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Computational mass spectrometry for metabolomics: Identification of metabolites and small molecules
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  • Published: 09 October 2010

Computational mass spectrometry for metabolomics: Identification of metabolites and small molecules

  • Steffen Neumann1 &
  • Sebastian Böcker2 

Analytical and Bioanalytical Chemistry volume 398, pages 2779–2788 (2010)Cite this article

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Abstract

The identification of compounds from mass spectrometry (MS) data is still seen as a major bottleneck in the interpretation of MS data. This is particularly the case for the identification of small compounds such as metabolites, where until recently little progress has been made. Here we review the available approaches to annotation and identification of chemical compounds based on electrospray ionization (ESI-MS) data. The methods are not limited to metabolomics applications, but are applicable to any small compounds amenable to MS analysis. Starting with the definition of identification, we focus on the analysis of tandem mass and MSn spectra, which can provide a wealth of structural information. Searching in libraries of reference spectra provides the most reliable source of identification, especially if measured on comparable instruments. We review several choices for the distance functions. The identification without reference spectra is even more challenging, because it requires approaches to interpret tandem mass spectra with regard to the molecular structure. Both commercial and free tools are capable of mining general-purpose compound libraries, and identifying candidate compounds. The holy grail of computational mass spectrometry is the de novo deduction of structure hypotheses for compounds, where method development has only started thus far. In a case study, we apply several of the available methods to the three compounds, kaempferol, reserpine, and verapamil, and investigate whether this results in reliable identifications.

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References

  1. Zhang J, Gonzalez E, Hestilow T, Haskins W, Huang Y (2009) Review of peak detection algorithms in liquid-chromatography-mass spectrometry. Curr Genomics 10(6):388–401

    Article  CAS  Google Scholar 

  2. America AHP, Cordewener JHG (2008) Comparative LC-MS: a landscape of peaks and valleys. Proteomics 8(4):731–749

    Article  CAS  Google Scholar 

  3. Lange E, Tautenhahn R, Neumann S, Gröpl C (2008) Critical assessment of alignment procedures for LC-MS proteomics and metabolomics measurements. BMC Bioinformatics 9:375+

    Article  Google Scholar 

  4. Vandenbogaert M, Li-Thiao-Té S, Kaltenbach H-M, Zhang R, Aittokallio T, Schwikowski B (2008) Alignment of LC-MS images, with applications to biomarker discovery and protein identification. Proteomics 8(4):650–672

    Article  CAS  Google Scholar 

  5. Meija J (2006) Mathematical tools in analytical mass spectrometry. Anal Bioanal Chem 385(3):486–499

    Article  CAS  Google Scholar 

  6. Iijima Y, Nakamura Y, Ogata Y, Tanaka K, Sakurai N, Suda K, Suzuki T, Suzuki H, Okazaki K, Kitayama M, Kanaya S, Aoki K, Shibata D (2008) Metabolite annotations based on the integration of mass spectral information. Plant J 54(5):949–962

    Article  CAS  Google Scholar 

  7. Böttcher C, von Roepenack-Lahaye E, Schmidt J, Schmotz C, Neumann S, Scheel D, Clemens S (2008) Metabolome analysis of biosynthetic mutants reveals a diversity of metabolic changes and allows identification of a large number of new compounds in arabidopsis. Plant Physiol 147(4):2107–2120

    Article  Google Scholar 

  8. Glauser G, Guillarme D, Grata E, Boccard J, Thiocone A, Carrupt P-A, Veuthey J-L, Rudaz S, Wolfender JL (2008) Optimized liquid chromatography-mass spectrometry approach for the isolation of minor stress biomarkers in plant extracts and their identification by capillary nuclear magnetic resonance. J Chromatogr A 1180(1–2):90–98

    Article  CAS  Google Scholar 

  9. Sumner LW, Amberg A, Barrett D, Beale M, Beger R, Daykin C, Fan T, Fiehn O, Goodacre R, Griffin JL, Hankemeier T, Hardy N, Harnly J, Higashi R, Kopka J, Lane A, Lindon JC, Marriott P, Nicholls A, Reily M, Thaden J, Viant MR (2007) Proposed minimum reporting standards for chemical analysis. Metabolomics 3(3):211–221

