Metabolomics Nature Reviews Drug Discovery Nicholson et al 2002 Ef fic ac To y xic ity Secondary Molecules Fil tra tio n Primary Molecules so Re on i t lu i D Co nce ntr ati on urea hippurate fumarate water creatinine ion rpt TMAO hippurate allantoin creatinine taurine citrate 2 oxoglutarate succinate Adapted from D Robertson Pfizer Global Research and Development Metabolomics Comprehensive Definition The quantitative measurement of the time related multiparametric metabolic response of living systems to pathophysiological exogenous or endogenous stimuli or genetic modification Operational Definition The systematic exploration of biofluid composition using NMR pattern recognition technology in order to associate target organ toxicity with NMR spectral patterns and identify novel surrogate markers of toxicity Adapted from D Robertson Pfizer Global Research and Development Metabolomics The study of the total metabolite pool metabolome metabolic regulation and fluxes in individual cells or cell types Can be achieved through a wide spectrum of technologic methods including LC MS GC MS and nuclear magnetic resonance NMR Metabonomics The study of the systemic biochemical profiles and regulation of function in whole organisms by analyzing a metabolite pool metabolome in biofluids and tissues Usually implies that the study is done specifically through nuclear magnetic resonance profiling Metabolome The quantitative complement of all the low molecular weight molecules present in cells in a particular physiological or developmental state Biofluid A fluid sample obtained from a living system The donor might typically be a human or an animal Fluids can be excreted such as urine sweat expressed or secreted such as milk bile obtained by intervention such as blood plasma serum or cerebrospinal fluid develop as a result of a pathological process such as blister or cyst fluid or be applied and collected such as dialysis fluid From Metabometrix Ltd Advantages of Metabolomics Identification of target organ severity onset duration and reversal of the effects time course Classify sample as normal vs abnormal Determine mechanisms of action within the organ Potential for identifying novel biomarkers of toxic effect Non invasive No a priori decisions about samples need be made No sample processing necessary other than cold collection Complete time course data can readily be obtained Minimization of compound requirements Relatively fast analysis 200 300 samples day Useful tool for modeling physiological variation and exposure conditions in animals and humans Adapted from D Robertson Pfizer Global Research and Development NMR spectroscopy Spectroscopy deals with the interactions between electromagnetic radiation and matter Spectroscopy is used to derive the properties of matter at the molecular level Nuclear magnetic resonance NMR exploits the magnetic properties of atomic nuclei The method functions as follows A substance is placed in a magnetic field Some atomic nuclei e g protons nuclei of hydrogen atoms then behave like microscopic compass needles called nuclear spins Each nuclear spin orientation corresponds to a different energy level The spins may jump between the levels when the sample is exposed to radio waves whose frequency exactly matches the energy spacing This is called resonance One way of measuring the energy is to change the irradiation frequency At resonance the spins flip causing an electric signal The strength of the signal is plotted as a function of frequency in a diagram the NMR spectrum In metabolomics it is the patterns that occur when many different biochemical entities are detected simultaneously in a mixture using 1H NMR that are interpreted From www nobel se NMR in Metabolomics Pro Non destructive Applicable to intact biomaterials More information rich in complex mixture analyses No extraction derivatization is necessary Con Less sensitive than MS History NMR has been used to study metabolites in biofluids for over a decade Metabolomics technology as it is known today 600 MHz 1H NMR was pioneered by Jeremy Nicholson Elaine Holmes and John Lindon of Imperial College in London Only recently have advances in flow through NMR hardware and pattern recognition software made the possibility of high throughput in vivo toxicity assessment a practical possibility NMR Acquisition and Gilson 215 Control System Refrigerated Metabolism Cage 0o C Varian Inova 600 Shielded magnet 120 ul flow probe NMR flow probe NaN3 Biomek Robot Deuterated Buffer TSP N2 gas Gilson 215 autosampler Data Processing Frozen Storage Adapted from D Robertson Pfizer Global Research and Development Adapted from D Robertson Pfizer Global Research and Development Adapted from D Robertson Pfizer Global Research and Development Normal Metabolic Profiles Day 5 Day 4 Day 3 Day 2 Day 1 Adapted from D Robertson Pfizer Global Research and Development Functional NMR Spectrum of Rat Urine Biomarker Windows Nature Reviews Drug Discovery Nicholson et al 2002 Toxicogenomics Hamadeh Afshari eds Wiley Liss 2004 Techniques and Procedures in Metabolomics NMR Spectra Primary Data Processing Unsupervised mapping of data in 3D space Supervised classification and calculation of confidence intervals Nature Reviews Drug Discovery Nicholson et al 2002 Pattern Recognition PR Methods PR and related multivariate statistical approaches can be used to discern significant patterns in complex data sets and are particularly appropriate in situations where there are more variables than samples in the data set The general aim of PR is to classify objects in this case 1H NMR spectra or to predict the origin of objects based on identification of inherent patterns in a set of indirect measurements PR methods can reduce the dimensionality of complex data sets via 2 or 3D mapping procedures thereby facilitating the visualization of inherent patterns in the data Principal Components Analysis PCA This is a data dimension reduction method that involves a mathematical procedure that transforms a number of possibly correlated variables into a smaller number of uncorrelated variables called principal components The first principal component accounts for as much of the variability in the data as possible and each succeeding component accounts for as much of the remaining variability as possible Use of PCA enables the best representation in terms of biochemical variation in the data set to be displayed in two or three dimensions Adapted from D Robertson Pfizer
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