bioRxivBiochemistryPreprint
Mass Spectrometry Imaging of Caenorhabditis elegans with Fluorescence Microscopy of Tissue-Specific Reporters and Oriented Cryo-Sectioning
Ryutaro Einar JacobsoniD, Elizabeth Wanchisn SmithiD, Yasuaki SaitohiD, Tian Autumn QiuiD
Abstract
Caenorhabditis elegans is a powerful model organism for studying development, neurobiology, aging, and toxicology, yet most studies rely on genetic and phenotypic measurements that do not directly capture their biochemical landscape. Mass spectrometry (MS)-based metabolomics has emerged to address this gap by enabling detection of small-molecule metabolites and lipids. Conventional chromatography-MS approaches require homogenization, eliminating spatial information during sample preparation. Mass spectrometry imaging (MSI) offers the ability to map metabolites and lipids in situ, however, its application to C. elegans is limited by challenges in sample preparation, particularly maintaining structural integrity during cryo-sectioning and assigning molecular features to specific tissues. In this work, we develop an integrated sample preparation workflow to overcome these constraints and enable high-resolution, spatially interpretable MSI of C. elegans adult hermaphrodites. We introduced a new imaging modality, fluorescence microscopy of tissue-specific, genetically encoded reporters, which expresses GFP in intestinal cells and RFP in neuronal nuclei. A mixed gelatin embedding medium preserved both structural morphology and fluorescence reporter signals during cryo-sectioning, and a simple sandwiching strategy enabled longitudinal sectioning of the worm body. Fluorescence microscopy and MSI were done on the same tissue. Using this integrated approach, we achieved matrix-assisted laser desorption/ionization (MALDI) MSI of adult C. elegans at 10 m pixel resolution. By achieving structural preservation and enabling fluorescence reporters as an additional imaging modality for data interpretation, this workflow overcomes key limitations in MSI of C. elegans and provides a practical framework for MSI analysis of microscale biological samples.
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