Gut microbial activity as influenced by fiber digestion: dynamic metabolomics in an in vitro colon simulator

Understanding the interaction between the gut microbial activity and the host is essential, and in vitro models are being used to test and develop hypotheses regarding the impact of food components/drugs on the human gut ecosystem. However, while in vitro models provide excellent possibilities for dynamic investigations, studies have commonly been restricted to analyses of few, targeted metabolites. In the present study, we employed NMR-based metabolomics combined with multilevel data analysis as a tool to characterize the impact of polydextrose (PDX) fiber on the in vitro derived fecal metabolome. This approach enabled us to identify and quantify the fiber-induced response on several fecal metabolites; we observed higher levels of butyrate, acetate, propionate, succinate, N-acetyl compound and a lower level of amino acids (leucine, valine, isoleucine, phenylalanine, and lysine), valerate, formate, isovalerate and trimethylamine among the PDX-treated sample compared to the control samples. In addition, by the application of multilevel data analysis we were able to examine the specific inter-individual variations, and caprylic acid was identified to be the main marker of distinct microbial compositions among the subjects. Our work is expected to provide a useful approach to understand the metabolic impact of potential prebiotic compounds and get deeper insight into the molecular regulation of gut-microbe activities in the complex gut system

Water diffusion in atmospherically relevant α-pinene secondary organic material

Secondary organic material (SOM) constitutes a large mass fraction of atmospheric aerosol particles. Understanding its impact on climate and air quality relies on accurate models of interactions with water vapour. Recent research shows that SOM can be highly viscous and can even behave mechanically like a solid, leading to suggestions that particles exist out of equilibrium with water vapour in the atmosphere. In order to quantify any kinetic limitation we need to know water diffusion coefficients for SOM, but this quantity has, until now, only been estimated and has not yet been measured. We have directly measured water diffusion coefficients in the water soluble fraction of α-pinene SOM between 240 and 280 K. Here we show that, although this material can behave mechanically like a solid, at 280 K water diffusion is not kinetically limited on timescales of 1 s for atmospheric-sized particles. However, diffusion slows as temperature decreases. We use our measured data to constrain a Vignes-type parameterisation, which we extend to lower temperatures to show that SOM can take hours to equilibrate with water vapour under very cold conditions. Our modelling for 100 nm particles predicts that under mid to upper tropospheric conditions radial inhomogeneities in water content produce a low viscosity surface region and more solid interior, with implications for heterogeneous chemistry and ice nucleation

Creatine-induced activation of antioxidative defence in myotube cultures revealed by explorative NMR-based metabonomics and proteomics

<p>Abstract</p> <p>Background</p> <p>Creatine is a key intermediate in energy metabolism and supplementation of creatine has been used for increasing muscle mass, strength and endurance. Creatine supplementation has also been reported to trigger the skeletal muscle expression of insulin like growth factor I, to increase the fat-free mass and improve cognition in elderly, and more explorative approaches like transcriptomics has revealed additional information. The aim of the present study was to reveal additional insight into the biochemical effects of creatine supplementation at the protein and metabolite level by integrating the explorative techniques, proteomics and NMR metabonomics, in a systems biology approach.</p> <p>Methods</p> <p>Differentiated mouse myotube cultures (C2C12) were exposed to 5 mM creatine monohydrate (CMH) for 24 hours. For proteomics studies, lysed myotubes were analyzed in single 2-DGE gels where the first dimension of protein separation was pI 5-8 and second dimension was a 12.5% Criterion gel. Differentially expressed protein spots of significance were excised from the gel, desalted and identified by peptide mass fingerprinting using MALDI-TOF MS. For NMR metabonomic studies, chloroform/methanol extractions of the myotubes were subjected to one-dimensional ¹H NMR spectroscopy and the intracellular oxidative status of myotubes was assessed by intracellular DCFH₂oxidation after 24 h pre-incubation with CMH.</p> <p>Results</p> <p>The identified differentially expressed proteins included vimentin, malate dehydrogenase, peroxiredoxin, thioredoxin dependent peroxide reductase, and 75 kDa and 78 kDa glucose regulated protein precursors. After CMH exposure, up-regulated proteomic spots correlated positively with the NMR signals from creatine, while down-regulated proteomic spots were negatively correlated with these NMR signals. The identified differentially regulated proteins were related to energy metabolism, glucose regulated stress, cellular structure and the antioxidative defence system. The suggested improvement of the antioxidative defence was confirmed by a reduced intracellular DCFH₂oxidation with increasing concentrations of CMH in the 24 h pre-incubation medium.</p> <p>Conclusions</p> <p>The explorative approach of this study combined with the determination of a decreased intracellular DCFH₂oxidation revealed an additional stimulation of cellular antioxidative mechanisms when myotubes were exposed to CMH. This may contribute to an increased exercise performance mediated by increased ability to cope with training-induced increases in oxidative stress.</p

Data mining of high density genomic variant data for prediction of Alzheimer's disease risk

