作者感谢 ArrayJet 对微阵列机器人的专家建议。SS 和 JS 感谢清迈大学 2022 年基本基金 （FF65/004） 的支持。

图1总结了MAPP方法的主要实验阶段。
1. 样品的制备
注意：在这里，该方法应用于植物组织以用于说明目的。选择的植物是 阿拉比卡咖啡、 Allium sativum var. ophioscorodon和 几个泰国芒果品种（Aokrong、Kam、Rad、Chokanan、Mamkamdang、Talabnak、Mahachanok 和 Nga）。选择这些植物是因为它们具有商业重要性。它们供人类消费的加工会产生目前未充分利用的农工废物，这些废物可能提供增值产品的来源，包括纯聚糖。因此，MAPP被用于表征废弃植物生物质的聚糖组成，用于生物勘探目的。
<ol><li>将植物材料分离成不同的组织（例如，根、茎和叶）。</li>
	<li>将植物组织在40°C的热风烘箱中干燥12-24小时（根据样品减少/增加时间）。或者，将样品在液氮中快速冷冻，然后冻干~4天。</li>
	<li>使用杵和研钵或机械组织裂解器（见 材料表）将样品均质成细粉，每个管中都有一个滚珠轴承。 注意：对于新鲜植物组织，建议在均质化前干燥或冻干。通常，对于大多数干燥样品，用研杵和研钵均质就足够了。对于特别有弹性的样品，如谷物、豆类和加工食品（如意大利面），液氮快速冷冻可以提高样品均质化的速度和效率。我们发现，机械均质化几乎与所有样品类型兼容，速度更快，劳动强度更低，并且有效地将重复使用相同设备（即研杵和研钵）导致样品交叉污染的风险降至最低。</li>
</ol>2.醇不溶性残留物（AIR）的制备
<ol><li>将 1.5 mL 70% （v/v） 乙醇加入 50-100 mg 风干均质样品材料中。</li>
	<li>彻底涡旋混合，然后在室温下以10,000× g 离心10分钟。使用移液管弃去所得上清液并保留沉淀。</li>
	<li>向剩余的沉淀中加入 1.5 mL 甲醇和氯仿 （1：1 [v/v]）。涡旋，离心，并按照步骤2.2弃去上清液。</li>
	<li>向剩余的沉淀中加入 1.5 mL 100% 丙酮。涡旋，离心，并按照步骤2.2弃去上清液。</li>
	<li>将所得颗粒在通风橱中过夜，使残留的丙酮蒸发，或在真空离心机中直至干燥。 注意： AIR 材料可以在环境温度下储存，直到需要为止。</li>
</ol>3. 聚糖提取
注意：如果可能，在组织裂解器中执行所有提取步骤，每个管中都有一个滚珠轴承，以帮助重悬。如果没有组织裂解器，可以通过连续搅拌或摇晃来进行提取。如果无法延长提取时间，则可能需要延长提取时间。
<ol><li>向 10 mg AIR 材料中加入 30 μL/mg 50 mM 环己二胺四乙酸（CDTA;见 材料表），pH 7.5。</li>
	<li>以 27 Hz 摇动 2 分钟，然后以 10 Hz 摇动 2 小时。</li>
	<li>在4°C下以10,000× g 离心10分钟。 保留所得上清液，将其加入无菌微量离心管中，并将其储存在4°C的旋转振荡器上。</li>
	<li>向残留沉淀中加入 30 μL/mg 4 M NaOH + 0.1 % （w/v） NaBH4。 注意：NaBH4 如果吞咽是有毒的。使用个人防护装备 （PPE）。在通风橱下处理。避免灰尘形成。避免吸入灰尘。请勿让产品与水接触。</li>
	<li>重复步骤 3.2 到 3.3。用 dH2O 洗涤残留的沉淀两到三次以除去残留的 NaOH。</li>
	<li>向沉淀中加入30μL / mg纤维素酶（最好是GH5内切-1,4-β-葡聚糖酶，在适当的酶缓冲液中 - 按照制造商的建议;参见 材料表），并在酶最佳温度下孵育16小时。</li>
	<li>将样品在4°C下以10,000× g 离心10分钟。保留上清液，转移到干净的微量离心管中，并在4°C下储存在旋转振荡器上。提取后，必须尽快打印样品。</li>
	<li>在4°C下再次以10,000× g 离心所有储存的提取物10分钟。 注意： 样品必须没有颗粒和碎屑。如有必要，在微阵列打印之前通过0.2μm自旋过滤器。特别是粘性样品与微阵列分析不兼容，因为微阵列仪毛细管和打印头很容易堵塞。作为一般规则，用户应该能够使用标准小容量移液器移液所有用于打印的样品。</li>
</ol>4. 标准的制定
<ol><li>在无菌dH2O中制备1mg / mL定义聚糖标准品（表1）的溶液。如果使用pachyman作为标准品，则溶解在4M NaOH中，并在溶解后用冰醋酸中和。</li>
	<li>将制备的标准品在4°C下在旋转振荡器上储存过夜，以使其完全溶解。</li>
	<li>将所有标准品在4°C下以10,000× g 离心10分钟，以沉淀任何碎片。所得上清液用于后续打印。</li>
</ol>5. 微阵列打印
<ol><li>在甘油系统缓冲液（GSB;混合47%甘油，52.9%dH2O，0.06%Triton X-100和0.04%杀菌剂[0.15%-0.17%硝酸铜和1.4%-2.0%硝酸镁水溶液]中制备1：20（v / v）稀释的黑色印度墨水/绘图墨水，并过滤灭菌）（参见 材料表）并在15,000× g （室温）下离心10分钟。 注意：需要墨水溶液在打印样品周围创建顶部和底部边框，以便可以在膜上目视检测到打印的微阵列。但是，墨水溶液可能含有沉淀物。所有溶液必须不含颗粒才能打印，因此移液时应避免干扰沉淀物。当不再可能时，请丢弃并重新准备。该溶液不容易过滤以去除颗粒。</li>
	<li>向第一个 384 孔板的第一部分加入 40 μL 墨水溶液和 GSB（图 2）。</li>
	<li>向所有稀释 1 （D1） 孔中加入 25 μL GSB。向所有稀释的 2、3 和 4 （D2-D4） 孔中加入 40 μL GSB。</li>
	<li>通过按顺序向 D1 孔中加入 25 μL 提取的聚糖样品，用 GSB 稀释提取的聚糖样品和确定的聚糖底物 1：1 （v/v）。</li>
	<li>从 D1 孔中取出 10 μL 样品并加入 D2 孔中，连续稀释每个样品四次。用移液管轻轻吸出以混合。</li>
