BM is supported by a Cancer Research UK PhD studentship. AG is supported by a Life Science Research Network Wales PhD studentship. VB is supported by a Cancer Research Wales PhD studentship. DKC is a Wellcome Trust Research Career Development Fellow (WT095767). AKS is a Wellcome Trust Investigator. GHM is funded by a joint Life Science Research Network Wales and Tenovus Cancer Care PhD Studentship. We thank the staff at Diamond Light Source for providing facilities and support.

1. Protein Expression
<ol>
	<li>Make gene constructs for the generation of soluble TCRs and pHLAs, as described in detail previously17,18. Design each construct with a 5&#39; BamH1 and a 3&#39; EcoR1 restriction site for insertion into the pGMT7 vector.</li>
	<li>Transform E. coli Rosetta (DE3)pLysS with a pGMT7-derived plasmid vector containing the sequence encoding the protein of interest by incubating 1 &#181;L of 50-200 ng/&#181;L plasmid with 5 &#181;L of E.coli for 5 min at 4 &#176;C, 2 min at 42 &#176;C, and 5 min at 4 &#176;C, and plate out overnight at 37 &#176;C on an LB agar plate supplemented with 50 mg/L carbenicillin.</li>
	<li>Pick individual colonies and grow at 37 &#176;C and 220 rpm in 30 mL of TYP media (16 g/L tryptone, 16 g/L yeast extract, and 5 g/L HK2O4) supplemented with 100 &#181;M carbenicillin until the suspension reaches an optical density (OD600) of between 0.4 and 0.6.</li>
	<li>Induce protein production in a 5 mL aliquot by introducing 0.5 mM isopropyl &#946;-D-1-thiogalactopyranoside (IPTG) for 3 h. Keep 20 &#181;L of suspension with and without induction for sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis and stain the gel.</li>
	<li>Add starter cultures to 1 L of TYP supplemented with 100 &#181;M carbenicillin and grow cells as described above in step 1.3 until the suspension reaches an OD600 between 0.4 and 0.6.</li>
	<li>Induce protein expression for 3 h with 0.5 mM IPTG. Centrifuge the cells for 20 min at 3,000 x g and pour off the supernatant carefully.</li>
	<li>Dissolve the pellet in 40 mL of lysis buffer (10 mM Tris, pH 8.1; 10 mM magnesium chloride, MgCl2; 150 mM NaCl; and 10% glycerol), sonicate on ice for 30 min at 60% power using a 2 s interval, and incubate at room temperature (RT) for 30 min with 0.1 g/L DNase.</li>
	<li>Treat the suspension containing the proteins in the form of inclusion bodies (IB) with 100 mL of wash buffer (0.5% Triton X-100; 50 mM Tris, pH 8.1; 100 mM NaCl; and 10 mM EDTA).</li>
	<li>Centrifuge the sample for 20 min at 4 &#176;C and 8,000 x g and pour off the supernatant carefully. Re-suspend the pellet in 100 mL of re-suspension buffer (50 mM Tris, pH 8.1; 100 mM NaCl; and 10 mM EDTA, pH 8.1), centrifuge as before at 8,000 x g, and pour off the supernatant carefully.</li>
	<li>Finally, dissolve the pellet in 10 mL of guanidine buffer (6 M guanidine; 50 mM Tris, pH 8.1; 2 mM EDTA, pH 8.1; and 100 mM NaCl) and measure the protein concentration at 280 nm using a spectrophotometer.</li>
</ol>
2. pHLA and TCR Refolding
<ol>
	<li>For the pHLA refolds, mix 30 mg of HLA-A2 (or HLA-A2 with a biotin tag) IBs, 30 mg of &#946;2m IBs, and 4 mg of peptide for 30 min at 37 &#176;C in a water bath in a final volume of 6 mL of guanidine buffer supplemented with 10 mM dithiothreitol (DTT).</li>
	<li>Initiate protein refolding by diluting the previous mix in 1 L of a pre-chilled HLA refold buffer (50 mM Tris, pH 8.1; 400 mM L-arginine; 2 mM EDTA, pH 8.1; 6 mM cysteamine; and 4 mM cystamine).</li>
	<li>Leave the HLA refold stirring at 4 &#176;C for 3 h and then transfer it into a 12.4 kDa MWCO (molecular weight cut-off) dialysis tube and dialyze twice for 24 h against 20 L of 10 mM Tris, pH 8.1.</li>
	<li>For the TCR refolds, mix 30 mg of TCR &#945; chain IBs and 30 mg of TCR &#946; chain IBs for 30 min at 37 &#176;C in a water bath in 6 mL of guanidine buffer supplemented with 10 mM DTT.</li>
	<li>Initiate protein refolding by diluting the denatured TCR mixture in 1 L of a pre-chilled TCR refold buffer (50 mM Tris, pH 8.1; 2.5 M urea; 2 mM EDTA, pH 8.1; 6 mM cysteamine; and 4 mM cystamine) for 3 h.</li>
	<li>Transfer the refold into a 12.4-kDa MWCO dialysis tube and dialyze twice for 24 h against 20 L of 10 mM Tris, pH 8.1.</li>
	<li>Filter both the pHLA or TCR refolds using a 0.45-&#181;m membrane filter for the purification steps.</li>
</ol>
3. Purification by Fast Protein Liquid Chromatography (FPLC)
<ol>
	<li>Load the filtered refold preparation (either pHLA or TCR) onto a 7.9 mL, 50 &#181;m anion exchange resin column pre-equilibrated with 20 mL of 10 mM Tris, pH 8.1 on a flexible and intuitive chromatography system.</li>
	<li>Elute the protein at 5 mL/min with a salt gradient (0-500 mM NaCl in 10 mM Tris, pH 8.1, over 8 column volumes) and collect 1-mL fractions.</li>
	<li>Analyze the fractions corresponding to the protein of interest by SDS-PAGE, pool the fractions containing the protein of interest together, and concentrate them down to 500 &#181;L with 10-kDa MWCO 20 or 10 kDa MWCO 4 by centrifugation for 20 min at 4,000 x g, discarding the flow-through.</li>
	<li>Load the concentrated protein preparations into a 2 mL injection loop onto a 24 mL size exclusion chromatography column pre-equilibrated with the appropriate elution buffer: phosphate-buffered saline (PBS), HBS (10 mM HEPES, pH 7.4; 150 mM NaCl; 3.4 mM EDTA; and 0.005% surfactant), or crystal buffer (10 mM Tris, pH 8.1, and 10 mM NaCl).</li>
	<li>Elute the proteins at a flow-rate of 0.5 mL/min over 1 column volume; collect 1 mL fractions containing the protein of interest verified by SDS-PAGE. 
