Microbiome-metabolome signatures in mice genetically prone to develop dementia, fed a normal or fatty diet

Abstract

Cognitive decline, obesity and gut dysfunction or microbial dysbiosis occur in association. Our aim was to identify gut microbiota-metabolomics signatures preceding dementia in genetically prone (3xtg) mice, with and without superimposed high-fat diet. We examined the composition and diversity of their gut microbiota, and serum and faecal metabolites. 3xtg mice showed brain hypometabolism typical of pre-demented stage, and lacked the physiological bacterial diversity between caecum and colon seen in controls. Cluster analyses revealed distinct profiles of microbiota, and serum and fecal metabolome across groups. Elevation in Firmicutes-to-Bacteroidetes abundance, and exclusive presence of Turicibacteraceae, Christensenellaceae, Anaeroplasmataceae and Ruminococcaceae, and lack of Bifidobacteriaceae, were also observed. Metabolome analysis revealed a deficiency in unsaturated fatty acids and choline, and an overabundance in ketone bodies, lactate, amino acids, TMA and TMAO in 3xtg mice, with additive effects of high-fat diet. These metabolic alterations were correlated with high prevalence of Enterococcaceae, Staphylococcus, Roseburia, Coprobacillus and Dorea, and low prevalence of S24.7, rc4.4 and Bifidobacterium, which in turn related to cognitive impairment and cerebral hypometabolism. Our results indicate an effect of transgenic background on gut microbiome-metabolome, enhanced by high-fat diet. The resulting profiles may precede overt cognitive impairment, suggesting their predictive or risk-stratifying potential.

Figure 1

The metabolome of 3xtg mice differs more from control mice than mice under HFD. PCA score plots based on the NMR metabolomic profile of serum (a), and fecal extracts from colon (b) and caecum (c). Each symbol represents a single sample shaped and coloured according to the respective group.

Figure 2

The serum metabolome of 3xtg mice differs from control mice, and HFD exerts additive effects. Relative fold changes for control and 3xtg mice under normal or HFD on NMR integrals for metabolic regions with higher VIP scores in PLS-DA serum analysis. Bars represent fold-change in metabolite content for each comparison (increased content: positive bars; decreased content: negative bars). ND, ND-fed control mice; 3xtg, ND-fed 3xtg mice; HFD, HFD-fed control mice; 3xtgHFD, HFD-fed 3xtg mice. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 3

The fecal metabolome of 3xtg mice is altered with respect to control mice. Relative fold changes for in test groups (HFD, and 3xtg mice under ND or HFD) versus control ND mice, derived from NMR integrals of metabolic regions with higher VIP scores in the PLS-DA analysis in colon and caecum faecal extracts. Bars represent fold-change in metabolite content in each comparison (increased content: positive bars; decreased content: negative bars). ND, ND-fed control mice; 3xtg, ND-fed 3xtg mice; HFD, HFD-fed control mice; 3xtgHFD, HFD-fed 3xtg mice. *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 4

HFD and 3xtg determine a dramatic rightward shift in the overall composition of gut microbiota. RDA plot at OTU level between animal groups and diet intervention. The analysis revealed a clear-cut separation between HFD and ND mice (a,b), and between 3xtg and control mice (c,d). Each symbol represents a single sample shaped and coloured according to the respective group.

Figure 5

HFD consumption, 3xtg background and location significantly influence the composition of the gut microbiome. LEfSe test-identified LDA scores showed the significant bacterial difference due to the effect of diet and location (a, ND and HFD, colon and caecum), and disease and location (b, ND and 3xtg, colon and caecum). Venn diagram showed shared families across groups (c, diet and location; d, disease and location).

Figure 6

Isolated and combined HFD plus 3xtg background determine a clear-cut separation in microbiota composition. Beta-diversity PCA using weighted (a) and unweighted-UniFrac distances (b). RDA plot at OTU level between groups (c, colon; d, caecum). Each symbol represents a single sample shaped and coloured according to the respective group.

Figure 7

Associations between colon microbiome and serum metabolome. Heatmap shows associations between metabolite profile and relative abundance of specific bacterial families and genera in ND and 3xtg groups. Red to blue scale: positive to negative associations. Pearson’s correlations were employed in agreement with data distribution, verified by Shapiro-Wilk test. *p < 0.05.

Figure 8

Associations between gut microbiome and cerebral parameters. Heatmap generated from Spearman correlation analysis shows associations between brain parameters (cognitive function and glucose metabolism) and relative abundance of specific bacterial phyla, families and genera across groups, in caecum and colon. Red to blue scale: positive to negative associations. Spearman’s correlations were employed in agreement with data distribution, verified by Shapiro-Wilk test. *p < 0.05. *p < 0.05.