Issue 9, 2024

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

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.

Graphical abstract: Systemic analysis of lipid metabolism from individuals to multi-organism systems

Supplementary files

Article information

Article type
Research Article
Submitted
14 May 2024
Accepted
30 Aug 2024
First published
09 Sep 2024
This article is Open Access
Creative Commons BY license

Mol. Omics, 2024,20, 570-583

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

S. Furse, C. Martel, D. F. Willer, D. Stabler, D. S. Fernandez-Twinn, J. Scott, R. Patterson-Cross, A. J. Watkins, S. Virtue, T. A. K. Prescott, E. Baker, J. Chennells, A. Vidal-Puig, S. E. Ozanne, G. C. Kite, M. Vítová, D. Chiarugi, J. Moncur, A. Koulman, G. A. Wright, S. G. Snowden and P. C. Stevenson, Mol. Omics, 2024, 20, 570 DOI: 10.1039/D4MO00083H

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