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Dietary Modulation of Gut Microbiota Contributes to Alleviation of Both Genetic and Simple Obesity in Children.

Zhang C, Yin A, Li H, Wang R, Wu G, Shen J, Zhang M, Wang L, Hou Y, Ouyang H, Zhang Y, Zheng Y, Wang J, Lv X, Wang Y, Zhang F, Zeng B, Li W, Yan F, Zhao Y, Pang X, Zhang X, Fu H, Chen F, Zhao N, Hamaker BR, Bridgewater LC, Weinkove D, Clement K, Dore J, Holmes E, Xiao H, Zhao G, Yang S, Bork P, Nicholson JK, Wei H, Tang H, Zhang X, Zhao L - EBioMedicine (2015)

Bottom Line: NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations.Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut.A diet rich in non-digestible but fermentable carbohydrates significantly promoted beneficial groups of bacteria and reduced toxin-producers, which contributes to the alleviation of metabolic deteriorations in obesity regardless of the primary driving forces.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Microbial Metabolism and Ministry of Education Key Laboratory of Systems Biomedicine, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.

ABSTRACT

Unlabelled: Gut microbiota has been implicated as a pivotal contributing factor in diet-related obesity; however, its role in development of disease phenotypes in human genetic obesity such as Prader-Willi syndrome (PWS) remains elusive. In this hospitalized intervention trial with PWS (n = 17) and simple obesity (n = 21) children, a diet rich in non-digestible carbohydrates induced significant weight loss and concomitant structural changes of the gut microbiota together with reduction of serum antigen load and alleviation of inflammation. Co-abundance network analysis of 161 prevalent bacterial draft genomes assembled directly from metagenomic datasets showed relative increase of functional genome groups for acetate production from carbohydrates fermentation. NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations. Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut. When transplanted into germ-free mice, the pre-intervention gut microbiota induced higher inflammation and larger adipocytes compared with the post-intervention microbiota from the same volunteer. Our multi-omics-based systems analysis indicates a significant etiological contribution of dysbiotic gut microbiota to both genetic and simple obesity in children, implicating a potentially effective target for alleviation.

Research in context: Poorly managed diet and genetic mutations are the two primary driving forces behind the devastating epidemic of obesity-related diseases. Lack of understanding of the molecular chain of causation between the driving forces and the disease endpoints retards progress in prevention and treatment of the diseases. We found that children genetically obese with Prader-Willi syndrome shared a similar dysbiosis in their gut microbiota with those having diet-related obesity. A diet rich in non-digestible but fermentable carbohydrates significantly promoted beneficial groups of bacteria and reduced toxin-producers, which contributes to the alleviation of metabolic deteriorations in obesity regardless of the primary driving forces.

No MeSH data available.


Related in: MedlinePlus

Changes of co-metabolism between host and gut microbiota. (a) Co-inertia analysis (CIA) of relationships between the metabolomics PCA (end of lines with empty symbol) and microbiota CAGs PCA (end of lines with solid symbol). (b) Bacterial CAGs significantly associated with the key metabolites modulated by the intervention. The bootstrapped Spearman correlation coefficient between the 161 prevalent bacterial CAGs and the key metabolites was more than 0.4 and FDR < 0.001. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red and blue colors indicating positive and negative correlations, respectively. (c) Species interaction network of the bacterial CAGs significantly associated with indoxyl sulfate. Only the bacterial CAGs with high quality draft genomes are shown here. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red colors indicating positive correlations. The triangle represents the presence of the tryptophanase gene. (d) Species interaction network of the bacterial CAGs significantly associated with TMAO. Only the bacterial CAGs with high quality draft genomes are shown here. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red colors indicating positive correlations. The triangle represents the presence of the gene cluster encoding choline TMA-lyase and choline TMA-lyase-activating enzyme.
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f0030: Changes of co-metabolism between host and gut microbiota. (a) Co-inertia analysis (CIA) of relationships between the metabolomics PCA (end of lines with empty symbol) and microbiota CAGs PCA (end of lines with solid symbol). (b) Bacterial CAGs significantly associated with the key metabolites modulated by the intervention. The bootstrapped Spearman correlation coefficient between the 161 prevalent bacterial CAGs and the key metabolites was more than 0.4 and FDR < 0.001. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red and blue colors indicating positive and negative correlations, respectively. (c) Species interaction network of the bacterial CAGs significantly associated with indoxyl sulfate. Only the bacterial CAGs with high quality draft genomes are shown here. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red colors indicating positive correlations. The triangle represents the presence of the tryptophanase gene. (d) Species interaction network of the bacterial CAGs significantly associated with TMAO. Only the bacterial CAGs with high quality draft genomes are shown here. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red colors indicating positive correlations. The triangle represents the presence of the gene cluster encoding choline TMA-lyase and choline TMA-lyase-activating enzyme.

