fab preparation kit (see the Table of Materials) to avoid crosslinking the T cell receptors by the divalent antibody (this step is optional).</li>
	<li>Resuspend both cell types in 500 &#181;L of imaging media (phenol red-free Leibovitz&#39;s L-15 medium with 10% FBS, 1% penicillin/streptomycin, 2 mM L-glutamine).</li>
</ol>
3. Conducting LLSM Daily Alignment
NOTE: (Important) This alignment protocol is based on the LLSM instrument used (see the Table of Materials). Each LLSM may be different and require different alignment strategies, especially those that are home-built. Carry out the appropriate routine alignment and continue to section 4.
<ol>
	<li>Add 10 mL of water plus 30 &#181;L fluorescein (1 mg/mL stock) to the LLSM bath (~10 mL volume), press Image (Home) to move the objective to image position, and look at a single Bessel laser beam pattern. Align the laser beam using the guides and pre-set region of interest (ROI) to make the beam a thin pattern balanced in all directions.
	<ol>
		<li>The beam should also appear focused in the finder camera. Use two mirror tilt adjustors, top micrometer, focus, and emission objective collar to adjust. See Figure 2A,B for correctly aligned beam.</li>
	</ol>
	</li>
	<li>Wash the bath and objectives with at least 200 mL of water to completely remove fluorescein.</li>
	<li>Image standard fluorescent beads in the imaging media (prepared by adhering beads to a 5 mm coverslip with poly-L-lysine, see the Table of Materials; this can be pre-prepared and re-used) for physical point spread function (PSF) in imaging media. 
	NOTE: There can only be one bead in view for later processing, so try to find a bead that is by itself in the viewer or can easily be cropped to obtain a single bead.
	<ol>
		<li>Turn on dither by setting to 3 in the &#39;X Galvo range&#39; box. Press Live to view the current field. Move along the Z direction to find the cover slip and beads. Find the center of a bead by moving along Z, press Stop to pause the laser. Check 3D, press Center and then press Execute. This will collect the data.</li>
		<li>Manually adjust the tilt mirror, objective collar, and focus micrometer for highest gray values, then adjust as necessary to obtain proper patterns for objective scan, z galvo, z+objective (totPSF), and sample scan (samplePSF) capture modes. See Figure 2C-F for properly adjusted maximum intensity projections (MIPs). 
		NOTE: The various captures modes (objective scan, z galvo, z+objective, and sample scan) change how the light-sheet moves through the sample. All scan modes should be used for alignment.</li>
		<li>The sample scan shows how data will be collected during the experiment. Collect the sample PSF by pressing Execute in sample scan mode for deskewing and deconvolution (see section 5). Change lasers to three color mode (488, 560, 647) and press Execute again. 
		NOTE: Since the LLSM images at an angle (57.2&#176;), images captured in the &#34;sample scan&#34; mode are collected at this angle, and are therefore &#34;skewed&#34;. De-skewing is the process of correcting for this angle and &#34;re-aligning&#34; the image to a true z-stack. These data must be collected in imaging media and in all channels that will be imaged during the experiment. If this is not collected properly, the data will not be properly de-skewed. Similarly, make sure media has been warmed to 37 &#176;C (or desired experimental temperature).</li>
	</ol>
	</li>
</ol>
4. Setting Up Cells with LLSM
<ol>
	<li>Add 100,000 APCs (50 &#181;L) from step 2.5 to a 5 mm-diameter circular coverslip from step 2.1 and allow them to settle for 10 min.</li>
	<li>Grease the sample holder then add the coverslip cell-side-up to it. Add a drop of imaging media to the back of the coverslip to avoid bubbles before placing in the bath. Screw the sample holder onto the piezo, and press Image (Home).</li>
	<li>Find an APC to image to ensure that the LLSM and imaging software (see Table of Materials) are functioning properly. 
	NOTE: We image at 0.4 &#181;m step size with 60 z-steps and 10 ms exposure for two colors with dither set to 3, which results in 1.54 s per frame of 3D image with ~200 nm XY and 400 nm Z resolution. These settings may need to be adjusted based on cell size, desired z-resolution, and strength of signal from the fluorescent labeling technique used. Laser power usage will also vary based on fluorescent labeling technique used.
	<ol>
		<li>Press Live to view the current image. Move along Z to find the cover slip and cells.</li>
		<li>Find the center of an APC by moving in the Z direction, then press Stop to pause the laser. Check 3D and input the desired settings (see step 4.3.1), press Center and then press Execute. This will collect the data.</li>
	</ol>
	</li>
	<li>Lower the stage to load position and add 50 &#181;L of T cells in imaging media (100,000 cells, from step 2.5) dropwise directly over the coverslip. It is best to let a drop form on the end of the pipette tip and then touch the tip to the bath liquid. Raise stage back by clicking &#34;Image (Return)&#34;.</li>
	<li>Begin imaging. Be sure to set the desired stack size and time lapse length. For example, image 60 z-stacks at a 0.4 &#181;m step size and input 500 time frames. (Typically) stop recording before 500 frames are reached to avoid photobleaching. Use Live mode to search for cell pairs, and when ready and desired settings have been entered, press Execute to collect data. See Movie 1 and Figure 1 for an example.</li>
</ol>
5. Track Surface Dynamics
<ol>
	<li>Export the data from the imaging software (see the Table of Materials). This will create z-stack TIF files for every time point in each color.</li>
	<li>First deskew and deconvolve the data. 
	NOTE: We use the LLSpy pipeline under license by HHMI&#39;s Janelia Research Campus18, but deskewing and deconvolution are also available within multiple imaging softwares (see Table of Materials).</li>
	<li>Debleach the data. 
	NOTE: We use Fiji&#39;s debleach feature with histogram matching (Fiji Pathway: Image | Adjust | Bleach Correction | Histogram Matching | OK).</li>
	<li>Import into the tracking software (see the Table of Materials). Track clusters according to software specifications. See Movie 2 for an example. 
	NOTE: Tracking results will depend upon the tracking software used, algorithm chosen, desired output parameters selected, etc. For example, in the tracking software we utilized (see the Table of Materials), we chose to allow the software to track irregular shapes, rather than assigning each feature a single spot, since TCR clusters are not organized into perfect spheres. In addition, we chose to collect 35 parameters, including speed, direction, volume, intensity, area, location, and track duration information. However, different methods or parameters will be beneficial to answer different questions.
	<ol>
		<li>If tracking is not desired, use the ClearVolume plugin for Fiji for visualizing and creating movies from hyperstack data.</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

