automated slide scanner microscope for bright field and fluorescence microscopy

用于明场和荧光显微镜的自动载玻片扫描显微镜

• 批准号: 470041852
• 金额: --
• 依托单位: Technische Universität München (TUM)
• 依托单位国家: 德国
• 项目类别: Major Research Instrumentation
• 财政年份: 2022
• 资助国家: 德国
• 起止时间: 2021-12-31 至 无数据
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/470041852?language=en
• 关键词: automated; slide; scanner; microscope; bright

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.

高分辨率显微镜可以对健康和疾病进行单细胞表型分析。我们的主要兴趣是更好地表征人类动脉粥样硬化斑块。结合激光显微切割显微镜和超灵敏质谱分析，可以通过称为深度视觉蛋白质组学 (DVP) 的创新方法首次实现单细胞水平的蛋白质组分析。该方法除了可以对单细胞异质性进行功能表征外，还可以对组织进行空间蛋白质组表征，并且在 DNA 和 RNA 水平上可能优于经典的单细胞方法。 DVP 使用高分辨率成像、人工智能 (AI) - 即生物图像分析软件 (BIAS) - 基于图像分析方法，通过新颖的超灵敏蛋白质组学工作流程进行单细胞表型分析和分离。具体来说，我们的目标是将强大的成像技术与公正的蛋白质组学相结合，深入表征和研究斑块浸润白细胞和平滑肌细胞（SMC）中体细胞突变的生物学相关性。我们假设体细胞突变可能在突变白细胞侵入后介导动脉粥样硬化斑块中的促动脉粥样硬化效应。非常相似，我们推测，与突变的白细胞相比，受体细胞突变影响的 SMC 可能支持克隆扩增、SMC 重编程、影响 SMC 表型转变并最终影响斑块稳定性。 DVP 将蛋白质丰度与复杂的细胞和亚细胞表型结合在一起，同时保持空间背景。 DVP 生成的数据将帮助我们发现新的蛋白质特征，这些特征将首次提供对表型水平上蛋白质组变异的分子洞察，以及人类动脉粥样硬化斑块中完整的空间元信息。