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Analytical Methods for Mass Spectrometry-Based Metabolomics Studies

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Advancements of Mass Spectrometry in Biomedical Research

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1140))

Abstract

The advancement of mass spectrometry-based analytical platform largely facilitates small-molecule metabolomics studies, which allows simultaneously analysis of a large number of metabolites from bio-samples and give a general picture of metabolic changes related to diseases or environmental alteration. Due to the large diversity of cellular metabolites, globally and precisely examining metabolic profile remains the most challenging part in metabolomic experiment. Mass spectrometry coupled with liquid chromatography enhances sensitivity and resolving power of metabolites identification and quantification, as well as versatility of analyzing a wide array of metabolites. In this chapter, we discussed the technical aspects of each step in the workflow of metabolomics studies we aimed to give technical guidelines for metabolomics investigation design and approach.

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References

  1. Nielsen, J. (2003). It is all about metabolic fluxes. Journal of Bacteriology, 185(24), 7031–7035.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Villas-Bôas, S. G., Mas, S., Åkesson, M., Smedsgaard, J., & Nielsen, J. (2005). Mass spectrometry in metabolome analysis. Mass Spectrometry Reviews, 24(5), 613–646.

    Article  PubMed  CAS  Google Scholar 

  3. Gibney, M. J., Walsh, M., Brennan, L., Roche, H. M., German, B., & Van Ommen, B. (2005). Metabolomics in human nutrition: Opportunities and challenges. The American Journal of Clinical Nutrition, 82(3), 497–503.

    Article  CAS  PubMed  Google Scholar 

  4. Armitage, E. G., & Barbas, C. (2014). Metabolomics in cancer biomarker discovery: Current trends and future perspectives. Journal of Pharmaceutical and Biomedical Analysis, 87, 1–11.

    Article  CAS  PubMed  Google Scholar 

  5. Brown, D. G., Rao, S., Weir, T. L., O’Malia, J., Bazan, M., Brown, R. J., et al. (2016). Metabolomics and metabolic pathway networks from human colorectal cancers, adjacent mucosa, and stool. Cancer & Metabolism, 4(1), 11.

    Article  Google Scholar 

  6. Wang, Z., Klipfell, E., Bennett, B. J., Koeth, R., Levison, B. S., DuGar, B., et al. (2011). Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature, 472(7341), 57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wang, Z., Tang, W. W., Buffa, J. A., Fu, X., Britt, E. B., Koeth, R. A., et al. (2014). Prognostic value of choline and betaine depends on intestinal microbiota-generated metabolite trimethylamine-N-oxide. European Heart Journal, 35(14), 904–910.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Warrier, M., Shih, D. M., Burrows, A. C., Ferguson, D., Gromovsky, A. D., Brown, A. L., et al. (2015). The TMAO-generating enzyme flavin monooxygenase 3 is a central regulator of cholesterol balance. Cell Reports, 10(3), 326–338.

    Article  CAS  PubMed  Google Scholar 

  9. Gregory, J. C., Buffa, J. A., Org, E., Wang, Z., Levison, B. S., Zhu, W., et al. (2015). Transmission of atherosclerosis susceptibility with gut microbial transplantation. The Journal of Biological Chemistry, 290(9), 5647–5660.

    Article  CAS  PubMed  Google Scholar 

  10. Ward, P. S., Patel, J., Wise, D. R., Abdel-Wahab, O., Bennett, B. D., Coller, H. A., et al. (2010). The common feature of leukemia-associated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting α-ketoglutarate to 2-hydroxyglutarate. Cancer Cell, 17(3), 225–234.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yang, M., Soga, T., & Pollard, P. J. (2013). Oncometabolites: Linking altered metabolism with cancer. The Journal of Clinical Investigation, 123(9), 3652–3658.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Xia, J., Broadhurst, D. I., Wilson, M., & Wishart, D. S. (2013). Translational biomarker discovery in clinical metabolomics: An introductory tutorial. Metabolomics, 9(2), 280–299.

    Article  CAS  PubMed  Google Scholar 

  13. Stewart, N. A., Buch, S. C., Conrads, T. P., & Branch, R. A. (2011). A UPLC-MS/MS assay of the “Pittsburgh cocktail”: Six CYP probe-drug/metabolites from human plasma and urine using stable isotope dilution. Analyst, 136(3), 605–612.