	<li>重复该过程，从 D2 孔中取出 10 μL 样品并将其添加到 D3 孔中。</li>
	<li>对 D4 重复上述步骤。混合后，从 D4 孔中取出 10 μL，使每个孔的最终体积为 40 μL。</li>
	<li>将 40 μL 墨水溶液和 GSB 加入最终板的最终块中。</li>
	<li>用粘性板盖盖住板，并在3,000× g （室温）下离心10分钟。确保离心后没有气泡残留，必要时重复。</li>
	<li>使用非接触式压电微阵列打印机器人，按照以下步骤将样品打印到硝酸纤维素膜上（参见 材料表）。 注意：以下是为获得最佳打印质量而建议的措施;然而，所需的具体参数最终将取决于所使用的仪器。我们建议用户联系仪器制造商，讨论其设备所需的适当自定义和打印设置。<ol><li>打印前，清空废液缓冲液储液槽，并根据需要用干净的 GSB 填充干净的缓冲液储液槽。打开仪器并使其稳定 >10 分钟（如果它具有集成的湿度和温度控制系统）。打开微阵列器并初始化系统。 注意： 建议运行测试以确定仪器的内部压力。如果压力太低，则可能需要进行高压吹扫。再次，与仪器制造商联系，讨论特定仪器的具体操作。</li>
		<li>用 GSB 吹扫打印头和毛细管数次，以去除碎屑和潜在污染物。通过单独加载 GSB 板或将仪器设置为直接从干净的缓冲液储液槽中打印来执行测试打印运行，绕过从加载的板中抽取样品。 注意：没有必要使用硝酸纤维素膜进行测试打印;干净的显微镜载玻片就足够了，其优点是在样品打印之前可以目视评估光斑大小、形状和质量。</li>
		<li>打印提取的聚糖样品时，对系统进行编程，使其在每个样品之间用干净的GSB冲洗。 注：通常，每个打印斑点的样品体积为 100 pL 至 10 nL，斑点尺寸范围为 20 μm 至 100 μm，具体取决于所选的样品体积。从一个来源 384 孔板打印 100 个微阵列芯片大约需要 40 分钟，包括系统冲洗。所得微阵列的大小约为 1 cm2 。额外的板将使阵列的长度增加约1厘米。印刷微阵列芯片设计示意图如 图3所示。一旦打印出来，微阵列就可以立即使用，并且可以储存数年。如果由于印刷过程中样品的潜在蒸发而需要重复打印作业，建议装入新的样品板并丢弃原始板。</li>
		<li>每周一次，彻底清洁打印头和毛细管。为此，在GSB中加载含有1：20稀释度的浓缩NaOH的384孔，并在显微镜载玻片上进行40分钟至1小时的打印运行。在继续操作之前，用户应确保此清洁溶液与他们的仪器兼容。</li>
	</ol></li>
	<li>保存为打印微阵列芯片生成的唯一网格文件（.gal 文件），以备下游分析。</li>
</ol>6. 微阵列探测
<ol><li>从硝酸纤维素膜上切下单个相同的打印微阵列，并将它们放入适当大小的容器中进行探测（例如，12孔或24孔微量滴定板）（参见 材料表）。阵列应平放在容器的底部。每个探针需要一个微阵列芯片，代表一个技术重复。</li>
	<li>为了减少非特异性结合，在旋转/摇摆振荡器上，将微阵列在MP-TBST封闭缓冲液（1x Tris缓冲盐水，pH 7.5，+ 0.1%[v/v] TWEEN 20 [TBST]并补充有5%[w/v]脱脂奶粉;参见 材料表）中孵育1小时。确保卷足以淹没整个阵列。</li>
	<li>孵育后，取出 MP-TBST 并用新体积的 MP-TBST 替换它。</li>
	<li>将阵列与单克隆抗体（mAb）或His标记的CBM或其他GRMP（例如凝集素）一起在MP-TBST中孵育2小时，稀释1：10-1：1,000（由制造商指定;参见 材料表）。</li>
	<li>孵育后，取出分子探针溶液并用干净的TBST覆盖阵列，确保阵列完全浸没。要去除残留的探针溶液，请立即取出 TBST 并更换新的体积。将阵列放在旋转/摇摆振荡器上 5 分钟。5 分钟后，取出 TBST，更换新的体积，然后放在旋转/摇摆的摇床上 5 分钟。 注意：此过程应重复三次，不包括最初添加和立即删除 TBST。</li>
	<li>将阵列与碱性磷酸酶偶联的二抗（抗小鼠，抗大鼠，抗兔，抗His，视情况而定;参见 材料表）在MP-TBST中1：1,000稀释2小时，在摇摆/旋转振荡器上孵育。 注：辣根过氧化物酶偶联的二抗也适用，与四甲基联苯胺 （TMB）/过氧化氢底物联合使用以显色。</li>
	<li>孵育后，按照步骤6.5重复洗涤程序，以除去非特异性结合的二抗。</li>
	<li>在硝基蓝四唑（NBT）/5-溴-4-氯-3-吲哚基磷酸酯（BCIP）显色溶液（参见 材料表）中覆盖阵列，用于抗体结合的显色检测。静置直至抗原结合位点出现紫色沉淀斑点（通常为5-30分钟，但应密切监测阵列以避免过饱和，因为反应可能迅速发生）。 注意：BCIP与皮肤接触时是有害的，可能会引起呼吸道刺激。使用个人防护装备。避免灰尘形成。避免吸入灰尘。</li>
	<li>要终止反应，请将阵列浸入干净的自来水中并大量清洗。</li>
	<li>将吸墨纸之间的阵列在室温下放置过夜以干燥。</li>
	<li>丢弃有明显缺陷的阵列，并在这种情况下重复探测协议（图4）。</li>
</ol>7. 分析和量化
<ol><li>使用桌面扫描仪以 2,400 点/英寸 （dpi） 的分辨率扫描开发的阵列。将图像转换为 TIFF 文件，然后转换为底片。</li>
	<li>使用微阵列分析软件（参见 材料表），将唯一的 .gal 网格文件叠加到每个微阵列图像上，以计算每个抗原结合位点产生的斑点的颜色强度并减去局部背景。</li>
	<li>将格网数据导出为 .txt 文件。然后，可以手动将这些数据导入到 Excel 工作表中进行分析。</li>
	<li>首先在每个样品稀释度上平均斑点强度，然后在包含的任何生物重复中平均斑点强度，从而为每个样品生成平均斑点信号强度值。</li>
	<li>将值 100 分配给最高平均点信号强度，并相应地对其余数据进行归一化。 注意：然后，可以使用 Excel33 中的条件格式函数或使用 R ggplot2 包40,41 中的 geom_tile 函数将归一化的平均点信号强度表示为相对聚糖表位丰度的热图。</li>
</ol>