<p>Abstract</p> <p>Background</p> <p>The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.</p> <p>Methods</p> <p>Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.</p> <p>Results</p> <p>The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with <it>APOE and GAB2 </it>SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with <it>ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH </it>respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included <it>APOE </it>and <it>GAB2 </it>SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.</p> <p>Conclusions</p> <p>With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.</p

Postprandial differences in the plasma metabolome of healthy Finnish subjects after intake of a sourdough fermented endosperm rye bread versus white wheat bread

<p>Abstract</p> <p>Background</p> <p>The mechanism behind the lowered postprandial insulin demand observed after rye bread intake compared to wheat bread is unknown. The aim of this study was to use the metabolomics approach to identify potential metabolites related to amino acid metabolism involved in this mechanism.</p> <p>Methods</p> <p>A sourdough fermented endosperm rye bread (RB) and a standard white wheat bread (WB) as a reference were served in random order to 16 healthy subjects. Test bread portions contained 50 g available carbohydrate. <it>In vitro </it>hydrolysis of starch and protein were performed for both test breads. Blood samples for measuring glucose and insulin concentrations were drawn over 4 h and gastric emptying rate (GER) was measured. Changes in the plasma metabolome were investigated by applying a comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry metabolomics platform (GC×GC-TOF-MS).</p> <p>Results</p> <p>Plasma insulin response to RB was lower than to WB at 30 min (P = 0.004), 45 min (P = 0.002) and 60 min (P < 0.001) after bread intake, and plasma glucose response was significantly higher at time point 90 min after RB than WB intake (P = 0.045). The starch hydrolysis rate was higher for RB than WB, contrary to the <it>in vitro </it>protein digestibility. There were no differences in GER between breads. From 255 metabolites identified by the metabolomics platform, 26 showed significant postprandial relative changes after 30 minutes of bread intake (p and q values < 0.05). Among them, there were changes in essential amino acids (phenylalanine, methionine, tyrosine and glutamic acid), metabolites involved in the tricarboxylic acid cycle (alpha-ketoglutaric, pyruvic acid and citric acid) and several organic acids. Interestingly, the levels of two compounds involved in the tryptophan metabolism (picolinic acid, ribitol) significantly changed depending on the different bread intake.</p> <p>Conclusions</p> <p>A single meal of a low fibre sourdough rye bread producing low postprandial insulin response brings in several changes in plasma amino acids and their metabolites and some of these might have properties beneficial for health.</p

Multivariate paired data analysis: multilevel PLSDA versus OPLSDA

Metabolomics data obtained from (human) nutritional intervention studies can have a rather complex structure that depends on the underlying experimental design. In this paper we discuss the complex structure in data caused by a cross-over designed experiment. In such a design, each subject in the study population acts as his or her own control and makes the data paired. For a single univariate response a paired t-test or repeated measures ANOVA can be used to test the differences between the paired observations. The same principle holds for multivariate data. In the current paper we compare a method that exploits the paired data structure in cross-over multivariate data (multilevel PLSDA) with a method that is often used by default but that ignores the paired structure (OPLSDA). The results from both methods have been evaluated in a small simulated example as well as in a genuine data set from a cross-over designed nutritional metabolomics study. It is shown that exploiting the paired data structure underlying the cross-over design considerably improves the power and the interpretability of the multivariate solution. Furthermore, the multilevel approach provides complementary information about (I) the diversity and abundance of the treatment effects within the different (subsets of) subjects across the study population, and (II) the intrinsic differences between these study subjects

Schizophrenia in Thailand: prevalence and burden of disease

Background: A previous estimate of the burden of schizophrenia in Thailand relied on epidemiological estimates from elsewhere. The aim of this study is to estimate the prevalence and disease burden of schizophrenia in Thailand using local data sources that recently have become available

Limits on WWZ and WW\gamma couplings from p\bar{p}\to e\nu jj X events at \sqrt{s} = 1.8 TeV

We present limits on anomalous WWZ and WW-gamma couplings from a search for WW and WZ production in p-bar p collisions at sqrt(s)=1.8 TeV. We use p-bar p -> e-nu jjX events recorded with the D0 detector at the Fermilab Tevatron Collider during the 1992-1995 run. The data sample corresponds to an integrated luminosity of 96.0+-5.1 pb^(-1). Assuming identical WWZ and WW-gamma coupling parameters, the 95% CL limits on the CP-conserving couplings are -0.33<lambda<0.36 (Delta-kappa=0) and -0.43<Delta-kappa<0.59 (lambda=0), for a form factor scale Lambda = 2.0 TeV. Limits based on other assumptions are also presented.Comment: 11 pages, 2 figures, 2 table

Analyzing and Mapping Sweat Metabolomics by High-Resolution NMR Spectroscopy

The content of human sweat is studied by high-resolution NMR, and the majority of organic components most often found in sweat of conditionally healthy people are identified. Original and simple tools are designed for sweat sampling from different areas of human body. The minimal surface area needed for sampling is in the range of 50–100 cm2. On all the surface parts of the human body examined in this work, the main constituents forming a sweat metabolic profile are lactate, glycerol, pyruvate, and serine. The only exception is the sole of the foot (planta pedis), where trace amounts of glycerol are found. An attempt is made to explain the presence of specified metabolites and their possible origin