Name: using x-ray crystallography, biophysics, and functional assays to determine the mechanisms governing t-cell receptor recognition of cancer antigens
Uploaded: 2017-02-06T11:00:00.000+00:00
Duration: 9 min 53 s
Description: 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

BM是由英国癌症研究中心博士助学金的支持。公司是由生命科学科研计算机网威尔士博士助学金的支持。 VB由癌症研究威尔士博士助学金的支持。 DKC是威康信托基金研究职业发展研究员（WT095767）。 AKS是威康信托基金研究员。 GHM通过接头生命科学研究网络威尔士和Tenovus癌症护理博士助学金资助。我们感谢在钻石光源的员工提供便利和支持。

1.蛋白表达<ol><li>使基因构建为可溶性的TCR和pHLAs的产生，如先前17,18进行详细说明。设计一个5&#39;BamH1位和3&#39;EcoRⅠ小限制位点用于插入pGMT7向量中的每个构造。 </li><li>转化大肠杆菌 Rosetta（DE3）pLysS中含有通过孵育50-200纳克/微升质粒与5微升大肠杆菌 5分钟的1微升编码感兴趣的蛋白质的序列的pGMT7衍生质粒载体在4℃下，2分钟，在42℃，并在4℃下5分钟，并在37℃下在补充有50毫克/升羧苄青霉素的LB琼脂平板过夜积垢。 </li><li>挑选单个菌落并在补充有100μM的羧苄青霉素，直到该悬浮液在37℃和220rpm下在30 TYP介质中的溶液（16克/升胰蛋白胨16克/升酵母提取物，和5克/升HK 2 O 4）生长到达光德nsity 0.4和0.6之间（OD 600）。 </li><li>通过3小时引入0.5毫异丙β-D-1-硫代半乳糖苷（IPTG）诱导蛋白质产生在5毫升等分试样。保持悬浮液的20μL的使用和不使用诱导十二烷基硫酸钠聚丙烯酰胺凝胶电泳（SDS-PAGE）进行分析和染色凝胶。 </li><li>添加起子培养至1L TYP补充有100μM的羧苄青霉素和如上面步骤1.3中所述，直至该悬浮液达到0.4和0.6之间的OD 600生长的细胞。 </li><li>诱导蛋白质表达为用0.5mM IPTG 3小时。离心20分钟将细胞以3000 xg离心，小心地倒出上清液。 </li><li>溶解在40ml裂解缓冲液的沉淀（10毫摩尔Tris，pH值8.1; 10mM氯化镁， 氯化镁 ; 150毫摩尔NaCl; 10％甘油）中，在冰上超声处理采用2秒的时间间隔30分钟，在60％的功率，并在室温（RT）下温育30分钟，0.1克/升的DNase。 </li><li>对待SUS含有包涵体（IB）用100mL洗涤缓冲液的形式蛋白质退休金（0.5％的Triton X-100; 50毫摩尔Tris，pH值8.1; 100毫摩尔NaCl;和10mM EDTA）中。 </li><li>离心样品在4℃下20分钟，8000 XG，小心地倒出上清液。重悬在100毫升再悬浮缓冲液的沉淀（50毫摩尔Tris，pH值8.1; 100毫摩尔NaCl; 10毫摩尔EDTA，pH值8.1），离心机如之前在8000 xg离心，并小心地倒出上清液。 </li><li>最后，溶解沉淀在10mL胍缓冲液（6M胍; 50毫摩尔Tris，pH值8.1; 2mM EDTA的，pH值8.1;和100mM NaCl）中，并用分光光度计测量280nm处的蛋白浓度。 </li></ol> 2. PHLA和TCR复性<ol><li>为PHLA refolds，（用生物素标记或HLA-A2），在37℃的水浴中在最终体积混合30毫克的HLA-A2的的IB，30毫克β2M的IB，以及30分钟4毫克肽的6毫升胍缓冲液中补充了10毫二硫苏糖醇醇（DTT）。 </li><li>通过在1升预先冷却的HLA再折叠缓冲液中稀释之前的混合引发蛋白复性（50毫摩尔Tris，pH值8.1; 400 mM L-精氨酸; 2mM EDTA的，pH值8.1; 6毫半胱胺;和4mM胱胺）。 </li><li>离开的HLA重折叠在4℃下搅拌3小时，然后将其转移到一个12.4 kDa的MWCO（分子量截止）透析管和用于对20升的10mM Tris，pH值8.1的24小时透析两次。 </li><li>对于TCR refolds，30分钟，在37℃的水浴中在6毫升补充有10毫摩尔DTT胍缓冲液中混合30毫克的TCRα链的IB和30毫克的TCRβ链的IB的。 </li><li>通过在1升预先冷却的TCR再折叠缓冲液中稀释变性的TCR混合物发起蛋白复性（50毫摩尔Tris，pH值8.1; 2.5M尿素; 2毫摩尔EDTA，pH值8.1; 6毫半胱胺;和4mM胱胺）3 H。 </li><li>转移到再折叠12.4 kDa的截留分子量透析管和24小时透析两次对20升10毫米的Tris，pH值8.1。 </li><li>同时过滤掉了PHLA或TCR REF使用用于纯化步骤0.45微米的膜过滤器的年轻人。 </li></ol> 3.纯化通过快速蛋白质液相层析（FPLC） <ol><li>加载过滤再折叠制备（无论PHLA或TCR）到7.9毫升，50微米阴离子交换树脂柱预平衡用20ml的10mM Tris，柔性和直观的色谱系统上的pH 8.1的。 </li><li>洗脱蛋白在含有盐梯度5毫升/分钟（0-500毫摩尔NaCl在10mM的Tris，pH值8.1，用8个柱体积），并收集1毫升的级分。 </li><li>分析对应于通过SDS-PAGE感兴趣的蛋白质的级分，汇集含有目的蛋白质一起的级分，并在4000 xg离心20分钟，离心浓缩下来到500μL10-kDa的截留分子量20或10 kDa的MWCO 4 ，丢弃流过。 </li><li>加载浓缩蛋白制剂到2mL注射环到24毫升尺寸排阻层析柱与该应用预平衡ropriate洗脱缓冲液:磷酸盐缓冲盐水（PBS），HBS（10mM的HEPES，pH值7.4; 150毫摩尔NaCl; 3.4毫摩尔EDTA和0.005％表面活性剂），或晶体缓冲液（10mM的Tris，pH值8.1，和10mM NaCl的）。 </li><li>洗脱以0.5毫升/分钟以上1柱体积的流率的蛋白质;收集含的通过SDS-PAGE验证感兴趣的蛋白1毫升的级分。 注意:这些方法被用于产生可溶性PMEL17 TCR和的gp100的TCR，以及所有在本研究中使用的pHLAs的HLA-A * 0201与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-图7A），或YLEPGPVAA（A2-YLE-8A）。 </li></ol> 4，表面等离子体共振（SPR）分析<ol><li>执行使用装备有在CM5传感器芯片19中的分子间相互作用分析系统平衡结合分析或热力学分析。 </li><li>通过激活F中的CM5芯片降脂1:100毫N-羟基琥珀酰亚胺（NHS）和400mM的1-乙基-3-（3-二甲基丙基）-carboiimide（EDC）的10分钟1混合，以10微升/分钟的流速，在25℃ C。 </li><li>负载大约5000响应单位（RU）链霉的（200微克的110微升/毫升10mM醋酸，pH4.5）中通过共价键在所有四个流动细胞连结至芯片表面，并使用1M乙醇胺盐酸100微升停用任何剩余的反应性基团。 </li><li> PHLA的夫妇约500-600位，在以10微升/分钟的缓慢流速〜1μM的商业缓冲液（由生产商提供），向CM5传感芯片，以确保在芯片表面上均匀分布。 </li><li>饱和，在商业缓冲液为1mM生物素（由生产商提供的）为60秒的芯片表面。 </li><li>注入在相关流动细胞可溶性TCR的十个连续稀释在30微升/分钟，在25℃的高流速。 </li><li>计算平衡结合常数（K D（E））使用非线性曲线拟合（γ=（P1X）/（P 2 + x）的）20个值。 注:Y =响应单位，X =分析师浓度，P1 = R 最大 P2 = 杀敌 。 </li><li>进行动力学分析假定1:1 Langmuir结合并在软件包2使用全局拟合算法拟合数据。 </li><li> 5℃，12℃，18℃，25℃，和30℃19:通过在以下温度重复该方法执行热力学实验。 </li><li>使用通过SPR确定在K D取值在不同的温度来计算ΔG°使用标准热力学等式（ΔG°= -RTlnK D）19。 注:R =气体常数，T =温度以K，LN =自然对数。 </li><li> 19 -根据吉布斯-亥姆霍兹方程（TΔS°ΔG°=△H）计算热力学参数。 </LI&gt; <li>积使用非线性回归拟合三参数方程（结合自由能，ΔG°（ΔG°= -RTlnK D）中 ，对温度（K）Y =ΔH+ΔCp*（X-298）-x *ΔS- X *ΔCp* LN（X / 298））19。 注:Y =温度K，X =ΔG°。 </li></ol> 5.温滴定量热（ITC） <ol><li>执行使用等温滴定热量ITC实验。注入30μMPHLA进入热量计单元和负载210μM的可溶性TCR到注射器。使用下面的缓冲液条件:20毫摩尔的Hepes含有150mM NaCl的（pH 7.4）中。 </li><li>执行20 TCR注射，每次2μL体积。使用分析软件计算出ΔH和杀敌 。 </li></ol> 6.结晶，衍射数据收集和模型修正<ol><li>执行使用结晶机器人结晶试验。 </li><li>通过生长晶体VAP或者通过与含有60微升结晶缓冲液（母液）21的储存器96孔的板中的坐滴技术扩散在18℃。 </li><li>通过在10-kDa的分子量截断离心浓缩以3000 xg离心纺丝浓缩可溶性PHLA在晶体缓冲器大约10毫克/毫升（0.2毫摩尔）。 </li><li>用于共结构复杂，混合TCR和PHLA在1:1的摩尔比在大约10毫克/毫升（0.1毫摩尔）得到的蛋白质溶液。 </li><li>添加200 NL PHLA的单独，或1:TCR和PHLA的1摩尔比混合，以从结晶屏幕使用结晶机器人每个储存溶液的200 nL和得分为结晶在显微镜下24小时，48小时，72后小时，然后每周一次。 </li><li>通过浸没并将它们存储在液氮温度（100 K）收获单晶通过手动将它们安装在冷冻循环的显微镜和下低温冷却它们。 注:加载晶体需要一点PRAC的蒂斯，并决定哪些晶体数据收集不够好来自经验。作为一个经验法则，更大和更经常晶体，效果更佳。 </li><li>在100 K。氮气流收集数据 注:此数据是在钻石光源（DLS）英国国家同步的科学设施收购。 </li><li>通过使用这两个MOSFLM 22估计与xia2的反射强度分析数据和XDS软件包23，然后扩展与SCALA或无目的24和CCP4软件包25中的数据。 </li><li>解决使用PHASER 26分子置换的结构。 </li><li>调整与COOT 27的模型和REFMAC5 28细化模型。 </li><li>准备图形表示与PYMOL 29。 </li><li>通过"接触"计算的接触计划在CCP4包。使用4截止的范德华接触和3.4截止的氢键和盐桥。 </li><li>计算出CCP4包使用"SC"节目表面的互补性。 </li><li>计算TCR-PHLA复杂的交叉角，如上所述30。 注:在本研究中，反射数据和最终的模型坐标分别与PDB数据库沉积（PMEL17 TCR-A2-YLE-9V PDB:5EU6，A2-YLE PDB:5EU3，A2-YLE-3A PDB:5EU4和A2 -YLE-5A PDB:5EU5）。 </li></ol>