使用微阵列聚合物分析阐明聚糖结构和存在

作者声明没有利益冲突。

这里描述的MAPP技术现在是一种成熟的聚糖分析方法。基本原理于2007年11月首次描述，但该技术经历了不断的发展，以利用微阵列技术、分子探针开发的最新创新以及我们对聚糖生物化学理解的进步。一般来说，聚糖，尤其是多糖，由于其结构复杂性和异质性45，以及它们不容易测序或合成的事实，比蛋白质和核苷酸更具分析性1。在许多情况下，没有一种技术可以最终破译聚糖复杂性;因此，MAPP通常与其他方法一起使用。这就是为什么通常选择AIR制备作为MAPP的起点的原因之一，因为AIR与大多数其他聚糖分析方法兼容34，便于随后的数据集比较。
由于在空气处理之前对样品进行均质化，一些空间信息总是会丢失。然而，由于多糖依次从样品中释放，因此所获得的馏分中表位的存在提供了有关该样品的分子结构和组成的信息17。因此，选择合适的提取方案对于该方法的成功至关重要。多个参数决定了提取方法的适用性：细胞结构、时间、温度、pH值、压力、溶剂的离子强度和固体颗粒样品的细度49。建议使用一系列更具腐蚀性的溶剂，以最大限度地提高成功提取组成聚糖和构建样品代表性成分图的可能性。对于大多数样品，CDTA、NaOH 和纤维素酶足以去除植物来源的储存和细胞壁多糖 33,50,51,52。对于某些组织样品，还包括 CaCl2、HCl 和 Na2CO3 的杂交提取方案已被证明是成功的53，而海洋微藻样品可能需要添加乙二胺四乙酸 （EDTA）10。
微阵列应包括一系列纯净的、明确的聚糖标准品，以用作阳性对照5.包含的标准品应根据样品的性质进行修改。打印后，需要选择合适的GRMP。多糖结构的杂交瘤单克隆抗体的产生具有挑战性54;聚糖结合抗体难以提高，亲和力低55。幸运的是，可以相对容易地获得 CBM 的基因序列信息，用于重组表达4 和工程化它们的结合特异性56,57。虽然已经开发了一个令人印象深刻的GRMP目录，大多数现在都可以从商业来源获得，但相对于自然界中存在的聚糖结构的多样性，只有一小部分被生产并成功表征了58。这可能会限制检测和区分某些结构的能力。建议使用一个或两个代表预期存在的每个主要聚糖结构的探针进行初始探测实验，其结合特异性得到了很好的表征。在随后的探测实验中，探针列表可以扩展到更广泛的聚糖，并深入研究精细结构。
虽然很平凡，但确保在每个孵育步骤后彻底清洗微阵列是探测程序成功的基础。无效去除非特异性结合的探针可能会在显色后引起高背景信号，从而掩盖结果。在这种情况下，有必要从新的微阵列开始重复探测过程。此外，应谨慎接触阵列，只能用镊子握住边缘;硝酸纤维素膜易碎，易损坏。显色解决方案会积聚裂缝和折痕，导致过度饱和，从而阻碍阵列分析。
MAPP 快速、适应性强且方便。该方法与来自任何生物或工业系统的动物、微生物或植物聚糖兼容，只要它们可以提取并固定在硝酸纤维素上，并且具有适当的分子探针。生成的数据提供了详细的、半定量的、成分的见解，这是 通过 其他聚糖分析方法无法轻易获得的。

聚糖在生命的各个领域无处不在，与其他大分子相比，聚糖在结构和功能上表现出无与伦比的多样性1。然而，由于它们的复杂性、生物合成和糖苷键的可变性，以及缺乏解剖聚糖结构的适当方法，我们对这种结构和功能多样性的理解相对有限2.
许多聚糖分析技术具有破坏性，需要将聚糖分解成其组成单糖，这可能会掩盖相关的三维和生物学背景3.相反，单克隆抗体 （mAb）、碳水化合物结合模块 （CBM）、凝集素、病毒凝集素和微生物粘附素（统称为聚糖识别分子探针 （GRMP）4）可识别并结合特定表位，可用作检测和区分复杂多聚糖基质中聚糖的工具 5,6。
在这里，我们介绍了微阵列聚合物分析（MAPP），这是一种快速、通用且无损的聚糖分析方法，适用于广泛的生物样品。该方法旨在提供一种稳健的高通量技术，用于分析来自不同生物和工业/商业系统的聚糖。MAPP 将聚糖定向分子探针的识别特异性与可重复的高性能微阵列筛选技术相结合，允许并行分析数千种分子相互作用。这种方法的结果是对目标样品或组织中聚糖的组成和相对丰度进行诊断。
MAPP 可以作为独立的独立方法使用，也可以与其他生化技术结合使用，例如免疫荧光显微镜 7,8,9 和单糖或连锁分析10,11。该技术还可用于绘制新型GRMP的表位特异性图谱，使用印有纯净且结构明确的寡糖标准品的阵列12。与其他方法（如酶联免疫吸附测定 （ELISA））相比，MAPP 的一个主要优势是它与小体积样品的兼容性13,14。此外，MAPP 可显著提高通量分析15 并提供有效的样品保存形式，因为打印样品在固定在硝酸纤维素上时干燥且稳定16。
GRMP的结合通常取决于许多连续糖残基的存在，这些残基共同形成一个结合位点（表位），该位点是特定多糖类（木聚糖、甘露聚糖、木葡聚糖等）所特有的。17. 相比之下，使用大多数生化技术（例如单糖组成或甲基化分析）量化的单个糖残留物（木糖、甘露糖、葡萄糖）可能是多个多糖类别的成分，因此难以分配18.
MAPP的开发是为了应对技术差距，即能够使用少量材料快速分析来自各种来源的多种聚糖。MAPP利用了过去三十年中开发和表征的GRMP的广泛库目：12,19,20,21,22,23,24,25,26,27,28,29,30,31,32.MAPP的发展是一个迭代的过程，技术也在不断完善和优化。现在有大量文献描述了MAPP在各种自然和工业系统中的应用，其中聚糖起着核心作用5,6,9,10,21,33,34,35,36,37,38,39。在这里，我们描述了MAPP的当前技术水平。

