High-throughput proteomic sample preparation using pressure cycling technology

Wei Liu, Chen Chen, Xue Cai, Zhangzhi Xue, Chunlong Wu, Rui Sun, Liujia Qian, Liang Yue, Weigang Ge, Xiao Yi, Huanhuan Gao, Jing Yu, Luang Xu, Yi Zhu, Tiannan Guo

Published: 2022-08-04 DOI: 10.1038/s41596-022-00727-1

mass spectrometry

pressure cycling technology

proteomic sample preparation

clinical proteomics

tissue lysis

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Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2.

Supplementary Data 1

Experimental data from Fig. 2. Proteomic data of mouse kidney samples in the form of FF, FFPE punch and FFPE slice.

Supplementary Data 2

Experimental data from Fig. 3. Proteomic data of 32 independent FFPE tissue samples (benign and tumor pairs) from eight types of cancer tissues.

Supplementary Data 3

PulseDIA-PASEF MS isolation window: part 1 setting.

Supplementary Data 4

PulseDIA-PASEF MS isolation window: part 2 setting.

Supplementary Video

The procedures for handling the PCT-MicroTubes, MicroCaps, MicroPestles with the PCT tool.

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Supplementary information

Aebersold, R. & Mann, M. Mass-spectrometric exploration of proteome structure and function. Nature 537, 347–355 (2016).
Zhu, Y., Aebersold, R., Mann, M. & Guo, T. SnapShot: clinical proteomics. Cell 184, 4840–4840.e1 (2021).
Xiao, Q. et al. High-throughput proteomics and AI for cancer biomarker discovery. Adv. Drug Deliv. Rev. 176, 113844 (2021).
Guo, T. et al. Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps. Nat. Med. 21, 407–413 (2015).
Zhu, Y. et al. Identification of protein abundance changes in hepatocellular carcinoma tissues using PCT-SWATH. Proteomics Clin. Appl. 13, 1700179 (2019).
Eckert, M. A. et al. Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts. Nature 569, 723–728 (2019).
Hood, B. L. et al. Proteomic analysis of formalin-fixed prostate cancer tissue. Mol. Cell Proteomics 4, 1741–1753 (2005).
Nie, X. et al. Multi-organ proteomic landscape of COVID-19 autopsies. Cell 184, 775–791.e14 (2021).
Wisniewski, J. R., Zougman, A., Nagaraj, N. & Mann, M. Universal sample preparation method for proteome analysis. Nat. Methods 6, 359–362 (2009).
Hwang, S. I. et al. Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues. Oncogene 26, 65–76 (2007).
Hughes, C. S. et al. Ultrasensitive proteome analysis using paramagnetic bead technology. Mol. Syst. Biol. 10, 757 (2014).
Hughes, C. S. et al. Single-pot, solid-phase-enhanced sample preparation for proteomics experiments. Nat. Protoc. 14, 68–85 (2019).
Fowler, C. B. et al. Elevated hydrostatic pressure promotes protein recovery from formalin-fixed, paraffin-embedded tissue surrogates. Lab Invest. 88, 185–195 (2008).
Powell, B. S., Lazarev, A. V., Carlson, G., Ivanov, A. R. & Rozak, D. A. Pressure cycling technology in systems biology. Methods Mol. Biol. 881, 27–62 (2012).
Shao, S. et al. Minimal sample requirement for highly multiplexed protein quantification in cell lines and tissues by PCT-SWATH mass spectrometry. Proteomics 15, 3711–3721 (2015).
Shao, S. et al. Reproducible tissue homogenization and protein extraction for quantitative proteomics using MicroPestle-assisted pressure-cycling technology. J. Proteome Res. 15, 1821–1829 (2016).
Thompson, A. et al. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem. 75, 1895–1904 (2003).
Ross, P. L. et al. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell Proteomics 3, 1154–1169 (2004).
Anderson, L. & Hunter, C. L. Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins. Mol. Cell Proteomics 5, 573–588 (2006).
