{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Furse S"],"funding":["Akademie Věd České Republiky","Medical Research Council","Natural Environment Research Council","Biotechnology and Biological Sciences Research Council"],"pagination":["570-583"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11381968"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["20(9)"],"pubmed_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 <i>Bombus "],"journal":["Molecular omics"],"pubmed_title":["Systemic analysis of lipid metabolism from individuals to multi-organism systems."],"pmcid":["PMC11381968"],"funding_grant_id":["BB/R003556/1","RVO 67985939","BB/T014210/1","BB/T015292/1","MC_UU_00014/4","NE/V012282/1"],"pubmed_authors":["Chiarugi D","Koulman A","Vidal-Puig A","Prescott TAK","Chennells J","Stabler D","Watkins AJ","Baker E","Virtue S","Willer DF","Scott J","Snowden SG","Martel C","Fernandez-Twinn DS","Wright GA","Stevenson PC","Moncur J","Ozanne SE","Patterson-Cross R","Kite GC","Vitova M","Furse S"],"additional_accession":[]},"is_claimable":false,"name":"Systemic analysis of lipid metabolism from individuals to multi-organism systems.","description":"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 <i>Bombus ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Oct","modification":"2026-07-15T17:49:15.183Z","creation":"2025-04-04T02:59:15.58Z"},"accession":"S-EPMC11381968","cross_references":{"pubmed":["39246063"],"doi":["10.1039/d4mo00083h"]}}