Mandic Sara, Flinders Bryn, Vandenbosch Michiel, Ohta Akane, Kuhara Atsushi, Heeren Ron M A, Fujiwara Masazumi
Department of Chemistry, Graduate School of Life, Environmental, Natural Science and Technology, Okayama University, Okayama, 700-8530, Japan.
Maastricht MultiModal Molecular Imaging Institute (M4i), Division of Imaging Mass Spectrometry, Maastricht University, 6229 ER, Maastricht, The Netherlands.
Sci Rep. 2025 Jul 8;15(1):24548. doi: 10.1038/s41598-025-09577-9.
Caenorhabditis elegans (C. elegans) is an important model organism for studying fat storage and lipid metabolism. Mass-spectrometry imaging (MSI) is an emerging technology for mapping the spatial distribution of lipids. However, MSI analysis of C. elegans is limited by the lack of reproducible sample preparation methods. Here, we present a microfluidics-based workflow for preparing consecutive nematode sections while retaining their internal structures, such as the pharynx, intestine, and embryos. This method enables multimodal analysis of single nematodes by MSI and Oil Red O staining, revealing a number of lipids spatially distributed across different body parts. The feature-based image reconstruction technique enables the three-dimensional reconstruction of nematodes based on optical images and MSI-based lipid mapping. The present method can correlate MSI data with various imaging modalities to provide detailed correlations between anatomical features and lipid distribution in nematodes.
秀丽隐杆线虫(C. elegans)是研究脂肪储存和脂质代谢的重要模式生物。质谱成像(MSI)是一种用于绘制脂质空间分布的新兴技术。然而,秀丽隐杆线虫的MSI分析受到缺乏可重复的样品制备方法的限制。在此,我们提出了一种基于微流控的工作流程,用于制备连续的线虫切片,同时保留其内部结构,如咽部、肠道和胚胎。该方法能够通过MSI和油红O染色对单个线虫进行多模态分析,揭示了许多在不同身体部位空间分布的脂质。基于特征的图像重建技术能够基于光学图像和基于MSI的脂质图谱对线虫进行三维重建。本方法可以将MSI数据与各种成像模态相关联,以提供线虫解剖特征与脂质分布之间的详细关联。