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LC-MS Lipidomics: Exploiting a Simple High-Throughput Method for the Comprehensive Extraction of Lipids in a Ruminant Fat Dose-Response Study.

Accepted version
Peer-reviewed

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Type

Article

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Authors

Ronis, Martin 

Abstract

Typical lipidomics methods incorporate a liquid-liquid extraction with LC-MS quantitation; however, the classic sample extraction methods are not high-throughput and do not perform well at extracting the full range of lipids especially, the relatively polar species (e.g., acyl-carnitines and glycosphingolipids). In this manuscript, we present a novel sample extraction protocol, which produces a single phase supernatant suitable for high-throughput applications that offers greater performance in extracting lipids across the full spectrum of species. We applied this lipidomics pipeline to a ruminant fat dose-response study to initially compare and validate the different extraction protocols but also to investigate complex lipid biomarkers of ruminant fat intake (adjoining onto simple odd chain fatty acid correlations). We have found 100 lipids species with a strong correlation with ruminant fat intake. This novel sample extraction along with the LC-MS pipeline have shown to be sensitive, robust and hugely informative (>450 lipids species semi-quantified): with a sample preparation throughput of over 100 tissue samples per day and an estimated ~1000 biological fluid samples per day. Thus, this work facilitating both the epidemiological involvement of ruminant fat, research into odd chain lipids and also streamlining the field of lipidomics (both by sample preparation methods and data presentation).

Description

Keywords

Folch, lipid profiling, odd chain lipids, protein precipitation, relative lipid composition (Mol%), sample preparation

Journal Title

Metabolites

Conference Name

Journal ISSN

2218-1989
2218-1989

Volume Title

10

Publisher

MDPI AG

Rights

All rights reserved
Sponsorship
Biotechnology and Biological Sciences Research Council (BB/M027252/2)
Biotechnology and Biological Sciences Research Council (BB/M027252/1)
MRC (MC_UU_00014/5)
BBSRC, grant number BB/M027252/1