We thank Xufeng Wu for access to the STORM microscope. This research was supported by the Intramural Research Program of the National Cancer Institute (NCI) Center for Cancer Research and the National Heart Lung and Blood Institute (NHLBI).

Caution: Please consult all relevant material safety data sheets (MSDS) before use. Several of the chemicals used in this protocol are toxic and carcinogenic. Please use all appropriate safety practices when performing the protocol including the use of engineering controls (fume hood, glovebox) and personal protective equipment (safety glasses, gloves, lab coat, full length pants, closed-toe shoes).
1. Multiplexed Imaging of Activated T Cells
<ol>
	<li>Directly conjugate antibodies with Alexa-647 (A647) dye using the Alexa 647 antibody labeling kit. Follow the labeling protocol provided by the manufacturer. 
	NOTE: Dialysis of antibody solution in 1x PBS is recommended before this step to increase antibody labeling efficiency.</li>
	<li>Spin labeled antibodies for 5 min at 20,800 rcf and collect supernatant to remove aggregated antibodies.</li>
	<li>Preparation of fluorescent nano-diamond-coated coverslips
	<ol>
		<li>Coat 8-well coverslip chambers (see reagent/material list) with 250 &#956;L 0.01% Poly-L-Lysine (PLL) for 15 min, aspirate, and dry at 65 &#176;C for 30 min. (No rinse before drying.)</li>
		<li>Prepare a dilution of 100 nm FNDs in 1x PBS. Test various dilutions to ensure enough FNDs are visible each field of view in step 1.2.7 (we are using a 1:200 dilution of FNDs provided by the manufacturer).</li>
		<li>Vortex the diluted FNDs for 1 min.</li>
		<li>Sonicate the FND supernatant for 30 s at a high-power setting.</li>
		<li>Incubate the sonicated FND supernatant in a PLL-coated 8-well coverslip chamber for 30 min at room temp.</li>
		<li>Wash 5x with 1x PBS and visualize the FND-coated chamber using 647 nm laser excitation on the TIRF microscope. Ideally, 4-10 individual FNDs should be visible in a field of view given the appropriate dilution of FNDs in step 1.2.2 (we are using a 100X objective with 256 x 256 camera pixel setting to yield 61 x 61 &#956;m field of view) with at least one FND present in each quadrant of the imaging field. If the FNDs appear to be clustered (i.e. FNDs with significantly higher signal than surrounding FNDs and a point spread function larger than 200 nm), centrifuge FNDs at 6,800 rcf for 1 min, and repeat the coating procedure using the FND supernatant.</li>
		<li>Add 250 &#956;l of anti-CD3 antibody (10 &#956;g/mL) in each well and incubate for 1 hr at 37 &#176;C, or overnight at 4 &#176;C.</li>
		<li>Remove solution and add 1x PBS for 30 sec. Repeat this wash step 5 times (wash 5x).</li>
	</ol>
	</li>
	<li>Activation of Jurkat T cells
	<ol>
		<li>Spin 1 ml of Jurkat T cells at 800 rcf for 6 min and resuspend in 300 &#956;l 1x HBS solution. Jurkat T cells should ideally be at a concentration of 0.5-1.0 x 106 cells/ml before spinning.&#160;1x HBS solution consists of HEPES buffer saline with 1% Bovine serum albumin as described previously22.</li>
		<li>Add 150 &#956;L of 1x HBS solution in each well and incubate at 37 &#176;C for 15 min.</li>
		<li>Add 50 &#956;L resuspended Jurkat T cells to each well and incubate for 3 min at 37 &#176;C.</li>
		<li>Add 300 &#956;L of 4% Paraformaldehyde to each well and incubate for 30 min at 37 &#176;C.</li>
		<li>Wash 3x with 1x PBS.</li>
		<li>Permeabilize cells by adding 250 &#956;L of 0.1% Triton-X solution for 5 min at room temp.</li>
		<li>Wash 3x with 1x PBS.</li>
		<li>Add 250 &#956;L 1% fish gelatin solution in 1x PBS to each well for 30 min at room temp.</li>
		<li>Wash 3x with 1x PBS.</li>
	</ol>
	</li>
	<li>Imaging activated Jurkat T cells using madSTORM
	<ol>
		<li>Add 200 &#956;L of labeled antibody at 0.1-0.5 &#956;g/mL to fixed cells for 1 hr at room temp.</li>
		<li>Wash 5x with 1x PBS.</li>
		<li>Add 1 ml of STORM buffer and cover the chamber with a glass coverslip to limit exposure to air. The STORM buffer has been described previously10. We recommend making new STORM buffer for each round of imaging and spinning the STORM buffer at 20,800 rcf for 2 min to remove precipitates.</li>
		<li>Using low 647 nm laser power in TIRF mode, locate a stained cell with at least 3 FNDs in the field of view. To aid in locating FNDs, concomitant excitation with 568 nm laser can be used to increase the brightness of the FND signal.&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; 
		NOTE: The performance of averaged fiducial correction described in section 2.1 improves with inclusion of more FNDs.</li>
		<li>Increase 647 nm laser power and acquire images. We typically acquire 10,000 frames at 200 ms exposure, 125 mW 647 nm laser, 100X TIRF objective lens (1.49 NA), 100X EM gain (5 MHz at 16 bit, conversion gain 1). Details of our imaging setup have been described previously10.</li>
		<li>Wash 5x with 1x TBS.</li>
		<li>Add 1 ml of elution buffer (3.5 M MgCl2, 20 mM PIPES, 0.1% Tween-20, pH 6.5) and incubate at room temp for 1 min.</li>
		<li>Repeat elution 3 times. (exact elution conditions and the number of elution rinses needed to remove the signal must be checked for each antibody used).</li>
		<li>Wash 3x with 1x TBS and add 1 ml of 1x PBS.</li>
