spp-spatial-proteomics

name	spp - Spatial Proteomics
description	Procedure for designing and analyzing spatial proteomics experiments to map protein localization and interactions in tissue context.
output	{"format":"prose"}

Spatial Proteomics

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Overview

Spatial proteomics maps where proteins are in cells and tissues, revealing organization that bulk measurements miss. This procedure guides technology selection, experiment design, data analysis, and biological interpretation for spatial protein profiling.

Steps

Step 1: Define the Biological Question

1. What do you want to learn about protein spatial organization?
2. Scale: subcellular / cellular / tissue / organ?
3. Multiplexing need: how many proteins simultaneously?
4. Throughput: how many samples/conditions?
5. Quantitative or qualitative readout?

Step 2: Select Technology

Method	Proteins	Resolution	Throughput	Best for
IF/IHC	1-5	Subcellular	High	Targeted validation
CODEX/PhenoCycler	40-60	Cellular	Medium	Tissue phenotyping
MIBI-TOF	40+	Subcellular	Low	High-resolution tissue
IMC	40+	~1μm	Low-Medium	Metal-tagged antibodies
MERFISH (protein)	100+	Subcellular	Medium	High-plex subcellular
Mass spec imaging	1000+	~10-50μm	Low	Discovery/unbiased

Selection criteria: resolution needed, multiplexing need, sample type, available equipment.

Step 3: Design the Experiment

1. Panel design: select proteins based on question (markers, targets, controls)
2. Antibody validation: confirm specificity for spatial context
3. Sample preparation: fixation, sectioning, antigen retrieval optimization
4. Controls: positive tissue, negative controls, isotype controls
5. Technical replicates: minimum 3 per condition
6. ROI selection strategy: random, targeted, or hybrid

Step 4: Execute and Acquire Data

1. Process samples per protocol
2. Acquire images/data per technology requirements
3. Include quality control checks at each stage
4. Document all deviations from protocol

Step 5: Analyze Spatial Data

1. Cell segmentation: identify individual cells
2. Phenotyping: classify cell types based on marker expression
3. Spatial statistics: analyze neighborhood composition, distances, interactions
   • Nearest neighbor analysis
   • Spatial autocorrelation
   • Interaction analysis (which cell types are adjacent?)
4. Cluster analysis: identify spatial niches or microenvironments
5. Comparison: statistical testing across conditions/samples

Step 6: Interpret and Validate

1. What spatial patterns emerge?
2. Do patterns correlate with biological outcomes?
3. Validate key findings with orthogonal methods
4. Place findings in biological context
5. Identify mechanistic hypotheses generated by spatial data

SPATIAL PROTEOMICS SUMMARY:
Question: [biological question]
Technology: [method selected]
Panel: [N proteins, key markers]
Samples: [N samples, N conditions]

Key spatial findings:
1. [pattern] — Statistical support: [test, p-value]
2. [pattern] — Statistical support: [test, p-value]

Biological interpretation: [what the spatial organization reveals]
Validation status: [validated / pending]

When to Use

• Studying tissue microenvironments (tumor, immune, developmental)
• Mapping cell-cell interactions in situ
• Understanding protein organization at subcellular level
• Complementing single-cell transcriptomics with spatial context

Verification

• Biological question clearly defined
• Technology matched to question requirements
• Panel validated for spatial context
• Adequate controls and replicates
• Spatial statistics appropriate for question
• Key findings validated