<table><tbody><tr><td>1,3:1,4-&amp;beta;-D-Glucan, Lichenan (icelandic moss)</td><td>Megazyme</td><td>P-LICHN</td><td></td></tr><tr><td>1,4-&amp;beta;-D-Mannan</td><td>Megazyme</td><td>P-MANCB</td><td></td></tr><tr><td>384-well microtiter plate</td><td>Greiner Bio-One</td><td>M1686</td><td></td></tr><tr><td>5-bromo-4-chloro-3-indolyl-phosphate (BCIP)</td><td>Melford</td><td>B74100-1.0</td><td></td></tr><tr><td>Acetone</td><td>Sigma</td><td>270725</td><td></td></tr><tr><td>Alkaline Phosphatase AffiniPure Goat Anti-Mouse IgG (H+L)</td><td>Jackson ImmunoResearch</td><td>115-055-003</td><td></td></tr><tr><td>Alkaline Phosphatase AffiniPure Goat Anti-Rat IgG (H+L)</td><td>Jackson ImmunoResearch</td><td>112-055-003</td><td></td></tr><tr><td>Alkaline Phosphatase AffiniPure Rabbit Anti-His Tag</td><td>Jackson ImmunoResearch</td><td>300-055-240</td><td></td></tr><tr><td>Arabinoxylan (wheat)</td><td>Megazyme</td><td>P-WAXYL</td><td></td></tr><tr><td>Array-Pro Analyzer Software</td><td>Media Cybernetics</td><td>Version 6.3</td><td></td></tr><tr><td>&lt;em&gt;Bacillus &lt;/em&gt;sp. Cellulase 5A (BCel5A)</td><td>NZYTech</td><td>CZ0564</td><td></td></tr><tr><td>BAM antibodies</td><td>SeaProbes</td><td>Various</td><td></td></tr><tr><td>Black drawing ink (indian ink)</td><td>Winsor &amp;amp; Newton</td><td>GWD030</td><td></td></tr><tr><td>Carbohydrate binding modules</td><td>NZYTech</td><td>Various</td><td></td></tr><tr><td>CCRC antibodies</td><td>CarboSource</td><td>Various</td><td></td></tr><tr><td>CDTA</td><td>Sigma</td><td>319945</td><td></td></tr><tr><td>Chloroform</td><td>Sigma</td><td>PHR1552</td><td></td></tr><tr><td>Ethanol</td><td>Sigma</td><td>1.11727</td><td></td></tr><tr><td>Galactan (potato)</td><td>Megazyme</td><td>P-GALPOT</td><td></td></tr><tr><td>Galactomannan (carob)</td><td>Megazyme</td><td>P-GALML</td><td></td></tr><tr><td>Glycerol solution</td><td>Sigma</td><td>49781-5L</td><td></td></tr><tr><td>Gum tragacanth (legumes)</td><td>Sigma-Aldrich</td><td>G1128</td><td></td></tr><tr><td>INCh antibodies</td><td>INRA</td><td>Various</td><td></td></tr><tr><td>LM and JIM antibodies</td><td>PlantProbes</td><td>Various</td><td></td></tr><tr><td>Marathon Argus Microarray Printer</td><td>ArrayJet</td><td></td><td></td></tr><tr><td>Methanol</td><td>Sigma&amp;nbsp;</td><td>34860</td><td></td></tr><tr><td>Monoclonal antibodies</td><td>Biosupplies Australia</td><td>Various</td><td></td></tr><tr><td>NaBH&lt;sub&gt;4&lt;/sub&gt;</td><td>Sigma</td><td>452882</td><td></td></tr><tr><td>NaOH</td><td>Sigma</td><td>S5881</td><td></td></tr><tr><td>Nitro-blue tetrazolium (NBT)</td><td>Melford</td><td>N66000-1.0</td><td></td></tr><tr><td>Nitrocellulose membrane</td><td>Thermo Fisher Scientific</td><td>88018</td><td></td></tr><tr><td>Pectin (degree of methyl esterification 46%)</td><td>Danisco</td><td>NA</td><td></td></tr><tr><td>ProClin 200</td><td>Sigma</td><td>48171-U</td><td></td></tr><tr><td>Rhamnogalacturonan (soybean pectic fibre)</td><td>Megazyme</td><td>P-RHAGN</td><td></td></tr><tr><td>Rotating mixer</td><td>Fisher Scientific</td><td>88-861-050</td><td></td></tr><tr><td>Rotating/rocking Shaker</td><td>Cole-Parmer</td><td></td><td></td></tr><tr><td>Skimmed milk powder</td><td>Marvel</td><td></td><td></td></tr><tr><td>Spin filter</td><td>Costar Spin-X</td><td>8160</td><td></td></tr><tr><td>Stainless steel beads</td><td>Qiagen</td><td>69989</td><td></td></tr><tr><td>TissueLyser II</td><td>Qiagen</td><td>85300</td><td></td></tr><tr><td>Tris</td><td>Sigma</td><td>93362</td><td></td></tr><tr><td>Triton X-100</td><td>Sigma</td><td>T8787-250ML</td><td></td></tr><tr><td>Tween 20</td><td>Sigma</td><td>P9416-100ML</td><td></td></tr><tr><td>Xylan (beechwood)</td><td>Megazyme</td><td>P-XYLNBE</td><td></td></tr><tr><td>Xyloglucan (tamarind)</td><td>Megazyme</td><td>P-XYGLN</td><td></td></tr><tr><td>&amp;beta;-Glucan (oat)</td><td>Megazyme</td><td>P-BGOM</td><td></td></tr></tbody></table>

microarray polymer profiling (mapp) for high-throughput glycan analysis

微阵列聚合物分析（MAPP）是一种可靠且可重复的方法，用于系统地确定各种生物样品（包括植物和藻类组织、食品材料以及人类、动物和微生物样品）中聚糖和糖缀合物的组成和相对丰度。微阵列技术通过提供小型化、高通量筛选平台来支持该方法的功效，允许仅使用少量分析物即可同时表征聚糖和高度特异性聚糖定向分子探针之间的数千种相互作用。组成聚糖经过化学和酶促分馏，然后依次从样品中提取并直接固定在硝酸纤维素膜上。聚糖组成是通过将特定的聚糖识别分子探针附着在勒索和打印的分子上来确定的。MAPP是对传统聚糖分析技术的补充，如单糖和连锁分析以及质谱分析。然而，聚糖识别分子探针提供了对聚糖结构构型的见解，这有助于阐明生物相互作用和功能作用。

