Molecular & Cellular ProteomicsBiochemistryPeer-reviewed journal article
Quantitative Label-Free Single-Cell Proteomics on the Orbitrap Astral MS
Valdemaras PetrosiusiD, Pedro Aragon-FernandeziD, Tabiwang N. ArreyiD, Jakob WoessmanniD, Nil ÜresiniD, Bauke de BoeriD, Jinyu SuiD, Benjamin FurtwängleriD, Hamish I. StewartiD, Eduard V. Denisov, Johannes Petzoldt, Amelia C. Peterson, Christian Hock, Eugen DamociD, Alexander MakaroviD, Vlad ZabrouskoviD, Bo Torben PorseiD, Erwin M. SchoofiD
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 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.
- organism: human
- assay: proteomics
- research focus: benchmarking
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- approach: experimental assay
- Citations
- 33
- FWCI
- 7.78
- Field percentile
- top 1%
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