Spatial Proteomics Services
Discover the precise localization and dynamics of proteins within tissues and cells with our high-precision spatial proteomics solutions. We help researchers, pharmaceutical developers, and CROs overcome the limitations of traditional proteomics by providing detailed subcellular protein maps that reveal cellular heterogeneity, protein interactions, and biomarker potential. With our expertise, you can accelerate discovery, validate targets, and gain actionable insights into complex biological systems.
Our Services: Multiplexed imaging, LCM-MS targeted sampling, pixel-level photo-biotinylation, and comprehensive bioinformatics and multi-omics integration.
Problems We Solve: Resolving spatial heterogeneity, detecting low-abundance proteins in specific regions, and validating spatially localized targets.
Our Advantages: Single-cell and subcellular resolution, high-sensitivity quantification, end-to-end project management, and customizable experimental design.
What Is Spatial Proteomics and Why It Matters？
Spatial proteomics is the large-scale study of protein localization and distribution within cells, tissues, and organs. Unlike conventional proteomics, which primarily quantifies global protein abundance, spatial proteomics adds a dimension of localization. This approach identifies the locations of proteins within subcellular compartments and how their spatial arrangement changes under physiological or pathological conditions.
Understanding protein localization provides critical insights into cellular function, signaling pathways, and the interplay among diverse cell types. Spatial proteomics enables the identification of molecular markers, elucidation of disease mechanisms, and discovery of potential therapeutic targets. By preserving the spatial context of proteins, researchers gain a deeper understanding of both the structural and functional aspects of proteomics landscapes.
Figure 1. Overview of spatial proteomics approaches in breast cancer (Brozova K, et al., 2023).
Key Technologies Behind High-Precision Spatial Proteomics
Imaging-Based Spatial Proteomics
Imaging-based approaches use labeled antibodies or fluorescent protein tags to visualize proteins directly within their native environment. Antibody-based imaging enables researchers to detect multiple proteins in a single tissue section, revealing the organization of proteins across different cell types and tissue regions. Fluorescent protein tags, introduced through genetic engineering, enable live-cell imaging, allowing to observe how proteins move and interact over time.
Mass Spectrometry-Based Spatial Proteomics
MS enables the precise identification and quantification of proteins. When combined with techniques like laser capture microdissection, MS can analyze proteins from precisely selected regions of a tissue. Mass spectrometry imaging enables the simultaneous mapping of hundreds of proteins while preserving their spatial context.
Photo-Biotinylation and Proximity Labeling
Photo-biotinylation and proximity labeling are chemical approaches that tag proteins within specific regions using light-sensitive or enzyme-driven reactions. These methods selectively label proteins in defined microenvironments, enabling enrichment and analysis of proteins that are often too rare to detect using conventional techniques.
Quantitative MS Strategies for Spatial Data
Quantitative MS strategies provide precise protein abundance measurements while preserving spatial information.
- Label-Free Quantification (LFQ): Measures protein abundance across samples without chemical labeling. Suitable for flexible sample sizes and dynamic studies.
- Isobaric Tagging (TMT/iTRAQ): Enables multiplexed comparison of protein levels across multiple samples with high precision.
- Isotope Labeling (SILAC, AQUA): Facilitates absolute quantification and copy number estimation for proteins within defined subcellular compartments.
Advantages of Spatial Proteomics Over Conventional Methods
- Subcellular Precision: Traditional methods report the total amount of a protein in a sample but cannot reveal where it resides. Spatial proteomics identifies the positions of proteins within cells, organelles, or tissue regions.
- Cellular Heterogeneity Insight: Many tissues contain diverse cell types and states. Conventional proteomics averages signals across all cells, masking rare or specialized populations. Spatial proteomics can detect differences between cell types, reveal unique protein patterns, and highlight subpopulations critical in disease or development.
- Dynamic Localization Monitoring: Proteins often move in response to stimuli, stress, or treatment. Spatial proteomics tracks these movements in real-time, enabling studies of protein trafficking, redistribution, or translocation that traditional approaches often miss.
- Enhanced Biomarker Discovery: By combining abundance and location data, spatial proteomics identifies biomarkers that are not only present but localized to relevant cellular compartments.
- Contextual Functional Analysis: Understanding protein function requires knowledge of interactions and local environment. Spatial proteomics integrates spatial context, revealing protein networks, cellular neighborhoods, and microenvironment influences that standard proteomics cannot capture.
Integrating Spatial Proteomics with Other Omics (Multi-omics)
Integrating spatial proteomics with other omics turns separate data layers into a single, spatially informed story about tissue biology. In plain terms: spatial proteomics tells you which proteins are where, and other omics tell you complementary things
What you can gain
- Stronger biomarkers: a protein that is both abundant and co-located with a disease-specific RNA signal is more convincing.
