Metabolomics

, Volume 9, Supplement 1, pp 4–29 | Cite as

Flow infusion electrospray ionisation mass spectrometry for high throughput, non-targeted metabolite fingerprinting: a review

  • John Draper
  • Amanda J. Lloyd
  • Royston Goodacre
  • Manfred Beckmann
Original Article

Abstract

Producing a comprehensive overview of the chemical content of biologically-derived material is a major challenge. Apart from ensuring adequate metabolome coverage and issues of instrument dynamic range, mass resolution and sensitivity, there are major technical difficulties associated with data pre-processing and signal identification when attempting large scale, high-throughput experimentation. To address these factors direct infusion or flow infusion electrospray mass spectrometry has been finding utility as a high throughput metabolite fingerprinting tool. With little sample pre-treatment, no chromatography and instrument cycle times of less than 5 min it is feasible to analyse more than 1,000 samples per week. Data pre-processing is limited to aligning extracted mass spectra and mass-intensity matrices are generally ready in a working day for a month’s worth of data mining and hypothesis generation. ESI-MS fingerprinting has remained rather qualitative by nature and as such ion suppression does not generally compromise data information content as originally suggested when the methodology was first introduced. This review will describe how the quality of data has improved through use of nano-flow infusion and mass-windowing approaches, particularly when using high resolution instruments. The increasingly wider availability of robust high accurate mass instruments actually promotes ESI-MS from a merely fingerprinting tool to the ranks of metabolite profiling and combined with MS/MS capabilities of hybrid instruments improved structural information is available concurrently. We summarise current applications in a wide range of fields where ESI-MS fingerprinting has proved to be an excellent tool for “first pass” metabolome analysis of complex biological samples. The final part of the review describes a typical workflow with reference to recently published data to emphasise key aspects of overall experimental design.

Keywords

Mass spectrometry Flow infusion electrospray ionisation Metabolomics 

Abbreviations

amu

Atomic mass unit

Da

Dalton

MS

Mass spectrometry

m/z

Mass-to-charge ratio

DIMS

Direct infusion MS

FIE-MS

Flow injection electrospray-ionisation MS

Q-TOF

Quadrupole-time-of-flight

FT-ICR-MS

Fourier transform ion cyclotron resonance MS

7 T

7 Tesla, strength of magnet

LC

Liquid chromatography

UHPLC

Ultra high pressure/performance liquid chromatography

GC

Gas chromatography

SIM

Single ion monitoring

DF

Discriminant function

LDA

Linear discriminant analysis

PCA

Principal components analysis

AUC

Area under the receiver/operator curve

QC

Quality control

MEDE

Metabolomics to characterize dietary exposure (FSA-funded project)

