Key Takeaways
- Spatial proteomics retains tissue architecture, whereas bulk proteomics averages across homogenized cells.
- Large studies have reported only a moderate correlation between mRNA and protein abundance, so protein data can add information to RNA data.
- Cyclic immunofluorescence increases marker number on standard fluorescence microscopes but requires long run times and extensive antibody validation.
- Mass spectrometry approaches include imaging mass cytometry with metal-tagged antibodies, antibody-free mass spectrometry imaging across a section, and LC-MS/MS after isolation of selected material.
- Laser capture microdissection (LCM) can isolate defined regions or cells for deep LC-MS/MS profiling.
What Is Spatial Proteomics?
Spatial proteomics measures which proteins are present and where they are located in cells and tissues. A T cell inside a tumor and one at the tumor margin may express different proteins, and spatial data can capture that difference.
Nature Methods named spatial proteomics its Method of the Year for 2024 (Nature Methods, 2024).
Why Protein Data Adds Information
Large-scale human proteome studies have found only a moderate correlation between mRNA and protein abundance. A 2022 analysis of tumor and cell-line profiles reported that measurement reproducibility accounts for a substantial part of the unexplained variation (Upadhya and Ryan, 2022). Post-transcriptional regulation, protein turnover, and post-translational modifications also contribute.
Spatial Proteomics and Spatial Transcriptomics
- Spatial transcriptomics measures RNA and can cover thousands of genes while retaining location in the section.
- Spatial proteomics measures proteins directly, including some modifications and interactions, at the scale the chosen method can resolve.
- Spatial multiomics methods measure both on the same section. For example, SPOTS combined whole-transcriptome capture with antibody-derived protein tags on the same tissue (Ben-Chetrit et al., 2023).
Fluorescence-Based Approaches
Conventional immunofluorescence is limited by spectral overlap between fluorophores, which restricts the number of markers per round. Cyclic immunofluorescence methods repeat cycles of staining, imaging, and signal removal or inactivation to build higher-plex images of the same section. Some methods use DNA-barcoded antibodies that are revealed iteratively.
Strengths:
- Preserve tissue morphology for spatial analysis
- Can run on standard fluorescence microscopes, depending on the method
- Suit targeted panels of known markers
Limitations:
- Each cycle takes time, and many cycles lead to long total run times.
- Repeated cycling can affect tissue integrity or antigenicity.
- Each antibody needs validation for the tissue and fixation.
Typical uses: immune phenotyping, tumor microenvironment mapping, and studies of known biomarkers.
Mass Spectrometry-Based Approaches
Imaging Mass Cytometry
Imaging mass cytometry (IMC) labels antibodies with metal isotopes instead of fluorophores. A laser ablates the tissue spot by spot, and the released metals are measured by mass spectrometry. Because no fluorophores are used, spectral overlap is not a limitation. Acquisition is slower than fluorescence imaging, and the tissue is consumed during analysis. IMC remains a targeted, antibody-based method: it measures proteins for which metal-tagged antibodies are available. A Nature Reviews Methods Primers overview covers multiplexed antibody imaging strategies of this kind (Nature Reviews Methods Primers).
Mass Spectrometry Imaging
Mass spectrometry imaging (MSI), such as MALDI-MSI, measures molecular signals directly across a section without antibodies and produces a continuous spatial map of detected ions. It is suited to discovery because it does not depend on a predefined antibody panel. Finer spatial resolution reduces the material per pixel, which can lower identification confidence. MSI is distinct from LC-MS/MS peptide proteomics after isolation of selected material (review).
Microdissection Followed by LC-MS/MS
Selected cells or regions can be isolated by laser capture microdissection (LCM) and analyzed by liquid chromatography-tandem mass spectrometry. Some workflows use image analysis to classify cells before microdissection. This approach can measure many proteins from defined cell populations, but throughput is lower and input amounts are small. LCM followed by LC-MS/MS is region-based sampling: it profiles selected material and does not automatically generate a continuous tissue-wide molecular map.
