Abstract: Isoflavones are found in leguminous plants, especially soybeans. They have a structural similarity to natural estrogens, which enables them to bind to estrogen receptors and elicit biological activities similar to natural estrogens. They have been suggested to be beneficial for the prevention and therapy of hormone-dependent diseases. After soy products are consumed, the bacteria of the intestinal microflora metabolize isoflavones to metabolites with altered absorption, bioavailability, and estrogenic characteristics. Variations in the effect of soy products have been correlated with the isoflavone metabolites found in plasma and urine samples of the individuals consuming soy products. The beneficial effects of the soy isoflavone daidzin, the glycoside of daidzein, have been reported in individuals producing equol, a reduction product of daidzein produced by specific colonic bacteria in individuals called equol producers. These individuals comprise 30% and 60% of populations consuming Western and soy-rich Asian diets, respectively. Since the higher percentage of equol producers in populations consuming soy-rich diets is correlated with a lower incidence of hormone-dependent diseases, considerable efforts have been made to detect the specific colonic bacteria involved in the metabolism of daidzein to the more estrogenic compound, equol, which should facilitate the investigation of the metabolic activities related to this compound.
Abstract: Currently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism. Advanced sampling procedures (solid-phase and needle traps microextraction) coupled with modern analytical technologies (proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry, ion mobility spectrometry, e-noses, etc.) allow the characterisation of EB composition to an unprecedented level. However, a key challenge in EB analysis is the proper statistical analysis and interpretation of the large and heterogeneous datasets obtained from EB research. There is no standard statistical framework/protocol yet available in literature that can be used for EB data analysis towards discovery of biomarkers for use in a typical clinical setup. Nevertheless, EB analysis has immense potential towards development of biomarkers for the early disease diagnosis of diseases.
Metabolites2014, 4(4), 1101-1118; doi:10.3390/metabo4041101 - published 19 December 2014 Show/Hide Abstract
Abstract: Dietary polyphenols, including red wine phenolic compounds, are extensively metabolized during their passage through the gastrointestinal tract; and their biological effects at the gut level (i.e., anti-inflammatory activity, microbiota modulation, interaction with cells, among others) seem to be due more to their microbial-derived metabolites rather than to the original forms found in food. In an effort to improve our understanding of the biological effects that phenolic compounds exert at the gut level, this paper summarizes the changes observed in the human fecal metabolome after an intervention study consisting of a daily consumption of 250 mL of wine during four weeks by healthy volunteers (n = 33). It assembles data from two analytical approaches: (1) UPLC-ESI-MS/MS analysis of phenolic metabolites in fecal solutions (targeted analysis); and (2) UHPLC-TOF MS analysis of the fecal solutions (non-targeted analysis). Both approaches revealed statistically-significant changes in the concentration of several metabolites as a consequence of the wine intake. Similarity and complementarity between targeted and non-targeted approaches in the analysis of the fecal metabolome are discussed. Both strategies allowed the definition of a complex metabolic profile derived from wine intake. Likewise, the identification of endogenous markers could lead to new hypotheses to unravel the relationship between moderate wine consumption and the metabolic functionality of gut microbiota.
Metabolites2014, 4(4), 1088-1100; doi:10.3390/metabo4041088 - published 11 December 2014 Show/Hide Abstract
Abstract: Heparan sulfate (HS) catabolism begins with endo-degradation of the polysaccharide to smaller HS oligosaccharides, followed by the sequential action of exo-enzymes to reduce these oligosaccharides to monosaccharides and inorganic sulfate. In mucopolysaccharidosis type IIIA (MPS IIIA) the exo-enzyme, N-sulfoglucosamine sulfohydrolase, is deficient resulting in an inability to hydrolyze non-reducing end glucosamine N-sulfate esters. Consequently, partially degraded HS oligosaccharides with non-reducing end glucosamine sulfate esters accumulate. We investigated the distribution of these HS oligosaccharides in tissues of a mouse model of MPS IIIA using high performance liquid chromatography electrospray ionization-tandem mass spectrometry. Oligosaccharide levels were compared to total uronic acid (UA), which was used as a measure of total glycosaminoglycan. Ten oligosaccharides, ranging in size from di- to hexasaccharides, were present in all the tissues examined including brain, spleen, lung, heart, liver, kidney and urine. However, the relative levels varied up to 10-fold, suggesting different levels of HS turnover and storage. The relationship between the di- and tetrasaccharides and total UA was tissue specific with spleen and kidney showing a different disaccharide:total UA ratio than the other tissues. The hexasaccharides showed a stronger correlation with total UA in all tissue types suggesting that hexasaccharides may more accurately reflect the storage burden in these tissues.
Metabolites2014, 4(4), 1034-1087; doi:10.3390/metabo4041034 - published 24 November 2014 Show/Hide Abstract
Abstract: Cell metabolism is the biochemical machinery that provides energy and building blocks to sustain life. Understanding its fine regulation is of pivotal relevance in several fields, from metabolic engineering applications to the treatment of metabolic disorders and cancer. Sophisticated computational approaches are needed to unravel the complexity of metabolism. To this aim, a plethora of methods have been developed, yet it is generally hard to identify which computational strategy is most suited for the investigation of a specific aspect of metabolism. This review provides an up-to-date description of the computational methods available for the analysis of metabolic pathways, discussing their main advantages and drawbacks. In particular, attention is devoted to the identification of the appropriate scale and level of accuracy in the reconstruction of metabolic networks, and to the inference of model structure and parameters, especially when dealing with a shortage of experimental measurements. The choice of the proper computational methods to derive in silico data is then addressed, including topological analyses, constraint-based modeling and simulation of the system dynamics. A description of some computational approaches to gain new biological knowledge or to formulate hypotheses is finally provided.