Spatially resolved ultra visual MicroProteomics via hydrogel-based tissue expansion

Nanoscale spatially resolved proteomics is crucial for mapping the heterogeneity of proteomes within biological samples. However, this remains a technical challenge due to the complexity of tissue micro-sampling techniques and the mass spectrometry analysis required for nanoscale specimen volumes. Here, we introduce a novel method called microProteomEx, which combines spatially resolved visual proteomics, enabling MS-based analysis of intact tissue samples guided by super-resolution imaging. microProteomEx enables the quantitative profiling of spatial proteome variability in mammalian tissues with an impressive lateral resolution of approximately 57 µm. This is achieved through re-embedding micro-sampling, which does not require custom or specialized equipment. When paired with ultrasensitive liquid chromatography-mass spectrometry, microProteomEx can identify around 900 proteins from tissue samples as small as ~12 cells. Region of interest selection is guided by super-resolution imaging of the expanded samples under a conventional diffraction-limited microscope, allowing the identification of ultrastructural morphological features with an effective spatial imaging resolution of 47.0 nm. Compared to the original protocol, ProteomEx, we have developed a workflow that is faster, simpler, offers higher spatial resolution, and achieves greater protein identification. We have validated the utility of microProteomEx in profiling the proteomes and super-resolution imaging of various biological tissues, including the brain, liver, kidney, and heart. This method preserves both the spatial proteomic data and cellular structure imaging information within the tissue context, which has significant implications for the molecular profiling of clinical samples and mouse models of Alzheimer"s disease. The combination of super-resolution imaging with spatially resolved proteomic analysis of intact tissues enables a new perspective of deep visual proteomics where proteome and cytoarchitecture can be analyzed and correlated on the same sample.