Mentions: Co-inertia analysis between the 376 bacterial CAGs and the urine metabolome revealed a significant co-variation between them (R = 0.52, P < 0.01, Figs. 6a and S32). Bootstrapped Spearman correlation analysis identified all bacterial CAGs (/r/ > 0.4 and FDR < 0.01) that were either positively or negatively associated with the key metabolites significantly modulated by the dietary intervention (Fig. 6b). Among the bacterial CAGs positively correlated with the potentially toxic metabolite indoxyl sulfate, nine from GIG7 and 18 (most of them are Bacteroides spp. and Alistipes spp.) contained the gene for tryptophanase (Fig. 6c), which transforms tryptophan to indole (Deeley and Yanofsky, 1982). Among those positively correlated with metabolically toxic TMAO, 13 bacterial CAGs from GIG7, 8, 14, 15, 16, and 18 (mostly in Ruminococcus spp., Parabacteroides spp. and Bacteroides spp.) had the gene cluster encoding choline TMA-lyase and choline TMA-lyase-activating enzyme (Fig. 6d), which are key for anaerobic choline degradation (Craciun and Balskus, 2012). The respective strains are the likely candidates for producing indole and TMA in the gut. They all belong to GIGs, which were reduced after the intervention (Fig. 3e). Their reduction may have contributed to the alleviation of the metabolic deteriorations in both genetic and diet-induced obesity.


Dietary Modulation of Gut Microbiota Contributes to Alleviation of Both Genetic and Simple Obesity in Children.

Zhang C, Yin A, Li H, Wang R, Wu G, Shen J, Zhang M, Wang L, Hou Y, Ouyang H, Zhang Y, Zheng Y, Wang J, Lv X, Wang Y, Zhang F, Zeng B, Li W, Yan F, Zhao Y, Pang X, Zhang X, Fu H, Chen F, Zhao N, Hamaker BR, Bridgewater LC, Weinkove D, Clement K, Dore J, Holmes E, Xiao H, Zhao G, Yang S, Bork P, Nicholson JK, Wei H, Tang H, Zhang X, Zhao L - EBioMedicine (2015)

Changes of co-metabolism between host and gut microbiota. (a) Co-inertia analysis (CIA) of relationships between the metabolomics PCA (end of lines with empty symbol) and microbiota CAGs PCA (end of lines with solid symbol). (b) Bacterial CAGs significantly associated with the key metabolites modulated by the intervention. The bootstrapped Spearman correlation coefficient between the 161 prevalent bacterial CAGs and the key metabolites was more than 0.4 and FDR < 0.001. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red and blue colors indicating positive and negative correlations, respectively. (c) Species interaction network of the bacterial CAGs significantly associated with indoxyl sulfate. Only the bacterial CAGs with high quality draft genomes are shown here. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red colors indicating positive correlations. The triangle represents the presence of the tryptophanase gene. (d) Species interaction network of the bacterial CAGs significantly associated with TMAO. Only the bacterial CAGs with high quality draft genomes are shown here. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red colors indicating positive correlations. The triangle represents the presence of the gene cluster encoding choline TMA-lyase and choline TMA-lyase-activating enzyme.
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Related In: Results  -  Collection