MZedDB

Database: tools for the annotation of high resolution MS metabolomics data

References

  1. Aharoni, A., De Vos, C. H. R., Verhoeven, H. A., et al. (2002). Nontargeted metabolome analysis by use of Fourier transform ion cyclotron mass spectrometry. OMICS: A Journal of Integrative Biology, 6, 217–234.CrossRefGoogle Scholar
  2. Allen, J., Davey, H. M., Broadhurst, D., et al. (2003). High-throughput classification of yeast mutants for functional genomics using metabolic footprinting. Nature Biotechnology, 21, 692–696.PubMedCrossRefGoogle Scholar
  3. Allen, J., Davey, H. M., Broadhurst, D., et al. (2004). Discrimination of modes of action of antifungal substances by use of metabolic footprinting. Applied and Environmental Microbiology, 70, 6157–6165.PubMedCrossRefGoogle Scholar
  4. Allwood, J. W., Ellis, D. I., Heald, J. K., Goodacre, R., & Mur, L. A. J. (2006). Metabolomic approaches reveal that phosphatidic and phosphatidyl glycerol phospholipids are major discriminatory non-polar metabolites in responses by Brachypodium distachyon to challenge by Magnaporthe grisea. Plant Journal, 46, 351–368.PubMedCrossRefGoogle Scholar
  5. Alves, J. D. O., Neto, W. B., Mitsutake, H., Alves, P. S. P., & Augusti, R. (2010). Extra virgin (EV) and ordinary (ON) olive oils: Distinction and detection of adulteration (EV with ON) as determined by direct infusion electrospray ionization mass spectrometry and chemometric approaches. Rapid Communications in Mass Spectrometry: RCM, 24, 1875–1880.PubMedCrossRefGoogle Scholar
  6. Annesley, T. M. (2003). Ion suppression in mass spectrometry. Clinical Chemistry, 49, 1041–1044.PubMedCrossRefGoogle Scholar
  7. Antignac, J. P., De Wasch, K., Monteau, F., et al. (2005). The ion suppression phenomenon in liquid chromatography-mass spectrometry and its consequences in the field of residue. Analytica Chimica Acta, 529, 129–136.CrossRefGoogle Scholar
  8. Antunes, L. C. M., Andersen, S. K., Menendez, A., et al. (2011a). Metabolomics reveals phospholipids as important nutrient sources during salmonella growth in bile in vitro and in vivo. Journal of Bacteriology, 193, 4719–4725.PubMedCrossRefGoogle Scholar
  9. Antunes, L. C. M., Arena, E. T., Menendez, A., et al. (2011b). Impact of Salmonella infection on host hormone metabolism revealed by metabolomics. Infection and Immunity, 79, 1759–1769.PubMedCrossRefGoogle Scholar
  10. Baigorri, R., Mari Zamarreno, A., Fuentes, M., et al. (2008). Multivariate statistical analysis of mass spectra as a tool for the classification of the main humic substances according to their structural and conformational features. Journal of Agricultural and Food Chemistry, 56, 5480–5487.PubMedCrossRefGoogle Scholar
  11. Beckmann, M., Enot, D. P., Overy, D. P., & Draper, J. (2007). Representation, comparison, and interpretation of metabolome fingerprint data for total composition analysis and quality trait investigation in potato cultivars. Journal of Agricultural and Food Chemistry, 55, 3444–3451.PubMedCrossRefGoogle Scholar
  12. Beckmann, M., Parker, D., Enot, D. P., Duval, E., & Draper, J. (2008). High-throughput, nontargeted metabolite fingerprinting using nominal mass flow injection electrospray mass spectrometry. Nature Protocols, 3, 486–504.PubMedCrossRefGoogle Scholar
  13. Beckmann, M., Enot, D. P., Overy, D. P., et al. (2010). Metabolite fingerprinting of urine suggests breed-specific dietary metabolism differences in domestic dogs. British Journal of Nutrition, 103, 1127–1138.PubMedGoogle Scholar
  14. Bino, R. J., Hall, R. D., Fiehn, O., et al. (2004). Potential of metabolomics as a functional genomics tool. Trends in Plant Science, 9, 418–425.PubMedCrossRefGoogle Scholar
  15. Boernsen, K. O., Gatzek, S., & Imbert, G. (2005). Controlled protein precipitation in combination with chip-based nanospray infusion mass spectrometry. An approach for metabolomics profiling of plasma. Analytical Chemistry, 77, 7255–7264.PubMedCrossRefGoogle Scholar
  16. Bradford, B. U., O’connell, T. M., Han, J., et al. (2008). Metabolomic profiling of a modified alcohol liquid diet model for liver injury in the mouse uncovers new markers of disease. Toxicology and Applied Pharmacology, 232, 236–243.PubMedCrossRefGoogle Scholar
  17. Breiman, L. (2001). Random forests. Machine Learning, 45, 5–32.CrossRefGoogle Scholar
  18. Broadhurst, D. I., & Kell, D. B. (2006). Statistical strategies for avoiding false discoveries in metabolomics and related experiments. Metabolomics, 2, 171–196.CrossRefGoogle Scholar
  19. Brown, S. C., Kruppa, G., & Dasseux, J. L. (2005). Metabolomics applications of FT-ICR mass spectrometry. Mass Spectrometry Reviews, 24, 223–231.PubMedCrossRefGoogle Scholar
  20. Brown, M., Dunn, W. B., Dobson, P., et al. (2009). Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics. Analyst, 134, 1322–1332.PubMedCrossRefGoogle Scholar
  21. Brown, M., Wedge, D. C., Goodacre, R., et al. (2011). Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets. Bioinformatics, 27, 1108–1112.PubMedCrossRefGoogle Scholar
  22. Castrillo, J. I., Hayes, A., Mohammed, S., Gaskell, S. J., & Oliver, S. G. (2003). An optimized protocol for metabolome analysis in yeast using direct infusion electrospray mass spectrometry. Phytochemistry, 62, 929–937.PubMedCrossRefGoogle Scholar
  23. Catchpole, G. S., Beckmann, M., Enot, D. P., et al. (2005). Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proceedings of the National academy of Sciences of the United States of America, 102, 14458–14462.PubMedCrossRefGoogle Scholar
  24. Catharino, R. R., Milagre, H. M. S., Saraiva, S. A., et al. (2007). Biodiesel typification and quality control by direct infusion electrospray ionization mass spectrometry fingerprinting. Energy & Fuels, 21, 3698–3701.CrossRefGoogle Scholar
  25. Chen, H., Wortmann, A., & Zenobi, R. (2007). Neutral desorption sampling coupled to extractive electrospray ionization mass spectrometry for rapid differentiation of biosamples by metabolomic fingerprinting. Journal of Mass Spectrometry, 42, 1123–1135.PubMedCrossRefGoogle Scholar
  26. Chen, H.-W., Hu, B., & Zhang, X. (2010a). Fundamental principles and practical applications of ambient ionization mass spectrometry for direct analysis of complex samples. Chinese Journal of Analytical Chemistry, 38, 1069–1088.CrossRefGoogle Scholar
