D.M.O. acknowledges European Research Council grant No. 337187 and the Marie-Curie Career Integration Grant No. 334303. P.W.W. acknowledges the Natural Sciences and Engineering Research Council of Canada's Discovery Grant program.

Note: Stages 1 and 2 take place before the day of imaging; ensure all media and supplements to be used before or on the day of imaging are equilibrated. Equilibration is achieved through warming of media and supplements to 37 &#176;C in an incubator set to 5% CO2. All cell culture work and coverslip plating steps take place in sterile conditions under a laminar flow hood.
1. Cell Transfection
<ol>
	<li>Transfect the T cells to be imaged 24 hr before the experiment with a plasmid encoding a fluorescent fusion construct for F-actin GFP labelling and imaging. Note: Cells should be split 24 hr prior to transfection (48 hr prior to imaging) to ensure cells are at optimal health and in their logarithmic growth phase.
	<ol>
		<li>Place 5 mL of RPMI supplement (RPMI 1640 plus 10% FBS and 1% Pen-Strep (optional)) in a single well of a 6-well plate into the incubator to equilibrate.</li>
		<li>Pellet 2 x 107 T cells cultured at 37 &#176;C +5 % CO2 in RPMI supplement using a centrifuge tube at 327 x g for 5 min and wash in an equal volume of pre-warmed electroporation media. Note: Electroporation medium is a reduced serum medium containing buffers and supplements (see consumables).</li>
		<li>After re-pelleting at 327 x g for 5 min, resuspend the cells in 500 &#181;l of electroporation media and slowly add to a cuvette, add 5 &#181;g of the plasmid in PCR grade dH2O for labelling F-actin.</li>
		<li>Gently tap the cuvette on the hood workspace to ensure removal of any air bubbles in the media, which can cause arcing of the electricity and to distribute the cells evenly within the media.</li>
		<li>Turn on the electroporation apparatus and set voltage to 300 V and capacitance to 290 &#937;. Electroporate sample using an exponential decay for 20 msec. Note: Optimization may be required for different cells and different plasmid constructs.</li>
		<li>Once the transfection protocol is complete, store cells on ice for 1 min before continuing.</li>
		<li>Carefully transfer the cells from the cuvette to the 6-well plate containing 5 mL of equilibrated RPMI supplement from step 1.1.1.</li>
		<li>Incubate the cells O/N at 37 &#176;C + 5% CO2.</li>
	</ol>
	</li>
</ol>
2. Coat Coverslips and Pre-warm Imaging Supplement
<ol>
	<li>Coat coverslips with antibodies to induce T cell stimulation.
	<ol>
		<li>Coat each chamber of an 8-well coverslip with 1 &#181;g / ml &#945;CD3 and &#945;CD28 in 200 &#181;l PBS.</li>
		<li>Store at 4 &#176;C O/N. Alternatively, coat coverslips 2 hr prior to imaging and keep in an incubator at 37 &#176;C to reduce drift during the imaging process by minimizing temperature changes to the coverslip.</li>
	</ol>
	</li>
	<li>Create a coverslip test sample with 0.1 &#181;m sub-diffraction fluorescent microspheres.
	<ol>
		<li>Vortex stock solution of beads to avoid clumps.</li>
		<li>On a new, clean coverslip of the same type as those used in step 2.1.1, pipette 5 &#181;l fluorescent microsphere stock solution onto the surface (as per manufacturer&#39;s instructions).</li>
		<li>Spread microsphere solution over the coverslip with pipette tip.</li>
		<li>Allow to dry, then apply 200 &#181;l mounting medium such as PBS. 
		Note: the mounting medium should match that used for imaging cell samples.</li>
	</ol>
	</li>
	<li>Equilibrate HBSS (+ 20 mM HEPES, hereafter called &#39;HBSS supplement&#39;) in a centrifuge tube by placing in an incubator to pre-warm O/N at 37 &#176;C + 5% CO2. 
	Note: the addition of HEPES is to buffer CO2, if using an incubation chamber with CO2 input skip this supplementation.</li>
</ol>
3. Microscope Set-up
<ol>
	<li>Turn on the stage-top incubator of the TIRF-SIM microscope and place enough distilled water in the reservoir of the microscope to fully cover the base of the heating element. Allow water to equilibrate to 37 &#176;C. Add the heating collar to the objective lens, also set to 37 &#176;C. 
	Note: Due to the sensitivity of the set-up, these steps are done the night before so the optical components are at a stable temperature prior to imaging.</li>
	<li>Place the TIRF 488 compatible grating block in the light path of the microscope and secure in place.
	<ol>
		<li>Switch the channel mode and the fiber cable to the &#39;Single&#39; position on the laser bed and microscope stage respectively to engage the correct optical path for the TIRF-SIM mode. Note: Skipping this step will lead to an error (Figure 1A) within the software window.</li>
	</ol>
	</li>
	<li>Turn on all microscope and computer components and open the acquisition control software.
	<ol>
		<li>Open the OC panel, Ti Pad, N-SIM Pad and ND Acquisition windows (Figure 1B). In the &#39;OC Panel&#39; select the option &#39;TIRF 488&#39; (Figure 2B, yellow arrow).</li>
		<li>In the N-SIM Pad window, select the &#39;TIRF-SIM&#39; and &#39;Moving&#39; settings (Figure 2C, yellow arrows). Select the settings button (Figure 1C, yellow box) and select &#39;TIRF 488 (for 100x TIRF 488nm)&#39; from the dropdown menu, hit &#39;Apply&#39; and &#39;OK&#39;.</li>
		<li>Set the camera settings within the &#39;DU897 settings&#39; to: Frame Rate 50 msec, Readout mode, EM Gain 3 MHz at 14-bit, and EM Gain Multiplier 300 with a Conversion Gain of 1 (Figure 1C, green box). 
		Note: see Representative Results for frame rate considerations.</li>
		<li>Calibrate the microscope&#39;s illumination for TIRF-SIM by selecting the 100x 1.49 NA CFI Apochromat TIRF objective, on the &#39;N-SIM Pad&#39; turn the 488 nm laser power to 10%. 
		Note: Pixel size of the raw images is 60 nm, with a 512 x 512 pixel field of view.</li>
		<li>Clean the objective lens using lens tissue to remove dust and oil.</li>
	</ol>
	</li>
	<li>Find the TIRF-SIM focal plane.
	<ol>
		<li>Start with the objective in the lowest possible z-plane. Place a drop of lens oil on the objective and add the fluorescent microsphere sample from step 2.2 to the microscope stage.</li>
