DD 和 YJC 承认来自情报局的支持 (项目 IFNX, 不。CE17001002) 和 ImmunoQure AG 提供单克隆抗体。我们感谢穆尼耶, Nathalia 贝伦, 克里斯汀 Bodemer, 亚历克斯贝洛, 伊莎贝尔 Melki, 皮埃尔卡尔捷提供临床样本。YJC 承认欧洲研究理事会 (GA 309449: YJC 的研究), 以及国家研究机构 (法国) 在 "未来投资" 项目下管理的国家补贴, 其参考 ANR-10-IAHU-01。

1. 抗体的选择
<ol><li>在开始之前, 该协议审查所有关键步骤 (表 1) 和选择最佳抗体。 注意: 对于这个协议高亲和力抗干扰素α抗体-IC50 在表 2中所描述的选择。优先选择对传统 ELISA 有效的配对。</li>
</ol>2. 对顺磁珠捕获抗体的共轭和不同浓度的测试
注: 在抗体共轭过程中, 始终保持珠共轭缓冲 (BCB) 和珠洗涤缓冲 (BWB) 在冰上。
<ol><li>
捕获抗体缓冲交换
	<ol>
<li>以初始数量的抗干扰素α抗体 A 测试3不同的珠动词比 (0.038 毫克/毫升, 0.075 毫克/毫升, 0.3 毫克/毫升)。 注: 低抗体涂层浓度可以是有益的, 如果检测提出了高背景信号。在缓冲交换过程中, 初始抗体数量应占估计损失的30%。根据制造商的指示和为了减少最初的背景, 测试了0.05 毫克/毫升, 0.1 毫克/毫升和0.3 毫克/毫升的浓度, 虽然这些确切的值往往没有得到由于上述可变损失的缓冲交换过程。</li>
		<li>将所需的抗体量添加到过滤器列连同 BCB, 最多可达500µL。</li>
		<li>离心机在 > 1万 x g 的列5分钟, 并丢弃流经。</li>
		<li>通过在 > 1万 x g 处添加450µL 的总容积, 然后将其 BCB 为5分钟, 并将其丢弃, 然后将该列清洗两次。</li>
		<li>将含有抗体的过滤器列放置在一个干净的离心管中倒置--该柱面的开口部分朝向新管的内侧, 离心机在 800 x g 处为1分钟。 注意: 此步骤将允许收集已清除的抗体。此步骤不需要缓冲区添加。</li>
		<li>用50µL BCB 和离心机在 800 x g 处冲洗膜, 2.1.5 1 分钟。</li>
		<li>用低容积分光光度计测定抗体浓度。</li>
		<li>添加 BCB 以达到所需的抗体浓度并记下最终音量。 注: 200 µL 的体积将用于描述协议的其余部分, 这个卷被称为2卷 (2V)。所有以下试剂卷将相应地被适应。</li>
		<li>漩涡, 并保持冰。</li>
	</ol>
</li>
	<li>
顺磁珠制备
	<ol>
<li>将 2.8 x 108珠子 (100 µL = 1V) 转移到离心管中。 注: 珠子的体积取决于2.1.8 获得的最终体积。</li>
		<li>脉冲旋转, 放入磁选机1分钟, 丢弃稀释剂, 从磁铁中取出。</li>
		<li>加入2V 的 BWB 和涡旋5秒。</li>
		<li>重复2.2.2 和2.2.3 两次, BWB 和两次 BCB。</li>
		<li>对于1V 的珠子添加190µL BCB, 涡 5 s, 脉冲旋转, 并储存在冰上洗净珠。</li>
	</ol>
</li>
	<li>
珠活化
	<ol>
<li>将1毫升的冷 BCB 加入10毫克的 1-乙基 3-(3-dimethylaminopropyl) carbodiimide 盐酸盐 (EDC) 和涡流, 直到溶液是均匀的。</li>
		<li>对于1V 的珠子添加10µL 冷稀释的 EDC 到洗涤珠, 漩涡, 并保持在一个振动筛在 1000 rpm 30 分钟的室温。 注: 由于在水溶液中的不稳定性, 应尽快完成对小珠的制备和添加。同时, 由于该系统具有极强的反应性, 所以在添加前必须有一个均匀的珠悬浮, 以防止异质珠的活化。添加后, 珠子必须保持悬浮。</li>
	</ol>
</li>
	<li>
抗体的珠共轭
	<ol>
<li>涡旋和脉冲旋转活化珠。现在把珠子放在磁选机里1分钟, 扔掉 BCB 上清, 然后把管子从磁铁上取下。</li>
		<li>用2V 的 BCB 把珠子洗净。涡流, 脉冲旋转, 并把磁选机1分钟。然后丢弃 BCB 缓冲器, 从磁铁中取出珠子。</li>
		<li>快速添加冷, 缓冲交换200µL (2V) 抗体的活化珠。</li>
		<li>涡流, 并保持在室温下的振动筛2小时。</li>
	</ol>
</li>
	<li>
珠封和最终清理
	<ol>
<li>脉冲旋转的抗体涂层珠悬浮, 放在磁分离器1分钟, 转移到新的管, 并测量浓度与低容积分光光度计。 注意: 这一步将提供有关珠子是否饱和的信息--任何高于零的值都会显示珠饱和度--因为检测到无法绑定到珠子的可溶性抗体将是可测量的。</li>
		<li>从磁铁中取出共轭珠, 加入2V 的 BWB, 涡流为5秒, 脉冲旋转, 并放入磁选机中1分钟。</li>
		<li>用低容积分光光度计将上清液转移到新管中, 测量浓度。 注意: 此步骤将提供有关抗体是否稳定地固定在珠子上的信息。在这上清液中检测到的抗体浓度将表明从珠子中分离出的抗体, 这种现象经常发生。即使很少的捕获抗体仍然附着在珠子上, 这种化验也常常奏效。</li>
		<li>从磁铁中取出共轭珠, 加入2V 的 BWB, 涡流为5秒, 脉冲旋转, 并放入磁选机中1分钟。</li>
		<li>从磁铁中取下共轭珠, 在室温下加入2V 的珠挡缓冲器, 涡旋5秒, 在振动筛中孵化30分钟。</li>
		<li>用 2V, 一次与 BWS, 和2x 与珠稀释剂缓冲 (丢弃所有上清液) 清洗抗体涂层和被阻拦的珠子3x。</li>
		<li>将涂层和被堵塞的珠子贮存在4°c 中, 直到使用2V 的珠稀释剂缓冲。 注: 在使用前, 必须使用磁选机用 250 x 珠 volume/20, 用探测器/样品稀释剂清洗一次珠子。</li>
	</ol>
</li>
</ol>3. 检测抗体 Biotinylation
<ol><li>
检测抗体缓冲交换
	<ol>
<li>服用260µg 的两个抗干扰素抗体克隆。 注意: 这在缓冲交换过程中考虑到30% 的损失, 并允许测试两种不同的生物素/抗体比值。</li>
		<li>使用 Biotinylation 反应缓冲器 (BRB) 代替 BCB 进行2.1。</li>
		<li>测量体积和抗体浓度, 调整体积以获得最终浓度为1毫克/毫升。 注: 这是一个建议的开始浓度, 但它可以优化, 如果化验没有达到所需的灵敏度。</li>
	</ol>
</li>
	<li>
检测抗体 Biotinylation
	<ol>
<li>把 N-hydroxysuccinimide-polyethylene-glycol4-biotin (NHS-PEG4-Biotin) 到室温和并用重悬共400µL 蒸馏水, 达到3.4 毫米的浓度。</li>
		<li>确定生物素: 抗体比测试和混合检测抗体和稀释的生物素相应地 (60:1 比率等于100µL 检测抗体和4.5 µL 生物素)。 注: 开始, 测试30:1 和60:1 比率。</li>
		<li>在室温下, 将抗体-生物素混合, 脉冲旋转和孵育30分钟。 注: 不需要摇动。</li>
	</ol>
</li>
	<li>
生物素化检测抗体纯化
	<ol>
<li>将生物素化抗体转移到新的过滤器中, 并进行 2.1, 执行3洗涤步骤与 BRB (400, 450 和450µL) 和最终收集。</li>
		<li>测量纯化, 生物素化检测抗体的体积和浓度, 贮存在4摄氏度, 直到使用。</li>
	</ol>
</li>
</ol>4. 检测优化
注: 使用单分子阵列分析仪软件的自制配置30。 单分子阵列分析仪由软件控制, 允许运行化验标准化, 执行样品 quantifications, 修改外部参数 (珠, 探测器, SBG, RGP 浓度; 样品稀释...) 和内部参数 (步骤数, 孵化时间...), 以达到最佳的化验条件, 也可以用来计算结果 (背景, LOD, 数量)。对于单分子阵列分析仪的设置和计算每轮优化所需的试剂量, 请参阅制造商的说明。使用2步配置执行第一轮优化。
<ol><li>在两种构型中检测捕获抗体-共轭珠和生物素化检测抗体的组合。<ol>
<li>测试组合三不同的抗干扰素α A 捕获抗体浓度与两种不同的抗干扰素α B biotinylation 比作为检测和捕获抗体, 反之亦然 (图 1) 通过选择适当的条件在分析器软件。</li>
		<li>选择最敏感的组合, 即提供最低 LOD 的条件, 并使用它进行进一步的步骤 注:图 1显示了0.3 毫克/毫升抗干扰素α a 抗体珠浓度和生物素: 抗体比值30:1 与抗干扰素α B 抗体导致最高灵敏度, 这证明了 LOD 11.6 的成品/毫升。(见补充表 1)。此组合将用于所有未来步骤。注意, 在任何一轮优化之前, 这一特定的检测都达到了极大的灵敏度。</li>
	</ol>
</li>
