ESPRESSO: spatiotemporal omics based on organelle phenotyping

Area of Science:

• Cell Biology
• Biotechnology
• Genomics

Background:

• Omics technologies (genomics, transcriptomics, proteomics, metabolomics) provide high-dimensional cell phenotypes.
• Current omics methods lack the ability to capture temporal biological data.
• Understanding complex biological systems requires methods with spatial and temporal resolution.

Purpose of the Study:

• Introduce ESPRESSO (Environmental Sensor Phenotyping RElayed by Subcellular Structures and Organelles) for single-cell phenotyping.
• Enable high-dimensional phenotyping resolved in space and time.
• Advance the exploration of cellular states and biological processes.

Main Methods:

• ESPRESSO combines fluorescent labeling, advanced microscopy, and image/data analysis.
• Extracts morphological and functional information from organelles at the single-cell level.
• Integrates spatial and temporal dimensions into cellular analysis.

Main Results:

• Validated ESPRESSO methodology across diverse cellular systems.
• Applied ESPRESSO to analyze cell type, stress response, differentiation, and immune cell polarization.
• Demonstrated correlation between phenotype changes and gene expression.
• Showcased applicability in 3D cultures.

Conclusions:

• ESPRESSO provides unprecedented spatial and temporal resolution for single-cell phenotyping.
• The technique enhances the understanding of dynamic cellular processes.
• ESPRESSO offers a novel path for exploring complex biological systems in space and time.