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

这里所概述的协议提供的T细胞应答中的任何人的疾病的背景下的分子和细胞解剖的框架。虽然癌症是本研究的主要焦点，我们使用了非常类似的方法来研究病毒32，33，34，35，T细胞反应36，37和38自身免疫，39，40中。此外，我们已使用这些技术更广泛地理解支配T-细胞抗原识别2，19，41，42中的分子原理。事实上，修改的不可预测性的肽残基，甚至是那些的T细胞受体接触残基之外，影响T细胞识别有heteroclitic肽的设计具有重要意义。这些发现直接促成新型的T细胞疗法的发展，包括多肽疫苗6,43和人工高亲和力的TCR 3，4，5，20，44，以及增强诊断45，46，47。 该协议中的关键步骤 高纯度的，功能性蛋白质的产生是所有的在本文中概述的方法是至关重要的。 修改和故障排除 在产生高纯度蛋白的困难往往涉及到高度表达制纯净，不溶性的IB从大肠杆菌表达系统。通常，修饰的表达协议（ 例如，诱导在不同的光密度，使用不同的大肠杆菌菌株，或者使用不同的介质形成）可以解决这些问题。 该技术的局限性 这些技术使用那些在细胞表面正常表达可溶性蛋白分子（TCR和PHLA）。因此，重要的是要确保结构/生物物理研究结果与蜂窝的方法来确认生物学意义一致。 相对于现有的/替代方法的技术意义 通过使用X-射线晶体学和通过功能分析证实生物物理学，我们和其他人已证明的TCR特异性的癌症抗原表位通常具有低结合亲和性48。这种低TCR亲和力可能有助于解释为什么T细胞ARË在清除癌细胞不能自然有效。抗癌的TCR和同源肿瘤抗原之间复合物的高分辨率原子结构已经开始揭示这个弱亲和力的分子基础。此外，这些研究是用于确定所依据设计来克服这个问题的治疗性干预的机制，播种未来改进16有帮助的。在这项研究中，我们检查了一个天然存在的αβTCR的第一结构中的复杂带的gp100 HLA-A * 0201限制性黑素瘤表位。的结构，与进行了深入的生物物理检查结合，揭示了相互作用的整体结合模式。我们还发现了意想不到的分子开关，从而发生的肽的突变形式，即废除TCR结合和CD8 + T细胞识别（功能实验）（使用表面等离子体共振评估）。这是唯一可能证明HLA抗原presentati的新机制使用所描述的高分辨率方法。 掌握这一技术后，未来的应用或指示 总体而言，当与鲁棒功能分析相结合我们的结果表明X-射线结晶学和生物物理方法的力量。使用这些方法，有可能以剖析出支配T-细胞抗原识别精确的分子机制。实际上，它也可以用这种方式来解决未连接的TCR的结构中，展示的构象变化如何抗原歧视49，50，51中发挥作用。更好地理解的高度复杂性和动态性的支撑TCR-PHLA相互作用也有治疗的设计明显的影响。能够直接"看"正在治疗靶向的修改对抗原识别中的分子，以及效果N，显然会提高这些药物的向前发展。在这项研究中，我们表明，即使改变在单个肽残未很大程度上由TCR接合可以不可预知发送到在与HLA结合的肽，其中，反过来，大幅改变的T细胞识别其它残基的结构变化。设计未来的疗法的广泛的人类疾病时T细胞抗原识别中所采用的分子机制的更完整的理解将是非常有益的。