    Article  CAS  Google Scholar 

  10. Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, Cheng D, Jewell K, Arndt D, Sawhney S, Fung C, Nikolai L, Lewis M, Coutouly M-A, Forsythe I, Tang P, Shrivastava S, Jeroncic K, Stothard P, Amegbey G, Block D, Hau DD, Wagner J, Miniaci J, Clements M, Gebremedhin M, Guo N, Zhang Y, Duggan GE, MacInnis GD, Weljie AM, Dowlatabadi R, Bamforth F, Clive D, Greiner R, Li L, Marrie T, Sykes BD, Vogel HJ, Querengesser L (2007) HMDB: the human metabolome database. Nucleic Acids Res 35(suppl 1):D521–D526

    Article  CAS  Google Scholar 

  11. Böcker S, Letzel M, Lipták ZS, Pervukhin A (2009) STRTUS: decomposing isotope patterns for metabolite identification. Bioinformatics 25(2):218–224

    Article  Google Scholar 

  12. Kind T, Fiehn O (2006) Metabolomic database annotations via query of elemental compositions: mass accuracy is insufficient even at less than 1 ppm. BMC Bioinformatics 7(1):234

    Article  Google Scholar 

  13. Bristow T, Constantine J, Harrison M, Cavoit F (2008) Performance optimisation of a new-generation orthogonal-acceleration quadrupole-time-of-flight mass spectrometer. Rapid Commun Mass Spectrom 22(8):1213–1222

    Article  CAS  Google Scholar 

  14. Laures AM-F, Wolff J-C, Eckers C, Borman PJ, Chatfield MJ (2007) Investigation into the factors affecting accuracy of mass measurements on a time-of-flight mass spectrometer using Design of Experiment. Rapid Commun Mass Spectrom 21(4):529–535

    Article  CAS  Google Scholar 

  15. Xu Y, Heilier J-F, Madalinski G, Genin E, Ezan E, Tabet J-C, Junot C (2010) Evaluation of accurate mass and relative isotopic abundance measurements in the LTQ-Orbitrap mass spectrometer for further metabolomics database building. Anal Chem 82(13):5490–5501. doi:10.1021/ac100271j

    Article  CAS  Google Scholar 

  16. Miura D, Tsuji Y, Takahashi K, Wariishi H, Saito K (2010) A strategy for the determination of the elemental composition by Fourier transform ion cyclotron resonance mass spectrometry based on isotopic peak ratios. Anal Chem 82(13):5887–5891

    Article  CAS  Google Scholar 

  17. Matsuda F, Shinbo Y, Oikawa A, Hirai MY, Fiehn O, Kanaya S, Saito K (2009) Assessment of metabolome annotation quality: a method for evaluating the false discovery rate of elemental composition searches. PLoS ONE 4(10):e7490

    Article  Google Scholar 

  18. Matsuda F, Yonekura-Sakakibara K, Niida R, Kuromori T, Shinozaki K, Saito K (2009) MS/MS spectral tag-based annotation of non-targeted profile of plant secondary metabolites. Plant J 57(3):555–577

    Article  CAS  Google Scholar 

  19. Matsuda F, Hirai MY, Sasaki E, Akiyama K, Yonekura-Sakakibara K, Provart NJ, Sakurai T, Shimada Y, Saito K (2010) AtMetExpress development: a phytochemical atlas of Arabidopsis development. Plant Physiol 152(2):566–578

    Article  CAS  Google Scholar 

  20. Plumb RS, Johnson KA, Rainville P, Smith BW, Wilson ID, Castro-Perez JM, Nicholson JK (2006) UPLC/MS(E); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid Commun Mass Spectrom 20(13):1989–1994

    Article  CAS  Google Scholar 

  21. Ipsen A, Want EJ, Lindon JC, Ebbels TMD (2010) A statistically rigorous test for the identification of parent-fragment pairs in LC-MS datasets. Anal Chem 82(5):1766–1778

    Article  CAS  Google Scholar 

  22. Tautenhahn R, Böttcher C, Neumann S (2007) Annotation of LC/ESI-MS mass signals. In: Hochreichter S, Wagner R (eds) Bioinformatics research and development (BIRD 2007). Lecture notes in computer science, vol 4414. Springer, Heidelberg, pp 371–380

  23. Borland L, Brickhouse M, Thomas T, Fountain AW (2010) Review of chemical signature databases. Anal Bioanal Chem 397(3):1019–1028