</ol><img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57421/57421fig1.jpg"> 图 1: 选择抗体定位, 捕获抗体浓度的珠子和 biotinylation 比.用抗干扰素α A 作为捕获抗体和抗干扰素α B 作为检测抗体 (a), 对两种可能的不同构型进行了测试, 反之亦然 (B)。IFNα-2c 被用作抗原。不同的捕获抗体浓度和生物素: 抗体 (B: A) 比率也测试两种配置。虚线显示 LOD 的最佳状态;抗干扰素α A 0.3 毫克/毫升作为捕获和抗干扰素α B 生物素: 探测器抗体比为 30 (LOD = 11.6 毫克/毫升对应的 AEB 值 0.017265)。使用了2步配置。生物素: 抗体 (B: A).<a href="/files/ftp_upload/57421/57421fig1large.jpg" target="_blank">请点击这里查看这个数字的大版本.</a>
<ol start="2"><li>比较2与3步配置。 注: 在3步的配置中, 有三种不同的孵化步骤, 一个与捕获抗体, 一个与检测抗体和最后第三个 SBG 酶标记。然而, 在2步的配置中, 捕获和检测抗体同时与感兴趣的分析物一起孵化。<ol>
<li>运行单分子阵列分析仪与捕获和检测抗体浓度和比率从4.1.2 选择2和3步配置预先配置在分析仪, 按照制造商的指令30。</li>
		<li>选择允许最高灵敏度的配置, 并将其保留为将来的步骤 注: 如图 2和辅助表 2所示, 2 步配置给每个浓度测试提供了稍微高的灵敏度和信号/背景比。因此, 为将来的步骤保留了2步的配置。</li>
	</ol>
</li>
</ol><img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57421/57421fig2.jpg"> 图 2: 2 vs 3 步配置比较.使用0.3 毫克/毫升抗干扰素α抗体作为捕获和抗干扰素α B 作为检测抗体的30生物素: 抗体比, 对2和3步构型进行了评估。IFNα-2c 被用作抗原。在3步条件设置中, 有三种不同的孵化步骤, 一个与捕获抗体, 一个与检测抗体和最后第三个 SBG 酶标签。然而, 在2步的配置中, 捕获和检测抗体同时与感兴趣的分析物一起孵化。<a href="/files/ftp_upload/57421/57421fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<ol start="3"><li>检测抗体与 SBG 浓度优化<ol>
<li>测试三不同浓度的检测抗体 (0.1, 0.3, 0.6 µg/毫升) 连同三不同浓度的 SBG (50, 150, 和 250 pM) 如上文所述30。</li>
		<li>选择具有最高灵敏度的浓度, 并保持它们的未来步骤。 注:图 3显示探测器0.3 µg/mL 和 SBG 150 pM 是显示最佳 LOD 的条件。这些条件也给出了低背景水平和中等振幅, 这种行为产生良好的标准偏差 (SD) 值 (辅助表 3)。典型的浓度范围在 0.1-1 µg/毫升之间的检测抗体和 50-200 pm 为 SBG, 虽然更高浓度 (如多达 300 pM) 的后者可能需要。重要的是要避免的条件, 将使背景高于 0.02 AEB。增加检测单克隆抗体 (SBG) 的浓度将提高信号响应和背景。然而, 如果信号的增量超越背景的变化, LOD 将会改善。可能出现的情况是, 背景的减少使低校准仪之间的差别更高。</li>
	</ol>
</li>
</ol><img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57421/57421fig3v2.jpg"> 图 3: 探测器和 SBG 浓度优化.评估了三种不同浓度的生物素化检测抗体 (0.1、0.3 和0.6 µg/毫升) 和三种不同浓度的 SBG (50、150和 250 pM)。虚线显示 LOD 的最佳状态;检测抗体在0.3 毫克/毫升和 SBG 150pM (LOD = 0.09 毫克/毫升对应的 AEB 值 0.017184)。<a href="/files/ftp_upload/57421/57421fig3v2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<ol start="4"><li>其他优化步骤<ol>
<li>如果未达到所需的灵敏度, 请使用分析器软件中的预配置选项测试不同步骤的不同潜伏期。</li>
		<li>如果检测不够灵敏, 请使用分析器软件中预配置的选项优化每种检测的珠子数量。 注: 一旦生物样品的测试开始, 样品体积是一个附加参数易受优化。确保样品根据健康和安全程序进行处理。</li>
	</ol>
</li>
</ol>5. 化验特异性和重现性
<ol><li>测试干扰素-α测定特异性, 通过测试与不同的干扰素α亚型和其他相关的蛋白质 (图 4a和4b)。</li>
</ol><img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/57421/57421fig4.jpg"> 图 4: 优化 IFNα单分子阵列法的特异性和灵敏度.(a) 对干扰素β、IFN-λ1、IFN-λ2、干扰素和干扰素-γ重组蛋白进行了测试, 以及 (B) 16 亚型干扰素α, 包括三种 IFN-α2类型 (IFN-α2a、IFN-α2b 和 IFN-α2c)。改编自 Rodero等。2017.<a href="/files/ftp_upload/57421/57421fig4large.jpg" target="_blank">请点击这里查看这个数字的更大版本.</a>
<ol start="2"><li>通过执行三项独立的复制实验和评估相互间的变异 (图 5), 评估优化试验的重现性。</li>
	<li>计算检测的 LOD 注: LOD 是用三空白 + 3 标准差 (SD) 的平均值计算的, 从而获得0.23 的 fg/mL 值。由于标准样品稀释系数为 1:3, 稀释因子的加入给出了0.69 个成品/mL 的 LOD。</li>
</ol><img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/57421/57421fig5.jpg"> 图 5: 优化的 pan-干扰素-α单分子阵列测定的重现性.三独立运行使用两种不同的珠子进行。对第二批进行了两次独立实验。每项测量都以重复的方法获得。虚线代表的 LOD, 由平均空白平均酶每珠 + SD 的所有运行。IFN-α17被用作参考, 考虑到衍生标准曲线是所有其他干扰素α亚型的代表, 如图 4b所示。图中显示平均值和 SD (误差线)。虚线显示不同运行的 LOD;运行 1: 0.073 个成品/毫升 AEB = 0.006238, 运行 2: 0.113 fg/毫升 AEB = 0.007119, 运行 3: 0.043 成品/毫升 AEB = 0.05518)。改编自 Rodero等。2017.<a href="/files/ftp_upload/57421/57421fig5large.jpg" target="_blank">请点击这里查看这个数字的更大版本.</a>
6. 蛋白质竞争化验
<ol><li>进行蛋白质竞争分析 (如图6所示), 进一步证明化验的特异性。 注: 使用 SLE 患者血浆样本 (n = 5)。<ol>
<li>当怀疑在生物样品中存在病毒时, 通过将非 ioinic 表面活性剂 (0.5% nonidet P40 替代物) 的200µL 添加到40毫升探测器/样品稀释剂中, 并大力进行涡流制备钝化缓冲器。</li>
		<li>离心生物样品含有1万克的感兴趣的分析物, 15 分钟4摄氏度, 以去除细胞碎片。</li>
		<li>混合185µL 检测器/样品稀释剂或灭活缓冲器与100µL 生物样品 (最终稀释因子 3) 和15µL 抗干扰素α抗体 A (初始浓度1毫克/毫升, 最终浓度50微克/毫升) 或缓冲。室温下孵育30分钟。</li>
		<li>如上文所述, 在单分子阵列分析仪上运行无抗干扰素α抗体的样品。 注: 在信号饱和情况下, 样品应进一步稀释。另外, 300 µL 是重复分析所需的卷。</li>
	</ol>
</li>
</ol><img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/57421/57421fig6.jpg"> 图 6: 蛋白质竞争化验.采用五种不同 SLE 患者的样本进行了竞争实验。生物样品在4摄氏度离心10.000 克, 15 分钟。他们被稀释1/3 与检测器/样品稀释剂含有 NP40 病毒灭活。15µl 抗干扰素α抗体 A (初始浓度1毫克/毫升, 最终浓度50µg/毫升) 或缓冲增加到总体积300µL. 在室温下进行孵化30分钟. 对照组以灰色和抗干扰素α A 治疗样品为例。抗体以黑色显示。图显示平均值和 SD (误差条)。虚线代表 LOD (AEB = 0.024774, 0.8037 fg/毫升)。从 Rodero等2017 适应<a href="/files/ftp_upload/57421/57421fig6large.jpg" target="_blank">, 请点击这里查看这个数字的大版本.</a>