  27. Chen, P., Harnly, J. M., & Lester, G. E. (2010b). Flow injection mass spectral fingerprints demonstrate chemical differences in rio red grapefruit with respect to year, harvest time, and conventional versus organic farming. Journal of Agricultural and Food Chemistry, 58, 4545–4553.PubMedCrossRefGoogle Scholar
  28. Chen, P., Lin, L.-Z., & Harnly, J. M. (2010c). Mass spectroscopic fingerprinting method for differentiation between Scutellaria lateriflora and the Germander (Teucrium canadense and T. chamaedrys) species. Journal of AOAC International, 93, 1148–1154.PubMedGoogle Scholar
  29. Cooper, H. J., & Marshall, A. G. (2001). Electrospray ionization Fourier transform mass spectrometric analysis of wine. Journal of Agricultural and Food Chemistry, 49, 5710–5718.PubMedCrossRefGoogle Scholar
  30. Davey, M. P., Burrell, M. M., Woodward, F. I., & Quick, W. P. (2008). Population-specific metabolic phenotypes of Arabidopsis lyrata ssp. petraea. New Phytologist, 177, 380–388.PubMedGoogle Scholar
  31. De Vos, R. C. H., Moco, S., Lommen, A., et al. (2007). Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nature Protocols, 2, 778–791.PubMedCrossRefGoogle Scholar
  32. Dettmer, K., Aronov, P. A., & Hammock, B. D. (2007). Mass spectrometry-based metabolomics. Mass Spectrometry Reviews, 26, 51–78.PubMedCrossRefGoogle Scholar
  33. Dittmar, T., & Koch, B. P. (2006). Thermogenic organic matter dissolved in the abyssal ocean. Marine Chemistry, 102, 208–217.CrossRefGoogle Scholar
  34. Draper, J., Enot, D. P., Parker, D., et al. (2009). Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour ‘rules’. BMC Bioinformatics, 10, 227.PubMedCrossRefGoogle Scholar
  35. Dunn, W. B. (2008). Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes. Physical Biology, 5, 011001.PubMedCrossRefGoogle Scholar
  36. Dunn, W. B., Bailey, N. J. C., & Johnson, H. E. (2005a). Measuring the metabolome: Current analytical technologies. Analyst, 130, 606–625.PubMedCrossRefGoogle Scholar
  37. Dunn, W. B., Overy, S., & Quick, W. P. (2005b). Evaluation of automated electrospray-TOF mass spectrometryfor metabolic fingerprinting of the plant metabolome. Metabolomics, 1, 137–148.CrossRefGoogle Scholar
  38. Dunn, W. B., Broadhurst, D., Brown, M., et al. (2008). Metabolic profiling of serum using ultra performance liquid chromatography and the LTQ-orbitrap mass spectrometry system. Journal of Chromatography B-Analytical Technologies in the Biomedical and Life Sciences, 871, 288–298.CrossRefGoogle Scholar
  39. Dunn, W. B., Broadhurst, D., Begley, P., et al. (2011). Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nature Protocols, 6, 1060–1083.PubMedCrossRefGoogle Scholar
  40. Enot, D. P., & Draper, J. (2007). Statistical measures for validating plant genotype similarity assessments following multivariate analysis of metabolome fingerprint data. Metabolomics, 3, 349–355.CrossRefGoogle Scholar
  41. Enot, D. P., Beckmann, M., Overy, D., & Draper, J. (2006). Predicting interpretability of metabolome models based on behavior, putative identity, and biological relevance of explanatory signals. Proceedings of the National academy of Sciences of the United States of America, 103, 14865–14870.PubMedCrossRefGoogle Scholar
  42. Enot, D. P., Beckmann, M., & Draper, J. (2007). Detecting a difference—assessing generalisability when modelling metabolome fingerprint data in longer term studies of genetically modified plants. Metabolomics, 3, 335–347.CrossRefGoogle Scholar
  43. Enot, D. P., Lin, W., Beckmann, M., et al. (2008). Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data. Nature Protocols, 3, 446–470.PubMedCrossRefGoogle Scholar
  44. Fard, A. M., Turner, A. G., & Willett, G. D. (2003). High-resolution electrospray-ionization Fourier-transform ion cyclotron resonance and gas chromatography-mass spectrometry of macadamia nut oil. Australian Journal of Chemistry, 56, 499–508.Google Scholar
  45. Favé, G., Beckmann, M., Lloyd, A., et al. (2011). Development and validation of a standardized protocol to monitor human dietary exposure by metabolite fingerprinting of urine samples. Metabolomics, 7, 1–16.CrossRefGoogle Scholar
  46. Favretto, D., & Flamini, R. (2000). Application of electrospray ionization mass spectrometry to the study of grape anthocyanins. American Journal of Enology and Viticulture, 51, 55–64.Google Scholar
  47. Favretto, D., Piovan, A., Filippini, R., & Caniato, R. (2001). Monitoring the production yields of vincristine and vinblastine in Catharanthus roseus from somatic embryogenesis. Semiquantitative determination by flow-injection electrospray ionization mass spectrometry. Rapid Communications in Mass Spectrometry, 15, 364–369.PubMedCrossRefGoogle Scholar
  48. Fiehn, O. (2002). Metabolomics—the link between genotypes and phenotypes. Plant Molecular Biology, 48, 155–171.PubMedCrossRefGoogle Scholar
  49. Fuhrer, T., Heer, D., Begemann, B., & Zamboni, N. (2011). High-throughput, accurate mass metabolome profiling of cellular extracts by flow injection-time-of-flight mass spectrometry. Analytical Chemistry, 83, 7074–7080.PubMedCrossRefGoogle Scholar
  50. Furuya, T., Nishi, T., Shibata, D., et al. (2008). Characterization of orphan monooxygenases by rapid substrate screening using FT-ICR mass spectrometry. Chemistry & Biology, 15, 563–572.CrossRefGoogle Scholar
  51. Giavalisco, P., Hummel, J., Lisec, J., et al. (2008). High-resolution direct infusion-based mass spectrometry in combination with whole (13)C metabolome isotope labeling allows unambiguous assignment of chemical sum formulas. Analytical Chemistry, 80, 9417–9425.PubMedCrossRefGoogle Scholar
  52. Giavalisco, P., Koehl, K., Hummel, J., Seiwert, B., & Willmitzer, L. (2009). (13)C Isotope-labeled metabolomes allowing for improved compound annotation and relative quantification in liquid chromatography-mass spectrometry-based metabolomic research. Analytical Chemistry, 81, 6546–6551.PubMedCrossRefGoogle Scholar
  53. Goodacre, R., Heald, J. K., & Kell, D. B. (1999). Characterisation of intact microorganisms using electrospray ionisation mass spectrometry. FEMS Microbiology Letters, 176, 17–24.CrossRefGoogle Scholar
  54. Goodacre, R., Vaidyanathan, S., Bianchi, G., & Kell, D. B. (2002). Metabolic profiling using direct infusion electrospray ionisation mass spectrometry for the characterisation of olive oils. Analyst, 127, 1457–1462.PubMedCrossRefGoogle Scholar
  55. Goodacre, R., York, E. V., Heald, J. K., & Scott, I. M. (2003). Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry. Phytochemistry, 62, 859–863.PubMedCrossRefGoogle Scholar
