Veličković Marija, Fillmore Thomas L, Attah Kwame, Posso Camilo, Pino James C, Zhao Rui, Williams Sarah M, Veličković Dušan, Jacobs Jon M, Burnum-Johnson Kristin E, Zhu Ying, Piehowski Paul D
bioRxiv. 2023 Mar 13:2023.03.13.531822. doi: 10.1101/2023.03.13.531822.
There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity at a cell-type-specific level to better understand and predict the function of complex biological systems, such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverages 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), the multiplexed isobaric labelling, and a nanoflow peptide fractionation approach. The integrated workflow allowed to maximize proteome coverage of laser-isolated tissue samples containing nanogram proteins. We demonstrated the deep spatial proteomics can quantify more than 5,000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 µm2) and reveal unique islet microenvironments.
人们对开发深入的蛋白质组学方法越来越感兴趣,这些方法用于在细胞类型特异性水平上绘制组织异质性,以便更好地理解和预测复杂生物系统(如人体器官)的功能。由于灵敏度有限和样品回收率低,现有的空间分辨蛋白质组学技术无法提供深度蛋白质组覆盖。在此,我们将激光捕获显微切割与低体积样品处理技术无缝结合,该技术包括一种名为microPOTS(用于微量样品的一锅式微滴处理)的微流控装置、多重等压标记和纳流肽分级分离方法。这种集成工作流程能够最大化含有纳克级蛋白质的激光分离组织样品的蛋白质组覆盖。我们证明了深度空间蛋白质组学可以从一个小尺寸的人胰腺组织像素(约60,000 µm²)中定量超过5000种独特蛋白质,并揭示独特的胰岛微环境。