Metabonomics: Application in Predictive and Mechanistic Toxicology

Abstract

Metabonomics is defined as the “quantitative measurement of time-related multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification” (Nicholson et al., 1999). More practically, metabonomics encompasses the application of nuclear magnetic resonance (NMR) spectroscopy, pattern recognition tools, and multivariate statistical methods to the evaluation of endogenous metabolites in biofluids and tissues. This technology represents a potentially powerful method for determining the systemic response to toxicity or disease. NMR spectroscopy is a nondestructive and noninvasive method that offers the advantages of minimal sample preparation and broad application to a variety of biofluids (including urine, plasma, saliva, etc) and tissues. Sample throughput is high, with analysis time under 30 minutes. For analysis of biofluids, time course evaluations can be readily conducted, providing for assessment of toxic change from onset to resolution. The analytical method is quantitative and provides detailed structural information. Recent efforts have included the use of NMR coupled with mass spectrometry thereby enabling more complete identification of metabolites. On the other hand, the potential disadvantages of NMR spectroscopy include its recognition as a generally insensitive technique, often requiring at least 100 ng of mass for detection. It is also an expensive tool, both in the instrumentation as well as the laboratory requirements to accommodate the instrument and its sensitive magnet (at least 600 MHz). Overall, the advantages of the application for resolving biological problems outweigh the analytical disadvantages of the technology, and over the past 15 years, an extensive body of research has been generated that demonstrates that metabonomic data are useful for assessment of toxic mechanisms, prediction of toxicity, and identification of clinically useful biomarkers (Nicholson et al., 2002). Furthermore, metabonomic applications are essential to the broad evaluation of systems biology and a vital component of the “omic triad” incorporating genomics, proteomics, and metabonomics. The most common metabolites identified by NMR analyses, especially in urine, are typically those associated with major endogenous metabolic pathways such as the Krebs cycle and include intermediates such as citrate, succinate, oxaloacetate, and α-ketoglutarate. Additional metabolites that