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. 2017 Feb 14:8:197.
doi: 10.3389/fmicb.2017.00197. eCollection 2017.

"V体育官网入口" Impact of Westernized Diet on Gut Microbiota in Children on Leyte Island

Jiro Nakayama  1 , Azusa Yamamoto  1 , Ladie A Palermo-Conde  2 , Kanako Higashi  1 , Kenji Sonomoto  1 , Julie Tan  2 , Yuan-Kun Lee  3
Affiliations

Impact of Westernized Diet on Gut Microbiota in Children on Leyte Island

Jiro Nakayama et al. Front Microbiol. .

Abstract

Urbanization has changed life styles of the children in some towns and cities on Leyte island in the Philippines. To evaluate the impact of modernization in dietary habits on gut microbiota, we compared fecal microbiota of 7 to 9-year-old children from rural Baybay city (n = 24) and urban Ormoc city (n = 19), and assessed the correlation between bacterial composition and diet. A dietary survey indicated that Ormoc children consumed fast food frequently and more meat and confectionary than Baybay children, suggesting modernization/westernization of dietary habits. Fat intake accounted for 27. 2% of the total energy intake in Ormoc children; this was remarkably higher than in their Baybay counterparts (18. 1%) and close to the upper limit (30%) recommended by the World Health Organization. Their fecal microbiota were analyzed by high-throughput 16S rRNA gene sequencing in conjunction with a dataset from five other Asian countries. Their microbiota were classified into two enterotype-like clusters with the other countries' children, each defined by high abundance of either Prevotellaceae (P-type) or Bacteroidaceae (BB-type), respectively. Baybay and Ormoc children mainly harbored P-type and BB-type, respectively. Redundancy analysis showed that P-type favored carbohydrates whereas BB-type preferred fats. Fat intake correlated positively with the Firmicutes-to-Bacteroidetes (F/B) ratio and negatively with the relative abundance of the family Prevotellaceae/genus Prevotella. A species-level analysis suggested that dietary fat positively correlated with an Oscillibacter species as well as a series of Bacteroides/Parabacteroides species, whereas dietary carbohydrate positively correlated with Dialister succinatiphilus known as succinate-utilizing bacteria and some succinate-producing species of family Prevotellaceae, Veillonellaceae, and Erysipelotrichaceae VSports手机版. We also found that a Succinivibrio species was overrepresented in the P-type community, suggesting the syntroph via hydrogen and succinate. Predicted metagenomics suggests that BB-type microbiota is well nourished and metabolically more active with simple sugars, amino acids, and lipids, while P-type community is more involved in digestion of complex carbohydrates. Overweight and obese children living in Ormoc, who consumed a high-fat diet, harbored microbiota with higher F/B ratio and low abundance of Prevotella. The altered gut microbiota may be a sign of a modern diet-associated obesity among children in developing areas. .

Keywords: 16S rRNA gene sequencing; Bacteroidetes; Firmicutes; Philippines; Prevotella; gut microbiota; high-fat diet; obesity. V体育安卓版.