	NOTE: These methods were used to generate soluble PMEL17 TCR and gp100 TCRs, as well as all of the pHLAs used in this study: HLA-A*0201 with YLEPGPVTA (A2-YLE), YLEPGPVTV (A2-YLE-9V), ALEPGPVTA (A2-YLE-1A), YLAPGPVTA (A2-YLE-3A), YLEAGPVTA (A2-YLE-4A), YLEPAPVTA (A2-YLE-5A), YLEPGAVTA (A2-YLE-6A), YLEPGPATA (A2-YLE-7A), or YLEPGPVAA (A2-YLE-8A).</li>
</ol>
4. Surface Plasmon Resonance (SPR) Analysis
<ol>
	<li>Perform equilibrium-binding analysis or thermodynamic analysis using a molecular interaction analysis system equipped with a CM5 sensor chip19.</li>
	<li>Activate the CM5 chip by flowing a 1:1 mix of 100 mM N-hydroxysuccinimide (NHS) and 400 mM 1-ethyl-3-(3-dimethylpropyl)-carboiimide (EDC) for 10 min at a flow rate of 10 &#181;L/min and at 25 &#176;C.</li>
	<li>Load approximately 5,000 response units (RU) of streptavidin (110 &#181;L of 200 &#181;g/mL in 10 mM acetate, pH 4.5) by covalent linking to the chip surface in all four flow-cells and use 100 &#181;L of 1 M ethanolamine hydrochloride to deactivate any remaining reactive groups.</li>
	<li>Couple approximately 500-600 RU of pHLA, at ~1 &#181;M in commercial buffer (provided by the manufacturer), to the CM5 sensor chip at a slow flow-rate of 10 &#181;L/min to ensure uniform distribution on the chip surface.</li>
	<li>Saturate the chip surface with 1 mM biotin in commercial buffer (provided by the manufacturer) for 60 s.</li>
	<li>Inject ten serial dilutions of soluble TCRs over the relevant flow-cells at a high flow-rate of 30 &#181;L/min at 25 &#176;C.</li>
	<li>Calculate the equilibrium-binding constant (KD (E)) values using a nonlinear curve fit (y = (P1x)/(P2+x)) 20. 
	NOTE: y = response units, x = analyst concentration, P1 = rmax, P2 = KD.</li>
	<li>Perform kinetics analysis assuming a 1:1 Langmuir binding and fit the data using a global-fit algorithm in the software package2.</li>
	<li>Perform thermodynamics experiments by repeating this method at the following temperatures: 5 &#176;C, 12 &#176;C, 18 &#176;C, 25 &#176;C, and 30 &#176;C19.</li>
	<li>Use the KD values determined by SPR at different temperatures to calculate &#916;G&#176; using the standard thermodynamic equation (&#916;G&#176; = -RTlnKD)19. 
	NOTE: R = gas constant, T = temperature in K, ln = natural log.</li>
	<li>Calculate the thermodynamic parameters according to the Gibbs-Helmholtz equation (&#916;G&#176; = &#916;H &#8722; T&#916;S&#176;)19.</li>
	<li>Plot the binding free energies, &#916;G&#176; (&#916;G&#176; = -RTlnKD), against temperature (K) using a nonlinear regression to fit the three-parameter equation (y = &#916;H+&#916;Cp*(x-298)-x*&#916;S-x*&#916;Cp*ln(x/298))19. 
	NOTE: y = temperature in K, x = &#916;G&#176;.</li>
</ol>
5. Isothermal Titration Calorimetry (ITC)
<ol>
	<li>Perform ITC experiments using an isothermal titration calorimeter. Inject 30 &#181;M pHLA into the calorimeter cell and load 210 &#181;M soluble TCR into the syringe. Use the following buffer conditions: 20 mM Hepes (pH 7.4) containing 150 mM NaCl.</li>
	<li>Perform 20 TCR injections, each of a 2 &#181;L volume. Calculate &#916;H and KD using analytical software.</li>
</ol>
6. Crystallization, Diffraction Data Collection, and Model Refinement
<ol>
	<li>Perform crystallization trials using a crystallization robot.</li>
	<li>Grow crystals by vapor diffusion at 18 &#176;C via the sitting drop technique in a 96-well plate with a reservoir containing 60 &#181;L of crystallization buffer (mother liquor)21.</li>
	<li>Concentrate the soluble pHLA to approximately 10 mg/mL (0.2 mM) in crystal buffer by spinning at 3,000 x g in a 10-kda molecular weight cut-off centrifugal concentrator.</li>
	<li>For the co-complex structures, mix the TCR and pHLA at a 1:1 molar ratio to obtain a protein solution at approximately 10 mg/mL (0.1 mM).</li>
	<li>Add 200 nL of pHLA alone, or the 1:1 molar ratio mix of TCR and pHLA, to 200 nL of each reservoir solution from the crystallization screen using a crystallization robot and score for crystals under a microscope after 24 h, 48 h, 72 h, and then once a week.</li>
	<li>Harvest single crystals by manually mounting them in cryo-loops under a microscope and cryo-cool them by submerging and storing them in liquid nitrogen (100 K). 
	NOTE: Loading crystals takes a bit of practice, and deciding which crystals are good enough for data collection comes with experience. As a rule of thumb, the larger and more regular the crystal, the better.</li>
	<li>Collect data in a stream of nitrogen gas at 100 K. 
	NOTE: This data was acquired at the Diamond Light Source (DLS) national synchrotron science facility in the UK.</li>
	<li>Analyze the data by estimating the reflection intensities with xia2 using both MOSFLM22 and XDS packages23, and then scale the data with SCALA or AIMLESS 24 and the CCP4 package25.</li>
	<li>Solve the structures with molecular replacement using PHASER26.</li>
	<li>Adjust the model with COOT27 and refine the model with REFMAC528.</li>
	<li>Prepare graphical representations with PYMOL29.</li>
	<li>Calculate the contacts by using the &#34;contact&#34; program in the CCP4 package. Use a 4 &#197; cut-off for van der Waals contacts and a 3.4 &#197; cut-off for hydrogen bonds and salt bridges.</li>
	<li>Calculate surface complementarity using the &#34;SC&#34; program in the CCP4 package.</li>
	<li>Calculate the crossing angle of the TCR-pHLA complex, as described30. 
	NOTE: For this study, the reflection data and final model coordinates were deposited with the PDB database (PMEL17 TCR-A2-YLE-9V PDB: 5EU6, A2-YLE PDB: 5EU3, A2-YLE-3A PDB: 5EU4, and A2-YLE-5A PDB: 5EU5).</li>
</ol>