The presented protocol was optimized for the usage of CD4+ T cells isolated from 5C.C7 transgenic mice on the LLSM instrument used, and therefore other cell systems and LLSMs may need to be optimized differently. However, this protocol shows the power of 4D imaging, as it can be used to quantify the dynamics of a surface receptor on an entire cell with the least distortion in physiological conditions. Therefore, there are many possible future applications of this technique.
A critical step is allowing the cells to settle at an appropriate concentration. If too many APCs settle on the coverslip and become too dense, it is hard to find a T cell that is interacting with only a single APC. When a T cell has multiple synapses, tracking and interpretation of data can become very complicated. Similarly, if too few APCs are present, finding a T cell forming a synapse is also difficult. In our hands, allowing 50,000 cells to settle for 10 min achieves an optimal density. However, this problem can be avoided if using a system with adherent cells. Cells can be grown in the incubator with the coverslips to a desired confluency.
Similarly, the number of T cells dropped into the system is dependent upon the size of the bath and the distance they can disperse. In the LLSM system used here, there is a 12 mL bath and a 2.5 mL bath, as opposed to the previous version of the system which only had a 10 mL bath available. We use the 12 mL bath for the original fluorescein imaging then switch to the 2.5 mL bath for imaging the cells. This allows for less thorough washing of the bath following the beam visualization step, and also lowers the number of T cells required for each imaging session. In turn, this would allow users to utilize fewer cells.
Finding cells at the correct point of interaction is also a challenge. In our hands, T cells take about 2 min to settle down to the APCs on the coverslip, so it is important to begin searching the coverslip for dynamic T cells close to APCs. A major improvement of this has been the recent addition of the LED light in the finder camera. If using a home-built system, we highly recommend including this feature in the design.
Finally, fluorescent labeling strategies are another important consideration. Each fluorescent protein or dye has a different quantum yield and rate of photobleaching. Fluorescent dyes are typically brighter, but if the cells have been stably transduced with a fluorescent protein labeled molecule, the label is replenished as the cell continues to produce the molecule. Therefore, labeling strategy is an important factor to consider when designing experiments.
We would like to conclude with a discussion on future directions for the technology. LLSM is also capable of structured illumination microscopy (SIM), which results in 150 nm XY resolution and 280 nm Z resolution, and is at least 10 times faster than widefield SIM12. Therefore, while LLSM provides unprecedented speed of 4D imaging, it cannot achieve the spatial resolution of current super-resolution techniques4,5,6. However, this resolution could be improved if a STED LLSM could be created. Light sheet STED and stimulated emission depletion with selective plane illumination microscopy (STED-SPIM) have been utilized, but lack the temporal resolution of LLSM21,22,23,24. If STED-SPIM were adapted to incorporate a lattice, we could potentially obtain 50 nm axial resolution with far less photobleaching, and image faster than currently available techniques. Nevertheless, with current available technologies, LLSM gives us the fastest temporal resolution with high axial resolution.