<ol>
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作者没有什么可透露的。

在这里, 我们描述了一个高度可重现的, 超灵敏单分子阵列数字 ELISA 的发展和验证, 以直接量化的干扰素α蛋白在人体样本 (步骤总结在表 1)。检测的最关键步骤之一是抗体对16的选择, 在动力学和表位结合方面的特点是成功测定的关键。重要的是要避免使用配对单克隆抗体的目标相同的表位或导致立体障碍。多克隆抗体可作为检测抗体来克服这种局限性。如果在任何给定的步骤没有达到期望的灵敏度, 应考虑进一步的优化可能性。这可能包括使用替代抗体对, 参数的变化, 如蛋白质类型 (如 BSA < 酪蛋白), pH 值 (6.0-8.5), 离子强度, 缓冲能力 (如氯化钠和磷酸盐浓度), 载体珠, 和/或存在的表面活性剂。在研制单分子阵列试验时, 需要对多种参数进行优化。但是, 总体而言, 提供高信号的条件: 背景比率和最小检测限是首选的 (请参见图 1、图 2和图 3)。
关于特异性, 干扰素α的检测显示任何其他 IFNs 测试 (β, γ, λ1, λ2, ω) 没有交叉反应 (图 4a), 并能够检测所有13干扰素α亚型 (图 4b)。然而, 该检测显示 IFN-α2亚型的亲和力较低 (图 4b和补充表 4)。有趣的是, 对不同类别的 IFN-α2 (a, b, c) 也有不同的敏感性, 这可能是由于不同的制造程序或不同的氨基酸序列, 因为 IFN-α2亚型是从各种商业供应商。有了这个唯一的例外, 所有的干扰素α物种作出了非常相似的反应。通过对样品的预处理与抗干扰素α A 克隆的结合, 进一步证明了该方法的特异性, 废除了该信号 (图 6和补充表 6)。
这种技术的一个主要优点是, 任何感兴趣的分析物都有可能成为目标16。此外, 可以测试不同的生物标本, 如血清, 血浆, 脑脊液, 细胞裂解物, 培养上清液31 , 甚至呼吸32。通常, 1:3 的等离子稀释是为了避免单分子阵列分析仪的潜在堵塞。然而, 感兴趣的分析物可能存在于相关生物样品的极低浓度, 并且可能需要更高浓度的样品 (取决于测定灵敏度)33。尽管有可能进行多路复用, 同时保持良好的灵敏度为34, 但它是一个更具挑战性的过程, 在相同的实验中测量大于6蛋白质的测试还有待开发35。
在这种低浓度下检测和量化细胞因子和其他生物相关蛋白的能力开辟了一个全新的应用范围33,36。众所周知, 许多蛋白质甚至在极低浓度下发挥作用, 直到现在都低于最佳 ELISAs37的检测极限。虽然其他免疫分析技术提供优于常规 ELISA19, 我们在这里证明, 单分子阵列数字 ELISA 是一个重现性和稳健的平台超灵敏检测低浓度细胞因子在人类样本。因此, 这项技术为生物标志物发现和改善病人对多种疾病的管理提供了巨大的潜力。

I 型 IFNs 是一种细胞因子的家族, 在协调抗病毒免疫应答中起着核心作用。他们首先发现了由萨克斯和 Lindenmann 60 年前1,2和它现在知道这个异构的多肽家庭包括14个不同的子类 (13 干扰素α亚型和1干扰素β)。I 型 IFNs 是清除病毒感染的必要条件, 但也牵涉到各种人类疾病的病理状态, 包括自身免疫性疾病系统性红斑狼疮 (SLE), 青少年皮肌炎 (JDM), 和类型i interferonopathies 的 i. 型干扰素诱导的信号, 导致病理3,4,5,6,7。
研究 I 型干扰素蛋白在生物样品中的水平一直是挑战, 因为它最初的鉴定为 "干扰物质"1,2。目前, 夹心酶联免疫吸附法 (ELISA) 是检测干扰素α蛋白最常用的方法。尽管是特定的, 简单, 快速, I 型干扰素 ELISAs 目前的重要限制, 如有限的敏感性。此外, 所有干扰素α亚型的测量都需要使用多种检测方法, 每个测试都有自己的探测能力和灵敏度。虽然有商业 ELISAs 检测不同亚型干扰素α, 他们的灵敏度是有限的 (1.95 pg/毫升, 12.5 pg/毫升, 12.5 pg/毫升, 分别) 往往不足以检测干扰素α蛋白的生物样品。为了克服这一局限性, 通过测量诱导基因表达或功能活动8、9、10、11,开发了几种生物代理检测法来量化 I 型干扰素。12,13,14. 尽管如此, 这些化验结果并不能直接测量干扰素α蛋白。
本研究采用单分子阵列数字 ELISA 技术, 研制出一种检测单干扰素-α蛋白分子的方法。数字 elisa 采用与常规 elisa 相同的基础化学, 然而, 反应发生在阵列包括5万个单独 46 femtoliter 大小井15,16。单蛋白分子由抗体涂层顺磁性珠捕获, 并标记为生物素化检测抗体, 其次是结合酶共轭, 链亲和素β-乳糖酶 (SBG)。随后, 珠被悬浮与荧光酵素基体, 试卤灵β D-galactopyranoside (RGP), 入单分子阵列。通过减少20亿乘以17的体积反应, 达到了高局部荧光信号浓度, 单分子计数变得可行, 因为每个分子产生的信号, 现在可以可靠地测量18。在本质上, 单分子阵列能够计数单个免疫复合物, 并确定每个珠的平均酶数 (AEB)。计数信号被检测到的 microwells 允许量化/数字化的蛋白质分子, 因为有直接相关的蛋白质浓度和比例之间的 immunocomplexed 珠和总数量的珠子呈现在femtoliter 大小的房间。
杨等。使用九种不同的技术和四个细胞因子免疫进行了广泛的跨平台评估研究, 目的是比较不同平台19之间的检测精度、灵敏度和数据相关性。研究的一个重要结果是, 单分子阵列和单分子计数免疫检测在亚 pg/mL 浓度范围内对人血清中细胞因子的测定具有最高灵敏度。采用单分子阵列数字 ELISA 细胞因子检测方法, 研究了 TNF α和 IL-6 在克罗恩病20、interferonopathy 和自体免疫患者中的作用, 以及不同 translationally 后修饰形式的 c--c主题趋化因子 10 (CXCL10) 在慢性肝炎和健康捐赠者接受西格列汀21,22。其他应用包括测量糖尿病视网膜病变患者的紫红23;通过血清/血浆测量丝光24和淀粉样β1-42 肽25, 在多发性硬化和阿尔茨海默病的背景下, 对脑部病理学进行研究。单分子阵列测定也可用于改进病原体的检测, 如 HIV 病毒储层26的表征, 以及检测 DNA27和微 rna28。单分子阵列技术的一个主要优点是这种高通用性, 因为如果有特定的抗体对, 就可以对任何感兴趣的分析物进行检测。此外, 自制的化验试剂盒在商业上是可以利用的, 允许开发新的化验, 其中的议定书是以修改后的形式详细说明的。
本文详细介绍了单分子阵列检测的发展和验证步骤, 从而提高了对干扰素α蛋白检测的灵敏度。单分子阵列检测的抗体应高度特异, 避免与相关蛋白的交叉反应 (如果相关的物种特异性考虑)。理想情况下, 应选择具有 KD小于 10-9米的抗体;高亲和性确保强约束, 具有较高的信号产生。抗体-抗原结合的动力学也很重要, 快速 k 和慢 k将有利于抗原抗体复合体的组装。从具有良好性能的经典 ELISA 的抗体对, 具有 1-100 pg/毫升的检测限制, 增加了获得高度敏感的单分子阵列检测的机会。张和同事对生物分子相互作用的每一个步骤进行了详细的动力学研究, 提出了一套预测分析灵敏度18的方程式。他们表明, 单分子阵列数字 ELISA 似乎是有效的范围内广泛的抗体亲和力 (KD~10−11 -10−9 M), 以及信号产生更依赖于这种抗体的速率。
为了利用高亲和抗体, 我们利用了自体免疫 polyendocrinopathy 综合征1型/自身免疫性 polyendocrinopathy-念珠菌病外胚层营养不良 (APS1/APECED)29的抗体。由于尚不清楚的原因, 绝大多数 AIRE 缺乏的人开发了一套核心的高亲和力抗体抗所有干扰素α亚型29, 我们选择了两个抗干扰素α抗体克隆的互补结合亲和性对于不同的干扰素α亚型, 估计由 IC50值。这些独特的高亲和抗体与单分子阵列技术的结合, 使干扰素α在 attomolar (fg/毫升) 浓度的直接量化。这种超灵敏干扰素α蛋白检测将有助于更好地了解干扰素诱发反应在不同疾病环境中的性质、调控和生物学影响。

