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Title: Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

Abstract

Nanoscale or single cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (Nanodroplet Processing in One pot for Trace Samples) platform as a major advance in overall sensitivity. NanoPOTS dramatically enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive LC-MS, nanoPOTS allows identification of ~1500 to ~3,000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins were consistently identified from as few as 10 cells. Furthermore, we demonstrate robust quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.

Authors:
 [1]; ORCiD logo [2];  [1]; ORCiD logo [3];  [2];  [2];  [2]; ORCiD logo [2];  [3];  [3]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Biological Sciences Division
  3. Univ. of Florida, Gainesville, FL (United States). Dept. of Pathology, Immunology and Laboratory Medicine
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE; National Institutes of Health (NIH)
OSTI Identifier:
1432521
Alternate Identifier(s):
OSTI ID: 1513201
Report Number(s):
PNNL-SA-125235
Journal ID: ISSN 2041-1723; PII: 3367
Grant/Contract Number:  
AC05-76RL01830; R21 EB020976; R33 CA225248; P41 GM103493; UC4 DK104167; DP3 DK110844; 1S10OD016350-01
Resource Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Zhu, Ying, Piehowski, Paul D., Zhao, Rui, Chen, Jing, Shen, Yufeng, Moore, Ronald J., Shukla, Anil K., Petyuk, Vladislav A., Campbell-Thompson, Martha, Mathews, Clayton E., Smith, Richard D., Qian, Wei-Jun, and Kelly, Ryan T. Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells. United States: N. p., 2018. Web. doi:10.1038/s41467-018-03367-w.
Zhu, Ying, Piehowski, Paul D., Zhao, Rui, Chen, Jing, Shen, Yufeng, Moore, Ronald J., Shukla, Anil K., Petyuk, Vladislav A., Campbell-Thompson, Martha, Mathews, Clayton E., Smith, Richard D., Qian, Wei-Jun, & Kelly, Ryan T. Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells. United States. https://doi.org/10.1038/s41467-018-03367-w
Zhu, Ying, Piehowski, Paul D., Zhao, Rui, Chen, Jing, Shen, Yufeng, Moore, Ronald J., Shukla, Anil K., Petyuk, Vladislav A., Campbell-Thompson, Martha, Mathews, Clayton E., Smith, Richard D., Qian, Wei-Jun, and Kelly, Ryan T. Wed . "Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells". United States. https://doi.org/10.1038/s41467-018-03367-w. https://www.osti.gov/servlets/purl/1432521.
@article{osti_1432521,
title = {Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells},
author = {Zhu, Ying and Piehowski, Paul D. and Zhao, Rui and Chen, Jing and Shen, Yufeng and Moore, Ronald J. and Shukla, Anil K. and Petyuk, Vladislav A. and Campbell-Thompson, Martha and Mathews, Clayton E. and Smith, Richard D. and Qian, Wei-Jun and Kelly, Ryan T.},
abstractNote = {Nanoscale or single cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (Nanodroplet Processing in One pot for Trace Samples) platform as a major advance in overall sensitivity. NanoPOTS dramatically enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive LC-MS, nanoPOTS allows identification of ~1500 to ~3,000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins were consistently identified from as few as 10 cells. Furthermore, we demonstrate robust quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.},
doi = {10.1038/s41467-018-03367-w},
journal = {Nature Communications},
number = 1,
volume = 9,
place = {United States},
year = {2018},
month = {2}
}

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journal, December 2018

  • Longuespée, Rémi; Casadonte, Rita; Schwamborn, Kristina
  • PROTEOMICS – Clinical Applications, Vol. 13, Issue 1
  • DOI: 10.1002/prca.201800167

Nanowell-mediated multidimensional separations combining nanoLC with SLIM IM-MS for rapid, high-peak-capacity proteomic analyses
journal, November 2018

  • Dou, Maowei; Chouinard, Christopher D.; Zhu, Ying
  • Analytical and Bioanalytical Chemistry, Vol. 411, Issue 21
  • DOI: 10.1007/s00216-018-1452-5

Benchtop-compatible sample processing workflow for proteome profiling of < 100 mammalian cells
journal, November 2018

