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Chemistry

בקנה מידה גדול Profiling metabolomic ללא ממוקד של סרום על ידי כרומטוגרפיה נוזלית ביצועים-Mass ספקטרומטריית Ultra (UPLC-MS)

Published: March 14, 2013 doi: 10.3791/50242

Materials

Name Company Catalog Number Comments
96 well plates - 500 μl wells VWR 40002-020 These are used for sample preparation
96 well plate mats VWR 89026-514 These are used for sample preparation
96 well plates - 350 μl wells Waters Corporation WAT058943 These are used for sample injection
96 well plate mats Waters Corporation 186000857 These are used for sample injection
96 well plate heat seals Waters Corporation 186002789 These can be used for sample injection or long term storage
96 well plate heat sealer Waters Corporation 186002786
LC-MS grade methanol Fluka 34966
LC-MS grade acetonitrile Fluka 34967
LC-MS grade aater Fluka 39253
LC-MS grade formic acid Fluka 56302
Multichannel electronic pipettor VWR 89000-674
Pipett tips Eclipse (purchased through Light Labs) B-5061/B-4061
Chilled centrifuge - Allegra X-12R Beckman Coulter N/A - contact Beckman Coulter
Acquity Ultra performance Liquid Chromatography (UPLC) System Waters Corporation N/A - contact Waters Corporation
UPLC C8 column (gradient option a) Waters Corporation 186002876
UplC T3 column (gradient option b) Waters Corporation 186003536
Xevo G2 Q-TOF Mass spectrometer Waters Corporation N/A - contact Waters Corporation

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References

  1. Theodoridis, G., Gika, H. G., Wilson, I. D. Mass Spectrometry-Based Holistic Analytical Approaches for Metabolite Profiling in Systems Biology Studies. Mass Spectrom. Rev. 30, 884-906 (2011).
  2. Zelena, E., et al. Development of a robust and repeatable UPLC-MS method for the long-term metabolomic study of human serum. Analytical Chemistry. 81, 1357-1364 (2009).
  3. Michopoulos, F., Lai, L., Gika, H., Theodoridis, G., Wilson, I. UPLC-MS-based analysis of human plasma for metabonomics using solvent precipitation or solid phase extraction. Journal of Proteome Research. 8, 2114-2121 (2009).
  4. Kamburov, A., Cavill, R., Ebbels, T. M., Herwig, R., Keun, H. C. Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA. Bioinformatics. 27, 2917-2918 (2011).
  5. Xia, J., Wishart, D. S. MetPA: a web-based metabolomics tool for pathway analysis and visualization. Bioinformatics. 26, 2342-2344 (2010).
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  8. Zhou, B., Xiao, J. F., Tuli, L., Ressom, H. W. LC-MS-based metabolomics. Mol. Biosyst. 8, 470-481 (2012).
  9. Weckwerth, W., Morgenthal, K. Metabolomics: from pattern recognition to biological interpretation. Drug Discov. Today. 10, 1551-1558 (2005).
  10. Smith, C. A., et al. METLIN - A metabolite mass spectral database. Ther. Drug Monit. 27, 747-751 (2005).
  11. Culpepper, S. A., Aguinis, H. R is for Revolution: A Cutting-Edge, Free, Open Source Statistical Package. Organ Res. Methods. 14, 735-740 (2011).
  12. Sumner, L. W., et al. Proposed minimum reporting standards for chemical analysis. Metabolomics. 3, 211-221 (2007).
  13. Vuckovic, D. Current trends and challenges in sample preparation for global metabolomics using liquid chromatography-mass spectrometry. Anal. Bioanal. Chem. 403, 1523-1548 (2012).
  14. Garcia-Canaveras, J. C., Donato, M. T., Castell, J. V., Lahoz, A. A comprehensive untargeted metabonomic analysis of human steatotic liver tissue by RP and HILIC chromatography coupled to mass spectrometry reveals important metabolic alterations. Journal of Proteome Research. 10, 4825-4834 (2011).
  15. Nordstrom, A., Want, E., Northen, T., Lehtio, J., Siuzdak, G. Multiple ionization mass spectrometry strategy used to reveal the complexity of metabolomics. Analytical Chemistry. 80, 421-429 (2008).
  16. Horai, H., et al. MassBank: a public repository for sharing mass spectral data for life sciences. J. Mass Spectrom. 45, 703-714 (2010).
  17. Wishart, D. S. Advances in metabolite identification. Bioanalysis. 3, 1769-1782 (2011).
  18. Broeckling, C., Heuberger, A., Prince, J., Ingelsson, E., Prenni, J. Assigning precursor-product ion relationships in indiscriminant MS/MS data from non-targeted metabolite profiling studies. Metabolomics. , 1-11 (2012).
  19. Kangas, L. J., et al. In silico identification software (ISIS): a machine learning approach to tandem mass spectral identification of lipids. Bioinformatics. 28, 1705-1713 (2012).
בקנה מידה גדול Profiling metabolomic ללא ממוקד של סרום על ידי כרומטוגרפיה נוזלית ביצועים-Mass ספקטרומטריית Ultra (UPLC-MS)
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Cite this Article

Broeckling, C. D., Heuberger, A. L., More

Broeckling, C. D., Heuberger, A. L., Prenni, J. E. Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS). J. Vis. Exp. (73), e50242, doi:10.3791/50242 (2013).

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