A.A. de Graaf

Linking phylogenetic identities of bacteria to starch fermentation in an in vitro model of the large intestine by RNA-based stable isotope probing

Carbohydrates, including starches, are an important energy source for humans, and are known for their interactions with the microbiota in the digestive tract. Largely, those interactions are thought to promote human health. Using 16S ribosomal RNA (rRNA)-based stable isotope probing (SIP), we identified starch-fermenting bacteria under human colon-like conditions. To the microbiota of the TIM-2 in vitro model of the human colon 7.4 g l(-1) of [U-(13)C]-starch was added. RNA extracted from lumen samples after 0 (control), 2, 4 and 8 h was subjected to density-gradient ultracentrifugation. Terminal-restriction fragment length polymorphism (T-RFLP) fingerprinting and phylogenetic analyses of the labelled and unlabelled 16S rRNA suggested populations related to Ruminococcus bromii, Prevotella spp. and Eubacterium rectale to be involved in starch metabolism. Additionally, 16S rRNA related to that of Bifidobacterium adolescentis was abundant in all analysed fractions. While this might be due to the enrichment of high-GC RNA in high-density fractions, it could also indicate an active role in starch fermentation. Comparison of the T-RFLP fingerprints of experiments performed with labelled and unlabelled starch revealed Ruminococcus bromii as the primary degrader in starch fermentation in the studied model, as it was found to solely predominate in the labelled fractions. LC-MS analyses of the lumen and dialysate samples showed that, for both experiments, starch fermentation primarily yielded acetate, butyrate and propionate. Integration of molecular and metabolite data suggests metabolic cross-feeding in the system, where populations related to Ruminococcus bromii are the primary starch degrader, while those related to Prevotella spp., Bifidobacterium adolescentis and Eubacterium rectale might be further involved in the trophic chain.

Profiling human gut bacterial metabolism and its kinetics using [U-13C]glucose and NMR.

This study introduces a stable‐isotope metabolic approach employing [U‐13C]glucose that, as a novelty, allows selective profiling of the human intestinal microbial metabolic products of carbohydrate food components, as well as the measurement of the kinetics of their formation pathways, in a single experiment. A well‐established, validated in vitro model of human intestinal fermentation was inoculated with standardized gastrointestinal microbiota from volunteers. After culture stabilization, [U‐13C]glucose was added as an isotopically labeled metabolic precursor. System lumen and dialysate samples were taken at regular intervals. Metabolite concentrations and isotopic labeling were determined by NMR, GC, and enzymatic methods. The main microbial metabolites were lactate, acetate, butyrate, formate, ethanol, and glycerol. They together accounted for a 13C recovery rate as high as 91.2%. Using an NMR chemical shift prediction approach, several minor products that showed 13C incorporation were identified as organic acids, amino acids, and various alcohols. Using computer modeling of the 12C contents and 13C labeling kinetics, the metabolic fluxes in the gut microbial pathways for synthesis of lactate, formate, acetate, and butyrate were determined separately for glucose and unlabeled background substrates. This novel approach enables the study of the modulation of human intestinal function by single nutrients, providing a new rational basis for achieving control of the short‐chain fatty acids profile by manipulating substrate and microbiota composition in a purposeful manner. Copyright

In vivo 1H-NMR procedure to determine several rat cerebral metabolite levels simultaneously, undisturbed by water and lipid signals

Methods developed for in vivo 1H-NMR spectroscopy are evaluated and applied using conscious rats. Good quality 1H-spectra of the brain are obtained using a surface coil and a spin echo pulse sequence with the binomial 1-1 and 2-2 water suppression pulses. However, comparing spectra from various rats with each other the water and lipid signals, which cause spectral overlap problems, may differ while the other spectral peaks agree well. Spatially one- and two-dimensional 1H spectroscopic imaging of the rat brain shows that the former signals stem from distinct spatial regions localized close to the rf coil. From a spectroscopic image, a spectrum over a limited spatial region is constructed in which the water signals are strongly reduced, the lipid signals are eliminated and lactic acid can be observed clearly simultaneously with other metabolites.

Measuring non-steady-state metabolic fluxes in starch-converting faecal microbiota in vitro

This paper explores human gut bacterial metabolism of starch using a combined analytical and computational modelling approach for metabolite and flux analysis. Non-steady-state isotopic labelling experiments were performed with human faecal microbiota in a well-established in vitro model of the human colon. After culture stabilisation, [U-13C] starch was added and samples were taken at regular intervals. Metabolite concentrations and 13C isotopomeric distributions were measured amongst other things for acetate, propionate and butyrate by mass spectrometry and NMR. The vast majority of metabolic flux analysis methods based on isotopomer analysis published to date are not applicable to metabolic non-steady-state experiments. We therefore developed a new ordinary differential equation-based representation of a metabolic model of human faecal microbiota to determine eleven metabolic parameters that characterised the metabolic flux distribution in the isotope labelling experiment. The feasibility of the model parameter quantification was demonstrated on noisy in silico data using a downhill simplex optimisation, matching simulated labelling patterns of isotopically labelled metabolites with measured metabolite and isotope labelling data. Using the experimental data, we determined an increasing net label influx from starch during the experiment from 94±1 µmol/l/min to 133±3 µmol/l/min. Only about 12% of the total carbon flux from starch reached propionate. Propionate production mainly proceeded via succinate with a small contribution via acrylate. The remaining flux from starch yielded acetate (35%) and butyrate (53%). Interpretation of 13C NMR multiplet signals further revealed that butyrate, valerate and caproate were mainly synthesised via cross-feeding, using acetate as a co-substrate. This study demonstrates for the first time that the experimental design and the analysis of the results by computational modelling allows the determination of time-resolved effects of nutrition on the flux distribution within human faecal microbiota in metabolic non-steady-state.