MAPP用于测定农业生物质废物的聚糖组成，包括泰国北部几个品种的芒果皮、阿拉比卡咖啡樱桃浆和咖啡豆加工废物，以及泰国黑蒜的根、茎和叶组织。 几种植物来源的多糖在食品工业中用作功能性成分42,43。因此，本实验的目的是推断这些丰富且目前未充分利用的农工废料是否可以提供增值纯多糖的来源。
空气材料通常用于制备用于聚糖分析的样品44。使用 AIR 有几个优点;用溶剂处理可有效去除内源性CAZymes、代谢物、小糖、脂质和色素，从而产生富含多糖和结构蛋白的样品34。此外，生产 AIR 是延长样品寿命的一种快速有效的方法，因为它具有热稳定性，可以储存数年。
使用CDTA、NaOH和纤维素酶从植物AIR材料中依次提取三种混合组分的组成聚糖。CDTA螯合Ca2+ 离子，从而从植物细胞壁中去除Ca2+ 交联的去酯化果胶45。碱性条件允许主要释放半纤维素，如甘露聚糖、木聚糖和β-葡聚糖，这是由于纤维素微纤维和半纤维素以及木质素和半纤维素之间的氢键和酯键皂化破坏而释放的 46.来自 芽孢杆菌 属的重组内切-1,4-β-葡聚糖酶用于降解结构纤维素微纤维的无定形区域，释放与细胞壁内纤维素结合的残留聚糖47。虽然这种方法有效地将聚糖分为这三大类，但应该注意的是，样品并不纯;由于提取方法的性质，如果样品中存在半纤维素，则不可避免地会被提取，并随后在全面性协定和纤维素酶组分中检测到不同程度的半纤维素。同样，如果样品中存在一些果胶，则会在 NaOH 提取中检测到一些果胶。
使用非接触式压电微阵列打印机器人 通过非共 价附着11 将提取的聚糖馏分固定在硝酸纤维素上，形成 300 个相同的微阵列。确定的聚糖标准品（表1）也作为阳性对照包含在打印的微阵列中（图5）。为所选聚糖标准品获得的 MAPP 结合谱与先前报道的表位特异性相对应。例如，LM21 与多种甘露聚糖（半乳甘露聚糖和葡甘露聚糖）表现出强结合，而 LM22 仅表现出与半乳甘露聚糖25 的弱结合。类似地，LM19优先与脱酯化的高半乳糖醛聚糖48结合，LM15优先与罗望子种子木聚糖23结合。
通过将聚糖定向单克隆抗体（表2）附着到印刷提取物上，检测了16个表位的相对丰度，诊断为非纤维素植物细胞壁多糖（图6）。大多数提取的聚糖是在碱性NaOH馏分中检测到的。在所有测试的芒果品种的果皮中记录了代表木聚糖/阿拉伯木聚糖的单克隆抗体 LM10 和 LM11 的强结合信号。在大蒜样品中，LM10 和 LM11 优先与根组织提取物 （Garlic R） 结合，并且仅与叶组织提取物 （Garlic L） 表现出弱结合。LM19 代表部分甲基酯化或未酯化的高半乳糖醛酸，与某些芒果品种提取物（Aokrong 和 Talabnak）强结合，但在其他品种（Chokanan、Mamkamdang、Mahachanok 和 Nga）中仅结合微弱，或无法检测到其结合。此外，LM19仅与咖啡果肉馏分结合，不与咖啡豆加工废料结合，以前认为咖啡豆由半纯化咖啡果胶组成（未发表的数据）。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65443/65443fig01.jpg"> 图1：MAPP方法的主要实验步骤。 （A） 样品被均质化以形成细粉。（B） 对均质样品进行处理以分离其 AIR。（C） 使用定制的提取方案依次提取组成聚糖。（D） 根据板布局，将提取的聚糖馏分、墨水和 GSB 转移到 384 孔板中，用于打印到硝酸纤维素上。（E）用选定的GRMP探测打印的微阵列。 （F）在将数据呈现为热图之前，对GRMP与打印的聚糖组分的结合进行量化和分析。 <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65443/65443fig01large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65443/65443fig02.jpg"> 图 2：用于样品、墨水和 GSB 上样的 384 孔板布局示例，每个提取的聚糖样品/标准品有 4 次稀释。 不同的颜色表示由不同提取试剂产生的样品，而不同的深浅表示连续稀释。代码中的第一个数字表示样品编号，而结束编号表示稀释数（D1 表示稀释度 1，D2 表示稀释度 2，依此类推）。例如，标记为“12D3”的孔表示聚糖样品12，稀释3。孔板应分为八个相同的部分，包括六列和八行。第一块印版的第一部分应仅包含墨水和缓冲液，并类似于示例印版布局。然后，可以根据板布局将提取的聚糖样品加载到后续的板切片中。不应将不同的提取试剂加载到同一板部分。如果没有足够的样品来填充整个切片，则用缓冲液填充该切片中的所有剩余孔;不要让任何井空着。如果需要多个印版，则加载所有样品后的下一部分应包含三列交替的墨水和 GSB——这可能不是第八部分，具体取决于要打印的样品数量。 <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65443/65443fig02large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65443/65443fig03.jpg"> 图 3：印刷微阵列芯片设计的示意图。 <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65443/65443fig03large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/65443/65443fig04.jpg"> 图 4：代表性微阵列。 （A） 无绑定。（B）结合信号被高背景信号遮挡。（C） 由于 NBT/BCIP 过饱和而导致的全身性蓝色/紫色染色。（D） 由于基材浓度高而导致的探测缺陷。（E） 由于打印头不干净而导致的打印缺陷。（F）与少数样品结合力强。（G） 与许多样品结合力强。 <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65443/65443fig04large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/65443/65443fig05.jpg"> 图 5：单克隆抗体与确定的聚糖标准品结合，用于验证打印和探测过程。 <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65443/65443fig05large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/65443/65443fig06.jpg"> 图6：从农业生物质废物中提取的聚糖的MAPP。 样品包括咖啡果肉废料（咖啡果肉和咖啡果胶）、几个泰国品种（AO、Aokrong;高甘;RD， 拉德;CH： 乔卡南;MA， Mamkamdang;TL， 塔拉布纳克;MH，马哈哈诺克;NG、Nga）和黑蒜叶（大蒜L）、茎（大蒜S）、鳞茎（大蒜BG）和根（大蒜R），使用CDTA、NaOH和纤维素酶（芽孢杆 菌属纤维素酶5A）。 <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65443/65443fig06large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
表1：将MAPP分析中使用的商业多糖标准品定义为阳性对照。<a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65443/65443_Table%201.xlsx" target="_blank">请按此下载此表格。</a>
表2：选择用于检测提取的植物聚糖微阵列的聚糖定向单克隆抗体。<a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65443/65443_Table%202.xlsx" target="_blank">请按此下载此表格。</a>

Watch this Scientific Journal Video about MAPP Protocol – Advancing Glycan Analysis at JoVE.com

作者聚焦：MAPP 实验方案 – 推进游离寡糖分析 

微阵列聚合物分析（MAPP）是一种高通量技术，用于对生物样品中的聚糖进行成分分析。

用于高通量聚糖分析的微阵列聚合物分析 （MAPP）

Microarray polymer profiling (MAPP) is a robust and reproducible approach to systematically determine the composition and relative abundance of glycans ...