The precise dynamics of molecules trafficking and diffusing on the three-dimensional cell surface in real time have been an enigma to solve. Microscopy has always been a balance of speed, sensitivity, and resolution; if any one or two are maximized, the third is minimized. Therefore, due to the small size and immense speed with which surface receptors move, tracking their dynamics has remained a major technological challenge to the field of cell biology. For example, many studies have been conducted using total internal reflection fluorescence (TIRF) microscopy1,2,3, which has high temporal resolution, but can only image a very thin slice of the T-cell membrane (~100 nm), and therefore misses events happening farther away in the cell. These TIRF images also only showing a two-dimensional section of the cell. By contrast, super-resolution techniques, such as stochastic optical reconstruction microscopy (STORM)4, photoactivated localization microscopy (PALM)5, and stimulated emission depletion microscopy (STED)6, can overcome the Abbe diffraction limit of light. These techniques have high spatial resolution (~20 nm resolution)4,5,6,7, but they often take many minutes to acquire a full two-dimensional (2D) or three-dimensional (3D) image, and therefore the temporal resolution is lost. In addition, techniques such as STORM and PALM that rely on blinking signals may have inaccuracies in counting8,9. Electron microscopy has by far the highest resolution (up to 50 pm resolution)10; it can even be conducted three-dimensionally with focused ion beam scanning electron microscopy (FIB-SEM), resulting in up to 3 nm XY and 500 nm Z resolution11. However, any form of electron microscopy requires harsh sample preparation and can only be conducted with fixed cells or tissues, eliminating the possibility of imaging live samples over time.
Techniques to obtain the high spatiotemporal resolution required to identify the dynamics of surface and intracellular molecules in live cells in their true physiological 3D nature is only being recently developed. One of these techniques is Lattice Light-Sheet Microscopy (LLSM)12, which utilizes a structured light sheet to drastically lower photobleaching. Developed in 2014 by Nobel Laureate Eric Betzig, the high axial resolution, low photobleaching and background noise, and ability to simultaneously image hundreds of planes per field of view make LLS microscopes superior to widefield, TIRF and confocal microscopes12,13,14,15,16,17,18,19. This four-dimensional (x, y, z and time) imaging technique, while still diffraction limited (~200 nm XYZ resolution), has incredible temporal resolution (we have achieved a frame rate of about 100 fps, resulting in a 3D reconstructed cell image with 0.85 seconds per frame) for 3D spatial acquisition.
LLSM can be generally used to track real-time dynamics of any molecules within any cell at the single-molecule and single-cell level, particularly those in highly motile cells such as immune cells. For example, we show here how to use LLSM to visualize T-cell receptor (TCR) dynamics. T cells are the effector cells of the adaptive immune system. TCRs are responsible for recognizing peptide-MHC (pMHC) ligands displayed on the surface of antigen-presenting cells (APC), which determines the selection, development, differentiation, fate, and function of a T cell. This recognition occurs at the interface between T cells and APCs, resulting in localized receptor clustering to form what is called the immunological synapse. While it is known that TCRs at the immunological synapse are imperative for T-cell effector function, still unknown are the underlying mechanisms of real-time TCR trafficking to the synapse. LLSM has allowed us to visualize in real time the dynamics of TCRs before and after trafficking to the synapse with the resultant pMHC-TCR interaction (Figure 1). LLSM can therefore be used to solve current questions of the formative dynamics of TCRs and provide insights to understand how a cell distinguishes between self and foreign antigens.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1 mL Syringe</td>