		<li>Photobleach using 647 nm laser at high power (125 mW) with 405 nm laser at 2-5 mW to photo-activate A647 dyes in dark state. Wait until all remaining signal from non-eluted antibody is photobleached. Typically this takes 2-5 s of laser exposure. Acquiring sample images (~100 frames) using the STORM settings in 1.3.5 after elution and photobleaching is recommended to confirm removal of signal. 
		We typically remove 99.8% of signal using this method. We recommend testing the elution efficiency of each antibody before use in madSTORM as shown previously10.</li>
		<li>Add 250 &#956;L 4% Paraformaldehyde for 15 min. This prevents reverse crosslinking of fixed molecules in the cell.</li>
		<li>Wash 3x with 1x PBS.</li>
		<li>Repeat steps 1.3.1-1.3.12 for sequential labeling of multiple targets. Figure 1 shows a composite image of multiple molecules in an activated Jurkat T cell acquired using madSTORM.</li>
	</ol>
	</li>
</ol>
2. Drift Correction and Alignment of Multiplexed Image Stacks
<ol>
	<li>Drift correction of madSTORM image stacks
	<ol>
		<li>Open images using ImageJ. We recommend converting the image files to a TIFF format before opening in ImageJ. Use rectangle ROI to select a single FND. Play the time lapse to make sure that the FND is visible in every frame of the image stack. Use Run Analysis in the ThunderSTORM plugin to localize the FND. For the averaged fiducial correction method described in 2.1.5, it is important that a single FND is localized in each image frame (i.e. number of identified peaks should be equal to the number of frames).</li>
		<li>If the FND is not identified in every frame, select another FND. If multiple peaks are located in a single frame, remove the peak that deviates the most from previous peaks.</li>
		<li>Repeat 2.1.2 for each FND in the image stack. Keep in mind that some FNDs should not be included in the drift correction process so they can serve as an independent gauge for drift correction precision as described in step 2.1.7.</li>
		<li>For faster, less precise drift correction, use either the cross correlation or fiducial correction algorithms included in ThunderSTORM to correct the FND images. Typically, we use 100 bins, 5 magnification, and 0.1 trajectory smoothing factor for cross correlation and 10 max distance, 0.1 min marker visibility ratio, and 0.01 trajectory smoothing factor for fiducial correction. Cross correlation and fiducial correction will yield a correction file which can be applied to other FNDs to test the drift correction precision.</li>
		<li>For more stringent, more precise drift correction, use the averaged fiducial correction (AFC) algorithm as described previously10. This process does not require optimization of parameters and yields higher localization precision than predicted by SMLM localization algorithms. However, averaged drift correction requires at least 4 FNDs and for the FNDs to be localized in every frame of the image stack. AFC drift correction performs better with inclusion of more FNDs because a large number of localized FNDs will lessen the distorting effect of an outlier peak in a given frame.</li>
		<li>Localize all point spread functions within the image stack using ThunderSTORM as described previously10. We typically use pixel size of 100 nm, photoelectrons per A/D count of 4.28, base level A/D count of 100, EM gain of 100, PSF: Integrated Gaussian localization, 5 pixel fitting radius, maximum likelihood fitting method, and 1.3 pixel initial sigma.</li>
		<li>Apply the drift correction factor acquired from FNDs to localizations from the entire image stack. Visually inspect the final image to ensure proper drift correction (Figure 2). The resulting drift correction factor should be independently tested on FNDs not included in the AFC procedure to measure the level of drift correction precision. The precision of drift-corrected, independent FNDs should be close to the average precision/uncertainty value calculated from the localization algorithm utilized in step 2.1.6.</li>
		<li>Repeat steps 2.1.1-2.1.7 for the madSTORM image stacks of sequentially labeled antibodies. Keep in mind, that localizing the same set of FNDs in each madSTORM image stack is critical for the following alignment procedure.</li>
	</ol>
	</li>
	<li>Alignment of madSTORM images
	<ol>
		<li>Calculate the centroid position of the drift corrected FNDs in each madSTORM image. To do this, find the mean x and y axis positions for each localized FND, and average the mean x and y positions of all FNDs in each madSTORM image. The detailed algorithm for this step has been described previously10. Align sequential madSTORM images using the centroid positions of FND fiducial markers. To perform the alignment, calculate the offset between two localized madSTORM images by subtracting the centroid position of FNDs in the second madSTORM image from the first. Then subtract the offset amount from all localizations in the second madSTORM image.</li>
		<li>We recommend using the first madSTORM image as a reference image and to repeat this alignment step between the first and third, first and fourth, etc. Test the alignment precision by measuring the offset between FNDs not included in the alignment process. Large offsets may indicate that different sets of FNDs were used when calculating the centroid positions of sequential madSTORM images.</li>
		<li>If so, steps 2.2.1-2.2.2 should be repeated using the same set of FNDs to perform alignment. 
		NOTE: Custom codes for both the AFC drift correction and alignment procedures are provided.</li>
	</ol>
	</li>
</ol>

