1. http://creativecommons.org/licens es/by-sa/2.0/

2. Large Scale Approaches to the Study of Metabolite Levels Prof:Rui Alves ralves@cmb.udl.es 973702406 Dept Ciencies Mediques Basiques, 1st Floor, Room 1.08 Website of the Course:http://web.udl.es/usuaris/pg193845/Courses/Bioinformatics_2007/ Course: http://10.100.14.36/Student_Server/

3. Genome, Proteome, now what? Metabolites!!!

4. Why Studying Metabolites Directly? Just because the activity of a protein change, do levels of product/substrate change? What happens with the levels of non- covalently bound regulators or small molecules imported from the medium?

5. Why Studying Metabolites Directly? Which metabolites does the cell regulate for each response? How are they regulated and by how much? How can we know what to change in the cell for biotechnological purposes of producing some metabolite (e.g. antibiotics) if we don’t know how the levels of these metabolites change?

6. From metabolites to metabolomics Metabolite is an intermediate of metabolism Metabolome is the metabolic complement (metabolite pool) of a cell, tissue or organism under a given set of conditions Metabolomics is the study of the metabolome

7. The Metabolome –Metabolite complement of a proteome Variable –In different cell and tissue types in same organism –In different growth and developmental stages of organism Dynamic –Depends on response of genome & proteome to environmental factors »Disease state »Drug challenge »Growth conditions »Stress

8. What can we do with Metabolomics Metabolomics enables: Qualitative and quantitative display of metabolite concentration patterns Assessment of global changes Comparative analysis of samples Provides information from which biological hypotheses may be developed

9. Tissue or biofluid sample Measure the metabolite profile Treat profile as ‘fingerprint’ for classification purposes Explore profile to gain mechanistic insight into the biological response Statistical bioinformatic tools Bioanalytical tools (applied/clinical) (basic research) 1. Mass spectrometry 2. 1 H NMR spectroscopy The procedure

10.  Low molecular weight organic metabolites: Amino acids Organic acids and bases Nucleotides Carbohydrates Osmolytes Lipids (broad non-specific resonances) Which metabolites can be observed by NMR?

11. NMR is possible because of Nuclear Spin All nuclei that contain odd numbers of protons or neutrons have an intrinsic magnetic moment and angular momentum Nuclear spin angular momentum is a quantized property of the nucleus in each atom, which arises from the sub-atomic properties of neutrons and protons The nuclear spin angular momentum of each atom is represented by a nuclear spin quantum number (I) All nuclei with even mass numbers have I=0,1,2… All nuclei with odd mass numbers have I=1/2,3/2... NMR is possible with all nuclei except I=0, but I=1/2 has simplest physics Biomolecular NMR  primarily 1 H, 13 C, 15 N ( 31 P)

12. Organism The experiment Marked metabolite Organism Magnetic field generator (frequency: what compound) (how much) Chemical shift is how much the spectrum changes with respect to a specific well known ground state

13. What the hell is chemical shift? All nuclei have a specific resonance spectrum This spectrum changes depending on the environment of an atom Thus the 1 H spectrum in CH 4 is different from that in 1 H 2

14. A few simple 1 H spectra

15. What about more complicated molecules? 1 H NMR Spectrum of Ubiquitin Things get very messy Subspectra become entangled

16. What to do about this? Use a different magnetic pulse to measure another spectrum! Magnetic field generator Magnetic field generator Cs ppm (pulse 1) Cs ppm (pulse 2) 2D NMR!!!!

17. Use 2D NMR to Resolve Overlapping Signals 1D 2D Sub-spectra overlapped Coupled spins Crosspeaks resolved! ppm (pulse 1) ppm (pulse 2) Concept can be extended to N- dimensional NMR!!!

18. Multi-Dimensional NMR If 2D cross peaks overlap  go to 3D or 4D ….. HNHN HH HH

19. Rule of thumb If two groups are different then you can always resolve the spectrum by applying a sufficiently high magnetic field

20. Data Analysis Fitting 5-10 rounded peaks is trivial, fitting 1000+ sharp peaks is not, i.e. dense matrix problem with very high probability of cumulative rounding errors and singularities(LLSOL - Stanford) Peak positions & shapes dependent on salt, pH, temperature, ligands, ligand/ion interactions, shimming, signal-to-noise digital resolution, phasing, field strength, etc. etc.

21. Metabolome Pipeline Multi-disciplinary teams required Meta-data (data about data) extremely important Data storage (database) important for large datasets Brown et al, Metabolomics, 2005, 1, 39-51 Spectrum identification can be made using for example Fourier Transforms Problems similar to those for “ID”ing mass spec spectra for proteins

22. Example Metabolomic changes due to polution in fresh water japanese fish (medaka)

23. PC1 score PC2 score Day 1 2 6 5 4 3 7 8 Developmental trajectory PCA scores plot: Summarizes changes in NMR-visible metabolome throughout embryogenesis in Japanese medaka Fertilization Hatch Chemical shift (ppm) 12345678910 PC 1 loadings -0.4 -0.2 0.0 0.2 0.4 Tyrosine ATP Histidine Creatine Alanine Lactate late stage embryos early stage embryos

24. Developmental toxicity of trichloroethylene (TCE) in Japanese medaka Expose medaka embryos to TCE throughout embryogenesis. Preserved replicates of ~100 eggs on day 7 of development.

25. PCA scores plot: Dose-dependent effects of TCE on medaka metabolome PC1 score PC2 score 2 6 5 4 3 7 8 Day 1 46 ppm TCE Day 7 controls 3 ppm TCE Trajectory?

26. PC1 score PC2 score Permanent toxicant-induced perturbation stage specific toxicity identified for targeted gene expression studies Perturbations to normal developmental trajectory Normal development C. A. Pincetich, et al, Comp. Biochem. Physiol. C 140, 103-113 (2005).

27. Advantages of metabolomics Changes in the levels of individual enzymes: expected to have little effect on measured metabolic fluxes do have significant effects on the conc n of metabolites ‘Downstream’ result of gene expression changes in metabolome are amplified relative to changes in the transcriptome and the proteome.

28. Advantages of metabolomics Metabolomics is complementary to transcriptomics and proteomics, but closer to the phenotype Number of metabolites expected to be smaller than number of genes or proteins (S. cerevisiae 6000 genes and 600 metabolites) Metabolomic analyses can cost up to two thirds less than other ‘omic’ analyses (more appropriate for high-throughput/large sample number studies than proteomics and transcriptomics) Plants have hundreds of thousands different chemical compounds, many still unknown!!!

29. Disadvantages Sometimes chemistry changes, depending on isotope composition Less sensitive than Mass spec

30. Molecular Phenotype Post-genomic Era of Biology Genome Gene expression Proteins Metabolism Metabolomics Proteomics Transcriptomics Genomics Genotype Environmental stressors

31. To Do Find metabolomics experiments on the web and write a report on them and how they relate to the hks rrs