Single and few cell analysis for correlative light microscopy, metabolomics, and targeted proteomics

The interactions of proteins, membranes, nucleic acid, and metabolites shape a cell's phenotype. These interactions are stochastic, and each cell develops differently, making it difficult to synchronize cell populations. Consequently, studying biological processes at the single- or few-cell lev...

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Veröffentlicht in:Lab on a chip 2024-09, Vol.24 (18), p.4321-4332
Hauptverfasser: Rima, Luca, Berchtold, Christian, Arnold, Stefan, Fränkl, Andri, Sütterlin, Rosmarie, Dernick, Gregor, Schlotterbeck, Götz, Braun, Thomas
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Sprache:eng
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Zusammenfassung:The interactions of proteins, membranes, nucleic acid, and metabolites shape a cell's phenotype. These interactions are stochastic, and each cell develops differently, making it difficult to synchronize cell populations. Consequently, studying biological processes at the single- or few-cell level is often necessary to avoid signal dilution below the detection limit or averaging over many cells. We have developed a method to study metabolites and proteins from a small number of or even a single adherent eukaryotic cell. Initially, cells are lysed by short electroporation and aspirated with a microcapillary under a fluorescent microscope. The lysate is placed on a carrier slide for further analysis using liquid-chromatography mass spectrometry (LC-MS) and/or reverse-phase protein (RPPA) approach. This method allows for a correlative measurement of (i) cellular structures and metabolites and (ii) cellular structures and proteins on the single-cell level. The correlative measurement of cellular structure by light-microscopy, metabolites by LC-MS, and targeted protein detection by RPPA was possible on the few-cell level. We discuss the method, potential applications, limitations, and future improvements. We combined a single-cell lysis and handover system with mass spectrometry and reverse-phase protein arrays, allowing correlative single- and few-cell analysis combining microscopy with metabolomics and targeted proteomics.
ISSN:1473-0197
1473-0189
1473-0189
DOI:10.1039/d4lc00269e