Serum cytokines.

<p><i>Apoe−/−</i> mice were treated with either <i>L. reuteri</i> ATCC 4659, <i>L. reuteri</i> DSM 1798 or <i>L. reuteri</i> L6798 in the drinking water for 12 weeks. Control mice received no bacterial supplement. Mice were fed a high-fat diet with 0.2% cholesterol. Data shown are mean (SD).</p

Primer sequences for RT-PCR quantification of mRNA expression.

<p>Primer sequences for RT-PCR quantification of mRNA expression.</p

No effects of <i>L. reuteri</i> treatment on glucose and insulin tolerance.

<p>Oral glucose (A) and insulin (B) tolerance tests and serum insulin (C) and leptin (D) levels of <i>Apoe−/−</i> mice treated with either <i>L. reuteri</i> ATCC 4659 (ATCC), <i>L. reuteri</i> DSM 1798 (DSM), or <i>L. reuteri</i> L6798 (L6978) in the drinking water for 12 weeks. Control mice received no bacterial supplement. Mice were fed a high-fat diet with 0.2% cholesterol. Data shown are mean (SD). one-way ANOVA was used to compare control mice and the ATCC, DSM and L6798 groups.</p

Liver lipids and gene expression of <i>Apoe−/−</i> mice treated with <i>L. reuteri</i> ATCC 4659, <i>L. reuteri</i> DSM 1798 or <i>L. reuteri</i> L6798 in the drinking water for 12 weeks.

<p>(A) Staining of 8 µm frozen liver sections with Oil-Red-O and haematoxylin/eosin. Stained area vs. total area was calculated to estimate the degree of lipids in the liver. (B) Amount of triglycerides and cholesterol in liver homogenates determined by a colorimetric assay (Infinity, Thermo Fisher Scientific Inc., Middletown, USA). (C–E) Gene expression of <i>Fas</i>, <i>Acc1</i> and <i>Cpt1a</i> in the liver. Expression of the mouse ribosomal protein L32 was used to normalize the expression levels. One-way ANOVA was used to compare control mice and the ATCC, DSM and L6798 groups. Data shown are mean (SD).</p

<i>L. reuteri</i> ATCC 4659 protects against diet-induced obesity in mice.

<p>Body weight gain (A), epididymal (B) and liver (C) weights in <i>Apoe−/−</i> mice treated with either <i>L. reuteri</i> ATCC 4659 (ATCC), <i>L. reuteri</i> DSM 1798 (DSM) or <i>L. reuteri</i> L6798 (L6978) in the drinking water for 12 weeks. Data shown are mean (SD). Repeated measures ANOVA was used to determine significant differences in body weight development between groups (<i>P</i><0.0001 Control vs ATCC, <i>P</i><0.01 Control vs L6798).</p

<i>In vitro</i> co-cultures of human gut bacterial species as predicted from co-occurrence network analysis

<div><p>Network analysis of large metagenomic datasets generated by current sequencing technologies can reveal significant co-occurrence patterns between microbial species of a biological community. These patterns can be analyzed in terms of pairwise combinations between all species comprising a community. Here, we construct a co-occurrence network for abundant microbial species encompassing the three dominant phyla found in human gut. This was followed by an <i>in vitro</i> evaluation of the predicted microbe-microbe co-occurrences, where we chose species pairs <i>Bifidobacterium adolescentis</i> and <i>Bacteroides thetaiotaomicron</i>, as well as <i>Faecalibacterium prausnitzii</i> and <i>Roseburia inulinivorans</i> as model organisms for our study. We then delineate the outcome of the co-cultures when equal distributions of resources were provided. The growth behavior of the co-culture was found to be dependent on the types of microbial species present, their specific metabolic activities, and resulting changes in the culture environment. Through this reductionist approach and using novel <i>in vitro</i> combinations of microbial species under anaerobic conditions, the results of this work will aid in the understanding and design of synthetic community formulations.</p></div

Co-occurrence network of significantly abundant species.

<p>A. Spearman correlation method. B. SparCC method. The nodes represent microbial species from the genus <i>Bacteroides</i> (green), <i>Bifidobacterium</i> (blue), <i>Faecalibacterium</i> (orange) and <i>Roseburia</i> (purple). The thickness of the edges represents the level of association depending on the value of Spearman’s correlation coefficient or the SparCC score respectively. Positive correlations are predicted to exist between species of Faecalibacterium and Roseburia, as shown in gray lines. Negative correlations are predicted to exist between species of Bacteroides and Bifidobacterium, as shown in red lines, except for (<i>Bacteroides pectinophilus</i>).</p

Profiles of log₁₀ 16S rRNA copies, extracellular metabolite concentrations, and pH of <i>Bifidobacterium adolescentis</i> and <i>Bacteroides thetaiotaomicron</i> in mono- and co-cultures in YCGMS (Yeast Casitone glucose maltose starch) medium for 56 h.

<p>A and B. Log₁₀ 16S rRNA copies per ml of culture, C-E. Starch, maltose and glucose consumption. F-H. Acetate, lactate and formate production. I-J. Succinate and propionate production. K. pH profile of mono- and co-cultures of <i>B</i>. <i>adolescentis</i> and <i>B</i>. <i>thetaiotaomicron</i>. BB = co-culture of <i>Bifidobacterium adolescentis</i> and <i>Bacteroides thetaiotaomicron</i>, Bad = mono-culture of <i>B</i>. <i>adolescentis</i>, Bth = mono-culture of <i>B</i>. <i>thetaiotaomicron</i>. Experiments were performed in triplicates and error bars represent the standard deviation between each biological replicate. P-values less than and greater than 0.01 are summarized with two asterisks and ‘non-significant (ns)’ respectively.</p

Co-occurrence network of significantly abundant species.

<p>A. Spearman correlation method. B. SparCC method. The nodes represent microbial species from the genus <i>Bacteroides</i> (green), <i>Bifidobacterium</i> (blue), <i>Faecalibacterium</i> (orange) and <i>Roseburia</i> (purple). The thickness of the edges represents the level of association depending on the value of Spearman’s correlation coefficient or the SparCC score respectively. Positive correlations are predicted to exist between species of Faecalibacterium and Roseburia, as shown in gray lines. Negative correlations are predicted to exist between species of Bacteroides and Bifidobacterium, as shown in red lines, except for (<i>Bacteroides pectinophilus</i>).</p

Diabetes incidence and insulitis in NOD mice.

<p>(A) Cumulative diabetes incidence in male and female GF and CONV-R mice. (B) Representative images of islets in four insulitis categories: 0 (no infiltration); p.i. (peri-insulitis); <50% destruction; >50% destruction. Scale bar represents 100 µm. (C, D) Distribution of islet scores and average insulitis score in GF and CONVR male (C) and female (D) mice at 4, 9 and 23 weeks (n = 6–7). Data are presented as mean ± s.e.m. **p<0.01 determined by Student's <i>t</i>-test.</p