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Updated: Jun 11, 2025
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Isolation of Adipose Tissue Nuclei for Single-Cell Genomic Applications
Published on: June 12, 2020
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Dissecting human adipose tissue heterogeneity using single-cell omics technologies
Giuliana Di Rocco1, Angelo Trivisonno2, Giovanni Trivisonno3
1Unit of Cellular Networks and Molecular Therapeutic Targets, IRCCS Regina Elena National Cancer Institute, 00144, Rome, Italy.
Stem Cell Research & Therapy
|September 28, 2024
Summary
Single-cell omics technologies reveal adipose tissue heterogeneity, identifying biomarkers for progenitor cells and understanding disease links. This advances regenerative medicine and clinical translation of adipose-derived therapies.
Area of Science:
- Biotechnology
- Genomics
- Cell Biology
Background:
- Adipose tissue is highly heterogeneous, impacting clinical applications.
- Understanding this heterogeneity is crucial for regenerative medicine and disease research.
- Current methods struggle to fully characterize adipose tissue complexity.
Purpose of the Study:
- To review methods for dissecting adipose tissue heterogeneity.
- To highlight advances in single-cell omics technologies for adipose tissue research.
- To explore the implications of adipose tissue complexity for clinical translation.
Main Methods:
- Single-cell omics technologies (genomic, epigenomic, transcriptomic, proteomic, lipidomic, matrisomic).
- Analysis of cellular heterogeneity, lineage hierarchy, and differentiation status.
- Review of current literature on adipose tissue characterization.
Main Results:
- Single-cell omics provide unprecedented resolution of adipose tissue heterogeneity.
- Identifies potential biomarkers for progenitor cell subpopulations.
- Links adipose tissue dysfunction to cancer, obesity, and metabolic syndrome.
- Highlights implications for regenerative medicine and cell-free approaches.
Conclusions:
- Single-cell omics are essential for understanding adipose tissue complexity.
- Advances in omics technology are key to exploring adipose tissue dynamics.
- Addressing heterogeneity is critical for establishing quality standards in clinical translation.
