Automated multi-target super-resolution microscopy with trust regions

具有信任区域的自动多目标超分辨率显微镜

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作者:David J Schodt, Farzin Farzam, Sheng Liu, Keith A Lidke

Abstract

We describe a dedicated microscope for automated sequential localization microscopy which we term Sequential Super-resolution Microscope (SeqSRM). This microscope automates precise stage stabilization on the order of 5-10 nanometers and data acquisition of all user-selected cells on a coverslip, limiting user interaction to only cell selection and buffer exchanges during sequential relabeling. We additionally demonstrate that nanometer-scale changes to cell morphology affect the fidelity of the resulting multi-target super-resolution overlay reconstructions generated by sequential super-resolution microscopy, and that regions affected by these shifts can be reliably detected and masked out using brightfield images collected periodically throughout the experiment. The SeqSRM enables automated multi-target imaging on multiple user-selected cells without the need for multiple distinct fluorophores and emission channels, while ensuring that the resulting multi-target localization data accurately reflect the relative organization of the underlying targets.

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