As the human genome sequencing projects near completion, there is an active search for technologies that can provide insights into the genetic basis for physiological variation and interpreting gene expression in terms of phenotype at the whole organism level in order to understand the pathophysiology of disease. We present a novel metabonomic approach to the investigation of genetic influences on metabolic balance and metabolite excretion patterns in two phenotypically normal mouse models (C57BL10J and Alpk:ApfCD). Chemometric techniques were applied to optimise recovery of biochemical information from complex 1 H NMR urine spectra and to determine metabolic biomarker differences between the two strains. Differences were observed in tricarboxylic acid cycle intermediates and methylamine pathway activity. We suggest here a new`metabotype' concept, which will be of value in relating quantitative physiological and biochemical data to both phenotypic and genetic variation in animals and man. ß

Metabolic phenotyping, or metabotyping, is increasingly being used as a probe in functional genomics studies. However, such pro¢ling is subject to intrinsic physiological variation found in all animal populations. Using a nuclear magnetic resonance-based metabonomic approach, we show that diurnal variations in metabolism can obscure the interpretation of strain-related metabolic di¡erences in two phenotypically normal mouse strains (C57BL10J and Alpk:ApfCD). To overcome this problem, diurnal-related metabolic variation was removed from these spectral data by application of orthogonal signal correction (OSC), a data ¢ltering method. Interpretation of the removed orthogonal variation indicated that diurnal-related variation had been removed and that the AM samples contained higher levels of creatine, hippurate, trimethylamine, succinate, citrate and 2-oxo-glutarate and lower levels of taurine, trimethylamine-N-oxide, spermine and 3-hydroxy-iso-valerate relative to the PM samples. We propose OSC will have great potential removing confounding variation obscuring subtle changes in metabolism in functional genomic studies and will be of bene¢t to optimising interpretation of proteomic and genomic datasets. ß

A 'global' model of hERG K(+) channel was built to satisfy three basic criteria for QSAR models in drug discovery: (1) assessment of the applicability domain, (2) assuring that model decisions can be interpreted by medicinal chemists and (3) assessment of model performance after the model was built. A combination of D-optimal onion design and hierarchical partial least squares modelling was applied to construct a global model of hERG blockade in order to maximize the applicability domain of the model and to enhance its interpretability. Additionally, easily interpretable hERG specific fragment-based descriptors were developed. Model performance was monitored, throughout a time period of 15 months, after model implementation. It was found that after this time duration a greater proportion of molecules were outside the model's applicability domain and that these compounds had a markedly higher average prediction error than those from molecules within the model's applicability domain. The model's predictive performance deteriorated within 4 months after building, illustrating the necessity of regular updating of global models within a drug discovery environment.

Abstract-High-resolution 1 H nuclear magnetic resonance (NMR) spectroscopy can be used to produce a biochemical fingerprint of low-molecular-weight metabolites from complex biological mixtures such as tissue extracts and biofluids. Changes in such fingerprint profiles can be used to characterize the effects of toxic insult in in vivo systems. The technique is nonselective and requires little sample preparation or derivatization. In the present study, earthworms (Eisenia veneta) were exposed to three different model xenobiotics by a standard filter paper contact test, and toxicant-induced biochemical changes were then investigated by characterizing the changes in endogenous metabolites visible in 600-MHz 1 H NMR spectra of tissue extracts. The NMR spectral intensities were converted to discrete numerical values and tabulated in order to provide data matrices suitable for multivariate analysis. Principal component analysis showed that changes had occurred in the biochemical profiles relative to the undosed controls. The 2-fluoro-4-methylaniline-treated worms showed a decrease in a resonance from a compound identified as 2-hexyl-5-ethyl-3-furansulfonate using a combination of high-performance liquid chromatography (HPLC)-Fourier transform mass spectrometry (IonSpec, Lake Forest, CA, USA) and 1 H and 13 C NMR spectroscopy. An increase in inosine monophosphate was also observed. The 4-fluoroaniline-treated worms showed a decrease in maltose concentrations, and 3,5-difluoroaniline exerted the same effect as 2-fluoro-4-methylaniline but to a lesser extent. These changes could potentially be used as novel biomarkers of xenobiotic toxicity and could be used to determine the mechanism of action of other toxic chemicals.