<table>
	<tbody>
		<tr>
			<td>Anti-IFN-&#945; antibody A (8H1 clone)</td>
			<td>ImmunoQure AG</td>
			<td>NA</td>
			<td>Not commercially available</td>
		</tr>
		<tr>
			<td>Anti-IFN-&#945; antibody B (12H5 clone)</td>
			<td>ImmunoQure AG</td>
			<td>NA</td>
			<td>Not commercially available</td>
		</tr>
		<tr>
			<td>Anti-IFN-&#945; antibody EBI-1 clone</td>
			<td>eBioscience</td>
			<td>BMS216C</td>
			<td></td>
		</tr>
		<tr>
			<td>Anti-IFN-&#945; antibody BMS216BK clone</td>
			<td>eBioscience</td>
			<td>BMS216BK</td>
			<td>Not an ELISA kit but bulk abs</td>
		</tr>
		<tr>
			<td>IFN &#945;2c</td>
			<td>eBioscience</td>
			<td>BMS305</td>
			<td>OK</td>
		</tr>
		<tr>
			<td>IFN &#945;I (17)</td>
			<td>PBL</td>
			<td>11150-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;2a</td>
			<td>PBL</td>
			<td>11100-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;2a</td>
			<td>PeproTech</td>
			<td>No longer available</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;2b</td>
			<td>PBL</td>
			<td>11105-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;1</td>
			<td>PBL</td>
			<td>11175-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;4a (M1)</td>
			<td>PBL</td>
			<td>11177-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;4b (a4)</td>
			<td>PBL</td>
			<td>11180-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;B2 (a8)</td>
			<td>PBL</td>
			<td>11115-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;C (a10)</td>
			<td>PBL</td>
			<td>11120-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;D (a1)</td>
			<td>PBL</td>
			<td>11125-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;G (a5)</td>
			<td>PBL</td>
			<td>11135-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;F (a21)</td>
			<td>PBL</td>
			<td>11130-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;H2 (a14)</td>
			<td>PBL</td>
			<td>11145-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;J1 (a7)</td>
			<td>PBL</td>
			<td>11160-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;K (a6)</td>
			<td>PBL</td>
			<td>11165-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#945;WA (a16)</td>
			<td>PBL</td>
			<td>11190-1</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#955;1</td>
			<td>PeproTech</td>
			<td>300-02L</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#955;2</td>
			<td>PeproTech</td>
			<td>300-02K</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#969;</td>
			<td>PeproTech</td>
			<td>300-02J</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#946;</td>
			<td>PeproTech</td>
			<td>300-02BC</td>
			<td></td>
		</tr>
		<tr>
			<td>IFN &#947;</td>
			<td>PeproTech</td>
			<td>300-02</td>
			<td></td>
		</tr>
		<tr>
			<td>Anti-IFN-&#945; ELISA</td>
			<td>PBL</td>
			<td>41115.1</td>
			<td></td>
		</tr>
		<tr>
			<td>96-well plates</td>
			<td>Corning</td>
			<td>3904</td>
			<td></td>
		</tr>
		<tr>
			<td>ISRE-Reporter</td>
			<td>Qiagen</td>
			<td>CCS-008L</td>
			<td></td>
		</tr>
		<tr>
			<td>Fu-GENE HD Transfection Reagent</td>
			<td>Promega</td>
			<td>E2311</td>
			<td></td>
		</tr>
		<tr>
			<td>Opti-MEM Reduced Serum Mediuem</td>
			<td>ThermoFischer Scientific</td>
			<td>31985062</td>
			<td></td>
		</tr>
		<tr>
			<td>Dual-Luciferase Reporter assay</td>
			<td>Promega</td>
			<td>E1910</td>
			<td></td>
		</tr>
		<tr>
			<td>Nonidet P40 Substitute</td>
			<td>Sigma-Aldrich</td>
			<td>74385</td>
			<td></td>
		</tr>
		<tr>
			<td>Spectrophotometer NanoDrop 1000</td>
			<td>Thermo Scientific</td>
			<td>No longer available</td>
			<td></td>
		</tr>
		<tr>
			<td>Amicon micocentrifuge tubes - 0.5mL filtres</td>
			<td>Merck Millipore</td>
			<td>UFC505096</td>
			<td></td>
		</tr>
		<tr>
			<td>Bead Conjugation Buffer</td>
			<td>Quanterix</td>
			<td>102040</td>
			<td>Can not be ordered separately</td>
		</tr>
		<tr>
			<td>Non-Encoded Paramagnetic Beads</td>
			<td>Quanterix</td>
			<td>101360</td>
			<td></td>
		</tr>
		<tr>
			<td>Bead Wash Buffer</td>
			<td>Quanterix</td>
			<td>102040</td>
			<td>Can not be ordered separately</td>
		</tr>
		<tr>
			<td>EDC</td>
			<td>Fisher Scientific</td>
			<td>11844071</td>
			<td></td>
		</tr>
		<tr>
			<td>Bead Blocking Buffer</td>
			<td>Quanterix</td>
			<td>102040</td>
			<td>Can not be ordered separately</td>
		</tr>
		<tr>
			<td>Bead Diluent Buffer</td>
			<td>Quanterix</td>
			<td>101362</td>
			<td></td>
		</tr>
		<tr>
			<td>Detector and Sample Diluent</td>
			<td>Quanterix</td>
			<td>101359</td>
			<td></td>
		</tr>
		<tr>
			<td>Biotinylation Reaction Buffer</td>
			<td>Quanterix</td>
			<td>102040</td>
			<td>Can not be ordered separately</td>
		</tr>
		<tr>
			<td>NHS-PEG4-Biotin</td>
			<td>Fisher Scientific</td>
			<td>11891195</td>
			<td></td>
		</tr>
		<tr>
			<td>diH2O</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge for 1.7mL microcentrifuge tubes (Heraens Fresco 21 Centrifuge)</td>
			<td>Thermo Scientific</td>
			<td>75002478</td>
			<td></td>
		</tr>
		<tr>
			<td>Standard laboratory vortex mixer (MS2 Minishaker)</td>
			<td>IKA</td>
			<td>MS2</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipettes (10, 20, 200 and 1000 &#956;l)</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Tips (10, 20, 200 and 1000 &#956;l)</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>1.7mL microcentrifuge tubes</td>
			<td>Eppendorf</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Magnetic separator that accomodates 1.7mL microcentrifuge tubes (Life Technologies DynaMag-2)</td>
			<td>ThermoFisher Scientific</td>
			<td>12321D</td>
			<td></td>
		</tr>
		<tr>
			<td>Mini benchtop centrifuge (Galaxy MinisStar)</td>
			<td>VWR</td>
			<td>521-2844</td>
			<td></td>
		</tr>
		<tr>
			<td>Mixer/Shaker (Eppendorf Thermomixer Comfort)</td>
			<td>Eppendorf</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Single molecule array (Simoa) reagents</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>SBG, Bead and Detector Barcode Labels</td>
			<td>Quanterix</td>
			<td>101652</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL Reagent Bottles</td>
			<td>Quanterix</td>
			<td>102411</td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa specimen 96-well plates</td>
			<td>Quanterix</td>
			<td>101457</td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa Discs</td>
			<td>Quanterix</td>
			<td>100001</td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa 2.0 conductive Tips</td>
			<td>Quanterix</td>
			<td>101726</td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa Cuvettes</td>
			<td>Quanterix</td>
			<td>100803</td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa SBG Reagent</td>
			<td>Quanterix</td>
			<td>102295</td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa RGP Reagent</td>
			<td>Quanterix</td>
			<td>101736</td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa System Buffer 1</td>
			<td>Quanterix</td>
			<td>100486</td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa System Buffer 2</td>
			<td>Quanterix</td>
			<td>100487</td>
			<td></td>
		</tr>
		<tr>
			<td>Sealing Oil</td>
			<td>Quanterix</td>
			<td>100206</td>
			<td></td>
		</tr>
		<tr>
			<td>ddH2O</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Simoa HD-1 Analyzer</td>
			<td>Quanterix</td>
			<td>100032</td>
			<td></td>
		</tr>
		<tr>
			<td>Technologies</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Single molecule array (Simoa)</td>
			<td>Quanterix</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Single molecule counting Erenna Immunoassay Systems</td>
			<td>Singluex</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