		<li>Select the Perfect Focus System (PFS) function located on the body of the microscope.</li>
		<li>Slowly move the objective up through the z-plane until the PFS button stops flashing to confirm the focal plane has been reached.</li>
		<li>Switch to &#39;Live&#39; view on the control software and image the microspheres for final adjustments made by using the PFS micro-manipulator wheel.</li>
	</ol>
	</li>
	<li>Observe the uniform illumination with no out-of-focus fluorescence emission above the 75 nm evanescent wave. 
	Note: Confirm structured illumination is fulfilled by observing a fluctuating illumination pattern from the fluorescent microsphere sample.</li>
	<li>Measure fluorescent microsphere sample and quantify the improved imaging resolution by observing the Full Width at Half Maximum (FWHM) of the intensity profile.
	<ol>
		<li>Open the Analyze software (v4.20.01), with the NIS-A N-SIM Analysis module installed and select &#39;Applications&#39; -&#62; &#39;Show N-SIM window&#39;.</li>
		<li>With the illumination modulation contrast (IMC) and high resolution noise suppression (HRNS) set to 1 for TIRF-SIM datasets (Figure 2), reconstruct the microsphere sample image to generate a reconstructed image of 1,024 x 1,024 pixels with a pixel size of 30 nm.</li>
		<li>Using the line profile tool with a width of 1 pixel (Figure 3A, yellow box), draw a line through the center of a single microsphere.</li>
		<li>Select the FWHM button (Figure 3B, yellow box) and click at the intensity maxima of the Gaussian distribution, followed by its intensity minima.</li>
		<li>Confirm the FWHM of the microsphere is in the range of 100 nm (Figure 3C). Note: the resolution achieved when imaging biological samples will vary depending on the signal to noise ratio from labelling efficiency and background fluorescence.</li>
	</ol>
	</li>
</ol>
4. Sample Preparation for Imaging
<ol>
	<li>Coverslip preparation.
	<ol>
		<li>Retrieve &#945;CD-coated coverslip from step 2.1 from fridge or incubator and remove PBS containing &#945;CD3 and &#945;CD28 from each well.</li>
		<li>Add 200 &#181;l of pre-warmed HBSS supplement from step 2.3 to each well of the coverslip. Wash and remove to ensure minimal &#945;CD3 and &#945;CD28 is left in solution. Add another 200 &#181;l of the HBSS supplement to the coverslip wells.</li>
		<li>Clean the underside of the coverslip with lens tissue to remove oil and particulates.</li>
	</ol>
	</li>
	<li>Position coverslip on the microscope stage and find the TIRF focal plane of the coverslip by using the PFS z-plane as found in step 3.4.</li>
	<li>Cell preparation.
	<ol>
		<li>Pipette 200 &#181;l of the media containing transfected cells from step 1.1.8 into a micro-centrifuge tube.</li>
		<li>Pellet cells in a micro-centrifuge at 268 x g for 20 sec and remove cell media.</li>
		<li>Resuspend cells in 200 &#181;l pre-warmed HBSS supplement from step 2.3.</li>
	</ol>
	</li>
</ol>
5. Imaging Cells
<ol>
	<li>Take cell-containing HBSS supplement to the microscope and gently pipette 200 &#181;l into one of the wells.</li>
	<li>While remaining in the TIRF focal plane at the coverslip (in PFS mode), use the microscopes eyepiece and epifluorescence illumination to track fluorescent cells approaching the coverslip.</li>
	<li>Once the cells land on the coverslip, switch to &#39;Live&#39; mode in the N-SIM Pad to bring the image up on the monitor and check the cells are in focus on the computer screen.</li>
	<li>To record time-courses, open the ND Acquisition window and select the &#39;Time&#39; tab, click &#39;Add&#39; and set &#39;Interval&#39; to No delay, &#39;Duration&#39; to 10 min, &#39;Loops&#39; is set to 1. 
	Note: Duration can be changed depending on the process of interest; the STICS software can extract quantitative results with image stacks of &#8776;10 frames when captured with &#39;No Delay&#39;.</li>
	<li>With identical acquisition settings to the bead sample, start recording data by selecting &#39;Run now&#39; in the ND Acquisition window.</li>
</ol>
6. Reconstructing SIM Images
<ol>
	<li>After imaging is complete, open the Analyze software (v4.20.01), with the NIS-A N-SIM Analysis module installed and select &#39;Applications&#39; -&#62; &#39;Show N-SIM window&#39;.</li>
	<li>With the illumination modulation contrast (IMC) and high resolution noise suppression (HRNS) set to 1 for TIRF-SIM datasets (Figure 2), reconstruct one (or multiple using the Batch tool) raw SIM file to produce a reconstructed SIM image.</li>
	<li>Confirm the reconstructed file has a pixel size of 30 nm, indicated in the image status bar. 
	Note: Pixel size does not affect STICS analysis but it should be at least 2x smaller in dimension than the PSF spatial resolution in order to ensure spatial correlation between pixels.</li>
	<li>Export the data as .tiff files, ready for STICS analysis.</li>
</ol>
7. STICS Analysis
<ol>
	<li>Download and extract the STIC(C)S Matlab software package (Wiseman lab; available as supplementary information). The script stics_vectormapping.m is the core of a single channel STICS analysis and the first 30 lines of code are used to define the input parameters as defined in section 2.1 of the manual. Open this script and define the input parameters for TIRF-SIM data analysis. It is suggested to also add the STIC(C)S folder with subfolders to the local machine Matlab path, as detailed in the appendix of the manual.
	<ol>
		<li>Define the input parameters for the data analysis by editing the corresponding lines of the code</li>
		<li>To perform analysis of the TIRF-SIM data to generate 1 vector map, set the temporal parameters to temporal subregion in line 31 to the maximum number of frames and the temporal shift in line 32 to 1. To obtain a time series of vector maps vary these parameters.</li>
		<li>For the Immobile removal filter, set the parameter &#39;filtering&#39; (line 23) to &#39;Moving average&#39; and set the &#39;MoveAverage&#39; parameter (line 24) to 21. 
		Note: This setting has been shown to work for slower moving and large fluorescence signals, as it is based on subtracting serial frames from the frame being analyzed.</li>
