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An Automated and Fast Sample Preparation Workflow for Laser Microdissection Guided Ultrasensitive Proteomics.
- Source :
-
Molecular & cellular proteomics : MCP [Mol Cell Proteomics] 2024 May; Vol. 23 (5), pp. 100750. Date of Electronic Publication: 2024 Mar 20. - Publication Year :
- 2024
-
Abstract
- Spatial tissue proteomics integrating whole-slide imaging, laser microdissection, and ultrasensitive mass spectrometry is a powerful approach to link cellular phenotypes to functional proteome states in (patho)physiology. To be applicable to large patient cohorts and low sample input amounts, including single-cell applications, loss-minimized and streamlined end-to-end workflows are key. We here introduce an automated sample preparation protocol for laser microdissected samples utilizing the cellenONE robotic system, which has the capacity to process 192 samples in 3 h. Following laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, our optimized protocol facilitates lysis, formalin de-crosslinking, and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows 'on-the-fly' sample clean-up, particularly pertinent for laser microdissection workflows. We validate our method in human tonsil archival tissue, where we profile proteomes of spatially-defined B-cell, T-cell, and epithelial microregions of 4000 μm <superscript>2</superscript> to a depth of ∼2000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.<br />Competing Interests: Conflict of interest D. H. and A. S. are employees at Cellenion. All other authors declare that they have no conflicts of interest with the contents of this article.<br /> (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1535-9484
- Volume :
- 23
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Molecular & cellular proteomics : MCP
- Publication Type :
- Academic Journal
- Accession number :
- 38513891
- Full Text :
- https://doi.org/10.1016/j.mcpro.2024.100750