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  Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition

Petrosius, V., Aragon-Fernandez, P., Ueresin, N., Kovacs, G., Phlairaharn, T., Furtwaengler, B., et al. (2023). Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition. Nature Communications, 14(1): 5910. doi:10.1038/s41467-023-41602-1.

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Petrosius, Valdemaras1, Autor
Aragon-Fernandez, Pedro1, Autor
Ueresin, Nil1, Autor
Kovacs, Gergo1, Autor
Phlairaharn, Teeradon2, Autor           
Furtwaengler, Benjamin1, Autor
op de Beeck, Jeff1, Autor
Skovbakke, Sarah L.1, Autor
Goletz, Steffen1, Autor
Thomsen, Simon Francis1, Autor
Keller, Ulrich auf dem1, Autor
Natarajan, Kedar N.1, Autor
Porse, Bo T.1, Autor
Schoof, Erwin M.1, Autor
Affiliations:
1external, ou_persistent22              
2Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565159              

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Schlagwörter: GROUND-STATE; STEM-CELLS; ENRICHMENT; PEPTIDES; SETScience & Technology - Other Topics;
 Zusammenfassung: Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
Single-cell proteomics by Mass Spectrometry (scpMS) provides unparalleled insights into cellular mechanisms from a proteome-centric standpoint. Here, the authors leverage sensitivity-tailored data acquisition methods to profile cell state heterogeneity in cultured model systems.

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Sprache(n): eng - English
 Datum: 2023-09-22
 Publikationsstatus: Online veröffentlicht
 Seiten: 16
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: ISI: 001185491300028
DOI: 10.1038/s41467-023-41602-1
 Art des Abschluß: -

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Titel: Nature Communications
  Kurztitel : Nat. Commun.
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: London : Nature Publishing Group
Seiten: - Band / Heft: 14 (1) Artikelnummer: 5910 Start- / Endseite: - Identifikator: ISSN: 2041-1723
CoNE: https://pure.mpg.de/cone/journals/resource/2041-1723