The authors have no conflicts of interest or competing financial interests.

The protocols outlined here provide a framework for the molecular and cellular dissection of T-cell responses in the context of any human disease. Although cancer was the main focus of this study, we have used very similar approaches to investigate T-cell responses to viruses32,33,34,35,36,37 and during autoimmunity38,39,40. Furthermore, we have used these techniques more broadly to understand the molecular principles that govern T-cell antigen recognition2,19,41,42. Indeed, the unpredictable nature of modifications to peptide residues, even those outside of the of the TCR contact residues, impacts T-cell recognition has important implications for the design of heteroclitic peptides. These findings have directly contributed to the development of novel T-cell therapies, including peptide vaccines6,43 and artificial high-affinity TCRs3,4,5,20,44, as well as of enhanced diagnostics45,46,47.
Critical steps within the protocol 
The generation of a highly pure, functional protein is essential for all of the methods outlined in this paper.
Modifications and troubleshooting 
Difficulties in generating highly pure protein often relate to the expression of highly-pure, insoluble IBs from the E. coli expression system. Usually, modifying the expression protocol (e.g., inducing at different optical densities, using different E. coli strains, or using different media formations) resolves these issues.
Limitations of the technique 
These techniques use soluble protein molecules (TCR and pHLA) that are normally expressed at the cell surface. Thus, it is important to ensure that structural/biophysical findings are consistent with cellular approaches to confirm biological significance.
Significance of the technique with respect to existing/alternative methods 
Through the use of X-ray crystallography and biophysics substantiated through functional analysis, we and others have demonstrated that TCRs specific for cancer epitopes are generally characterized by low binding affinities48. This low TCR affinity may help explain why T cells are not naturally effective at clearing cancer. High-resolution atomic structures of complexes between anti-cancer TCRs and cognate tumor antigens are starting to reveal the molecular basis for this weak affinity. Furthermore, these studies are helpful for determining the mechanisms that underlie the therapeutic interventions designed to overcome this issue, seeding future improvements16. In this study, we examined the first structure of a naturally-occurring &#945;&#946;TCR in complex with a gp100 HLA-A*0201-restricted melanoma epitope. The structure, combined with an in-depth biophysical examination, revealed the overall binding mode of the interaction. We also uncovered an unexpected molecular switch, which occurred in a mutated form of the peptide, that abrogated TCR binding (assessed using surface plasmon resonance) and CD8+ T-cell recognition (functional experiments). It was only possible to demonstrate this new mechanism of HLA antigen presentation using the high-resolution methods described.
Future applications or directions after mastering this technique 
Overall, our results demonstrate the power of X-ray crystallography and biophysical methods when combined with robust functional analyses. Using these approaches, it is possible to dissect out precise molecular mechanisms that govern T-cell antigen recognition. Indeed, it is also possible to use this approach to solve the structure of unligated TCRs, demonstrating how conformational changes can play a role during antigen discrimination49,50,51. A better understanding of the highly complex and dynamic nature that underpins TCR-pHLA interactions also has obvious implications for therapy design. Being able to directly &#34;see&#34; the molecules that are being therapeutically targeted, as well as the effect that modifications have on antigen recognition, will clearly improve the development of these medicines going forward. In this study, we show that even changes in a single peptide residue that is not heavily engaged by a TCR can unpredictably transmit structural changes to other residues in the HLA-bound peptide, which, in turn, dramatically alters T-cell recognition. A more complete understanding of the molecular mechanisms employed during T-cell antigen recognition will be hugely beneficial when designing future therapies for a wide range of human diseases.