<ol>
	<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>Hess, S. T., Girirajan, T. P., Mason, M. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultra-high+resolution+imaging+by+fluorescence+photoactivation+localization+microscopy.">Ultra-high resolution imaging by fluorescence photoactivation localization microscopy.</a> Biophys J. 91 (11), 4258-4272 (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> Nat Methods. 3 (10), 793-795 (2006).</li><li>van de Linde, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Direct+stochastic+optical+reconstruction+microscopy+with+standard+fluorescent+probes.">Direct stochastic optical reconstruction microscopy with standard fluorescent probes.</a> Nat Protoc. 6 (7), 991-1009 (2011).</li><li>Mortensen, K. I., Churchman, L. S., Spudich, J. A., Flyvbjerg, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimized+localization+analysis+for+single-molecule+tracking+and+super-resolution+microscopy.">Optimized localization analysis for single-molecule tracking and super-resolution microscopy.</a> Nat Methods. 7 (5), 377-381 (2010).</li><li>Thompson, R. E., Larson, D. R., Webb, W. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Precise+nanometer+localization+analysis+for+individual+fluorescent+probes.">Precise nanometer localization analysis for individual fluorescent probes.</a> Biophys J. 82 (5), 2775-2783 (2002).</li><li>Rieger, B., Stallinga, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+lateral+and+axial+localization+uncertainty+in+super-resolution+light+microscopy.">The lateral and axial localization uncertainty in super-resolution light microscopy.</a> Chemphyschem. 15 (4), 664-670 (2014).</li><li>Pertsinidis, A., Zhang, Y., Chu, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Subnanometre+single-molecule+localization,+registration+and+distance+measurements.">Subnanometre single-molecule localization, registration and distance measurements.</a> Nature. 466 (7306), 647-651 (2010).</li><li>Bates, M., Jones, S. A., 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=Stochastic+optical+reconstruction+microscopy+(STORM):+a+method+for+superresolution+fluorescence+imaging.">Stochastic optical reconstruction microscopy (STORM): a method for superresolution fluorescence imaging.</a> Cold Spring Harb Protoc. (6), 498-520 (2013).</li><li>Yi, J., 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=madSTORM:+a+superresolution+technique+for+large-scale+multiplexing+at+single-molecule+accuracy.">madSTORM: a superresolution technique for large-scale multiplexing at single-molecule accuracy.</a> Mol Biol Cell. 27 (22), 3591-3600 (2016).</li><li>Bates, M., Huang, B., Dempsey, G. T., 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=Multicolor+super-resolution+imaging+with+photo-switchable+fluorescent+probes.">Multicolor super-resolution imaging with photo-switchable fluorescent probes.</a> Science. 317 (5845), 1749-1753 (2007).</li><li>Dempsey, G. T., Vaughan, J. C., Chen, K. H., 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=Evaluation+of+fluorophores+for+optimal+performance+in+localization-based+super-resolution+imaging.">Evaluation of fluorophores for optimal performance in localization-based super-resolution imaging.</a> Nat Methods. 8 (12), 1027-1036 (2011).</li><li>Erdelyi, 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=Correcting+chromatic+offset+in+multicolor+super-resolution+localization+microscopy.">Correcting chromatic offset in multicolor super-resolution localization microscopy.</a> Opt Express. 21 (9), 10978-10988 (2013).</li><li>Gerdes, M. J., 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=Highly+multiplexed+single-cell+analysis+of+formalin-fixed,+paraffin-embedded+cancer+tissue.">Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue.</a> Proc Natl Acad Sci U S A. 110 (29), 11982-11987 (2013).</li><li>Jungmann, R., 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=Multiplexed+3D+cellular+super-resolution+imaging+with+DNA-PAINT+and+Exchange-PAINT.">Multiplexed 3D cellular super-resolution imaging with DNA-PAINT and Exchange-PAINT.</a> Nat Methods. 11 (3), 313-318 (2014).</li><li>Nanguneri, S., Flottmann, B., Horstmann, H., Heilemann, M., Kuner, T. <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+tomographic+super-resolution+fluorescence+imaging+of+serially+sectioned+thick+samples.">Three-dimensional tomographic super-resolution fluorescence imaging of serially sectioned thick samples.</a> PLoS One. 7 (5), e38098 (2012).</li><li>Schubert, W., 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=Analyzing+proteome+topology+and+function+by+automated+multidimensional+fluorescence+microscopy.">Analyzing proteome topology and function by automated multidimensional fluorescence microscopy.</a> Nat Biotechnol. 24 (10), 1270-1278 (2006).</li><li>Tam, J., Cordier, G. A., Borbely, J. S., Sandoval Alvarez, A., Lakadamyali, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cross-talk-free+multi-color+STORM+imaging+using+a+single+fluorophore.">Cross-talk-free multi-color STORM imaging using a single fluorophore.</a> PLoS One. 9 (7), e101772 (2014).</li><li>Valley, C. C., Liu, S., Lidke, D. S., Lidke, K. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sequential+superresolution+imaging+of+multiple+targets+using+a+single+fluorophore.">Sequential superresolution imaging of multiple targets using a single fluorophore.</a> PLoS One. 10 (4), e0123941 (2015).</li><li>Hoebe, R. 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=Controlled+light-exposure+microscopy+reduces+photobleaching+and+phototoxicity+in+fluorescence+live-cell+imaging.">Controlled light-exposure microscopy reduces photobleaching and phototoxicity in fluorescence live-cell imaging.</a> Nat Biotechnol. 25 (2), 249-253 (2007).</li><li>Kiuchi, T., Higuchi, M., Takamura, A., Maruoka, M., Watanabe, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multitarget+super-resolution+microscopy+with+high-density+labeling+by+exchangeable+probes.">Multitarget super-resolution microscopy with high-density labeling by exchangeable probes.</a> Nat Methods. 12 (8), 743-746 (2015).</li><li>Campi, G., Varma, R., Dustin, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Actin+and+agonist+MHC-peptide+complex-dependent+T+cell+receptor+microclusters+as+scaffolds+for+signaling.">Actin and agonist MHC-peptide complex-dependent T cell receptor microclusters as scaffolds for signaling.</a> J Exp Med. 202 (8), 1031-1036 (2005).</li><li>Sarkar, S. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wide-field+in+vivo+background+free+imaging+by+selective+magnetic+modulation+of+nanodiamond+fluorescence.">Wide-field in vivo background free imaging by selective magnetic modulation of nanodiamond fluorescence.</a> Biomed Opt Express. 5 (4), 1190-1202 (2014).</li></ol>

