OMAP-1 Organ Mapping Antibody Panel (OMAP) for Multiplexed Antibody-Based Imaging of Human Lymph Node with IBEX, v1.4

OMAP-1 was designed for IBEX (Iterative Bleaching Extends multi-pleXity) imaging of fixed frozen human lymph nodes<br>(https://doi.org/10.1038/s41596-021-00644-9; https://doi.org/10.1073/pnas.2018488117). The panel contains 39<br>antibodies and the nuclear marker Hoechst 33342 for image alignment and nuclear segmentation. his OMAP provides a<br>spatial context for all anatomical structures and most cell types present in the [ASCT+B lymph node table,<br>v1.1](https://doi.org/10.48539/HBM573.SHCQ.259). Additionally, the inclusion of protein biomarkers BCL2, CD10, CD138,<br>and CD44 allow profiling of lymph node disease states, e.g. follicular lymphoma and metastasis. The core and<br>prioritized OMAP targets detailed here overlap (~50-85%) with panels developed for multiplexed imaging of lymphoid<br>samples using other technologies and sample preparations (https://doi.org/10.7554/eLife.31657,<br>https://doi.org/10.1002/eji.202048891). This OMAP does not contain antibodies for typing pericytes, plasmacytoid<br>dendritic cells, or different T helper lineages (Th1, Th2, Th17). Beyond spatial mapping of healthy human lymph nodes,<br>this OMAP was used to characterize the tissue microenvironment of follicular lymphoma lymph nodes. For this study,<br>object-based cellular segmentation was performed using a convolutional neural network (CNN)-based approach with Mask<br>R-CNN architecture and ResNet-50 as a backbone. As an input three channels were used: Hoechst for nuclei, CD45 as a<br>base membrane, and composite of several other membrane markers (CD138, CD163, CD94, CD69, CD8, CD4). More details and<br>accompanying datasets associated with OMAP-1 can be found here (https://doi.org/10.1101/2022.06.03.494716,<br>https://doi.org/10.5281/zenodo.5244550). Several antibodies required custom conjugation by commercial suppliers or<br>antibody conjugation kits (e.g., AF532, Thermo A20182).

OMAP-1 专为固定冰冻人淋巴结的IBEX（Iterative Bleaching Extends multi-pleXity）成像实验设计，相关研究可参见https://doi.org/10.1038/s41596-021-00644-9 与 https://doi.org/10.1073/pnas.2018488117。该抗体组合包含39种抗体，以及用于图像配准与细胞核分割的核标志物Hoechst 33342。本OMAP可为[ASCT+B淋巴结表v1.1](https://doi.org/10.48539/HBM573.SHCQ.259)中收录的所有解剖结构与多数细胞类型提供空间分布背景。此外，该组合纳入了蛋白标志物BCL2、CD10、CD138与CD44，可用于分析淋巴结疾病状态，例如滤泡性淋巴瘤与肿瘤转移。本文详述的核心与优先靶向OMAP靶点，与采用其他技术及样本制备方法开发的淋巴组织多重成像抗体组合存在约50%~85%的重叠（参考文献：https://doi.org/10.7554/eLife.31657、https://doi.org/10.1002/eji.202048891）。本OMAP未包含用于分型周细胞、浆细胞样树突状细胞或不同辅助性T细胞亚群（Th1、Th2、Th17）的抗体。除可实现健康人淋巴结的空间图谱绘制外，本OMAP还被用于表征滤泡性淋巴瘤淋巴结的组织微环境。在该研究中，研究人员采用基于卷积神经网络（Convolutional Neural Network, CNN）、以Mask R-CNN为架构、ResNet-50作为骨干网络的方法完成了基于对象的细胞分割。输入通道包含三类：用于标记细胞核的Hoechst、作为基础膜标记的CD45，以及CD138、CD163、CD94、CD69、CD8、CD4等多种膜标志物的复合信号。更多与OMAP-1相关的细节及配套数据集可通过以下链接获取：https://doi.org/10.1101/2022.06.03.494716、https://doi.org/10.5281/zenodo.5244550。部分抗体需由商业供应商定制偶联，或使用抗体偶联试剂盒完成标记（例如AF532，货号Thermo A20182）。