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Randomized Controlled Trial
. 2015 Mar;9(3):552-62.
doi: 10.1038/ismej.2014.177. Epub 2014 Oct 3.

Structural modulation of gut microbiota during alleviation of type 2 diabetes with a Chinese herbal formula

Jia Xu  1 , Fengmei Lian  2 , Linhua Zhao  2 , Yufeng Zhao  3 , Xinyan Chen  2 , Xu Zhang  1 , Yun Guo  2 , Chenhong Zhang  1 , Qiang Zhou  2 , Zhengsheng Xue  1 , Xiaoyan Pang  1 , Liping Zhao  4 , Xiaolin Tong  2
Affiliations
Randomized Controlled Trial

Structural modulation of gut microbiota during alleviation of type 2 diabetes with a Chinese herbal formula

Jia Xu et al. ISME J. 2015 Mar.

Abstract

The gut microbiota is hypothesized to have a critical role in metabolic diseases, including type 2 diabetes (T2D). A traditional Chinese herbal formula, Gegen Qinlian Decoction (GQD), can alleviate T2D. To find out whether GQD modulates the composition of the gut microbiota during T2D treatment, 187 T2D patients were randomly allocated to receive high (HD, n=44), moderate (MD, n=52), low dose GQD (LD, n=50) or the placebo (n=41) for 12 weeks in a double-blinded trial. Patients who received the HD or MD demonstrated significant reductions in adjusted mean changes from baseline of fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) compared with the placebo and LD groups. Pyrosequencing of the V3 regions of 16S rRNA genes revealed a dose-dependent deviation of gut microbiota in response to GQD treatment. This deviation occurred before significant improvement of T2D symptoms was observed. Redundancy analysis identified 47 GQD-enriched species level phylotypes, 17 of which were negatively correlated with FBG and 9 with HbA1c. Real-time quantitative PCR confirmed that GQD significantly enriched Faecalibacterium prausnitzii, which was negatively correlated with FBG, HbA1c and 2-h postprandial blood glucose levels and positively correlated with homeostasis model assessment of β-cell function. Therefore, these data indicate that structural changes of gut microbiota are induced by Chinese herbal formula GQD. Specifically, GQD treatment may enrich the amounts of beneficial bacteria, such as Faecalibacterium spp. In conclusion, changes in the gut microbiota are associated with the anti-diabetic effects of GQD.

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Figures

Figure 1
Figure 1
GQD significantly improved glycemic control and HOMA-β in T2D patients. (a) Change in FBG, (b) change in HbA1c and (c) change in HOMA-β. Placebo (n=41), LD (n=50), MD (n=52) and HD (n=44). Data are presented as mean±S.E.M. *P<0.05, **P<0.01 and ***P<0.001 vs placebo using ANCOVA; +P<0.05, ++P<0.01 and +++P<0.001 vs LD using ANCOVA.
Figure 2
Figure 2
Dose-dependent alterations of the gut microbiota in T2D patients treated with different doses of GQD at weeks 0 and 12. (a) Weighted Unifrac PCoA of gut microbiota based on the OUT data from the first pyrosequencing run. (b) Clustering of gut microbiota based on mahalanobis distances calculated with multivariate analysis of variance (MANOVA). Each point represents the mean principal coordinate (PC) score of all patients in a group at one time point, and the error bar represents the s.e.m. The sample number (n) at week 0: placebo=30, LD=28, MD=32 and HD=28. The sample number (n) at week 12: placebo=30, LD=28, MD=32 and HD=28. ***P<0.0001.
Figure 3
Figure 3
Trajectory of the gut microbiota in T2D patients treated with HD GQD and placebo at weeks 0, 4, 8 and 12. (a) Unweighted Unifrac PCoA of gut microbiota based on the OUT data from the second pyrosequencing run. (b) Clustering of gut microbiota based on mahalanobis distances calculated with multivariate analysis of variance (MANOVA). Each point represents the mean principal coordinate (PC) score of all patients in a group at one time point, and the error bar represents the s.e.m. Placebo: n=36; HD: n=36. ***P<0.0001.
Figure 4
Figure 4
Biplot of redundancy analysis (RDA) of the microbiota composition responding to GQD therapy in T2D patients. The type of treatment and time were used as environmental variables. Responding OTUs that explained more than 4% of the variability of the samples are indicated by blue arrows. Top-left, P-value was obtained by Monte Carlo permutation procedure (MCPP).
Figure 5
Figure 5
Heat map of redundancy analysis (RDA)-identified key OTUs responding to GQD treatment and Spearman's correlation between identified OTUs and HbA1c or FBG. The color of the spots in the left panel represents the mean relative abundance (normalized and log-transformed) of the OTU in each group. The OTUs are organized according to their phylogenetic positions. The color of the spots in the right panel represents R-value of Spearman's correlation between the OTU and HbA1c or FBG. The family and genus names of the OTUs are shown on the right. +P<0.05.
Figure 6
Figure 6
Relative abundance of F. prausnitzii as quantified by q-PCR. (a) The impact of different treatments on the relative abundance of F. prausnitzii before and after treatment. The sample number (n) for each group: placebo=21, LD=19, MD=19 and HD=20. (b) The differences of F. prausnitzii among four groups at week 12. The sample number (n) for each group at week 0: placebo=31, LD=23, MD=26 and HD=29. The sample number for each group at week 12: placebo=26, LD=25, MD=24 and HD=28. ΔP<0.05, ΔΔP<0.05 vs before treatment using Wilcoxon's signed rank test. *P<0.05 and **P<0.01. Placebo, LD, or MD vs HD using Mann–Whitney test. Data are represented as mean±s.e.m.
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