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f0030: Changes of co-metabolism between host and gut microbiota. (a) Co-inertia analysis (CIA) of relationships between the metabolomics PCA (end of lines with empty symbol) and microbiota CAGs PCA (end of lines with solid symbol). (b) Bacterial CAGs significantly associated with the key metabolites modulated by the intervention. The bootstrapped Spearman correlation coefficient between the 161 prevalent bacterial CAGs and the key metabolites was more than 0.4 and FDR < 0.001. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red and blue colors indicating positive and negative correlations, respectively. (c) Species interaction network of the bacterial CAGs significantly associated with indoxyl sulfate. Only the bacterial CAGs with high quality draft genomes are shown here. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red colors indicating positive correlations. The triangle represents the presence of the tryptophanase gene. (d) Species interaction network of the bacterial CAGs significantly associated with TMAO. Only the bacterial CAGs with high quality draft genomes are shown here. Lines between nodes represent correlations between the nodes they connect, with line width indicating the correlation magnitude, and red colors indicating positive correlations. The triangle represents the presence of the gene cluster encoding choline TMA-lyase and choline TMA-lyase-activating enzyme.
Mentions: Co-inertia analysis between the 376 bacterial CAGs and the urine metabolome revealed a significant co-variation between them (R = 0.52, P < 0.01, Figs. 6a and S32). Bootstrapped Spearman correlation analysis identified all bacterial CAGs (/r/ > 0.4 and FDR < 0.01) that were either positively or negatively associated with the key metabolites significantly modulated by the dietary intervention (Fig. 6b). Among the bacterial CAGs positively correlated with the potentially toxic metabolite indoxyl sulfate, nine from GIG7 and 18 (most of them are Bacteroides spp. and Alistipes spp.) contained the gene for tryptophanase (Fig. 6c), which transforms tryptophan to indole (Deeley and Yanofsky, 1982). Among those positively correlated with metabolically toxic TMAO, 13 bacterial CAGs from GIG7, 8, 14, 15, 16, and 18 (mostly in Ruminococcus spp., Parabacteroides spp. and Bacteroides spp.) had the gene cluster encoding choline TMA-lyase and choline TMA-lyase-activating enzyme (Fig. 6d), which are key for anaerobic choline degradation (Craciun and Balskus, 2012). The respective strains are the likely candidates for producing indole and TMA in the gut. They all belong to GIGs, which were reduced after the intervention (Fig. 3e). Their reduction may have contributed to the alleviation of the metabolic deteriorations in both genetic and diet-induced obesity.

Bottom Line: NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations.Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut.A diet rich in non-digestible but fermentable carbohydrates significantly promoted beneficial groups of bacteria and reduced toxin-producers, which contributes to the alleviation of metabolic deteriorations in obesity regardless of the primary driving forces.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Microbial Metabolism and Ministry of Education Key Laboratory of Systems Biomedicine, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.

ABSTRACT

Unlabelled: Gut microbiota has been implicated as a pivotal contributing factor in diet-related obesity; however, its role in development of disease phenotypes in human genetic obesity such as Prader-Willi syndrome (PWS) remains elusive. In this hospitalized intervention trial with PWS (n = 17) and simple obesity (n = 21) children, a diet rich in non-digestible carbohydrates induced significant weight loss and concomitant structural changes of the gut microbiota together with reduction of serum antigen load and alleviation of inflammation. Co-abundance network analysis of 161 prevalent bacterial draft genomes assembled directly from metagenomic datasets showed relative increase of functional genome groups for acetate production from carbohydrates fermentation. NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations. Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut. When transplanted into germ-free mice, the pre-intervention gut microbiota induced higher inflammation and larger adipocytes compared with the post-intervention microbiota from the same volunteer. Our multi-omics-based systems analysis indicates a significant etiological contribution of dysbiotic gut microbiota to both genetic and simple obesity in children, implicating a potentially effective target for alleviation.

Research in context: Poorly managed diet and genetic mutations are the two primary driving forces behind the devastating epidemic of obesity-related diseases. Lack of understanding of the molecular chain of causation between the driving forces and the disease endpoints retards progress in prevention and treatment of the diseases. We found that children genetically obese with Prader-Willi syndrome shared a similar dysbiosis in their gut microbiota with those having diet-related obesity. A diet rich in non-digestible but fermentable carbohydrates significantly promoted beneficial groups of bacteria and reduced toxin-producers, which contributes to the alleviation of metabolic deteriorations in obesity regardless of the primary driving forces.

No MeSH data available.


Related in: MedlinePlus