Name: determination of high-affinity antibody-antigen binding kinetics using four biosensor platforms
Uploaded: 2017-04-17T15:00:00.000+00:00
Duration: 15 min 27 s
Description: Watch this Scientific Journal Video about Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms at JoVE.com

作者感谢诺厄·迪托和亚当·迈尔斯有关IBIS MX96技术援助。

1.蛋白质和抗体<ol><li>如先前所述17生产和纯化可心类型9（PCSK9）人前蛋白转化酶枯草杆菌蛋白酶和10小鼠来源抗PCSK9的mAb。 </li><li>通过依次注入每个样品的10微克到使用UPLC系统19的分析型大小排阻（SEC）柱评估纯化产物的纯度。 </li></ol> 2.在的Biacore T100动力学测量<ol><li> 仪器和试剂准备 <ol><li>平衡在室温下将CM5传感器芯片15分钟。 </li><li>解冻的200mM 1-乙基-3-（3-二甲基氨基丙基）碳二亚胺盐酸盐（EDC）和在室温下的50mM N-羟基琥珀酰亚胺（NHS）的2个200μL等分试样两个200μL等分试样。 </li><li>制备1-L瓶1X HBS-EP的液（10mM HEPES [pH 7.4的]，150mM NaCl的，​​3mM的EDTA，和0.005％体积/体积的聚山梨醇酯P20）由二运行缓冲液粘固在水中的10倍HBS-EP +原液。 </li><li>在0.063微克在10mM乙酸钠（pH 4.5）和500每种mAb样品的制备μL1 mL蛋白质A / G中的30微克/毫升/ mL的在HBS-EP运行缓冲液。在冰上解冻人类PCSK9的冷冻瓶。 </li><li>在控制软件中，单击"工具|排屑"，将传感器芯片插入鞘和关闭。点击"工具|温度设置"，输入"25"°C作为分析温度和"10"°C作为车厢内温度。 </li></ol></li><li> 表面固定 <ol><li>在控制软件中，单击"文件|打开/新向导模板"，并从左侧面板的列表中选择"固定化"。 </li><li>点击"新建"，进入固定设置窗口。选择"CM5"作为芯片类型，并选择每个周期的"1"流动池。 </li><li>检查框每个"固定流动池1/2/3/4"以ACTIVA旁边TE上的选项。选择"瞄准固定的水平"和"胺"作为所有流细胞的方法。 </li><li>输入"30微克/姆·普罗阿/ G"作为配体，确保该目标电平被设定为"10000"个响应单位（RU）的所有流动池。 </li><li>选中"运行前总理"，然后单击"下一步"。选择"试剂架2"，定义相应的试剂和吸移管成单独的样品瓶的位置。插入机架回仪器，然后点击"开始"，然后输入一个实验名称保存到启动运行。 </li></ol></li><li> 分析物结合和再生循环 <ol><li>点击"文件|打开/新方法"，选择"20140812胡抗PCSK9的IgG结合hu PCSK9"，打开方法。查看该方法的参数。 </li><li>在"测定步骤"，保证有10个循环，其中"胡PCSK9"与"样品"在"Purp选择的名称OSE"。该复制数量被设置为‘1’。 </li><li>在"循环类型"中，设置接触时间为"220" S为捕捉1在流道"2"，"110" S用于捕捉2过流动路径"3"，和"55" S用于捕捉3以上流路"4"。流速是所有捕获的周期"10"μL/分钟。 </li><li>选择"样品1"，勾选"样品溶液"作为变量。设置的接触时间为"600" S和离解时间为"2700"结束了流动路径"1，2，3，4"。流速被设定为"30"μL/分钟。 </li><li>选择"再生1"，在溶液字段中输入"甘氨酸-HCl pH为1.5"，并设置所述接触时间为"20"结束了流动路径"1，2，3，4"。 </li><li>在 "变量设置" 中，输入2倍滴定 "100nM的 - 6.25 nM的" 的浓度周期1-3中， "为50nM - 3.12 nM的" 为周期4-8，和 "为5nM - 0.323 nM的" F或周期9-10。 </li><li>在"安装运行"，选择检测流道"2-1，3-1，4-1"，点击"下一步"，选中"运行前总理"，然后单击"下一步"。 </li><li>选择"样品和试剂机架1"，相应地定义为所用试剂的位置和移液管成单独的样品小瓶中。插入机架插入仪器，然后点击"开始"，然后输入一个实验名称保存到启动运行。 </li></ol></li><li> 数据分析使用BIA评价 <ol><li>点击"动力学/亲和性|表面结合"，选择FC"2-1"，"3-1"或"4-1"分开，并检查所有显示的曲线从各种分析物浓度，以及"零"浓度空白。 </li><li>点击"下一步"，获得缓冲减去空白曲线。然后点击"动力学"，选择"1:1结合"的模式，并点击"适合"获得拟合动能parameTER值。 </li><li>对于多个单克隆抗体表面的整体拟合，单击"多个存在的R 最大 "在底部，并从其他FCS添加结合曲线对于相同的单克隆抗体到列表中。 </li><li>点击"下一步"，以获取所有缓冲液空白扣除结合曲线。然后点击"动力学"，选择"1:1结合"的模式，并选择"适合当地的"为每个R 最大的参数，以获得整体拟合动力学参数。 </li></ol></li></ol> 3.在的Proteon XPR36动力学测量<ol><li> 仪器和试剂准备 <ol><li>平衡一个GLM传感器芯片和一个2-L瓶PBS-T-EDTA的（PBS [pH为7.4]，0.005％Tween-20的，和3mM EDTA）运行在室温下缓冲液中15分钟。 </li><li>在控制软件，点击"退出"，然后插入GLM芯片。将芯片温度为"25"℃，自动进样器温度为"10"℃。点击"甘油初始化"，并按照提示说明初始化芯片。 </li><li>点击"文件|打开"预调制协议从列表中，准备解决方案到96孔板。然后单击"运行"，选择协议，并单击"开始"。 </li><li>解冻的400mM EDC的一个1mL的等分试样并在室温下100mM的N-羟基（磺基-NHS）中的一个1毫升等分。 </li><li>在0.25微克/毫升，0.125微克/毫升，和0.063微克/毫升在PBS-T制备2蛋白A / G中的混合物在60微克/ mL，在10mM乙酸钠（pH 4.5）和500每种mAb样品的μL -EDTA运行缓冲液。在冰上解冻人类PCSK9的冷冻瓶。 </li></ol></li><li> 固定化，分析物结合和再生 <ol><li>点击"文件|新建|新协议"。在"配置"，进入实验的名称，选择"GLM"芯片，选择"微孔板"，然后输入"2.2"毫升体积。 </li><li>选择"协议|样片"，在井定义 "EDC /硫代NHS" 作为 "活化剂" H1-H6， "蛋白A / G"，如 "配体" 在G1-G6， "乙醇胺" 为 "钝化剂" F1-F6 "甘氨酸"，如E1-E6，PBS-T-EDTA "再生"， "为 "空白" 在D1-D6， "单克隆抗体X样品" 如 "" 在C1-C6，和 "配体人类PCSK9" 为" 分析物在孔H1-H6在第二个96-孔板中。 </li><li>选择在"协议编辑器"，"步骤"，双击"固定化"，步骤包括EDC /硫代NHS，蛋白A / G的三个后续水平注射和1M乙醇胺各自以"30"μL的流量/分钟，"300" S的接触时间。 </li><li>点击"再生"，注入三"18"在水平方向和垂直方向上的"100"μL/分钟，接着用两个"60" -s甘氨酸（pH值1.5）的脉冲在-s PBS-T-EDTA的脉冲"25" μL/分钟可在两个方向。 </li><li>点击"配体"，在使用的"25"μL/ min的流速和"160" S的接触时间在垂直方向注入单抗1抗体2。 </li><li>点击"分析物"，注入人类PCSK9的五个浓度（在100nM至6.25 nM的2倍连续稀释），并在同时6个水平通道空白缓冲液中，在"40"μL/ min的"600"的关联时间秒，然后通过解离时间"2700"秒。 </li><li>点击"再生"，注入两个"18"在水平方向和垂直方向上的"100"μL/分钟-s甘氨酸（pH值1.5）的脉冲。 </li><li>重复上述步骤，对于其余的mAb每个结合周期后。 注意:除了100nM的 - 6.25 nM的人类PCSK9浓度系列，25nM的 - 1.56和5nM - 0.313 nM的浓度系列被使用。 </li><li>根据试剂的位置制备样品和试剂在两块96孔板在步骤3.2.2所定义，然后点击"运行"选项卡，选择协议/实验，并单击"开始"。 </li></ol></li><li> 数据分析使用的Proteon经理 <ol><li>单击"面板类型"，然后选择"分析物"。然后点击"协议步骤"，然后选择列表中的所有结合曲线。 </li><li>点击"自动程序"，然后单击"进程|通道参考|中间点"。然后单击"进程|双基准|行| A6"。 </li><li>点击"创建数据集"，保存个人数据集对于每一个mAb在所有三个表面的动力学分析。 </li><li>点击"分析数据集"，突出每个单抗数据集，并单击"分析|动力学"。选择"朗缪尔"模式和"同步KA / KD"，然后单击"下一步"。 </li><li>突出两个结合和解离配合范围，选择"本地" R 最大 ，然后单击"下一步"完成这一配合获得拟合动力学参数。 </li><li>重复上述步骤，但选择"分组" R 最大为嵌合，以获得用于计算配体的表面活性实验读取最大值。 </li></ol></li></ol> 4.在八位RED384动力学测量<ol><li> 试剂和样品板制备 <ol><li>制备50毫升1×KB的（动力学缓冲液含有PBS pH值[7.4]，0.02％吐温-20，0.1％白蛋白和0.05％叠氮化钠）稀释在PBS中的10倍的原液。 </li><li>分配1X KB成以每孔200μL的96孔板。在这些单独的孔48水合物抗人捕获（AHC）的生物传感器的提示至少10分钟。 </li><li>在20微克/毫升，10微克/毫升，以及5微克/毫升在1×KB，以及人类PCSK9在从100nM的7个滴定浓度制备每种mAb样品至1.56 nM的2倍连续稀释。 </li><li>加载的mAb样品放入一个384孔倾斜底微孔板（referred作为试剂板）和人类PCSK9溶液加入到以每孔90μL的另一个384孔微孔板（被称为样品板）。 </li><li>负载系列1X KB的和甘氨酸（pH为1.5）在样品板内孔中的解决方案。 注意:这些1X KB井被用于芯片预处理，基线稳定，并分析分解。甘氨酸溶液用于再生。 </li></ol></li><li> 实验方法设置 <ol><li>在数据采集软件，点击"实验|新实验向导|新动力学实验通过|基本动力学"。 </li><li>在"板块定义"，按照下面的步骤来定义样品类型和位置。 <ol><li>选择"16"频道和"384好"的格式。 </li><li>通过按住左键点击Shift键在井同时突出16个孔限定在所述板显示的样品和试剂的位置。 </li><li>上点右键含有单克隆抗体的样品，并选择"装载"井，以表示在该单克隆抗体被加载（或捕获）到所述传感器AHC步骤。在表格右侧输入单抗名称和浓度。 </li><li>右击含有人PCSK9孔中，并选择"样品"来表示在该单克隆抗体捕获的传感器被浸渍和结合相互作用进行测量的步骤。进入右侧的表中相应的摩尔浓度。 </li><li>定义含有1x KB为"缓冲区"或"中和"，将孔与含有甘氨酸为"再生"的孔中。 </li></ol></li><li>在"化验定义"，按照下面的步骤来定义试验设置: <ol><li>点击"添加"，然后选择"基线"，"再生"，"平衡"，"加载"，"协会"和"解离"步骤列表以"30" S次，"30&quot; ， "18" S "200" S "500"，且 "1800" S，分别将摇速度是 "1000" 转。 </li><li>的步骤添加到"测定步骤列表"，在步骤第一次点击，然后在位于任一个样品或试剂板中的孔中。步骤如下: <ol><li>平衡 - 再生:前提的AHC传感器由"15" -s倾角的三个周期中的甘氨酸（pH为1.5）中，用"15"交替-s在1×KB骤降。 </li><li>加载:捕获mAb的样品到AHC传感器，用于"200"秒。 </li><li>基线:有关步骤之前建立"60" S的BLI信号。 </li><li>协会:浸传感器到含有不同浓度的人PCSK9的用于"500"关联-s期间井。 </li><li>解离:浸PCSK9结合的传感器为1个KB的新井为"1800" -s解离期。 </li><li>再生:浸MAB-PCSK9 BOU第二传感器成甘氨酸（pH值1.5）的两个"18"的孔-s每个结合周期之间的脉冲。 </li></ol></li></ol></li><li>在"回顾实验"，通过步骤滑动并回到以前的选项卡进行必要的更改。 </li><li>在"运行实验"，输入"60"的拖延时间并摇晃样品板而等待。设置板的温度为"25"℃，并按下"GO"。 </li></ol></li><li> 数据分析使用福特生物的数据分析软件 <ol><li>点击"数据选择|加载的数据|动力学| PCSK9抗体结合PCSK9 14年7月23日" </li><li>在"处理"，处理该数据，如下所示: <ol><li>在步骤1:单击"传感器选择"突出显示H1-H6传感器，右键单击它们，然后单击"更改传感器类型|引用传感器。" </li><li>在步骤2中，检查"减法"，然后选择"平均参考传感器";从平均的6个空白缓冲液传感器减去每个有源样品传感器。 </li><li>在步骤3中，点击"对齐Y轴"，选择"基线"对齐所有之前关联基线步骤中的结合曲线。 </li><li>在步骤5中，检查"Savitsky-格雷过滤"通过提高信噪比来平滑结合曲线，并点击"过程数据！"。 </li><li>在步骤6中，点击"处理结果"，以查看所处理的结合曲线。 </li><li>在步骤7，检查在每个处理步骤后显示所述结合曲线右侧的四个面板，并且点击"保存处理后的数据"。 </li></ol></li><li>在"分析"，勾选"协会与解离"，并选择"1:1"的模式。 </li><li>突出了"全球（全）"的"颜色"适合和他们组结合曲线。使用"R 最大连接"来执行组上涂覆有相同m个传感器装配抗体浓度，以获得用于计算配体的表面活性实验读取最大值，并且"R 最大值由传感器取消关联"，以在涂覆有多个的mAb浓度传感器执行全局拟合。 </li><li>点击"拟合曲线"获得安装动力学参数。在每个拟合分析结束保存结果。 </li></ol></li></ol> 5.在IBIS MX96动力学测量<ol><li> 仪器和试剂准备 <ol><li>平衡在室温下COOH-G芯片15分钟。 </li><li>制备1-L瓶系统的运行缓冲液（PBS [pH为7.4]，0.01％吐温20）和所述固定缓冲液（10mM乙酸钠[pH为5.0]，0.01％吐温20）的。 </li><li>通过在这两个系统中运行缓冲液和乙酸钠（pH5.0）中固定化缓冲液2倍系列稀释从20微克/毫升制备每种mAb至0.16微克/毫升。 </li><li>分配的mAb样品分成两月arate 96孔板，其中每种mAb占用8个垂直孔中以每孔200μL的滴定浓度。 </li><li>的400mM EDC和100mM磺基-NHS的解冻等分试样在室温下。 </li><li>制备蛋白A / G的300μL，在50μg/ mL的在乙酸钠（pH5.0）中固定缓冲液和吸液管它到小瓶中。 </li><li>通过在运行缓冲液的系统2倍系列稀释从100nM的制备人类PCSK9的200μL至0.39纳米。吸取它们放在不同的小瓶。 </li></ol></li><li> 与胺偶联的抗体阵列的多周期动力学 <ol><li>混合EDC /硫代NHS（400毫摩尔/ 100毫米）的等分试样，并将该混合物分配到顶部48个孔一个新的96孔板的每孔加入200μL。 </li><li>放置在第2位的单克隆抗体源板（稀释在乙酸钠[pH为5.0]），并在打印机内部位置1处的EDC /硫代NHS试剂板。 </li><li>安装所述传感器芯片到CFM。打开 "CFM 2.0" software，然后单击"加载设置| 96胺夫妇"。 10×8抗体阵列被创建如下: <ol><li>递送EDC /硫代NHS在试剂板使用48个微通道的传感器的上半部分，和循环它们在传感器表面上方为"5"分钟。 </li><li>递送在源板到传感器和循环它们穿过活化的表面，用于"10"分钟的上半部分的单克隆抗体的样品。 </li><li>从50mL的锥形管中在抗体表面为"5"分钟递送固定缓冲液。 </li><li>重复在源板的底部一半的剩余样品的mAb上述程序。 </li></ol></li><li>停靠印刷传感器芯片到仪器中。在控制软件中，单击"文件|连接|打开测量|现有的测量"，选择"2014年8月15日"。 </li><li>在"常规"，选择"G - 系统总理""全系统脚本"下。然后选择"G - QuencH"通过注入150μL的1M乙醇胺以停用的mAb表面。 </li><li>点击"相机"以可视化的单克隆抗体阵列并在必要时调整对比度。放置红色方框包围的单克隆抗体斑点，移动绿色方框位于用于参照单抗活跃点之间的interspots。 </li><li>在"分析周期"，选择 - 在"IBIS脚本""A AP标准执行"。设置基线1.0分钟，10.0分钟用于关联，和在8μL/ s的速度为解离90层的步骤。 </li><li>内部的"循环"，注入人类PCSK9一种浓度在下列五个缓冲液注射的时间。再生与每个结合周期之间甘氨酸pH为2.0的单克隆抗体的表面。 </li></ol></li><li> 与Fc的捕获抗体阵列单周期动力学 <ol><li>安装一个新的传感器芯片到CFM。重复步骤5.2.3至通过与蛋白A / G取代的mAb样品以上5.2.5。 </li><li>去除从MX96传感器芯片，并插入它放回CFM打印机。 </li><li>递送的mAb在板使用48个微通道中的蛋白A / G传感器表面的上半部分，和循环它们跨越使用双向流动10分钟的表面。 </li><li>重复在板的底部的一半的剩余样品的mAb上述步骤。 </li><li>停靠印刷传感器芯片到MX96仪器。在数据采集软件，单击"文件|连接|打开测量|现有测量|下一步"，选择"蛋白A + G结合kinetic7.30.14"。 </li><li>点击"相机"以可视化的单克隆抗体阵列并在必要时调整对比度。放置红色方框包围的单克隆抗体斑点，移动绿色方框位于用于参照单抗活跃点之间的interspots。 </li><li>在"分析周期"，选择 - 在"IBIS脚本""A AP标准执行"。设置为"1.0分钟"为基准，"10.0分"用于关联，和‘8μL/秒‘的速度10’在解离步骤’。 </li><li>内部的"循环"，注入人类PCSK9一种浓度在下列五个缓冲液注射的时间。否再生每一分析物注射之间执行。 </li></ol></li><li> 数据分析使用Sprint和洗涤器 <ol><li>在SprintX sofware，单击"文件|打开三角文件"，选择列表中的全部样本，并分析"后再点击"检查"保存SprintX文件"，"校正"和"RLL决心"。 注:RLL值是指在传感器表面上固定化的/捕获的mAb水平。 </li><li>检查"引用"，然后选择"本地"，使用相邻的参考点。还要检查第一次注射"对齐"，然后单击"开始自动化。" </li><li>在这种串行卡，"工具栏上显示标尺"，选择对其进行调整选择基线之前立即第一样品注射的小区域，并选择"零"。 </li><li>通过选择"导出到文件IBMX"，然后单击生成用于洗涤器中分析的.IBMX文件"开始自动化。" </li><li>启动洗涤器并加载.IBMX文件。输入"100N"为"股票浓"和"2"作为"稀释因子"。 </li><li>作物数据，删除之前喷射的开始所有基线，并在关联的起始对齐的结合曲线。 注:对于单周期动力学实验，不对齐的曲线。 </li><li>转到"动力学"标签中，调整为喷射结束时间标尺，选择"K d"和配合，然后"固定杀敌 "。选择"K A K D"，并再次适应它。 </li><li>浮第k d柱和再装配，以进一步细化配合。 注:对于单周期结合曲线的嵌合，点击"选择采用"并取消选择"减"，然后选择"独立"和漂浮"开始汽化室"栏目，以适应联想型材回到理论基础的起源。 </li><li>审查结果选项卡的安装参数的影响。 </li></ol></li></ol>