We have nothing to disclose.

The sequential multiplexing, drift correction, and alignment procedures in madSTORM allow precise, highly multiplexed visualization of heterogenous structures in cells.10 In addition, madSTORM avoids the limitations of multi-color STORM such as chromatic aberration and sub-optimal photoswitching/emission properties of non-far red dyes9,12. As the elution step significantly reduces steric interference from sequentially bound antibodies, mad...

A variety of super-resolution microscopy techniques have been developed to overcome the diffraction limit of light microscopy (~200 nm). Among these is a category of techniques called single molecule localization microscopy (SMLM) which includes photo-activation localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM). SMLM techniques share in the use of fluorophores that can be switched between on (fluorescent) and off (dark/photo-switched) states, allowing sequential localization of fluorescence from single molecules1,2,3.
Due to its compatibility with commercially available dyes and microscopes, direct STORM (dSTORM) has become a widely adopted SMLM technique4. dSTORM can routinely achieve ~10 nm localization precision, defined as the uncertainty in calculating the center of a diffraction-limited point spread function (PSF). However, despite the high precision estimated using localization algorithms5,6,7, accurate determination of the actual location of single molecules has been hampered by a number of issues. First, mechanical movement of the microscope stage during image acquisition adds significant uncertainty to localization precision. As SMLM images are obtained over thousands of time-lapse frames, nano-scale movements of the microscope stage can significantly compromise the precision of the final super-resolution image8. To compensate for stage movement during image acquisition, stage drift is commonly estimated from regression-based fitting of binned localizations from the image itself (cross correlation) or sequential localizations from fiducial markers (fiducial correction)1,9. However, these methods require optimization of multiple parameters for each image stack, and cannot account for stage movements at short time scales such as mechanical vibration. Gold nano-particles and multi-color fluorescent beads have been used as fiducial markers in SMLM, but they are not photo-stable, and result in significantly lower precision after drift correction than the nitrogen vacancy-center fluorescent nano-diamonds (FNDs) used in madSTORM10.
In addition to the diffraction limit, light microscopy is further restricted by spectral limits. Simultaneous visualization of multiple targets requires fluorescent probes with non-overlapping spectral profiles, generally restricting fluorescence-based light microscopy to 6 colors and SMLM to 2-3 colors4,11,12. Moreover, non-linear chromatic aberration causes misalignment of multicolor images, which require extensive alignment procedures using multi-colored fiducial markers8,13. To overcome these limits, previous studies have imaged multiple targets using repetitive photobleaching or chemical quenching of sequentially bound fluorophores14,15,16,17,18,19. While these methods can overcome the spectral limits of microscopy, fluorescence bleaching is known to be a toxic process20, and prolonged bleaching or quenching may cause unwanted side effects such as loss of crosslinking. Furthermore, the accumulation of fluorescent probes could lead to steric blocking of binding sites in the sample, preventing large-scale multiplexing and robust targeting of epitopes. To avoid such steric interference, a recent study achieved multiplexing using stochastic exchange of freely diffusing protein fragments21. Whereas this method allows dense labeling of cellular structures, it requires extensive biochemical preparation to isolate peptide fragments, cannot locate single molecule positions, and does not readily facilitate large-scale multiplexing using commercially available probes. We present a detailed video protocol describing the sequential binding and elution of fluorescently antibodies for multiplexed, antibody size-limited dSTORM (madSTORM) imaging, and use of fluorescent nano-diamonds to achieve precise drift correction and alignment.