  • Xu, Kerui; Liang, Yiran; Piehowski, Paul D.
  • Analytical and Bioanalytical Chemistry, Vol. 411, Issue 19
  • DOI: 10.1007/s00216-018-1493-9

Automated mass spectrometry imaging of over 2000 proteins from tissue sections at 100-μm spatial resolution
journal, January 2020


Spatial proteomics: a powerful discovery tool for cell biology
journal, January 2019


Facile carrier-assisted targeted mass spectrometric approach for proteomic analysis of low numbers of mammalian cells
journal, August 2018

  • Shi, Tujin; Gaffrey, Matthew J.; Fillmore, Thomas L.
  • Communications Biology, Vol. 1, Issue 1
  • DOI: 10.1038/s42003-018-0107-6

New mass spectrometry technologies contributing towards comprehensive and high throughput omics analyses of single cells
journal, January 2019

  • Couvillion, Sneha P.; Zhu, Ying; Nagy, Gabe
  • The Analyst, Vol. 144, Issue 3
  • DOI: 10.1039/c8an01574k

Nanowell-mediated two-dimensional liquid chromatography enables deep proteome profiling of <1000 mammalian cells
journal, January 2018

  • Dou, Maowei; Zhu, Ying; Liyu, Andrey
  • Chemical Science, Vol. 9, Issue 34
  • DOI: 10.1039/c8sc02680g

Single cell protein analysis for systems biology
journal, August 2018

  • Levy, Ezra; Slavov, Nikolai
  • Essays in Biochemistry, Vol. 62, Issue 4
  • DOI: 10.1042/ebc20180014

Exploiting Interdata Relationships in Next-generation Proteomics Analysis
journal, May 2019

  • Vitrinel, Burcu; Koh, Hiromi W. L.; Mujgan Kar, Funda
  • Molecular & Cellular Proteomics, Vol. 18, Issue 8 suppl 1
  • DOI: 10.1074/mcp.mr118.001246

Proteomics, Glycomics, and Glycoproteomics of Matrisome Molecules
journal, August 2019

  • Raghunathan, Rekha; Sethi, Manveen K.; Klein, Joshua A.
  • Molecular & Cellular Proteomics, Vol. 18, Issue 11
  • DOI: 10.1074/mcp.r119.001543

Streamlined Protocol for Deep Proteomic Profiling of FAC-sorted Cells and Its Application to Freshly Isolated Murine Immune Cells
journal, February 2019

  • Myers, Samuel A.; Rhoads, Andrew; Cocco, Alexandra R.
  • Molecular & Cellular Proteomics, Vol. 18, Issue 5
  • DOI: 10.1074/mcp.ra118.001259

Sensitive Quantitative Proteomics of Human Hematopoietic Stem and Progenitor Cells by Data-independent Acquisition Mass Spectrometry
journal, April 2019

  • Amon, Sabine; Meier-Abt, Fabienne; Gillet, Ludovic C.
  • Molecular & Cellular Proteomics, Vol. 18, Issue 7
  • DOI: 10.1074/mcp.tir119.001431

Nanoproteomics comes of age
journal, October 2018


The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes
journal, June 2019


Islet–immune interactions in type 1 diabetes: the nexus of beta cell destruction
journal, August 2019

  • Peters, L.; Posgai, A.; Brusko, T. M.
  • Clinical & Experimental Immunology, Vol. 198, Issue 3
  • DOI: 10.1111/cei.13349

Beyond mass spectrometry, the next step in proteomics
journal, January 2020


A multiomics focusing towards the molecular networks of lung development
journal, November 2019

  • Clair, Geremy
  • American Journal of Physiology-Lung Cellular and Molecular Physiology, Vol. 317, Issue 5
  • DOI: 10.1152/ajplung.00364.2019

Single-cell proteomics reveals changes in expression during hair-cell development
journal, November 2019

  • Zhu, Ying; Scheibinger, Mirko; Ellwanger, Daniel Christian
  • eLife, Vol. 8
  • DOI: 10.7554/elife.50777

Focus on the spectra that matter by clustering of quantification data in shotgun proteomics
journal, June 2020