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. 2017 Jul 10;12(7):e0180991.
doi: 10.1371/journal.pone.0180991. eCollection 2017.

Taurine does not affect the composition, diversity, or metabolism of human colonic microbiota simulated in a single-batch fermentation system

Affiliations

Taurine does not affect the composition, diversity, or metabolism of human colonic microbiota simulated in a single-batch fermentation system

Kengo Sasaki et al. PLoS One. .

Abstract

Accumulating evidence suggests that dietary taurine (2-aminoethanesulfonic acid) exerts beneficial anti-inflammatory effects in the large intestine. In this study, we investigated the possible impact of taurine on human colonic microbiota using our single-batch fermentation system (Kobe University Human Intestinal Microbiota Model; KUHIMM). Fecal samples from eight humans were individually cultivated with and without taurine in the KUHIMM. The results showed that taurine remained largely undegraded after 30 h of culturing in the absence of oxygen, although some 83% of the taurine was degraded after 30 h of culturing under aerobic conditions. Diversity in bacterial species in the cultures was analyzed by 16S rRNA gene sequencing, revealing that taurine caused no significant change in the diversity of the microbiota; both operational taxonomic unit and Shannon-Wiener index of the cultures were comparable to those of the respective source fecal samples. In addition, principal coordinate analysis indicated that taurine did not alter the composition of bacterial species, since the 16S rRNA gene profile of bacterial species in the original fecal sample was maintained in each of the cultures with and without taurine. Furthermore, metabolomic analysis revealed that taurine did not affect the composition of short-chain fatty acids produced in the cultures. These results, under these controlled but artificial conditions, suggested that the beneficial anti-inflammatory effects of dietary taurine in the large intestine are independent of the intestinal microbiota. We infer that dietary taurine may act directly in the large intestine to exert anti-inflammatory effects.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exist.

Figures

Fig 1
Fig 1. Changes in concentrations of taurine in the Kobe University Human Intestinal Microbiota Model (KUHIMM) cultures.
“Change” indicates the ratio of the concentration at 30 h after the initiation of fermentation to the starting concentration (about 10 mM). Fermentation was initiated by inoculating separate cultures with one of each of the human fecal samples (M39, M38, F40, M43, M60, F62, M25, and M34). In addition, changes in taurine concentration were investigated under aerobic conditions in the KUHIMM following inoculation of 4 separate cultures with one of each of 4 of the human fecal samples (M39, M38, F40, and M34).
Fig 2
Fig 2. Comparison of operational taxonomic unit (OTU) number and bacterial diversity (Shannon-Wiener index) among original fecal samples and respective KUHIMM cultures grown in the absence or presence of taurine following inoculation with one of each of the fecal samples from 8 human subjects (M39, M38, F40, M43, M60, F62, M25, and M34).
Fig 3
Fig 3. Principal coordinate analysis (PCoA).
Samples are color coded as follows: M39, yellow; M38, red; F40, pink; M43, cyan; M60, dark green; F62, gray; M25, green; and M34, blue. Transformations from the original fecal samples to the corresponding KUHIMM culture are shown as arrows. Transformations from the original fecal samples to the corresponding KUHIMM cultures containing taurine are provided but lack an arrow.
Fig 4
Fig 4. Phylum-level compositional view of bacteria in the eight human fecal samples used as inocula (“F”), in corresponding KUHIMM cultures at 30 h after the initiation of fermentation (“C”), and in corresponding KUHIMM cultures containing taurine at 30 h after the initiation of fermentation (“T”).
Individual fecal sample sources are designated as follows: M39 (male, age 39), M38 (male, age 38), F40 (female, age 40), M43 (male, age 43), M60 (male, age 60), F62 (female, age 62), M25 (male, age 25), and M34 (male, age 34). A compositional view of bacterial phyla based on the taxonomic assignment of 16S rRNA genes is shown. Bacterial composition of each sample was estimated based on the results of the RDP classifier.
Fig 5
Fig 5
Time-dependent changes of short-chain fatty acid (SCFA) concentrations in the KUHIMM cultures inoculated with one of each of the human fecal samples (A: M39, B: M38, C: F40, D: M43, E: M60, F: F62, G: M25, H: M34).

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