			<td>BD</td>
			<td>309659</td>
			<td>For T cell harvest</td>
		</tr>
		<tr>
			<td>2-Mercaptoethanol</td>
			<td>Sigma-Aldrich</td>
			<td>M3148-25ML</td>
			<td>For T cell culture</td>
		</tr>
		<tr>
			<td>5 mm round coverslips</td>
			<td>World Precision Instruments</td>
			<td>502040</td>
			<td>For Imaging</td>
		</tr>
		<tr>
			<td>70um Sterile Cell Strainer</td>
			<td>Corning</td>
			<td>7201431</td>
			<td>For T cell harvest</td>
		</tr>
		<tr>
			<td>Alexa Fluor 488 anti-mouse TCR &#946; chain Antibody</td>
			<td>BioLegend</td>
			<td>109215</td>
			<td>For Imaging</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum (FBS)</td>
			<td>X&#38;Y Cell Culture</td>
			<td>FBS-500</td>
			<td>For T cell culture</td>
		</tr>
		<tr>
			<td>Ficoll</td>
			<td>GE Healthcare</td>
			<td>17-1440-02</td>
			<td>Denisty gradient reagent for T cell harvest</td>
		</tr>
		<tr>
			<td>Fluorescein sodium salt</td>
			<td>Sigma-Aldrich</td>
			<td>F6377</td>
			<td>For microscope alignment</td>
		</tr>
		<tr>
			<td>FluoSpheres Carboxylate-Modified Microspheres</td>
			<td>Thermo Fisher Scientific</td>
			<td>F8810</td>
			<td>For microscope alignment</td>
		</tr>
		<tr>
			<td>Imaris</td>
			<td>Bitplane</td>
			<td>N/A</td>
			<td>Tracking Software; Other options for tracking software include Amira or Trackmate (Fiji).</td>
		</tr>
		<tr>
			<td>Lattice Light-Sheet Microscope</td>
			<td>3i</td>
			<td>N/A</td>
			<td>Microscope Used</td>
		</tr>
		<tr>
			<td>Leibovitz&#39;s L-15 Medium, no phenol red</td>
			<td>Thermo Fisher Scientific</td>
			<td>21083027</td>
			<td>For Imaging</td>
		</tr>
		<tr>
			<td>L-Glutamine</td>
			<td>Thermo Fisher Scientific</td>
			<td>25030-081</td>
			<td>For T cell culture</td>
		</tr>
		<tr>
			<td>LLSpy</td>
			<td>Janelia Research Campus</td>
			<td>N/A</td>
			<td>LLSpy was used under license from Howard Hughes Medical Institute, Janelia Research Campus. Contact innovation@janelia.hhmi.org for access. Other deconvolution and deksewing methods are available in image processing softwares such as Fiji, Slidebook, Amira, and others. <a href="https://llspy.readthedocs.io/en/latest/" target="_blank">https://llspy.readthedocs.io/en/latest/</a></td>
		</tr>
		<tr>
			<td>Moth Cytochrome C (MCC), sequence ANERADLIAYLKQATK</td>
			<td>Elimbio</td>
			<td>Custom Synthesis</td>
			<td>For T cell harvest</td>
		</tr>
		<tr>
			<td>Penacillin/Streptamycin</td>
			<td>Life Technologies</td>
			<td>15140122_3683884612</td>
			<td>For T cell culture</td>
		</tr>
		<tr>
			<td>Poly-L-Lysine</td>
			<td>Phenix Research Products</td>
			<td>P8920-100ML</td>
			<td>For Imaging</td>
		</tr>
		<tr>
			<td>RBC Lysis Buffer</td>
			<td>eBioscience</td>
			<td>00-4300-54</td>
			<td>For T cell harvest</td>
		</tr>
		<tr>
			<td>Recombinant mouse IL-2</td>
			<td>Sigma-Aldrich</td>
			<td>I0523</td>
			<td>For T cell culture</td>
		</tr>
		<tr>
			<td>RPMI 1640 Medium</td>
			<td>Corning</td>
			<td>MT10040CV</td>
			<td>For T cell culture</td>
		</tr>
		<tr>
			<td>Slidebook</td>
			<td>3i</td>
			<td>N/A</td>
			<td>LLSM imaging software</td>
		</tr>
		<tr>
			<td>Surgical Dissection Tools</td>
			<td>Nova-Tech International</td>
			<td>DSET10</td>
			<td>For T cell harvest</td>
		</tr>
		<tr>
			<td>T-25 Flasks</td>
			<td>Eppendorf</td>
			<td>2231710126</td>
			<td>For T cell culture</td>
		</tr>
		<tr>
			<td>Thermo Scientific Pierce Fab Micro Preparation Kits</td>
			<td>Thermo Fisher Scientific</td>
			<td>44685</td>
			<td>For preparing Fab</td>
		</tr>
	</tbody>
</table>