    Article  CAS  Google Scholar 

  24. Gower JC, Legendre P (1986) Metric and Euclidean properties of dissimilarity coefficients. J Classif 3(1):5–48

    Article  Google Scholar 

  25. Stein SE (1994) Estimating probabilities of correct identification from results of mass spectral library searches. J Am Soc Mass Spectrom 5(4):316–323

    Article  CAS  Google Scholar 

  26. Horai H, Arita M, Kanaya S, Nihei Y, Ikeda T, Suwa K, Ojima Y, Tanaka K, Tanaka S, Aoshima K, Oda Y, Kakazu Y, Kusano M, Tohge T, Matsuda F, Sawada Y, Nakanishi H, Ikeda K, Akimoto N, Maoka T, Takahashi H, Ara T, Shibata D, Neumann S, Iida T, Tanaka K, Funatsu K, Matsuura F, Soga T, Taguchi R, Saito K, Nishioka T (2010) MassBank: a public repository for sharing mass spectral data for life sciences. J Mass Spectrom 45:703–714

    Article  CAS  Google Scholar 

  27. Dworzanski JP, Snyder AP, Chen R, Zhang H, Wishart D, Li L (2004) Identification of bacteria using tandem mass spectrometry combined with a proteome database and statistical scoring. Anal Chem 76(8):2355–2366

    Article  CAS  Google Scholar 

  28. Pavlic M, Libiseller K, Oberacher H (2006) Combined use of ESI-QqTOF-MS and ESI-QqTOF-MS/MS with mass-spectral library search for qualitative analysis of drugs. Anal Bioanal Chem 386(1):69–82

    Article  CAS  Google Scholar 

  29. Oberacher H, Pavlic M, Libiseller K, Schubert B, Sulyok M, Schuhmacher R, Csaszar E, Köfeler HC (2009) On the inter-instrument and the inter-laboratory transferability of a tandem mass spectral reference library: 2. Optimization and characterization of the search algorithm. J Mass Spectrom 44(4):494–502

    Article  CAS  Google Scholar 

  30. Mylonas R, Mauron Y, Masselot A, Binz P-A, Budin N, Fathi M, Viette V, Hochstrasser DF, Lisacek F (2009) X-Rank: a robust algorithm for small molecule identification using tandem mass spectrometry. Anal Chem 81(18):7604–7610

    Article  CAS  Google Scholar 

  31. Smith CA, Maille GO, Want EJ, Qin C, Trauger SA, Brandon TR, Custodio DE, Abagyan R, Siuzdak G (2005) METLIN: a metabolite mass spectral database. In: Proceedings of the 9th international congress of therapeutic drug monitoring and clinical toxicology, Louisville, Kentucky, vol 27, pp 747–751

  32. Reemtsma T (2009) Determination of molecular formulas of natural organic matter molecules by (ultra-) high-resolution mass spectrometry: status and needs. J Chromatogr A 1216(18):3687–3701

    Article  CAS  Google Scholar 

  33. Mohamed R, Varesio E, Ivosev G, Burton L, Bon-ner R, Hopfgartner G (2009) Comprehensive analytical strategy for biomarker identification based on liquid chromatography coupled to mass spectrometry and new candidate confirmation tools. Anal Chem 81(18):7677–7694

    Article  CAS  Google Scholar 

  34. Böcker S, Rasche F (2008) Towards de novo identification of metabolites by analyzing tandem mass spectra. Bioinformatics 24:T49–T55, Proc. of European Conference on Computational Biology (ECCB 2008)

    Article  Google Scholar 

  35. Advanced Chemistry Development, Inc (2010) ACD/MS Fragmenter. http://www.acdlabs.com/products/adh/ms/ms_frag/

  36. Pelander A, Tyrkkö E, Ojanperä I (2009) In silico methods for predicting metabolism and mass fragmentation applied to quetiapine in liquid chromatography/time-of-flight mass spectrometry urine drug screening. Rapid Commun Mass Spectrom 23(4):506–514

    Article  CAS  Google Scholar 

  37. Tyrkkö E, Pelander A, Ojanperä I (2010) Differentiation of structural isomers in a target drug database by LC/Q-TOFMS using fragmentation prediction. Drug Test Anal 2(6):259–270