    Article  CAS  PubMed  Google Scholar 

  14. Zhu, H., Bogdanov, M. B., Boyle, S. H., Matson, W., Sharma, S., Matson, S., et al. (2013). Pharmacometabolomics of response to sertraline and to placebo in major depressive disorder–possible role for methoxyindole pathway. PLoS One, 8(7), e68283.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Ellero-Simatos, S., Lewis, J., Georgiades, A., Yerges-Armstrong, L., Beitelshees, A., Horenstein, R., et al. (2014). Pharmacometabolomics reveals that serotonin is implicated in aspirin response variability. CPT: Pharmacometrics & Systems Pharmacology, 3(7), 1–9.

    Google Scholar 

  16. Villas-Bôas, S. G. (2007). Sampling and sample preparation. In Metabolome analysis: An introduction (pp. 39–82). NJ: John Wiley & Sons.

    Chapter  Google Scholar 

  17. Mushtaq, M. Y., Choi, Y. H., Verpoorte, R., & Wilson, E. G. (2014). Extraction for metabolomics: Access to the metabolome. Phytochemical Analysis: PCA, 25(4), 291–306.

    Article  CAS  PubMed  Google Scholar 

  18. Liu, X., Sadhukhan, S., Sun, S., Wagner, G. R., Hirschey, M. D., Qi, L., et al. (2015). High-resolution metabolomics with acyl-CoA profiling reveals widespread remodeling in response to diet. Molecular & Cellular Proteomics: MCP, 14(6), 1489–1500.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Fan, J., Ye, J., Kamphorst, J. J., Shlomi, T., Thompson, C. B., & Rabinowitz, J. D. (2014). Quantitative flux analysis reveals folate-dependent NADPH production. Nature, 510(7504), 298.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Winder, C. L., Dunn, W. B., Schuler, S., Broadhurst, D., Jarvis, R., Stephens, G. M., et al. (2008). Global metabolic profiling of Escherichia coli cultures: An evaluation of methods for quenching and extraction of intracellular metabolites. Analytical Chemistry, 80(8), 2939–2948.

    Article  CAS  PubMed  Google Scholar 

  21. Want, E. J., Masson, P., Michopoulos, F., Wilson, I. D., Theodoridis, G., Plumb, R. S., et al. (2013). Global metabolic profiling of animal and human tissues via UPLC-MS. Nature Protocols, 8(1), 17.

    Article  CAS  PubMed  Google Scholar 

  22. Theobald, U., Mailinger, W., Reuss, M., & Rizzi, M. (1993). In vivo analysis of glucose-induced fast changes in yeast adenine nucleotide pool applying a rapid sampling technique. Analytical Biochemistry, 214(1), 31–37.

    Article  CAS  PubMed  Google Scholar 

  23. Villas-Bôas, S. G., Højer-Pedersen, J., Åkesson, M., Smedsgaard, J., & Nielsen, J. (2005). Global metabolite analysis of yeast: Evaluation of sample preparation methods. Yeast, 22(14), 1155–1169.

    Article  PubMed  CAS  Google Scholar 

  24. Jang, C., Chen, L., & Rabinowitz, J. D. (2018). Metabolomics and isotope tracing. Cell, 173(4), 822–837.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wittmann, C., Krömer, J. O., Kiefer, P., Binz, T., & Heinzle, E. (2004). Impact of the cold shock phenomenon on quantification of intracellular metabolites in bacteria. Analytical Biochemistry, 327(1), 135–139.

    Article  CAS  PubMed  Google Scholar 

  26. Beltran, A., Suarez, M., Rodriguez, M. A., Vinaixa, M., Samino, S., Arola, L., et al. (2012). Assessment of compatibility between extraction methods for NMR- and LC/MS-based metabolomics. Analytical Chemistry, 84(14), 5838–5844.

    Article  CAS  PubMed  Google Scholar 

  27. Geier, F. M., Want, E. J., Leroi, A. M., & Bundy, J. G. (2011). Cross-platform comparison of Caenorhabditis elegans tissue extraction strategies for comprehensive metabolome coverage. Analytical Chemistry, 83(10), 3730–3736.

