Surfactant-assisted one-pot sample preparation for label-free single-cell proteomics
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Published:2021-03-01
Issue:1
Volume:4
Page:
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ISSN:2399-3642
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Container-title:Communications Biology
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language:en
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Short-container-title:Commun Biol
Author:
Tsai Chia-FengORCID, Zhang Pengfei, Scholten David, Martin Kendall, Wang Yi-TingORCID, Zhao Rui, Chrisler William B., Patel Dhwani B., Dou Maowei, Jia Yuzhi, Reduzzi CarolinaORCID, Liu Xia, Moore Ronald J.ORCID, Burnum-Johnson Kristin E.ORCID, Lin Miao-Hsia, Hsu Chuan-Chih, Jacobs Jon M.ORCID, Kagan Jacob, Srivastava Sudhir, Rodland Karin D.ORCID, Steven Wiley H.ORCID, Qian Wei-JunORCID, Smith Richard D.ORCID, Zhu Ying, Cristofanilli Massimo, Liu TaoORCID, Liu HuipingORCID, Shi TujinORCID
Abstract
AbstractLarge numbers of cells are generally required for quantitative global proteome profiling due to surface adsorption losses associated with sample processing. Such bulk measurement obscures important cell-to-cell variability (cell heterogeneity) and makes proteomic profiling impossible for rare cell populations (e.g., circulating tumor cells (CTCs)). Here we report a surfactant-assisted one-pot sample preparation coupled with mass spectrometry (MS) method termed SOP-MS for label-free global single-cell proteomics. SOP-MS capitalizes on the combination of a MS-compatible nonionic surfactant, n-Dodecyl-β-D-maltoside, and hydrophobic surface-based low-bind tubes or multi-well plates for ‘all-in-one’ one-pot sample preparation. This ‘all-in-one’ method including elimination of all sample transfer steps maximally reduces surface adsorption losses for effective processing of single cells, thus improving detection sensitivity for single-cell proteomics. This method allows convenient label-free quantification of hundreds of proteins from single human cells and ~1200 proteins from small tissue sections (close to ~20 cells). When applied to a patient CTC-derived xenograft (PCDX) model at the single-cell resolution, SOP-MS can reveal distinct protein signatures between primary tumor cells and early metastatic lung cells, which are related to the selection pressure of anti-tumor immunity during breast cancer metastasis. The approach paves the way for routine, precise, quantitative single-cell proteomics.
Funder
U.S. Department of Health & Human Services | NIH | National Cancer Institute
Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)
Reference71 articles.
1. Wang, Z., Gerstein, M. & Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 10, 57–63 (2009). 2. Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90–94 (2011). 3. Patel, A. P. et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344, 1396–1401 (2014). 4. Bendall, S. C., Nolan, G. P., Roederer, M. & Chattopadhyay, P. K. A deep profiler’s guide to cytometry. Trends Immunol. 33, 323–332 (2012). 5. Shi, T. J. et al. Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics. Proteomics 12, 1074–1092 (2012).
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