Technical Development Unit 1: Intelligent live imaging of metastasis patterns and subcellular molecular states at the whole organism level

项目摘要 荧光显微镜结合光学透明斑马鱼异种移植模型有可能 旨在揭示癌细胞的功能异质性和适应性，这是其转移潜力的基础。 然而，这需要连接不同的鳞片，因为转移的部位可以跨越整个有机体，并且 其中的癌细胞需要用亚微米3D分辨率进行成像。此外，特定区域的低入住率 转移的壁龛需要对许多异种移植物进行成像。这扩展了当前显微镜的能力 技术，因为它们不能提供高通量、高空间分辨率和整体生物体成像 能力的同时。为了突破这一界限，我们将开发一种新的多模显微镜来 以高通量的方式在生物体和亚细胞尺度上自主成像。一种光遗传学 模块还允许操纵路径或将选定的癌细胞进行光转换以进行跟踪或 单细胞测序方法。计算流水线将自动检测和选择循环 用于高分辨率成像的多个异种移植物的转移部位。这将第一次允许 形态、存活和增殖以及信号转导等功能状态的定量比较 在不同的利基市场之间。我们预计，多模式显微镜和计算技术的结合 自主成像管道将为癌症功能异质性的关键方面提供新的线索 转移。

Project Summary Fluorescence microscopy combined with the optically transparent Zebrafish xenograft model has the potential to unravel the functional heterogeneity and adaptation of cancer cells that underlies their metastatic potential. However, this requires bridging disparate scales, as metastatic sites can form across an entire organism, and cancer cells within need to be imaged with sub-micron 3D resolution. Further, low occupancy of specific metastatic niches requires imaging many xenografts. This stretches the capabilities of current microscope technology as they fail to provide high-throughput, high-spatial resolution, and whole organism imaging capability at the same time. To break through this boundary, we will develop a new multi-modal microscope to autonomously image both at the organism and subcellular scale in a high-throughput fashion. An optogenetic module further allows to manipulate pathways or photo-convert selected cancer cells for either tracking or single cell sequencing approaches. A computational pipeline will automatically detect and select recurring metastatic sites across many xenografts for high-resolution imaging. This will allow for the first time the quantitative comparison of functional states such as morphology, survival and proliferation, and signaling between different niches. We anticipate that the combination of multi-modal microscopy and the computational pipelines for autonomous imaging will shed new light on key aspects of functional heterogeneity in cancer metastasis.