- Mechanistic insight: co-localized changes in protein, RNA, and metabolites point to active pathways.
- Cellular neighborhood maps: combine protein maps with single-cell RNA to define functional niches.
Key points
- Match resolution. If your proteomics is at 10 µm, avoid pairing it with data that is only available at whole-tissue scale.
- Choose complementary assays. Typical pairings: spatial proteomics+Spatial phosphoproteomics, or+spatial transcriptomics , or+metabolomics, or+single-cell RNA-seq for deeper cell-type resolution.
- Align data spatially. Co-register images or annotate matching ROIs so each protein measurement links to the correct RNA/metabolite readout.
Creative Proteomics' Spatial Proteomics Service Workflow
- Sample Preparation: Tissue sections or cultured cells are processed to preserve spatial integrity. FFPE or fresh-frozen tissues can be accommodated.
- Enrichment and ROI Selection: Proteins from specific regions are isolated using LCM, photolabeling, or targeted extraction techniques.
- Detection: Imaging or MS-based approaches are applied to capture spatial protein profiles.
- Bioinformatics Analysis: Quantitative and spatial data are processed, normalized, and analyzed to identify protein localization patterns, co-expression, and functional networks.
- Result Delivery: Data is provided in publication-ready formats, including protein maps, heatmaps, and statistical summaries.
Deliverables and Reporting Standards
- High-resolution spatial protein maps.
- Quantitative protein abundance tables per ROI or subcellular compartment.
- Multi-dimensional visualizations, including heatmaps, violin plots, and cell neighborhood diagrams.
- Statistical analyses highlighting significant spatial changes.
Applications of Spatial Proteomics in Biomedical Research
- Cancer research: Map tumor heterogeneity, monitor protein changes in the microenvironment, and track how cancer cells respond to therapy.
- Neuroscience: Study protein distribution in brain tissue, revealing how localization influences synaptic function and disease progression.
- Immunology: Analyze immune cell infiltration, interactions, and protein signaling networks within tissues.
- Biomarker discovery: Identify spatial protein patterns linked to disease, accelerating the development of diagnostic and therapeutic targets.
- Single-cell analysis: Explore rare cell types and their spatial relationships, uncovering new functional states and cellular behaviors.
Sample Requirements
| Sample Type | Fresh-frozen or formalin-fixed paraffin-embedded (FFPE) tissue sections | Ensure samples are well-preserved to maintain protein integrity |
| Section Thickness | Typically 5–10 μm | Thin sections improve imaging resolution and mass spectrometry sensitivity |
| Sample Size | Small tissue areas (as little as a few mm²) are sufficient | Laser capture microdissection enables precise collection |
| Storage Conditions | Keep samples at –80 °C (fresh-frozen) or at room temperature (FFPE blocks) | Avoid repeated freeze–thaw cycles to reduce protein degradation |
| Fixation Quality | Proper fixation is essential for FFPE samples | Over-fixation can mask protein epitopes, reducing antibody binding efficiency |
| Labeling Compatibility | Samples must be compatible with immunofluorescence staining or MS preparation | Inform us about prior treatments or staining procedures |
| Documentation | Provide clear metadata, including tissue source, preparation method, and preservation history | Helps ensure accurate interpretation and reproducibility |
Why Choose Creative Proteomics for Spatial Proteomics Services
- Advanced Technology: Combines imaging, mass spectrometry, and photolabeling for high-resolution mapping.
- Full-Service Workflow: From sample preparation to data analysis, all stages are managed under strict quality control.
- Custom Solutions: Experimental designs tailored to client objectives, sample types, and research goals.
- Multi-Omics Integration: Capability to integrate spatial proteomics with transcriptomics and metabolomics for deeper biological insight.
- Proven Track Record: Decades of experience with CROs, pharmaceutical R&D, and academic research institutions.
FAQ
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Q1: How should spatial proteomics results be validated experimentally?
A1: Validation should combine orthogonal assays: targeted MS (PRM/SRM) or parallel reaction monitoring for quantitative confirmation; independent immunohistochemistry or immunofluorescence for localization and antibody corroboration; and functional assays when mechanistic claims are made.
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Q2: What is the role of proximity labeling in spatial proteomics?
A2: Proximity labeling is a technique used to identify proteins that are in close spatial proximity to a target protein. By tagging nearby proteins with a biotinylation enzyme, researchers can capture and analyze these interacting partners, providing insights into protein complexes and cellular microenvironments.
