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LipidBlast in silico tandem mass spectrometry database for lipid identification

Nature Methods volume 10, pages 755–758 (2013)Cite this article

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Abstract

Current tandem mass spectral libraries for lipid annotations in metabolomics are limited in size and diversity. We provide a freely available computer-generated tandem mass spectral library of 212,516 spectra covering 119,200 compounds from 26 lipid compound classes, including phospholipids, glycerolipids, bacterial lipoglycans and plant glycolipids. We show platform independence by using tandem mass spectra from 40 different mass spectrometer types including low-resolution and high-resolution instruments.

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Figure 1: Creation, validation and application of in silico–generated tandem mass spectra in LipidBlast.
Figure 2: Platform independence of LipidBlast.

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Acknowledgements

We thank the Lipid MAPS consortium and the US National Institute of General Medical Sciences for providing extensive lipid identification and database services; the NIST Mass Spectrometry group for providing the freely available NIST MS Search GUI program and for help with the Lib2NIST converter; ModLab (Universität Frankfurt am Main) for providing the free SMILIB enumeration tool; and ChemAxon for a free research license for the Marvin and Instant-JChem cheminformatics tools. K.-H.L. was supported by the National Research Foundation of Korea, Ministry of Education, Science and Technology (grant 2010-0021368), the Korea Healthcare Technology R&D Project, Ministry of Health and Welfare (grant A103017) and the Cooperative Research Program for Agriculture Science and Technology Development (project PJ00948604), Rural Development Administration, Republic of Korea. T.K. and O.F. were supported by the US National Science Foundation (MCB 1139644) and US National Institutes of Health (P20 HL113452 and U24 DK097154).

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Authors and Affiliations

  1. Metabolics Core, UC Davis Genome Center, University of California, Davis, Davis, California, USA

    Tobias Kind, Kwang-Hyeon Liu, Do Yup Lee, Brian DeFelice, John K Meissen & Oliver Fiehn

  2. College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea

    Kwang-Hyeon Liu

  3. Department of Advanced Fermentation Fusion Science and Technology, Kookmin University, Seoul, Republic of Korea

    Do Yup Lee

Authors
  1. Tobias Kind
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  2. Kwang-Hyeon Liu
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  4. Brian DeFelice
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  5. John K Meissen
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  6. Oliver Fiehn
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Contributions

T.K., K.-H.L., D.Y.L. and O.F. designed the experiments. T.K., K.-H.L., B.D., J.K.M. and D.Y.L. performed mass spectrometric experiments. T.K. and K.-H.L. performed mass spectral fragmentation analysis and compound annotations. T.K. created the compound structures and developed the in silico MS/MS libraries and wrote and validated the algorithm. T.K. and O.F. wrote the manuscript in interaction with all contributing authors.

Corresponding authors

Correspondence to Tobias Kind or Oliver Fiehn.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Figure and Note

Supplementary Figure 1–5 and Supplementary Note 1 (PDF 10817 kb)

Supplementary Table 1

Detailed statistics of the LipidBlast MS/MS libraries with detailed lipid compound numbers (XLS 97 kb)

Supplementary Table 2

Complete table of mass spectrometry platforms that can be used with the LipidBlast libraries (XLS 112 kb)

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Kind, T., Liu, KH., Lee, D. et al. LipidBlast in silico tandem mass spectrometry database for lipid identification. Nat Methods 10, 755–758 (2013). https://doi.org/10.1038/nmeth.2551

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