Differentiation between Cistus L. (Sub-) Species (Cistaceae) Using NMR Metabolic Fingerprinting.

The genus Cistus is taxonomically complex, as taxonomic classification of individual species based on morphological criteria is often difficult and ambiguous. However, specific species contain valuable natural products, especially terpenoids and polyphenols, which exert various biological effects and might therefore be used for treatment of a broad array of disorders. Hence, a fast and reliable method for clear identification of different Cistus (sub-) species is required. Approaches for analysis of secondary metabolite profiles, e.g., with NMR, might remedy the challenging classification of Cistus (sub-) species and help to identify specific markers for differentiation between them. In the present study, 678 samples from wild-growing Cistus populations, including 7 species and 6 subspecies/varieties thereof, were collected in 3 years from populations in 11 countries all over the Mediterranean basin. Samples were extracted with buffered aqueous methanol and analysed with NMR. From the resulting 1D-1H-NOESY and J-Res profile spectra, marker signals or spectral regions for the individual (sub-) species were identified with multivariate statistical tools. By examining the NMR profiles of these extracts, we were able to identify discriminators and specific markers for the investigated Cistus (sub-) species. Various influencing factors, like (sub-) species, wild harvestings of different populations from several countries, numerous collection sites, different years, and cultivation in greenhouses have been considered in this work. As the here identified markers are independent from these influencing factors, the results can be considered a robust model and might be used for future differentiation between Cistus (sub-) species.

Prebiotic Effects of Partially Hydrolyzed Guar Gum on the Composition and Function of the Human Microbiota-Results from the PAGODA Trial.

(1) Background: Alterations in the structural composition of the human gut microbiota have been identified in various disease entities along with exciting mechanistic clues by reductionist gnotobiotic modeling. Improving health by beneficially modulating an altered microbiota is a promising treatment approach. Prebiotics, substrates selectively used by host microorganisms conferring a health benefit, are broadly used for dietary and clinical interventions. Herein, we sought to investigate the microbiota-modelling effects of the soluble fiber, partially hydrolyzed guar gum (PHGG). (2) Methods: We performed a 9 week clinical trial in 20 healthy volunteers that included three weeks of a lead-in period, followed by three weeks of an intervention phase, wherein study subjects received 5 g PHGG up to three times per day, and concluding with a three-week washout period. A stool diary was kept on a daily basis, and clinical data along with serum/plasma and stool samples were collected on a weekly basis. PHGG-induced alterations of the gut microbiota were studied by 16S metagenomics of the V1-V3 and V3-V4 regions. To gain functional insight, we further studied stool metabolites using nuclear magnetic resonance (NMR) spectroscopy. (3) Results: In healthy subjects, PHGG had significant effects on stool frequency and consistency. These effects were paralleled by changes in α- (species evenness) and ß-diversity (Bray-Curtis distances), along with increasing abundances of metabolites including butyrate, acetate and various amino acids. On a taxonomic level, PHGG intake was associated with a bloom in Ruminococcus, Fusicatenibacter, Faecalibacterium and Bacteroides and a reduction in Roseburia, Lachnospiracea and Blautia. The majority of effects disappeared after stopping the prebiotic and most effects tended to be more pronounced in male participants. (4) Conclusions: Herein, we describe novel aspects of the prebiotic PHGG on compositional and functional properties of the healthy human microbiota.

Metabolomic analysis-Addressing NMR and LC-MS related problems in human feces sample preparation.

Metabolomics is a well-established field in fundamental clinical research with applications in different human body fluids. However, metabolomic investigations in feces are currently an emerging field. Fecal sample preparation is a demanding task due to high complexity and heterogeneity of the matrix. To gain access to the information enclosed in human feces it is necessary to extract the metabolites and make them accessible to analytical platforms like NMR or LC-MS. In this study different pre-analytical parameters and factors were investigated i.e. water content, different extraction solvents, influence of freeze-drying and homogenization, ratios of sample weight to extraction solvent, and their respective impact on metabolite profiles acquired by NMR and LC-MS. The results indicate that profiles are strongly biased by selection of extraction solvent or drying of samples, which causes different metabolites to be lost, under- or overstated. Additionally signal intensity and reproducibility of the measurement were found to be strongly dependent on sample pre-treatment steps: freeze-drying and homogenization lead to improved release of metabolites and thus increased signals, but at the same time induced variations and thus deteriorated reproducibility. We established the first protocol for extraction of human fecal samples and subsequent measurement with both complementary techniques NMR and LC-MS.