A framework for ultra-low input spatial tissue proteomics

Spatial tissue proteomics combining microscopy-based cell phenotyping with ultrasensitive mass spectrometry (MS)-based proteomics is an emerging and powerful concept for the study of cell function and heterogeneity in health and disease. However, optimized workflows that preserve morphological information for image-based phenotype discovery and maximize proteome coverage of few or even single cells from laser microdissected archival tissue, are currently lacking. Here, we report a robust and scalable workflow for the proteomic analysis of ultra-low input formalin-fixed, paraffin-embedded (FFPE) material. Benchmarking in the murine liver resulted in up to 2,000 quantified proteins from single hepatocyte contours and nearly 5,000 proteins from 50-cell regions with high quantitative reproducibility. Applied to human tonsil, we profiled 146 microregions including spatially defined T and B lymphocyte niches and quantified cell-type specific markers, cytokines, immune cell regulators and transcription factors. These rich data also highlighted proteome dynamics in spatially defined zones of activated germinal centers, illuminating sites undergoing active B-cell proliferation and somatic hypermutation. Our results demonstrate the power of spatially-resolved proteomics for tissue phenotyping by integrating high-content imaging, laser microdissection, and ultrasensitive mass spectrometry. This approach has broad implications for a wide range of biomedical applications, including early disease profiling, drug target discovery and biomarker research.