    Article  CAS  PubMed  Google Scholar 

  28. Shestov, A. A., Lee, S. C., Nath, K., Guo, L., Nelson, D. S., Roman, J. C., et al. (2016). (13)C MRS and LC-MS flux analysis of tumor intermediary metabolism. Frontiers in Oncology, 6, 135.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bedi Jr., K. C., Snyder, N. W., Brandimarto, J., Aziz, M., Mesaros, C., Worth, A. J., et al. (2016). Evidence for intramyocardial disruption of lipid metabolism and increased myocardial ketone utilization in advanced human heart failure. Circulation, 133(8), 706–716.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Samuelson, O., & Sjostrom, E. (1952). Utilization of ion exchangers in analytical chemistry. XXIV. Isolation of monosaccharides. Svensk Kemisk Tidskrift, 64, 305–314.

    CAS  Google Scholar 

  31. Alpert, A. J. (1990). Hydrophilic-interaction chromatography for the separation of peptides, nucleic acids and other polar compounds. Journal of Chromatography, 499, 177–196.

    Article  CAS  PubMed  Google Scholar 

  32. Tang, D. Q., Zou, L., Yin, X. X., & Ong, C. N. (2016). HILIC-MS for metabolomics: An attractive and complementary approach to RPLC-MS. Mass Spectrometry Reviews, 35(5), 574–600.

    Article  CAS  PubMed  Google Scholar 

  33. Hemström, P., & Irgum, K. (2006). Hydrophilic interaction chromatography. Journal of Separation Science, 29(12), 1784–1821.

    Article  PubMed  CAS  Google Scholar 

  34. Alpert, A. J., Shukla, M., Shukla, A. K., Zieske, L. R., Yuen, S. W., Ferguson, M. A., et al. (1994). Hydrophilic-interaction chromatography of complex carbohydrates. Journal of Chromatography, 676(1), 191–202.

    Article  CAS  PubMed  Google Scholar 

  35. Jandera, P., Hájek, T., Škeříková, V., & Soukup, J. (2010). Dual hydrophilic interaction-RP retention mechanism on polar columns: Structural correlations and implementation for 2-D separations on a single column. Journal of Separation Science, 33(6–7), 841–852.

    Article  CAS  PubMed  Google Scholar 

  36. McCalley, D. V. (2010). Study of the selectivity, retention mechanisms and performance of alternative silica-based stationary phases for separation of ionised solutes in hydrophilic interaction chromatography. Journal of Chromatography, 1217(20), 3408–3417.

    Article  CAS  PubMed  Google Scholar 

  37. Cubbon, S., Antonio, C., Wilson, J., & Thomas-Oates, J. (2010). Metabolomic applications of HILIC–LC–MS. Mass Spectrometry Reviews, 29(5), 671–684.

    Article  CAS  PubMed  Google Scholar 

  38. Gama, M. R., da Costa Silva, R. G., Collins, C. H., & Bottoli, C. B. (2012). Hydrophilic interaction chromatography. TrAC Trends in Analytical Chemistry, 37, 48–60.

    Article  CAS  Google Scholar 

  39. Guo, Y., & Gaiki, S. (2005). Retention behavior of small polar compounds on polar stationary phases in hydrophilic interaction chromatography. Journal of Chromatography, 1074(1–2), 71–80.

    Article  CAS  PubMed  Google Scholar 

  40. Buszewski, B., & Noga, S. (2012). Hydrophilic interaction liquid chromatography (HILIC)—A powerful separation technique. Analytical and Bioanalytical Chemistry, 402(1), 231–247.

    Article  CAS  PubMed  Google Scholar 

  41. Bajad, S. U., Lu, W., Kimball, E. H., Yuan, J., Peterson, C., & Rabinowitz, J. D. (2006). Separation and quantitation of water soluble cellular metabolites by hydrophilic interaction chromatography-tandem mass spectrometry. Journal of Chromatography, 1125(1), 76–88.

    Article  CAS  PubMed  Google Scholar 

  42. Cubbon, S., Bradbury, T., Wilson, J., & Thomas-Oates, J. (2007). Hydrophilic interaction chromatography for mass spectrometric metabonomic studies of urine. Analytical Chemistry, 79(23), 8911–8918.

    Article  CAS  PubMed  Google Scholar 

  43. Zhang, X., Rauch, A., Lee, H., Xiao, H., Rainer, G., & Logothetis, N. K. (2007). Capillary hydrophilic interaction chromatography/mass spectrometry for simultaneous determination of multiple neurotransmitters in primate cerebral cortex. Rapid Communications in Mass Spectrometry: An International Journal Devoted to the Rapid Dissemination of Up-to-the-Minute Research in Mass Spectrometry, 21(22), 3621–3628.