X-ray crystallography has been, and will continue to be, an extremely powerful technique to understand the nature of ligand-receptor interactions. By visualizing these interactions in atomic detail, not only is it possible to divulge the molecular mechanisms governing many biological processes, but it is also possible to directly alter contact interfaces for therapeutic benefit. Coupled with techniques such as surface plasmon resonance and isothermal titration calorimetry (to name just a couple), such modifications can then be analyzed biophysically to assess the direct impact on binding affinity, interaction kinetics, and thermodynamics. Finally, by performing functional experiments on relevant cell types, a detailed picture of the molecular and functional impact of modifications to receptor-ligand interactions can be gleaned, providing very specific mechanistic information. Overall, these types of methods provide an atomic resolution picture enabling the determination of how biological systems work, with attendant implications for diagnostic and therapeutic advances.
Our laboratory routinely uses these techniques to study the receptors that mediate human T-cell immunity to pathogens and cancer, in autoimmunity, and during transplantation. Here, we focus on the human CD8+ T-cell response to cancer, mediated by an interaction between the T-cell receptor (TCR) and human leukocyte antigen (HLA)-restricted tumor-derived peptides (pHLA). This is important because, although CD8+ T cells are able to target cancer cells, we and others have previously shown that anti-cancer TCRs suboptimally bind to their cognate pHLA1,2. Thus, many laboratories have attempted to alter either the TCR3,4,5 or the peptide ligand6,7,8 in order to increase immunogenicity and to better target cancer cells. However, these approaches are not always effective and can have severe side effects, including off-target toxicities4,9,10. Further research exploring the molecular mechanisms that govern T-cell recognition of cancer antigens will be vital to overcome these shortfalls.
In the present study, we focused on the responses against autologous melanoma cells by CD8+ T cells specific for a fragment of the differentiation melanocyte antigen glycoprotein 100 (gp100), gp100280-288, presented by HLA-A*0201 (the most commonly-expressed human pHLA class I). This antigen has been a widely studied target for melanoma immunotherapy and has been developed as a so-called &#34;heteroclitic&#34; peptide in which a valine replaces alanine at anchor position 9 to improve pHLA stability11. This approach was used to enhance the induction of melanoma-reactive CTLs in vitro and has been successfully used in clinical trials12. However, modifications to peptide residues can have unpredictable effects on T-cell specificity, demonstrated by the poor efficacy of most heterolitic peptides in the clinic6,13. Indeed, another heteroclitic form of gp100280-288, in which peptide residue Glu3 was substituted for Ala, abrogated recognition by a polyclonal population of gp100280-288-specific T cells14,15. We have previously demonstrated that even minor changes in peptide anchor residues can substantially alter T-cell recognition in unpredictable ways6,16. Thus, the study focused on building a more detailed picture of how CD8+ T cells recognize gp100 and how modifications of the interaction between TCRs and pHLA could impact this function.
Here, we generated highly pure, soluble forms of two TCRs specific for gp100280-288 presented by HLA-A*0201 (A2-YLE), as well as the natural and altered forms of pHLA. These reagents were used to generate protein crystals to solve the ternary atomic structure of a human TCR in complex with the heteroclitic form of A2-YLE, as well as two of the mutant pHLAs in unligated form. We then used a peptide scanning approach to demonstrate the impact of peptide substitutions on TCRs by performing in-depth biophysical experiments. Finally, we generated a genetically modified CD8+ T-cell line, re-programmed to express one of the A2-YLE-specific TCRs, in order to perform functional experiments to test the biological impact of the various peptide modifications. These data demonstrate that even modifications to peptide residues that are outside of the TCR binding motif can have unpredictable knock-on effects on adjacent peptide residues that abrogate TCR binding and T-cell recognition. Our findings represent the first example of the structural mechanisms underlying T-cell recognition of this important therapeutic target for melanoma.

<table><tbody><tr><td>S.O.C. media</td><td>Invitrogen</td><td></td><td></td></tr><tr><td>Orbi-Safe New Orbit incubator</td><td>Sanyo</td><td></td><td></td></tr><tr><td>carbenicillin&amp;nbsp;</td><td>Sigma</td><td></td><td></td></tr><tr><td>IPTG&amp;nbsp;</td><td>Fisher</td><td></td><td></td></tr><tr><td>Quick Coomassie Stain SafeStain&amp;nbsp;</td><td>Generon</td><td></td><td></td></tr><tr><td>Legend RT centrifuge&amp;nbsp;</td><td>Sorvall</td><td></td><td></td></tr><tr><td>Tris&amp;nbsp;</td><td>Fisher</td><td></td><td></td></tr><tr><td>magnesium chloride&amp;nbsp;</td><td>Arcos</td><td></td><td></td></tr><tr><td>NaCl&amp;nbsp;</td><td>Fisher</td><td></td><td></td></tr><tr><td>glycerol&amp;nbsp;</td><td>Sigma-Aldrich</td><td></td><td></td></tr><tr><td>Sonopuls HD 2070&amp;nbsp;</td><td>Bandelin</td><td></td><td></td></tr><tr><td>DNAse&amp;nbsp;</td><td>Fisher</td><td></td><td></td></tr><tr><td>Triton</td><td>Sigma-Aldrich</td><td></td><td></td></tr><tr><td>EDTA&amp;nbsp;</td><td>Fisher</td><td></td><td></td></tr><tr><td>guanidine&amp;nbsp;</td><td>Fisher</td><td></td><td></td></tr><tr><td>NanoDrop ND1000&amp;nbsp;</td><td>Thermo</td><td></td><td></td></tr><tr><td>Peptides</td><td>Peptide Protein Research</td><td></td><td></td></tr><tr><td>dithiothreitol&amp;nbsp;</td><td>Sigma-Aldrich</td><td></td><td></td></tr><tr><td>L-arginine&amp;nbsp;</td><td>SAFC</td><td></td><td></td></tr><tr><td>cysteamine&amp;nbsp;</td><td>Fisher</td><td></td><td></td></tr><tr><td>cystamine&amp;nbsp;</td><td>Fisher</td><td></td><td></td></tr><tr><td>dialysis tubing&amp;nbsp;</td><td>Sigma-Aldrich</td><td></td><td></td></tr><tr><td>urea&amp;nbsp;</td><td>Sigma-Aldrich</td><td></td><td></td></tr><tr><td>Metricel 0.45 &amp;mu;m membrane filter</td><td>Pall</td><td></td><td></td></tr><tr><td>POROS 10/100 HQ&amp;nbsp;</td><td>Applied biosystems</td><td></td><td></td></tr><tr><td>&amp;Auml;KTA pure FPLC system&amp;nbsp;</td><td>GE Healthcare Life Sciences</td><td></td><td></td></tr><tr><td>10 kDa MWCO Vivaspin 20&amp;nbsp;</td><td>Sartorius</td><td></td><td></td></tr><tr><td>10 kDa MWCO Vivaspin 4&amp;nbsp;</td><td>Sartorius</td><td></td><td></td></tr><tr><td>Superdex 200 10/300 GL column&amp;nbsp;</td><td>GE Healthcare Life Sciences</td><td></td><td></td></tr><tr><td>Phosphate Buffer Saline&amp;nbsp;</td><td>Oxoid</td><td></td><td></td></tr><tr><td>BIAcore buffer HBS&amp;nbsp;</td><td>GE Healthcare Life Sciences</td><td></td><td></td></tr><tr><td>Biotinylation kit</td><td>Avidity</td><td></td><td></td></tr><tr><td>BIAcore T200</td><td>GE Healthcare Life Sciences</td><td></td><td></td></tr><tr><td>CM5 chip coupling kit</td><td>GE Healthcare Life Sciences</td><td></td><td></td></tr><tr><td>streptavidin&amp;nbsp;</td><td>Sigma-Aldrich</td><td></td><td></td></tr><tr><td>Microcal VP-ITC&amp;nbsp;</td><td>GE Healthcare Life Sciences</td><td></td><td></td></tr><tr><td>Hepes&amp;nbsp;</td><td>Sigma-Aldrich</td><td></td><td></td></tr><tr><td>Gryphon crystallisation robot</td><td>Art Robbins Instruments</td><td></td><td></td></tr><tr><td>Intelli-plate&amp;nbsp;</td><td>Art Robbins Instruments</td><td></td><td></td></tr><tr><td>Crystallisation screens and reagents</td><td>Molecular Dimensions</td><td></td><td></td></tr><tr><td>75 cm&lt;sup&gt;2 &lt;/sup&gt;flask&amp;nbsp;</td><td>Greiner Bio-One</td><td></td><td></td></tr><tr><td>0.22 &amp;mu;m filters</td><td>Miller-GP, Millipore</td><td></td><td></td></tr><tr><td>Ultra-Clear ultracentrifuge tube&amp;nbsp;</td><td>Beckman Coulter</td><td></td><td></td></tr><tr><td>Optima L-100 XP with SW28 rotor</td><td>Beckman Coulter</td><td></td><td></td></tr><tr><td>CD8 microbeads&amp;nbsp;</td><td>Miltenyi Biotec</td><td></td><td></td></tr><tr><td>anti-CD3/CD28 Dynabeads&amp;nbsp;</td><td>Invitrogen</td><td></td><td></td></tr><tr><td>anti-PE microbeads&amp;nbsp;</td><td>Miltenyi Biotec</td><td></td><td></td></tr><tr><td>CK medium, PHA</td><td>Alere Ltd</td><td></td><td></td></tr><tr><td>anti-TCRV&amp;beta; mAb&amp;nbsp;</td><td>BD</td><td></td><td></td></tr><tr><td>dasatinib&amp;nbsp;</td><td>Axon</td><td></td><td></td></tr><tr><td>MIP-1&amp;beta; and TNF&amp;alpha; ELISA&amp;nbsp;</td><td>R&amp;amp;D Systems</td><td></td><td></td></tr><tr><td>&amp;nbsp;&lt;sup&gt;51&lt;/sup&gt;Cr&amp;nbsp;</td><td>PerkinElmer</td><td></td><td></td></tr><tr><td>1450 Microbeta counter</td><td>PerkinElmer</td><td></td><td></td></tr></tbody></table>

