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Metabolomics 5/2/2014. ‘Omics Family Tree W. M. Claudino, et al., Journal of Clinical Oncology, 2007, 25(19), pp. 2840-2846 5/2/2014.

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Presentation on theme: "Metabolomics 5/2/2014. ‘Omics Family Tree W. M. Claudino, et al., Journal of Clinical Oncology, 2007, 25(19), pp. 2840-2846 5/2/2014."— Presentation transcript:

1 Metabolomics 5/2/2014

2 ‘Omics Family Tree W. M. Claudino, et al., Journal of Clinical Oncology, 2007, 25(19), pp. 2840-2846 5/2/2014

3 Metabolomics mɪˈtabəlɒmɪks/ Noun BIOCHEMISTRY noun: metabolomics 1.The scientific study of the set of metabolites present within an organism, cell, or tissue. The Oxford Dictionary 5/2/2014

4 How are metabolites influenced? W. M. Claudino, et al., Journal of Clinical Oncology, 2007, 25(19), pp. 2840-2846 5/2/2014

5 Instrumental Analysis Gas Chromatography Mass Spectrometry (GC-MS) High Performance Liquid Chromatography (HPLC) Nanostructure Initiator Mass Spectrometry (NIMS) Secondary Ion Mass Spectrometry (SIMS) Nuclear Magnetic Resonance (NMR) 5/2/2014

6 Image : www.metabolomics.biozentrum.uni-wuerzburg.de/research1/ 5/2/2014

7 Metabolic Fingerprinting Generally a no a priori approach Diagnostic based upon correlation of metabolites Qualitative analysis 5/2/2014

8 Metabolic Fingerprinting H. Wang, et al., Molecular Cancer, 2013, 12(121). DOI: 10.1186/1476-4598-12-121 600 MHz representative 1 H NMR spectra of tissue samples. A normal control B stage I of rectal cancer C stage II of rectal cancer D stage III of rectal cancer E stage IV of rectal cancer. 5/2/2014

9 Principal Component Analysis Principal Component Analysis (PCA) scores plot showing discriminate metabolites from cancer tissues, versus normal controls H. Wang, et al., Molecular Cancer, 2013, 12(121). DOI: 10.1186/1476-4598-12-121 5/2/2014

10 Orthogonal Projections to Latent Structures What in X is related to Y – Predictive What in X is not related to Y – Orthogonal (J. Trygg 2010) H. Wang, et al., Molecular Cancer, 2013, 12(121). DOI: 10.1186/1476-4598-12-121 Image: Positive region – Cancerous tissues Negative region – Normal tissues 5/2/2014

11 Statistical Validation of Multivariate Models H. Wang, et al., Molecular Cancer, 2013, 12(121). DOI: 10.1186/1476-4598-12-121 R 2 = Explained Variance Q 2 = Predictable ability of the model 5/2/2014

12 Metabolite Screening and Targeted Analysis Requires some prior knowledge Identification of metabolites Quantitative approach 5/2/2014

13 1.Human Metabolome Database (www.hmdb.ca)www.hmdb.ca 2.Pubchem (http://pubchem.ncbi.nlm.nih.gov)http://pubchem.ncbi.nlm.nih.gov 3.Metabolights (www.ebi.ac.uk/metabolights)www.ebi.ac.uk/metabolights 4.Kegg (www.genome.jp/kegg)www.genome.jp/kegg 5.Metlin (http://metlin.scripps.edu)http://metlin.scripps.edu 6.Massbank (www.massbank.jp)www.massbank.jp Metabolite Screening and Targeted Analysis 5/2/2014

14 Mestrelab : Mnova Predicts NMR spectra of compounds 5/2/2014

15 http://www.hmdb.ca/metabolites/HMDB00190 Example http://www.frontiersin.org/Journal/10.3389/fncel.20 13.00179/full Fetal Bovine Serum (FBS) - 1 H NMR spectrum acquired on 300MHz Oxford Instrument – 04/02/2014 5/2/2014

16 Recommended Reading 1.D. I. Broadhurst and D. B. Kell, Metabolomics, 2007, 2(4), pp. 171-196. DOI: 10.1007-511306-006-0037-z 2.R. Goodacre, et al., Trends in Biotechnol., 2004, 22(5), pp. 245-252. 3.R. Zenobi, Science, 2013, 342, pp. 1201-1212. DOI: 10.1126/science.1243259 4.N. V. Reo, Drug Chem. Toxicol., 2002, 25(4), pp. 375-382. 5.W. M. Claudino, et al., Journal of Clinical Oncology, 2007, 25(19), pp. 2840-2846. 6.H. Wang, et al., Molecular Cancer, 2013, 12(121). 7.D. L. Massart et al., Chemometrics : A Textbook, Elsevier, New York, 1988. 8.J. Trygg and S. Wold, J. Chemom., 2002, 16(3), pp. 119-128. 5/2/2014

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