This study employs spectroscopy-based metabolic profiling of fecal extracts from healthy subjects and patients with active or inactive ulcerative colitis (UC) and Crohn's disease (CD) to substantiate the potential use of spectroscopy as a non-invasive diagnostic tool and to characterize the fecal metabolome in inflammatory bowel disease (IBD). Stool samples from 113 individuals (UC 48, CD 44, controls 21) were analyzed by 1 H nuclear magnetic resonance (NMR) spectroscopy (Bruker 600 MHz, Bruker BioSpin, Rheinstetten, Germany). Data were analyzed with principal component analysis and orthogonal-projection to latent structure-discriminant analysis using SIMCA-P ? 12 and MATLAB. Significant differences were found in the metabolic profiles making it possible to differentiate between active IBD and controls and between UC and CD. The metabolites holding differential power primarily belonged to a range of amino acids, microbiota-related short chain fatty acids, and lactate suggestive of an inflammation-driven malabsorption and dysbiosis of the normal bacterial ecology. However, removal of patients with intestinal surgery and anti-TNF-a antibody treatment eliminated the discriminative power regarding UC versus CD. This study consequently demonstrates that 1 H NMR spectroscopy of fecal extracts is a potential non-invasive diagnostic tool and able to characterize the inflammationdriven changes in the metabolic profiles related to malabsorption and dysbiosis. Intestinal surgery and medication are to be accounted for in future studies, as it seems to be factors of importance in the discriminative process.

NMR-based metabonomics has been widely employed to understand the stressor-induced perturbations to mammalian metabolism. However, inter-sample chemical shift variations for metabolites remain an outstanding problem for effective data mining. In this work, we systematically investigated the effects of pH and ionic strength on the chemical shifts for a mixture of 9 urinary metabolites. We found that the chemical shifts were decreased with the rise of pH but increased with the increase of ionic strength, which probably resulted from the pH- and ionic strength-induced alteration to the ionization equilibrium for the function groups. We also found that the chemical shift variations for most metabolites were reduced to less than 0.004 ppm when the pH was 7.1-7.7 and the salt concentration was less than 0.15 M. Based on subsequent optimization to minimize chemical shift variation, sample dilution and maximize the signal-to-noise ratio, we proposed a new buffer system consisting of K(2)HPO(4) and NaH(2)PO(4) (pH 7.4, 1.5 M) with buffer-urine volume ratio of 1 : 10 for human urinary metabonomic studies; we suggest that the chemical shifts for the proton signals of citrate and aromatic signals of histidine be corrected prior to multivariate data analysis especially when high resolution data were employed. Based on these, an optimized sample preparation method has been developed for NMR-based urinary metabonomic studies.

Metabonomic analysis is an important molecular phenotyping method for understanding plant ecotypic variations and gene functions. Here, we systematically characterized the metabonomic variations associated with three Salvia miltiorrhiza Bunge (SMB) cultivars using the combined NMR and LC-DAD-MS detections in conjunction with multivariate data analysis. Our results indicated that NMR methods were effective to quantitatively detect the abundant plant metabolites including both the primary and secondary metabolites whereas the LC-DAD-MS methods were excellent for selectively detecting the secondary metabolites. We found that the SMB metabonome was dominated by 28 primary metabolites including sugars, amino acids, and carboxylic acids and 4 polyphenolic secondary metabolites, among which N-acetylglutamate, asparate, fumurate, and yunnaneic acid D were reported for the first time in this plant. We also found that three SMB cultivars growing at the same location had significant metabonomic differences in terms of metabolisms of carbohydrates, amino acids, and choline, TCA cycle, and the shikimate-mediated secondary metabolisms. We further found that the same SMB cultivar growing at different locations differed in their metabonome. These results provided important information on the ecotypic dependence of SMB metabonome on the growing environment and demonstrated that the combination of NMR and LC-MS methods was effective for plant metabonomic phenotype analysis.