Furse, Samuel, Martel, Carlos, Willer, David F., Stabler, Daniel, Fernandez-Twinn, Denise S., Scott, Jennifer, Patterson-Cross, Ryan, Watkins, Adam J., Virtue, Samuel, Prescott, Thomas A. K., Baker, Ellen, Chennels, Jennifer, Vidal-Puig, Antonio, Ozanne, Susan E., Kite, Geoffrey C., Vítová, Milada, Chiarugi, Davide, Moncur, John, Koulman, Albert, Wright, Geraldine A., Snowden, Stuart G. and Stevenson, Philip C. ORCID: 0000-0002-0736-3619 (2024) Systemic analysis of lipid metabolism from individuals to multi-organism systems. Molecular Omics. ISSN 2515-4184 (Online) (doi:https://doi.org/10.1039/D4MO00083H)

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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.

Item Type:	Article
Uncontrolled Keywords:	lipidomics, lipid isolation, high throughput, traffic analysis, network analysis, LCMS
Subjects:	Q Science > Q Science (General) S Agriculture > S Agriculture (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Natural Resources Institute Faculty of Engineering & Science > Natural Resources Institute > Centre for Sustainable Agriculture 4 One Health Faculty of Engineering & Science > Natural Resources Institute > Centre for Sustainable Agriculture 4 One Health > Chemical Ecology & Plant Biochemistry
Last Modified:	04 Oct 2024 14:39
URI:	http://gala.gre.ac.uk/id/eprint/47843

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