Enhanced in situ spatial proteomics by effective combination of MALDI imaging and LC-MS/MS.
Mol. Cell. Proteomics 23:100811 (2024)
Highly specialized cells are fundamental for proper functioning of complex organs. Variations in cell-type specific gene expression and protein composition have been linked to a variety of diseases. Investigation of the distinctive molecular makeup of these cells within tissues is therefore critical in biomedical research. Although several technologies have emerged as valuable tools to address this cellular heterogeneity, most workflows lack sufficient in situ resolution and are associated with high cost and extremely long analysis times. Here, we present a combination of experimental and computational approaches that allows a more comprehensive investigation of molecular heterogeneity within tissues than by either shotgun LC-MS/MS or MALDI imaging alone. We applied our pipeline on mouse brain, which contains a wide variety of cell types that not only perform unique functions but also exhibit varying sensitivities to insults. We explored the distinct neuronal populations within the hippocampus, a brain region crucial for learning and memory that is involved in various neurological disorders. As an example, we identified the groups of proteins distinguishing the neuronal populations of dentate gyrus (DG) and the cornu ammonis (CA) in the same brain section. Most of the annotated proteins matched the regional enrichment of their transcripts, thereby validating the method. As the method is highly reproducible, the identification of individual masses through the combination of MALDI-IMS and LC-MS/MS methods can be used for the much faster and more precise interpretation of MALDI-IMS measurements only. This greatly speeds up spatial proteomic analyses and allows the detection of local protein variations within the same population of cells. The method's general applicability has the potential to be used to investigate different biological conditions and tissues and a much higher throughput than other techniques making it a promising approach for clinical routine applications.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Data Integration ; Dentate Gyrus ; Imaging Mass Spectrometry ; Laser Capture Microdissection ; Spatial Proteomics; Mass-spectrometry; Gene-expression; Resolution; Atlas
Keywords plus
Sprache
englisch
Veröffentlichungsjahr
2024
Prepublished im Jahr
0
HGF-Berichtsjahr
2024
ISSN (print) / ISBN
1535-9476
e-ISSN
1535-9484
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 23,
Heft: 8,
Seiten: ,
Artikelnummer: 100811
Supplement: ,
Reihe
Verlag
American Society for Biochemistry and Molecular Biology
Verlagsort
Radarweg 29, 1043 Nx Amsterdam, Netherlands
Tag d. mündl. Prüfung
0000-00-00
Betreuer
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Prüfer
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Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
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Priorität
Begutachtungsstatus
Peer reviewed
POF Topic(s)
30201 - Metabolic Health
Forschungsfeld(er)
Genetics and Epidemiology
PSP-Element(e)
G-500693-001
Förderungen
Forschungsmodul Medizin program of the Medical Faculty, LMU
Fritz-Thyssen Stiftung
German Center for Diabetes Research
Deutsche Forschungsgemeinschaft (DFG)
Copyright
Erfassungsdatum
2024-07-15