using x-ray crystallography, biophysics, and functional assays to determine the mechanisms governing t-cell receptor recognition of cancer antigens

Human CD8+ cytotoxic T lymphocytes (CTLs) are known to play an important role in tumor control. In order to carry out this function, the cell surface-expressed T-cell receptor (TCR) must functionally recognize human leukocyte antigen (HLA)-restricted tumor-derived peptides (pHLA). However, we and others have shown that most TCRs bind sub-optimally to tumor antigens. Uncovering the molecular mechanisms that define this poor recognition could aid in the development of new targeted therapies that circumnavigate these shortcomings. Indeed, present therapies that lack this molecular understanding have not been universally effective. Here, we describe methods that we commonly employ in the laboratory to determine how the nature of the interaction between TCRs and pHLA governs T-cell functionality. These methods include the generation of soluble TCRs and pHLA and the use of these reagents for X-ray crystallography, biophysical analysis, and antigen-specific T-cell staining with pHLA multimers. Using these approaches and guided by structural analysis, it is possible to modify the interaction between TCRs and pHLA and to then test how these modifications impact T-cell antigen recognition. These findings have already helped to clarify the mechanism of T-cell recognition of a number of cancer antigens and could direct the development of altered peptides and modified TCRs for new cancer therapies.

Watch this Scientific Journal Video about Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens at JoVE.co

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Here, we describe methods that we commonly employ in the laboratory to determine how the nature of the interaction between the T-cell receptor and tumor antigens, presented by human leukocyte antigens, governs T-cell functionality; these methods include protein production, X-ray crystallography, biophysics, and functional T-cell experiments.

Human CD8+ cytotoxic T lymphocytes (CTLs) are known to play an important role in tumor control. In order to carry out this function, the cell ...

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Immunology and Infection

11.4K Views.  Cardiff University. Here, we describe methods that we commonly employ in the laboratory to determine how the nature of the interaction between the T-cell receptor and tumor antigens, presented by human leukocyte antigens, governs T-cell functionality; these methods include protein production, X-ray crystallography, biophysics, and functional T-cell experiments. 

Video: Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Determining Optimal Cytotoxic Activity of Human Her2neu Specific CD8 T cells by Comparing the Cr51 Release Assay to the xCELLigence System