		<li>Change lines 33-38 to set the name of the output files and titles of the output vector maps, as well as the output directory path and define in what format the vector map images should be saved.</li>
	</ol>
	</li>
</ol>
<table>
	<tbody>
		<tr>
			<td>Pixel size (&#181;m)</td>
			<td>0.03 &#181;m</td>
			<td>Line 19</td>
		</tr>
		<tr>
			<td>Frame rate (sec)</td>
			<td>1 sec</td>
			<td>Line 20</td>
		</tr>
		<tr>
			<td>Maximum lag time (frames)</td>
			<td>20 frames</td>
			<td>Line 21</td>
		</tr>
		<tr>
			<td>Subregion size (pixels)</td>
			<td>8 pixels</td>
			<td>Line 29</td>
		</tr>
		<tr>
			<td>Subregion spacing (pixels)</td>
			<td>1 pixel</td>
			<td>Line 30</td>
		</tr>
	</tbody>
</table>
<ol start="2">
	<li>Open the script run1ChannelSTICS in the Matlab Editor window. Load the image series by running lines 1-23 of this script. 
	Note: This script can be used to load and pre-process image series, plot the vector maps and speed histograms and run a batch processing for many files. If required, crop the image to a region of interest by using the line 24-26 of this script.
	<ol>
		<li>Run lines 29-35 of run1ChannelSTICS to start STICS analysis. When prompted, select a polygon to indicate a specific region of interest (ROI), if desired. Ensure that the ROI does not overlap with the cell edge, as boundary artefacts occur when STICS analyzes these regions.</li>
		<li>Run lines 38-52 to display the vector maps. To plot the velocity magnitude histogram, run lines 53-72.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Monks, C., Freiberg, B., Kupfer, H., Sciaky, N., Kupfer, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+segregation+of+supramolecular+activation+clusters+in+T+cells.">Three-dimensional segregation of supramolecular activation clusters in T cells.</a> Nature. 395, 82-86 (1998).</li><li>Lanzavecchia, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antigen-specific+interaction+between+T+and+B+cells.">Antigen-specific interaction between T and B cells.</a> Nature. 314, 537-539 (1985).</li><li>Grakoui, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+immunological+synapse:+a+molecular+machine+controlling+T+cell+activation.">The immunological synapse: a molecular machine controlling T cell activation.</a> Science. 285 (5425), 221-227 (1999).</li><li>Delon, J., Bercovici, N., Liblau, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+antigen+recognition+by+naive+CD4++T+cells:+compulsory+cytoskeletal+alterations+for+the+triggering+of+an+intracellular+calcium+response.">Imaging antigen recognition by naive CD4+ T cells: compulsory cytoskeletal alterations for the triggering of an intracellular calcium response.</a> European journal of Immunology. 28 (2), 716-729 (1998).</li><li>Varma, R., Campi, G., Yokosuka, T., Saito, T., Dustin, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=T+Cell+Receptor-Proximal+Signals+Are+Sustained+in+Peripheral+Microclusters+and+Terminated+in+the+Central+Supramolecular+Activation+Cluster.">T Cell Receptor-Proximal Signals Are Sustained in Peripheral Microclusters and Terminated in the Central Supramolecular Activation Cluster.</a> Immunity. 25 (1), 117-127 (2006).</li><li>Rust, M. J., Bates, M., Zhuang, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sub-diffraction-limit+imaging+by+stochastic+optical+reconstruction+microscopy+(STORM).">Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM).</a> Nature methods. 3, 793-796 (2006).</li><li>Betzig, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+intracellular+fluorescent+proteins+at+nanometer+resolution.">Imaging intracellular fluorescent proteins at nanometer resolution.</a> Science. 313 (5793), 1642-1645 (2006).</li><li>Klar, T. A., Jakobs, S., Dyba, M., Egner, A., Hell, S. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+microscopy+with+diffraction+resolution+barrier+broken+by+stimulated+emission.">Fluorescence microscopy with diffraction resolution barrier broken by stimulated emission.</a> Proceedings of the National Academy of Sciences. 97 (15), 8206-8210 (2000).</li><li>Gustafsson, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Surpassing+the+lateral+resolution+limit+by+a+factor+of+two+using+structured+illumination+microscopy.">Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy.</a> Journal of Microscopy. 198 (2), 82-87 (2000).</li><li>Hebert, B., Costantino, S., Wiseman, P. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatiotemporal+image+correlation+spectroscopy+(STICS)+theory,+verification,+and+application+to+protein+velocity+mapping+in+living+CHO+cells.">Spatiotemporal image correlation spectroscopy (STICS) theory, verification, and application to protein velocity mapping in living CHO cells.</a> Biophysical Journal. 88 (5), 3601-3614 (2005).</li><li>Ashdown, G. W., Cope, A., Wiseman, P. W., Owen, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+Flow+Quantified+beyond+the+Diffraction+Limit+by+Spatiotemporal+Image+Correlation+of+Structured+Illumination+Microscopy+Data.">Molecular Flow Quantified beyond the Diffraction Limit by Spatiotemporal Image Correlation of Structured Illumination Microscopy Data.</a> Biophysical Journal. 107 (9), 21-23 (2014).</li><li>Brown, C. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Probing+the+integrin-actin+linkage+using+high-resolution+protein+velocity+mapping.">Probing the integrin-actin linkage using high-resolution protein velocity mapping.</a> Journal of Cell Science. 19 (24), 5204-5214 (2006).</li><li>Yi, J., Xufeng, S. W., Crites, T., Hammer, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Actin+retrograde+flow+and+actomyosin+II+arc+contraction+drive+receptor+cluster+dynamics+at+the+immunological+synapse+in+Jurkat+T+cells.">Actin retrograde flow and actomyosin II arc contraction drive receptor cluster dynamics at the immunological synapse in Jurkat T cells.</a> Molecular Biology of the Cell. 23 (5), 834-852 (2012).</li><li>Watanabe, N., Mitchison, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-molecule+speckle+analysis+of+actin+filament+turnover+in+lamellipodia.">Single-molecule speckle analysis of actin filament turnover in lamellipodia.</a> Science. 8 (5557), 1083-1086 (2002).</li></ol>

