Additional file 1 of Strain engineering and metabolic flux analysis of a probiotic yeast Saccharomyces boulardii for metabolizing l-fucose, a mammalian mucin component

Additional file 1. Genome-scale metabolic model of Saccharomyces cerevisiae that metabolizes fucose. Table S1. Sequences of the plasmids constructed in this study

Receiver operating characteristic (ROC) curve of 3 combined biomarkers for distinguishing Behcet’s disease (BD) with arthritis from seronegative arthritis (SNA) groups.

<p>Glutamate, citramalate, and valine were selected and validated as putative biomarkers for BD with arthritis for distinguishing BD with arthritis from SNA groups by ROC curve analysis. The sensitivity and specificity were 100% and 61.1%, respectively, and the value of the area under curve (AUC) was 0.870.</p

Identification of 123 metabolites from synovial fluid samples of 24 patients with Behcet’s disease with arthritis and seronegative arthritis using BinBase.

<p>Identification of 123 metabolites from synovial fluid samples of 24 patients with Behcet’s disease with arthritis and seronegative arthritis using BinBase.</p

The orthogonal least square-discriminative analysis (OPLS-DA) of metabolomic profiles of synovial fluids of Behcet’s disease (BD) with arthritis and seronegative arthritis (SNA).

<p>(A) The score plot of the OPLS-DA model for the BD with arthritis and SNA groups (t[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135856#pone.0135856.ref001" target="_blank">1</a>], score of the non-orthogonal component; to[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135856#pone.0135856.ref002" target="_blank">2</a>], score of the orthogonal component). The generated explained variation values, 0.45 of <i>R</i>^<i>2</i><i>X</i> and 0.91 of <i>R</i>^<i>2</i><i>Y</i>, and the predictive capability, 0.64 of <i>Q</i>^<i>2</i> indicated the excellence in modeling and prediction of the OPLS-DA model, respectively, with clear discrimination between BD with arthritis and SNA groups. (B) V-plot with p(corr) and VIP values of 123 different metabolites in OPLS-DA. The metabolites with p(corr) < 0 were those decreased in the BD with arthritis group while the metabolites with p(corr) > 0 were those increased in the BD with arthritis group. The metabolites with VIP > 1 were represented in Fig 1B.</p

MOESM1 of Enhanced production of 2,3-butanediol by engineered Saccharomyces cerevisiae through fine-tuning of pyruvate decarboxylase and NADH oxidase activities

Additional file 1: Table S1. Kinetic constants (Km and Vmax) of Pdc enzymes, Figure S1. Batch cultivation of the BD4 strain and the BD5 strain in minimal medium, Figure S2. Amino acid sequence of the C. tropicalis pyruvate decarboxylase I, Figure S3. In vitro Pdc activities in the control and four engineered S. cerevisiae strains expressing C. tropicalis pyruvate decarboxylase gene (CtPDC1) differentially, Figure S4. Fermentation profiles of the CtPDC1 expressing strains with glucose as a sole carbon source in minimal medium, Figure S5. The NADH and NAD+ concentrations in the BD5_G1CtPDC1_nox strain with various aeration conditions, Figure S6. Profiles of batch cultivations for metabolomic analysis, Figure S7. Principal component analysis (PCA) of intracellular metabolite profiles of BD5_G1CtPDC1 and BD5_G1CtPDC1_nox in different aerobic conditions, Figure S8. Hierarchical clustering analysis (HCA) of metabolite profiles of BD5_G1CtPDC1 and BD5_G1CtPDC1_nox in different aerobic conditions, Figure S9. Comparison of intracellular metabolites between BD5_G1CtPDC1 at aerobic condition (Ct100) and BD5_G1CtPDC1_nox at microaerobic condition (N50), Figure S10. Specific glucose uptake rates of the wild type D452-2 and engineered strains

The intensities of metabolites related to amino acid metabolism (A) and fatty acid metabolism (B).

<p>The intensities of metabolites related to amino acid metabolism (A) and fatty acid metabolism (B).</p

PCA score (A) and loading plots (B) of RA fibroblast-like synoviocytes (FLS), which were not stimulated (Control), stimulated with TNF-α (TNF), and treated with curcumin (Curcumin).

<p>(A) Principal component (PC)1 explained the significant separation of metabolite profiles between the TNF-α-stimulated group on the negative region of the PC1, and the control and curcumin-treated groups on the positive region of the PC1. Further, the control group was clearly separated from the curcumin-treated group on PC2. (B) PC1 was explained by 84 metabolites that correlated positively with the axis, and 35 metabolites that correlated negatively.</p

Hierarchical clustering analysis of 119 identified metabolites from RA FLS.

<p>The results of heat mapping generated through metabolomic analysis and the relevant changes discovered. A heat map showed that the metabolite profiles of controls were similar to those of the curcumin-treated group. Red color reflects an increase, and blue color a decrease.</p