研究人员提出了DISCO-MS，一种结合了全器官/全生物体清扫和成像、基于深度学习的图像分析、机器人组织提取和超高灵敏度质谱分析的技术。DISCO-MS产生的蛋白质组数据与啮齿动物和人类组织中的未清理样本没有区别。研究人员用DISCO-MS研究了脑损伤后沿轴突束的小胶质细胞激活情况，并对阿尔茨海默病小鼠模型中早期和晚期的单个淀粉样β斑块进行了描述。DISCO-bot机器人样品提取使研究人员能够揭示完整小鼠体内免疫细胞的区域异质性和完整人类心脏的主动脉斑块。DISCO-MS在对整个标本进行三维无偏差成像后，能够对临床前和临床组织进行无偏差的蛋白质组分析，从而确定复杂疾病的诊断和治疗机会。
据悉，复杂组织的空间分子分析对于研究生理和病理状态下的细胞功能至关重要。然而，目前还缺乏对大型生物标本进行三维成像的分子分析方法。
附：英文原文
Title: Spatial proteomics in three-dimensional intact specimens
Author: Harsharan Singh Bhatia, Andreas-David Brunner, Furkan ztürk, Saketh Kapoor, Zhouyi Rong, Hongcheng Mai, Marvin Thielert, Mayar Ali, Rami Al-Maskari, Johannes Christian Paetzold, Florian Kofler, Mihail Ivilinov Todorov, Muge Molbay, Zeynep Ilgin Kolabas, Moritz Negwer, Luciano Hoeher, Hanno Steinke, Alina Dima, Basavdatta Gupta, Doris Kaltenecker, züm Sehnaz Caliskan, Daniel Brandt, Natalie Krahmer, Stephan Müller, Stefan Frieder Lichtenthaler, Farida Hellal, Ingo Bechmann, Bjoern Menze, Fabian Theis, Matthias Mann, Ali Ertürk
Issue&Volume: 2022/12/22
Abstract: Spatial molecular profiling of complex tissues is essential to investigate cellularfunction in physiological and pathological states. However, methods for molecularanalysis of large biological specimens imaged in 3D are lacking. Here, we presentDISCO-MS, a technology that combines whole-organ/whole-organism clearing and imaging,deep-learning-based image analysis, robotic tissue extraction, and ultra-high-sensitivitymass spectrometry. DISCO-MS yielded proteome data indistinguishable from unclearedsamples in both rodent and human tissues. We used DISCO-MS to investigate microgliaactivation along axonal tracts after brain injury and characterized early- and late-stageindividual amyloid-beta plaques in a mouse model of Alzheimer’s disease. DISCO-botrobotic sample extraction enabled us to study the regional heterogeneity of immunecells in intact mouse bodies and aortic plaques in a complete human heart. DISCO-MSenables unbiased proteome analysis of preclinical and clinical tissues after unbiasedimaging of entire specimens in 3D, identifying diagnostic and therapeutic opportunitiesfor complex diseases.
DOI: 10.1016/j.cell.2022.11.021
Source: https://www.cell.com/cell/fulltext/S0092-8674(22)01465-9