Mao Yiheng, Li Yuan, Zheng Zhendong, Xu Yanfen, Ke Mi, He An, Liang Fuchao, Zhang Keren, Wang Xi, Gao Weina, Tian Ruijun
Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Guangming Advanced Research Institute, Southern University of Science and Technology, Shenzhen 518055, China.
Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Guangming Advanced Research Institute, Southern University of Science and Technology, Shenzhen 518055, China.
Cell Syst. 2025 Jun 18;16(6):101291. doi: 10.1016/j.cels.2025.101291. Epub 2025 May 8.
Spatial proteomics enables in-depth mapping of tissue architectures, mostly achieved by laser microdissection-mass spectrometry (LMD-MS) and antibody-based imaging. However, trade-offs among sampling precision, throughput, and proteome coverage still limit the applicability of these strategies. Here, we propose proximity labeling for spatial proteomics (PSPro) by combining precise antibody-targeted biotinylation and efficient affinity purification for all-at-once cell-type proteome capture with sub-micrometer resolution from single tissue slice. With fine-tuned labeling parameters, PSPro shows reliable performance in benchmarking against flow cytometry- and LMD-based proteomic workflows. We apply PSPro to tumor and spleen slices, enriching thousands of proteins containing known markers from ten cell types. We further incorporate LMD into PSPro to facilitate comparison of cell subpopulations from the same tissue slice, revealing spatial proteome heterogeneity of cancer cells and immune cells in pancreatic tumor. Collectively, PSPro converts the traditional "antibody-epitope" paradigm to an "antibody-cell-type proteome" for spatial biology in a user-friendly manner. A record of this paper's transparent peer review process is included in the supplemental information.
空间蛋白质组学能够对组织结构进行深入测绘,这主要通过激光显微切割-质谱(LMD-MS)和基于抗体的成像来实现。然而,采样精度、通量和蛋白质组覆盖范围之间的权衡仍然限制了这些策略的适用性。在此,我们通过将精确的抗体靶向生物素化和高效的亲和纯化相结合,提出了用于空间蛋白质组学的邻近标记法(PSPro),以便从单个组织切片中以亚微米分辨率一次性捕获细胞类型蛋白质组。通过微调标记参数,PSPro在与基于流式细胞术和LMD的蛋白质组学工作流程的基准测试中表现出可靠的性能。我们将PSPro应用于肿瘤和脾脏切片,富集了来自十种细胞类型的数千种含有已知标志物的蛋白质。我们进一步将LMD纳入PSPro,以促进对来自同一组织切片的细胞亚群的比较,揭示胰腺肿瘤中癌细胞和免疫细胞的空间蛋白质组异质性。总体而言,PSPro以用户友好的方式将传统的“抗体-表位”范式转变为用于空间生物学的“抗体-细胞类型蛋白质组”范式。本文透明的同行评审过程记录包含在补充信息中。