我们的研究重点是复杂聚糖在各种家庭、工业和商业系统中的发生功能和结构。对非接触式微阵列技术的进一步改进以及我们快速访问碳水化合物结合模块序列信息的能力正在提高我们打印和检测聚糖微阵列的能力。由于聚糖在生物合成中的结构异质性、复杂性和可变性，研究聚糖具有挑战性。许多聚糖分析方法需要将聚糖分解成其组成单糖。MAPP提供了一个多功能的聚糖分析平台，可保留许多重要的结构3D信息。

microarray-polymer-profiling-mapp-for-high-throughput-glycan-analysis

Universidad de Cartagena UDEC

Research

JoVE Journal

Biology

Microarray Polymer Profiling (MAPP) for High-Throughput Glycan Analysis

1.6K 次观看.  Newcastle University. 我们的研究重点是复杂聚糖在各种家庭、工业和商业系统中的发生功能和结构。对非接触式微阵列技术的进一步改进以及我们快速访问碳水化合物结合模块序列信息的能力正在提高我们打印和检测聚糖微阵列的能力。由于聚糖在生物合成中的结构异质性、复杂性和可变性，研究聚糖具有挑战性。许多聚糖分析方法需要将聚糖分解成其组成单糖。MAPP提供了一个多功能的聚...

视频: 作者聚焦：MAPP 实验方案 – 推进游离寡糖分析 

Polymer Microarrays for High Throughput Discovery of Biomaterials

The discovery of novel biomaterials that are optimized for a specific biological application is readily achieved using polymer microarrays, which allows a combinatorial library of materials to be screened in a parallel, high throughput format1. Herein is described the formation and characterization of a polymer microarray using an on-chip photopolymerization technique 2. This involves mixing monomers at varied ratios to produce a library of monomer solutions, transferring the solution to a glass slide format using a robotic printing device and curing with UV irradiation. This format is readily amenable to many biological assays, including stem cell attachment and proliferation, cell sorting and low bacterial adhesion, allowing the ready identification of 'hit' materials that fulfill a specific biological criterion3-5. Furthermore, the use of high throughput surface characterization (HTSC) allows the biological performance to be correlated with physio-chemical properties, hence elucidating the biological-material interaction6. HTSC makes use of water contact angle (WCA) measurements, atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). In particular, ToF-SIMS provides a chemically rich analysis of the sample that can be used to correlate the cell response with a molecular moiety. In some cases, the biological performance can be predicted from the ToF-SIMS spectra, demonstrating the chemical dependence of a biological-material interaction, and informing the development of hit materials5,3.

A description of the formation of a polymer microarray using an on-chip photopolymerization technique. The high throughput surface characterization using atomic force microscopy, water contact angle measurements, X-ray photoelectron spectroscopy and time of flight secondary ion mass spectrometry and a cell attachment assay is also described.

聚合物芯片高通量发现的生物材料

The discovery of novel biomaterials that are optimized for a specific biological application is readily achieved using polymer microarrays, which allows a ...

科研

生物工程

Glycan Node Analysis: A Bottom-up Approach to Glycomics

Synthesized in a non-template-driven process by enzymes called glycosyltransferases, glycans are key players in various significant intra- and extracellular events. Many pathological conditions, notably cancer, affect gene expression, which can in turn deregulate the relative abundance and activity levels of glycoside hydrolase and glycosyltransferase enzymes. Unique aberrant whole glycans resulting from deregulated glycosyltransferase(s) are often present in trace quantities within complex biofluids, making their detection difficult and sometimes stochastic. However, with proper sample preparation, one of the oldest forms of mass spectrometry (gas chromatography-mass spectrometry, GC-MS) can routinely detect the collection of branch-point and linkage-specific monosaccharides ("glycan nodes") present in complex biofluids. Complementary to traditional top-down glycomics techniques, the approach discussed herein involves the collection and condensation of each constituent glycan node in a sample into a single independent analytical signal, which provides detailed structural and quantitative information about changes to the glycome as a whole and reveals potentially deregulated glycosyltransferases. Improvements to the permethylation and subsequent liquid/liquid extraction stages provided herein enhance reproducibility and overall yield by facilitating minimal exposure of permethylated glycans to alkaline aqueous conditions. Modifications to the acetylation stage further increase the extent of reaction and overall yield. Despite their reproducibility, the overall yields of N-acetylhexosamine (HexNAc) partially permethylated alditol acetates (PMAAs) are shown to be inherently lower than their expected theoretical value relative to hexose PMAAs. Calculating the ratio of the area under the extracted ion chromatogram (XIC) for each individual hexose PMAA (or HexNAc PMAA) to the sum of such XIC areas for all hexoses (or HexNAcs) provides a new normalization method that facilitates relative quantification of individual glycan nodes in a sample. Although presently constrained in terms of its absolute limits of detection, this method expedites the analysis of clinical biofluids and shows considerable promise as a complementary approach to traditional top-down glycomics.

This article presents an enhanced form of a novel bottom-up glycomics technique designed to analyze the pooled compositional profile of glycans in unfractionated biofluids through the chemical breakdown of glycans into their constituent linkage-specific monosaccharides for detection by GC-MS. Potential applications include early detection of cancer and other glycan-affective disorders.

聚糖节点分析:自下而上的方法，以糖原组学

Synthesized in a non-template-driven process by enzymes called glycosyltransferases, glycans are key players in various significant intra- and ...

化学

Profiling Anti-Neu5Gc IgG in Human Sera with a Sialoglycan Microarray Assay

Cells are covered with a cloak of carbohydrate chains (glycans) that is commonly altered in cancer and that includes variations in sialic acid (Sia) expression. These are acidic sugars that have a 9-carbon backbone and that cap vertebrate glycans on cell surfaces. Two of the major Sia forms in mammals are N-acetylneuraminic acid (Neu5Ac) and its hydroxylated form, N-glycolylneuraminic acid (Neu5Gc). Humans cannot produce endogenous Neu5Gc due to the inactivation of the gene encoding cytidine 5&#39;monophosphate-Neu5Ac (CMP-Neu5Ac) hydroxylase (CMAH). Foreign Neu5Gc is acquired by human cells through the dietary consumption of red meat and dairy and subsequently appears on diverse glycans on the cell surface, accumulating mostly on carcinomas. Consequently, humans have circulating anti-Neu5Gc antibodies that play diverse roles in cancer and other chronic inflammation-mediated diseases and that are becoming potential diagnostic and therapeutic targets. Here, we describe a high-throughput sialoglycan microarray assay to assess such anti-Neu5Gc antibodies in the human sera. Neu5Gc-containing glycans and their matched pairs of controls (Neu5Ac-containing glycans), each with a core primary amine, are covalently linked to epoxy-coated glass slides. We exemplify the printing of 56 slides in a 16-well format using a specific nano-printer capable of generating up to 896 arrays per print. Each slide can be used to screen 16 different human sera samples for the evaluation of anti-Neu5Gc antibody specificity, intensity, and diversity. The protocol describes the complexity of this robust tool and provides a basic guideline for those aiming to investigate the response to Neu5Gc dietary carbohydrate antigen in diverse clinical samples in an array format.