    Article  Google Scholar 

  38. Highchem, Ltd (2010) Mass Frontier. http://www.highchem.com/massfrontier/mass-frontier.html

  39. Horai H, Arita M, Ojima Y, Nihei Y, Kanaya S, Nishioka T (2009) Traceable analysis of multiple-stage mass spectra through precursor-product annotations. In: Grosse I, Neumann S, Posch S, Schreiber F, Stadler PF (eds) GCB. Lecture notes in informatics (GI), vol 157, pp 173–178

  40. Heinonen M, Rantanen A, Mielikäinen T, Kokkonen J, Kiuru J, Ketola RA, Rousu J (2008) FiD: a software for ab initio structural identification of product ions from tandem mass spectrometric data. Rapid Commun Mass Spectrom 22(19):3043–3052

    Article  CAS  Google Scholar 

  41. Hill AW, Mortishire-Smith RJ (2005) Automated assignment of high-resolution collisionally activated dissociation mass spectra using a systematic bond disconnection approach. Rapid Commun Mass Spectrom 19(21):3111–3118

    Article  CAS  Google Scholar 

  42. Heinonen M, Rantanen A, Mielikäinen T, Pitkänen E, Kokkonen J, Rousu J (2006) Ab initio prediction of molecular fragments from tandem mass spectrometry data. In: Proceedings of the German conference on bioinformatics (GCB 2006). Lecture notes in informatics, pp 40–53

  43. Böcker S, Rasche F, Steijger T (2009) Annotating fragmentation patterns. In: Proceedings of the workshop on algorithms in bioinformatics (WABI 2009). Lecture notes in computer science, vol 5724. Springer, Heidelberg, pp 13–24

  44. Hill DW, Kertesz TM, Fontaine D, Friedman R, Grant DF (2008) Mass spectral metabonomics beyond elemental formula: chemical database querying by matching experimental with computational fragmentation spectra. Anal Chem 80(14):5574–5582

    Article  CAS  Google Scholar 

  45. Wolf S, Schmidt S, Müller-Hannemann M, Neumann S (2010) In silico fragmentation for computer assisted identification of metabolite mass spectra. BMC Bioinformatics 11(1):148

    Article  Google Scholar 

  46. Levsen K, Schiebel H-M, Terlouw JK, Jobst KJ, Elend M, Preiss A, Thiele H, Ingendoh A (2007) Even-electron ions: a systematic study of the neutral species lost in the dissociation of quasi-molecular ions. J Mass Spectrom 42(8):1024–1044

    Article  CAS  Google Scholar 

  47. Alex A, Harvey S, Parsons T, Pullen FS, Wright P, Riley J-A (2009) Can density functional theory (DFT) be used as an aid to a deeper understanding of tandem mass spectrometric fragmentation pathways? Rapid Commun Mass Spectrom 23(17):2619–2627

    Article  CAS  Google Scholar 

  48. Wright P, Alex A, Nyaruwata T, Parsons T, Pullen F (2010) Using density functional theory to rationalise the mass spectral fragmentation of maraviroc and its metabolites. Rapid Commun Mass Spectrom 24(7):1025–1031

    Article  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, 06120, Halle, Germany

    Steffen Neumann

  2. Department of Mathematics and Computer Science, Friedrich-Schiller-University, Jena, 07743, Jena, Germany

    Sebastian Böcker

Authors
  1. Steffen Neumann
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  2. Sebastian Böcker
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Corresponding author

Correspondence to Steffen Neumann.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Online Resource 1

Molecular structures and details used for the identification case studies (PDF 890 kb)

Online Resource 2

Computational mass spectrometry for metabolomics: focus on the identification of metabolites and small molecules (TXT 11.2 kb)

Online Resource 3

Results of the FiD software (PDF 482 kb)

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Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

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Cite this article

Neumann, S., Böcker, S. Computational mass spectrometry for metabolomics: Identification of metabolites and small molecules. Anal Bioanal Chem 398, 2779–2788 (2010). https://doi.org/10.1007/s00216-010-4142-5

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  • Received: 14 June 2010

  • Revised: 16 August 2010

  • Accepted: 18 August 2010

  • Published: 09 October 2010

  • Issue Date: December 2010

  • DOI: https://doi.org/10.1007/s00216-010-4142-5

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Keywords

  • Mass spectrometry
  • Metabolomics
  • Compound identification
  • Spectral library
  • Structure elucidation
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