visualizing surface t-cell receptor dynamics four-dimensionally using lattice light-sheet microscopy

The signaling and function of a cell are dictated by the dynamic structures and interactions of its surface receptors. To truly understand the structure-function relationship of these receptors in situ, we need to visualize and track them on the live cell surface with enough spatiotemporal resolution. Here we show how to use recently developed Lattice Light-Sheet Microscopy (LLSM) to image T-cell receptors (TCRs) four-dimensionally (4D, space and time) at the live cell membrane. T cells are one of the main effector cells of the adaptive immune system, and here we used T cells as an example to show that the signaling and function of these cells are driven by the dynamics and interactions of the TCRs. LLSM allows for 4D imaging with unprecedented spatiotemporal resolution. This microscopy technique therefore can be generally applied to a wide array of surface or intracellular molecules of different cells in biology.

Here, we describe the isolation, preparation, and imaging of primary mouse 5C.C7 T cells using a lattice light-sheet microscope. During section 3, it is imperative to align the microscope correctly, and to collect PSF daily with which to deconvolve the data after collection. In Figure 2, we show the correct alignment images that will be seen when aligning the microscope. Figure 2A and Figure 2B show the correct beam path and beam alignment, respectively, when imaged in fluorescein. The objective scan should show a large X shape in the XZ and YZ projections that is as symmetrical as possible; this should also be adjusted to be as small of an X as possible (Figure 2C). This is mainly achieved by adjusting the emission objective collar. The z galvo scan should show an oval in XZ and XY with a single dot on either side (above and below for XZ and to the left and right for YZ) (Figure 2D). This is mainly achieved by adjusting the galvo mirror tilt, either manually or with the motorized adjustment in the software. Finally, both the z+objective scan and the sample scan should show dots that look as round as possible (Figure 2E and Figure 2F, respectively). These may have a small X, but this should be as dimished as possible. These should be well aligned if the objective scan and z galvo were set well, but if adjustments are necessary, they will be mostly conducted with the galvo mirror. It is important to note that during this alignment, any time the collar and galvo are adjusted, the focus (micrometer above the emission objective) will need to be adjusted as well.
Using this protocol, we can see the four-dimensional dynamics of the TCRs on a T-cell surface (Figure 1, Movie 1). The main advantage of this microscope lies in the ability to track the visualized surface units of the TCRs, and to obtain quantified data from their size, motion, signal intensity, etc. (see Table of Materials). Movie 2 shows an example of the tracks obtained.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59914/59914fig1.jpg" /> 
Figure 1: 4-dimensional imaging of T cell-APC Synapse. (A) A representative example 3D time-lapse LLSM images showing a T cell interacting with an APC. Shown are the TCR (green, labeled by anti-TCR-AF488) dynamics in recognizing antigens presented on the surface of an APC (red, cytosolic mCherry). Scale bar = 5 &#956;m. Also see Movie 1. (B) Orthogonal XY slice of (A). Inset is a reference frame of a whole cell. Scale bar = 5 &#956;m. (C) Orthogonal YZ slice of (A). Inset is a reference frame of a whole cell. Scale bar = 5 &#956;m. (D) Dual orthogonal slice of (A). Inset is reference frame of whole cell. Scale bar = 5 &#956;m. Also see Movie 3. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59914/59914fig1alarge.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/59914/59914fig2a.jpg" /> 
Figure 2: LLSM alignment. (A) Desired beam pattern for LLSM imaging experiment. (B) Screenshot of the beam alignment process; on the left is the focus window showing the narrowed, focused beam; at the top right is a graph showing that the beam is centered within the window; at the bottom right is the finder camera, which should also be a thin, focused beam. (C) Maximum intensity projections (MIPs) of a bead by objective scan. (D) Maximum intensity projections (MIPs) of a bead by z-galvo scan. (E) Maximum intensity projections (MIPs) of a bead by z+objective scan. (F) Maximum intensity projections (MIPs) of a bead by sample scan. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59914/59914fig2alarge.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Movie 1" src="/files/ftp_upload/59914/59914movie1a.jpg" /> 
Movie 1: T cell synapse formation. Two-color volume rendering of the interaction of a T cell labeled with &#945;TCR-AF488 (green) with a target APC expressing cytosolic mCherry (red) over 70 time points at 1.54 s interval. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59914/JoVE_Movie_1.avi" target="_blank">Please click here to view this video. (Right-click to download.)</a>
<img alt="Movie 2" src="/files/ftp_upload/59914/59914movie2a.jpg" /> 
Movie 2: Tracking TCR dynamic motion. Compare with Movie 1. Clusters corresponding to visible TCR structures were tracked in 3D over time with imaging software. Dragon tails showing cluster positions over the previous four frames are color-coded by displacement length. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59914/JoVE_Movie_2.avi" target="_blank">Please click here to view this video. (Right-click to download.)</a>
<img alt="Movie 3" src="/files/ftp_upload/59914/59914movie3a.jpg" /> 
Movie 3: Orthogonal slices of T cell synapse. Compare with Movie 1 and Figure 1B-D. Dual orthogonal slice of Movie 1, showing that &#945;TCR&#946;-AF488 Fab is indeed labeling the cell surface TCRs. Inset is a reference frame of whole cell. Scale bar = 5 &#956;m. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59914/JoVE_Movie_3.avi" target="_blank">Please click here to view this video. (Right-click to download.)</a>

Watch this Scientific Journal Video about Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy at JoVE.com

Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy

The goal of this protocol is to show how to use Lattice Light-Sheet Microscopy to four-dimensionally visualize surface receptor dynamics in live cells. Here T cell receptors on CD4+ primary T cells are shown.

The signaling and function of a cell are dictated by the dynamic structures and interactions of its surface receptors. To truly understand the ...

visualizing-surface-t-cell-receptor-dynamics-four-dimensionally-using

Nanyang Technological University

Research

JoVE Journal

Biochemistry

7.9K Views.  The University of Chicago. The goal of this protocol is to show how to use Lattice Light-Sheet Microscopy to four-dimensionally visualize surface receptor dynamics in live cells. Here T cell receptors on CD4+ primary T cells are shown.

Video: Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy

Extracellular Protein Microarray Technology for High Throughput Detection of Low Affinity Receptor-Ligand Interactions

Secreted factors, membrane-tethered receptors, and their interacting partners are main regulators of cellular communication and initiation of signaling cascades during homeostasis and disease, and as such represent prime therapeutic targets. Despite their relevance, these interaction networks remain significantly underrepresented in current databases; therefore, most extracellular proteins have no documented binding partner. This discrepancy is primarily due to the challenges associated with the study of the extracellular proteins, including expression of functional proteins, and the weak, low affinity, protein interactions often established between cell surface receptors. The purpose of this method is to describe the printing of a library of extracellular proteins in a microarray format for screening of protein-protein interactions. To enable detection of weak interactions, a method based on multimerization of the query protein under study is described. Coupled to this microbead-based multimerization approach for increased multivalency, the protein microarray allows robust detection of transient protein-protein interactions in high throughput. This method offers a rapid and low sample consuming-approach for identification of new interactions applicable to any extracellular protein. Protein microarray printing and screening protocol are described. This technology will be useful for investigators seeking a robust method for discovery of protein interactions in the extracellular space.

Here, we present a protocol to screen extracellular protein microarrays for identification of novel receptor-ligand interactions in high throughput. We also describe a method to enhance detection of transient protein-protein interactions by using protein-microbead complexes.

Secreted factors, membrane-tethered receptors, and their interacting partners are main regulators of cellular communication and initiation of signaling ...