<table border="0" cellpadding="0" cellspacing="0" width="598">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:269px;">8 well coverslip chamber</td>
			<td style="width:117px;">Lab-tek</td>
			<td style="width:124px;">155409</td>
			<td style="width:88px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">0.1% Poly-L-Lysine solution</td>
			<td>Sigma-Aldrich</td>
			<td>P8920</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">NV-100nm Fluorescent Nano-diamond</td>
			<td>Adamas</td>
			<td>Red FND</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">anti-CD3&#949; antibody</td>
			<td>BD Biosciences</td>
			<td>555329</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Bovine serum albumin, Fraction V</td>
			<td>KSE Scientific</td>
			<td>98-100P</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Triton-X</td>
			<td>Sigma-Aldrich</td>
			<td>T9284</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">10% Paraformaldehyde</td>
			<td>EMS</td>
			<td>15712</td>
			<td>Carcinogen</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Gelatin from fresh water fish skin</td>
			<td>Sigma-Aldrich</td>
			<td>G7041</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Alexa 647 antibody labeling kit</td>
			<td>Thermo Fisher</td>
			<td>A20186</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Magnesium Chloride hexahydrate</td>
			<td>Sigma-Aldrich</td>
			<td>138924</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PIPES</td>
			<td>Sigma-Aldrich</td>
			<td>P6757</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Tween-20</td>
			<td>Fisher Scientific</td>
			<td>BP337-500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">2-Mercaptoethanol</td>
			<td>Sigma-Aldrich</td>
			<td>M7154</td>
			<td>Highly toxic, air sensitive</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Cysteamine</td>
			<td>Sigma-Aldrich</td>
			<td>30070</td>
			<td>Highly toxic&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Cyclooctatetraene 98%</td>
			<td>Sigma-Aldrich</td>
			<td>138924</td>
			<td>Highly toxic, air sensitive</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">10x PBS</td>
			<td>KD Medical</td>
			<td>RGF-3210</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">10x TBS</td>
			<td>KD Medical</td>
			<td>RGF-3385</td>
			<td></td>
		</tr>
	</tbody>
</table>

highly multiplexed, super-resolution imaging of t cells using madstorm

Imaging heterogeneous cellular structures using single molecule localization microscopy has been hindered by inadequate localization precision and multiplexing ability. Using fluorescent nano-diamond fiducial markers, we describe the drift correction and alignment procedures required to obtain high precision in single molecule localization microscopy. In addition, a new multiplexing strategy, madSTORM, is described in which multiple molecules are targeted in the same cell using sequential binding and elution of fluorescent antibodies. madSTORM is demonstrated on an activated T cell to visualize the locations of different components within a membrane-bound, multi-protein structure called the T cell receptor microcluster. In addition, application of madSTORM as a general tool for visualization of multi-protein structures is discussed.

The sequential elution and staining method was used to produce the multiplexed madSTORM image of microclusters and other structures in an activated Jurkat T cell (Figure 1, check figure alignments). Each pseudo-colored image represents one round of madSTORM imaging acquired in steps 1.1.1 to 1.3.13. As described previously10, the field of view should be monitored for residual signal from previous, non-eluted antibody to avoid crosstalk...

Watch this Scientific Journal Video about Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM at JoVE.com

Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM

We demonstrate a method to image multiple molecules within heterogeneous nano-structures at single molecule accuracy using sequential binding and elution of fluorescently labeled antibodies.

Imaging heterogeneous cellular structures using single molecule localization microscopy has been hindered by inadequate localization precision and ...

highly-multiplexed-super-resolution-imaging-of-t-cells-using-madstorm

Research

JoVE Journal

Immunology and Infection

7.3K Views.  National Institutes of Health. We demonstrate a method to image multiple molecules within heterogeneous nano-structures at single molecule accuracy using sequential binding and elution of fluorescently labeled antibodies.

Video: Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM

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 ...