Cytotoxic CD8 T cells constitute a subgroup of T cells that are capable of inducing the death of infected or malignant host cells1. These cells express a specialized receptor, called the T cell receptor (TCR), which can recognize a specific antigenic peptide bound to HLA class I molecules2. Engagement of infected cells or tumor cells through their HLA class I molecule results in production of lytic molecules such as granzymes and perforin resulting in target cell death. While it is useful to determine frequencies of antigen-specific CD8 T cells using assays such as the ELIspot or flow cytometry, it is also helpful to ascertain the strength of CD8 T cell responses using cytotoxicity assays3. The most recognizable assay for assessing cytotoxic function is the Chromium Release Assay (CRA), which is considered a standard assay 4. The CRA has several limitations, including exposure of cells to gamma radiation, lack of reproducibility, and a requirement for large numbers of cells. Over the past decade, there has been interest in adopting new strategies to overcome these limitations. Newer approaches include those that measure caspase 
release 4, BLT esterase activity 5 and surface expression of CD107 6. The impedance-based assay, using the Roche xCelligence system, was examined in the present paper for its potential as an alternative to the CRA. Impedance or opposition to an electric current occurs when adherent tumor cells bind to electrode plates. Tumor cells detach following killing and electrical impedance is reduced which can be measured by the xCelligence system. The ability to adapt the impedance-based approach to assess cell-mediated killing rests on the observation that T cells do not adhere tightly to most surfaces and do not appear to have much impact on impedance thus diminishing any concern of direct interference of the T cells with the measurement. Results show that the impedance-based assay can detect changes in the levels of antigen-specific cytotoxic CD8 T cells with increased sensitivity relative to the standard CRA. Based on these results, impedance-based approaches may be good alternatives to CRAs or other approaches that aim to measure cytotoxic CD8 T cell functionality.

The chromium release assay, a common assay for detecting cytotoxic T cell activity, has several limitations. Using antigen-specific CD8 T cells and the human breast cancer tumor line, SKBR3, in the present article, an impedance-based approach was examined for the capability of detecting cell killing.

Cytotoxic CD8 T cells constitute a subgroup of T  cells that are capable of inducing the death of infected or malignant host  cells1. These cells express ...

A TIRF Microscopy Technique for Real-time, Simultaneous Imaging of the TCR and its Associated Signaling Proteins

Signaling is initiated through the T Cell Receptor (TCR) when it is engaged by antigenic peptide fragments bound by Major Histocompatibility Complex (pMHC) proteins expressed on the surface of antigen presenting cells (APCs). The TCR complex is composed of the ligand binding TCR&alpha;&beta; heterodimer that associates non-covalently with CD3 dimers (the &#949;&delta; and &#949;&gamma; heterodimers and the &zeta;&zeta; homodimer)1. Upon engagement of the receptor, the CD3 &zeta; chains are phosphorylated by the Src family kinase, Lck. This leads to the recruitment of the Syk family kinase, Zap70, which is then phosphorylated and activated by Lck. After that, Zap70 phosphorylates the adapter proteins LAT and SLP76, initiating the formation of the proximal signaling complex containing a large number of different signaling molecules2. 
The formation of this complex eventually results in calcium and Ras-dependent transcription factor activation and the consequent initiation of a complex series of gene expression programs that give rise to T cell differentiation2. TCR signals (and the resulting state of differentiation) are modulated by many other factors, including antigen potency and crosstalk with co-stimulatory/co-inhibitory, chemokine, and cytokine receptors 3-4. Studying the spatial and temporal organization of the proximal signaling complex under various stimulation conditions is, therefore, key to understanding the TCR signaling pathway as well as its regulation by other signaling pathways.
One very useful model system to study signaling initiated by the TCR at the plasma membrane in T cells is glass-supported lipid bilayers, as described previously5-6. They can be utilized to present antigenic pMHC complexes, adhesion, and co-stimulatory molecules to T cells-serving as artificial APCs. By imaging the T cells interacting with the lipid bilayer using total internal reflection fluorescence microscopy (TIRFM), we can restrict the excitation to within 100 nm of the space between the glass and the cell surface 7-8. This allows us to image primarily the signaling events occurring at the plasma membrane. As we are interested in imaging the recruitment of signaling proteins to the TCR complex, we describe a two-camera TIRF imaging system wherein the TCR, labeled with fluorescent Fab (fragment antigen binding) fragments of the H57 antibody (purified from hybridoma H57-597, ATCC, ATCC Number:HB-218) which is specific for TCR&beta;, and signaling proteins, tagged with GFP, may be imaged simultaneously and in real time. This strategy is necessary due to the highly dynamic nature of both the T cells and of the signaling events that are occurring at the TCR. This imaging modality has allowed researchers to image single ligands 9-11 as well as recruitment of signaling molecules to activated receptors and is an excellent system to study biochemistry in-situ12-16.

The compartmentalization of proteins either within the plasma membrane or into intracellular locations is one regulatory mechanism that can greatly influence signaling outcomes; hence, to understand signaling it is important to study the spatial and temporal behavior of the proteins involved. We describe here a TIRF microscopy based system to study signal transduction in T cells, but is broadly applicable.

Signaling is initiated through the T Cell Receptor (TCR) when it is engaged by antigenic peptide fragments bound by Major Histocompatibility Complex ...

In Vitro Tumor Cell Rechallenge For Predictive Evaluation of Chimeric Antigen Receptor T Cell Antitumor Function

The field of chimeric antigen receptor (CAR) T cell therapy is rapidly advancing with improvements in CAR design, gene-engineering approaches and manufacturing optimizations. One challenge for these development efforts, however, has been the establishment of in vitro assays that can robustly inform selection of the optimal CAR T cell products for in vivo therapeutic success. Standard in vitro tumor-lysis assays often fail to reflect the true antitumor potential of the CAR T cells due to the relatively short co-culture time and high T cell to tumor ratio. Here, we describe an in vitro co-culture method to evaluate CAR T cell recursive killing potential at high tumor cell loads. In this assay, long-term cytotoxic function and proliferative capacity of CAR T cells is examined in vitro over 7 days with additional tumor targets administered to the co-culture every other day. This assay can be coupled with profiling T cell activation, exhaustion and memory phenotypes. Using this assay, we have successfully distinguished the functional and phenotypic differences between CD4+ and CD8+ CAR T cells against glioblastoma (GBM) cells, reflecting their differential in vivo antitumor activity in orthotopic xenograft models. This method provides a facile approach to assess CAR T cell potency and to elucidate the functional variations across different CAR T cell products.

Here, we describe an in vitro co-culture method to recursively challenge tumor-targeted T cells, which allows for phenotypic and functional analysis of antitumor T cell activity.

The field of chimeric antigen receptor (CAR) T cell therapy is rapidly advancing with improvements in CAR design, gene-engineering approaches and ...

