Metabonomics Data Acquisition Methods

The two principal methods used comprise 1H nuclear magnetic resonance (NMR) spectroscopy and liquid-chromatography mass spectrometry (LC-MS). Nuclear magnetic resonance spectroscopy is nondestructive and provides detailed information on molecular structure, molecular dynamics, and mobility, especially in complex mixture analysis. Mass spectrometry is more sensitive than NMR spectroscopy and is used extensively for molecule identification, but in complex mixtures of very variable composition, the separation step increases variability. Most published studies on mammalian biology have used NMR spectroscopy, but LC-MS techniques with electrospray ionization are increasing in usage.

Typically, metabonomics is carried out on biofluids as these provide an integrated view of systems biology. The biochemical profiles of the main diagnostic fluids reflect both normal variation and the impact of drug toxicity or disease on single or multiple organ systems.[3] Urine and plasma obtained essentially noninvasively are appropriate for clinical trials monitoring and disease diagnosis. However, there is a wide range of fluids that can be, and have been, studied, including cerebrospinal, seminal, amniotic, synovial, digestive, blister and cyst fluids, and lung aspirates and dialysis fluids.[3]

A NMR spectrum of urine contains thousands of sharp lines from predominantly low-molecular weight metabolites (Fig. 1). The position of each spectral band (its chemical shift) gives information on molecular group identity. The splitting pattern on each band (J-coupling) provides knowledge about through-bond connectivity to nearby protons and molecular conformations. The band areas relate to the number of protons giving rise to the peak and hence to the relative concentrations of the substances in the sample. Absolute concentrations can be obtained if an internal standard of known concentration is added to the sample.

Plasma and serum contain both low- and high-molecular weight components, and these give a wide range of signal line widths. Broad bands from protein and lipoprotein signals contribute strongly to the 1H NMR spectra, with sharp peaks from small molecules superimposed. Standard NMR pulse sequences can be used for spectral editing experiments. These are based on molecular diffusion coefficients or on NMR relaxation times and can be used to select only the contributions from macromolecules or the signals from the small molecule metabolites, respectively.

Nuclear magnetic resonance spectra take only a few minutes to acquire using robotic flow-injection methods, with automatic sample preparation involving buffering and addition of D2O as a magnetic field lock signal for the

Fig. 1 1H NMR spectrum of human urine, with expansions showing the level of complexity. Peaks arise from different chemical types of hydrogen in the substances. The areas relate to molar concentrations, and the positions and splittings allow information to be obtained on molecular identity. The signal from water has been suppressed by an NMR procedure to avoid dynamic range errors in the detection process.

Fig. 1 1H NMR spectrum of human urine, with expansions showing the level of complexity. Peaks arise from different chemical types of hydrogen in the substances. The areas relate to molar concentrations, and the positions and splittings allow information to be obtained on molecular identity. The signal from water has been suppressed by an NMR procedure to avoid dynamic range errors in the detection process.

spectrometer. The large NMR signal from water is eliminated by the use of standard NMR solvent suppression methods. Using flow probes, the capacity for NMR analysis has increased and ~ 200 samples can be measured per day. Commercially available cryogenic NMR probes where the detector coil and preamplifier are cooled to around 20 K to provide up to a x 5 reduction in thermal noise. This has permitted the routine use of high-throughput natural abundance 13C NMR spectroscopy of biofluids.

The use of mass spectrometry is increasing,[5] and for applications on biofluids, an HPLC chromatogram is generated with MS detection, using electrospray ionization (usually with both positive and negative ion chromato-grams). At each point in the chromatogram, there is a full mass spectrum and so the data are three-dimensional (3-D), retention time, mass, and intensity, and this can be used as input to pattern-recognition (PR) studies.

The study of small pieces of intact tissues is possible using 1H magic angle spinning (MAS) NMR spectroscopy.1-6"1 Spinning the sample 4-6 kHz typically) at an angle of 54.7° relative to the magnetic field reduces the line broadening effects seen in such heterogeneous, nonliquid samples. Studies have shown that diseased or toxin-affected tissues have characteristically different metabolic profiles to those taken from healthy organs. 1H magic angle spinning NMR spectroscopy can also be used to probe metabolite dynamics and compartmentation. It can also be applied to in vitro systems such as tissue extracts or cell systems such as spheroids. A combined metabonomic analysis of different biofluids, tissue extracts, and intact tissues is possible, providing a comprehensive view of the biochemical responses to a pathological situation, an approach termed integrated metabonomics.

Principal components analysis (PCA), one of the simplest techniques used extensively in metabonomics, allows the expression of most of the variance within a data set using a smaller number of factors or principal components. Each PC is a linear combination of the original data parameters with successive PCs explaining the maximum amount of variance possible, not accounted for by the previous PCs. Each PC is by definition independent of the other PCs. Conversion of the data matrix to PCs results in two matrices, scores and loadings. Scores are the new coordinates for the samples and may be regarded as the new variables, and in a scores plot, each point represents a single NMR spectrum. The PC loadings define the way in which the old variables are linearly combined to form the new variables and indicate which variables carry the greatest weight in transforming the position of the original samples from the data matrix into their new position in the scores matrix. In the loadings plot, each point represents a different NMR spectral region.

Unsupervised methods such as PCA are useful for comparing pathological samples with control samples, but supervised analyses that model each class individually are preferred where the number of classes is large. A widely used supervised method is partial least squares (PLS). This is a method which relates a data matrix containing independent (e.g., spectral) variables to a matrix containing dependent variables (e.g., variables describing the diagnosis) for those samples. Partial least squares can be used to examine the influence of time on a data set, which is useful for biofluid NMR data collected from samples taken over a time course of the progression of a pathological effect. Partial least squares can also be combined with discriminant analysis (DA) to establish the optimal position to place a discriminant surface which best separates classes.

Getting Started With Dumbbells

Getting Started With Dumbbells

The use of dumbbells gives you a much more comprehensive strengthening effect because the workout engages your stabilizer muscles, in addition to the muscle you may be pin-pointing. Without all of the belts and artificial stabilizers of a machine, you also engage your core muscles, which are your body's natural stabilizers.

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