The authors developed multiplexed Deep Visual Proteomics (mxDVP), an end-to-end workflow combining high-plex imaging, automated computational analysis, and spatially guided ultra-sensitive mass spectrometry, powered by the open-source image analysis framework PIPΣX for whole-slide membrane-aware segmentation, annotation, and laser microdissection export, achieving more than 6,000 protein identifications from as few as 100 small islet cells; applied to human pancreatic islets it segmented over 860,000 cells and resolved twelve endocrine subtypes, including rare polyhormonal and intermediate-state populations showing spatial organization patterns, co-expression of INSM1 and SCG3, and hybrid α/β/δ signatures.
The authors developed multiplexed Deep Visual Proteomics (mxDVP), an end-to-end workflow combining high-plex imaging, automated computational analysis, and spatially guided ultra-sensitive mass spectrometry, powered by the open-source image analysis framework PIPΣX for whole-slide membrane-aware segmentation, annotation, and laser microdissection export, achieving more than 6,000 protein identifications from as few as 100 small islet cells; applied to human pancreatic islets it segmented over 860,000 cells and resolved twelve endocrine subtypes, including rare polyhormonal and intermediate-state populations showing spatial organization patterns, co-expression of INSM1 and SCG3, and hybrid α/β/δ signatures.