Cancer Research

Quantitative High-throughput Single-cell Cytotoxicity Assay For T Cells

Cancer immunotherapy can harness the specificity of immune response to target and eliminate tumors. Adoptive cell therapy (ACT) based on the adoptive transfer of T cells genetically modified to express a chimeric antigen receptor (CAR) has shown considerable promise in clinical trials1-4. There are several advantages to using CAR+ T cells for the treatment of cancers including the ability to target non-MHC restricted antigens and to functionalize the T cells for optimal survival, homing and persistence within the host; and finally to induce apoptosis of CAR+ T cells in the event of host toxicity5.
Delineating the optimal functions of CAR+ T cells associated with clinical benefit is essential for designing the next generation of clinical trials. Recent advances in live animal imaging like multiphoton microscopy have revolutionized the study of immune cell function in vivo6,7. While these studies have advanced our understanding of T-cell functions in vivo, T-cell based ACT in clinical trials requires the need to link molecular and functional features of T-cell preparations pre-infusion with clinical efficacy post-infusion, by utilizing in vitro assays monitoring T-cell functions like, cytotoxicity and cytokine secretion. Standard flow-cytometry based assays have been developed that determine the overall functioning of populations of T cells at the single-cell level but these are not suitable for monitoring conjugate formation and lifetimes or the ability of the same cell to kill multiple targets8.
Microfabricated arrays designed in biocompatible polymers like polydimethylsiloxane (PDMS) are a particularly attractive method to spatially confine effectors and targets in small volumes9. In combination with automated time-lapse fluorescence microscopy, thousands of effector-target interactions can be monitored simultaneously by imaging individual wells of a nanowell array. We present here a high-throughput methodology for monitoring T-cell mediated cytotoxicity at the single-cell level that can be broadly applied to studying the cytolytic functionality of T cells.

We describe a single-cell high-throughput assay to measure cytotoxicity of T cells when incubated with tumor target cells. This method employs a dense, elastomeric array of sub-nanoliter wells (~100,000 wells/array) to spatially confine the T cells and target cells at defined ratios and is coupled to fluorescence microscopy to monitor effector-target conjugation and subsequent apoptosis.

Cancer immunotherapy can harness the specificity of  immune response to target and eliminate tumors. Adoptive cell therapy (ACT)  based on the adoptive ...

Real-time Live Imaging of T-cell Signaling Complex Formation

Protection against infectious diseases is mediated by the immune system 1,2. T lymphocytes are the master coordinators of the immune system, regulating the activation and responses of multiple immune cells 3,4. T-cell activation is dependent on the recognition of specific antigens displayed by antigen presenting cells (APCs). The T-cell antigen receptor (TCR) is specific to each T-cell clone and determines antigen specificity 5. The binding of the TCR to the antigen induces the phosphorylation of components of the TCR complex. In order to promote T-cell activation, this signal must be transduced from the membrane to the cytoplasm and the nucleus, initiating various crucial responses such as recruitment of signaling proteins to the TCR;APC site (the immune synapse), their molecular activation, cytoskeletal rearrangement, elevation of intracellular calcium concentration, and changes in gene expression 6,7. The correct initiation and termination of activating signals is crucial for appropriate T-cell responses. The activity of signaling proteins is dependent on the formation and termination of protein-protein interactions, post translational modifications such as protein phosphorylation, formation of protein complexes, protein ubiquitylation and the recruitment of proteins to various cellular sites 8. Understanding the inner workings of the T-cell activation process is crucial for both immunological research and clinical applications.
Various assays have been developed in order to investigate protein-protein interactions; however, biochemical assays, such as the widely used co-immunoprecipitation method, do not allow protein location to be discerned, thus precluding the observation of valuable insights into the dynamics of cellular mechanisms. Additionally, these bulk assays usually combine proteins from many different cells that might be at different stages of the investigated cellular process. This can have a detrimental effect on temporal resolution. The use of real-time imaging of live cells allows both the spatial tracking of proteins and the ability to temporally distinguish between signaling events, thus shedding light on the dynamics of the process 9,10. We present a method of real-time imaging of signaling-complex formation during T-cell activation. Primary T-cells or T-cell lines, such as Jurkat, are transfected with plasmids encoding for proteins of interest fused to monomeric fluorescent proteins, preventing non-physiological oligomerization 11. Live T cells are dropped over a coverslip pre-coated with T-cell activating antibody 8,9, which binds to the CD3/TCR complex, inducing T-cell activation while overcoming the need for specific activating antigens. Activated cells are constantly imaged with the use of confocal microscopy. Imaging data are analyzed to yield quantitative results, such as the colocalization coefficient of the signaling proteins.

We describe a live-cell imaging method that provides insight into protein dynamics during the T-cell activation process. We demonstrate the combined usage of the T-cell spreading assay, confocal microscopy and imaging analysis to yield quantitative results to follow signaling complex formation throughout T-cell activation.

Protection against infectious diseases is mediated by the immune system 1,2. T lymphocytes are the master coordinators of the immune system, regulating ...

Analyzing Tumor and Tissue Distribution of Target Antigen Specific Therapeutic Antibody

Monoclonal antibodies are high affinity multifunctional drugs that work by variable independent mechanisms to eliminate cancer cells. Over the last few decades, the field of antibody-drug conjugates, bispecific antibodies, chimeric antigen receptors (CAR) and cancer immunotherapy has emerged as the most promising area of basic and therapeutic investigations. With numerous successful human trials targeting immune checkpoint receptors and CAR-T cells in leukemia and melanoma at a breakthrough pace, it is highly exciting times for oncologic therapeutics derived from variations of antibody engineering. Regrettably, a significantly large numbers of antibody and CAR based therapeutics have also proven disappointing in human trials of solid cancers because of the limited availability of immune effector cells in the tumor bed. Importantly, nonspecific distribution of therapeutic antibodies in tissues other than tumors also contribute to the lack of clinical efficacy, associated toxicity and clinical failure. As faithful translation of preclinical studies into human clinical trails are highly relied on mice tumor xenograft efficacy and safety studies, here we highlight a method to test the tumor and general tissue distribution of therapeutic antibodies. This is achieved by labeling the protein-A purified antibody with near Infrared fluorescent dye followed by live imaging of tumor bearing mice.

