Plate IV.214 · Publications
Spatial proteomics in three-dimensional intact specimens
Article in Cell, December 2022.
Abstract
Spatial molecular profiling of complex tissues is essential to investigate cellular function in physiological and pathological states. However, methods for molecular analysis of large biological specimens imaged in 3D are lacking. Here, we present DISCO-MS, a technology that combines whole-organ/whole-organism clearing and imaging, deep-learning-based image analysis, robotic tissue extraction, and ultra-high-sensitivity mass spectrometry. DISCO-MS yielded proteome data indistinguishable from uncleared samples in both rodent and human tissues. We used DISCO-MS to investigate microglia activation along axonal tracts after brain injury and characterized early- and late-stage individual amyloid-beta plaques in a mouse model of Alzheimer's disease. DISCO-bot robotic sample extraction enabled us to study the regional heterogeneity of immune cells in intact mouse bodies and aortic plaques in a complete human heart. DISCO-MS enables unbiased proteome analysis of preclinical and clinical tissues after unbiased imaging of entire specimens in 3D, identifying diagnostic and therapeutic opportunities for complex diseases. VIDEO ABSTRACT.
Cite
@article{bhatia2022spatial,
title = {{Spatial proteomics in three-dimensional intact specimens}},
author = {Bhatia, Harsharan Singh and Brunner, Andreas-David and Öztürk, Furkan and Kapoor, Saketh and Rong, Zhouyi and Mai, Hongcheng and Thielert, Marvin and Ali, Mayar and Al-Maskari, Rami and Paetzold, Johannes Christian and Kofler, Florian and Todorov, Mihail Ivilinov and Molbay, Muge and Kolabas, Zeynep Ilgin and Negwer, Moritz and Hoeher, Luciano and Steinke, Hanno and Dima, Alina and Gupta, Basavdatta and Kaltenecker, Doris and Caliskan, Özüm Sehnaz and Brandt, Daniel and Krahmer, Natalie and Müller, Stephan and Lichtenthaler, Stefan Frieder and Hellal, Farida and Bechmann, Ingo and Menze, Bjoern and Theis, Fabian and Mann, Matthias and Ertürk, Ali},
journal = {Cell},
publisher = {Elsevier BV},
year = {2022},
month = dec,
doi = {10.1016/j.cell.2022.11.021},
url = {https://doi.org/10.1016/j.cell.2022.11.021},
pmid = {36563667}
}