development and validation of an ultrasensitive single molecule array digital enzyme-linked immunosorbent assay for human interferon-&#945;

本协议的主要目的是描述干扰素 (干扰素) α单分子阵列数字酶联免疫吸附试验 (ELISA) 检测的发展和有效性。该系统使人类干扰素α蛋白的定量化具有前所未有的灵敏度, 对其他干扰素的种类无交叉反应性。
该协议的第一个关键步骤是抗体对的选择, 其次是捕获抗体与顺磁性珠的共轭, 以及检测抗体的 biotinylation。在此步骤之后, 可以修改不同的参数, 如检测配置、检测抗体浓度和缓冲成分, 直到达到最佳灵敏度为止。最后, 评估了该方法的特异性和重现度, 以确保结果的可信度。在这里, 我们开发了一种干扰素-α单分子阵列检测, 用高亲和性自身抗体从 biallelic 突变的患者中分离出的0.69 毫升/mL, 其自身免疫调节蛋白 (AIRE) 导致自身免疫性 polyendocrinopathy综合征1型/自身免疫性 polyendocrinopathy-念珠菌性外胚层营养不良 (APS1/APECED)。重要的是, 这些抗体能够检测到所有13种干扰素α亚型。
这种新方法允许首次在 attomolar 浓度下检测和定量测定人类生物样品中的干扰素α蛋白。这种工具对于监测人类健康和疾病状态中这种细胞因子的水平非常有用, 尤其是感染、自身免疫和 autoinflammation。

