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Updated: Sep 3, 2025
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-tune Virtual Microdissection
Veronica Ibarra-Lopez1, Sangeeta Jayakar2, Yeqing Angela Yang3
1Department of Pathology, Genentech; ibarralv@gene.com.
Automated protocols enhance spatial proteomics by guiding region selection. While not compatible with spatial transcriptomics, specific cell populations are detectable in small regions using manual methods.
Area of Science:
- Spatial Omics
- Biotechnology
- Immunofluorescence
Background:
- Multiplexing in spatial omics allows simultaneous assessment of multiple markers with spatial context.
- Spatial proteomics and transcriptomics utilize photo-cleavable oligo-tagged antibodies and probes for multiplexed analysis.
- Quantification of cleaved oligos from specific tissue regions reveals underlying biological insights.
Purpose of the Study:
- To demonstrate automated custom antibody visualization protocols for guiding region of interest (ROI) selection in spatial proteomics.
- To evaluate the performance of this automated protocol with spatial transcriptomics assays.
- To develop and validate a 3-plex immunofluorescence (IF) assay for automated marker visualization.
Main Methods:
- Development of a 3-plex IF assay using tyramide signal amplification (TSA) on an automated platform.
- Automation of the visualization protocol with a validated 3-plex assay for quality and reproducibility.
- Evaluation of SYTO dyes as DAPI alternatives for TSA-based IF imaging on a spatial profiling platform.
- Testing of small ROI selection (50 µm and 300 µm) for spatial transcriptomics to investigate specific cell populations.
Main Results:
- Automated visualization protocols significantly benefit spatial proteomics by standardizing ROI selection.
- The developed automated visualization protocol was not compatible with spatial transcriptomics assays.
- Specific cell populations were successfully detected in small ROIs (50-300 µm) using standard manual visualization protocols for spatial transcriptomics.
Conclusions:
- Automated, standardized protocols are crucial for optimizing ROI selection in spatial proteomics.
- The automated visualization method is not suitable for spatial transcriptomics.
- Manual visualization protocols remain effective for detecting specific cell populations in small ROIs within spatial transcriptomics studies.
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