X射线晶体学已经，并且将继续是一个非常强大的技术来理解配体 - 受体相互作用的性质。通过可视化的原子细节这些相互作用，不仅是有可能泄露理事许多生物过程的分子机制，但它也可以直接改变为治疗益处接触界面。加之技术如表面等离子体共振和等温滴定量热法（仅举几），这样的修改可以被生物物理分析，以评估结合亲和力相互作用动力学和热力学的直接影响。最后，通过在相关的细胞类型执行功能实验中，修饰的受体 - 配体相互作用的分子和功能的影响的详细图像可以收集，提供非常具体的机械信息。总体而言，这些类型的方法提供的原子分辨率图像使阻止<html>的生物系统如何工作，具有诊断和治疗的进步随之而来的影响mination。 我们实验室常规使用这些技术来研究介导人T细胞免疫病原体和癌症，自身免疫的受体，和移植中。这里，我们专注于人类CD8 + T细胞应答于癌症，由T细胞受体（TCR）和人白细胞抗原（HLA）-restricted肿瘤衍生肽（PHLA）之间的相互作用介导的。因为，虽然CD8 + T细胞能够靶向癌细胞，我们和其他人以前曾表明，抗癌的TCR次优结合其同源PHLA 1,2这是很重要的。因此，许多实验室已尝试改变任TCR 3，4，5或肽配位体6，类=以增加免疫原性，并更好地靶癌细胞"外部参照"&gt; 7,8。然而，这些方法并不总是有效，并且可以具有严重的副作用，包括脱靶毒性4，9，10。进一步的研究探讨支配癌抗原的T细胞识别的分子机制将是克服这些缺点是至关重要的。 在本研究中，我们侧重于针对由特定的分化黑色素细胞抗原的一个片段CD8 + T细胞自体的黑色素瘤细胞的响应糖蛋白100（的gp100）的gp100 280-288，由HLA-A * 0201（最常提出-expressed人PHLA I类）。该抗原已黑素瘤免疫治疗的广泛研究的目标，并已发展为一个所谓的"heteroclitic"肽，其中一个缬氨酸取代丙氨酸在锚位9，以提高稳定性PHLA 11。这种方法被用来增强体外黑素瘤-反应性CTL的诱导，并已在临床试验中12被成功地使用。然而，修改的肽残基可以具有对T细胞特异性，通过最heterolitic肽的疗效不佳在诊所6,13展示了不可预测的影响。实际上，的gp100 280-288的另一个heteroclitic形式，其中肽残Glu3代替丙氨酸，通过的gp100 280-288特异性T细胞14，15的多克隆群体废止认可。之前我们已经证实，即使在肽锚残留微小的变化能极大地改变不可预知的方式6，16的T细胞识别。因此，研究的重点是构建ING的CD8 + T细胞是如何识别的TCR和PHLA之间的相互作用的gp100以及如何修改的更详细的图像可能会影响该功能。 在这里，我们产生的具体由HLA-A * 0201（A2-YLE）颁发的gp100 280-288 2电阻温度系数的高纯度，可溶性形式，以及PHLA的自然和改变形式。这些试剂被用来产生蛋白质晶体使用A2-YLE的heteroclitic形式，以及两个在未连接形式的突变体pHLAs来解决人类的TCR的三元原子结构复杂。然后，我们使用的肽扫描方法，通过进行深入的生物物理实验，以证明肽取代的上的TCR的影响。最后，我们产生了转基因CD8 + T细胞系，重新编程以表达A2-YLE特异性的TCR的一个，以执行功能性实验来测试各种肽修饰的生物学影响。这些数据表明，即使莫迪fications的肽是T细胞受体结合基序之外的残基可具有不可预测的连锁上废除TCR结合和T细胞识别相邻的肽残基的影响。我们的研究结果表示底层黑素瘤此重要的治疗目标的T细胞识别的结构机制的第一个例子。

<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.