总之, 一个 pan-干扰素-α单分子阵列检测的限制0.69 的成品/毫升, 使用2步配置与捕获珠涂覆0.3 毫克/毫升抗干扰素α抗体和抗干扰素α B 检测抗体生物素化在生物素: 抗体比30被开发了。生物素化检测抗体和 SBG 浓度分别为0.3 µg/毫升和 150 pM。这种高度特异的检测能够检测出所有13种干扰素α亚型, 不与其他类型的 IFNs 发生交叉反应。因此, 虽然无法识别和量化每种干扰素α, 但它们都可以被检测和测量, 同时给出含有13种不同子类的干扰素α的总浓度值。
为探讨新研制的检测方法对健康个体血浆和血清中干扰素α蛋白的诊断价值, 并与 SLE 和 JDM 患者的样本进行比较。如图 7所示, 与健康对照组相比, 两种疾病群中均检测出高水平的干扰素α蛋白。虚线表明了传统的商用 ELISA 的 LOD, 说明这种方法不会检测到这些患者组的干扰素α蛋白, 尽管已知的这种细胞因子与这些表型的关联。此外, 干扰素α可以被量化超过5对数的数量, 说明了广泛的动态范围的检测, 与检测水平之间的 1-10 的 fg/毫升确认高度敏感的性质的化验。
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/57421/57421fig7.jpg"> 图 7: 从患者群中测定血浆和血清中干扰素α蛋白的数量.这个数字已经从 Rodero. 2017. 用泛 IFNα单分子阵列法对健康对照组 (n = 20) 和患有 SLE (n = 72) 和 JDM (n = 43) 的患者进行了血浆检测。采用单向方差分析试验 (克鲁斯卡尔) 和邓恩的多组比较试验进行了研究。中值被描述。虚线表示参考人类抗干扰素α ELISA 的 LOD (1.95 pg/毫升 = 1950 fg/毫升)。<a href="/files/ftp_upload/57421/57421fig7large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody>
<tr>
<td>步</td>
			<td>考虑</td>
			<td>参考</td>
		</tr>
<tr>
<td rowspan="3">1. 抗体对选择</td>
			<td>目标不同的表位</td>
			<td rowspan="3">表2</td>
		</tr>
<tr>
<td>高亲和力</td>
		</tr>
<tr>
<td>快速 k开/慢 k
</td>
		</tr>
<tr>
<td>2. 抗体对取向</td>
			<td rowspan="3">选择最低检测限制条件</td>
			<td rowspan="3">图1</td>
		</tr>
<tr>
<td>3. 捕获抗体浓度</td>
		</tr>
<tr>
<td>4. 生物素: 探测器抗体比</td>
		</tr>
<tr>
<td>5. 2 vs 3 步配置</td>
			<td>选择具有最高信号的条件: 背景比</td>
			<td>图2</td>
		</tr>
<tr>
<td>6. 检测抗体浓度</td>
			<td rowspan="2">选择最低检测限制条件</td>
			<td rowspan="2">图3</td>
		</tr>
<tr>
<td>7. SBG 浓度</td>
		</tr>
<tr>
<td>8. 特异性</td>
			<td>评估交叉反应性</td>
			<td rowspan="2">图4</td>
		</tr>
<tr>
<td>9. 灵敏度</td>
			<td>评估子类型的识别 (如果适用)</td>
		</tr>
<tr>
<td>10. 重现性</td>
			<td>评估化验变异性</td>
			<td>图5</td>
		</tr>
</tbody></table>表 1: 单分子阵列测定的发展和优化步骤摘要.本表总结了单分子阵列检测的发展和优化所需的不同步骤, 从抗体对的初始选择直到重现性的评估。
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody>
<tr>
<td>抗原</td>
			<td>8H1 (A)</td>
			<td>12H5 (B)</td>
			<td>Sifalimumab</td>
			<td>Rontalizumab</td>
		</tr>
<tr>
<td>IFNα1</td>
			<td>28。3</td>
			<td>51。3</td>
			<td>460</td>
			<td>22.63</td>
		</tr>
<tr>
<td>IFNα2</td>
			<td>2563</td>
			<td>10。7</td>
			<td>9.02</td>
			<td>2.15</td>
		</tr>
<tr>
<td>IFNα4</td>
			<td>5.11</td>
			<td>2.99</td>
			<td>35.35</td>
			<td>325。3</td>
		</tr>
<tr>
<td>IFNα5</td>
			<td>2.01</td>
			<td>19。6</td>
			<td>93.29</td>
			<td>2.49</td>
		</tr>
<tr>
<td>IFNα6</td>
			<td>64。7</td>
			<td>3.03</td>
			<td>4.97</td>
			<td>-</td>
		</tr>
<tr>
<td>IFNα7</td>
			<td>0。9</td>
			<td>0.63</td>
			<td>233。1</td>
			<td>-</td>
		</tr>
<tr>
<td>IFNα8</td>
			<td>302</td>
			<td>0.83</td>
			<td>691</td>
			<td>10.86</td>
		</tr>
<tr>
<td>IFNα10</td>
			<td>2.54</td>
			<td>0.71</td>
			<td>43。2</td>
			<td>-</td>
		</tr>
<tr>
<td>IFNα14</td>
			<td>3224</td>
			<td>2。1</td>
			<td>14.52</td>
			<td>0。9</td>
		</tr>
<tr>
<td>IFNα16</td>
			<td>1.83</td>
			<td>32.99</td>
			<td>59.18</td>
			<td>28.65</td>
		</tr>
<tr>
<td>IFNα17</td>
			<td>2.21</td>
			<td>0.77</td>
			<td>890。9</td>
			<td>23.86</td>
		</tr>
<tr>
<td>IFNα21</td>
			<td>2.78</td>
			<td>12.87</td>
			<td>1769</td>
			<td>5。8</td>
		</tr>
</tbody></table>表 2: Pan α抗体的选择.IC50 (ng/毫升) 用干扰素刺激的反应元素 (ISRE)-荧光素酶中和法测定。表显示了用于所有干扰素α亚型的单分子阵列检测中抗体的 IC50 值。1万 HEK 293 星享细胞被播种在白色半区域96井板和反向转染与 50 ng 预混 ISRE-萤火虫荧光素酶的记者和 Renilla 荧光素酶的结构, 根据制造商的指示使用染用试剂。荧光素酶表达结构作为内部规范化控制。细胞在一夜间孵化在减少的血清培养基补充0.1 毫米不必要的氨基酸, 1 毫米丙酮酸钠, 0.5% 胎牛血清在37°c, 5% CO2在一个湿润的气氛。在夜间孵化后, 细胞被刺激24小时, 其中含有重组人干扰素α的混合物, 有或没有抗干扰素α抗体或对照 IgG, 在37摄氏度 preincubated 1 小时。经过24小时的刺激, 双荧光素酶的报告化验是根据制造商的指示进行。«-»没有确定。Sifalimumab 是一个完全人类, 免疫球蛋白 G1 κ单克隆抗体, 结合和中和大多数干扰素α亚型;Rontalizumab 是一种抗干扰素α的人性化单克隆抗体。改编自迈耶等2016 和 Rodero等。2017。
补充表 1: 选择抗体定位, 捕获抗体浓度的珠子和 biotinylation 比.用抗干扰素α A 作为捕获抗体和抗干扰素α B 作为检测抗体 (a), 对两种可能的不同构型进行了测试, 反之亦然 (B)。IFNα-2c 被用作抗原。不同的捕获抗体浓度和生物素: 抗体 (B: A) 比率也测试两种配置。饱和度 (Sat)。橙色: 用于 LOD 计算的 AEB 值;这些浓度被认为是空白的, 因为 AEB 值保持稳定。LOD 计算为平均空白 + 3SD.<a href="/files/ftp_upload/57421/Supplementary_Table_1.xlsx">请单击此处下载此文件.</a>
补充表 2: 测试 2 vs 3 步配置.用 IFNα-2c 作为抗原对2和3步构型进行了评估。AEB 值以及信号/背景口粮 (S/B) 都显示在这两个条件。<a href="/files/ftp_upload/57421/Supplementary_Table_2.xlsx">请单击此处下载此文件.</a>
辅助表 3: 检测器和 SBG 浓度优化.评估了三种不同浓度的生物素化检测抗体 (0.1、0.3 和0.6 µg/毫升) 和三种不同浓度的 SBG (50、150和 250 pM)。AEB 值显示在九测试条件下。橙色: 用于 LOD 计算的 AEB 值;这些浓度被认为是空白的, 因为 AEB 值保持稳定。LOD 计算为平均空白 + 3SD.<a href="/files/ftp_upload/57421/Supplementary_Table_3.xlsx">请单击此处下载此文件.</a>
补充表 4: 优化 IFNα单分子阵列法的特异性和灵敏度.当干扰素β、IFN-λ1、IFN-λ2、干扰素和干扰素-γ重组蛋白 (A) 和干扰素-α (B) 的16亚型进行测试时, 每个珠子的平均酶值均显示出来。«-»没有确定。<a href="/files/ftp_upload/57421/Supplementary_Table_4.xlsx">请单击此处下载此文件.</a>
补充表 5: 优化 IFNα单分子阵列测定的重现性.所有三独立奔跑的平均 AEB 值显示由10.000 个 fg/毫升的集中。«-»没有确定。饱和度 (Sat)。<a href="/files/ftp_upload/57421/Supplementary_Table_5.xlsx">请单击此处下载此文件.</a>
补充表 6: 蛋白质竞争化验.所有测试的条件都显示每个珠子的平均酶值。测量是重复进行的。<a href="/files/ftp_upload/57421/Supplementary_Table_6.xlsx">请单击此处下载此文件.</a>

Watch this Scientific Journal Video about Development and Validation of an Ultrasensitive Single Molecule Array Digital Enzyme-linked Immunosorbent Assay for Human Interferon-Î± at JoVE.com

Development and Validation of an Ultrasensitive Single Molecule Array Digital Enzyme-linked Immunosorbent Assay for Human Interferon-&#945;

在这里, 我们提出一个协议来描述一个单一的分子阵列数字 ELISA 检测的发展和验证, 这使得对所有干扰素α亚型的超敏检测在人体标本。

人干扰素α超灵敏单分子阵列数字酶联免疫吸附试验的研制与验证

The main aim of this protocol is to describe the development and validation of an interferon (IFN)-&#945; single molecule array digital Enzyme-Linked ...

development-validation-an-ultrasensitive-single-molecule-array

Universidad de Cartagena UDEC

Research

JoVE Journal

Immunology and Infection

11.9K 次观看.  Institut Pasteur. 在这里, 我们提出一个协议来描述一个单一的分子阵列数字 ELISA 检测的发展和验证, 这使得对所有干扰素α亚型的超敏检测在人体标本。

视频: Development and Validation of an Ultrasensitive Single Molecule Array Digital Enzyme-linked Immunosorbent Assay for Human Interferon-α

Enzyme-linked Immunospot Assay (ELISPOT):  Quantification of Th-1 Cellular Immune Responses Against Microbial Antigens

Adaptive immunity is an important component to clearance of intracellular pathogens. The ability to detect and quantify these responses in humans is an important diagnostic tool. The enzyme-linked immunospot assay (ELISPOT) is gaining popularity for its ability to identify cellular immune responses against microbial antigens, including immunosuppressed populations such as those with HIV infection, transplantation, and steroid use. This assay has the capacity to quantify the immune responses against specific microbial antigens, as well as distinguish if these responses are Th1 or Th2 in character. ELISPOT is not limited to the site of inflammation. It is versatile in its ability to assess for immune responses within peripheral blood, as well as sites of active involvement such as bronchoalveolar lavage, cerebral spinal fluid, and ascites. Detection of immune responses against a single or multiple antigens is possible, as well as specific epitopes within microbial proteins. This assay facilitates detection of immune responses over time, as well as distinctions in antigens recognized by host T cells. Dual color ELISPOT assays are available for detection of simultaneous expression of two cytokines. Recent applications for this technique include diagnosis of extrapulmonary tuberculosis, as well as investigation of the contribution of infectious antigens to autoimmune diseases.