  56. Goodacre, R., Broadhurst, D., Smilde, A., Kristal, B. S., Baker, J. D., Beger, R., et al. (2007). Proposed minimum reporting standards for data analysis in metabolomics. Metabolomics, 3, 231–241.CrossRefGoogle Scholar
  57. Gorlach, E., & Richmond, R. (1999). Discovery of quasi-molecular ions in electrospray spectra by automated searching for simultaneous adduct mass differences. Analytical Chemistry, 71, 5557–5562.CrossRefGoogle Scholar
  58. Gougeon, R. D., Lucio, M., Frommberger, M., et al. (2009). The chemodiversity of wines can reveal a metabologeography expression of cooperage oak wood. Proceedings of the National academy of Sciences of the United States of America, 106, 9174–9179.PubMedCrossRefGoogle Scholar
  59. Grata, E., Boccard, J., Glauser, G., et al. (2007). Development of a two-step screening ESI-TOF-MS method for rapid determination of significant stress-induced metabolome modifications in plant leaf extracts: The wound response in Arabidopsis thaliana as a case study. Journal of Separation Science, 30, 2268–2278.PubMedCrossRefGoogle Scholar
  60. Gray, G. R., & Heath, D. (2005). A global reorganization of the metabolome in Arabidopsis during cold acclimation is revealed by metabolic fingerprinting. Physiologia Plantarum, 124, 236–248.CrossRefGoogle Scholar
  61. Gross, J. H. (2004). Mass spectrometry: A textbook. Heidelberg: Springer.Google Scholar
  62. Gu, H., Hu, B., Li, J., et al. (2010). Rapid analysis of aerosol drugs using nano extractive electrospray ionization tandem mass spectrometry. Analyst, 135, 1259–1267.PubMedCrossRefGoogle Scholar
  63. Guilhaus, M., Mlynski, V., & Selby, D. (1997). Perfect timing: Time-of-flight mass spectrometry. Rapid Communications in Mass Spectrometry, 11, 951–962.CrossRefGoogle Scholar
  64. Hall, R., Beale, M., Fiehn, O., Hardy, N., Sumner, L., & Bino, R. (2002). Plant metabolomics: The missing link in functional genomics strategies. The Plant Cell, 14, 1437–1440.PubMedCrossRefGoogle Scholar
  65. Han, J., Danell, R. M., Patel, J. R., et al. (2008a). Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry. Metabolomics, 4, 128–140.PubMedCrossRefGoogle Scholar
  66. Han, X., Yang, K., & Gross, R. W. (2008b). Microfluidics-based electrospray ionization enhances the intrasource separation of lipid classes and extends identification of individual molecular species through multi-dimensional mass spectrometry: Development of an automated high-throughput platform for shotgun lipidomics. Rapid Communications in Mass Spectrometry, 22, 2115–2124.PubMedCrossRefGoogle Scholar
  67. Hasegawa, M., Takenaka, S., Kuwamura, M., Yamate, J., & Tsuyama, S. (2007). Urinary metabolic fingerprinting for amiodarone-induced phospholipidosis in rats using FT-ICR MS. Experimental and Toxicologic Pathology, 59, 115–120.PubMedCrossRefGoogle Scholar
  68. Hasegawa, M., Ide, M., Kuwamura, M., Yamate, J., & Takenaka, S. (2010). Metabolic fingerprinting in toxicological assessment using FT-ICR MS. Journal of Toxicologic Pathology, 23, 67–74.PubMedCrossRefGoogle Scholar
  69. Helm, R. F., Jervis, J., Ray, W. K., Willoughby, N., Irvin, B., Hastie, J., et al. (2010). Mass spectral analyses of corn stover prehydrolysates to assess conditioning processes. Agricultural and Food Chemistry, 58, 12642–12649.CrossRefGoogle Scholar
  70. Higgs, R. E., Zahn, J. A., Gygi, J. D., & Hilton, M. D. (2001). Rapid method to estimate the presence of secondary metabolites in microbial extracts. Applied and Environmental Microbiology, 67, 371–376.PubMedCrossRefGoogle Scholar
  71. Hirai, M. Y., Yano, M., Goodenowe, D. B., et al. (2004). Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana. Proceedings of the National academy of Sciences of the United States of America, 101, 10205–10210.PubMedCrossRefGoogle Scholar
  72. Hojer-Pedersen, J., Smedsgaard, J., & Nielsen, J. (2008). The yeast metabolome addressed by electrospray ionization mass spectrometry: Initiation of a mass spectral library and its applications for metabolic footprinting by direct infusion mass spectrometry. Metabolomics, 4, 393–405.CrossRefGoogle Scholar
  73. Hrydziuszko, O., Silva, M. A., Perera, M. T. P. R., et al. (2010). Application of metabolomics to investigate the process of human orthotopic liver transplantation: A proof-of-principle study. OMICS: A Journal of Integrative Biology, 14, 143–150.CrossRefGoogle Scholar
  74. Hu, B., So, P.-K., Chen, H., & Yao, Z.-P. (2011). Electrospray ionization using wooden tips. Analytical Chemistry, 83, 8201–8207.PubMedCrossRefGoogle Scholar
  75. Iijima, Y., Nakamura, Y., Ogata, Y., et al. (2008). Metabolite annotations based on the integration of mass spectral information. Plant Journal, 54, 949–962.PubMedCrossRefGoogle Scholar
  76. Jansson, J., Willing, B., Lucio, M., et al. (2009). Metabolomics reveals metabolic biomarkers of Crohn’s disease. PLoS One, 4, e6386.PubMedCrossRefGoogle Scholar
  77. Johnson, H. E., Lloyd, A. J., Mur, L. A. J., Smith, A. R., & Causton, D. R. (2007). The application of MANOVA to analyse Arabidopsis thaliana metabolomic data from factorially designed experiments. Metabolomics, 3, 517–530.CrossRefGoogle Scholar
  78. Junot, C., Madalinski, G., Tabet, J. C., & Ezan, E. (2010). Fourier transform mass spectrometry for metabolome analysis. Analyst, 135, 2203–2219.PubMedCrossRefGoogle Scholar
  79. Kaderbhai, N. N., Broadhurst, D. I., Ellis, D. I., Goodacre, R., & Kell, D. B. (2003). Functional genomics via metabolic footprinting: Monitoring metabolite secretion by Escherichia coli tryptophan metabolism mutants using FT-IR and direct injection electrospray mass spectrometry. Comparative and Functional Genomics, 4, 376–391.PubMedCrossRefGoogle Scholar
  80. Kai, K., Hashidzume, H., Yoshimura, K., et al. (2009). Metabolomics for the characterization of cytochromes P450-dependent fatty acid hydroxylation reactions in Arabidopsis. Plant Biotechnology, 26, 175–182.CrossRefGoogle Scholar
  81. Kim, S., Kaplan, L. A., & Hatcher, P. G. (2006). Biodegradable dissolved organic matter in a temperate and a tropical stream determined from ultra-high resolution mass spectrometry. Limnology and Oceanography, 51, 1054–1063.CrossRefGoogle Scholar
  82. 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, 234.PubMedCrossRefGoogle Scholar
  83. Kind, T., & Fiehn, O. (2007). Seven golden rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC Bioinformatics, 8, 105.PubMedCrossRefGoogle Scholar