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FIGURE 1
FIGURE 1
Geographic location of Baybay and Ormoc, and dietary habits of school-age children in these cities. (A) Map of east and southeast Asia with a detailed view of Leyte island indicating the location of Baybay and Ormoc. The scale bar in the enlarged map indicates 50 km. (B) Composition of daily dietary intake in children of Baybay (n = 24) and Ormoc (n = 16). The contribution of each food was estimated from the parents’ answers to the food frequency questionnaire (FFQ) and was converted to energy units (kcal) according to the databases of energy and nutrition composition of food. The average per city is presented. Red and blue asterisks indicate significantly higher in Baybay and Ormoc children, respectively, with ∗p < 0.05 (single asterisk) or ∗∗p < 0.001 (double asterisks) in Wilcoxon rank-sum test. Variation across individual of this dataset is shown in Supplementary Figure S2. (C) Nutrient composition (in %) of the overall dietary intake in children from Baybay and Ormoc. The energy ratio of macronutrients (kcal/day) was estimated according to the same data and databases as in (B), averaged per city, and represented as pie charts. Variation across individual of this dataset is shown in Supplementary Figure S3.
FIGURE 2
FIGURE 2
Principal component analysis (PCA) and clustering of gut bacterial community of 43 Leyte children and 295 Asian Microbiome Project (AMP) Phase I children. (A) PCA plot of 338 children samples. Family level bacterial composition of 338 samples was subjected to PCA and the first two principal components, PC1 and PC2, were plotted. “O,” Ormoc children; “B,” Baybay children; colored circles, countries of the AMP Phase I study. Percentage values in parentheses next to PC1 and PC2 represents percentage of variance explained by each component. (B) Clustering of the 338 samples. The family level composition data were subjected to Jensen–Shannon divergence and partitioning around medoids cluster analysis. To maximize the Calinski–Harabasz index, an optimal number of clusters was chosen; the result was then validated based on prediction strength (PS) and average silhouette width (SW). The clustering result is displayed using the PCA plot. The center of gravity of each cluster is indicated by a rectangle with the name of a type of microbiota. The colored ellipse covers 67% of the samples belonging to a cluster. The five largest PCA loadings of bacterial families are indicated by arrows next to their family names.
FIGURE 3
FIGURE 3
Characteristics of the gut bacterial community in Leyte children. (A) Relative abundance of five major bacterial families in fecal samples of Baybay (n = 24) and Ormoc (n = 19) children (left panel) and of P-type (n = 25) and BB-type (n = 18) children (right panel). The box plots show the smallest and largest values, 25 and 75% quartiles, the median, and outliers. Bif, Bifidobacteriaceae; Bac, Bacteroidaceae; Pre, Prevotellaceae; Lac, Lachnospiraceae, Rum, Ruminococcaceae. The Wilcoxon rank-sum test was performed to detect statistical differences between the two cities and the p-value is shown over the tested pair of box plots. (B) Rarefaction curve of the number of OTUs observed in samples from Baybay and Ormoc children (left panel) and from P-type and BB-type children (right panel). The number of OTUs was determined in each sample at each sequencing depth. The mean and standard deviation of each group are shown in the rarefaction plot. (C) Alpha-diversities of fecal bacterial community in individual samples from Baybay and Ormoc children (left three panels) and from P-type and BB-type children (right three panels). Individual OTU-composition data (OTU table) were rarified using 5,000 reads per participant in ten iterations. The number of observed OTUs, PD_whole_tree, and Shannon–Wiener index were calculated for each rarified OTU composition and averaged within the 10 iterations. The covariance of these calculated indices was computed for each country and was graphed as a box plot showing the smallest and largest values, 25 and 75% quartiles, the median, and outliers. It is noted that Shannon–Wiener index represents an entropic index but not itself diversity which should be expressed as the exponential of this value.
FIGURE 4
FIGURE 4
Correlation between dietary nutrients and gut bacterial communities in Leyte children. (A) Constrained analysis of principal coordinates (CAP) for the correlation between macronutrient intake and fecal bacterial composition. The individual datasets (n = 24 for Baybay, indicated by alphabet “B”; n = 16 for Ormoc, indicated by “O”) describing the energy ratios of macronutrient (carbohydrate, fat, and protein) intake were subjected to distance-based redundancy analysis (db-RDA) based on the Bray–Curtis distance between their family level bacterial communities. The alphabets representing the city of sample origin are colored according to the microbiota types classified in Figure 2B; “Green” and “Orange” letters indicate P-type and BB-type, respectively. The inset partition diagram explains bacterial community variance (adjusted R2) in terms of dietary macronutrients and/or city of residence, with p-values showing the significance of constraints calculated with 999 permutations. (B) Loading plot of bacterial phyla and families on the CAP ordination. The loadings of families were calculated by the db-RDA. The loadings of the three major phyla were calculated using envfit analysis to fit the phylum compositions of 40 samples to the CAP ordination. The size of each phylum circle represents total population size in the 40 Leyte samples. (C) Envfit plot of dietary nutrients on the CAP ordination. The daily intake level of each nutrient was correlated with sample variance in the CAP using envfit analysis; the nutrients showing significant correlation in 999 permutations (p < 0.05) were displayed by loading vectors. For macronutrients, their energy ratio data were subjected to envfit analysis and all three showed significance. The size of each macronutrient circle is proportional to R2 in the envfit analysis. (D) Gradient of dietary fat intake (energy %) on the CAP ordination. The fat energy intake ratio of the 40 Leyte children was fitted to the CAP coordinate by the ‘ordisurf’ function and regression splines are displayed.
FIGURE 5
FIGURE 5
Fecal bacterial composition and correlation with dietary fat intake. Plots representing data from 40 Leyte children are ordered by CAP1 score on the x-axis, and by their fat energy intake ratio (A), fecal Firmicutes-to-Bacteroidetes (F/B) ratio (B), and fecal bacterial family composition (C) on the y-axis.
FIGURE 6
FIGURE 6
Association map among fecal bacterial species and dietary macronutrients in Leyte children. Pairwise Spearman’s correlation analysis was performed using the 40 Leyte children dataset of the relative abundances of 80 species (mean % > 0.1% for 40 children samples) and the energy ratio of the daily consumed three macronutrients. Correlation coefficients higher than 0.4 or lower than -0.4 with p < 0.05 were extracted and are visualized in association map using the Prefuse Force Directed Layout in Cytoscape 3.3.0. Only positive correlations are represented as blue-line edges. The colors of the species nodes represent taxonomy at family or higher level. The sizes of nodes represent mean population among the Leyte children. Species name associated with nodes indicates a closest species identified by SeqmatchQ400 analysis. Species names colored green, orange, or red represent species showing a significant association with the intake ratio of carbohydrate, fat, and protein, respectively. Species names colored orange and bolded represent species showing a significant association with intake ratio of both fat and protein.
FIGURE 7
FIGURE 7
Correlation between gut bacterial community and genome-encoded functions. (A) Envfit plot of KEGG pathways at hierarchy level 2 on the CAP ordination computed in Figure 4. The abundances of KEGG pathways at hierarchy level 2 was estimated in each subject by the PICRUSt analysis based on the 16S rRNA composition data. Then, they were correlated with sample variance in the CAP by using envfit program; the KEGG pathways showing significant correlation in 999 permutations (p < 0.05) were displayed by red circles placed at the tips of undrawn vectors. The size of circle for each KEGG pathway is proportional to R2 in the envfit analysis. The code number of KEGG pathway is written beside the circle and is listed with the functional annotation in (C). (B) Envfit plot of KEGG pathway at hierarchy level 3 on the CAP ordination. The plot was simulated by the same methods used for level 2 in (A). The KEGG pathways showing significant correlation in 999 permutations (p < 0.05) were displayed by the pathway code no. placed at the tips of undrawn vectors. The code numbers are colored by the KEGG pathway hierarchy level 2 and are listed with the functional annotation in (C). (C) The code numbers and their functional annotations of KEGG pathways figured in (A) for hierarchy level 2 and (B) for hierarchy level 3. The letters are colored the same as for the codes in the other panels. (D) Contribution of each bacterial family to the KEGG pathways in the bacterial community of Leyte children. For each KEGG pathways, gene counts were estimated in each bacterial family based on the KEGG gene content table (ko_13_5). Then, counts from all families were summed and graphed as pie chart. (E) Abundances of two KEGG genes annotated as amylases (upper two graphs) and KEGG pathways, respectively, annotated as primary and secondary bile acids (lower two graphs). Relative abundances of these KEGG genes and KEGG pathways were calculated by the PICRUSt and were displayed as box plots showing the smallest and largest values, 25 and 75% quartiles, the median, and outliers. Statistical difference in the abundance was examined between BB-type and P-type groups by Wilcoxon rank-sum test for the two amylase genes and Student’s t-test for the pathways of primary and secondary bile acid biosynthesis. Single and double asterisks represent p < 0.05 and p < 0.001, respectively.
FIGURE 8
FIGURE 8
Correlation between high-fat diet-altered gut microbiota and obesity in Leyte children. (A) Distribution of fat energy intake (%), (B) Firmicutes-to-Bacteroidetes (F/B) ratio, and (C) relative abundance of Prevotella in underweight (UW) – normal weight (NW) group and overweight (OW) – obese (OB) group. Statistical differences between the two groups were examined by the Student’t-test in (A) and the Wilcoxon rank-sum test in (B) and (C). The post hoc power analysis was perform to retrospectively examine the observed power in these tests.
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"V体育ios版" References

