Calorie restriction slows age-related microbiota changes in an Alzheimer's disease model in female mice

Abstract

Alzheimer's disease (AD) affects an estimated 5.8 million Americans, and advanced age is the greatest risk factor. AD patients have altered intestinal microbiota. Accordingly, depleting intestinal microbiota in AD animal models reduces amyloid-beta (Aβ) plaque deposition. Age-related changes in the microbiota contribute to immunologic and physiologic decline. Translationally relevant dietary manipulations may be an effective approach to slow microbiota changes during aging. We previously showed that calorie restriction (CR) reduced brain Aβ deposition in the well-established Tg2576 mouse model of AD. Presently, we investigated whether CR alters the microbiome during aging. We found that female Tg2576 mice have more substantial age-related microbiome changes compared to wildtype (WT) mice, including an increase in Bacteroides, which were normalized by CR. Specific gut microbiota changes were linked to Aβ levels, with greater effects in females than in males. In the gut, Tg2576 female mice had an enhanced intestinal inflammatory transcriptional profile, which was reversed by CR. Furthermore, we demonstrate that Bacteroides colonization exacerbates Aβ deposition, which may be a mechanism whereby the gut impacts AD pathogenesis. These results suggest that long-term CR may alter the gut environment and prevent the expansion of microbes that contribute to age-related cognitive decline.

Figure 1

Genotype, diet, and sex shape microbiota structure. Differences between microbiota were visualized by PCoA of unweighted UniFrac distances (panels a–e). (a) Overall stratification by diet and mouse genotype. (b) Tg2576 mice show altered microbiota from littermate WT mice, regardless of diet. (c) Diet shifts the microbiota in both WT and Tg2576 mice. (d,e) Male and female mice show differences in microbiota. (b–e) Clusters were significantly different by Permanova test, p < 0.05. (f) Unweighted UniFrac distances between WT and Tg2576 female mice (gray bars) were larger than within genotype distances. (g) CR reduces intragroup microbiota variation compared to AL-fed mice. (h) UniFrac distances between males and females were larger than intragroup distances within each sex. Bonferroni adjusted t-test, *p < 0.05, ***p < 0.001.

Figure 2

The effect of CR on the aging microbiota in WT and Tg2576 mice. (a) Composition of the fecal microbiota from study day 0 (~3 MO) until study day 369 (~15 MO). Mice were individually housed throughout the experiment, eliminating cage effects. (b) Age-related microbiota drift. Divergence from microbiota at study day 59 was measured using unweighted UniFrac distances on a per-mouse basis; slopes were calculated and tested by linear regression whether significantly non-zero. *p < 0.05. (c–f) Microbial taxa that are increased in 5 MO or 15 MO female mice, LEfSe p < 0.05. Each cladogram represents all taxa detected at >0.1%, shown at the Kingdom phylogenetic level through the genus level. A yellow circle depicts taxa present, but not enriched. Red circles are enriched in aging, and green enriched in young animals. The size of the circle corresponds to the population of each taxon.

Figure 3

CR modulates plaque load and microbiota in a sex-specific manner. (a) Aβ40 and Aβ42 levels are reduced in the entorhinal cortex by CR (blue) in female Tg2576 mice, n = 7–8/group, T-test, as measured by ELISA (AL, black). (b) CR decreases Aβ plaque load in the hippocampus in females, as determined by immunohistochemistry. (c) Aβ40 and Aβ42 levels in the entorhinal cortex. Panels a–c modified from Schafer et al., Neurobiology of Aging 2015 with permission. (d) OTUs from younger (Early, 5–10 MO) or older (Late, 12–15 MO) mice, that were predictive of Aβ40 and Aβ 42 levels in the brain. (e) Microbiota that correlate with Aβ40 and Aβ42 levels differ by sex. *p < 0.05, ** < 0.01, *** < 0.001, Spearman correlation. (f) AL-fed Tg2576 female mice (red) show accelerated age-related changes in Faecalibaculum and Bacteroides compared to WT (black) and are reversed by CR (orange). (g) Males show minimal age-related bacterial patterns that correlate with Aβ plaque burden.

Figure 4

Bacterial KEGG Pathways associated with disease. (a) KEGG pathways from early (5–11 MO) or late (12–15 MO) that were predictive of Aβ40 and Aβ42 levels in the brain. (b) Relative abundance of select KEGG pathways over time.

Figure 5

CR reverses APP-associated gene expression in the intestine. Ileal gene expression was measured by Nanostring nCounter analysis in 15 MO female mice. (a) Enumeration of significantly upregulated or downregulated genes modulated by diet in WT or Tg2576 mice and modulated by genotype in AL- or CR-fed mice. (b,c) Expression levels of genes that are modulated by diet in WT (b) and in Tg2576 (c) mice. (d) Selection of genes altered by diet in both WT and Tg2576 mice. (e,f) Expression levels of genes that differ between WT and Tg2576 littermates in AL (e) and in CR (f) mice. (g) Selection of genes that show altered expression in AL-fed Tg2576 mice compared to AL-fed WT mice, which are reduced to WT levels with a CR diet. *p < 0.05, **p < 0.01, ***p < 0.001 t-test.

Figure 6

Bacteroides fragilis promotes Aβ deposition. (a) Merged fluorescent image of Aβ (red) and nuclei (blue). (b,c) Cortical (b) and hippocampal (c) regions were outlined in 3 brain sections per mouse and plaque area and number were quantified in ImageJ. Aβ-labeled plaques are shown in red, region of interest and automatically detected plaques shown in yellow. p-value listed for Student t-test, n = 3–4 mice/group.