    Article  CAS  Google Scholar 

  44. Zauner, G., Deelder, A. M., & Wuhrer, M. (2011). Recent advances in hydrophilic interaction liquid chromatography (HILIC) for structural glycomics. Electrophoresis, 32(24), 3456–3466.

    Article  CAS  PubMed  Google Scholar 

  45. Gika, H. G., Theodoridis, G. A., Vrhovsek, U., & Mattivi, F. (2012). Quantitative profiling of polar primary metabolites using hydrophilic interaction ultrahigh performance liquid chromatography–tandem mass spectrometry. Journal of Chromatography, 1259, 121–127.

    Article  CAS  PubMed  Google Scholar 

  46. Paek, I. B., Moon, Y., Ji, H. Y., Kim, H.-H., Lee, H. W., Lee, Y.-B., et al. (2004). Hydrophilic interaction liquid chromatography–tandem mass spectrometry for the determination of levosulpiride in human plasma. Journal of Chromatography B, 809(2), 345–350.

    Article  CAS  Google Scholar 

  47. Liu, X., Ser, Z., Cluntun, A. A., Mentch, S. J., & Locasale, J. W. (2014). A strategy for sensitive, large scale quantitative metabolomics. Journal of Visualized Experiments: JoVE, (87). https://doi.org/10.3791/51358

  48. Liu, X., Ser, Z., & Locasale, J. W. (2014). Development and quantitative evaluation of a high-resolution metabolomics technology. Analytical Chemistry, 86(4), 2175–2184.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Hopfgartner, G., Varesio, E., Tschäppät, V., Grivet, C., Bourgogne, E., & Leuthold, L. A. (2004). Triple quadrupole linear ion trap mass spectrometer for the analysis of small molecules and macromolecules. Journal of Mass Spectrometry, 39(8), 845–855.

    Article  CAS  PubMed  Google Scholar 

  50. Contrepois, K., Jiang, L., & Snyder, M. (2015). Optimized analytical procedures for the untargeted metabolomic profiling of human urine and plasma by combining hydrophilic interaction and reverse-phase liquid chromatography-mass spectrometry. Molecular Cell Proteomics, 14, 1684–1695.

    Article  CAS  Google Scholar 

  51. Guo, Y., & Gaiki, S. (2011). Retention and selectivity of stationary phases for hydrophilic interaction chromatography. Journal of Chromatography, 1218(35), 5920–5938.

    Article  CAS  PubMed  Google Scholar 

  52. Jandera, P. (2011). Stationary and mobile phases in hydrophilic interaction chromatography: A review. Analytica Chimica Acta, 692(1–2), 1–25.

    Article  CAS  PubMed  Google Scholar 

  53. Cecchi, T. (2011). Retention mechanism for ion-pair chromatography with chaotropic reagents. From ion-pair chromatography toward a unified salt chromatography. Advances in Chromatography, 49, 1–35.

    CAS  PubMed  Google Scholar 

  54. Lu, W., Clasquin, M. F., Melamud, E., Amador-Noguez, D., Caudy, A. A., & Rabinowitz, J. D. (2010). Metabolomic analysis via reversed-phase ion-pairing liquid chromatography coupled to a stand alone orbitrap mass spectrometer. Analytical Chemistry, 82(8), 3212–3221.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Gong, L., & McCullagh, J. S. (2014). Comparing ion-pairing reagents and sample dissolution solvents for ion-pairing reversed-phase liquid chromatography/electrospray ionization mass spectrometry analysis of oligonucleotides. Rapid Communications in Mass Spectrometry: RCM, 28(4), 339–350.

    Article  CAS  PubMed  Google Scholar 

  56. Guo, L., Worth, A. J., Mesaros, C., Snyder, N. W., Glickson, J. D., & Blair, I. A. (2016). Diisopropylethylamine/hexafluoroisopropanol-mediated ion-pairing ultra-high-performance liquid chromatography/mass spectrometry for phosphate and carboxylate metabolite analysis: Utility for studying cellular metabolism. Rapid Communications in Mass Spectrometry: RCM, 30(16), 1835–1845.

    Article  CAS  PubMed  Google Scholar 

  57. Apffel, A., Chakel, J. A., Fischer, S., Lichtenwalter, K., & Hancock, W. S. (1997). Analysis of oligonucleotides by HPLC-electrospray ionization mass spectrometry. Analytical Chemistry, 69(7), 1320–1325.

