PNNL

Abstract

Metabonomics is the latest and least mature of the systems biology triad, which also includes genomics and proteomics, and has its origins in the early orthomolecular medicine work pioneered by Linus Pauling and Arthur Robinson. It was defined by Nicholson and colleagues in 1999 as the quantitative measurement of perturbations in the metabolite complement of an integrated biological system in response to internal or external stimuli, and is often used today to describe many non-global types of metabolite analyses. Applications of metabonomics are extensive and include toxicology, nutrition, pharmaceutical research and development, physiological monitoring and disease diagnosis. For example, blood samples from millions of neonates are tested routinely by mass spectrometry (MS) as a diagnostic tool for inborn errors of metabolism. The metabonome encompasses a wide range of structurally diverse metabolites; therefore, no single analytical platform will be sufficient. Specialized sample preparation and detection techniques are required, and advances in NMR and MS technologies have led to enhanced metabonome coverage, which in turn demands improved data analysis approaches. The role of MS in metabonomics is still evolving as instrumentation and software becomes more sophisticated and as researchers realize the strengths and limitations of current technology. MS offers a wide dynamic range, high sensitivity, and reproducible, quantitative analysis. These attributes are essential for addressing the challenges of metabonomics, as the range of metabolite concentrations easily exceeds nine orders of magnitude in biofluids, and the diversity of molecular species ranges from simple amino and organic acids to lipids and complex carbohydrates. Additional challenges arise in generating a comprehensive metabolite profile, downstream data processing and analysis, and structural characterization of important metabolites. A typical workflow of MS-based metabonomics is shown in Figure 1. Gas chromatography-(GC)-MS was the most commonly used MS-based method for small molecule analysis in the 1970s and 1980s. It is still used today for the detection of many metabolic disorders and plays a strong role in plant metabonomics. Liquid chromatography (LC)-MS approaches have grown in popularity for metabolite studies, due to simpler sample preparation, reduced analysis times through the introduction of ultra-high performance liquid chromatography (UPLC)-MS and the ability to observe a wider range of metabolites. This chapter will discuss the role of MS in metabonomics, the techniques involved in this exciting area, and the current and future applications of the field. The various bioinformatics tools and multivariate analysis techniques used to maximize information recovery and to aid in the interpretation of the very large data sets typically obtained in metabonomics studies will also be discussed. While there are many different MS-based approaches utilized in metabonomics studies, emphasis will be placed on more established methods.