Dietary aluminium intake disrupts the overall structure of gut microbiota in Wistar rats

Abstract

Approximately, 40% of ingested dietary aluminium accumulates in the intestine, which has been considered a target organ for dietary aluminium exposure. The gut microbiota may be the first protective barrier against the toxic metal aluminium and a crucial mediator of the bioavailability of metal aluminium. We previously evaluated dietary aluminium intake and its health risks in a population from Jilin Province, China, and found that the average daily intake of aluminium in the diet of residents in Jilin Province was 0.163 mg/kg after the total diet survey. In the present study, the equivalent concentration of aluminium in rats was extrapolated by the average dietary aluminium intake in the population of Jilin Province based on body surface area. Furthermore, healthy adult Wistar rats were randomly divided into four groups (n = 15 for each group): a control group and three groups treated with aluminium solution (1, 10, and 100 mg/kg/day, intragastrically) for 28 days. Following treatment, necrosis of renal tubular epithelial cells, hyperplasia of bile ducts and hyperplasia of heart tissue, as well as fiber in the liver, kidney, and heart tissues of aluminium-treated rats were observed, although there were no significant changes in the spleen and brain. Subsequently, fecal samples were withdrawn for 16S rRNA gene sequence analysis. It was found that aluminium decreased the microbiota diversity and changed the overall community structure of the gut microbiota, including three phyla and four genera, together with the regulation of 12 signaling pathways. Collectively, treatment with aluminium markedly altered the structure of the gut microbiota, suggesting that the disorders of intestinal flora induced by aluminium may be an important mechanism for aluminium toxicity.

Keywords: 16S rRNA sequencing; dietary aluminium; food safety; gut microbiome.

FIGURE 1

Effects of aluminium on body weight and food consumption of rats. (a) Schematic overview of the experimental design. (b, c) Changes in body weight and food consumption of different groups are shown for Wistar rats administered aluminium solution for 4 weeks. Data are represented as the means ± standard deviation (SD) (n > 6)

FIGURE 2

Representative H&E‐stained slices of major organs (heart, liver, spleen, kidney, and brain)

FIGURE 3

Diversity analysis of the fecal microbiota communities based on OTUs. (a) Venn diagram of different groups. (b, d) Comparison of the richness and diversity indices of different groups. (c) Chao1 rarefaction curve. (e) Shannon rarefaction curve. (f) Evaluation of the community structure of intestinal microbes from 16S rRNA sequencing using PLS‐DA in different groups. Data are represented as the means ± SD (n > 6); *p < .05

FIGURE 4

Taxonomy analysis of microbiota components. (a) Relative abundance of the phylum from each sample. (b) The average abundance of each phylum in the control group, Al‐L group, Al‐M group, and Al‐H group. (c) Significant intergroup differences were found in the three phyla. (d) Heatmap showing the relative abundance of genera ranking in the top 50 from each sample. (e) Significant intergroup differences were found in four genera. Data are represented as the means ± SD (n > 6); *p < .05, **p < .01 versus the C group; ^# p < .05 versus the Al‐H group

FIGURE 5

Microbiome function prediction according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. (a) KEGG level 2 metabolic pathways. (b) Heatmap showing the specific annotated information of each KEGG orthologous group (KO) in the metabolic pathway