Light sheet-based fluorescence microscopy offers efficient solutions to study complex processes on multiple biologically relevant scales. Sample chamber-based setups, which are specifically designed to preserve the three-dimensional integrity of the specimen and usually feature sample rotation, are the best choice in developmental biology. For instance, they have been used to document the entire embryonic morphogenesis of the fruit fly Drosophila melanogaster and the red flour beetle Tribolium castaneum. However, many available live imaging protocols provide only experimental frameworks for single embryos. Especially for comparative studies, such approaches are inconvenient, since sequentially imaged specimens are affected by ambient variance. Further, this limits the number of specimens that can be assayed within a given time. We provide an experimental framework for simultaneous live imaging that increases the throughput in sample chamber-based setups and thus ensuressimilar ambient conditions for all specimens. Firstly, we provide a calibration guideline for light sheet fluorescence microscopes. Secondly, we propose a mounting method for multiple embryos that is compatible with sample rotation. Thirdly, we provide exemplary three-dimensional live imaging datasets of Drosophila, for which we juxtapose three transgenic lines with fluorescently labeled nuclei, as well as of Tribolium, for which we compare the performance of three transgenic sublines that carry the same transgene, but at different genomic locations. Our protocol is specifically designed for comparative studies as it pro-actively addresses ambient variance, which is always present in sequential live imaging. This is especially important for quantitative analyses and characterization of aberrational phenotypes, which result e.g., from knockout experiments. Further, it increases the overall throughput, which is highly convenient when access to light sheetfluorescence microscopes is limited. Finally, the proposed mounting method can be adapted for other insect species and further model organisms, e.g., zebrafish, with basically no optimization effort.
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