采用上述方法，我们产生可溶性TCR（ 表1）和PHLA分子由CD8 + T细胞的深入进行的gp100 280-288识别分子分析。的改性大肠杆菌表达系统用于生成不溶性的IB为两者的TCR（α和β链）和pHLAs（α链和β2M）的每个单独的链。这种方法具有相对廉价和容易建立优势，并产生蛋白质的产量大（100-500毫克/升的文化）。此外，如果保存在-80℃下的不溶性蛋白质是高度稳定的。然后，我们使用一个完善的重折叠和纯化技术产生功能性的，同质的，可溶性蛋白。此方法是用于产生蛋白质为生物物理，结构，和细胞的实验中，以及可用于诊断或治疗试剂是有用的。 表2）结合亲和力。该实验结果显示其残留肽是最重要的TCR结合。使用这种技术的结合亲和力的高分辨率分析是用于确定控制蛋白质 - 蛋白质相互作用的生物学机制，用于分析治疗分子的结合亲和力是非常有用的，以及。 然后，我们在复杂结晶的特定黑素瘤可溶性TCR（PMEL17 TCR）具有修饰的肿瘤衍生PHLA（A2-YLE-9V）调查在原子分辨率（ 图1和2和表3）的结合模式。这些实验提供了两个分子之间的结合界面的直接可视化，providin摹关于执政的相互作用的基本原则的关键信息。我们进一步进行同时使用SPR和ITC的相互作用的热力学分析，揭示了使结合（ 图3）作出积极贡献。这些分析是由两种蛋白质（ 图4和表4）之间的接触印迹的高分辨率描述进一步支持。 然后，我们解决了未连接PHLA分子的结构，呈现肽的突变形式，揭示了一种分子开关可以解释为什么废除TCR结合某些突变（ 图5）。 总体而言，这些技术提供了新的数据证明该机制解释T细胞如何识别黑素瘤衍生的抗原是抗癌疗法的一个重要目标。更广泛地说，这些技术可用于研究几乎任何受体 - 配体相互作用，揭示可能被靶向用于新的治疗进展的新的生物机制。 <img alt="图1" src="/files/ftp_upload/54991/54991fig1.jpg" /> 图1:密度图分析。左栏显示了省略，其中该模型是在不存在肽的精制地图。差密度在3.0西格马轮廓，正轮廓示于绿色和负轮廓是红色的。右手栏示出了在1.0西格马随后细化使用由REFMAC5施加自动非晶体学对称约束后所观察到的图（示出为围绕蛋白质链的棒表示灰色目）。 （ 一 ）PMEL17 TCR-A2-YLE-9V与TCR CDR3模型循环色蓝（α链）和橙色（β链）和绿色的肽。 （B）型号为A2-与YLE肽呈深绿色。 （℃）A2-YLE-3A与肽橙色的型号（A2-YLE-3A，有在不对称单位2的分子，但这些实际上是相同的省略和密度图的方面，因此，只复制1此处示出）。 （D）为A2-YLE-5A与肽涂上粉红色的模型。从31参考授权转载。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54991/54991fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图2" src="/files/ftp_upload/54991/54991fig2.jpg" /> 图2:PMEL17的TCR与A2-YLE-9V复杂的概述。在PMEL17 TCR-A2-YLE-9V复杂的（A）卡通表示。该TCR颜色为黑色; TCR CDR环显示（红，CDR1α;深绿色，CDR2α，蓝色，CDR3α;黄色，CDR1β;浅绿色，CDR2 ^6 ;;橙色，CDR3β）;与HLA-A * 0201以灰色示出。该YLE-9V肽是由青枝表示。在PMEL17 TCR CDR的残基（B）表面，并坚持表示回路（颜色编码为A），使联系A2-YLE表面（A2，灰色; YLE-9V，青枝）。黑斜线指示TCR的相对于所述YLEPGPVTV肽（46.15°）的长轴交叉角。 （ 三 ）PMEL17 TCR的A2-YLE-9V表面上（A2，灰色）的联系足迹;紫色和绿色（表面和棍棒）表示HLA-A * 0201和YLE残留物，分别由GP100 TCR接触。截止3.4的氢键和4对于范德华联系。经许可后转载自参考31. <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54991/54991fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alT ="图3"SRC ="/文件/ ftp_upload / 54991 / 54991fig3.jpg"/&gt; 图3:PMEL17 TCR-A2-YLE的相互作用的热力学分析。 （A）PMEL17 TCR均衡结合在5至A2-YLE响应，12，18，25和37℃跨越九至十TCR系列稀释。 SPR生和拟合数据（假设为1:1 Langmuir结合）在每个曲线的插图中示出，并用于使用全局拟合算法（BIA评估3.1） 来计算和K off值为ķ。该表显示平衡结合（K D（E））和动力学结合常数（K D（K）= K 关闭 / K 于 ）在每个温度。的平衡结合常数（K D，μM）利用非线性拟合计算的值（Y =（P1X）/（P 2 + X））。 （B）中的热力学参数是根据吉布斯-亥姆霍兹方程计算（ΔG°=ΔH° - TΔS°）。的结合自由能，ΔG°（ΔG°= -RTlnK D），反对温度作图（使用非线性回归拟合三参数方程K）（Y =ΔH°+ΔCp°*（X-298）-X *ΔS°-x *ΔCp° * LN（X / 298））。焓（ΔH°）和熵（TΔS°）在298K（25℃）示于千卡/摩尔和温度（K）的非线性回归计算作图的自由能（△G°）。 （C）等温量热滴定法（ITC）的三围为PMEL17 TCR-A2-YLE互动。焓（ΔH°）和熵（TΔS°）在298K（25℃）示于千卡/摩尔。从31参考授权转载。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54991/54991fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图4" src="/files/ftp_upload/54991/54991fig4.jpg" /> <str<html>翁&gt;图4:PMEL17 CDR环聚焦肽残留PRO4，Val7和Thr8。 （A）中的YLE-9V肽和PMEL17 CDR环残基之间的联系方式的示意图（彩色编码如在图2A）。在面板的底部的数字显示了TCR与肽之间的总接触。 （B）中的PMEL17 TCR和所述YLE-9V肽（绿色棒）表示范德之间联系范德华接触（黑色虚线）和氢键（红色虚线）由TCRCDR3α（蓝色）制成，CDR1β（黄色） ，CDR2β（AQUA），和CDR3β（橙色）循环。在下部面板是YLE PRO4，Val7和Thr8，之间的触点的紧密视图分别和TCR CDR环残基（枝颜色编码为在图1A）。截止3.4的氢键和4对于范德华联系。从31参考授权转载。rge.jpg"目标="_空白"&gt;点击此处查看该图的放大版本。 <img alt="图5" src="/files/ftp_upload/54991/54991fig5.jpg" /> 图5:HLA-A * 0201主办YLE，YLE-3A的构象比较，A2-YLE-5A肽。 （A）YLE（深绿色棒）和YLE-3A（橙色支）由HLA-A的叠加* 0201α1螺旋（灰色卡通）肽对齐。盒装残基表明Glu3的突变成丙氨酸。该插图显示Glu3Ala替代如何导致一个位置的邻居残留PRO4在A2-YLE-3A结构相比，A2-YLE结构转变（黑色箭头）。 （B）YLE（深绿色棒）和YLE-5A（粉红色支）由HLA-A * 0201α1螺旋（灰色卡通）的叠加肽对齐。盒装残基表明甘氨酸5的突变成丙氨酸。从参考许可转载<sup&gt; 31。