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Highly-Multiplexed Tissue Imaging with Raman Dyes
Published on: April 21, 2022
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Translating genomic tools to Raman spectroscopy analysis enables high-dimensional tissue characterization on
Manuel Sigle1, Anne-Katrin Rohlfing1, Martin Kenny2,3
1Department of Cardiology and Angiology, University Hospital Tuebingen, Eberhard Karls University Tuebingen, 72076, Tuebingen, Germany.
Nature Communications
|September 19, 2023
Summary
Raman microspectroscopy reveals molecular details in tissues, complementing spatial transcriptomics. This label-free method analyzes cell and matrix composition, aiding disease research.
Area of Science:
- Biomedical Engineering
- Molecular Biology
- Biochemistry
Background:
- Spatial transcriptomics offers genetic insights into tissue reorganization.
- Biomolecular composition analysis lags behind genomic studies, creating an information gap.
- Raman microspectroscopy provides high-resolution, untargeted spatiomolecular information.
Purpose of the Study:
- To demonstrate spatially resolved Raman "spectromics" for molecular-level tissue analysis.
- To repurpose bioinformatic tools from transcriptomics for "spectromics" data.
- To reveal homogeneity, heterogeneity, and dynamics of cell-matrix interactions.
Main Methods:
- Spatially resolved Raman microspectroscopy was applied to histological sections.
- Bioinformatic analysis tools, typically used for transcriptomics, were adapted.
- Murine myocardial infarction and cardiac hypertrophy models were studied.
Main Results:
- Identification of myocardial subclusters approaching pathological areas.
- Definition of the surrounding metabolic and cellular (immune) landscape.
- Demonstration of Raman "spectromics" for label-free, non-invasive tissue characterization.
Conclusions:
- Spatially resolved Raman "spectromics" bridges the gap in biomolecular sample analysis.
- The approach enables profound characterization of histological samples.
- This method allows for combination with downstream analyses on the same specimen.
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