Quantitative Label-Free Single-Cell Proteomics on the Orbitrap Astral MS

Single-cell proteomics by mass spectrometry (scp-MS) holds the potential to provide unprecedented insights into molecular features directly linked to the cellular phenotype while deconvoluting complex organisms into their basic building blocks. Tailored sample preparation that maximizes the extracted amount of material that is introduced into the mass spectrometer has rapidly propelled the field forward. However, the measured signal is still at the lower edge of detection, approaching the sensitivity boundary of current instrumentation. Here, we investigate the capacity of the enhanced sensitivity of the Orbitrap Astral mass spectrometer to facilitate deeper proteome profiles from low-input to single-cell samples. We carry out a comprehensive data acquisition method survey to pinpoint which parameters provide the most sensitivity. Furthermore, we explore the quantitative accuracy of the obtained measurements to ensure that the obtained abundances are in line with expected ground truth values. We culminate our technical exploration by generating small datasets from two cultured cell lines and a primary bone marrow sample, to showcase obtainable proteome coverage differences from different source materials. Finally, as a proof of concept, we explore protein covariation to showcase how information on known protein complexes is captured inherently in our scp-MS data.

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Publication Details

Journal
Molecular & Cellular Proteomics
Published
2025-05-05
DOI
https://doi.org/10.1016/j.mcpro.2025.100982
Citations
14
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
9.83

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article

Quantitative Label-Free Single-Cell Proteomics on the Orbitrap Astral MS

Alexander Makarov, Pedro Aragon-Fernandez, Erwin M. Schoof, Christian Hock et al.
14 citations
Molecular & Cellular Proteomics
Advanced Proteomics Techniques and Applications
9.83
article

Quantitative Label-Free Single-Cell Proteomics on the Orbitrap Astral MS

Alexander Makarov, Pedro Aragon-Fernandez, Erwin M. Schoof, Christian Hock, Jakob Woessmann, Eduard Denisov, Nil Üresin, Bo Porse, J. Petzoldt, Valdemaras Petrosius, Tabiwang N. Arrey, Vlad Zabrouskov, Jinyu Su, Eugen Damoc, Hamish Stewart, Amelia C. Peterson, Bauke de Boer, Benjamin Furtwängler
article en
14 citations

Abstract

Single-cell proteomics by mass spectrometry (scp-MS) holds the potential to provide unprecedented insights into molecular features directly linked to the cellular phenotype while deconvoluting complex organisms into their basic building blocks. Tailored sample preparation that maximizes the extracted amount of material that is introduced into the mass spectrometer has rapidly propelled the field forward. However, the measured signal is still at the lower edge of detection, approaching the sensitivity boundary of current instrumentation. Here, we investigate the capacity of the enhanced sensitivity of the Orbitrap Astral mass spectrometer to facilitate deeper proteome profiles from low-input to single-cell samples. We carry out a comprehensive data acquisition method survey to pinpoint which parameters provide the most sensitivity. Furthermore, we explore the quantitative accuracy of the obtained measurements to ensure that the obtained abundances are in line with expected ground truth values. We culminate our technical exploration by generating small datasets from two cultured cell lines and a primary bone marrow sample, to showcase obtainable proteome coverage differences from different source materials. Finally, as a proof of concept, we explore protein covariation to showcase how information on known protein complexes is captured inherently in our scp-MS data.

Molecular & Cellular ProteomicsVol. 24(6)
University of Copenhagen (DK), Copenhagen University Hospital (DK), Thermo Fisher Scientific (United States) (US), Thermo Fisher Scientific (Germany) (DE), Technical University of Denmark (DK)
Novo Nordisk, Danmarks Tekniske Universitet, Eva og Henry Frænkels Mindefond, Novo Nordisk Fonden, LEO Fondet, Candys Foundation
Zero hunger
Openalex Percentile: Top 1%
Advanced Proteomics Techniques and Applications
9.83
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