In this review, metabonomics, a combination of data-rich analytical chemical measurements and chemometrics for profiling metabolism in complex systems, is described and its applications are reviewed. Metabonomics is typically carried out using biofluids or tissue samples. The relevance of the technique is reviewed in relation to other '-omics', and it is shown how the methods can be applied to physiological evaluation, drug safety assessment, characterization of genetically modified animal models of disease, diagnosis of human disease, and drug therapy monitoring. The different types of analytical data, mainly from nuclear magnetic resonance spectroscopy and mass spectrometry, are summarized. The outputs from a metabonomics study allow sample classification, for example according to phenotype, drug safety or disease diagnosis, and interpretation of the reasons for classification yields information on combination biomarkers of effect. Transcriptomic and metabonomic data is currently being further integrated into a holistic understanding of systems biology. An assessment of the possible future role and impact of metabonomics is presented.

Strategies such as genomics, proteomics and metabonomics are being applied with increasing frequency in the pharmaceutical industry. For each of these approaches, toxicological response can be measured by terms of deviation from control or baseline status. However, in order to accurately define drug-induced response, it is necessary to characterize the normal degree of physiological variation in the absence of stimuli. Here, 1 H NMR spectroscopic-based analyses of the metabolic composition of urine in experimental animals under various normal physiological conditions are reviewed. In particular, the effects of inter-animal and diurnal variation, gender, age, diet, species, strain, hormonal status and stress on the biochemical composition of urine are explored. Pattern recognition methods facilitate the comparison of urine NMR spectra over a given time-course, enabling the establishment of changes in profile and highlighting the dynamic metabolic status of an organism. Thus metabonomic approaches based on information-rich spectroscopic data sets can be used to evaluate normal physiological variation and for investigation of drug safety issues.

Recent findings have shown an inverse association between circulating C15:0/C17:0 fatty acids with disease risk, therefore, their origin needs to be determined to understanding their role in these pathologies. Through combinations of both animal and human intervention studies, we comprehensively investigated all possible contributions of these fatty acids from the gut-microbiota, the diet, and novel endogenous biosynthesis. Investigations included an intestinal germ-free study and a C15:0/C17:0 diet dose response study. Endogenous production was assessed through: a stearic acid infusion, phytol supplementation, and a Hacl1 −/− mouse model. Two human dietary intervention studies were used to translate the results. Finally, a study comparing baseline C15:0/C17:0 with the prognosis of glucose intolerance. We found that circulating C15:0/C17:0 levels were not influenced by the gut-microbiota. The dose response study showed C15:0 had a linear response, however C17:0 was not directly correlated. The phytol supplementation only decreased C17:0. Stearic acid infusion only increased C17:0. Hacl1 −/− only decreased C17:0. The glucose intolerance study showed only C17:0