All-at-once spatial proteome profiling of complex tissue context with single-cell-type resolution by proximity proteomics.

Yiheng Mao, Yuan Li, Zhendong Zheng, Yanfen Xu, Mi Ke, An He, Fuchao Liang, Keren Zhang, Xi Wang, Weina Gao, Ruijun Tian
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Abstract

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.

所有的空间蛋白质组分析复杂的组织背景与单细胞型分辨率接近蛋白质组学。
空间蛋白质组学能够深入绘制组织结构,主要通过激光显微解剖-质谱(LMD-MS)和基于抗体的成像来实现。然而,采样精度,吞吐量和蛋白质组覆盖率之间的权衡仍然限制了这些策略的适用性。在这里,我们提出了空间蛋白质组学(PSPro)的接近标记,通过结合精确的抗体靶向生物素化和高效的亲和纯化,以亚微米分辨率从单个组织切片捕获所有细胞型蛋白质组。通过微调标记参数,PSPro在流式细胞术和基于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,从10种细胞类型中富集数千种含有已知标记物的蛋白质。我们进一步将LMD纳入PSPro,以促进来自同一组织切片的细胞亚群的比较,揭示胰腺癌细胞和免疫细胞的空间蛋白质组异质性。总的来说,PSPro以用户友好的方式将传统的“抗体-表位”范式转化为空间生物学的“抗体-细胞型蛋白质组”。本文的透明同行评议过程记录包含在补充信息中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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