The authors declare that they have no competing financial interests.

This technique will allow researchers to image and quantify previously unresolvable details in cells expressing fluorescence. In our results we show that F-actin flows in a symmetrical fashion from the cell periphery towards the cell center in the T cell IS. These findings are consistent with previous results from 1D line profile kymograph data13 and extend the capacity of analysis to 2D and super-resolution data.
The presented technique is a progression from kymograph imaging which...

The goal of the experiment is to image and characterize the molecular flow of filamentous- (F-) actin in living T cells, beyond the diffraction limit in order to establish flow direction and magnitude during immunological synapse (IS) formation. This technique will be carried out using a structured illumination microscope (SIM) in total internal reflection fluorescence (TIRF) mode, imaging Jurkat T-cells forming an artificial synapse on activating coverslips coated with anti-CD3- and anti-CD28 antibodies. The IS forms between a T cell and its target; an antigen presenting cell (APC) upon T cell receptor (TCR) activation1,2. As this is the first step in determining whether the adaptive immune system generates an immune response to an infection, the consequences of incorrect responsiveness to stimuli can cause a number of diseases. The importance of the T cell-APC interaction is well documented, however, the role(s) of the mature IS after initial TCR signal internalization are yet to be fully understood.
As the cytoskeleton is thought to aid two processes linked to TCR activation (the movement of molecules at the plasma membrane and the control of signaling molecules dependent on the actin cytoskeleton3,4 ), understanding how the cytoskeleton rearranges spatially and temporally will elucidate the steps of molecular reorganization during synapse formation. The retrograde flow of F-actin is thought to corral TCR clusters towards the center of the immunological synapse, this translocation is believed to be vital for signal cessation and recycling; aiding the fine balance of T cell activation5.
While standard fluorescence microscopy is a flexible tool that continues to provide insight about many biological events including cell-cell interactions, it is limited by the system&#39;s ability to accurately resolve multiple fluorophores residing closer than the diffraction limit (&#8776;200 nm) of each other. As many molecular events within cells involve dense populations of molecules and exhibit dynamic rearrangement either in quiescence or upon specific stimulation, conventional light microscopy does not provide the full picture.
The use of super resolution imaging has allowed researchers to circumvent the diffraction limit using a variety of techniques. Single molecule localization microscopy (SMLM) such as PALM and STORM6,7 has the ability to resolve the location of molecules up to a precision of around 20 nm, however, these techniques rely on long acquisition times, building up an image over many frames. Generally this requires samples to be fixed or for structures to exhibit low mobility so single fluorophores are not misinterpreted as multiple points. While stimulated emission depletion (STED) imaging allows super-resolution through very selective confocal excitation8, the required scanning approach can be slow over whole cell fields of view. STED also demonstrates significant phototoxicity for higher resolutions due to the increase in power of the depletion beam.
Structured illumination microscopy (SIM9) provides an alternative to these methods, capable of doubling the resolution of a standard fluorescence microscope and is more compatible with live cell imaging than current SMLM techniques. It uses lower laser powers, on a wide-field system for whole-cell fields of view; providing increased acquisition speeds, and is compatible with standard fluorophore labelling. The wide-field nature of SIM also permits the utilization of total internal reflection fluorescence (TIRF) for highly selective excitation, with penetration depths in the axial dimension of &#60;100 nm.
Image correlation spectroscopy (ICS) is a method of correlating fluctuations in fluorescence intensity. An evolution of ICS; Spatio-temporal image correlation spectroscopy (STICS10) correlates intracellular fluorescent signals in time and space. By correlating pixel intensities with surrounding pixels in lagging frames via a correlation function, information is gained regarding flow speeds and directionality. To ensure static objects do not interfere with the STICS analysis, an immobile object filter is implemented, which works by subtracting a moving average of the pixel intensities.
The technique presented here is believed to be the first demonstration of image correlation spectroscopy being applied to super-resolution microscopy data to quantify the molecular flow in live cells11. This method improves on diffraction-limited imaging of F-actin flow via STICS analysis12 and would suit researchers who wish to determine two-dimensional molecular flow in live cells, from data acquired at spatial resolutions beyond the diffraction limit of light.

