High-dimensional imaging using combinatorial channel multiplexing and deep learning

doi:10.1038/s41587-025-02585-0

2025-03-25

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DOI：10.1038/s41587-025-02585-0

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理解组织结构与功能需要能够在单细胞分辨率下定量多种蛋白质表达并保留空间信息的工具。目前的成像技术为每种蛋白质使用单独的通道，限制了通量和可扩展性。在此，我们介绍了组合多重标记（CombPlex），一种组合染色平台与算法框架相结合的技术，用于指数级增加测量的蛋白质数量。每种蛋白质可以在多个通道中成像，每个通道包含多种蛋白质的聚合图像。这些组合压缩的图像随后通过深度学习解压缩为单个蛋白质图像。我们在将22种蛋白质的染色压缩至五个成像通道时实现了准确的重建。我们在荧光显微镜和质谱成像中均验证了该方法，并展示了其在多种组织和癌症类型中的成功应用。CombPlex能够提升任何成像模式测量蛋白质的数量，且无需专用仪器。

Keyword:

IMMUNOHISTOCHEMISTRY

CELLS

期刊

Nature Biotechnology

IF:

41.7

论文数:

1.2W

被引数:

10.1W

机构

Weizmann Inst Sci

学者数:

753

论文数: 280

被引数: 161

comprehens canc ctr tubingen

学者数:

论文数: 2

被引数: 1

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