Quantitative lipidomics for three-dimensional cell culture using deuterium oxide metabolic labeling

IF 5.6 1区化学 Q1 CHEMISTRY, ANALYTICAL

Talanta Pub Date : 2025-07-21 DOI:10.1016/j.talanta.2025.128612

Jonghyun Kim , Kyoung-Jin Choi , Sung Bum Park , Yoon-Ju Na , Ki Young Kim , Tae-Young Kim

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Abstract

Three-dimensional (3D) cell culture offers a more physiologically relevant model than traditional two-dimensional culture, yet standardized methods for lipid quantification in 3D systems are lacking. This study presents a novel quantitative lipidomic approach combining 3D culture with deuterium oxide (D₂O) metabolic labeling to provide comprehensive insights into metabolic alterations. Using a hydrogel-based 3D system, we cultured preadipocytes and adipocytes, incorporating macrophage co-culture to induce insulin resistance. Relative lipid quantification was achieved using D₂O labeling for global omics relative quantification (DOLGOReQ). This method enabled the quantification of hundreds of lipids across major categories, including glycerolipids, glycerophospholipids, fatty acyls, and sphingolipids, while also revealing cell-type-specific D-labeling efficiencies. DOLGOReQ analysis revealed that macrophage co-culture significantly reduced long-chain free fatty acids and triacylglycerols (TGs). Quantitative correlation analysis between TGs and free fatty acids indicated that the macrophage-mediated TG reduction stemmed from decreased free fatty acid availability, the precursors for lipid synthesis. Furthermore, macrophages increased D-labeling efficiency, suggesting enhanced lipolysis contributing to TG reduction. DOLGOReQ not only facilitates relative quantification of lipid changes but also provides valuable insights into lipid turnover dynamics. These findings establish DOLGOReQ as a powerful tool for investigating global lipid metabolism changes induced by external stimuli in 3D cell culture.

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使用氧化氘代谢标记的三维细胞培养定量脂质组学

三维（3D）细胞培养提供了一个比传统的二维培养更生理学相关的模型，然而在三维系统中缺乏标准化的脂质定量方法。本研究提出了一种新的定量脂质组学方法，将3D培养与氧化氘（D2O）代谢标记相结合，为代谢改变提供全面的见解。采用基于水凝胶的3D系统，我们培养了前脂肪细胞和脂肪细胞，并结合巨噬细胞共培养诱导胰岛素抵抗。使用D2O标记进行全球组学相对定量（DOLGOReQ）来实现相对脂质定量。该方法能够对主要类别的数百种脂质进行定量，包括甘油脂、甘油磷脂、脂肪酰基和鞘脂，同时也揭示了细胞类型特异性d标记效率。DOLGOReQ分析显示，巨噬细胞共培养显著减少了长链游离脂肪酸和三酰甘油（TGs）。TG与游离脂肪酸之间的定量相关性分析表明，巨噬细胞介导的TG降低源于游离脂肪酸可用性的降低，游离脂肪酸是脂质合成的前体。此外，巨噬细胞提高了d标记效率，表明脂肪分解增强有助于TG降低。DOLGOReQ不仅促进了脂质变化的相对量化，而且为脂质周转动力学提供了有价值的见解。这些发现表明DOLGOReQ是研究3D细胞培养中外部刺激引起的整体脂质代谢变化的有力工具。

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来源期刊

Talanta 化学-分析化学

CiteScore

12.30

自引率

4.90%

发文量

861

审稿时长

29 days

期刊介绍： Talanta provides a forum for the publication of original research papers, short communications, and critical reviews in all branches of pure and applied analytical chemistry. Papers are evaluated based on established guidelines, including the fundamental nature of the study, scientific novelty, substantial improvement or advantage over existing technology or methods, and demonstrated analytical applicability. Original research papers on fundamental studies, and on novel sensor and instrumentation developments, are encouraged. Novel or improved applications in areas such as clinical and biological chemistry, environmental analysis, geochemistry, materials science and engineering, and analytical platforms for omics development are welcome. Analytical performance of methods should be determined, including interference and matrix effects, and methods should be validated by comparison with a standard method, or analysis of a certified reference material. Simple spiking recoveries may not be sufficient. The developed method should especially comprise information on selectivity, sensitivity, detection limits, accuracy, and reliability. However, applying official validation or robustness studies to a routine method or technique does not necessarily constitute novelty. Proper statistical treatment of the data should be provided. Relevant literature should be cited, including related publications by the authors, and authors should discuss how their proposed methodology compares with previously reported methods.