  84. Kind, T., & Fiehn, O. (2010). Advances in structure elucidation of small molecules using mass spectrometry. Bioanalytical Reviews, 2, 23–60.PubMedCrossRefGoogle Scholar
  85. King, R., Bonfiglio, R., Fernandez-Metzler, C., Miller-Stein, C., & Olah, T. (2000). Mechanistic investigation of ionization suppression in electrospray ionization. Journal of the American Society for Mass Spectrometry, 11, 942–950.PubMedCrossRefGoogle Scholar
  86. Koch, B. P., Witt, M. R., Engbrodt, R., Dittmar, T., & Kattner, G. (2005). Molecular formulae of marine and terrigenous dissolved organic matter detected by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Geochimica et Cosmochimica Acta, 69, 3299–3308.CrossRefGoogle Scholar
  87. Koek, M. M., Jellema, R. H., Van Der Greef, J., Tas, A. C., & Hankemeier, T. (2011). Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives. Metabolomics, 7, 307–328.PubMedCrossRefGoogle Scholar
  88. Koulman, A., Tapper, B. A., Fraser, K., et al. (2007). High-throughput direct-infusion ion trap mass spectrometry: A new method for metabolomics. Rapid Communications in Mass Spectrometry, 21, 421–428.PubMedCrossRefGoogle Scholar
  89. Koulman, A., Woffendin, G., Narayana, V. K., et al. (2009). High-resolution extracted ion chromatography, a new tool for metabolomics and lipidomics using a second-generation orbitrap mass spectrometer. Rapid Communications in Mass Spectrometry, 23, 1411–1418.PubMedCrossRefGoogle Scholar
  90. Kuhl, C., Tautenhahn, R., Boettcher, C., Larson, T. R., & Neumann, S. (2012). CAMERA: An integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets. Analytical Chemistry, 84, 283–289.PubMedCrossRefGoogle Scholar
  91. Kujawinski, E. B., Del Vecchio, R., Blough, N. V., Klein, G. C., & Marshall, A. G. (2004). Probing molecular-level transformations of dissolved organic matter: Insights on photochemical degradation and protozoan modification of DOM from electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Marine Chemistry, 92, 23–37.CrossRefGoogle Scholar
  92. Lafaye, A., Labarre, J., Tabet, J. C., Ezan, E., & Junot, C. (2005). Liquid chromatography-mass spectrometry and N-15 metabolic labeling for quantitative metabolic profiling. Analytical Chemistry, 77, 2026–2033.PubMedCrossRefGoogle Scholar
  93. Li, M., Hu, B., Li, J., et al. (2009). Extractive electrospray ionization mass spectrometry toward in situ analysis without sample pretreatment. Analytical Chemistry, 81, 7724–7731.PubMedCrossRefGoogle Scholar
  94. Liger-Belair, G., Cilindre, C., Gougeon, R. D., et al. (2009). Unraveling different chemical fingerprints between a champagne wine and its aerosols. Proceedings of the National academy of Sciences of the United States of America, 106, 16545–16549.PubMedCrossRefGoogle Scholar
  95. Lin, L., Yu, Q., Yan, X., et al. (2010). Direct infusion mass spectrometry or liquid chromatography mass spectrometry for human metabonomics? A serum metabonomic study of kidney cancer. Analyst, 135, 2970–2978.PubMedCrossRefGoogle Scholar
  96. Lisec, J., Schauer, N., Kopka, J., Willmitzer, L., & Fernie, A. R. (2006). Gas chromatography mass spectrometry-based metabolite profiling in plants. Nature Protocols, 1, 387–396.PubMedCrossRefGoogle Scholar
  97. Liu, G., Ji, Q. C., & Arnold, M. E. (2010). Identifying, evaluating, and controlling bioanalytical risks resulting from nonuniform matrix ion suppression/enhancement and nonlinear liquid chromatography-mass spectrometry assay response. Analytical Chemistry, 82, 9671–9677.PubMedCrossRefGoogle Scholar
  98. Liu, J., Wang, H., Cooks, R. G., & Ouyang, Z. (2011). Leaf spray: Direct chemical analysis of plant material and living plants by mass spectrometry. Analytical Chemistry, 83, 7608–7613.PubMedCrossRefGoogle Scholar
  99. Lloyd, A. J., Allwood, J. W., Winder, C. L., et al. (2011a). Metabolomic approaches reveal that cell wall modifications play a major role in ethylene-mediated resistance against Botrytis cinerea. Plant Journal, 67, 852–868.PubMedCrossRefGoogle Scholar
  100. Lloyd, A. J., Beckmann, M., Favé, G., Mathers, J. C., & Draper, J. (2011b). Proline betaine and its biotransformation products are potential biomarkers of habitual citrus fruit consumption in fasting urine samples. British Journal of Nutrition, 106, 812–824.PubMedCrossRefGoogle Scholar
  101. Lloyd, A. J., Favé, G., Beckmann, M., et al. (2011c). Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods. American Journal of Clinical Nutrition, 94, 981–991.PubMedCrossRefGoogle Scholar
  102. Lokhov, P. G., Kharybin, O. N., & Archakov, A. I. (2012). Diagnosis of lung cancer based on direct-infusion electrospray mass spectrometry of blood plasma metabolites. International Journal of Mass Spectrometry, 309, 200–205.Google Scholar
  103. Lowe, R. G. T., Allwood, J. W., Galster, A. M., et al. (2010). A combined (1)H nuclear magnetic resonance and electrospray ionization mass spectrometry analysis to understand the basal metabolism of plant-pathogenic fusarium spp. Molecular Plant-Microbe Interactions, 23, 1605–1618.PubMedCrossRefGoogle Scholar
  104. Lucio, M., Fekete, A., Weigert, C., et al. (2010). Insulin sensitivity is reflected by characteristic metabolic fingerprints—a Fourier transform mass spectrometric non-targeted metabolomics approach. PLoS One, 5, e13317.PubMedCrossRefGoogle Scholar
  105. Luthria, D. L., Lin, L.-Z., Robbins, R. J., et al. (2008). Discriminating between cultivars and treatments of broccoli using mass spectral fingerprinting and analysis of variance-principal component analysis. Journal of Agricultural and Food Chemistry, 56, 9819–9827.PubMedCrossRefGoogle Scholar
  106. Lyons-Weiler, J., Pelikan, R., Zeh, H. J., et al. (2005). Assessing the statistical significance of the achieved classification error of classifiers constructed using serum peptide profiles, and a prescription for random sampling repeated studies for massive high-throughput genomic and proteomic studies. Cancer Informatics, 1, 53–77.PubMedGoogle Scholar
  107. Madalinski, G., Godat, E., Alves, S., et al. (2008). Direct introduction of biological samples into a LTQ-Orbitrap hybrid mass spectrometer as a tool for fast metabolome analysis. Analytical Chemistry, 80, 3291–3303.PubMedCrossRefGoogle Scholar
  108. March, R. E. (1997). An introduction to quadrupole ion trap mass spectrometry. Journal of Mass Spectrometry, 32, 351–369.CrossRefGoogle Scholar