Probing The Structure And Dynamics Of Nucleosomes Using Atomic Force Microscopy Imaging

Chromatin, which is a long chain of nucleosome subunits, is a dynamic system that allows for such critical processes as DNA replication and transcription to take place in eukaryotic cells. The dynamics of nucleosomes provides access to the DNA by replication and transcription machineries, and critically contributes to the molecular mechanisms underlying chromatin functions. Single-molecule studies such as atomic force microscopy (AFM) imaging have contributed significantly to our current understanding of the role of nucleosome structure and dynamics. The current protocol describes the steps enabling high-resolution AFM imaging techniques to study the structural and dynamic properties of nucleosomes. The protocol is illustrated by AFM data obtained for the centromere nucleosomes in which H3 histone is replaced with its counterpart centromere protein A (CENP-A). The protocol starts with the assembly of mono-nucleosomes using a continuous dilution method. The preparation of the mica substrate functionalized with aminopropyl silatrane (APS-mica) that is used for the nucleosome imaging is critical for the AFM visualization of nucleosomes described and the procedure to prepare the substrate is provided. Nucleosomes deposited on the APS-mica surface are first imaged using static AFM, which captures a snapshot of the nucleosome population. From analyses of these images, such parameters as the size of DNA wrapped around the nucleosomes can be measured and this process is also detailed. The time-lapse AFM imaging procedure in the liquid is described for the high-speed time-lapse AFM that can capture several frames of nucleosome dynamics per second. Finally, the analysis of nucleosome dynamics enabling the quantitative characterization of the dynamic processes is described and illustrated.

Here, we present a protocol to characterize nucleosome particles at the single-molecule level using static and time-lapse atomic force microscopy (AFM) imaging techniques. The surface functionalization method described allows for the capture of the structure and dynamics of nucleosomes in high-resolution at the nanoscale.

Chromatin, which is a long chain of nucleosome subunits, is a dynamic system that allows for such critical processes as DNA replication and transcription ...

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Dynamic protein-protein interactions control cellular behavior, from motility to DNA replication to signal transduction. However, monitoring dynamic interactions among multiple proteins in a protein interaction network is technically difficult. Here, we present a protocol for Quantitative Multiplex Immunoprecipitation (QMI), which allows quantitative assessment of fold changes in protein interactions based on relative fluorescence measurements of Proteins in Shared Complexes detected by Exposed Surface epitopes (PiSCES). In QMI, protein complexes from cell lysates are immunoprecipitated onto microspheres, and then probed with a labeled antibody for a different protein in order to quantify the abundance of PiSCES. Immunoprecipitation antibodies are conjugated to different MagBead spectral regions, which allows a flow cytometer to differentiate multiple parallel immunoprecipitations and simultaneously quantify the amount of probe antibody associated with each. QMI does not require genetic tagging and can be performed using minimal biomaterial compared to other immunoprecipitation methods. QMI can be adapted for any defined group of interacting proteins, and has thus far been used to characterize signaling networks in T cells and neuronal glutamate synapses. Results have led to new hypothesis generation with potential diagnostic and therapeutic applications. This protocol includes instructions to perform QMI, from the initial antibody panel selection through to running assays and analyzing data. The initial assembly of a QMI assay involves screening antibodies to generate a panel, and empirically determining an appropriate lysis buffer. The subsequent reagent preparation includes covalently coupling immunoprecipitation antibodies to MagBeads, and biotinylating probe antibodies so they can be labeled by a streptavidin-conjugated fluorophore. To run the assay, lysate is mixed with MagBeads overnight, and then beads are divided and incubated with different probe antibodies, and then a fluorophore label, and read by flow cytometry. Two statistical tests are performed to identify PiSCES that differ significantly between experimental conditions, and results are visualized using heatmaps or node-edge diagrams.

Quantitative Multiplex Immunoprecipitation (QMI) uses flow cytometry for sensitive detection of differences in the abundance of targeted protein-protein interactions between two samples. QMI can be performed using a small amount of biomaterial, does not require genetically engineered tags, and can be adapted for any previously defined protein interaction network.

Dynamic protein-protein interactions control cellular behavior, from motility to DNA replication to signal transduction. However, monitoring dynamic ...

Production of Dynein and Kinesin Motor Ensembles on DNA Origami Nanostructures for Single Molecule Observation

Cytoskeletal motors are responsible for a wide variety of functions in eukaryotic cells, including mitosis, cargo transport, cellular motility, and others. Many of these functions require motors to operate in ensembles. Despite a wealth of knowledge about the mechanisms of individual cytoskeletal motors, comparatively less is known about the mechanisms and emergent behaviors of motor ensembles, examples of which include changes to ensemble processivity and velocity with changing motor number, location, and configuration. Structural DNA nanotechnology, and the specific technique of DNA origami, enables the molecular construction of well-defined architectures of motor ensembles. The shape of cargo structures as well as the type, number and placement of motors on the structure can all be controlled. Here, we provide detailed protocols for producing these ensembles and observing them using total internal reflection fluorescence microscopy. Although these techniques have been specifically applied for cytoskeletal motors, the methods are generalizable to other proteins that assemble in complexes to accomplish their tasks. Overall, the DNA origami method for creating well-defined ensembles of motor proteins provides a powerful tool for dissecting the mechanisms that lead to emergent motile behavior.

The goal of this protocol is to form ensembles of molecular motors on DNA origami nanostructures and observe the ensemble motility using total internal reflection fluorescence microscopy.

