4.6 Article

Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library

Journal

JOURNAL OF CHEMINFORMATICS
Volume 9, Issue -, Pages -

Publisher

BIOMED CENTRAL LTD
DOI: 10.1186/s13321-017-0205-3

Keywords

In silico MS/MS; Retention time prediction; Mass fragmentation; Lipids

Funding

  1. Database Integration Coordination Program of the National Bioscience Database Center
  2. JSPS KAKENHI [15H05897, 15H05898, 15H04648, 15K01812]
  3. Science and Technology Research Promotion Program for Agriculture, Forestry, Fisheries and Food Industry
  4. JST-Core Research for Evolutionary Science and Technology (JST-CREST)
  5. Japan Agency for Medical Research and Development (AMED-PRIME)
  6. Grants-in-Aid for Scientific Research [15H05898, 15K01812, 15H05897, 15H04648] Funding Source: KAKEN

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Background: Liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) is used for comprehensive metabolome and lipidome analyses. Compound identification relies on similarity matching of the retention time (RT), precursor m/z, isotopic ratio, and MS/MS spectrum with reference compounds. For sphingolipids, however, little information on the RT and MS/MS references is available. Results: Negative-ion ESI-MS/MS is a useful method for the structural characterization of sphingolipids. We created theoretical MS/MS spectra for 21 sphingolipid classes in human and mouse (109,448 molecules), with substructure-level annotation of unique fragment ions by MS-FINDER software. The existence of ceramides with beta-hydroxy fatty acids was confirmed in mouse tissues based on cheminformatic- and quantum chemical evidences. The RT of sphingo- and glycerolipid species was also predicted for our LC condition. With this information, MS-DIAL software for untargeted metabolome profiling could identify 415 unique structures including 282 glycerolipids and 133 sphingolipids from human cells (HEK and HeLa) and mouse tissues (ear and liver). Conclusions: MS-DIAL and MS-FINDER software programs can identify 42 lipid classes (21 sphingo- and 21 glycerolipids) with the in silico RT and MS/MS library. The library is freely available as Microsoft Excel files at the software section of our RIKEN PRIMe website (http://prime.psc.riken.jp/).

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