Systemic analysis of lipid metabolism from individuals to multi-organism systems.

IF 3 4区生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY

Molecular omics Pub Date : 2024-09-09 DOI:10.1039/d4mo00083h

Samuel Furse, Carlos Martel, David F Willer, Daniel Stabler, Denise S Fernandez-Twinn, Jennifer Scott, Ryan Patterson-Cross, Adam J Watkins, Samuel Virtue, Thomas A K Prescott, Ellen Baker, Jennifer Chennells, Antonio Vidal-Puig, Susan E Ozanne, Geoffrey C Kite, Milada Vítová, Davide Chiarugi, John Moncur, Albert Koulman, Geraldine A Wright, Stuart G Snowden, Philip C Stevenson

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引用次数: 0

Abstract

Lipid metabolism is recognised as being central to growth, disease and health. Lipids, therefore, have an important place in current research on globally significant topics such as food security and biodiversity loss. However, answering questions in these important fields of research requires not only identification and measurement of lipids in a wider variety of sample types than ever before, but also hypothesis-driven analysis of the resulting 'big data'. We present a novel pipeline that can collect data from a wide range of biological sample types, taking 1 000 000 lipid measurements per 384 well plate, and analyse the data systemically. We provide evidence of the power of the tool through proof-of-principle studies using edible fish (mackerel, bream, seabass) and colonies of Bombus terrestris. Bee colonies were found to be more like mini-ecosystems and there was evidence for considerable changes in lipid metabolism in bees through key developmental stages. This is the first report of either high throughput LCMS lipidomics or systemic analysis in individuals, colonies and ecosystems. This novel approach provides new opportunities to analyse metabolic systems at different scales at a level of detail not previously feasible, to answer research questions about societally important topics.

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从个体到多机体系统的脂质代谢系统分析。

脂质代谢被认为是生长、疾病和健康的核心。因此，脂质在当前有关粮食安全和生物多样性丧失等全球重大课题的研究中占有重要地位。然而，要回答这些重要研究领域的问题，不仅需要在比以往更多的样本类型中识别和测量脂质，还需要对由此产生的 "大数据 "进行假设驱动分析。我们介绍了一种新型管道，它可以从多种生物样本类型中收集数据，每 384 孔板可测量 1 000 000 个脂质，并对数据进行系统分析。我们通过使用食用鱼（鲭鱼、鳊鱼、鲈鱼）和蜂群进行原理验证研究，证明了该工具的强大功能。研究发现，蜂群更像是一个小型生态系统，有证据表明，蜜蜂在关键发育阶段的脂质代谢发生了很大变化。这是首次报道高通量 LCMS 脂质组学或个体、蜂群和生态系统的系统分析。这种新方法提供了新的机会，可以在不同尺度上分析代谢系统，其详细程度是以前无法做到的，从而回答有关社会重要课题的研究问题。

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来源期刊

Molecular omics Biochemistry, Genetics and Molecular Biology-Biochemistry

CiteScore

5.40

自引率

3.40%

发文量

期刊介绍： Molecular Omics publishes high-quality research from across the -omics sciences. Topics include, but are not limited to: -omics studies to gain mechanistic insight into biological processes – for example, determining the mode of action of a drug or the basis of a particular phenotype, such as drought tolerance -omics studies for clinical applications with validation, such as finding biomarkers for diagnostics or potential new drug targets -omics studies looking at the sub-cellular make-up of cells – for example, the subcellular localisation of certain proteins or post-translational modifications or new imaging techniques -studies presenting new methods and tools to support omics studies, including new spectroscopic/chromatographic techniques, chip-based/array technologies and new classification/data analysis techniques. New methods should be proven and demonstrate an advance in the field. Molecular Omics only accepts articles of high importance and interest that provide significant new insight into important chemical or biological problems. This could be fundamental research that significantly increases understanding or research that demonstrates clear functional benefits. Papers reporting new results that could be routinely predicted, do not show a significant improvement over known research, or are of interest only to the specialist in the area are not suitable for publication in Molecular Omics.