Enzyme-linked Immunospot Assay ELISPOT:  Quantification of Th-1 Cellular Immune Responses Against Microbial Antigens

Identification of microbial targets of adaptive immunity in idiopathic diseases can be accomplished by the use of the enzyme-linked immunospot assay.

酶联免疫斑点法（ELISPOT）:TH - 1细胞对微生物抗原的免疫应答的定量

Adaptive immunity is an important component to clearance of intracellular pathogens.  The ability to detect and quantify these responses in humans is an ...

科研

免疫与感染

Use of Interferon-&gamma; Enzyme-linked Immunospot Assay to Characterize Novel T-cell Epitopes of Human Papillomavirus

A protocol has been developed to overcome the difficulties of isolating and characterizing rare T cells specific for pathogens, such as human papillomavirus (HPV), that cause localized infections. The steps involved are identifying region(s) of HPV proteins that contain T-cell epitope(s) from a subject, selecting for the peptide-specific T cells based on interferon-&gamma; (IFN-&gamma;) secretion, and growing and characterizing the T-cell clones (Fig. 1). Subject 1 was a patient who was recently diagnosed with a high-grade squamous intraepithelial lesion by biopsy and underwent loop electrical excision procedure for treatment on the day the T cells were collected1. A region within the human papillomavirus type 16 (HPV 16) E6 and E7 proteins which contained a T-cell epitope was identified using an IFN- g enzyme-linked immunospot (ELISPOT) assay performed with overlapping synthetic peptides (Fig. 2). The data from this assay were used not only to identify a region containing a T-cell epitope, but also to estimate the number of epitope specific T cells and to isolate them on the basis of IFN- &gamma; secretion using commercially available magnetic beads (CD8 T-cell isolation kit, Miltenyi Biotec, Auburn CA). The selected IFN-&gamma; secreting T cells were diluted and grown singly in the presence of an irradiated feeder cell mixture in order to support the growth of a single T-cell per well. These T-cell clones were screened using an IFN- &gamma; ELISPOT assay in the presence of peptides covering the identified region and autologous Epstein-Barr virus transformed B-lymphoblastoid cells (LCLs, obtained how described by Walls and Crawford)2 in order to minimize the number of T-cell clone cells needed. Instead of using 1 x 105 cells per well typically used in ELISPOT assays1,3, 1,000 T-cell clone cells in the presence of 1 x 105 autologous LCLs were used, dramatically reducing the number of T-cell clone cells needed. The autologous LCLs served not only to present peptide antigens to the T-cell clone cells, but also to keep a high cell density in the wells allowing the epitope-specific T-cell clone cells to secrete IFN-&gamma;. This assures successful performance of IFN-&gamma; ELISPOT assay. Similarly, IFN- &gamma; ELISPOT assays were utilized to characterize the minimal and optimal amino acid sequence of the CD8 T-cell epitope (HPV 16 E6 52-61 FAFRDLCIVY) and its HLA class I restriction element (B58). The IFN- &gamma; ELISPOT assay was also performed using autologous LCLs infected with vaccinia virus expressing HPV 16 E6 or E7 protein. The result demonstrated that the E6 T-cell epitope was endogenously processed. The cross-recognition of homologous T-cell epitope of other high-risk HPV types was shown. This method can also be used to describe CD4 T-cell epitopes4.

Use of Interferon-&#947; Enzyme-linked Immunospot Assay to Characterize Novel T-cell Epitopes of Human Papillomavirus

Characterizing T-cell epitopes of pathogens that cause localized infections such as human papillomavirus is a challenge because of limited number of T cells in circulation. A method is described in which rare T cells were isolated and were characterized starting with a very small number of cells.

使用γ-干扰素酶酶联免疫检测的特点人类乳头状瘤病毒的新型T-细胞表位

A protocol has been developed to overcome the difficulties of isolating and characterizing rare T cells specific for pathogens, such as human ...

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 ...

Characterization of Inflammatory Responses During Intranasal Colonization with Streptococcus pneumoniae

Nasopharyngeal colonization by Streptococcus pneumoniae is a prerequisite to invasion to the lungs or bloodstream1. This organism is capable of colonizing the mucosal surface of the nasopharynx, where it can reside, multiply and eventually overcome host defences to invade to other tissues of the host. Establishment of an infection in the normally lower respiratory tract results in pneumonia. Alternatively, the bacteria can disseminate into the bloodstream causing bacteraemia, which is associated with high mortality rates2, or else lead directly to the development of pneumococcal meningitis. Understanding the kinetics of, and immune responses to, nasopharyngeal colonization is an important aspect of S. pneumoniae infection models.
Our mouse model of intranasal colonization is adapted from human models3 and has been used by multiple research groups in the study of host-pathogen responses in the nasopharynx4-7. In the first part of the model, we use a clinical isolate of S. pneumoniae to establish a self-limiting bacterial colonization that is similar to carriage events in human adults. The procedure detailed herein involves preparation of a bacterial inoculum, followed by the establishment of a colonization event through delivery of the inoculum via an intranasal route of administration. Resident macrophages are the predominant cell type in the nasopharynx during the steady state. Typically, there are few lymphocytes present in uninfected mice8, however mucosal colonization will lead to low- to high-grade inflammation (depending on the virulence of the bacterial species and strain) that will result in an immune response and the subsequent recruitment of host immune cells. These cells can be isolated by a lavage of the tracheal contents through the nares, and correlated to the density of colonization bacteria to better understand the kinetics of the infection.

Characterization of Inflammatory Responses During Intranasal Colonization with Streptococcus pneumoniae

Colonization of the murine nasopharynx with Streptococcus pneumoniae and the subsequent extraction of adherent or recruited cells is described. This technique involves flushing the nasopharynx and collection of the fluid through the nares and is adaptable for various readouts, including differential cell quantification and analysis of mRNA expression in situ.

肺炎链球菌在鼻内殖民期间炎症反应的特征

Nasopharyngeal colonization by Streptococcus pneumoniae is a prerequisite to invasion to the lungs or bloodstream1. This organism is capable of colonizing ...

Visualizing Protein-DNA Interactions in Live Bacterial Cells Using Photoactivated Single-molecule Tracking

Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome organization are governed by DNA-binding proteins that recognize specific DNA structures or sequences. In vitro experiments have helped to generate detailed models for the function of many types of DNA-binding proteins, yet, the exact mechanisms of these processes and their organization in the complex environment of the living cell remain far less understood. We recently introduced a method for quantifying DNA-repair activities in live Escherichia coli cells using Photoactivated Localization Microscopy (PALM) combined with single-molecule tracking. Our general approach identifies individual DNA-binding events by the change in the mobility of a single protein upon association with the chromosome. The fraction of bound molecules provides a direct quantitative measure for the protein activity and abundance of substrates or binding sites at the single-cell level. Here, we describe the concept of the method and demonstrate sample preparation, data acquisition, and data analysis procedures.

Photoactivated localization microscopy (PALM) combined with single-molecule tracking allows direct observation and quantification of protein-DNA interactions in live Escherichia coli cells.

可视化的活细菌细胞蛋白-DNA相互作用使用光活化的单分子跟踪

Protein-DNA interactions are at the heart of many fundamental cellular processes. For example, DNA replication, transcription, repair, and chromosome ...

Application of Long-term cultured Interferon-&#947; Enzyme-linked Immunospot Assay for Assessing Effector and Memory T Cell Responses in Cattle

Effector and memory T cells are generated through developmental programing of na&#239;ve cells following antigen recognition. If the infection is controlled up to 95 % of the T cells generated during the expansion phase are eliminated (i.e., contraction phase) and memory T cells remain, sometimes for a lifetime. In humans, two functionally distinct subsets of memory T cells have been described based on the expression of lymph node homing receptors. Central memory T cells express C-C chemokine receptor 7 and CD45RO and are mainly located in T-cell areas of secondary lymphoid organs. Effector memory T cells express CD45RO, lack CCR7 and display receptors associated with lymphocyte homing to peripheral or inflamed tissues. Effector T cells do not express either CCR7 or CD45RO but upon encounter with antigen produce effector cytokines, such as interferon-&#947;. Interferon-&#947; release assays are used for the diagnosis of bovine and human tuberculosis and detect primarily effector and effector memory T cell responses. Central memory T cell responses by CD4+ T cells to vaccination, on the other hand, may be used to predict vaccine efficacy, as demonstrated with simian immunodeficiency virus infection of non-human primates, tuberculosis in mice, and malaria in humans. Several studies with mice and humans as well as unpublished data on cattle, have demonstrated that interferon-&#947; ELISPOT assays measure central memory T cell responses. With this assay, peripheral blood mononuclear cells are cultured in decreasing concentration of antigen for 10 to 14 days (long-term culture), allowing effector responses to peak and wane; facilitating central memory T cells to differentiate and expand within the culture.