Peterson, A. C., Russell, J. D., Bailey, D. J., Westphall, M. S. & Coon, J. J. Parallel reaction monitoring for high resolution and high mass accuracy quantitative, targeted proteomics. Mol. Cell Proteomics 11, 1475–1488 (2012).
Gallien, S. et al. Targeted proteomic quantification on quadrupole-orbitrap mass spectrometer. Mol. Cell Proteomics 11, 1709–1723 (2012).
Venable, J. D., Dong, M. Q., Wohlschlegel, J., Dillin, A. & Yates, J. R. Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat. Methods 1, 39–45 (2004).
Powell, K. Technology to watch in 2018. Nature 553, 531–534 (2018).
Zhang, F., Ge, W., Ruan, G., Cai, X. & Guo, T. Data-independent acquisition mass spectrometry-based proteomics and software tools: a glimpse in 2020. Proteomics 20, 1900276 (2021).
Gao, H. et al. Accelerated lysis and proteolytic digestion of biopsy-level fresh-frozen and FFPE tissue samples using pressure cycling technology. J. Proteome Res. 19, 1982–1990 (2020).
Zhu, Y. & Guo, T. High-throughput proteomic analysis of fresh-frozen biopsy tissue samples using pressure cycling technology coupled with SWATH Mass spectrometry. Methods Mol. Biol. 1788, 279–287 (2018).
Zhu, Y. et al. High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification. Mol. Oncol. 13, 2305–2328 (2019).
Zhu, T. et al. DPHL: a DIA pan-human protein mass spectrometry library for robust biomarker discovery. Genomics Proteomics Bioinformatics 18, 104–119 (2020).
Ge, W. et al. Computational optimization of spectral library size improves DIA-MS proteome coverage and applications to 15 tumors. J. Proteome Res. 20, 5392–5401 (2021).
Cheng, Y., Chen, Y. & Yu, C. Fast and efficient non-reduced Lys-C digest using pressure cycling technology for antibody disulfide mapping by LC–MS. J. Pharm. Biomed. Anal. 129, 203–209 (2016).
Nie, S., Greer, T., Huang, X., Zheng, X. & Li, N. Development of a simple non-reduced peptide mapping method that prevents disulfide scrambling of mAbs without affecting tryptic enzyme activity. J. Pharm. Biomed. Anal. 209, 114541 (2022).
Huang, Y., Burchmore, R., Jonsson, N. N., Johnson, P. C. D. & Eckersall, P. D. Technical report: In-gel sample preparation prior to proteomic analysis of bovine faeces increases protein identifications by removal of high molecular weight glycoproteins. J. Proteomics 261, 104573 (2022).
Wu, C. et al. Coupling suspension trapping-based sample preparation and data-independent acquisition mass spectrometry for sensitive exosomal proteomic analysis. Anal. Bioanal. Chem. 414, 2585–2595 (2022).
Xuan, Y. et al. Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies. Nat. Commun. 11, 5248 (2020).
Hunt, A. L. et al. Extensive three-dimensional intratumor proteomic heterogeneity revealed by multiregion sampling in high-grade serous ovarian tumor specimens. iScience 24, 102757 (2021).
Lee, S. et al. Molecular analysis of clinically defined subsets of high-grade serous ovarian cancer. Cell Rep. 31, 107502 (2020).
Li, D. et al. pFind: a novel database-searching software system for automated peptide and protein identification via tandem mass spectrometry. Bioinformatics 21, 3049–3050 (2005).
Demichev, V., Messner, C. B., Vernardis, S. I., Lilley, K. S. & Ralser, M. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat. Methods 17, 41–44 (2020).
Cai, X. et al. PulseDIA: data-independent acquisition mass spectrometry using multi-injection pulsed gas-phase fractionation. J. Proteome Res. 20, 279–288 (2021).
Ma, J. et al. iProX: an integrated proteome resource. Nucleic Acids Res. 47, D1211–D1217 (2019).

High-throughput proteomic sample preparation using pressure cycling technology

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