title: Extension of least squares spectral resolution algorithm to high-resolution lipidomics data.
abstract: Lipidomics, which focuses on the global study of molecular lipids in biological systems, has been driven tremendously by technical advances in mass spectrometry (MS) instrumentation, particularly high-resolution MS. This requires powerful computational tools that handle the high-throughput lipidomics data analysis. To address this issue, a novel computational tool has been developed for the analysis of high-resolution MS data, including the data pretreatment, visualization, automated identification, deconvolution and quantification of lipid species. The algorithm features the customized generation of a lipid compound library and mass spectral library, which covers the major lipid classes such as glycerolipids, glycerophospholipids and sphingolipids. Next, the algorithm performs least squares resolution of spectra and chromatograms based on the theoretical isotope distribution of molecular ions, which enables automated identification and quantification of molecular lipid species. Currently, this methodology supports analysis of both high and low resolution MS as well as liquid chromatography-MS (LC-MS) lipidomics data. The flexibility of the methodology allows it to be expanded to support more lipid classes and more data interpretation functions, making it a promising tool in lipidomic data analysis.
authors.affiliation: Department of Chemistry, University of Bergen, PO Box 7803, N-5020 Bergen, Norway.
authors.forename: Ying-Xu
authors.initials: YX
authors.lastname: Zeng
authors.affiliation: Department of Chemistry, University of Bergen, PO Box 7803, N-5020 Bergen, Norway. Electronic address: svein.mjos@kj.uib.no.
authors.forename: Svein Are
authors.initials: SA
authors.lastname: Mjøs
authors.affiliation: Bioinformatics and Biostatistics Core Facility, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL) and Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: Fabrice P A
authors.initials: FP
authors.lastname: David
authors.affiliation: Proteomics Core Facility, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
authors.forename: Adrien W
authors.initials: AW
authors.lastname: Schmid
mesh_terms: D000465:Algorithms; D002853:Chromatography, Liquid; D016018:Least-Squares Analysis; D008055:Lipids / Q000737:chemistry*; D053719:Tandem Mass Spectrometry
chemical_list: D008055:Lipids
keywords: Algorithm; High-resolution mass spectrometry; Least squares spectral resolution; Lipid; Lipidomics; Liquid chromatography-mass spectrometry