automated slide scanner microscope for bright field and fluorescence microscopy

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High-resolution microscopy allows to perform single-cell phenotyping in health and disease. Our key interest is to better characterize the human atherosclerotic plaque. In combination with laser microdissection microscopy and ultra-sensitive mass spectrometry, proteomic profiling at the single cell level could be achieved for the first time in an innovative approach called Deep Visual Proteomics (DVP). The approach allows besides the functional characterization of the heterogeneity of single cells also the implementation of a spatial proteomic characterization of tissues and is potentially superior to classical single-cell approaches at the DNA and RNA level. DVP uses high-resolution imaging, artificial intelligence (AI) - namely Biology Image Analysis Software (BIAS) - based image analysis approach for single-cell phenotyping and isolation with a novel ultrasensitive proteomics workflow. Specifically, we aim to characterize and study in depth the biological relevance of somatic mutations in plaque infiltrating leukocytes and smooth muscle cells (SMCs) combining powerful imagining technologies with unbiased proteomics. We hypothesize that somatic mutations might mediate proatherosclerotic effects in atherosclerotic plaques after invasion of mutated leukocytes. Very similar, we speculate that comparable to mutated leukocytes, SMCs affected by somatic mutations might support clonal expansion, reprogramming of SMCs, impact SMC phenotype transitions and finally affect plaque stability. DVP brings together protein abundance with complex cellular and subcellular phenotypes while maintaining spatial context. The data generated by DVP will assist us in discovering novel protein signatures that will provide, for the first time, molecular insights into proteome variation at the phenotypic level with complete spatial metainformation in human atherosclerotic plaque.