Abstract
Mass spectrometry raw data repositories, including Metabolomics Workbench and MetaboLights, have contributed to increased transparency in metabolomics studies and the discovery of novel insights in biology by reanalysis with updated computational metabolomics tools. Herein, we reanalyzed the previously published lipidomics data from nine algal species, resulting in the annotation of 1437 lipids achieving a 40% increase in annotation compared to the previous results. Specifically, diacylglyceryl-carboxyhydroxy-methylcholine (DGCC) in Pavlova lutheri and Pleurochrysis carterae, glucuronosyldiacylglycerol (GlcADG) in Euglena gracilis, and P. carterae, phosphatidylmethanol (PMeOH) in E. gracilis, and several oxidized phospholipids (oxidized phosphatidylcholine, OxPC; phosphatidylethanolamine, OxPE; phosphatidylglycerol, OxPG; phosphatidylinositol, OxPI) in Chlorella variabilis were newly characterized with the enriched lipid spectral databases. Moreover, we integrated the data from untargeted and targeted analyses from data independent tandem mass spectrometry (DIA-MS/MS) acquisition, specifically the sequential window acquisition of all theoretical fragment-ion MS/MS (SWATH-MS/MS) spectra, to increase the lipidomic annotation coverage. After the creation of a global library of precursor and diagnostic ions of lipids by the MS-DIAL untargeted analysis, the co-eluted DIA-MS/MS spectra were resolved in MRMPROBS targeted analysis by tracing the specific product ions involved in acyl chain compositions. Our results indicated that the metabolite quantifications based on DIA-MS/MS chromatograms were somewhat inferior to the MS1-centric quantifications, while the annotation coverage outperformed those of the untargeted analysis of the data dependent and DIA-MS/MS data. Consequently, integrated analyses of untargeted and targeted approaches are necessary to extract the maximum amount of metabolome information, and our results showcase the value of data repositories for the discovery of novel insights in lipid biology.
Highlights
Many studies using mass spectrometry (MS)-based untargeted metabolomics have provided novel insights in biology, and the importance of metabolomics data repositories has been recognized [1]
Since the specificity of lipid metabolism is highly influenced by genetics, evolution, and the environment of living organisms, increasing lipidomics coverage is an emerging requirement in biology
The reanalysis of published data was demonstrated where 17 lipid classes were newly characterized in nine algal species in addition to the 15 lipid classes annotated previously
Summary
Many studies using mass spectrometry (MS)-based untargeted metabolomics have provided novel insights in biology, and the importance of metabolomics data repositories has been recognized [1]. MS repositories aim to (A) increase the transparency and reproducibility of MS-centric metabolomics studies, (B) provide a benchmark for testing new analytical and computational methodologies, (C) share the results of metabolome analyses for providing opportunities for data-driven hypothesis generation, and (D) reanalyze published data with continuous identification efforts to obtain novel insights and discover novel metabolites. Few studies have demonstrated the value of MS repositories except for the first purpose. Case studies showing remarkable results toward the other three purposes would facilitate data sharing by researchers and academic journals [5].
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