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我们的头对头比较研究表明，每一个传感器平台都有自己的长处和短处。尽管抗体的结合轮廓是通过视觉比较相似（ 图3 - 6），并且将获取的动力学速率常数的排列顺序是在整个工具高度一致（ 图7），我们的结果表明，基于SPR的文书连续流动流体）是在解决具有较慢解离速率高亲和力相互作用更好。在解离相向上漂移在数据集观察到（ 例如 ，单克隆抗体2，单抗5，和mAb 9; 图5）通过BLI自由流体的仪器产生的。这一发现可以在很大程度上超过在微板中，这是该系统的一个主要限制时间归因于样品蒸发。与此固有的限制，实验时间也被限制为小于12个小时;因此，实验用的sh编程orter倍相比，那些的其它平台（10分钟关联和45分钟解离）（500秒关联和30分钟解离）。然而，缩短实验时间并未以减轻对数据质量/一致性蒸发的影响，如由基于BLI-仪器所产生的速率常数显示出较少的线性度如在一些离速率的波动的结果（ 图8C ）。除了样品蒸发，在所使用的捕获试剂的差异可能也有助于在得到的结果的差异。虽然在所有三个基于流体-SPR平台使用蛋白A / G，AHC传感器在非流体BLI平台中使用。因为蛋白A / G是可能对所述的单克隆抗体并不比AHC，基于抗体的生物传感器表面，从所述蛋白A / G表面上的单克隆抗体 - 抗原复合物的解离速率可人为地出现比更快亲和力较弱从AHC表面获得。这种可能性支持By中的实验数据显示，通过BLI平台所产生的解离速率值比从其他仪器（ 图7， 红色线 ）得到的那些一致地低。尽管如此，BLI平台具有比其他平台不同的优势。例如，它是相对于传感器的选择和测定配置高度灵活由于可即时使用的各种预涂覆的传感器。在我们的实验中，使用AHC传感器，消除了配体固定步骤的需求，降低了准备时间。此外，相比于其他流体SPR平台，其特点复杂油管和值开关配置的BLI平台需要更少的维护。此功能对于涉及原油样品，可能会导致堵塞和污染问题实验的优势。 至于治疗的候选人增加高效，快速，准确鉴定的需求，需要对BIθ传感器吞吐量也不断提高。在四个生物传感器平台上，从能够96-配体阵列打印的生物传感器的吞吐量是最高，其次由耦合到一个十字交叉36 - 配体格式和与16信道同时读出所述基于BLI的生物传感器的生物传感器，其最终增加在单一结合循环中测量到96，分别为36和16，交互的数量。这些可以通过能力比传统SPR平台，这是由仅具有4通过单个串行流连接流动池限定的显著更高。由于我们的实验中所涉及的在与长的解离时间的多个表面密度评价10个单克隆抗体相对较小的样本集，器乐吞吐量在确定实验的效率发挥适度的作用。有在三个高通量平台的实验时间没有显著差异，在所有情况下，实验是在一天内完成。在另一方面，传统的串行流SPR实验需要3天完成，尽管设置之后，数据采集的步行路程自动化。在涉及（在数百或数千IE）大量样品的，对于离率排名/动力学筛选或表位分级的目的等的研究，吞吐量成为一个关键因素。 虽然在IBIS MX96吞吐量比其他生物传感器的高几个数量级，因此对于这些目的的最佳选择，它有几个缺点。特别地，由CFM阵列印刷示出大的表面的不一致（ 图1）和降低的数据再现性（ 图8D和图8E）。为了精确动力学测量，在生物传感器表面上的配体的量是需要被控制，以确保结合反应不是由次要因素如干扰的关键参数传质或空间位阻。对于T100的Biacore和的Proteon XPR36，基于如在研究第17条中所述集合R 最大值的标准计算确定了最佳R L的水平。在另一方面，对于八比特组RED384和IBIS MX96平台，被获得的单克隆抗体捕获水平凭经验利用在恒定时间进行一系列2倍连续稀释的抗体。缺乏知识或捕获步骤的控制的导致了高密度的表面，并且可能已受到损害的动力学速率常数的精度高的结合的响应信号（ 图2）。此外，从SPR检测器的打印机的分离进行涉及再生的多个结合周期测量时也提出了挑战。执行多周期动力学设置的唯一方法是通过mAb的直接胺偶联，而不是被固定化的蛋白A / G通过的mAb的Fc来捕获表面在其他三个生物传感器平台。其结果是，需要一个额外的再生侦察实验，以确定最佳的再生条件。这种设置的结果是有联系的一个〜低90％观察到的表面活性相比于Fc捕获方法（ 图9）中，除了较长的实验时间。要执行的Fc捕获方法，另一种单周期动力学的方法获得通过。这种方法涉及分析物在每次注射（ 图2）之间的增加的浓度没有再生的顺序注射。这非常方便，但较不常见施加方法不仅缩短实验时间和减少的试剂消耗，而且也产生了动力学速率常数高度相似于那些来自其它生物传感器（ 图7）。因此，在应用该单周期动力学方法克服了仪器的固有构造限制和提供了一个机会在高通量的方式获得高分辨率的动力学速率常数。 尽管吞吐量是在T100的Biacore一个主要的限制，我们的结果共同表明它产生的最一致的数据以最高的质量。这之后通过的Proteon XPR36，其具有约10倍更高的吞吐量。表征高亲和力的抗体 - 抗原相互作用，当仪器的检测限达到可技术上具有挑战性当其以产生高质量的数据能力变得具有优势。而在八位RED384的仪器的系统的限制阻碍解离速率常数的精确测量（ 即 ，低于灵敏度的解决慢解离速率足够的信号衰减），两者的Biacore T100和的Proteon XPR36可以提供敏感和可靠检测分化。

