Strict vegetarian diet improves the risk factors associated with metabolic diseases by modulating gut microbiota and reducing intestinal inflammation
Version of Record online: 18 JUL 2013
© 2013 John Wiley & Sons Ltd and Society for Applied Microbiology
Environmental Microbiology Reports
Volume 5, Issue 5, pages 765–775, October 2013
How to Cite
Kim, M.-S., Hwang, S.-S., Park, E.-J. and Bae, J.-W. (2013), Strict vegetarian diet improves the risk factors associated with metabolic diseases by modulating gut microbiota and reducing intestinal inflammation. Environmental Microbiology Reports, 5: 765–775. doi: 10.1111/1758-2229.12079
- Issue online: 2 OCT 2013
- Version of Record online: 18 JUL 2013
- Accepted manuscript online: 26 JUN 2013 12:32PM EST
- Manuscript Accepted: 19 JUN 2013
- Manuscript Received: 16 JUN 2013
- Mid-Career Researcher Program. Grant Number: 2012-0008806
- NRF-2012-Forstering Core Leaders of the Future Basic Science Program
- Seoul Scholarship Foundation
Fig. S1. Changes in blood pressure in subjects consuming an SVD. Systolic and diastolic blood pressure was measured twice a day during the study (A–F) (HA, a; HB, b; HC, c; HD, d; HE, e; and HF, f). Circles indicate systolic blood pressure and squares indicate diastolic blood pressure.
Fig. S2. The dietary intervention induces changes of the gut microbiota over time. To determine whether an SVD causes the changes in the gut microbiota, the communities were compared the community of day 28 as the baseline with those of all other days. The data are based on unweighted UniFrac distance (A) and weighted UniFrac distance (B). The P-values were calculated using Pearson's correlation. The P-values in parenthesis were derived from a linear regression.
Fig. S3. Principal coordinates analysis (PCoA) of the gut microbiota and gut enterotypes. Individual changes in the gut microbial communities (A) were defined according to unweighted UniFrac analysis. The enterotypes (B) were determined by cluster analysis using the partitioning around medoids method based on Jensen–Shannon divergence and visualized by between-class analysis. The genera that make the main contribution to a particular enterotype are indicated around each cluster.
Fig. S4. Quantification of the abundances of the Enterobacteriaceae family and the Gammaproteobacteria phylum. Using quantitative PCR analysis based on 16S rRNA gene sequences, the decrease in the abundances of the Enterobacteriaceae family (A) and the Gammaproteobacteria phylum (B) were observed in subject HA, HC, HE and HF (Pearson's correlation; *P < 0.05).
Fig. S5. Phylogeny of 16S rRNA gene sequences derived from unclassified Lachnospiraceae and Ruminococcaceae. The phylogenetic status of the OTUs (blue) assigned to unclassified Lachnospiraceae and Ruminococcaceae were determined by constructing a phylogenetic tree using the neighbor-joining method based on the V2 region sequences of the 16S rRNA genes. The sequences derived from colonic interfold microbes and from Lachnospiraceae isolates (red) (Nava et al., 2011; Reeves et al., 2012) were included in the phylogeny.
Table S1. Characteristics of the volunteers in this study.
Table S2. Menus of an SVD in the diet therapy.
Table S3. Nutrient components of an SVD [mean ± standard deviation (SD)].
Table S4. Alpha-diversity of the gut microbial communities of the subjects.
Table S5. The changes in the relative and absolute abundances of taxonomic groups mainly affected by an SVD.
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