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Q3: What are the advantages of using mass spectrometry imaging (MSI) in spatial proteomics?
A3: Mass Spectrometry Imaging (MSI) allows for the direct visualization of the spatial distribution of proteins and other biomolecules within tissue sections. This label-free technique provides high-resolution, quantitative data, enabling the identification of molecular signatures associated with disease states. MSI is particularly useful for exploring heterogeneous tissue samples and identifying biomarkers in their native context.
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Q4: How does spatial proteomics contribute to understanding tissue heterogeneity?
A4: Spatial proteomics provides a detailed map of protein expression patterns across different regions of tissue samples. By revealing variations in protein localization and abundance, it helps to elucidate the underlying heterogeneity within tissues.
Demo
Demo: Spatial Proteomics Analysis of Soft and Stiff Regions in Human Acute Arterial Thrombus
This study employed a spatial proteomic workflow that combined laser-capture microdissection and mass spectrometry to compare stiff, fibrin- and platelet-rich regions with soft, erythrocyte-rich regions of human arterial thrombi from patients with myocardial and cerebral infarctions. The findings demonstrate that thrombus stiffness is driven by specific molecular pathways, highlighting TGF-β1 as a potential therapeutic target to enhance thrombolysis and improve thrombectomy outcomes.
Figure 2. Spatial proteomic analyses of carotid and coronary artery-derived thrombi reveal signature genes and pathways (Mai H, et al., 2023).
Figure 3. Spatial proteomics reveals a common upregulated protein from carotid and coronary arterial thrombi (Mai H, et al., 2023).
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Case Study
Case: Spatially resolved proteomic map shows that extracellular matrix regulates epidermal growth.
Abstract
Epidermal stem cells (EpSCs) in the basal layer rely on niche signals from the extracellular matrix (ECM) and the basement membrane (BM) for their proliferation, maintenance of stemness, and epithelial integrity. In secondary syphilis (SSP), BM-associated ECM proteins, including TGFBI, are downregulated, impairing EpSC function. Spatial organization of ECM and EpSC proteins is critical for understanding stem cell regulation and tissue repair.
Methods
- Spatial proteomics: Laser capture microdissection (LCM) was used to isolate eight layers of native and decellularized human skin, followed by mass spectrometry-based proteomics to quantify ECM and EpSC-associated proteins across the skin architecture.
- In vitro: Human primary EpSCs and hiPSC-derived EpSCs were treated with recombinant TGFBI; proliferation, stemness, and differentiation were assessed using transcriptomics, proteomics, immunofluorescence, and Western blotting.
- In vivo: Mouse wound healing models were treated with TGFBI or siRNA; re-epithelialization, EpSC proliferation, and ECM remodeling were analyzed.
- Mechanistic studies: Wnt/β-catenin signaling involvement was tested using the inhibitor XAV939.
Results
- Spatial proteomics revealed downregulation of BM- and ECM-associated proteins, including TGFBI, in SSP skin, highlighting disrupted EpSC niches.
- TGFBI treatment enhanced EpSC proliferation, stemness, and epithelial characteristics, upregulating cell–cell junction proteins and mesenchymal-epithelial transition markers while suppressing differentiation markers.
- Mechanistically, TGFBI activated Wnt/β-catenin signaling, promoting nuclear β-catenin and LEF-1 accumulation.
- In vivo, TGFBI accelerated wound healing and restored ECM and EpSC-related protein expression, while TGFBI knockdown delayed re-epithelialization.
- SSP-EpSCs showed impaired function that was rescued by TGFBI, restoring cell cycle, epidermal development, and mitochondrial-associated proteins.
Figure 4. Quantitative proteome profiling of spatially distinct protein signatures in normal human skin.
Figure 5. Epidermal dysfunction of secondary syphilis patients based on spatial proteome profiles.
Conclusion
Spatial proteomics revealed that TGFBI is a key ECM component of the EpSC niche. By mapping its localization and interactions, the study demonstrated that TGFBI promotes proliferation, stemness, and epithelial integrity through the Wnt/β-catenin signaling pathway, thereby enhancing skin regeneration and restoring SSP-EpSC function.
Related Services
References
- Brožová K, et al. Spatial proteomics for the molecular characterization of breast cancer. Proteomes, 2023, 11(2): 17.
- Mai H, et al. Spatial proteomics analysis of soft and stiff regions in human acute arterial thrombus. Stroke, 2023, 54(6): 1636-1644.
- Li J, et al. Spatially resolved proteomic map shows that extracellular matrix regulates epidermal growth. Nature communications, 2022, 13(1): 4012.
