Translating genomic tools to Raman spectroscopy analysis enables high-dimensional tissue characterization on molecular resolution.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
19 09 2023
19 09 2023
Historique:
received:
18
09
2022
accepted:
04
09
2023
medline:
21
9
2023
pubmed:
20
9
2023
entrez:
19
9
2023
Statut:
epublish
Résumé
Spatial transcriptomics of histological sections have revolutionized research in life sciences and enabled unprecedented insights into genetic processes involved in tissue reorganization. However, in contrast to genomic analysis, the actual biomolecular composition of the sample has fallen behind, leaving a gap of potentially highly valuable information. Raman microspectroscopy provides untargeted spatiomolecular information at high resolution, capable of filling this gap. In this study we demonstrate spatially resolved Raman "spectromics" to reveal homogeneity, heterogeneity and dynamics of cell matrix on molecular levels by repurposing state-of-the-art bioinformatic analysis tools commonly used for transcriptomic analyses. By exploring sections of murine myocardial infarction and cardiac hypertrophy, we identify myocardial subclusters when spatially approaching the pathology, and define the surrounding metabolic and cellular (immune-) landscape. Our innovative, label-free, non-invasive "spectromics" approach could therefore open perspectives for a profound characterization of histological samples, while additionally allowing the combination with consecutive downstream analyses of the very same specimen.
Identifiants
pubmed: 37726278
doi: 10.1038/s41467-023-41417-0
pii: 10.1038/s41467-023-41417-0
pmc: PMC10509269
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
5799Informations de copyright
© 2023. Springer Nature Limited.
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