<table border="0" cellpadding="0" cellspacing="0" width="799">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:271px;">Consumables:</td>
			<td style="width:245px;"></td>
			<td style="width:123px;"></td>
			<td style="width:160px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Jurkat E6.1 cells</td>
			<td>APCC</td>
			<td>ATTC TIB-152</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">RPMI</td>
			<td>Life Technologies</td>
			<td>21875-091</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">FBS</td>
			<td>Sigma</td>
			<td>F7524-500ML</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Penicillin-Strepromycin&#160;</td>
			<td>Life Technologies</td>
			<td>15140-122</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">HBSS</td>
			<td>&#160;Life Technologies</td>
			<td>14025-050</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">HEPES</td>
			<td>Life Technologies</td>
			<td>15630-056</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">#1.5 8-well Labtek coverslips</td>
			<td>NUNC, Labtek</td>
			<td>155409</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">LifeAct GFP construct</td>
			<td>Ibidi</td>
			<td>60101</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">OptiMem</td>
			<td>Life Technologies</td>
			<td>51985-042</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">anti-CD3</td>
			<td>Cambridge Bioscience</td>
			<td>317315</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">anti-CD28</td>
			<td>BD Bioscience / Insight Biotechnology</td>
			<td>555725</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">PBS</td>
			<td>Life Technologies</td>
			<td>20012-019</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Lens oil</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Name</td>
			<td>Company</td>
			<td>Catalog number</td>
			<td>Comments</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Equipment:</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Gene Pulsar Xcell System</td>
			<td>BioRad</td>
			<td>165-2660</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Cuvette (0.4cm)</td>
			<td>BioRad</td>
			<td>165-2088</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Centrifuge (5810R)</td>
			<td>Eppendorf&#160;</td>
			<td>5805 000.327</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Centrifuge (Heraeus)</td>
			<td>Biofuge pico</td>
			<td>75003235</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">6 well plate</td>
			<td>Corning</td>
			<td>3516</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Stage-top incubator</td>
			<td>Tokai Hit</td>
			<td>INUH-TIZSH</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nikon N-SIM microscope</td>
			<td>Nikon</td>
			<td>Contact company</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nikon Analyse software</td>
			<td>Nikon</td>
			<td>Contact company</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Incubator (190D)</td>
			<td>LEEC</td>
			<td>Contact company</td>
			<td></td>
		</tr>
	</tbody>
</table>

cortical actin flow in t cells quantified by spatio-temporal image correlation spectroscopy of structured illumination microscopy data

Filamentous-actin plays a crucial role in a majority of cell processes including motility and, in immune cells, the formation of a key cell-cell interaction known as the immunological synapse. F-actin is also speculated to play a role in regulating molecular distributions at the membrane of cells including sub-membranous vesicle dynamics and protein clustering. While standard light microscope techniques allow generalized and diffraction-limited observations to be made, many cellular and molecular events including clustering and molecular flow occur in populations at length-scales far below the resolving power of standard light microscopy. By combining total internal reflection fluorescence with the super resolution imaging method structured illumination microscopy, the two-dimensional molecular flow of F-actin at the immune synapse of T cells was recorded. Spatio-temporal image correlation spectroscopy (STICS) was then applied, which generates quantifiable results in the form of velocity histograms and vector maps representing flow directionality and magnitude. This protocol describes the combination of super-resolution imaging and STICS techniques to generate flow vectors at sub-diffraction levels of detail. This technique was used to confirm an actin flow that is symmetrically retrograde and centripetal throughout the periphery of T cells upon synapse formation.

Microscope settings
After successfully achieving all steps the researcher will have accomplished structured illumination (SIM) imaging of F-actin flow in a T cell synapse (Video 1), and quantified this molecular flow by spatio-temporal image correlation spectroscopy (Figure 411). Before recording images, ensure the sample illumination is uniform across the nine raw images and that structured illuminat...

Watch this Scientific Journal Video about Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data at JoVE.com

Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data

To investigate flow velocities and directionality of filamentous-actin at the T cell immunological synapse, live-cell super-resolution imaging is combined with total internal reflection fluorescence and quantified with spatio-temporal image correlation spectroscopy.

Filamentous-actin plays a crucial role in a majority of cell processes including motility and, in immune cells, the formation of a key cell-cell ...

cortical-actin-flow-t-cells-quantified-spatio-temporal-image

Research

JoVE Journal

Immunology and Infection

9.6K visualizações.  King's College London. To investigate flow velocities and directionality of filamentous-actin at the T cell immunological synapse, live-cell super-resolution imaging is combined with total internal reflection fluorescence and quantified with spatio-temporal image correlation spectroscopy. 