A sialoglycan microarray assay can be used to evaluate anti-Neu5Gc antibodies in human sera, making it a potential high-throughput diagnostic assay for cancer and other chronic inflammation-mediated human diseases.

使用唾液酸多糖微阵列测定在人血清中分析抗Neu5Gc IgG

Cells are covered with a cloak of carbohydrate chains (glycans) that is commonly altered in cancer and that includes variations in sialic acid (Sia) ...

行为学

N-glycan Profiling of Glycoproteins by Hydrophilic Interaction Liquid Chromatography with Fluorescence and Mass Spectrometric Detection

Glycosylation is a vital modification found in proteins. N-glycan profiling of glycoproteins is required to detect novel biomarker candidates and determine glycan alterations in diseases. Most commercially available biopharmaceutical proteins are glycoproteins. The efficacy of these drugs is affected by glycosylation patterns. Therefore, an in-depth characterization method for the N-glycans is necessary. Here, we present a comprehensive approach for qualitative and quantitative analysis of N-glycans using hydrophilic interaction liquid chromatography equipped with fluorescence detection and tandem mass spectrometry (HILIC-FLD-MS/MS). N-glycans were released from glycoproteins with a facile method and labeled by a procainamide fluorophore tag in the strategy. Subsequently, the procainamide labeled N-glycans were analyzed by a HILIC-FLD-MS/MS technique. In this approach, N-glycan structures were confirmed by the tandem mass spectrometric analysis, whereas fluorescence detection was used for the quantitative analysis. An application for data analysis of the detected N-glycan peaks is described in the study. This protocol can be applied to any glycoprotein extracted from various species.

N-glycan Profiling of Glycoproteins by Hydrophilic Interaction Liquid Chromatography with Fluorescence and Mass Spectrometric Detection

N-glycan profiling of glycoproteins is essential for discovering novel biomarkers and understanding glycan functions in cellular events. Additionally, N-glycan analysis of protein biopharmaceuticals is very important for human use. In this current article, a high-throughput strategy for identifying and quantifying N-glycan structures was presented using the HILIC-FLD-MS/MS technique.

Glycosylation is a vital modification found in proteins. N-glycan profiling of glycoproteins is required to detect novel biomarker candidates and ...

生物化学

<meta charset="utf8"></head><body>使用糖组学指导的糖蛋白质组学分析结直肠癌组织

Glycomics-Guided Glycoproteomics Facilitates Comprehensive Profiling of the Glycoproteome in Complex Tumor Microenvironments

Glycosylation is a common and structurally diverse protein modification that impacts a wide range of tumorigenic processes. Mass spectrometry-driven glycomics and glycoproteomics have emerged as powerful approaches to analyze liberated glycans and intact glycopeptides, respectively, offering a deeper understanding of the heterogeneous glycoproteome in the tumor microenvironment (TME). This protocol details the glycomics-guided glycoproteomics method, an integrated omics technology, which firstly employs porous graphitized carbon-LC-MS/MS-based glycomics to elucidate the glycan structures and their quantitative distribution in the glycome of tumor tissues, cell populations, or bodily fluids being investigated. This allows for a comparative glycomics analysis to identify altered glycosylation across patient groups, disease stages, or conditions, and, importantly, serves to enhance the downstream glycoproteomics analysis of the same sample(s) by creating a library of known glycan structures, thus reducing the data search time and the glycoprotein misidentification rate. Focusing on N-glycoproteome profiling, the sample preparation steps for the glycomics-guided glycoproteomics method are detailed in this protocol, and key aspects of the data collection and analysis are discussed. The glycomics-guided glycoproteomics method provides quantitative information on the glycoproteins present in the TME and their glycosylation sites, site occupancy, and site-specific glycan structures. Representative results are presented from formalin-fixed paraffin-embedded tumor tissues from colorectal cancer patients, demonstrating that the method is sensitive and compatible with tissue sections commonly found in biobanks. Glycomics-guided glycoproteomics, therefore, offers a comprehensive view into the heterogeneity and dynamics of the glycoproteome in complex TMEs, generating robust biochemical data required to better understand the glycobiology of cancers.

<meta charset="utf8"></head><body>糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

This protocol details the glycomics-guided glycoproteomics method, an integrated omics technology that offers comprehensive insights into the heterogeneous glycoproteome in complex tumor microenvironments required to better understand the glycobiology of cancers.

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组 

Glycosylation is a common and structurally diverse protein modification that impacts a wide range of tumorigenic processes. Mass spectrometry-driven ...

癌症研究

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System

Monoclonal antibodies (mAbs) are one of the most popular and well-characterized biological products manufactured today. Most commonly produced using Chinese hamster ovary (CHO) cells, culture and process conditions must be optimized to maximize antibody titers and achieve target quality profiles. Typically, this optimization uses automated microscale bioreactors (15 mL) to screen multiple process conditions in parallel. Optimization criteria include culture performance and the critical quality attributes (CQAs) of the monoclonal antibody (mAb) product, which may impact its efficacy and safety. Culture performance metrics include cell growth and nutrient consumption, while the CQAs include the mAb's N-glycosylation and aggregation profiles, charge variants, and molecular weight. This detailed protocol describes how to purify and subsequently analyze HCCF samples produced by an automated microbioreactor system to gain valuable performance metrics and outputs. First, an automated protein A fast protein liquid chromatography (FPLC) method is used to purify the mAb from harvested cell culture samples. Once concentrated, the glycan profiles are analyzed by mass spectrometry using a specific platform (refer to the Table of Materials). Antibody molecular weights and aggregation profiles are determined using size exclusion chromatography-multiple angle light scattering (SEC-MALS), while charge variants are analyzed using microchip capillary zone electrophoresis (mCZE). In addition to the culture performance metrics captured during the bioreactor process (i.e., culture viability, cell counts, and common metabolites including glutamine, glucose, lactate, and ammonia), spent media is analyzed to identify limiting nutrients to improve the feeding strategies and overall process design. Therefore, a detailed protocol for the absolute quantification of amino acids by liquid chromatography-mass spectrometry (LC-MS) of spent media is also described. The methods used in this protocol take advantage of high-throughput platforms that are compatible for large numbers of small-volume samples.