Choosing a Method
| Factor | Fluorescence cyclic imaging | Imaging mass cytometry | Mass spectrometry imaging | LCM with LC-MS/MS |
|---|---|---|---|---|
| Detection | Targeted antibodies (fluorophores) | Targeted metal-tagged antibodies | Antibody-free ion map across section | Antibody-free LC-MS/MS of isolated material |
| Panel | Predefined markers | Predefined markers | Untargeted detected signals | Untargeted proteins from selected regions |
| Spatial product | High-plex image of section | High-plex image of section | Continuous molecular map of section | Region-based profiles, not a continuous map |
| Resolution | Subcellular | Subcellular to cellular | Varies with instrument | Defined by microdissection |
| Throughput | Moderate, limited by cycles | Lower | Moderate | Lower |
| Main use | Phenotyping known markers | Phenotyping without spectral overlap | Discovery mapping across a section | Deep profiling of selected regions or cells |
Consider five factors:
- Plex needed: a few markers, dozens of markers, or an untargeted proteome.
- Spatial resolution: subcellular, single-cell, or region-level.
- Budget: instrument access, reagents, and analysis effort.
- Throughput: number of samples and tissue area per run.
- Existing infrastructure: available microscopes and mass spectrometers.
Laxco Tools for Spatial Proteomics Workflows
These are separate platforms and do not form a single integrated analysis system:
- Accuva Cellect: a laser capture microdissection system for isolating selected cells or regions before protein extraction and mass spectrometry. It uses an infrared laser for capture of single cells or small numbers of cells and a UV laser for cutting dense structures. Protein extraction and mass spectrometry are separate downstream laboratory procedures. Laxco lists training and 48-hour response times for Accuva Cellect.
- LEAP AI: combines Accuva LEAP optics with Media Cybernetics Image-Pro AI for pre-trained deep-learning segmentation, measurement, and reporting. LEAP AI is a separate imaging and analysis platform; it is not built into Accuva Cellect, does not automatically select cells for Cellect capture, and does not control the Cellect laser.
- SLi6Pro: an inverted widefield fluorescence microscope with SeBaLIT™ LED-based illumination. It supports three-color multiplex fluorescence imaging and lists compatibility with more than 110 fluorochromes across approximately 390–662 nm. Fluorochrome compatibility is not the same as simultaneous channel capacity.
Laxco does not perform proteomic analysis as a laboratory service.
Frequently Asked Questions
Which approach suits discovery of unknown proteins?
Untargeted mass spectrometry approaches suit discovery of proteins outside a predefined antibody panel. Mass spectrometry imaging maps detected molecular signals across a section as a continuous ion map, while LCM followed by LC-MS/MS profiles selected regions or cells in more depth without producing a continuous tissue-wide map. Antibody-based methods, including cyclic immunofluorescence and imaging mass cytometry, suit known targets for which validated antibodies exist.
What does Accuva Cellect contribute to a spatial proteomics workflow?
Accuva Cellect isolates selected cells or tissue regions under microscopic guidance before protein extraction and mass spectrometry. Its infrared laser captures single cells or small groups, and its UV laser cuts dense structures.
Can I run multiplexed immunofluorescence on a Laxco microscope?
The SLi6Pro supports three-color multiplex fluorescence with SeBaLIT illumination across approximately 390–662 nm and lists compatibility with more than 110 fluorochromes. Treat the dye count as fluorochrome compatibility, not simultaneous channel capacity. Cyclic high-plex protocols also depend on reagents, stage registration, and software, so confirm requirements with a Laxco specialist.
How can segmentation results be kept consistent across samples?
Apply the same validated segmentation protocol to every image. LEAP AI provides pre-trained deep-learning segmentation and batch-ready protocols through Media Cybernetics Image-Pro AI, which helps reduce differences between operators and sessions.
What should I compare before requesting a quote?
List your target proteins or discovery goals, tissue types, required resolution, sample numbers, and available mass spectrometry and imaging resources. A Laxco specialist can then advise on an Accuva Cellect, LEAP AI, or SLi6Pro configuration.