  109. Marshall, A. G., & Hendrickson, C. L. (2008). High-resolution mass spectrometers. Annual Review of Analytical Chemistry, 1, 579–599.PubMedCrossRefGoogle Scholar
  110. Mas, S., Villas-Boas, S. G., Hansen, M. E., Akesson, M., & Nielsen, J. (2007). A comparison of direct infusion MS and GC-MS for metabolic footprinting of yeast mutants. Biotechnology and Bioengineering, 96, 1014–1022.PubMedCrossRefGoogle Scholar
  111. Mattoli, L., Cangi, F., Ghiara, C., et al. (2011). A metabolite fingerprinting for the characterization of commercial botanical dietary supplements. Metabolomics, 7, 437–445.CrossRefGoogle Scholar
  112. Mauri, P., & Pietta, P. (2000a). Electrospray characterization of selected medicinal plant extracts. Journal of Pharmaceutical and Biomedical Analysis, 23, 61–68.PubMedCrossRefGoogle Scholar
  113. Mauri, P., & Pietta, P. (2000b). High performance liquid chromatography/electrospray mass spectrometry of Hypericum perforatum extracts. Rapid Communications in Mass Spectrometry, 14, 95–99.PubMedCrossRefGoogle Scholar
  114. Mauri, P., Migliazza, B., & Pietta, P. (1999). Liquid chromatography/electrospray mass spectrometry of bioactive terpenoids in Ginkgo biloba L. Journal of Mass Spectrometry, 34, 1361–1367.PubMedCrossRefGoogle Scholar
  115. McDougall, G., Martinussen, I., & Stewart, D. (2008). Towards fruitful metabolomics: High throughput analyses of polyphenol composition in berries using direct infusion mass spectrometry. Journal of Chromatography B, 871, 362–369.CrossRefGoogle Scholar
  116. Minor, E. C., Steinbring, C. J., Longnecker, K., & Kujawinski, E. B. (2012). Characterization of dissolved organic matter in Lake Superior and its watershed using ultrahigh resolution mass spectrometry. Organic Geochemistry, 43, 1–11.CrossRefGoogle Scholar
  117. Mittelstrass, K., Ried, J. S., Yu, Z., Krumsiek, J., Gieger, C., et al. (2011). Discovery of sexual dimorphisms in metabolic and genetic biomarkers. PLoS Genetics, 7(8), e1002215. doi:10.1371/journal.pgen.1002215.PubMedCrossRefGoogle Scholar
  118. 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. Analytical Chemistry, 82, 5887–5891.PubMedCrossRefGoogle Scholar
  119. Mougous, J. D., Leavell, M. D., Senaratne, R. H., et al. (2002). Discovery of sulfated metabolites in mycobacteria with a genetic and mass spectrometric approach. Proceedings of the National academy of Sciences of the United States of America, 99, 17037–17042.PubMedCrossRefGoogle Scholar
  120. Mungur, R., Glass, A. D. M., Goodenow, D. B., & Lightfoot, D. A. (2005). Metabolite fingerprinting in transgenic Nicotiana tabacum altered by the Escherichia coli glutamate dehydrogenase gene. Journal of Biomedicine and Biotechnology, 2, 198–214.CrossRefGoogle Scholar
  121. Nakamura, Y., Kimura, A., Saga, H., et al. (2007). Differential metabolomics unraveling light/dark regulation of metabolic activities in Arabidopsis cell culture. Planta, 227, 57–66.PubMedCrossRefGoogle Scholar
  122. Nakamura, Y., Kanaya, S., Sakurai, N., et al. (2008). A tool for high-throughput prediction of molecular formulas and identification of isotopic peaks from large-scale mass spectrometry data. Plant Biotechnology, 25, 377–380.CrossRefGoogle Scholar
  123. Nam, S., Joo, S., Kim, S., et al. (2008). Induced metabolite changes in Myriophyllum spicatum during co-existence experiment with the Cyanobacterium Microcystis aeruginosa. Journal of Plant Biology, 51, 373–378.CrossRefGoogle Scholar
  124. Ohno, T., He, Z., Sleighter, R. L., Honeycutt, C. W., & Hatcher, P. G. (2010). Ultrahigh resolution mass spectrometry and indicator species analysis to identify marker components of soil- and plant biomass-derived organic matter fractions. Environmental Science and Technology, 44, 8594–8600.PubMedCrossRefGoogle Scholar
  125. Ohta, D., Shibata, D., & Kanaya, S. (2007). Metabolic profiling using Fourier-transform ion-cyclotron-resonance mass spectrometry. Analytical and Bioanalytical Chemistry, 389, 1469–1475.PubMedCrossRefGoogle Scholar
  126. Ohta, D., Kanaya, S., & Suzuki, H. (2010). Application of Fourier-transform ion cyclotron resonance mass spectrometry to metabolic profiling and metabolite identification. Current Opinion in Biotechnology, 21, 35–44.PubMedCrossRefGoogle Scholar
  127. Oikawa, A., Nakamura, Y., Ogura, T., et al. (2006). Clarification of pathway-specific inhibition by Fourier transform ion cyclotron resonance/mass spectrometry-based metabolic phenotyping studies. Plant Physiology, 142, 398–413.PubMedCrossRefGoogle Scholar
  128. Overy, S. A., Walker, H. J., Malone, S., et al. (2005). Application of metabolite profiling to the identification of traits in a population of tomato introgression lines. Journal of Experimental Botany, 56, 287–296.PubMedCrossRefGoogle Scholar
  129. Overy, D. P., Enot, D. P., Tailliart, K., et al. (2008). Explanatory signal interpretation and metabolite identification strategies for nominal mass FIE-MS metabolite fingerprints. Nature Protocols, 3, 471–485.PubMedCrossRefGoogle Scholar
  130. Parker, D., Beckmann, M., Enot, D. P., et al. (2008). Rice blast infection of Brachypodium distachyon as a model system to study dynamic host/pathogen interactions. Nature Protocols, 3, 435–445.PubMedCrossRefGoogle Scholar
  131. Parker, D., Beckmann, M., Zubair, H., et al. (2009). Metabolomic analysis reveals a common pattern of metabolic re-programming during invasion of three host plant species by Magnaporthe grisea. Plant Journal, 59, 723–737.PubMedCrossRefGoogle Scholar
  132. Payne, T. G., Southam, A. D., Arvanitis, T. N., & Viant, M. R. (2009). A signal filtering method for improved quantification and noise discrimination in Fourier transform ion cyclotron resonance mass spectrometry-based metabolomics data. Journal of the American Society for Mass Spectrometry, 20, 1087–1095.PubMedCrossRefGoogle Scholar
  133. Pietta, P. G., Gardana, C., & Pietta, A. M. (2002). Analytical methods for quality control of propolis. Fitoterapia, 73, S7–S20.PubMedCrossRefGoogle Scholar
  134. Piovan, A., Filippini, R., & Favretto, D. (1998). Characterization of the anthocyanins of Catharanthus roseus (L.) G. Don in vivo and in vitro by electrospray ionization ion trap mass spectrometry. Rapid Communications in Mass Spectrometry, 12, 361–367.CrossRefGoogle Scholar
  135. Piovan, A., Filippini, R., Caniato, R., et al. (2004). Detection of hypericins in the “red glands” of Hypericum elodes by ESI-MS/MS. Phytochemistry, 65, 411–414.PubMedCrossRefGoogle Scholar
