DOI 10.1021/acs.analchem.6c04271
On-Slide Preparation of Caenorhabditis elegans toward Quantitative, High-Resolution LA-ICP-TOF Mass Spectrometry Imaging.
Аннотация
Metal homeostasis is essential for biological functions and has been implicated in many diseases. Laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS) imaging is a powerful tool for spatially resolved elemental imaging in heterogeneous tissues. The nematode Caenorhabditis elegans (C. elegans) is a well-established model organism for metal biology research. However, there have been few reports on mass spectrometry-based metal imaging of C. elegans due to challenges in sample preparation for high-resolution and quantitative analysis. In this study, we established an integrated workflow consisting of sample preparation, imaging, and quantitative analysis for whole-animal elemental imaging of C. elegans by LA-ICP-TOF-MS. With the assistance of 3D-printed uniform layer media application tools (ULMATs), water-based and hydrocarbon-based embedding media were evaluated, and petrolatum, commercially known as Vaseline, stood out for its performance in preserving C. elegans over time for LA-ICP-TOF-MS imaging. Worms were subjected to microscopy and LA-ICP-TOF-MS imaging where we achieved a 2-μm spatial resolution by oversampling laser shots during ablation. Quantitative elemental maps were obtained using gelatin standards sectioned at a 40-μm thickness to closely mimic the average tissue ablation depth of a day 1 adult C. elegans. This work established a comprehensive LA-ICP-TOF-MS imaging workflow for model organism C. elegans and addressed key analytical bottlenecks associated with sample handling, tissue preservation, spatial resolution, and quantitation in whole-organism elemental imaging of C. elegans. The methodology expands the analytical capabilities of LA-ICP-TOF-MS imaging for microscale biological systems and provides an adaptable workflow for future spatial metal biology research using C. elegans and other similar model systems.
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Обработка статьи · этапы, ошибки и управление
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История · было → стало
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