Online-2D NanoLC-MS for Crude Serum Proteome Profiling : Assessing Sample Preparation Impact on Proteome Composition
(2021) In Analytical Chemistry 93(28). p.9663-9668- Abstract
Although current LC-MS technology permits scientists to efficiently screen clinical samples in translational research, e.g., steroids, biogenic amines, and even plasma or serum proteomes, in a daily routine, maintaining the balance between throughput and analytical depth is still a limiting factor. A typical approach to enhance the proteome depth is employing offline two-dimensional (2D) fractionation techniques before reversed-phase nanoLC-MS/MS analysis (1D-nanoLC-MS). These additional sample preparation steps usually require extensive sample manipulation, which could result in sample alteration and sample loss. Here, we present and compare 1D-nanoLC-MS with an automated online-2D high-pH RP × low pH RP separation method for deep... (More)
Although current LC-MS technology permits scientists to efficiently screen clinical samples in translational research, e.g., steroids, biogenic amines, and even plasma or serum proteomes, in a daily routine, maintaining the balance between throughput and analytical depth is still a limiting factor. A typical approach to enhance the proteome depth is employing offline two-dimensional (2D) fractionation techniques before reversed-phase nanoLC-MS/MS analysis (1D-nanoLC-MS). These additional sample preparation steps usually require extensive sample manipulation, which could result in sample alteration and sample loss. Here, we present and compare 1D-nanoLC-MS with an automated online-2D high-pH RP × low pH RP separation method for deep proteome profiling using a nanoLC system coupled to a high-resolution accurate-mass mass spectrometer. The proof-of-principle study permitted the identification of ca. 500 proteins with ∼10,000 peptides in 15 enzymatically digested crude serum samples collected from healthy donors in 3 laboratories across Europe. The developed method identified 60% more peptides in comparison with conventional 1D nanoLC-MS/MS analysis with ca. 4 times lower throughput while retaining the quantitative information. Serum sample preparation related changes were revealed by applying unsupervised classification techniques and, therefore, must be taken into account while planning multicentric biomarker discovery and validation studies. Overall, this novel method reduces sample complexity and boosts the number of peptide and protein identifications without the need for extra sample handling procedures for samples equivalent to less than 1 μL of blood, which expands the space for potential biomarker discovery by looking deeper into the composition of biofluids.
(Less)
- author
- Zheng, Runsheng ; Govorukhina, Natalia ; Arrey, Tabiwang N. ; Pynn, Christopher ; Van Der Zee, Ate ; Marko-Varga, György LU ; Bischoff, Rainer and Boychenko, Alexander
- organization
- publishing date
- 2021-07
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Analytical Chemistry
- volume
- 93
- issue
- 28
- pages
- 6 pages
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- scopus:85111086993
- pmid:34236853
- ISSN
- 0003-2700
- DOI
- 10.1021/acs.analchem.1c01291
- language
- English
- LU publication?
- yes
- id
- 2638b774-685c-44b7-aa54-5b4f96be8aca
- date added to LUP
- 2021-12-27 14:26:16
- date last changed
- 2024-06-15 23:26:40
@article{2638b774-685c-44b7-aa54-5b4f96be8aca,
abstract = {{<p>Although current LC-MS technology permits scientists to efficiently screen clinical samples in translational research, e.g., steroids, biogenic amines, and even plasma or serum proteomes, in a daily routine, maintaining the balance between throughput and analytical depth is still a limiting factor. A typical approach to enhance the proteome depth is employing offline two-dimensional (2D) fractionation techniques before reversed-phase nanoLC-MS/MS analysis (1D-nanoLC-MS). These additional sample preparation steps usually require extensive sample manipulation, which could result in sample alteration and sample loss. Here, we present and compare 1D-nanoLC-MS with an automated online-2D high-pH RP × low pH RP separation method for deep proteome profiling using a nanoLC system coupled to a high-resolution accurate-mass mass spectrometer. The proof-of-principle study permitted the identification of ca. 500 proteins with ∼10,000 peptides in 15 enzymatically digested crude serum samples collected from healthy donors in 3 laboratories across Europe. The developed method identified 60% more peptides in comparison with conventional 1D nanoLC-MS/MS analysis with ca. 4 times lower throughput while retaining the quantitative information. Serum sample preparation related changes were revealed by applying unsupervised classification techniques and, therefore, must be taken into account while planning multicentric biomarker discovery and validation studies. Overall, this novel method reduces sample complexity and boosts the number of peptide and protein identifications without the need for extra sample handling procedures for samples equivalent to less than 1 μL of blood, which expands the space for potential biomarker discovery by looking deeper into the composition of biofluids. </p>}},
author = {{Zheng, Runsheng and Govorukhina, Natalia and Arrey, Tabiwang N. and Pynn, Christopher and Van Der Zee, Ate and Marko-Varga, György and Bischoff, Rainer and Boychenko, Alexander}},
issn = {{0003-2700}},
language = {{eng}},
number = {{28}},
pages = {{9663--9668}},
publisher = {{The American Chemical Society (ACS)}},
series = {{Analytical Chemistry}},
title = {{Online-2D NanoLC-MS for Crude Serum Proteome Profiling : Assessing Sample Preparation Impact on Proteome Composition}},
url = {{http://dx.doi.org/10.1021/acs.analchem.1c01291}},
doi = {{10.1021/acs.analchem.1c01291}},
volume = {{93}},
year = {{2021}},
}