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Protein-retention expansion microscopy for visualizing subcellular organelles in fixed brain tissue

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BACKGROUND Protein expansion microscopy (proExM) is a powerful technique that crosslinks proteins to a swellable hydrogel to physically expand and optically clear biological samples. The resulting increased resolution (~70nm) and… Click to show full abstract

BACKGROUND Protein expansion microscopy (proExM) is a powerful technique that crosslinks proteins to a swellable hydrogel to physically expand and optically clear biological samples. The resulting increased resolution (~70nm) and physical separation of labeled proteins make it an attractive tool for studying the localization of subcellular organelles in densely packed tissues, such as the brain. However, the digestion and expansion process greatly reduce fluorescence signals making it necessary to optimize ExM conditions per sample for specific end goals. NEW METHOD Here we compare the staining and digestion conditions of existing proExM workflows to identify the optimal protocol for visualizing subcellular organelles (mitochondria and the Golgi apparatus) within reporter-labeled neurons in fixed mouse brain tissue. RESULTS We found that immunostaining before proExM and using a proteinase K based digestion for 8hours consistently resulted in robust fluorescence retention for immunolabeled subcellular organelles and genetically-encoded reporters. COMPARISON WITH EXISTING METHODS With these methods, we more accurately quantified mitochondria size and number and better visualized Golgi ultrastructure in individual CA2 neurons in the mouse hippocampus. CONCLUSIONS This organelle optimized proExM protocol will be broadly useful for investigators interested in visualizing the spatial distribution of immunolabeled subcellular organelles in various reporter mouse lines, reducing effort, time and resources on the optimization process.

Keywords: microscopy; visualizing subcellular; brain; expansion microscopy; subcellular organelles

Journal Title: Journal of Neuroscience Methods
Year Published: 2021

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