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Title: Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here in this study, we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-μm-i.d. columns increase signal intensity by >3-fold relative to those using 75-μm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos MS significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ~3-fold increase in peptide identifications and 1.7-fold increase in identified protein groups for 2 ng tryptic digests of the bacterium S. oneidensis. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~95% for 0.5 ng samples and by ~42% for 2 ng samples. Using the best combination of the above variables, we were able to identify >3,000 proteins from 10 ng tryptic digests from both HeLa and THP-1 mammalian cell lines. We also identified >950 proteins from subnanogram archaeal/bacterial cocultures. Finally, the present ultrasensitive LC-MS platform achieves a level of proteome coveragemore » not previously realized for ultra-small sample loadings, and is expected to facilitate the analysis of subnanogram samples, including single mammalian cells.« less
Authors:
 [1] ;  [1] ;  [2] ;  [2] ;  [3] ;  [3] ;  [1] ;  [2] ;  [2] ;  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Laboratory
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Biological Sciences Division
  3. California Inst. of Technology (CalTech), Pasadena, CA (United States). Division of Geological and Planetary Sciences
Publication Date:
Report Number(s):
PNNL-SA-125645
Journal ID: ISSN 1387-3806; PII: S1387380617302130
Grant/Contract Number:
AC02-05CH11231; AC05-76RL01830; P41 GM103493; 1R21EB020976-01A1; R21 EB020976-01A1
Type:
Accepted Manuscript
Journal Name:
International Journal of Mass Spectrometry
Additional Journal Information:
Journal Volume: 427; Journal ID: ISSN 1387-3806
Publisher:
Elsevier
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Institutes of Health (NIH)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; ultrasensitive; nanoLC; Orbitrap Fusion Lumos; match between runs; subnanogram proteomics; small cell populations; NanoLC
OSTI Identifier:
1395289
Alternate Identifier(s):
OSTI ID: 1379954

Zhu, Ying, Zhao, Rui, Piehowski, Paul D., Moore, Ronald J., Lim, Sujung, Orphan, Victoria J., Paša-Tolić, Ljiljana, Qian, Wei-Jun, Smith, Richard D., and Kelly, Ryan T.. Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples. United States: N. p., Web. doi:10.1016/J.IJMS.2017.08.016.
Zhu, Ying, Zhao, Rui, Piehowski, Paul D., Moore, Ronald J., Lim, Sujung, Orphan, Victoria J., Paša-Tolić, Ljiljana, Qian, Wei-Jun, Smith, Richard D., & Kelly, Ryan T.. Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples. United States. doi:10.1016/J.IJMS.2017.08.016.
Zhu, Ying, Zhao, Rui, Piehowski, Paul D., Moore, Ronald J., Lim, Sujung, Orphan, Victoria J., Paša-Tolić, Ljiljana, Qian, Wei-Jun, Smith, Richard D., and Kelly, Ryan T.. 2017. "Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples". United States. doi:10.1016/J.IJMS.2017.08.016. https://www.osti.gov/servlets/purl/1395289.
@article{osti_1395289,
title = {Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples},
author = {Zhu, Ying and Zhao, Rui and Piehowski, Paul D. and Moore, Ronald J. and Lim, Sujung and Orphan, Victoria J. and Paša-Tolić, Ljiljana and Qian, Wei-Jun and Smith, Richard D. and Kelly, Ryan T.},
abstractNote = {One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here in this study, we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-μm-i.d. columns increase signal intensity by >3-fold relative to those using 75-μm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos MS significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ~3-fold increase in peptide identifications and 1.7-fold increase in identified protein groups for 2 ng tryptic digests of the bacterium S. oneidensis. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~95% for 0.5 ng samples and by ~42% for 2 ng samples. Using the best combination of the above variables, we were able to identify >3,000 proteins from 10 ng tryptic digests from both HeLa and THP-1 mammalian cell lines. We also identified >950 proteins from subnanogram archaeal/bacterial cocultures. Finally, the present ultrasensitive LC-MS platform achieves a level of proteome coverage not previously realized for ultra-small sample loadings, and is expected to facilitate the analysis of subnanogram samples, including single mammalian cells.},
doi = {10.1016/J.IJMS.2017.08.016},
journal = {International Journal of Mass Spectrometry},
number = ,
volume = 427,
place = {United States},
year = {2017},
month = {9}
}