    1. Arumugam M., Raes J., Pelletier E., Le Paslier D., Yamada T., Mende D. R., et al. (2011). Enterotypes of the human gut microbiome. Nature 473 174–180. 10.1038/nature10187 - DOI - PMC - PubMed
    1. Bäckhed F., Ding H., Wang T., Hooper L. V., Koh G. Y., Nagy A., et al. (2004). The gut microbiota as an environmental factor that regulates fat storage. Proc. Natl. Acad. Sci. U.S.A. 101 15718–15723. 10.1073/pnas.0407076101 - DOI - PMC - PubMed
    1. Backhed F., Ley R. E., Sonnenburg J. L., Peterson D. A., Gordon J. I. (2005). Host-bacterial mutualism in the human intestine. Science 307 1915–1920. 10.1126/science.1104816 - DOI (VSports) - PubMed
    1. Bäckhed F., Manchester J. K., Semenkovich C. F., Gordon J. I. (2007). Mechanisms underlying the resistance to diet-induced obesity in germ-free mice. Proc. Natl. Acad. Sci. U.S.A. 104 979–984. 10.1073/pnas.0605374104 - V体育官网 - DOI - PMC - PubMed
    1. Bell D. S. H. (2015). Changes seen in gut bacteria content and distribution with obesity: causation or association? Postgrad. Med. 127 863–868. 10.1080/00325481.2015.1098519 - DOI (VSports最新版本) - PubMed