Here we present a protocol to study the in vivo localization of antibodies in mice tumor xenograft models.

Monoclonal antibodies are high affinity multifunctional drugs that work by variable independent mechanisms to eliminate cancer cells. Over the last few ...

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

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

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

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

Biochemistry

Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay

T-cells are remarkably specific and effective when recognizing antigens in the form of peptides embedded in MHC molecules (pMHC) on the surface of Antigen Presenting Cells (APCs). This is despite T-cell antigen receptors (TCRs) exerting usually a moderate affinity (&#181;M range) to antigen when binding is measured in vitro1. In view of the molecular and cellular parameters contributing to T-cell antigen sensitivity, a microscopy-based methodology has been developed as a means to monitor TCR-pMHC binding in situ, as it occurs within the synapse of a live T-cell and an artificial and functionalized glass-supported planar lipid bilayer (SLB), which mimics the cell membrane of an Antigen presenting Cell (APC) 2. Measurements are based on F&#246;rster Resonance Energy Transfer (FRET) between a blue- and red-shifted fluorescent dye attached to the TCR and the pMHC. Because the efficiency of FRET is inversely proportional to the sixth power of the inter-dye distance, one can employ FRET signals to visualize synaptic TCR-pMHC binding. The sensitive of the microscopy approach supports detection of single molecule FRET events. This allows to determine the affinity and off-rate of synaptic TCR-pMHC interactions and in turn to interpolate the on-rate of binding. Analogous assays could be applied to measure other receptor-ligand interactions in their native environment.

Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay

This manuscript describes how to conduct (single molecule) F&#246;rster Resonance Energy Transfer (FRET)- based assays to measure the binding dynamics between T-cell antigen receptor (TCR) and antigenic peptide-loaded MHC molecules as they occur within the immunological synapse of a T-cell in contact with a functionalized planar supported lipid bilayer.

T-cells are remarkably specific and effective when recognizing antigens in the form of peptides embedded in MHC molecules (pMHC) on the surface of Antigen ...

Bioengineering

Quantifying Antibody-Dependent Cellular Cytotoxicity in a Tumor Spheroid Model: Application for Drug Discovery

Monoclonal antibody-based immunotherapy targeting tumor antigens is now a mainstay of cancer treatment. One of the clinically relevant mechanisms of action of the antibodies is antibody-dependent cellular cytotoxicity (ADCC), where the antibody binds to the cancer cells and engages the cellular component of the immune system, e.g., natural killer (NK) cells, to kill the tumor cells. The effectiveness of these therapies could be improved by identifying adjuvant compounds that increase the sensitivity of the cancer cells or the potency of the immune cells. In addition, undiscovered drug interactions in cancer patients co-medicated for previous conditions or cancer-associated symptoms may determine the success of the antibody therapy; therefore, such unwanted drug interactions need to be eliminated. With these goals in mind, we created a cancer ADCC model and describe here a simple protocol to find ADCC-modulating drugs. Since 3D models such as cancer cell spheroids are superior to 2D cultures in predicting in vivo responses of tumors to anticancer therapies, spheroid co-cultures of EGFP-expressing HER2+ JIMT-1 breast cancer cells and the NK92.CD16 cell lines were set up and induced with Trastuzumab, a monoclonal antibody clinically approved against HER2-positive breast cancer. JIMT-1 spheroids were allowed to form in cell-repellent U-bottom 96-well plates. On day 3, NK cells and Trastuzumab were added. The spheroids were then stained with Annexin V-Alexa 647 to measure apoptotic cell death, which was quantitated in the peripheral zone of the spheroids with an automated microscope. The applicability of our assay to identify ADCC-modulating molecules is demonstrated by showing that Sunitinib, a receptor tyrosine kinase inhibitor approved by the FDA against metastatic cancer, almost completely abolishes ADCC. The generation of the spheroids and image acquisition and analysis pipelines are compatible with high-throughput screening for ADCC-modulating compounds in cancer cell spheroids.

Here, we present a method to identify compounds that modulate the ADCC mechanism, an important cancer cell-killing mechanism of antitumor antibodies. The cytotoxic effect of NK cells is measured in breast cancer cell spheroids in the presence of Trastuzumab. Image analysis identifies live and dead killer and target cells in spheroids.

Monoclonal antibody-based immunotherapy targeting tumor antigens is now a mainstay of cancer treatment. One of the clinically relevant mechanisms of ...

Identification of Mediators of T-cell Receptor Signaling via the Screening of Chemical Inhibitor Libraries

The T-cell receptor (TCR) signaling pathway comprises a multitude of mediators that transmit signals upon the activation of the TCR. Different strategies have been proposed and implemented for the identification of new mediators of TCR signaling, which would improve the understanding of T-cell processes, including activation and thymic selection. We describe a screening assay that enables the identification of molecules that influence TCR signaling based on the activation of developing thymocytes. Strong TCR signals cause developing thymocytes to activate apoptotic machinery in a process known as negative selection. Through the application of kinase inhibitors, those with targets that affect TCR signaling are able to override the process of negative selection. The method detailed in this paper can be used to identify inhibitors of canonical kinases with established roles in the TCR signaling pathways and also inhibitors of new kinases yet to be established in the TCR signaling pathways. The screening strategy here can be applied to screens of higher throughput for the identification of novel druggable targets in TCR signaling.

Identification of Mediators of T-cell Receptor Signaling via the Screening of Chemical Inhibitor Libraries

This paper uses a flow-cytometry-based assay to screen libraries of chemical inhibitors for the identification of inhibitors and their targets that influence T-cell receptor signaling. The methods described here can also be expanded for high-throughput screenings.

The T-cell receptor (TCR) signaling pathway comprises a multitude of mediators that transmit signals upon the activation of the TCR. Different strategies ...

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

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