    Article  CAS  PubMed  Google Scholar 

  58. Frederick, D. W., Trefely, S., Buas, A., Goodspeed, J., Singh, J., Mesaros, C., et al. (2017). Stable isotope labeling by essential nutrients in cell culture (SILEC) for accurate measurement of nicotinamide adenine dinucleotide metabolism. The Analyst, 142(23), 4431–4437.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Basu, S. S., Mesaros, C., Gelhaus, S. L., & Blair, I. A. (2011). Stable isotope labeling by essential nutrients in cell culture for preparation of labeled coenzyme A and its thioesters. Analytical Chemistry, 83(4), 1363–1369.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Guo, L., Shestov, A. A., Worth, A. J., Nath, K., Nelson, D. S., Leeper, D. B., et al. (2016). Inhibition of mitochondrial complex II by the anticancer agent lonidamine. The Journal of Biological Chemistry, 291(1), 42–57.

    Article  CAS  PubMed  Google Scholar 

  61. Tolstikov, V. V., & Fiehn, O. (2002). Analysis of highly polar compounds of plant origin: Combination of hydrophilic interaction chromatography and electrospray ion trap mass spectrometry. Analytical Biochemistry, 301(2), 298–307.

    Article  CAS  PubMed  Google Scholar 

  62. Moco, S., Vervoort, J., Bino, R. J., De Vos, R. C., & Bino, R. (2007). Metabolomics technologies and metabolite identification. TrAC Trends in Analytical Chemistry, 26(9), 855–866.

    Article  CAS  Google Scholar 

  63. Liu, X., & Locasale, J. W. (2017). Metabolomics: A primer. Trends in Biochemical Sciences, 42(4), 274–284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. D’Atri, V., Causon, T., Hernandez-Alba, O., Mutabazi, A., Veuthey, J. L., Cianferani, S., et al. (2018). Adding a new separation dimension to MS and LC–MS: What is the utility of ion mobility spectrometry? Journal of Separation Science, 41(1), 20–67.

    Article  PubMed  CAS  Google Scholar 

  65. Smith, C. A., O’Maille, G., Want, E. J., Qin, C., Trauger, S. A., Brandon, T. R., et al. (2005). METLIN: A metabolite mass spectral database. Therapeutic Drug Monitoring, 27(6), 747–751.

    Article  CAS  PubMed  Google Scholar 

  66. Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., et al. (2012). HMDB 3.0—The human metabolome database in 2013. Nucleic Acids Research, 41(D1), D801–D807.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. Kanehisa, M., Goto, S., Sato, Y., Kawashima, M., Furumichi, M., & Tanabe, M. (2013). Data, information, knowledge and principle: Back to metabolism in KEGG. Nucleic Acids Research, 42(D1), D199–D205.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Horai, H., Arita, M., Kanaya, S., Nihei, Y., Ikeda, T., Suwa, K., et al. (2010). MassBank: A public repository for sharing mass spectral data for life sciences. Journal of Mass Spectrometry, 45(7), 703–714.

    Article  CAS  PubMed  Google Scholar 

  69. Kind, T., & Fiehn, O. (2007). Seven golden rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC Bioinformatics, 8(1), 105.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Tachibana, C. (2014). What’s next in’omics: The metabolome. Science, 345(6203), 1519–1521.

    Article  Google Scholar 

  71. 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  PubMed  PubMed Central  CAS  Google Scholar 

  72. Kind, T., Wohlgemuth, G., Lee, D. Y., Lu, Y., Palazoglu, M., Shahbaz, S., et al. (2009). FiehnLib: Mass spectral and retention index libraries for metabolomics based on quadrupole and time-of-flight gas chromatography/mass spectrometry. Analytical Chemistry, 81(24), 10038–10048.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Saccenti, E., Hoefsloot, H. C., Smilde, A. K., Westerhuis, J. A., & Hendriks, M. M. (2014). Reflections on univariate and multivariate analysis of metabolomics data. Metabolomics, 10(3), 361–374.

    Article  CAS  Google Scholar 

  74. Keun, H. C., Ebbels, T. M., Bollard, M. E., Beckonert, O., Antti, H., Holmes, E., et al. (2004). Geometric trajectory analysis of metabolic responses to toxicity can define treatment specific profiles. Chemical Research in Toxicology, 17(5), 579–587.