The acquisition of reliable kinetic parameters for characterizing antibody-antigen interactions is an essential component of the drug discovery and development process1. Optical Surface Plasmon Resonance (SPR) biosensors, the "gold standard" for real-time detection of these interactions, have been used for approximately two decades to enable early selection of criteria-meeting therapeutic antibody candidates2,3. In addition to providing an affinity ranking of antibody candidates by the rapid binding screening of crude supernatants4, and rigorous kinetic constant determinations of purified preparations5, biosensors can further differentiate the functional activity of lead candidates via epitope binning studies6,7. 
To meet the growing demand of antibody-based products for various therapeutic indications8, a wide variety of innovative biosensor instruments have been developed in recent years that increase the efficiency of candidate identification and characterization9,10. These instruments differ in microfluidic channel configuration design and/or in the optical principles involved in detecting biomolecular interactions. Specifically, the Octet RED38411, ProteOn XPR3612, and IBIS MX967 have expanded the number of interactions measured in a single binding cycle to 16, 36, and 96 respectively, representing significant throughput improvements over the traditional Biacore platform. Although these various biosensor platforms all provide essential kinetic data for characterizing antibody-antigen interactions, they differ in experimental setup and operational procedures due to variations in instrumental configurations. For example, in the IBIS MX96's SPR imaging array platform, the multiplex ligand immobilization step is performed in an off-line mode in an external printing device separate from the detector7,13; in contrast, the other three biosensor platforms utilize an "all-in-one" setup, where the addition of component onto the sensor surface, whether it is the activation reagent, ligand, or analyte, is recorded in real time and through pre-programmed commands in sequential order. In the Octet RED384, a unique feature of this BioLayer Interferometry (BLI)-based platform is the availability of pre-coated optical fiber biosensors for immediate "dip-and-read" use14, eliminating the need for ligand surface preparation and initiation/conditioning steps, which are often required for the sensor chips in SPR-based platforms. This instrument's fluidic-free design also simplifies the mechanics and avoids clogging and contamination concerns when dealing with crude samples. With the novel 6 x 6 crisscrossing fluidic design in the ProteOn XPR36, a "one-shot" kinetics approach can be implemented by switching the flow channels between horizontal and vertical directions to create 36 interaction spots15. Instead of assessing binding kinetics one ligand or analyte concentration at a time, as is done in the traditional serial flow Biacore T100 platform, this approach offers the ability to monitor up to 36 different interactions simultaneously in a single binding cycle. 
Despite their differences, these four biosensor platforms are all widely used by many laboratories worldwide. For new users with little hands-on biosensor experience, deciding which instrument to use can be a challenging task given the differences in instrumental design. To determine the most appropriate instrument for their research purposes, factors such as data quality, performance consistency, throughput, ease of operation, and material consumption need to be considered collectively. While several benchmark studies have explored the variability of kinetic rate constants obtained from multiple laboratories and biosensors5,16, a recently published head-to-head comparison study further addresses the systematic factors that influence data reliability from the instrumental performance point of view17,18. The protocols supplied in this video focus on the experimental setup and procedures in detail, and are accompanied by the research article entitled, "Comparison of biosensor platforms in the evaluation of high affinity antibody-antigen binding kinetics"17. These protocols are intended not only to help new biosensor users implement these instruments for their research purposes, but also to provide additional insights for current biosensor users regarding technical challenges and considerations in experimental designs for evaluating high-affinity antibody-antigen interactions.

