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Updated: May 31, 2025
09:19
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
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Novel photocrosslinking chemical probes utilized for high-resolution spatial transcriptomics.
Leslie Spitalny1, Natalie Falco1, Whitney England1
1Department of Pharmaceutical Sciences, University of California Irvine California 92697 USA rspitale@uci.edu.
RSC Chemical Biology
|January 23, 2025
Summary
Researchers developed CrossSeq, a new spatial transcriptomic analysis method. This technique uses photocrosslinking probes to precisely isolate cells for RNA sequencing, advancing our understanding of tissue microenvironments.
Area of Science:
- Cell biology
- Molecular biology
- Genomics
Background:
- Cellular functions are optimized within complex tissue microenvironments through specific RNA expression.
- Spatial transcriptomics merges cell tagging with RNA sequencing for understanding spatial RNA expression.
- Current methods face limitations in spatial resolution, RNA sequencing capacity, and multiplexing for distinct cell isolation.
Purpose of the Study:
- To develop a novel method, CrossSeq, for multiplexed spatial transcriptomic analysis.
- To overcome limitations of existing spatial transcriptomic techniques regarding resolution, RNA capacity, and multiplexing.
- To enable precise isolation of spatially-distinct cells within tissue landscapes for detailed analysis.
Main Methods:
- CrossSeq utilizes photocrosslinking fluorescent probes and confocal microscopy for region demarcation.
- Investigated phenyl azide and diazirine crosslinking scaffolds, defining their photoactivity.
- Deployed an aryl azide scaffold with three fluorophores for multiplexing on glyoxal-fixed cells, followed by flow cytometry analysis.
Main Results:
- Successfully demonstrated the capability of CrossSeq to demarcate user-defined regions of interest on fixed cells.
- Defined photoactivity profiles for phenyl azide and diazirine crosslinking scaffolds.
- Applied CrossSeq to a metastatic cancer cell model to analyze gene expression differences between migratory and exterior cell populations.
Conclusions:
- CrossSeq offers a valuable new tool for spatial transcriptomic analysis.
- The technology enables easier access to spatial transcriptomic data using conventional microscopy.
- CrossSeq facilitates the investigation of gene expression dynamics in specific cellular locations within complex biological systems.
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