Long-term cultured interferon-&#947; enzyme-linked immunospot assay is used as a measure of central memory responses and correlates with protective anti-mycobacterial vaccine responses. With this assay, peripheral blood mononuclear cells are stimulated with mycobacterial antigens and interleukin-2 for 14 days, enabling differentiation and expansion of central memory T cells.

长期培养的干扰素γ酶联免疫检测方法的评估效应和记忆T细胞应答的牛应用

Effector and memory T cells are generated through developmental programing of na&#239;ve cells following antigen recognition. If the infection is ...

Development and Validation of a Quantitative PCR Method for Equid Herpesvirus-2 Diagnostics in Respiratory Fluids

The protocol describes a quantitative RT-PCR method for the detection and quantification of EHV-2 in equine respiratory fluids according to the NF U47-600 norm. After the development and first validation step, two distinct characterization steps were performed according to the AFNOR norm: (a) characterization of the qRT-PCR assay alone and (b) characterization of the whole analytical method. The validation of the whole analytical method included the portrayal of all steps between the extraction of nucleic acids and the final PCR analysis. 
Validation of the whole method is very important for virus detection by qRT-PCR in order to get an accurate determination of the viral genome load. Since the extraction step is the primary source of loss of biological material, it may be considered the main source of error of quantification between one protocol and another. For this reason, the AFNOR norm NF-U-47-600 recommends including the range of plasmid dilution before the extraction step. In addition, the limits of quantification depend on the source from which the virus is extracted. Viral genome load results, which are expressed in international units (IU), are easier to use in order to compare results between different laboratories. 
This new method of characterization of qRT-PCR should facilitate the harmonization of data presentation and interpretation between laboratories.

Here, we present a protocol for the development and validation of a quantitative PCR method used for the detection and quantification of EHV-2 DNA in equine respiratory fluids. The EHV-2 qRT-PCR validation protocol involves a three-part procedure: development, characterization of qRT-PCR assay alone, and characterization of the whole analytical method.

为马科动物疱疹病毒2诊断的呼吸道液体定量PCR检测方法的开发和验证

The protocol describes a quantitative RT-PCR method for the detection and quantification of EHV-2 in equine respiratory fluids according to the NF U47-600 ...

Establishment of a High-throughput Setup for Screening Small Molecules That Modulate c-di-GMP Signaling in Pseudomonas aeruginosa

Bacterial resistance to traditional antibiotics has driven research attempts to identify new drug targets in recently discovered regulatory pathways. Regulatory systems that utilize intracellular cyclic di-GMP (c-di-GMP) as a second messenger are one such class of target. c-di-GMP is a signaling molecule found in almost all bacteria that acts to regulate an extensive range of processes including antibiotic resistance, biofilm formation and virulence. The understanding of how c-di-GMP signaling controls aspects of antibiotic resistant biofilm development has suggested approaches whereby alteration of the cellular concentrations of the nucleotide or disruption of these signaling pathways may lead to reduced biofilm formation or increased susceptibility of the biofilms to antibiotics. We describe a simple high-throughput bioreporter protocol, based on green fluorescent protein (GFP), whose expression is under the control of the c-di-GMP responsive promoter cdrA, to rapidly screen for small molecules with the potential to modulate c-di-GMP cellular levels in Pseudomonas aeruginosa (P. aeruginosa). This simple protocol can screen upwards of 3,500 compounds within 48 hours and has the ability to be adapted to multiple microorganisms.

Establishment of a High-throughput Setup for Screening Small Molecules That Modulate c-di-GMP Signaling in Pseudomonas aeruginosa

This article describes the high-throughput assay that has been successfully established to screen large libraries of small molecules for their potential ability to manipulate cellular levels of cyclic di-GMP in Pseudomonas aeruginosa, providing a new powerful tool for antibacterial drug discovery and compound testing.

高通量设置的建立筛选小分子能调节C-二GMP信令<em&gt;绿脓杆菌</em

Bacterial resistance to traditional antibiotics has driven research attempts to identify new drug targets in recently discovered regulatory pathways. ...

Assay of Adhesion Under Shear Stress for the Study of T Lymphocyte-Adhesion Molecule Interactions

Overall, T cell adhesion is a critical component of function, contributing to the distinct processes of cellular recruitment to sites of inflammation and interaction with antigen presenting cells (APC) in the formation of immunological synapses. These two contexts of T cell adhesion differ in that T cell-APC interactions can be considered static, while T cell-blood vessel interactions are challenged by the shear stress generated by circulation itself. T cell-APC interactions are classified as static in that the two cellular partners are static relative to each other. Usually, this interaction occurs within the lymph nodes. As a T cell interacts with the blood vessel wall, the cells arrest and must resist the generated shear stress.1,2 These differences highlight the need to better understand static adhesion and adhesion under flow conditions as two distinct regulatory processes. The regulation of T cell adhesion can be most succinctly described as controlling the affinity state of integrin molecules expressed on the cell surface, and thereby regulating the interaction of integrins with the adhesion molecule ligands expressed on the surface of the interacting cell. Our current understanding of the regulation of integrin affinity states comes from often simplistic in vitro model systems. The assay of adhesion using flow conditions described here allows for the visualization and accurate quantification of T cell-epithelial cell interactions in real time following a stimulus. An adhesion under flow assay can be applied to studies of adhesion signaling within T cells following treatment with inhibitory or stimulatory substances. Additionally, this assay can be expanded beyond T cell signaling to any adhesive leukocyte population and any integrin-adhesion molecule pair.

This flow adhesion assay provides a simple, high impact model of T cell-epithelial cell interactions. A syringe pump is used to generate shear stress, and confocal microscopy captures images for quantification. The goal of these studies is to effectively quantify T cell adhesion using flow conditions.

在剪切粘结力的测定T淋巴细胞粘附分子相互作用的研究

Overall, T cell adhesion is a critical component of function, contributing to the distinct processes of cellular recruitment to sites of inflammation and ...

Measuring Influenza Neuraminidase Inhibition Antibody Titers by Enzyme-linked Lectin Assay

Antibodies to neuraminidase (NA), the second most abundant surface protein on influenza virus, contribute toward protection against influenza. Traditional methods to measure NA inhibiting (NI) antibody titers are not practical for routine serology. This protocol describes the enzyme-linked lectin assay (ELLA), a practical alternative method to measure NI titers that is performed in 96 well plates coated with a large glycoprotein substrate, fetuin. NA cleaves terminal sialic acids from fetuin, exposing the penultimate sugar, galactose. Peanut agglutinin (PNA) is a lectin with specificity for galactose and therefore the extent of desialylation can be quantified using a PNA-horseradish peroxidase conjugate, followed by addition of a chromogenic peroxidase substrate. The optical density that is measured is proportional to NA activity. To measure NI antibody titers, serial dilutions of sera are incubated at 37 &#176;C O/N on fetuin-coated plates with a fixed amount of NA. The reciprocal of the highest serum dilution that results in &#8805;50% inhibition of NA activity is designated as the NI antibody titer. The ELLA provides a practical format for routine evaluation of human antibody responses following influenza infection or vaccination.

We describe the enzyme-linked lectin assay (ELLA) for measuring influenza neuraminidase (NA)-inhibition antibody titers in sera. The assay uses peanut agglutinin to quantify galactose residues that become accessible when NA removes sialic acid from fetuin-coated, 96-well plates.

通过酶联凝集素测定来测量神经氨酸酶流感抑制抗体滴度

Antibodies to neuraminidase (NA), the second most abundant surface protein on influenza virus, contribute toward protection against influenza. Traditional ...