<table><tbody><tr><td>Biacore T100 System</td><td>GE Healthcare</td><td>28975001</td><td>The T100 system has been upgraded to T200</td></tr><tr><td>CM5 Sensor Chip&amp;nbsp;</td><td>GE Healthcare</td><td>BR100012</td><td></td></tr><tr><td>BIAevaluation&amp;nbsp;</td><td>GE Healthcare</td><td></td><td>Version 4.1</td></tr><tr><td>Biacore T100 Control Software</td><td>GE Healthcare</td><td></td><td>The T100 control software has been upgraded to T200</td></tr><tr><td>Amine Coupling Kit</td><td>GE Healthcare</td><td>BR100050&amp;nbsp;</td><td>It contains: 750 mg 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC), 115 mg N-hydroxysuccinimide (NHS), 10.5 mL 1.0 M ethanolamine-HCl pH 8.5&amp;nbsp;</td></tr><tr><td>HBS-EP+ Buffer 10&amp;times;</td><td>GE Healthcare</td><td>BR100669</td><td>Concentrated stock solution&amp;nbsp;</td></tr><tr><td>Plastic Vials, o.d. 7 mm</td><td>GE Healthcare</td><td>BR100212&amp;nbsp;</td><td></td></tr><tr><td>Rubber Caps, type 3</td><td>GE Healthcare</td><td>BR100502</td><td></td></tr><tr><td>Plastic Vials and Caps, o.d. 11 mm</td><td>GE Healthcare</td><td>BR100214&amp;nbsp;</td><td></td></tr><tr><td>ProteOn XPR36 Protein Interaction Array System</td><td>Bio-Rad</td><td>1760100</td><td></td></tr><tr><td>ProteOn Manager Software&amp;nbsp;</td><td>Bio-Rad</td><td>1760200</td><td>Version 3.1.0.6</td></tr><tr><td>GLM Sensor Chip</td><td>Bio-Rad</td><td>1765012</td><td></td></tr><tr><td>Amine Coupling Kit</td><td>Bio-Rad</td><td>1762410</td><td>It includes EDAC (EDC), sulfo-NHS, ethanolamine HCl&amp;nbsp;</td></tr><tr><td>Regeneration and Conditioning Kit and Buffers</td><td>Bio-Rad</td><td>1762210</td><td>It includes 1 each glycine buffer (pH 1.5, 2.0, 2.5, 3.0), and NaOH, SDS, HCl, phosphoric acid, NaCl; 50 mL each solution&amp;nbsp;</td></tr><tr><td>2 L PBS/Tween/EDTA buffer</td><td>Bio-Rad</td><td>1762730</td><td>It includes hosphate buffered saline (PBS), pH 7.4, 0.005% Tween 20, 3 mM EDTA&amp;nbsp;</td></tr><tr><td>Octet RED384 System</td><td>Fort&amp;eacute;Bio</td><td></td><td></td></tr><tr><td>Data Analysis Software</td><td>Fort&amp;eacute;Bio</td><td></td><td>Version 9.0.0.4</td></tr><tr><td>Dip and Read Anti-hIgG Fc Capture (AHC) Biosensors</td><td>Fort&amp;eacute;Bio</td><td>18-5060</td><td>One tray of 96 biosensors&amp;nbsp;</td></tr><tr><td>384-Well Tilted-Bottom Plate&amp;nbsp;</td><td>Fort&amp;eacute;Bio</td><td>18-5080</td><td></td></tr><tr><td>Biosensor Dispenser</td><td>Fort&amp;eacute;Bio</td><td>18-5016</td><td></td></tr><tr><td>Kinetics Buffer 10x</td><td>Fort&amp;eacute;Bio</td><td>18-1092</td><td>10x concentration. Contains ProClin 300.&amp;nbsp;</td></tr><tr><td>IBIS MX96 SPRi System</td><td>Wasatch Microfluidics</td><td></td><td></td></tr><tr><td>Microfluidics Continuous Flow Microspotter (CFM) Printer</td><td>Wasatch Microfluidics</td><td></td><td>Version 2.0</td></tr><tr><td>SensEye COOH-G chip</td><td>Wasatch Microfluidics</td><td></td><td>1-09-04-004</td></tr><tr><td>Data Analysis Software</td><td>Wasatch Microfluidics</td><td></td><td>Version 6.19.3.17</td></tr><tr><td>SPRint Data Analysis Software</td><td>Wasatch Microfluidics</td><td></td><td>Version 6.15.2.1</td></tr><tr><td>Scrubber 2</td><td>BioLogic Software</td><td></td><td>Version 2</td></tr><tr><td>Pierce Recombinant Protein A/G</td><td>ThermoFisher Scientific</td><td>21186</td><td></td></tr></tbody></table>

determination of high-affinity antibody-antigen binding kinetics using four biosensor platforms

无标签的光学生物传感器是在药物发现的生物分子相互作用的表征功能强大的工具。在这项研究中，我们描述了在我们的实验室进行评估的结合亲和力和对人前蛋白转化酶枯草杆菌蛋白酶Kexin 9型十大高亲和力的单克隆抗体（mAb）（PCSK9）的动力学使用四个常规使用的生物传感器平台。虽然两者的Biacore T100和的Proteon XPR36从成熟的表面等离子体共振（SPR）技术衍生，前者具有串行流构造连接的四个流动池，在平行通过一个简易6×6十字形而后者呈现36个反应斑点微流体通道的配置。的IBIS MX96也控制装置根据上述SPR传感器技术，具有一个额外的成像特征是，在空间方向提供检测。这再加上连续流动Microspotter（CFM）检测技术通过e显著扩展的吞吐量同时nabling 96个反应运动多路复用阵列印刷和检测。与此相反，八位位组RED384是基于生物层干涉测量（BLI）光学原理，使用光纤探针作为生物传感器来检测干涉图案时在尖端表面结合相互作用发生变化。不同于基于SPR的平台上，BLI系统不依赖于连续流射流;替代地，传感器尖端收集读数，同时它们的轨道搅拌期间浸没在384孔微孔板的分析物溶液。 每一种生物传感器平台都有自己的优点和缺点。提供的这些工具来提供优质的动力学数据，所描述的协议说明了使用相同的测定形式和相同的高品质的试剂来表征抗体 - 抗原动力学适合的简单的1实验能力的直接比较:1分子相互作用模型。

