Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets
| Autor: | Yufeng Shen, Anil K. Shukla, Yiran Liang, Kaitlynn C. Schwarz, Wei-Jun Qian, Jordan N. Smith, Maowei Dou, Richard D. Smith, William B. Chrisler, Rosalie K. Chu, Paul D. Piehowski, Fangjun Wang, Ronald J. Moore, Ying Zhu, Ryan T. Kelly |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Proteomics Proteome Microfluidics Laser Capture Microdissection Mass spectrometry 01 natural sciences Biochemistry Analytical Chemistry Rats Sprague-Dawley 03 medical and health sciences Automation Protein purification Animals Humans Sample preparation Dimethyl Sulfoxide Molecular Biology Laser capture microdissection Principal Component Analysis Chemistry 010401 analytical chemistry Technological Innovation and Resources Brain Xenograft Model Antitumor Assays 0104 chemical sciences Label-free quantification 030104 developmental biology Biophysics Nanoparticles Female Peptides |
| Zdroj: | Molecularcellular proteomics : MCP. 17(9) |
| ISSN: | 1535-9484 |
| Popis: | Current mass spectrometry (MS)-based proteomics approaches are ineffective for mapping protein expression in tissue sections with high spatial resolution because of the limited overall sensitivity of conventional workflows. Here we report an integrated and automated method to advance spatially resolved proteomics by seamlessly coupling laser capture microdissection (LCM) with a recently developed nanoliter-scale sample preparation system termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples). The workflow is enabled by prepopulating nanowells with DMSO, which serves as a sacrificial capture liquid for microdissected tissues. The DMSO droplets efficiently collect laser-pressure catapulted LCM tissues as small as 20 μm in diameter with success rates >87%. We also demonstrate that tissue treatment with DMSO can significantly improve proteome coverage, likely due to its ability to dissolve lipids from tissue and enhance protein extraction efficiency. The LCM-nanoPOTS platform was able to identify 180, 695, and 1827 protein groups on average from 12-μm-thick rat brain cortex tissue sections having diameters of 50, 100, and 200 μm, respectively. We also analyzed 100-μm-diameter sections corresponding to 10–18 cells from three different regions of rat brain and comparatively quantified ∼1000 proteins, demonstrating the potential utility for high-resolution spatially resolved mapping of protein expression in tissues. |
| Databáze: | OpenAIRE |
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