Diet, Environments, and Gut Microbiota. A Preliminary Investigation in Children Living in Rural and Urban Burkina Faso and Italy

Abstract

Diet is one of the main factors that affects the composition of gut microbiota. When people move from a rural environment to urban areas, and experience improved socio-economic conditions, they are often exposed to a "globalized" Western type diet. Here, we present preliminary observations on the metagenomic scale of microbial changes in small groups of African children belonging to the same ethnicity and living in different environments, compared to children living on the urban area of Florence (Italy). We analyzed dietary habits and, by pyrosequencing of the 16S rRNA gene, gut microbiota profiles from fecal samples of children living in a rural village of Burkina Faso (n = 11), of two groups of children living in different urban settings (Nanoro town, n = 8; Ouagadougou, the capital city, n = 5) and of a group of Italian children (n = 13). We observed that when foods of animal origin, those rich in fat and simple sugars are introduced into a traditional African diet, composed of cereals, legumes and vegetables, the gut microbiota profiles changes. Microbiota of rural children retain a geographically unique bacterial reservoir (Prevotella, Treponema, and Succinivibrio), assigned to ferment fiber and polysaccharides from vegetables. Independently of geography and ethnicity, in children living in urban areas these bacterial genera were progressively outcompeted by bacteria more suited to the metabolism of animal protein, fat and sugar rich foods, similarly to Italian children, as resulted by PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a predictive functional profiling of microbial communities using 16S rRNA marker gene. Consequently, we observed a progressive reduction of SCFAs measured by gas chromatography-mass spectrometry, in urban populations, especially in Italian children, respect to rural ones. Our results even if in a limited number of individuals point out that dietary habit modifications in the course of urbanization play a role in shaping gut microbiota, and that ancient microorganisms, such as fiber-degrading bacteria, are at risk of being eliminated by the fast paced globalization of foods and by the advent of westernized lifestyle.

Keywords: Africa; children; diet; environment; microbiota; short chain fatty acids; urbanization.

FIGURE 1

Rural and urban environments in Burkina Faso. (A) Rural village in Boulpon, (B) urban village in Nanoro town, (C) Ouagadougou, the capital city of Burkina Faso (personal photographs of Prof. P. Lionetti), and (D) map of Burkina Faso.

FIGURE 2

Variety of food consumption in the four children populations. Pie charts indicate the percentages of daily foods assumed by the African and European populations. BR: children form rural village; BT: children from Nanoro town; BC: children from capital city of Burkina Faso; EU: children from Europe (Florence, Italy).

FIGURE 3

Quantification of SCFAs levels in fecal samples from African and EU populations by SPME-GC-MS. Mean values ( ± SEM) are plotted. Comparison among groups by one-tailed Student’s t-test. ^∗p < 0.05; ^∗∗p ≤ 0.01; ^∗∗∗p ≤ 0.001.

FIGURE 4

Clustering of African and European populations based on microbiota composition. (A) Box plot of relative abundances of the statistically significant different major phyla in African and European populations (Wilcoxon rank sum test; ^∗p-value < 0.05, ^∗∗p-value < 0.01, ^∗∗∗p-value < 0.001). (B) Heatmap plot indicating the sequence abundances (percentage; blue-scale squares) assigned at each phylum in each sample. Dendrograms, obtained with Average Neighbor UPGMA method, are used to cluster each fecal sample of the children populations (horizontal) based on phyla abundances. Each sample, belonging to respective group, is represented by a different color: green = BR, brown = BT, yellow = BC, and blue = EU.

FIGURE 5

Beta diversity (A) Principal coordinates analysis (PCoA) derived from unweighted and weighted UniFrac and Bray–Curtis distances among samples of the four populations (p = 0.0001 by PERMANOVA). Colored dots representative of the four populations are as in Figure 4. For each axis, in square brackets, the percent of variation explained was reported. (B) Beta diversity and correlation with the principal abundant bacterial families, represented by colored rectangles (p = 0.0001 by PERMANOVA). Different sizes of rectangles indicate the size of relative family abundance. For each axis, in square brackets, the percent of variation explained was reported.

FIGURE 6

Disappearance of ancient microbial pattern and acquisition of “Western” microbial profiles passing from rural to urban environments in Burkina Faso populations. Box plot of relative abundances of the statistically significant different genera in African groups in comparison with European population (Wilcoxon pairwise test; ^∗p-value < 0.05, ^∗∗p-value < 0.01, ^∗∗∗p-value < 0.001).

FIGURE 7

Differences in the most representative bacterial functional classes (KEGG categories level 3). (A–D) Functional pathways significantly enriched in African and European populations based on PICRUSt prediction. LEfSe results indicate a sequentially significant ranking among populations (Alpha value = 0.05 for the factorial Kruskal–Wallis test among classes). The threshold for the logarithmic LDA score was 2.0.