图1示出了从CFM和斑点单抗水平，抗体阵列图像由两个固定化方法，和图2显示了这些单克隆抗体的阵列从所述多循环在MX96产生的动能的相应的结合传感图和单周期动力学测量。实时结合和从在四个生物传感器平台上产生的多个抗体包被的表面动力学拟合曲线示于图3 - 6。 图7示出了从这些结合曲线全局分析获得的最终动力学速率和平衡结合常数的比较。单个关联（K A），解离（K d）和平衡（K D）结合常数列于表1中。为了证明在同一台仪器内产生的数据集的可变性， <st荣&gt;图8示出K A，K D，和Kð的曲线图在不同的mAb表面密度，而图9进一步比较跨过生物传感器平台上的mAb表面的计算的结合活性。 <img alt="图1" src="/files/ftp_upload/55659/55659fig1.jpg" /> 的胺偶联（A）和Fc-捕获从CFM打印（B）抗体曲面在IBIS MX96图1.多重配体阵列。印刷阵列的图像被显示在左侧面板，在由红色正方形包围的灰色区域表示抗体的存在。位于有源抗体点之间的较暗interspots用于参照扣除。每列包含在鉴定下方和所述图像的左侧的滴定浓度印刷的抗体。印刷抗体通过计算二量化的量fference在有源和参考位置之间的本体移位被示出在右侧面板。 <a href="http://ecsource.jove.com/files/ftp_upload/55659/55659fig1large.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/55659/55659fig2.jpg" /> 图2比较的实时从多周期（A）结合传感和单周期（B）在IBIS MX96动力学实验。人类PCSK9的以增加整个10×8抗体阵列浓度连续注射每个对应的传感段，如上所述。 <a href="http://ecsource.jove.com/files/ftp_upload/55659/55659fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图3" src="/files/ftp_upload/55659/55659fig3.jpg" /> <st荣&gt;图3.绑定捕获抗体与人PCSK9和1相互作用的传感图:1个动力学模型拟合叠加在的Biacore T100。该相互作用在高（ 上图），中期（ 中图），和低（ 底部面板）密度表面进行评价。所述覆盖光滑的黑色的线表示在不同的人类PCSK9浓度（彩色线条）到1的结合的响应信号的动力学拟合:1相互作用模型。 <a href="http://ecsource.jove.com/files/ftp_upload/55659/55659fig3large.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/55659/55659fig4.jpg" /> 图4.结合的捕获抗体与人PCSK9和1相互作用的传感图:1个动力学模型拟合叠加在的Proteon XPR36。该相互作用在高（ 上图），MEDI评价UM-（ 中图），和低（ 底部面板）密度表面。所述覆盖光滑的黑色的线表示在不同的人类PCSK9浓度（彩色线条）到1的结合的响应信号的动力学拟合:1相互作用模型。 <a href="http://ecsource.jove.com/files/ftp_upload/55659/55659fig4large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图5" src="/files/ftp_upload/55659/55659fig5.jpg" /> 图5.绑定捕获抗体与人PCSK9和1相互作用的传感图:1个动力学模型拟合叠加在八位RED384。该相互作用在高（ 上图），中期（ 中图），和低（ 底部面板）密度表面进行评价。所述覆盖红色线表示在不同的人类PCSK9浓度（彩色线条）的结合的响应信号的动力学拟合至1:<html> 1个相互作用模型。 <a href="http://ecsource.jove.com/files/ftp_upload/55659/55659fig5large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图6" src="/files/ftp_upload/55659/55659fig6.jpg" /> 图6.绑定胺偶联（A）和Fc捕获的（B）的抗体与人PCSK9和1相互作用的传感图:1个动力学模型拟合叠加在IBIS MX96。结合型材被组织为遵循图1中的阵列板10层地图×8的面板。黑线表示在不同的人类PCSK9浓度所记录的结合响应信号，并且叠加红色线表示拟合曲线。 <a href="http://ecsource.jove.com/files/ftp_upload/55659/55659fig6large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 古尔7&quot; SRC = "/文件/ ftp_upload / 55659 / 55659fig7.jpg"/&gt; 图7.协会比较K A（A），解离ķD（B），和均衡ķD（C）由所述四个生物传感器平台生成结合常数。 6 -动力学参数是从图3中的结合曲线的全局分析的。该仪器表示为如下:的Biacore T100（蓝色），的Proteon XPR36（绿），八位位组RED384（红），IBIS MX96，胺偶联（紫色），和IBIS MX96，FC-捕获（橙色）。 <a href="http://ecsource.jove.com/files/ftp_upload/55659/55659fig7large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图8" src="/files/ftp_upload/55659/55659fig8.jpg" /> 图8.在在BIAC的多个抗体表面密度比较动力学速率常数的一致性的<html>矿石T100（A），的Proteon XPR36（B），八位位组RED384（C），IBIS MX96，胺偶联（D），和IBIS MX96，FC-捕获（E）。动力学参数K A（ 顶部子板）中，k D（ 中间子板）和K D（ 底部子板）从个别抗体表面密度组分析的。 <a href="http://ecsource.jove.com/files/ftp_upload/55659/55659fig8large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图9" src="/files/ftp_upload/55659/55659fig9.jpg" /> 图 中四个生物传感器平台的抗体曲面及其标准差（误差条）9.结合活性。该值是使用在研究文章17描述公式计算。large.jpg"目标=‘_空白’&gt;点击此处查看该图的放大版本。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td rowspan="2"></td><td> K A </td><td> 杀敌 </td><td> 杀敌 </td></tr><tr><td> （M -1 S -1） </td><td> （秒-1） </td><td> （nm）的 </td></tr><tr><td> 单抗1 </td><td> 11.7（7.8）×10 5 </td><td> 4.89（4.18）×10 -5 </td><td> 0.052（0.05） </td></tr><tr><td> 单抗2 </td><td> 1.53（0.28）×10 5 </td><td> 1.30（1.54）×10 -5 </td><td> 0.092（0.12） </td></tr><tr><td> 3单抗 </td><td> 11.4（8.3）×10 5 </td><td> 27.6（11.0）×10 -5 </td><td> 0.333（0.20） </td></tr><tr><td> 单抗4 </td><td> 3.61（1.6）×10 5 </td><td> 20.1（12.3）×10 -5 </td><td> 0.659（0.54） </td></tr><tr><td> 5单抗 </td><td> 0.59（0.21）×10 5 </td><td> 3.46（2.50）×10 -5 </td><td> 0.663（0.46） </td></tr><tr><td> 6单抗 </td><td> 1.19（0.78）×10 5 </td><td> 7.21（3.83）×10 -5 </td><td> 0.894（0.64） </td></tr><tr><td> 单抗7 </td><td> 1.29（0.53）×10 5 </td><td> 16.4（5.63）×10 -5 </td><td> 1.57（1.02） </td></tr><tr><td> 8单抗 </td><td> 4.02（2.23）×10 5 </td><td> 22.8（10.7）×10 -5 </td><td> 0.768（0.68） </td></tr><tr><td> 单抗9 </td><td> 4.20（2.13）×10 5 </td><td> 6.67（4.3）×10 -5 </td><td> 0.197（0.16） </td></tr><tr><td> 单克隆抗体10 </td><td> 1.20（0.49）×10 5 </td><td> 12.5（7.64）×10 -5 </td><td> 1.27（0.80） </td></tr></tbody></table> 表1: 动态速率和平衡结合的由四个生物传感器仪器到1结合曲线的全球拟合得到10个单抗常数:1相互作用模型。

Watch this Scientific Journal Video about Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms at JoVE.com

Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms

在这里，我们描述了抗原抗体的结合亲和力和使用四种常用的生物传感器平台动力学测量协议。

高亲和力抗体 - 抗原的结合动力学的测定，使用四个生物传感器平台

Label-free optical biosensors are powerful tools in drug discovery for the characterization of biomolecular interactions. In this study, we describe the ...

determination-high-affinity-antibody-antigen-binding-kinetics-using

Research

JoVE Journal

Biochemistry

20.6K 次观看.  Boehringer Ingelheim Pharmaceuticals, Inc.. 在这里，我们描述了抗原抗体的结合亲和力和使用四种常用的生物传感器平台动力学测量协议。 

视频: Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms

Bio-layer Interferometry for Measuring Kinetics of Protein-protein Interactions and Allosteric Ligand Effects

We describe the use of Bio-layer Interferometry to study inhibitory interactions of subunit &#949;&#160;with the catalytic complex of Escherichia coli&#160;ATP synthase. Bacterial F-type ATP synthase is the target of a new, FDA-approved antibiotic to combat drug-resistant tuberculosis. Understanding bacteria-specific auto-inhibition of ATP synthase by the C-terminal domain of subunit &#949;&#160;could provide a new means to target the enzyme for discovery of antibacterial drugs. The C-terminal domain of &#949;&#160;undergoes a dramatic conformational change when the enzyme transitions between the active and inactive states, and catalytic-site ligands can influence which of &#949;&#39;s conformations is predominant. The assay measures kinetics of &#949;&#39;s binding/dissociation with the catalytic complex, and indirectly measures the shift of enzyme-bound &#949;&#160;to and from the apparently nondissociable inhibitory conformation. The Bio-layer Interferometry signal is not overly sensitive to solution composition, so it can also be used to monitor allosteric effects of catalytic-site ligands on &#949;&#39;s conformational changes.

