Metabonomics and MRS BCMB/CHEM 8190

Transcription

1 Metabonomics and MRS BCMB/CHEM 8190

2 Metabolomics, Metabonomics, Metabolic Profiling Definition: The quantitative measurement of the dynamic multi parametric metabolic response of living systems to physiological stimuli or genetic modification. (J.K. Nicholson, J.C. Lindon, E. Holmes, Xenobiotica 29, , 1999) What do you observe? Metabolites the small molecule (< 1500 Da) substrates and products of the complex enzyme networks that support life Why study metabolomics? Metabolite variations are the end product of the action of proteins, which are the end product of gene expression, they correlate more directly with disease, toxicological effects, and environmental variations. References: Wishart, D. S. (2008). Applications of metabolomics in drug discovery and development. Drugs in R&D 9, Lindon, J. C., Holmes, E. & Nicholson, J. K. (2007). Metabonomics in pharmaceutical R & D. Febs Journal 274,

3 bservation of Metabolites Mass Spectrometry (MS) Nuclear Magnetic Resonance (NMR) Advantages High Sensitivity (pico grams) bserve a diverse number of molecular species Simple relationship between observable and molecule: a direct measure of molecular weight Limitations Limited molecular structure detail Requires pre-analysis separation Quantitation is relative and usually requires isotopic labeling Some metabolites are difficult to detect because of ionization difficulties Advantages Real-time application to many systems without pre-treatment Quantitative response to concentrations of metabolites Near universal detection Rich in structural information Limitations Not nearly as sensitive as mass spectrometry (micro grams) Structural analysis is more complex Information content may be overwhelming without isotopic labeling

4 Metabolites at mm Conc. Can be bserved From: Drost, Riddle and Clarke, Med. Phys. (2002)

5 Sigma-Aldrich Some Common Metabolic Cycles

6 Wikipedia

7 Example of a Typical Metabolomics Application: 1H NMR spectra for urine from three different mouse strains Don t actually need assignments to see differences Cloarec et al. (2005) Anal. Chem. 77:

8 Principle Component Analysis or PLS Can be Used to Distinguish Mouse Strains Principle component analysis can be applied: D = A-1 x C x A; A linear combination giving the least correlated representation Can also apply methods such as PLS (projection on latent structure) to pick variables giving highest differentiation of sets -PLS cross-validated scores for the discrimination among 1H NMR urine spectra of three mouse strains.

9 Separating and Assigning Spectra in Mixtures Increases Information Content Statistical Total Correlation Spectroscopy: STCSY Collect 100 1D spectra of samples that vary in composition Reference each to the average of all spectra rder in a matrix, M; of n spectra and v spectral points Construct covariance matrix, C = (1/(n-1)) M t x M If peaks are correlated in amplitude get a cross-peak Numeric example: two line spectra, compounds a and b Ref: Cloarec et al. (2005). Analytical Chemistry 77, a b a b X =

10 A Simple Example: Correlating Peaks in a Mixture of Two Sugar Molecules Glc- Glucose Gal- Galactose Lactose PPM

11 Coupling Constants Distinguish α and β Anomers Also Numbers of Protons on Adjacent Sites Glc- Glucose F - Fructose Sucrose PPM

12 STCSY 2D Spectrum: 150 samples of mixed lactose and sucrose L S L L S S L L L S S S Mixture of lactose and sucrose

13 STCY Spectrum of Mouse Urine Spectrum generated by looking at correlated variations in hundreds of spectra. Coupling between methylenes is shown

14 STCSY Shows Connections Even When no Coupling Exists Couplings between methylene and aromatic protons shown

15 Application to a Time-Evolving Metabolic Sub-System: The Golgi: a biological factory for glycan synthesis NDP-[ 13 C]sugar1 NDP-[ 13 C]sugar2 NDP-[ 13 C]sugar3 Transferase 1 Transferase 2 Transferase 3 H H H H H H H H H NHAc H H Acceptor H H Protein H H H HN H H H H H H H H HN H H Golgi H H H H polysaccharides and glycoproteins

16 Kinetics of Subset of the Glycan Synthesis System: UDP-apiose/UDP-xylose synthase Guyett, P., Glushka, J., Gu, X. G. & Bar-Peled, M. (2009). Carbohydrate Research 344,

17 Following the UDP-apiose/UDP-xylose synthase reaction by 1D 1 H NMR. Time=16hrs 0 hrs This spectrum is particularly well resolved: Can mathematical / statistical methods improve our ability to deconvolute overlapping peaks? Can we fit these time courses to kinetic models in which many enzymes, substrates and products participate?

18 STCSY: Positive and Negative Correlations Indicate Substrate Product Relationships

19 β

20 Metabolic Changes Can Also be Followed in 31 P NMR

21 Magic Angle Spinning of tissue Samples Removes Bulk Susceptibility Effects From: Lindon, Holmes and Nicholson, Prog. NMR Spec. (2004) 45: Fig. 7. (a) The 600 MHz 1H MAS NMR CPMG spectrum of intact control liver tissue; (b) 600 MHz 1H NMR spectrum of a control lipid-soluble liver tissue extract; (c) 600 MHz solvent presaturation 1H NMR spectrum of a control aqueous-soluble liver tissue extract; 3HB, 3-D-hydroxybutyrate; Ala, alanine; Cho, choline; Chol, cholesterol; EDTA, ethylenediaminetetraacetic acid; Glu, glucose; Gln, glutamine; Glu, glutamate; GPC, glycerophosphorylcholine; Gly, glycerol; Ile, isoleucine; LDL, low-density lipoprotein; Leu, leucine; Lys, lysine; PCho, phosphocholine; Phe, phenylalanine; TMA, trimethylamine-n-oxide; Val, valine; VLDL, very low-density lipoprotein.

22 MRS in Monitoring Disease Progression: a Mouse Model of Alzheimer s Disease Figure 1. Changes in brain metabolites as a function of age. 9.4T study on 18μL voxels. Myoinositol is also seen in APP-PS1 mice. (Marjanska,, Ugurbil, Garwood, (2005) PNAS 102,

23 Example of Isotope Editing Using 13 C Acetyl-CoA Synthetase (ACS) Reaction In Vivo MRS/MRI Further transfers of acetyl from Co-A to carnitine occur

24 DNP Enhanced 13 C-Acetate: IV Injection in a Mouse Magnus Karlsson, René Zandt, Pernille R. Jensen, Georg Hansson, Sven Månsson, Anna Gisselsson and Mathilde H. Lerche (2008) Experimental NMR Conference, Asilomar CA