  136. Pope, G. A., Mackenzie, D. A., Defemez, M., et al. (2007). Metabolic footprinting as a tool for discriminating between brewing yeasts. Yeast, 24, 667–679.PubMedCrossRefGoogle Scholar
  137. Proschogo, N. W., Albertson, P. L., Bursle, J., et al. (2012). Aging effects on macadamia nut oil studied by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Journal of Agriculture and Food Chemistry, ahead of print.Google Scholar
  138. Rojas-Cherto, M., Kasper, P. T., Willighagen, E. L., et al. (2011). Elemental composition determination based on MS(n). Bioinformatics, 27, 2376–2383.PubMedCrossRefGoogle Scholar
  139. Rossello-Mora, R., Lucio, M., Pena, A., et al. (2008). Metabolic evidence for biogeographic isolation of the extremophilic bacterium Salinibacter ruber. ISME Journal, 2, 242–253.PubMedCrossRefGoogle Scholar
  140. Rubio-Aliaga, I., de Roos, B., Sailer, M., McLoughlin, G. A., et al. (2011). Alterations in hepatic one-carbon metabolism and related pathways following a high-fat dietary intervention. Physiological Genomics, 43, 408–416.PubMedCrossRefGoogle Scholar
  141. Saito, K., & Matsuda, F. (2010). Metabolomics for functional genomics, systems biology, and biotechnology. In: S. B. W. R. O. D. Merchant (Ed.), Annual Review of Plant Biology, vol. 61.Google Scholar
  142. Sana, T. R., Roark, J. C., Li, X., Waddell, K., & Fischer, S. M. (2008). Molecular formula and METLIN personal metabolite database matching applied to the identification of compounds generated by LC/TOF-MS. Journal of Biomolecular Techniques: JBT, 19, 258–266.PubMedGoogle Scholar
  143. Sawaya, A., Catharino, R. R., Facco, E. M. P., et al. (2011). Monitoring of wine aging process by electrospray ionization mass spectrometry. Ciencia E Tecnologia De Alimentos, 31, 730–734.CrossRefGoogle Scholar
  144. Scalbert, A., Brennan, L., Fiehn, O., et al. (2009). Mass-spectrometry-based metabolomics: Limitations and recommendations for future progress with particular focus on nutrition research. Metabolomics, 5, 435–458.PubMedCrossRefGoogle Scholar
  145. Schmidt, J., Boettcher, C., Kuhnt, C., Kutchan, T. M., & Zenk, M. H. (2007). Poppy alkaloid profiling by electrospray tandem mass spectrometry and electrospray FT-ICR mass spectrometry after ring-13 C(6)-tyramine feeding. Phytochemistry, 68, 189–202.PubMedCrossRefGoogle Scholar
  146. Scholz, M., Gatzek, S., Sterling, A., Fiehn, O., & Selbig, J. (2004). Metabolite fingerprinting: Detecting biological features by independent component analysis. Bioinformatics, 20, 2447–2454.PubMedCrossRefGoogle Scholar
  147. Schultz, G. A., Corso, T. N., Prosser, S. J., & Zhang, S. (2000). A fully integrated monolithic microchip electrospray device for mass spectrometry. Analytical Chemistry, 72, 4058–4063.PubMedCrossRefGoogle Scholar
  148. Scott, I. M., Vermeer, C. P., Liakata, M., et al. (2010). Enhancement of plant metabolite fingerprinting by machine learning. Plant Physiology, 153, 1506–1520.PubMedCrossRefGoogle Scholar
  149. Sleighter, R. L., & Hatcher, P. G. (2008). Molecular characterization of dissolved organic matter (DOM) along a river to ocean transect of the lower Chesapeake Bay by ultrahigh resolution electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Marine Chemistry, 110, 140–152.CrossRefGoogle Scholar
  150. Smedsgaard, J., & Frisvad, J. C. (1996). Using direct electrospray mass spectrometry in taxonomy and secondary metabolite profiling of crude fungal extracts. Journal of Microbiological Methods, 25, 5–17.CrossRefGoogle Scholar
  151. Smedsgaard, J., & Frisvad, J. C. (1997). Terverticillate penicillia studied by direct electrospray mass spectrometric profiling of crude extracts. 1. Chemosystematics. Biochemical Systematics and Ecology, 25, 51–64.CrossRefGoogle Scholar
  152. Smedsgaard, J., Hansen, M. E., & Frisvad, J. C. (2004). Classification of terverticillate Penicillia by electrospray mass spectrometric profiling. Studies in Mycology, 49, 243–251.Google Scholar
  153. Somorjai, R. L., Dolenko, B., & Baumgartner, R. (2003). Class prediction and discovery using gene microarray and proteomics mass spectroscopy data: Curses, caveats, cautions. Bioinformatics, 19, 1484–1491.PubMedCrossRefGoogle Scholar
  154. Soule, M. C. K., Longnecker, K., Giovannoni, S. J., & Kujawinski, E. B. (2010). Impact of instrument and experiment parameters on reproducibility of ultrahigh resolution ESI FT-ICR mass spectra of natural organic matter. Organic Geochemistry, 41, 725–733.CrossRefGoogle Scholar
  155. Southam, A. D., Payne, T. G., Cooper, H. J., Arvanitis, T. N., & Viant, M. R. (2007). Dynamic range and mass accuracy of wide-scan direct infusion nanoelectrospray Fourier transform ion cyclotron resonance mass spectrometry-based metabolomics increased by the spectral stitching method. Analytical Chemistry, 79, 4595–4602.PubMedCrossRefGoogle Scholar
  156. Stenson, A. C., Marshall, A. G., & Cooper, W. T. (2003). Exact masses and chemical formulas of individual Suwannee River fulvic acids from ultrahigh resolution electrospray ionization Fourier transform ion cyclotron resonance mass spectra. Analytical Chemistry, 75, 1275–1284.PubMedCrossRefGoogle Scholar
  157. Stoll, N., Schmidt, E., & Thurow, K. (2006). Isotope pattern evaluation for the reduction of elemental compositions assigned to high-resolution mass spectral data from electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Journal of the American Society for Mass Spectrometry, 17, 1692–1699.PubMedCrossRefGoogle Scholar
  158. Sumner, L. W., Mendes, P., & Dixon, R. A. (2003). Plant metabolomics: Large-scale phytochemistry in the functional genomics era. Phytochemistry, 62, 817–836.PubMedCrossRefGoogle Scholar
  159. Sun, J., & Chen, P. (2011). A flow-injection mass spectrometry fingerprinting method for authentication and quality assessment of Scutellaria lateriflora-based dietary supplements. Analytical and Bioanalytical Chemistry, 401, 1577–1584.PubMedCrossRefGoogle Scholar
  160. Szymańska, E., Saccenti, E., Smilde, A. K., & Westerhuis, J. A. (2011). Double-check: Validation of diagnostic statistics for PLS-DA models in metabolomics studies. Metabolomics,. doi:10.1007/s11306-011-0330-3.Google Scholar
  161. Takahashi, H., Kai, K., Shinbo, Y., et al. (2008). Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry. Analytical and Bioanalytical Chemistry, 391, 2769–2782.PubMedCrossRefGoogle Scholar
  162. Tautenhahn, R., Boettcher, C., Neumann, S. (2007). Annotation of LC/ESI-MS mass signals. In: S. W. R. Hochreiter (Ed.), Bioinformatics Research and Development, Proceedings.Google Scholar
