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基于微流控液滴的样品制备、多重同重标记与纳流肽段分级分离联用,用于组织微环境的深度蛋白质组分析 profiling 应该为 profiling

Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment.

机构信息

Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States.

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States.

出版信息

Anal Chem. 2024 Aug 13;96(32):12973-12982. doi: 10.1021/acs.analchem.4c00523. Epub 2024 Aug 1.

Abstract

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.

摘要

人们越来越感兴趣的是开发深入的蛋白质组学方法,以便以细胞类型特异性的方式绘制组织异质性图谱,从而更好地理解和预测复杂生物系统(如人体器官)的功能。现有的空间分辨蛋白质组学技术由于灵敏度有限和样品回收率差,无法提供深度蛋白质组覆盖。在这里,我们无缝地将激光捕获显微切割与小体积样品处理技术相结合,该技术包括一种称为 microPOTS(微量样品一锅式微滴处理)的微流控装置、多重等压标记和纳流肽分级方法。该集成工作流程使我们能够最大限度地提高包含纳克级蛋白质的激光分离组织样品的蛋白质组覆盖率。我们证明,深度空间蛋白质组学平台可以从小尺寸的人胰腺组织像素(约 60,000 μm)中定量超过 5000 种独特蛋白质,并区分胰腺中独特的蛋白质丰度模式。此外,microPOTS 芯片的使用消除了对先进微制造能力和专用纳升级液体处理设备的需求,使蛋白质组学实验室更容易获得该技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb29/11325296/a08580017340/ac4c00523_0001.jpg

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