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Updated: Jun 15, 2025
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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
4.9K
Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics.
Gunsagar S Gulati1, Jeremy Philip D'Silva2, Yunhe Liu3
1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Nature Reviews. Molecular Cell Biology
|August 21, 2024
Summary
Single-cell and spatial transcriptomics reveal cellular diversity and tissue microenvironments. These powerful tools are advancing biological research and clinical translation through innovative computational methods.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- Single-cell transcriptomics has significantly advanced the understanding of cellular heterogeneity in health and disease.
- Spatial transcriptomics provides crucial context by mapping cells within their multicellular neighborhoods, identifying tissue ecotypes.
Purpose of the Study:
- To review recent advancements in single-cell and spatial transcriptomics technologies and computational methodologies.
- To discuss challenges and future prospects in analyzing complex transcriptomic data for biological discovery and clinical applications.
Main Methods:
- Analysis of large-scale datasets from targeted and whole-transcriptome profiling of millions of cells.
- Integration of sample processing, data integration, cell state identification, trajectory modeling, deconvolution, and spatial analysis techniques.
- Application of deep learning and foundation models for advanced transcriptomic data analysis.
Main Results:
- New insights into developmental hierarchies, cellular plasticity, and tissue microenvironments.
- Identification of spatially recurrent cellular phenotypes (ecotypes) and subtle cell states.
- Demonstrated utility of advanced computational methods, including deep learning, for transcriptomic data interpretation.
Conclusions:
- Single-cell and spatial transcriptomics are revolutionizing biological research by providing unprecedented cellular and spatial resolution.
- These technologies hold significant promise for translation to clinical applications in fields such as stem cell biology, immunology, and oncology.