  163. Taylor, N. S., Weber, R. J. M., Southam, A. D., et al. (2009). A new approach to toxicity testing in Daphnia magna: Application of high throughput FT-ICR mass spectrometry metabolomics. Metabolomics, 5, 44–58.CrossRefGoogle Scholar
  164. Tohge, T., Nishiyama, Y., Hirai, M. Y., et al. (2005). Functional genomics by integrated analysis of metabolome and transcriptome of Arabidopsis plants over-expressing an MYB transcription factor. Plant Journal, 42, 218–235.PubMedCrossRefGoogle Scholar
  165. Tremblay, L. B., Dittmar, T., Marshall, A. G., Cooper, W. J., & Cooper, W. T. (2007). Molecular characterization of dissolved organic matter in a North Brazilian mangrove porewater and mangrove-fringed estuaries by ultrahigh resolution Fourier transform-ion cyclotron resonance mass spectrometry and excitation/emission spectroscopy. Marine Chemistry, 105, 15–29.CrossRefGoogle Scholar
  166. Vaidyanathan, S., Rowland, J. J., Kell, D. B., & Goodacre, R. (2001). Discrimination of aerobic endospore-forming bacteria via electrospray-ionization mass spectrometry of whole cell suspensions. Analytical Chemistry, 73, 4134–4144.PubMedCrossRefGoogle Scholar
  167. Vaidyanathan, S., Kell, D. B., & Goodacre, R. (2002). Flow-injection electrospray ionization mass spectrometry of crude cell extracts for high-throughput bacterial identification. Journal of the American Society for Mass Spectrometry, 13, 118–128.PubMedCrossRefGoogle Scholar
  168. van den Berg, R. A., Hoefsloot, H. C. J., Westerhuis, J. A., Smilde, A. K., & van der Werf, M. J. (2006). Centering, scaling, and transformations: Improving the biological information content of metabolomics data. BMC Genomics, 7, 142.PubMedCrossRefGoogle Scholar
  169. Villagra, E., Santos, L. S., Gontijo Vaz, B., Eberlin, M. N., & Felipe Laurie, V. (2012). Varietal discrimination of Chilean wines by direct injection mass spectrometry analysis combined with multivariate statistics. Food Chemistry, 131, 692–697.CrossRefGoogle Scholar
  170. Villas-Boas, S. G., Mas, S., Akesson, M., Smedsgaard, J., & Nielsen, J. (2005). Mass spectrometry in metabolome analysis. Mass Spectrometry Reviews, 24, 613–646.PubMedCrossRefGoogle Scholar
  171. Wang, H., Manicke, N. E., Yang, Q., et al. (2011). Direct analysis of biological tissue by paper spray mass spectrometry. Analytical Chemistry, 83, 1197–1201.PubMedCrossRefGoogle Scholar
  172. Ward, J. L., Forcat, S., Beckmann, M., et al. (2010). The metabolic transition during disease following infection of Arabidopsis thaliana by Pseudomonas syringae pv. tomato. Plant Journal, 63, 443–457.CrossRefGoogle Scholar
  173. Weber, R. J. M., & Viant, M. R. (2010). MI-Pack: Increased confidence of metabolite identification in mass spectra by integrating accurate masses and metabolic pathways. Chemometrics and Intelligent Laboratory Systems, 104, 75–82.CrossRefGoogle Scholar
  174. Werner, E., Heilier, J.-F., Ducruix, C., et al. (2008). Mass spectrometry for the identification of the discriminating signals from metabolomics: Current status and future trends. Journal of Chromatography B-Analytical Technologies in the Biomedical and Life Sciences, 871, 143–163.CrossRefGoogle Scholar
  175. Westerhuis, J. A., Hoefsloot, H. C. J., Smit, S., Vis, D. J., Smilde, A. K., van Velzen, E. J. J., et al. (2008). Assessment of PLSDA cross validation. Metabolomics, 4, 81–89.CrossRefGoogle Scholar
  176. Wickremsinhe, E. R., Singh, G., Ackermann, B. L., Gillespie, T. A., & Chaudhary, A. K. (2006). A review of nanoelectrospray ionization applications for drug metabolism and pharmacokinetics. Current Drug Metabolism, 7, 913–928.PubMedCrossRefGoogle Scholar
  177. Windig, W., Phalp, J. M., & Payne, A. W. (1996). A noise and background reduction method for component detection in liquid chromatography mass spectrometry. Analytical Chemistry, 68, 3602–3606.CrossRefGoogle Scholar
  178. Wishart, D. S. (2009). Computational strategies for metabolite identification in metabolomics. Bioanalysis, 1, 1579–1596.PubMedCrossRefGoogle Scholar
  179. Wishart, D. S. (2011). Advances in metabolite identification. Bioanalysis, 3, 1769–1782.PubMedCrossRefGoogle Scholar
  180. Wu, Z., Chingin, K., Chen, H., et al. (2010). Sampling analytes from cheese products for fast detection using neutral desorption extractive electrospray ionization mass spectrometry. Analytical and Bioanalytical Chemistry, 397, 1549–1556.PubMedCrossRefGoogle Scholar
  181. Yang, L., Bennett, R., Strum, J., et al. (2009). Screening phosphatidylcholine biomarkers in mouse liver extracts from a hypercholesterolemia study using ESI-MS and chemometrics. Analytical and Bioanalytical Chemistry, 393, 643–654.PubMedCrossRefGoogle Scholar
  182. Yue, M.-E., Xu, J., Li, Q.-Q., & Hou, W.-G. (2011). Identification of coumarins in traditional Chinese medicine by direct-injection electrospray ionisation tandem mass spectrometry and high-performance liquid chromatography-mass spectrometry. Journal of Analytical Chemistry, 66, 290–295.CrossRefGoogle Scholar
  183. Zahn, J. A., Higgs, R. E., & Hilton, M. D. (2001). Use of direct-infusion electrospray mass spectrometry to guide empirical development of improved conditions for expression of secondary metabolites from actinomycetes. Applied and Environmental Microbiology, 67, 377–386.PubMedCrossRefGoogle Scholar
  184. Zamfir, A. D., Lion, N., Vukelic, Z., et al. (2005). Thin chip microsprayer system coupled to quadrupole time-of-flight mass spectrometer for glycoconjugate analysis. Lab on a Chip, 5, 298–307.PubMedCrossRefGoogle Scholar
  185. Zhang, L. K., Rempel, D., Pramanik, B. N., & Gross, M. L. (2005). Accurate mass measurements by Fourier transform mass spectrometry. Mass Spectrometry Reviews, 24, 286–309.CrossRefGoogle Scholar
  186. Zulak, K. G., Cornish, A., Daskalchuk, T. E., et al. (2007). Gene transcript and metabolite profiling of elicitor-induced opium poppy cell cultures reveals the coordinate regulation of primary and secondary metabolism. Planta, 225, 1085–1106.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • John Draper
    • 1
  • Amanda J. Lloyd
    • 1
  • Royston Goodacre
    • 2
  • Manfred Beckmann
    • 1
  1. 1.Institute of Biological Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
  2. 2.School of Chemistry and Manchester Interdisciplinary BiocentreUniversity of ManchesterManchesterUK

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