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54991/54991fig5large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> TCR </td><td> CDR1α </td><td> CDR2α </td><td> CDR3α </td><td> CDR1β </td><td> CDR1β </td><td> CDR1β </td></tr><tr><td> PMEL17 </td><td> DSAIYN </td><td> IQSSQRE </td><td> CAVLSSGGSNYKLTFG </td><td> SGHTA </td><td> FQGTGA </td><td> CASSFIGGTDTQYFG </td></tr><tr><td> GP100 </td><td> TSINN </td><td> IRSNERE </td><td> CATDGDTPLVFG </td><td> LNHDA </td><td> SQIVND </td><td> CASSIGGPYEQYFG </td></tr><tr><td><str翁&gt; MPD </td><td> KALYS </td><td> LLKGGEQ </td><td> CGTETNTGNQFYFG </td><td> SGHDY </td><td> FNNNVP </td><td> CASSLGRYNEQFFG </td></tr><tr><td> 296 </td><td> DSASNY </td><td> IRSNVGE </td><td> CAASTSGGTSYGKLTFG </td><td> MNHEY </td><td> SMNVEV </td><td> CASSLGSSYEQYFG </td></tr></tbody></table> 表1:PMEL17 的TCR CDR3地区，GP100，MPD和296具体的gp100，电阻温度系数的对齐。从31参考授权转载。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> 肽序列 </td><td> 肽 </td><td> PMEL17 TCR TRAV21 TRBV7-3亲和杀敌 </td><td> GP100 TCR TRAV17 TRBV19阿菲无穷大杀敌 </td></tr><tr><td> YLEPGPVTA </td><td> YLE </td><td> 7.6±2微米</td><td> 26.5±2.3μM </td></tr><tr><td> YLEPGPVT V </td><td> YLE-9V </td><td> 6.3±1.2μM </td><td> 21.9±2.4μM </td></tr><tr><td> 一个 LEPGPVTA </td><td> YLE-1A </td><td> 15.9±4.1μM </td><td> 60.6±5.4μM </td></tr><tr><td> YL 一个 PGPVTA </td><td> YLE-3A </td><td>无约束力</td><td>无约束力</td></tr><tr><td> YLE 一个 GPVTA </td><td> YLE-4A </td><td> 19.7±1.3μM </td><td> 144.1±7.8μM </td></tr><tr><td> YLEP 一个 PVTA </td><td> YLE-5A </td><td> &gt; 1毫米</td><td> &gt; 1mM的</td></tr><tr><td> YLEPG 一个 VTA </td><td> YLE-6A </td><td> 11.4±2.7μM </td><td> 954.9±97.8μM </td></tR&gt; <tr><td> YLEPGP 一个 TA </td><td> YLE-7A </td><td> 31.1±4μM </td><td> 102.0±9.2μM </td></tr><tr><td> YLEPGPV A A </td><td> YLE-8A </td><td> 38.1±7.4μM </td><td> 121.0±7.5μM </td></tr></tbody></table> 表2:PMEL17 TCR的亲和力分析（K D）和GP100 TCR到的gp100 280-288肽变体。从31参考授权转载。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> 参数 </td><td> PMEL17 TCR-A2-YLE-9V </td><td> A2-YLE </td><td> A2-YLE-3A </td><td> A2-YLE-5A </td></tr><tr><td> PDB代码&lt;/ STRONG&gt; </td><td> 5EU6 </td><td> 5EU3 </td><td> 5EU4 </td><td> 5EU5 </td></tr><tr><td> 数据统计 </td><td></td><td></td><td></td><td></td></tr><tr><td>空间群</td><td> P1 </td><td> P1 21 1 </td><td> P1 </td><td> P1 21 1 </td></tr><tr><td>晶胞参数（） </td><td> A = 45.52，B = 54.41，C = 112.12，A = 85.0°，B = 81.6°，G = 72.6° </td><td> A = 52.81，B = 80.37，C = 56.06，B = 112.8° </td><td> A = 56.08，B = 57.63，C = 79.93，A = 90.0°，B = 89.8°，G = 63.8° </td><td> A = 56.33，B = 79.64，C = 57.74，B = 116.2° </td></tr><tr><td>辐射源</td><td> DIAMOND I03 </td><td> DIAMOND I03 </td><td> DIAMOND I02 </td><td> DIAMOND I02 </td></tr><tr><td>波长（埃） </td><td> 0.9763 </td><td> 0.9999 </td><td> 0.9763 </td><td> 0.9763 </td></tr><tr><td> Measu红色的分辨率范围（A） </td><td> 51.87 - 2.02 </td><td> 45.25 - 1.97 </td><td> 43.39 - 2.12 </td><td> 43.42 - 1.54 </td></tr><tr><td>外分辨率壳牌（） </td><td> 2.07 - 2.02 </td><td> 2.02 - 1.97 </td><td> 2.18 - 2.12 </td><td> 1.58 - 154 </td></tr><tr><td>观察思考</td><td> 128191（8,955） </td><td> 99442（7056） </td><td> 99386（7,463） </td><td> 244577（17745） </td></tr><tr><td>独特思考</td><td> 64983（4785） </td><td> 30103（2249） </td><td> 49667（3,636） </td><td> 67308（4,962） </td></tr><tr><td>完备性（％） </td><td> 97.7（96.7） </td><td> 98.5（99.3） </td><td> 97.4（96.7） </td><td> 99.6（99.9） </td></tr><tr><td>多重</td><td> 2.0（1.9） </td><td> 3.3（3.1） </td><td> 2.0（2.1） </td><td> 3.6（3.6） </td></tr><tr><td> I /西格玛（I） </td><td> 5.5（1.9） </td><td> 7.2（1.9） </td><td> 6.7（2。3） </td><td> 13（2.3） </td></tr><tr><td> RPIM（％） </td><td> 5.7（39.8） </td><td> 8.8（44.7） </td><td> 8.7（41.6） </td><td> 4.5（35.4） </td></tr><tr><td> - [R 合并 （％） </td><td> 7.8（39.6） </td><td> 9.8（50.2） </td><td> 8.7（41.6） </td><td> 5.0（53.2） </td></tr><tr><td> 细化统计 </td><td></td><td></td><td></td><td></td></tr><tr><td>决议（A） </td><td> 2.02 </td><td> 1.97 </td><td> 2.12 </td><td> 1.54 </td></tr><tr><td>不使用反射</td><td> 61688 </td><td> 28557 </td><td> 47153 </td><td> 63875 </td></tr><tr><td>在Rfree集无反射</td><td> 3294 </td><td> 1526 </td><td> 2514 </td><td> 3406 </td></tr><tr><td> - [R