Vídeo: Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data

Retroviral Transduction of T-cell Receptors in Mouse T-cells

T-cell receptors (TCRs) play a central role in the immune system. TCRs on T-cell surfaces can specifically recognize peptide antigens presented by antigen presenting cells (APCs)1. This recognition leads to the activation of T-cells and a series of functional outcomes (e.g. cytokine production, killing of the target cells). Understanding the functional role of TCRs is critical to harness the power of the immune system to treat a variety of immunology related diseases (e.g. cancer or autoimmunity).
It is convenient to study TCRs in mouse models, which can be accomplished in several ways. Making TCR transgenic mouse models is costly and time-consuming and currently there are only a limited number of them available2-4. Alternatively, mice with antigen-specific T-cells can be generated by bone marrow chimera. This method also takes several weeks and requires expertise5. Retroviral transduction of TCRs into in vitro activated mouse T-cells is a quick and relatively easy method to obtain T-cells of desired peptide-MHC specificity. Antigen-specific T-cells can be generated in one week and used in any downstream applications. Studying transduced T-cells also has direct application to human immunotherapy, as adoptive transfer of human T-cells transduced with antigen-specific TCRs is an emerging strategy for cancer treatment6.
Here we present a protocol to retrovirally transduce TCRs into in vitro activated mouse T-cells. Both human and mouse TCR genes can be used. Retroviruses carrying specific TCR genes are generated and used to infect mouse T-cells activated with anti-CD3 and anti-CD28 antibodies. After in vitro expansion, transduced T-cells are analyzed by flow cytometry.

We present a protocol to produce antigen-specific mouse T-cells using retroviral transduction

T-cell receptors (TCRs) play a central role in the immune system. TCRs on T-cell surfaces can specifically recognize peptide antigens presented by antigen ...

piggyBac Transposon System Modification of Primary Human T Cells

The piggyBac transposon system is naturally active, originally derived from the cabbage looper moth1,2. This non-viral system is plasmid based, most commonly utilizing two plasmids with one expressing the piggyBac transposase enzyme and a transposon plasmid harboring the gene(s) of interest between inverted repeat elements which are required for gene transfer activity. PiggyBac mediates gene transfer through a "cut and paste" mechanism whereby the transposase integrates the transposon segment into the genome of the target cell(s) of interest. PiggyBac has demonstrated efficient gene delivery activity in a wide variety of insect1,2, mammalian3-5, and human cells6 including primary human T cells7,8. Recently, a hyperactive piggyBac transposase was generated improving gene transfer efficiency9,10.
Human T lymphocytes are of clinical interest for adoptive immunotherapy of cancer11. Of note, the first clinical trial involving transposon modification of human T cells using the Sleeping beauty transposon system has been approved12. We have previously evaluated the utility of piggyBac as a non-viral methodology for genetic modification of human T cells. We found piggyBac to be efficient in genetic modification of human T cells with a reporter gene and a non-immunogenic inducible suicide gene7. Analysis of genomic integration sites revealed a lack of preference for integration into or near known proto-oncogenes13. We used piggyBac to gene-modify cytotoxic T lymphocytes to carry a chimeric antigen receptor directed against the tumor antigen HER2, and found that gene-modified T cells mediated targeted killing of HER2-positive tumor cells in vitro and in vivo in an orthotopic mouse model14. We have also used piggyBac to generate human T cells resistant to rapamycin, which should be useful in cancer therapies where rapamycin is utilized15.
Herein, we describe a method for using piggyBac to genetically modify primary human T cells. This includes isolation of peripheral blood mononuclear cells (PBMCs) from human blood followed by culture, gene modification, and activation of T cells. For the purpose of this report, T cells were modified with a reporter gene (eGFP) for analysis and quantification of gene expression by flow cytometry.
PiggyBac can be used to modify human T cells with a variety of genes of interest. Although we have used piggyBac to direct T cells to tumor antigens14, we have also used piggyBac to add an inducible safety switch in order to eliminate gene modified cells if needed7. The large cargo capacity of piggyBac has also enabled gene transfer of a large rapamycin resistant mTOR molecule (15 kb)15. Therefore, we present a non-viral methodology for stable gene-modification of primary human T cells for a wide variety of purposes.

piggyBac Transposon System Modification of Primary Human T Cells

We describe a method to genetically modify primary human T cells with a transgene using the non-viral piggyBac transposon system. T cells modified to using the piggyBac transposon system exhibit stable transgene expression.

The piggyBac transposon system is naturally active, originally derived from the cabbage looper moth1,2. This non-viral system is plasmid based, most ...

Highly Resolved Intravital Striped-illumination Microscopy of Germinal Centers

Monitoring cellular communication by intravital deep-tissue multi-photon microscopy is the key for understanding the fate of immune cells within thick tissue samples and organs in health and disease. By controlling the scanning pattern in multi-photon microscopy and applying appropriate numerical algorithms, we developed a striped-illumination approach, which enabled us to achieve 3-fold better axial resolution and improved signal-to-noise ratio, i.e. contrast, in more than 100 &#181;m tissue depth within highly scattering tissue of lymphoid organs as compared to standard multi-photon microscopy. The acquisition speed as well as photobleaching and photodamage effects were similar to standard photo-multiplier-based technique, whereas the imaging depth was slightly lower due to the use of field detectors. By using the striped-illumination approach, we are able to observe the dynamics of immune complex deposits on secondary follicular dendritic cells &#8211; on the level of a few protein molecules in germinal centers.

High-resolution intravital imaging with enhanced contrast up to 120 &#181;m depth in lymph nodes of adult mice is achieved by spatially modulating the excitation pattern of a multi-focal two-photon microscope. In 100 &#181;m depth we measured resolutions of 487 nm (lateral) and 551 nm (axial), thus circumventing scattering and diffraction limits.

Monitoring cellular communication by intravital deep-tissue multi-photon microscopy is the key for understanding the fate of immune cells within thick ...