The protocols here describe kinetic assays of protein-protein interactions with Bio-layer Interferometry. F-type ATP synthase, which is involved in cellular energy metabolism, can be inhibited by its &#949; subunit in bacteria. We have adapted Bio-layer Interferometry to study interactions of the catalytic complex with &#949;&#8217;s inhibitory C-terminal domain.

生物层干涉测量的蛋白质 - 蛋白质相互作用和变构配体反应动力学的影响

We describe the use of Bio-layer Interferometry to study inhibitory interactions of subunit &#949;&#160;with the catalytic complex of Escherichia ...

科研

化学

An ELISA Based Binding and Competition Method to Rapidly Determine Ligand-receptor Interactions

A comprehensive understanding of signaling pathways requires detailed knowledge regarding ligand-receptor interaction. This article describes two fast and reliable point-by-point protocols of enzyme-linked immunosorbent assays (ELISAs) for the investigation of ligand-receptor interactions: the direct ligand-receptor interaction assay (LRA) and the competition LRA. As a case study, the ELISA based analysis of the interaction between different lambda interferons (IFNLs) and the alpha subunit of their receptor (IL28RA) is presented: the direct LRA is used for the determination of dissociation constants (KD values) between receptor and IFN ligands, and the competition LRA for the determination of the inhibitory capacity of an oligopeptide, which was designed to compete with the IFNLs at their receptor binding site. Analytical steps to estimate KD and half maximal inhibitory concentration (IC50) values are described. Finally, the discussion highlights advantages and disadvantages of the presented method and how the results enable a better molecular understanding of ligand-receptor interactions.

The presented protocols describe two enzyme-linked immunosorbent assay (ELISA) based techniques for the rapid investigation of ligand-receptor interactions: The first assay allows the determination of dissociation constant between ligand and receptor. The second assay enables a rapid screening of blocking peptides for ligand-receptor interactions.

的ELISA基结合和竞争法快速测定配体 - 受体相互作用

A comprehensive understanding of signaling pathways requires detailed knowledge regarding ligand-receptor interaction. This article describes two fast and ...

Characterization of Glycoproteins with the Immunoglobulin Fold by X-Ray Crystallography and Biophysical Techniques

Glycoproteins on the surface of cells play critical roles in cellular function, including signalling, adhesion and transport. On leukocytes, several of these glycoproteins possess immunoglobulin (Ig) folds and are central to immune recognition and regulation. Here, we present a platform for the design, expression and biophysical characterization of the extracellular domain of human B cell receptor CD22. We propose that these approaches are broadly applicable to the characterization of mammalian glycoprotein ectodomains containing Ig domains. Two suspension human embryonic kidney (HEK) cell lines, HEK293F and HEK293S, are used to express glycoproteins harbouring complex and high-mannose glycans, respectively. These recombinant glycoproteins with different glycoforms allow investigating the effect of glycan size and composition on ligand binding. We discuss protocols for studying the kinetics and thermodynamics of glycoprotein binding to biologically relevant ligands and therapeutic antibody candidates. Recombinant glycoproteins produced in HEK293S cells are amenable to crystallization due to glycan homogeneity, reduced flexibility and susceptibility to endoglycosidase H treatment. We present methods for soaking glycoprotein crystals with heavy atoms and small molecules for phase determination and analysis of ligand binding, respectively. The experimental protocols discussed here hold promise for the characterization of mammalian glycoproteins to give insight into their function and investigate the mechanism of action of therapeutics.

We present approaches for the biophysical and structural characterization of glycoproteins with the immunoglobulin fold by biolayer interferometry, isothermal titration calorimetry, and X-ray crystallography.

用 X 射线晶体学和生物物理技术表征免疫球蛋白折叠的糖蛋白

Glycoproteins on the surface of cells play critical roles in cellular function, including signalling, adhesion and transport. On leukocytes, several of ...

生物化学

Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

Protein dimerization events that occur only in the presence of a small-molecule ligand enable the development of small-molecule biosensors for the dissection and manipulation of biological pathways. Currently, only a limited number of chemically induced dimerization (CID) systems exist and engineering new ones with desired sensitivity and selectivity for specific small-molecule ligands remains a challenge in the field of protein engineering. We here describe a high throughput screening method, combinatorial binders-enabled selection of CID (COMBINES-CID), for the de novo engineering of CID systems applicable to a large variety of ligands. This method uses the two-step selection of a phage-displayed combinatorial nanobody library to obtain 1) &#34;anchor binders&#34; that first bind to a ligand of interest and then 2) &#34;dimerization binders&#34; that only bind to anchor binder-ligand complexes. To select anchor binders, a combinatorial library of over 109 complementarity-determining region (CDR)-randomized nanobodies is screened with a biotinylated ligand and hits are validated with the unlabeled ligand by bio-layer interferometry (BLI). To obtain dimerization binders, the nanobody library is screened with anchor binder-ligand complexes as targets for positive screening and the unbound anchor binders for negative screening. COMBINES-CID is broadly applicable to select CID binders with other immunoglobulin, non-immunoglobulin, or computationally designed scaffolds to create biosensors for in vitro and in vivo detection of drugs, metabolites, signaling molecules, etc.

Creating chemically induced protein dimerization systems with desired affinity and specificity for any given small molecule ligand would have many biological sensing and actuation applications. Here, we describe an efficient, generalizable method for de novo engineering of chemically induced dimerization systems via the stepwise selection of a phage-displayed combinatorial single-domain antibody library.

通过组合单域抗体库的分步噬菌体选择创建高度特异性化学诱导蛋白分解系统

Protein dimerization events that occur only in the presence of a small-molecule ligand enable the development of small-molecule biosensors for the ...

Rapid Determination of Antibody-Antigen Affinity by Mass Photometry

Measurements of the specificity and affinity of antigen-antibody interactions are critically important for medical and research applications. In this protocol, we describe the implementation of a new single-molecule technique, mass photometry (MP), for this purpose. MP is a label- and immobilization-free technique that detects and quantifies molecular masses and populations of antibodies and antigen-antibody complexes on a single-molecule level. MP analyzes the antigen-antibody sample within minutes, allowing for the precise determination of the binding affinity and simultaneously providing information on the stoichiometry and the oligomeric state of the proteins. This is a simple and straightforward technique that requires only picomole quantities of protein and no expensive consumables. The same procedure can be used to study protein-protein binding for proteins with a molecular mass larger than 50 kDa. For multivalent protein interactions, the affinities of multiple binding sites can be obtained in a single measurement. However, the single-molecule mode of measurement and the lack of labeling imposes some experimental limitations. This method gives the best results when applied to measurements of sub-micromolar interaction affinities, antigens with a molecular mass of 20 kDa or larger, and relatively pure protein samples. We also describe the procedure for performing the required fitting and calculation steps using basic data analysis software.