cryst（不切断）（％） </td><td> 18.1 </td><td> 19.7 </td><td> 17.2 </td><td> 17.0 </td></tr><tr><td> r 无 </td><td> 22.2 </td><td> 25.5 </td><td> 21.1 </td><td> 20.1 </td></tr><tr><td> 根均理想几何偏差平方 </td><td></td><td></td><td></td><td></td></tr><tr><td>键长（埃） </td><td> 0.018（0.019）* </td><td> 0.019（0.019）* </td><td> 0.021（0.019）* </td><td> 0.018（0.019）* </td></tr><tr><td>键角（°） </td><td> 1.964（1.939）* </td><td> 1.961（1.926）* </td><td> 2.067（1.927）* </td><td> 1.914（1.936）* </td></tr><tr><td>整体坐标误差（） </td><td> 0.122 </td><td> 0.153 </td><td> 0.147 </td><td> .055 </td></tr><tr><td>拉马钱德兰统计</td><td></td><td></td><td></td><td></td></tr><tr><td>最惠国待遇</td><td> 791（96％） </td><td> 371（98％） </td><td> 749（99％） </td><td> 384（98％） </td></tr><tr><td>允许的</td><td> 32（4％） </td><td> 6（2％） </td><td> 10（1％） </td><td> 5（1％） </td></tr><tr><td>离群值</td><td> 2（0％） </td><td> 3（1％） </td><td> 1（0％） </td><td> 2（0％） </td></tr></tbody></table> 表3: 数据缩减和细化统计（分子置换）。从31参考授权转载。括号中的数值是分辨率最高的外壳。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> HLA /肽残基 </td><td> TCR残留 </td><td> 第范德华（≤4Å） </td><td> 第氢键（≤3.4Å） </td></tr><tr><td> Gly62 </td><td> αGly98 </td><td> 3 </td><td></td></tr><tr><td></td><td> αSer99 </td><td> 1 </td><td></td></tr><tr><td> Arg65 </td><td> αSer99 </td><td> 2 </td><tD&gt; </td></tr><tr><td> Arg65Ø </td><td> αAsn100Nδ2 </td><td> 2 </td><td> 1 </td></tr><tr><td> Arg65 NH1 </td><td> βAsp58Oδ2 </td><td></td><td> 1 </td></tr><tr><td></td><td> βSer59 </td><td> 8 </td><td></td></tr><tr><td> Lys66 </td><td> αGly98 </td><td> 1 </td><td></td></tr><tr><td></td><td> αSer99 </td><td> 4 </td><td></td></tr><tr><td></td><td> αAsn100 </td><td> 4 </td><td></td></tr><tr><td> Ala69 </td><td> αAsn100 </td><td> 2 </td><td></td></tr><tr><td></td><td> βAla56 </td><td> 2 </td><td></td></tr><tr><td> Gln72Nε2 </td><td> βGln51Ø </td><td> 3 </td><td> 1 </td></tr><tr><td></td><td> βGly54 </td><td> 7 </td><td></td></tr><tr><td></td><td> βAla55 </td><td> 1 </td><tD&gt; </td></tr><tr><td> Thr73 </td><td> βGln51 </td><td> 1 </td><td></td></tr><tr><td> Val76 </td><td> βGln51 </td><td> 3 </td><td></td></tr><tr><td></td><td> βGly52 </td><td> 2 </td><td></td></tr><tr><td> Lys146 </td><td> βPhe97 </td><td> 3 </td><td></td></tr><tr><td></td><td> βIle98 </td><td> 3 </td><td></td></tr><tr><td> Ala150 </td><td> βIle98 </td><td> 1 </td><td></td></tr><tr><td></td><td> βAsp102 </td><td> 3 </td><td></td></tr><tr><td> Val152 </td><td> βIle98 </td><td> 1 </td><td></td></tr><tr><td> Glu154 </td><td> αTyr32 </td><td> 1 </td><td></td></tr><tr><td> Gln155ñ </td><td> αTyr32OH </td><td> 4 </td><td> 1 </td></tr><tr><td> Gln155Oε1 </td><td> βThr101ñ </td><td> 10 </td><td> 1 </td></tr><tR&gt; <td> Tyr1 OH </td><td> αGly97Ø </td><td> 1 </td><td> 1 </td></tr><tr><td></td><td> αGly98 </td><td> 1 </td><td></td></tr><tr><td></td><td> αSer96 </td><td> 1 </td><td></td></tr><tr><td> Glu3 </td><td> αTyr101 </td><td> 1 </td><td></td></tr><tr><td> PRO4 </td><td> αSer96 </td><td> 1 </td><td></td></tr><tr><td></td><td> αSer99 </td><td> 1 </td><td></td></tr><tr><td></td><td> αAsn100 </td><td> 4 </td><td></td></tr><tr><td> ØPRO4 </td><td> αTyr101ñ </td><td> 14 </td><td> 1 </td></tr><tr><td> Gly5 </td><td> αTyr101 </td><td> 3 </td><td></td></tr><tr><td></td><td> βGly100 </td><td> 2 </td><td></td></tr><tr><td> Val7 </td><td> βIle98 </td><td> 7 </td><td></td></tr><tr><td></td><td> βGly99 </td><td> 2</td><td></td></tr><tr><td></td><td> βGly100 </td><td> 2 </td><td></td></tr><tr><td> Thr8 </td><td> βThr31 </td><td>五</td><td></td></tr><tr><td></td><td> βGln51 </td><td> 1 </td><td></td></tr><tr><td></td><td> βPhe97 </td><td> 1 </td><td></td></tr><tr><td> Thr8ñ </td><td> βIle98Ø </td><td> 6 </td><td> 1 </td></tr></tbody></table> 表4:PMEL17 TCR-A2-YLE-9V联系表。从31参考授权转载。