    Article  CAS  PubMed  Google Scholar 

  75. Morrison, D. F. (2005). Multivariate analysis of variance. In Encyclopedia of biostatistics (5th ed.). NJ: John Wiley & Sons.

    Google Scholar 

  76. Ellis, D. I., & Goodacre, R. (2006). Metabolic fingerprinting in disease diagnosis: Biomedical applications of infrared and Raman spectroscopy. Analyst, 131(8), 875–885.

    Article  CAS  PubMed  Google Scholar 

  77. Shlens, J. (2005). A tutorial on principal component analysis. La Jolla: Systems Neurobiology Laboratory, Salk Insitute for Biological Studies.

    Google Scholar 

  78. Xie, L. W., Atanasov, A. G., Guo, D. A., Malainer, C., Zhang, J. X., Zehl, M., et al. (2014). Activity-guided isolation of NF-kappaB inhibitors and PPARgamma agonists from the root bark of Lycium chinense Miller. Journal of Ethnopharmacology, 152(3), 470–477.

    Article  CAS  PubMed  Google Scholar 

  79. Nyamundanda, G., Brennan, L., & Gormley, I. C. (2010). Probabilistic principal component analysis for metabolomic data. BMC Bioinformatics, 11(1), 571.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Pan, Z., Gu, H., Talaty, N., Chen, H., Shanaiah, N., Hainline, B. E., et al. (2007). Principal component analysis of urine metabolites detected by NMR and DESI–MS in patients with inborn errors of metabolism. Analytical and Bioanalytical Chemistry, 387(2), 539–549.

    Article  CAS  PubMed  Google Scholar 

  81. Gu, H., Pan, Z., Xi, B., Asiago, V., Musselman, B., & Raftery, D. (2011). Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: Application to the detection of breast cancer. Analytica Chimica Acta, 686(1–2), 57–63.

    Article  CAS  PubMed  Google Scholar 

  82. Wold, S., Sjöström, M., & Eriksson, L. (2001). PLS-regression: A basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58(2), 109–130.

    Article  CAS  Google Scholar 

  83. Boulesteix, A.-L., & Strimmer, K. (2006). Partial least squares: A versatile tool for the analysis of high-dimensional genomic data. Briefings in Bioinformatics, 8(1), 32–44.

    Article  PubMed  CAS  Google Scholar 

  84. Fonville, J. M., Richards, S. E., Barton, R. H., Boulange, C. L., Ebbels, T. M., Nicholson, J. K., et al. (2010). The evolution of partial least squares models and related chemometric approaches in metabonomics and metabolic phenotyping. Journal of Chemometrics, 24(11–12), 636–649.

    Article  CAS  Google Scholar 

  85. Mehmood, T., Martens, H., Sæbø, S., Warringer, J., & Snipen, L. (2011). A partial least squares based algorithm for parsimonious variable selection. Algorithms for Molecular Biology, 6(1), 27.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Mehmood, T., Liland, K. H., Snipen, L., & Sæbø, S. (2012). A review of variable selection methods in partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 118, 62–69.

    Article  CAS  Google Scholar 

  87. Xi, B., Gu, H., Baniasadi, H., & Raftery, D. (2014). Statistical analysis and modeling of mass spectrometry-based metabolomics data. In Mass spectrometry in metabolomics (pp. 333–353). New York: Springer.

    Google Scholar 

  88. Gromski, P. S., Muhamadali, H., Ellis, D. I., Xu, Y., Correa, E., Turner, M. L., et al. (2015). A tutorial review: Metabolomics and partial least squares-discriminant analysis—a marriage of convenience or a shotgun wedding. Analytica Chimica Acta, 879, 10–23.

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Penn SRP Center and Center of Excellence in Environmental Toxicology Center, Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Siyu Wang, Ian A. Blair & Clementina Mesaros

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  1. Siyu Wang
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  2. Ian A. Blair
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  3. Clementina Mesaros
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Correspondence to Clementina Mesaros .

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Editors and Affiliations

  1. Biochemistry and Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, USA

    Alisa G. Woods

  2. Biochemistry and Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, USA

    Costel C. Darie

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Wang, S., Blair, I.A., Mesaros, C. (2019). Analytical Methods for Mass Spectrometry-Based Metabolomics Studies. In: Woods, A., Darie, C. (eds) Advancements of Mass Spectrometry in Biomedical Research. Advances in Experimental Medicine and Biology, vol 1140. Springer, Cham. https://doi.org/10.1007/978-3-030-15950-4_38

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