Cargando…
Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library
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 spectr...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5352698/ https://www.ncbi.nlm.nih.gov/pubmed/28316657 http://dx.doi.org/10.1186/s13321-017-0205-3 |
_version_ | 1782514996382531584 |
---|---|
author | Tsugawa, Hiroshi Ikeda, Kazutaka Tanaka, Wataru Senoo, Yuya Arita, Makoto Arita, Masanori |
author_facet | Tsugawa, Hiroshi Ikeda, Kazutaka Tanaka, Wataru Senoo, Yuya Arita, Makoto Arita, Masanori |
author_sort | Tsugawa, Hiroshi |
collection | PubMed |
description | 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 β-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/). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-017-0205-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5352698 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-53526982017-03-17 Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library Tsugawa, Hiroshi Ikeda, Kazutaka Tanaka, Wataru Senoo, Yuya Arita, Makoto Arita, Masanori J Cheminform Research Article 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 β-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/). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-017-0205-3) contains supplementary material, which is available to authorized users. Springer International Publishing 2017-03-15 /pmc/articles/PMC5352698/ /pubmed/28316657 http://dx.doi.org/10.1186/s13321-017-0205-3 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Tsugawa, Hiroshi Ikeda, Kazutaka Tanaka, Wataru Senoo, Yuya Arita, Makoto Arita, Masanori Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library |
title | Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library |
title_full | Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library |
title_fullStr | Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library |
title_full_unstemmed | Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library |
title_short | Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library |
title_sort | comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5352698/ https://www.ncbi.nlm.nih.gov/pubmed/28316657 http://dx.doi.org/10.1186/s13321-017-0205-3 |
work_keys_str_mv | AT tsugawahiroshi comprehensiveidentificationofsphingolipidspeciesbyinsilicoretentiontimeandtandemmassspectrallibrary AT ikedakazutaka comprehensiveidentificationofsphingolipidspeciesbyinsilicoretentiontimeandtandemmassspectrallibrary AT tanakawataru comprehensiveidentificationofsphingolipidspeciesbyinsilicoretentiontimeandtandemmassspectrallibrary AT senooyuya comprehensiveidentificationofsphingolipidspeciesbyinsilicoretentiontimeandtandemmassspectrallibrary AT aritamakoto comprehensiveidentificationofsphingolipidspeciesbyinsilicoretentiontimeandtandemmassspectrallibrary AT aritamasanori comprehensiveidentificationofsphingolipidspeciesbyinsilicoretentiontimeandtandemmassspectrallibrary |