Metabonomic data interpretation

Moreover, there are a number of publicly available free and commercial spectral (e.g., MS- and NMR-based), chemical, and biochemical/metabolic pathway databases that can be useful in identification and characterization of metabolites, as well as interpretation of metabonomics data at a biochemical pathway level. Examples of such databases are listed in Table 10.4. In a very recent publication, Loftus et al. [150] provided an example in which unknown analytes in complex biological matrices can be detected and characterized using high mass accuracy ESI MS" and formula prediction software, as well as by comparison to mass spectral databases, rather than by following the standard identification route via comparison to an authentic standard. This seems to be an attractive and a promising alternative for future profiling studies. 

Metabonomics has changed the way data are analyzed. Instead of the single biomarker concept, the goal is to simultaneously measure the entire range of plasma metabolites to see changes in the patterns of the biomarkers. This requires both analytical platforms that can assess the broad range of metabolites in an individual and the knowledge of metabolism that is necessary to interpret the analytical data. 

Metabonomics has received considerable attention in the toxicological community, but based on published literature, metabonomic applications do not appear to be as widely used as transcriptomics (toxicogenomics). However, this is not a reflection on the utility of the approach, but more likely a consequence of the need to have a complex infrastructure, particularly with respect to data analysis and interpretation in order to carry out the technology. 

Designing a successful metabonomics experiment is truly a multidisciplinary exercise, and one must consider details of the in-life portion, sample collection, sample preparation, analytical data generation, data processing, analysis, and interpretation. The in-life portion involves study subjects selection, acclimatization, dosing or treatment, and sample collection and has been discussed in detail elsewhere (Robertson et al., 2002). The following sections will focus on the remaining steps in this process as it pertains to LC—MS. 

Hnatyshyn S, Sanders M, Shipkova P, Luk E, Warrack B, Reily M, Poster 375 Automated Mass Spectra Interpretation Approach to Data Reduction for LC-MS Metabonomics Analysis, Poster presented at the American Society for Mass Spectrometry Conference, June 5, Denver, CO, 2008... 

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