Cytoskeletal motors are responsible for a wide variety of functions in eukaryotic cells, including mitosis, cargo transport, cellular motility, and ...

Screening for Phytoestrogens using a Cell-based Estrogen Receptor  &#946; Reporter Assay

Plants are a source of food for many animals, and&#160;they can produce thousands of chemicals. Some of these compounds affect physiological processes in the vertebrates that consume them, such as endocrine function. Phytoestrogens, the most well studied endocrine-active phytochemicals, directly interact with the hypothalamo-pituitary gonadal axis of the vertebrate endocrine system. Here we present the novel use of a cell-based assay to screen plant extracts for the presence of compounds that have estrogenic biological activity. This assay uses mammalian cells engineered to highly express estrogen receptor beta (ER&#946;) and that have been transfected with a luciferase gene. Exposure to compounds with estrogenic activity results in the cells producing light. This assay is a reliable and simple way to test for biological estrogenic activity. It has several improvements over transient transfection assays, most notably, ease of use, the stability of the cells, and the sensitivity of the assay.

We have optimized a commercially available estrogen receptor &#946; reporter assay for screening human and nonhuman primate foods for estrogenic activity. We validated this assay by showing that the known estrogenic human food soy registers high, while other foods show no activity.

Plants are a source of food for many animals, and&#160;they can produce thousands of chemicals. Some of these compounds affect physiological processes in ...

Monitoring Protein-RNA Interaction Dynamics In Vivo at High Temporal Resolution Using &#967;CRAC

The interaction between RNA-binding proteins (RBPs) and their RNA substrates exhibits fluidity and complexity. Within its lifespan, a single RNA can be bound by many different RBPs that will regulate its production, stability, activity, and degradation. As such, much has been done to understand the dynamics that exist between these two types of molecules. A particularly important breakthrough came with the emergence of &#8216;cross-linking and immunoprecipitation&#8217; (CLIP). This technique allowed stringent investigation into which RNAs are bound by a particular RBP. In short, the protein of interest is UV cross-linked to its RNA substrates in vivo, purified under highly stringent conditions, and then the RNAs covalently cross-linked to the protein are converted into cDNA libraries and sequenced. Since its conception, many derivative techniques have been developed in order to make CLIP amenable to particular fields of study. However, cross-linking using ultraviolet light is notoriously inefficient. This results in extended exposure times that make the temporal study of RBP-RNA interactions impossible. To overcome this issue, we recently designed and built much-improved UV irradiation and cell harvesting devices. Using these new tools, we developed a protocol for time-resolved analyses of RBP-RNA interactions in living cells at high temporal resolution: Kinetic CRoss-linking and Analysis of cDNAs (&#967;CRAC). We recently used this technique to study the role of yeast RBPs in nutrient stress adaptation. This manuscript provides a detailed overview of the &#967;CRAC method and presents recent results obtained with the Nrd1 RBP.

Kinetic cross-linking and analysis of cDNA is a method that allows investigation of the dynamics of protein-RNA interactions in living cells at high temporal resolution. Here the protocol is described in detail, including the growth of yeast cells, UV cross-linking, harvesting, protein purification, and next generation sequencing library preparation steps.

The interaction between RNA-binding proteins (RBPs) and their RNA substrates exhibits fluidity and complexity. Within its lifespan, a single RNA can be ...

Visualizing Diffusional Dynamics of Gold Nanorods on Cell Membrane using Single Nanoparticle Darkfield Microscopy

Analyzing the diffusional dynamics of nanoparticles on cell membrane plays a significant role in better understanding the cellular uptake process and provides a theoretical basis for the rational design of nano-medicine delivery. Single particle tracking (SPT) analysis could probe the position and orientation of individual nanoparticles on cell membrane, and reveal their translational and rotational states. Here, we show how to use traditional dark-field microscopy to monitor the dynamics of gold nanorods (AuNRs) on live cell membrane. We also show how to extract the location and orientation of AuNRs using ImageJ and MATLAB, and how to characterize the diffusive states of AuNRs. Statistical analysis of hundreds of particles show that single AuNRs perform Brownian motion on the surface of U87 MG cell membrane. However, individual long trajectory analysis shows that AuNRs have two distinctly different types of motion states on the membrane, namely long-range transport and limited-area confinement. Our SPT methods can be potentially used to study the surface or intracellular particle diffusion in different biological cells and can become a powerful tool for investigations of complex cellular mechanisms.

Here, we show the use of traditional dark-field microscopy to monitor the dynamics of gold nanorods (AuNRs) on cell membrane. The location and orientation of single AuNRs are detected using ImageJ and MATLAB, and the diffusive states of AuNRs are characterized by single particle tracking analysis.

Analyzing the diffusional dynamics of nanoparticles on cell membrane plays a significant role in better understanding the cellular uptake process and ...