We describe a single-molecule approach to antigen-antibody affinity measurements using mass photometry (MP). The MP-based protocol is fast, accurate, uses a very small amount of material, and does not require protein modification.

通过质量光度法快速测定抗体抗原亲和力

Measurements of the specificity and affinity of antigen-antibody interactions are critically important for medical and research applications. In this ...

Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology

Biomolecular interactions play versatile roles in numerous cellular processes&#160;by regulating and coordinating functionally relevant biological events. Biomolecules such as proteins, carbohydrates, vitamins, fatty acids, nucleic acids, and enzymes are fundamental building blocks of living beings; they assemble into complex networks in biosystems to synchronize a myriad of life events. Proteins typically utilize complex interactome networks to carry out their functions; hence it is mandatory to evaluate such interactions to unravel their importance in cells at both cellular and organism levels. Toward this goal, we introduce a rapidly emerging technology, field-effect biosensing (FEB), to determine specific biomolecular interactions. FEB is a benchtop, label-free, and reliable biomolecular detection technique to determine specific interactions and uses high-quality electronic-based biosensors. The FEB technology can monitor interactions in the nanomolar range due to the biocompatible nanomaterials used on its biosensor surface. As a proof of concept, the protein-protein interaction (PPI) between heat shock protein 90 (Hsp90) and cell division cycle 37 (Cdc37) was elucidated. Hsp90 is an ATP-dependent molecular chaperone that plays an essential role in the folding, stability, maturation, and quality control of many proteins, thereby regulating multiple vital cellular functions. Cdc37 is regarded as a protein kinase-specific molecular chaperone, as it specifically recognizes and recruits protein kinases to Hsp90 to regulate their downstream signal transduction pathways. As such, Cdc37 is considered a co-chaperone of Hsp90. The chaperone-kinase pathway (Hsp90/Cdc37 complex) is hyper-activated in multiple malignancies promoting cellular growth; therefore, it is a potential target for cancer therapy. The present study demonstrates the efficiency of FEB technology using the Hsp90/Cdc37 model system. FEB detected a strong PPI between the two proteins (KD values of 0.014 &#181;M, 0.053 &#181;M, and 0.072 &#181;M in three independent experiments). In summary, FEB is a label-free and cost-effective PPI detection platform, which offers fast and accurate measurements.

Field-effect biosensing (FEB) is a label-free technique for detecting biomolecular interactions. It measures the electric current through the graphene biosensor to which the binding targets are immobilized. The FEB technology was used to evaluate biomolecular interactions between Hsp90 and Cdc37 and a strong interaction between the two proteins was detected.

使用场效应生物传感技术探索分子伴侣Hsp90与其客户蛋白激酶Cdc37之间的生物分子相互作用

Biomolecular interactions play versatile roles in numerous cellular processes&#160;by regulating and coordinating functionally relevant biological events. ...

The Use of a &#946;-lactamase-based Conductimetric Biosensor Assay to Detect Biomolecular Interactions

Biosensors are becoming increasingly important and implemented in various fields such as pathogen detection, molecular diagnosis, environmental monitoring, and food safety control. In this context, we used &#946;-lactamases as efficient reporter enzymes in several protein-protein interaction studies. Furthermore, their ability to accept insertions of peptides or structured proteins/domains strongly encourages the use of these enzymes to generate chimeric proteins. In a recent study, we inserted a single-domain antibody fragment into the Bacillus licheniformis BlaP &#946;-lactamase. These small domains, also called nanobodies, are defined as the antigen-binding domains of single chain antibodies from camelids. Like common double chain antibodies, they show high affinities and specificities for their targets. The resulting chimeric protein exhibited a high affinity against its target while retaining the &#946;-lactamase activity. This suggests that the nanobody and &#946;-lactamase moieties remain functional. In the present work, we report a detailed protocol that combines our hybrid &#946;-lactamase system to the biosensor technology. The specific binding of the nanobody to its target can be detected thanks to a conductimetric measurement of the protons released by the catalytic activity of the enzyme.

In this work, we report a new method to study protein-protein interactions using a conductimetric biosensor based on the hybrid &#946;-lactamase technology. This method relies on release of protons upon hydrolysis of &#946;-lactams.

基于β-酶的电导生物传感器检测技术在分子间相互作用中的应用

Biosensors are becoming increasingly important and implemented in various fields such as pathogen detection, molecular diagnosis, environmental ...

生物工程

<meta charset="utf8"></head><body>使用无标记方法定量分析 RPA-ssDNA 结合动力学

Analyzing DNA-Protein Interactions with Streptavidin-Based Biolayer Interferometry

Protein-DNA interactions underpin essential cellular processes. Understanding these interactions is critical for elucidating the molecular mechanisms of various pathways. Key factors such as the structure, sequence, and length of a DNA molecule can significantly influence protein binding. Bio-layer interferometry (BLI) is a label-free technique that measures binding kinetics between molecules, offering a straightforward and precise approach to quantitatively study protein-DNA interactions. A major advantage of BLI over traditional gel-based methods is its ability to provide real-time data on binding kinetics, enabling accurate measurement of the equilibrium dissociation constant (KD) for dynamic protein-DNA interactions. This article presents a basic protocol for determining the KD value of the interaction between a DNA replication protein, replication protein A (RPA), and a single-stranded DNA (ssDNA) substrate. RPA binds ssDNA with high affinity but must also be easily displaced to facilitate subsequent protein interactions within biological pathways. In the described BLI assay, biotinylated ssDNA is immobilized on a streptavidin-coated biosensor. The binding kinetics (association and dissociation) of RPA to the biosensor-bound DNA are then measured. The resulting data are analyzed to derive precise values for the association rate constant (ka), dissociation rate constant (kd), and equilibrium binding constant (KD) using system software.

<meta charset="utf8"></head><body>使用基于链霉亲和素的生物膜干涉测量法分析 DNA-蛋白质相互作用

This article describes a protocol for studying DNA-protein interactions using a streptavidin-based biolayer interferometry (BLI) system. It outlines the essential steps and considerations for utilizing either basic or advanced binding kinetics to determine the equilibrium binding affinity (KD) of the interaction.

使用基于链霉亲和素的生物膜干涉测量法分析 DNA-蛋白质相互作用

Protein-DNA interactions underpin essential cellular processes. Understanding these interactions is critical for elucidating the molecular mechanisms of ...

高亲和力抗体 - 抗原的结合动力学的测定，使用四个生物传感器平台

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生物层干涉测量的蛋白质 - 蛋白质相互作用和变构配体反应动力学的影响

的ELISA基结合和竞争法快速测定配体 - 受体相互作用

用 X 射线晶体学和生物物理技术表征免疫球蛋白折叠的糖蛋白

通过组合单域抗体库的分步噬菌体选择创建高度特异性化学诱导蛋白分解系统

通过质量光度法快速测定抗体抗原亲和力

使用场效应生物传感技术探索分子伴侣Hsp90与其客户蛋白激酶Cdc37之间的生物分子相互作用

基于β-酶的电导生物传感器检测技术在分子间相互作用中的应用

使用基于链霉亲和素的生物膜干涉测量法分析 DNA-蛋白质相互作用

使用基于链霉亲和素的生物膜干涉测量法分析 DNA-蛋白质相互作用

使用基于链霉亲和素的生物膜干涉测量法分析 DNA-蛋白质相互作用