Ex vivo Imaging of T Cells in Murine Lymph Node Slices with Widefield and Confocal Microscopes

Na&iuml;ve T cells continuously traffic to secondary lymphoid organs, including peripheral lymph nodes, to detect rare expressed antigens. The migration of T cells into lymph nodes is a complex process which involves both cellular and chemical factors including chemokines. Recently, the use of two-photon microscopy has permitted to track T cells in intact lymph nodes and to derive some quantitative information on their behavior and their interactions with other cells. While there are obvious advantages to an in vivo system, this approach requires a complex and expensive instrumentation and provides limited access to the tissue. To analyze the behavior of T cells within murine lymph nodes, we have developed a slice assay 
1, originally set up by neurobiologists and transposed recently to murine thymus 2. In this technique, fluorescently labeled T cells are plated on top of an acutely prepared lymph node slice. In this video-article, the localization and migration of T cells into the tissue are analyzed in real-time with a widefield and a confocal microscope. The technique which complements in vivo two-photon microscopy offers an effective approach to image T cells in their natural environment and to elucidate mechanisms underlying T cell migration.

Ex vivo Imaging of T Cells in Murine Lymph Node Slices with Widefield and Confocal Microscopes

This protocol describes a method to image fluorescent T cells introduced into lymph node slices. The technique permits real-time analyses of T cell migration with traditional widefield fluorescence or confocal microscopes.

Na&iuml;ve T cells continuously traffic to secondary lymphoid organs, including peripheral lymph nodes, to detect rare expressed antigens. The migration ...

Expansion of Human Peripheral Blood  &gamma;&delta; T Cells using Zoledronate

Human &gamma;&delta; T cells can recognize and respond to a wide variety of stress-induced antigens, thereby developing innate broad anti-tumor and anti-infective activity.1 The majority of &gamma;&delta; T cells in peripheral blood have the V&gamma;9V&delta;2 T cell receptor. These cells recognize antigen in a major histocompatibility complex-independent manner and develop strong cytolytic and Th1-like effector functions.1Therefore, &gamma;&delta; T cells are attractive candidate effector cells for cancer immunotherapy. V&gamma;9V&#x03B4;2 T cells respond to phosphoantigens such as (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate (HMBPP), which is synthesized in bacteria via isoprenoid biosynthesis;2 and isopentenyl pyrophosphate (IPP), which is produced in eukaryotic cells through the mevalonate pathway.3 In physiological condition, the generation of IPP in nontransformed cell is not sufficient for the activation of &gamma;&delta; T cells. Dysregulation of mevalonate pathway in tumor cells leads to accumulation of IPP and &gamma;&delta; T cells activation.3 Because aminobisphosphonates (such as pamidronate or zoledronate) inhibit farnesyl pyrophosphate synthase (FPPS), the enzyme acting downstream of IPP in the mevalonate pathway, intracellular levels of IPP and sensitibity to &gamma;&delta; T cells recognition can be therapeutically increased by aminobisphosphonates. IPP accumulation is less efficient in nontransfomred cells than tumor cells with a pharmacologically relevant concentration of aminobisphosphonates, that allow us immunotherapy for cancer by activating &gamma;&delta; T cells with aminobisphosphonates. 4 Interestingly, IPP accumulates in monocytes when PBMC are treated with aminobisphosphonates, because of efficient drug uptake by these cells. 5 Monocytes that accumulate IPP become antigen-presenting cells and stimulate V&gamma;9V&delta;2 T cells in the peripheral blood.6 Based on these mechanisms, we developed a technique for large-scale expansion of &gamma;&delta; T cell cultures using zoledronate and interleukin-2 (IL-2).7 Other methods for expansion of &gamma;&delta; T cells utilize the synthetic phosphoantigens bromohydrin pyrophosphate (BrHPP)8 or 2-methyl-3-butenyl-1-pyrophosphate (2M3B1PP).9 All of these methods allow ex vivo expansion, resulting in large numbers of &gamma;&delta; T cells for use in adoptive immunotherapy. However, only zoledronate is an FDA-approved commercially available reagent. Zoledronate-expanded &gamma;&delta; T cells display CD27-CD45RA- effector memory phenotype and thier function can be evaluated by IFN-&gamma; production assay. 7

Expansion of Human Peripheral Blood  &#947;&#948; T Cells using Zoledronate

A method to expand &gamma;&delta; T cells from peripheral blood mononuclear cells (PBMC) is described. PBMC-derived &gamma;&delta; T cells are stimulated and expanded using zoledronate and interleukin-2 (IL-2). Large scale expansion of &gamma;&delta; T cells can be applied to autologous cellular immunotherapy of cancer.

Human &gamma;&delta; T cells can recognize and respond to a wide variety of stress-induced antigens, thereby developing innate broad anti-tumor and ...