Induction of Murine Intestinal Inflammation by Adoptive Transfer of Effector CD4+CD45RBhigh T Cells into Immunodeficient Mice

There are many different animal models available for studying the pathogenesis of human inflammatory bowel diseases (IBD), each with its own advantages and disadvantages. We describe here an experimental colitis model that is initiated by adoptive transfer of syngeneic splenic CD4+CD45RBhigh T cells into T and B cell deficient recipient mice. The CD4+CD45RBhigh T cell population that largely consists of na&#239;ve effector cells is capable of inducing chronic intestinal inflammation, closely resembling key aspects of human IBD. This method can be manipulated to study aspects of disease onset and progression. Additionally it can be used to study the function of innate, adaptive, and regulatory immune cell populations, and the role of environmental exposures, i.e., the microbiota, in intestinal inflammation. In this article we illustrate the methodology for inducing colitis with a step-by-step protocol. This includes a video demonstration of key technical aspects required to successfully develop this murine model of experimental colitis for research purposes.

Induction of Murine Intestinal Inflammation by Adoptive Transfer of Effector CD4+CD45RBhigh T Cells into Immunodeficient Mice

Here, we present a protocol to induce colonic inflammation in mice by adoptive transfer of syngeneic CD4+CD45RBhigh T cells into T and B cell deficient recipients. Clinical and histopathological features mimic human inflammatory bowel diseases. This method allows the study of the initiation of colonic inflammation and progression of disease.

There are many different animal models available for studying the pathogenesis of human inflammatory bowel diseases (IBD), each with its own advantages ...

T Cells Capture Bacteria by Transinfection from Dendritic Cells

Recently, we have shown, contrary to what is described, that CD4+ T cells, the paradigm of adaptive immune cells, capture bacteria from infected dendritic cells (DCs) by a process called transinfection. Here, we describe the analysis of the transinfection process, which occurs during the course of antigen presentation. This process was unveiled by using CD4+ T cells from transgenic OTII mice, which bear a T cell receptor (TCR) specific for a peptide of ovoalbumin (OVAp), which therefore can form stable immune complexes with infected dendritic cells loaded with this specific OVAp. The dynamics of green fluorescent protein (GFP)-expressing bacteria during DC-T cell transmission can be monitored by live-cell imaging and the quantification of bacterial transinfection can be performed by flow cytometry. In addition, transinfection can be quantified by a more sensitive method based in the use of gentamicin, a non-permeable aminoglycoside antibiotic killing extracellular bacteria but not intracellular ones. This classical method has been used previously in microbiology to study the efficiency of bacterial infections. We hereby explain the protocol of the complete process, from the isolation of the primary cells to the quantification of transinfection.

Here a protocol is presented to measure bacterial capture by CD4+ T cells which occurs during antigen presentation via transinfection from pre-infected dendritic cells (DC). We show how to perform the necessary steps: isolation of primary cells, infection of DC, DC/T cell conjugate formation, and measurement of bacterial T cell transfection.

Recently, we have shown, contrary to what is described, that CD4+ T cells, the paradigm of adaptive immune cells, capture bacteria from infected dendritic ...

The Use of Flow Cytometry to Assess the State of Chromatin in T Cells

During a proper immune response, quiescent T cells become activated upon antigen presentation to their antigen-specific T cell receptor. This leads to clonal proliferation of only those T cells that bear a receptor that recognizes the antigen. Chromatin decondensation is a hallmark of T cell activation and is required for T cells to acquire the ability to proliferate after antigen engagement. This change in chromatin condensation can be detected using antibodies raised against histone proteins. These antibodies cannot bind to their epitopes in na&#239;ve T cells as well as they can in activated T cells. We describe how to simultaneously stain T cell-specific surface markers, track viability with a fixable dead cell stain, and measure chromatin status via intracellular staining of Histone H3 proteins. Stained cells are analyzed by flow cytometry and chromatin condensation status is measured as the mean fluorescence intensity (MFI) of the Histone H3 stain. Chromatin decondensation during T cell activation is demonstrated as an increase in the MFI

Flow cytometry can be utilized to assess the state of chromatin within T cells. This protocol allows scientists to interpret evidence of chromatin decondensation during T cell activation demonstrated by an increase in the mean florescence intensity (MFI) of fluorescent Histone H3 antibodies

During a proper immune response, quiescent T cells become activated upon antigen presentation to their antigen-specific T cell receptor. This leads to ...

Preparation of CD4+ T Cells for Analysis of GD3 and GD2 Ganglioside Membrane Expression by Microscopy

The methods described herein for activation of na&#239;ve CD4+ T cells in suspension and their adherence in coverslips for confocal microscopy analysis allow the spatial localization and visualization of gangliosides involved in CD4+ T cell activation, that complement expression profiling experiments such as flow cytometry, western blotting or real-time PCR. The quantification of ganglioside expression through flow cytometry and their cellular localization through microscopy can be obtained by the use of anti-ganglioside antibodies with high affinity and specificity. Nonetheless, an adequate handling of cells in suspension involves the treatment of culture plates to promote the necessary adherence required for fluorescence or confocal microscopy acquisition. In this work, we describe a protocol for determining GD3 and GD2 ganglioside expression and colocalization with the TCR during na&#239;ve CD4+ T cell activation. Also, real-time PCR experiments using &#60;40,000 cells are described for the determination of the GD3 and GM2/GD2 synthase genes, demonstrating that gene analysis experiments can be performed with a low number of cells and without the need of additional low input RNA kits.