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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.

利用X射线晶体学，生物物理学，和功能分析，以确定管理机制T细胞癌抗原的受体识别

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 ...

using-x-ray-crystallography-biophysics-functional-assays-to-determine

Universidad San Sebastian

Research

JoVE Journal

Immunology and Infection

11.4K 次观看.  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. 

视频: 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.

确定最佳人力Her2neu特异性CD8 + T细胞的细胞毒活性的比较CR51发行含量xCELLigence系统

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 ...

科研

免疫与感染

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.

一个实时，同步成像的TCR和其相关的信号转导蛋白的T​​IRF显微镜技术

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.

体外肿瘤细胞恢复对 chimeric 抗原受体 t 细胞抗肿瘤功能的预测评价

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

癌症研究

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.

定量高通量单细胞的细胞毒性T细胞的测定

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.

T细胞实时成像实时信号复合物的形成

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.

靶性抗原特异性治疗抗体的肿瘤及组织分布分析

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.

使用莱迪思光片显微镜可视化表面 T-Cell 受体动力学四维

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

生物化学

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.

测量TCR-的pMHC结合<em&gt;原位</em&gt;使用基于FRET的显微镜分析

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 ...

生物工程

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.

量化肿瘤球状体模型中抗体依赖性细胞毒性:药物发现应用

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.

化学抑制剂库筛选 t 细胞受体信号的中介识别

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

利用X射线晶体学，生物物理学，和功能分析，以确定管理机制T细胞癌抗原的受体识别

摘要

探索更多视频

此视频中的章节

确定最佳人力Her2neu特异性CD8 + T细胞的细胞毒活性的比较CR51发行含量xCELLigence系统

一个实时，同步成像的TCR和其相关的信号转导蛋白的TIRF显微镜技术

体外肿瘤细胞恢复对 chimeric 抗原受体 t 细胞抗肿瘤功能的预测评价

定量高通量单细胞的细胞毒性T细胞的测定

T细胞实时成像实时信号复合物的形成

靶性抗原特异性治疗抗体的肿瘤及组织分布分析

使用莱迪思光片显微镜可视化表面 T-Cell 受体动力学四维

测量TCR-的pMHC结合

量化肿瘤球状体模型中抗体依赖性细胞毒性:药物发现应用

化学抑制剂库筛选 t 细胞受体信号的中介识别

利用X射线晶体学，生物物理学，和功能分析，以确定管理机制T细胞癌抗原的受体识别

摘要

探索更多视频

此视频中的章节

确定最佳人力Her2neu特异性CD8 + T细胞的细胞毒活性的比较CR51发行含量xCELLigence系统

一个实时，同步成像的TCR和其相关的信号转导蛋白的T​​IRF显微镜技术

体外肿瘤细胞恢复对 chimeric 抗原受体 t 细胞抗肿瘤功能的预测评价

定量高通量单细胞的细胞毒性T细胞的测定

T细胞实时成像实时信号复合物的形成

靶性抗原特异性治疗抗体的肿瘤及组织分布分析

使用莱迪思光片显微镜可视化表面 T-Cell 受体动力学四维

测量TCR-的pMHC结合

量化肿瘤球状体模型中抗体依赖性细胞毒性:药物发现应用

化学抑制剂库筛选 t 细胞受体信号的中介识别

一个实时，同步成像的TCR和其相关的信号转导蛋白的TIRF显微镜技术