Generation of Induced Regulatory T Cells from Primary Human Na&iuml;ve and Memory T Cells

The development and maintenance of immunosuppressive CD4+ regulatory T cells (Tregs) contribute to the peripheral tolerance needed to remain in immunologic homeostasis with the vast amount of self and commensal antigens in and on the human body. Perturbations in the balance between Tregs and inflammatory conventional T cells can result in immunopathology or cancer. Although therapeutic injection of Tregs has been shown to be efficacious in murine models of colitis1 , type I diabetes2 , rheumatoid arthritis and graft versus host disease,4 several fundamental differences in human versus mouse Treg biology5 has thus far precluded clinical use. The lack of sufficient number, purity, stability and homing specificity of therapeutic Tregs necessitated a dynamic platform of human Treg development on which to optimize conditions for their ex vivo expansion6.
Here we describe a method for the differentiation of induced Tregs (iTregs) from a single human peripheral blood donor which can be broken down into four stages: isolation of peripheral blood mononuclear cells, magnetic selection of CD4+ T cells, in vitro cell culture and fluorescence activated cell sorting (FACS) of T cell subsets. Since the Treg signature transcription factor forkhead box P3 (FoxP3) is an activation-induced transcription factor in humans7 and no other unique marker exists, a combinatorial panel of markers must be used to identify T cells with suppressor activity. After six days in culture, cells in our system can be demarcated into na&iuml;ve T cells, memory T cells or iTregs based on their relative expression of CD25 and CD45RA. As memory and na&iuml;ve T cells have different reported polarization requirements and plasticities8 , pre-sorting of the initial T cell population into CD45RA+ and CD45RO+ subsets can be used to examine these discrepancies. Consistent with others, our CD25HiCD45RA- iTregs express high levels of FoxP39 , GITR and CTLA-411 and low levels of CD12712 . Following FACS of each population, resultant cells can be used in a suppressor assay which evaluates the relative ability to retard the proliferation of carboxyfluorescein succinimidyl ester (CFSE)-labeled autologous T cells.

Generation of Induced Regulatory T Cells from Primary Human Na&#239;ve and Memory T Cells

We describe a method for generating regulatory, memory and na&#239;ve T cells from a single human blood donor. Polarized Tregs can be then compared to other subsets in a variety of genetic and functional applications with genetic homogeneity, including a suppression assay also detailed here.

The development and maintenance of immunosuppressive CD4+ regulatory T cells (Tregs) contribute to the peripheral tolerance needed to remain in ...

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 ...

Averaging of Viral Envelope Glycoprotein Spikes from Electron Cryotomography Reconstructions using Jsubtomo

Enveloped viruses utilize membrane glycoproteins on their surface to mediate entry into host cells. Three-dimensional structural analysis of these glycoprotein &#8216;spikes&#8217; is often technically challenging but important for understanding viral pathogenesis and in drug design. Here, a protocol is presented for viral spike structure determination through computational averaging of electron cryo-tomography data. Electron cryo-tomography is a technique in electron microscopy used to derive three-dimensional tomographic volume reconstructions, or tomograms, of pleomorphic biological specimens such as membrane viruses in a near-native, frozen-hydrated state. These tomograms reveal structures of interest in three dimensions, albeit at low resolution. Computational averaging of sub-volumes, or sub-tomograms, is necessary to obtain higher resolution detail of repeating structural motifs, such as viral glycoprotein spikes. A detailed computational approach for aligning and averaging sub-tomograms using the Jsubtomo software package is outlined. This approach enables visualization of the structure of viral glycoprotein spikes to a resolution in the range of 20-40 &#197; and study of the study of higher order spike-to-spike interactions on the virion membrane. Typical results are presented for Bunyamwera virus, an enveloped virus from the family Bunyaviridae. This family is a structurally diverse group of pathogens posing a threat to human and animal health.

An approach is presented for determining structures of viral membrane glycoprotein complexes using a combination of electron cryo-tomography and sub-tomogram averaging with the computational package Jsubtomo.

Enveloped viruses utilize membrane glycoproteins on their surface to mediate entry into host cells. Three-dimensional structural analysis of these ...

Super-resolution Imaging of the Natural Killer Cell Immunological Synapse on a Glass-supported Planar Lipid Bilayer

The glass-supported planar lipid bilayer system has been utilized in a variety of disciplines. One of the most useful applications of this technique has been in the study of immunological synapse formation, due to the ability of the glass-supported planar lipid bilayers to mimic the surface of a target cell while forming a horizontal interface. The recent advances in super-resolution imaging have further allowed scientists to better view the fine details of synapse structure. In this study, one of these advanced techniques, stimulated emission depletion (STED), is utilized to study the structure of natural killer (NK) cell synapses on the supported lipid bilayer. Provided herein is an easy-to-follow protocol detailing: how to prepare raw synthetic phospholipids for use in synthesizing glass-supported bilayers; how to determine how densely protein of a given concentration occupies the bilayer's attachment sites; how to construct a supported lipid bilayer containing antibodies against NK cell activating receptor CD16; and finally, how to image human NK cells on this bilayer using STED super-resolution microscopy, with a focus on distribution of perforin positive lytic granules and filamentous actin at NK synapses. Thus, combining the glass-supported planar lipid bilayer system with STED technique, we demonstrate the feasibility and application of this combined technique, as well as intracellular structures at NK immunological synapse with super-resolution.