A detailed protocol for the purification and subsequent analysis of a monoclonal antibody from harvested cell culture fluid (HCCF) of automated microbioreactors has been described. Use of analytics to determine critical quality attributes (CQAs) and maximizing limited sample volume to extract vital information is also presented.

使用自动微生物反应器系统从中国仓鼠卵巢细胞中纯化和分析单克隆抗体

Monoclonal antibodies (mAbs) are one of the most popular and well-characterized biological products manufactured today. Most commonly produced using ...

Printed Glycan Array: A Sensitive Technique for the Analysis of the Repertoire of Circulating Anti-carbohydrate Antibodies in Small Animals

The repertoire of circulating anti-carbohydrate antibodies of a given individual is often associated with its immunological status. Not only the individual immune condition determines the success in combating internal and external potential threat signals, but also the existence of a particular pattern of circulating anti-glycan antibodies (and their serological level variation) could be a significant marker of the onset and progression of certain pathological conditions. Here, we describe a Printed Glycan Array (PGA)-based methodology that offers the opportunity to measure hundreds of glycan targets with very high sensitivity; using a minimal amount of sample, which is a common restriction present when small animals (rats, mice, hamster, etc.) are used as models to address aspects of human diseases. As a representative example of this approach, we show the results obtained from the analysis of the repertoire of natural anti-glycan antibodies in BALB/c mice. We demonstrate that each BALB/c mouse involved in the study, despite being genetically identical and maintained under the same conditions, develops a particular pattern of natural anti-carbohydrate antibodies. This work claims to expand the use of PGA technology to investigate repertoire (specificities) and the levels of circulating anti-carbohydrates antibodies, both in health and during any pathological condition.

This work shows the potential of printed glycan array (PGA) technology for the analysis of circulating anti-carbohydrate antibodies in small animals.

印制糖类阵列是分析小动物循环抗碳水化合物抗体汇辑的一种敏感技术

The repertoire of circulating anti-carbohydrate antibodies of a given individual is often associated with its immunological status. Not only the ...

免疫与感染

Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples

In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed.
Introduction
Glycosylation of protein, which is the most ubiquitous post-translational modification on proteins, modifies the physical, chemical, and biological properties of a protein, and plays a fundamental role in various biological processes1-6. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases 7-12. In fact, most current cancer biomarkers, such as the L3 fraction of &alpha;-1 fetoprotein (AFP) for hepatocellular carcinoma 13-15, and CA199 for pancreatic cancer 16, 17 are all aberrant glycan moieties on glycoproteins. However, methods to study protein glycosylation have been complicated, and not suitable for routine laboratory and clinical settings. Chen et al. has recently invented a chemically blocked antibody microarray with a glycan-binding protein (GBP) detection method for high-throughput and multiplexed profile glycosylation of native glycoproteins in a complex sample 18. In this affinity based microarray method, multiple immobilized glycoprotein-specific antibodies capture and isolate glycoproteins from the complex mixture directly on the microarray slide, and the glycans on each individual captured protein are measured by GBPs. Because all normal antibodies contain N-glycans which could be recognized by most GBPs, the critical step of this method is to chemically block the glycans on the antibodies from binding to GBP. In the procedure, the cis-diol groups of the glycans on the antibodies were first oxidized to aldehyde groups by using NaIO4 in sodium acetate buffer avoiding light. The aldehyde groups were then conjugated to the hydrazide group of a cross-linker, 4-(4-N-MaleimidoPhenyl)butyric acid Hydrazide HCl (MPBH), followed by the conjugation of a dipeptide, Cys-Gly, to the maleimide group of the MPBH. Thus, the cis-diol groups on glycans of antibodies were converted into bulky none hydroxyl groups, which hindered the lectins and other GBPs bindings to the capture antibodies. This blocking procedure makes the GBPs and lectins bind only to the glycans of captured proteins. After this chemically blocking, serum samples were incubated with the antibody microarray, followed by the glycans detection by using different biotinylated lectins and GBPs, and visualized with Cy3-streptavidin. The parallel use of an antibody panel and multiple lectin probing provides discrete glycosylation profiles of multiple proteins in a given sample 18-20. This method has been used successfully in multiple different labs 1, 7, 13, 19-31. However, stability of MPBH and Cys-Gly, complicated and extended procedure in this method affect the reproducibility, effectiveness and efficiency of the method. In this new protocol, we replaced both MPBH and Cys-Gly with one much more stable reagent glutamic acid hydrazide (Glu-hydrazide), which significantly improved the reproducibility of the method, simplified and shorten the whole procedure so that the it can be completed within one working day. In this new protocol, we describe the detailed procedure of the protocol which can be readily adopted by normal labs for routine protein glycosylation study and techniques which are necessary to obtain reproducible and repeatable results.

In this study, we describe an improved protocol for a multiplexed high-throughput antibody microarray with lectin detection method that can be used in glycosylation profiling of specific proteins. This protocol features new reliable reagents and significantly reduces the time, cost, and lab equipment requirements as compared to the previous procedure.

化学阻断抗体芯片复用高通量的复杂样品中特定蛋白糖基化的剖析

 In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that ...

用于高通量聚糖分析的微阵列聚合物分析（MAPP）

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此视频中的章节

聚合物芯片高通量发现的生物材料

聚糖节点分析:自下而上的方法，以糖原组学

使用唾液酸多糖微阵列测定在人血清中分析抗Neu5Gc IgG

N-glycan Profiling of Glycoproteins by Hydrophilic Interaction Liquid Chromatography with Fluorescence and Mass Spectrometric Detection

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

使用自动微生物反应器系统从中国仓鼠卵巢细胞中纯化和分析单克隆抗体

印制糖类阵列是分析小动物循环抗碳水化合物抗体汇辑的一种敏感技术

化学阻断抗体芯片复用高通量的复杂样品中特定蛋白糖基化的剖析

用于高通量聚糖分析的微阵列聚合物分析 （MAPP）

副本

摘要

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此视频中的章节

聚合物芯片高通量发现的生物材料

聚糖节点分析:自下而上的方法，以糖原组学

使用唾液酸多糖微阵列测定在人血清中分析抗Neu5Gc IgG

N-glycan Profiling of Glycoproteins by Hydrophilic Interaction Liquid Chromatography with Fluorescence and Mass Spectrometric Detection

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

使用自动微生物反应器系统从中国仓鼠卵巢细胞中纯化和分析单克隆抗体

印制糖类阵列是分析小动物循环抗碳水化合物抗体汇辑的一种敏感技术

化学阻断抗体芯片复用高通量的复杂样品中特定蛋白糖基化的剖析

用于高通量聚糖分析的微阵列聚合物分析（MAPP）