Quantification of Subcellular Glycogen Distribution in Skeletal Muscle Fibers using Transmission Electron Microscopy

With the use of transmission electron microscopy, high-resolution images of fixed samples containing individual muscle fibers can be obtained. This enables quantifications of ultrastructural aspects such as volume fractions, surface area to volume ratios, morphometry, and physical contact sites of different subcellular structures. In the 1970s, a protocol for enhanced staining of glycogen in cells was developed and paved the way for a string of studies on the subcellular localization of glycogen and glycogen particle size using transmission electron microscopy. While most analyses interpret glycogen as if it is homogeneously distributed within the muscle fibers, providing only a single value (e.g., an average concentration), transmission electron microscopy has revealed that glycogen is stored as discrete glycogen particles located in distinct subcellular compartments. Here, the step-by-step protocol from tissue collection to the quantitative determination of the volume fraction and particle diameter of glycogen in the distinct subcellular compartments of individual skeletal muscle fibers is described. Considerations on how to 1) collect and stain tissue specimens, 2) perform image analyses and data handling, 3) evaluate the precision of estimates, 4) discriminate between muscle fiber types, and 5) methodological pitfalls and limitations are included.

A modified post-fixation procedure increases the contrast of glycogen particles in tissue. This paper provides a step-by-step protocol describing how to handle the tissue, conduct the imaging, and use stereological methods to obtain unbiased and quantitative data on fiber type-specific subcellular glycogen distribution in skeletal muscle.

With the use of transmission electron microscopy, high-resolution images of fixed samples containing individual muscle fibers can be obtained. This ...

Simultaneous Visualization of the Dynamics of Crosslinked and Single Microtubules In Vitro by TIRF Microscopy

Microtubules are polymers of &#945;&#946;-tubulin heterodimers that organize into distinct structures in cells. Microtubule-based architectures and networks often contain subsets of microtubule arrays that differ in their dynamic properties. For example, in dividing cells, stable bundles of crosslinked microtubules coexist in close proximity to dynamic non-crosslinked microtubules. TIRF-microscopy-based in vitro reconstitution studies enable the simultaneous visualization of the dynamics of these different microtubule arrays. In this assay, an imaging chamber is assembled with surface-immobilized microtubules, which are either present as single filaments or organized into crosslinked&#160;bundles. Introduction of tubulin, nucleotides, and protein regulators allows direct visualization of associated proteins and of dynamic properties of single and crosslinked microtubules. Furthermore, changes that occur as dynamic single microtubules organize into bundles can be monitored in real-time. The method described here allows for a systematic evaluation of the activity and localization of individual proteins, as well as synergistic effects of protein regulators on two different microtubule subsets under identical experimental conditions, thereby providing mechanistic insights that are inaccessible by other methods.

Simultaneous Visualization of the Dynamics of Crosslinked and Single Microtubules In Vitro by TIRF Microscopy

Here, a TIRF microscopy-based in vitro reconstitution assay is presented to simultaneously quantify and compare the dynamics of two microtubule populations. A method is described to simultaneously view the collective activity of multiple microtubule-associated proteins on crosslinked microtubule bundles and single microtubules.

Microtubules are polymers of &#945;&#946;-tubulin heterodimers that organize into distinct structures in cells. Microtubule-based architectures and ...

Using Microfluidics and Fluorescence Microscopy to Study the Assembly Dynamics of Single Actin Filaments and Bundles

In order to decipher the complex molecular mechanisms that regulate the assembly and disassembly of actin filaments, it is a great asset to monitor individual reactions live in well-controlled conditions. To do so, live single-filament experiments have emerged over the past 20 years, mostly using total internal reflection fluorescence (TIRF) microscopy, and have provided a trove of key results. In 2011, in order to further expand the possibilities of these experiments and to avoid recurring problematic artifacts, we introduced simple microfluidics in these assays. This study details our basic protocol, where individual actin filaments are anchored by one end to the passivated coverslip surface, align with the flow, and can be successively exposed to different protein solutions. We also present the protocols for specific applications and explain how controlled mechanical forces can be applied, thanks to the viscous drag of the flowing solution. We highlight the technical caveats of these experiments and briefly present possible developments based on this technique. These protocols and explanations, along with today&#39;s availability of easy-to-use microfluidics equipment, should allow non-specialists to implement this assay in their labs.

We present protocols for simple actin filament microfluidic assays, in combination with fluorescence microscopy, that allow one to accurately monitor individual actin filaments in real-time while sequentially exposing them to different protein solutions.

In order to decipher the complex molecular mechanisms that regulate the assembly and disassembly of actin filaments, it is a great asset to monitor ...

Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy

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Extracellular Protein Microarray Technology for High Throughput Detection of Low Affinity Receptor-Ligand Interactions

Probing The Structure And Dynamics Of Nucleosomes Using Atomic Force Microscopy Imaging

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Production of Dynein and Kinesin Motor Ensembles on DNA Origami Nanostructures for Single Molecule Observation

Screening for Phytoestrogens using a Cell-based Estrogen Receptor β Reporter Assay

Monitoring Protein-RNA Interaction Dynamics In Vivo at High Temporal Resolution Using χCRAC

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Quantification of Subcellular Glycogen Distribution in Skeletal Muscle Fibers using Transmission Electron Microscopy

Simultaneous Visualization of the Dynamics of Crosslinked and Single Microtubules In Vitro by TIRF Microscopy

Using Microfluidics and Fluorescence Microscopy to Study the Assembly Dynamics of Single Actin Filaments and Bundles