We describe here a combination of the glass-supported lipid bilayer technique of forming immunological synapses with the super-resolution imaging technique of stimulated emission depletion (STED) microscopy. The goal of this protocol is to provide users with the instructions necessary to successfully carry out these two techniques.

The glass-supported planar lipid bilayer system has been utilized in a variety of disciplines. One of the most useful applications of this technique has ...

Analysis of Yersinia enterocolitica Effector Translocation into Host Cells Using Beta-lactamase Effector Fusions

Many gram-negative bacteria including pathogenic Yersinia spp. employ type III secretion systems to translocate effector proteins into eukaryotic target cells. Inside the host cell the effector proteins manipulate cellular functions to the benefit of the bacteria. To better understand the control of type III secretion during host cell interaction, sensitive and accurate assays to measure translocation are required. We here describe the application of an assay based on the fusion of a Yersinia enterocolitica effector protein fragment (Yersinia outer protein; YopE) with TEM-1 beta-lactamase for quantitative analysis of translocation. The assay relies on cleavage of a cell permeant FRET dye (CCF4/AM) by translocated beta-lactamase fusion. After cleavage of the cephalosporin core of CCF4 by the beta-lactamase, FRET from coumarin to fluorescein is disrupted and excitation of the coumarin moiety leads to blue fluorescence emission. Different applications of this method have been described in the literature highlighting its versatility. The method allows for analysis of translocation in vitro and also in in vivo, e.g., in a mouse model. Detection of the fluorescence signals can be performed using plate readers, FACS analysis or fluorescence microscopy. In the setup described here, in vitro translocation of effector fusions into HeLa cells by different Yersinia mutants is monitored by laser scanning microscopy. Recording intracellular conversion of the FRET reporter by the beta-lactamase effector fusion in real-time provides robust quantitative results. We here show exemplary data, demonstrating increased translocation by a Y. enterocolitica YopE mutant compared to the wild type strain.

Analysis of Yersinia enterocolitica Effector Translocation into Host Cells Using Beta-lactamase Effector Fusions

Effector translocation into host cells via a type III secretion system is a common virulence strategy among gram-negative bacteria. A beta-lactamase effector fusion based assay for quantitative analysis of translocation was applied. In Yersinia infected cells, conversion of a FRET reporter by the beta-lactamase is monitored using laser scanning microscopy.

Many gram-negative bacteria including pathogenic Yersinia spp. employ type III secretion systems to translocate effector proteins into eukaryotic target ...

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.

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 ...

In Vitro Differentiation of Human CD4+FOXP3+ Induced Regulatory T Cells (iTregs) from Na&#239;ve CD4+ T Cells Using a TGF-&#946;-containing Protocol

Regulatory T cells (Tregs) are an integral part of peripheral tolerance, suppressing immune reactions against self-structures and thus preventing autoimmune diseases. Clinical approaches to adoptively transfer Tregs, or to deplete Tregs in cancer, are underway with promising first outcomes. 
Because the number of naturally occurring Tregs (nTregs) is very limited, studying certain Treg features using in vitro induced Tregs (iTregs) can be advantageous. To date, the best although not absolutely specific protein marker to delineate Tregs is the transcription factor FOXP3. Despite the importance of Tregs including non-redundant roles of peripherally induced Tregs, the protocols to generate iTregs are currently controversial, particularly for human cells. This protocol therefore describes the in vitro differentiation of human CD4+FOXP3+ iTregs from human na&#239;ve T cells using a range of Treg-inducing factors (TGF-&#946; plus IL-2 only, or their combination with retinoic acid, rapamycin or butyrate) in parallel. It also describes the phenotyping of these cells by flow cytometry and qRT-PCR. 
These protocols result in reproducible expression of FOXP3 and other Treg signature genes and enable the study of general FOXP3-regulatory mechanisms as well as protocol-specific effects to delineate the impact of certain factors. iTregs can be utilized to study various phenotypic aspects as well as molecular mechanisms of Treg induction. Detailed molecular studies are facilitated by relatively large cell numbers that can be obtained. 
A limitation for the application of iTregs is the relative instability of FOXP3 expression in these cells compared to nTregs. iTregs generated by these protocols can also be used for functional assays such as studying their suppressive function, in which iTregs induced by TGF-&#946; plus retinoic acid and rapamycin display superior suppressive activity. However, the suppressive capacity of iTregs can differ from nTregs and the use of appropriate controls is crucial.

This protocol describes the reproducible generation and phenotyping of human induced regulatory T cells (iTregs) from na&#239;ve CD4+ T cells in vitro. Different protocols for FOXP3 induction allow for the study of specific iTreg phenotypes obtained with respective protocols.