Preparation of CD4+ T Cells for Analysis of GD3 and GD2 Ganglioside Membrane Expression by Microscopy

We describe a standard antibody staining protocol for use in microscopy to determine the membrane expression and localization of gangliosides in resting and activated human na&#239;ve CD4+ T cells. Also described are real-time PCR experiments using &#60;40,000 cells that do not require additional low input RNA kits.

The methods described herein for activation of na&#239;ve CD4+ T cells in suspension and their adherence in coverslips for confocal microscopy analysis ...

Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy

Fluorescence correlation spectroscopy (FCS) is a powerful technique for studying the diffusion of molecules within biological membranes with high spatial and temporal resolution. FCS can quantify the molecular concentration and diffusion coefficient of fluorescently labeled molecules in the cell membrane. This technique has the ability to explore the molecular diffusion characteristics of molecules in the plasma membrane of immune cells in steady state (i.e., without processes affecting the result during the actual measurement time). FCS is suitable for studying the diffusion of proteins that are expressed at levels typical for most endogenous proteins. Here, a straightforward and robust method to determine the diffusion rate of cell membrane proteins on primary lymphocytes is demonstrated. An effective way to perform measurements on antibody-stained live cells and commonly occurring observations after acquisition are described. The recent advancements in the development of photo-stable fluorescent dyes can be utilized by conjugating the antibodies of interest to appropriate dyes that do not bleach extensively during the measurements. Additionally, this allows for the detection of slowly diffusing entities, which is a common feature of proteins expressed in cell membranes. The analysis procedure to extract molecular concentration and diffusion parameters from the generated autocorrelation curves is highlighted. In summary, a basic protocol for FCS measurements is provided; it can be followed by immunologists with an understanding of confocal microscopy but with no other previous experience of techniques for measuring dynamic parameters, such as molecular diffusion rates.

A method to measure protein diffusion in membranes of primary immune cells using fluorescence correlation spectroscopy (FCS) is described. In this paper, the use of antibodies for fluorescent labeling is illustrated.

Fluorescence correlation spectroscopy (FCS) is a powerful technique for studying the diffusion of molecules within biological membranes with high spatial ...

Isolation and Flow Cytometric Analysis of Human Endocervical Gamma Delta T Cells

The female reproductive tract (FRT) mucosal immune system serves as the first line of defense. Better knowledge of the genital mucosa is therefore essential for understanding pathogenicity of different pathogens including HIV. Gamma delta (GD) T cells are the prototype of &#39;unconventional&#39; T cells and represent a relatively small subset of T cells defined by their expression of heterodimeric T-cell receptors (TCRs) composed of gamma and delta chains. This sets them apart from the classical and much better known CD4+ helper T cells and CD8+ cytotoxic T cells that are defined by alpha-beta TCRs. GD T cells often show tissue-specific localization and are enriched in epithelium. GD T cells orchestrate immune responses in inflammation, tumor surveillance, infectious disease, and autoimmunity.
Here, we present a method to reproducibly isolate and analyze human endocervical intraepithelial GD T lymphocytes. We have used endocervical cytobrush samples from women participating in the Women&#39;s Interagency HIV Infection Study (WIHS). Knowledge about GD T cells interactions during conditions in which there is an insult to the vaginal mucosal could be applied to any clinical study in which mucosal vulnerability is addressed, including the development of vaginal microbicides.In addition, knowledge about mucosal GD T cell responses has potential for application of GD T cell-based immune therapy in treating infectious diseases.

We describe here an isolation method to obtain human endocervical intraepithelial lymphocytes for the analysis of intraepithelial gamma delta T cells. This protocol can be extended for the purification of endocervical gamma delta T cells by magnetic beads or by cell sorting.

The female reproductive tract (FRT) mucosal immune system serves as the first line of defense. Better knowledge of the genital mucosa is therefore ...

Induction of Paralysis and Visual System Injury in Mice by T Cells Specific for Neuromyelitis Optica Autoantigen Aquaporin-4

While it is recognized that aquaporin-4 (AQP4)-specific T cells and antibodies participate in the pathogenesis of neuromyelitis optica (NMO), a human central nervous system (CNS) autoimmune demyelinating disease, creation of an AQP4-targeted model with both clinical and histologic manifestations of CNS autoimmunity has proven challenging. Immunization of wild-type (WT) mice with AQP4 peptides elicited T cell proliferation, although those T cells could not transfer disease to na&#239;ve recipient mice. Recently, two novel AQP4 T cell epitopes, peptide (p) 135-153 and p201-220, were identified when studying immune responses to AQP4 in AQP4-deficient (AQP4-/-) mice, suggesting T cell reactivity to these epitopes is normally controlled by thymic negative selection. AQP4-/- Th17 polarized T cells primed to either p135-153 or p201-220 induced paralysis in recipient WT mice, that was associated with predominantly leptomeningeal inflammation of the spinal cord and optic nerves. Inflammation surrounding optic nerves and involvement of the inner retinal layers (IRL) were manifested by changes in serial optical coherence tomography (OCT). Here, we illustrate the approaches used to create this new in vivo model of AQP4-targeted CNS autoimmunity (ATCA), which can now be employed to study mechanisms that permit development of pathogenic AQP4-specific T cells and how they may cooperate with B cells in NMO pathogenesis.

Here, we present a protocol to induce paralysis and opticospinal inflammation by transfer of aquaporin-4 (AQP4)-specific T cells from AQP4-/- mice into WT mice. In addition, we demonstrate how to use serial optical coherence tomography to monitor visual system dysfunction.

While it is recognized that aquaporin-4 (AQP4)-specific T cells and antibodies participate in the pathogenesis of neuromyelitis optica (NMO), a human ...