Environmental enrichment restores cognitive deficits caused by the HFHC diet. No statistically significant differences were found in the body weight between groups throughout the 14 weeks of administration of the diet (Fig. 1a) (p = 0.306). As expected, significant differences between weeks were revealed (p < 0.001), with normal weight gain according to age in both experimental groups (Fig. 1b). The normal increase in weight was accompanied by the absence of statistically significant locomotor deficits in all groups (p = 0.151; Fig. 1c).
When the experimental groups performed the novel object recognition task, there were no statistically significant differences between e1 and e2 in any of the groups (NC: p = 0.153; NC + EE: p = 0.157; HFHC: p = 0.895; HFHC + EE: p = 0.106), which means that these animals spent a similar amount of time exploring in the first and second phases of the test. However, when we compared the discrimination ratios, we found that the NC group was able to discriminate between a previously-encountered object and a novel object because d1 and d2 were statistically higher than zero (d1: p < 0.001; d2: p < 0.001), whereas the HFHC group was not able to distinguish the new object (d1: p = 0.442; d2: p = 0.442). After the implementation of EE, the NC + EE group maintained its recognition ability (d1: p < 0.001; d2: p < 0.001), and we found that the HFHC + EE group was now able to recognise the novel object (d1: p = 0.010; d2: p = 0.010). When we compared the discrimination ratio between the experimental groups, we found that the NC, NC + EE, and HFHC + EE groups showed statistically significant higher d2 than the HFHC group (p = 0.003). The HFHC group initially displayed an object recognition impairment that was reversed by the introduction of EE (Fig. 1d).
To explore whether or not the EE improvement only occurred in a particular network, the experimental groups were tested on a spatial working memory task. Whereas the NC group was able to remember the position of the platform, showing a statistically significant lower latency in the retention trial compared to the sample trial (p = 0.003), the HFHC group did not show statistically significant differences between the sample and retention trials (p = 0.333). After EE, the NC + EE maintained their capacity to remember the position of the platform (p = 0.002), and HFHC + EE were now able to remember it as well (p = 0.002). Our results showed that the HFHC impaired spatial working memory was ameliorated by the EE. When comparing the mean latencies in each trial between groups, we observed that, although the sample latencies were statistically similar, (p = 0.941), the retention latencies differed (p = 0.008) because they were significantly higher in HFHC than in NC, NC + EE, and HFHC + EE (Fig. 1e).
Each group was fed their respective diet for 14 weeks. From week 8 to 12, NC+EE and HFHC+EE were subjected to EE, whereas HFHC+LGG and HFHC+AKK were given their respective probiotic daily, and HFHC+PBS received phosphate buffered saline. From weeks 12 to 14, the cognitive evaluation took place, at the end of which the animals were sacrificed and the samples were collected. b Body weight across weeks. Two-way ANOVA (Group x Week) was used to assess weight gain. No changes in body weight between groups were found throughout the 14 weeks of the administration of the diet, and significant differences across the weeks were revealed. c Locomotor function evaluation measured on the Rotarod-accelerod test. Bar charts (mean±SEM) represent the maximum speed (rpm) of the animals on the rod, compared with the Kruskal-Wallis test. There were no statistically significant differences between groups. d Novel object recognition test. Bar charts (mean±SEM) represent the discrimination ratio (d2) between the new object and the one previously observed. Mann–Whitney’s U test for independent samples (* comparison with zero) and one-way ANOVA followed by Tukey’s test (# comparison of NC, NC+EE, HFHC and HFHC+EE d2 value) were used. NC and NC+EE groups were able to recognise the new object; whereas HFHC was not able to discriminate it, HFHC+EE showed a recovered novel object recognition ability. #p<0.05, **p≤0.010, ***p<0.001. e Spatial working memory test. Bar charts (mean±SEM)represent the average latency on the sample and retention trials. Two-tailed paired t-tests (* comparison with its respective sample) and one-way ANOVA followed by Tukey’s test (# comparison between NC, NC + EE and HFHC + EE) were used. NC and NC + EE groups remembered the position of the platform in the retention trial; whereas HFHC was not able to remember it, HFHC + EE displayed recovered spatial working memory. #p < 0.05, **p ≤ 0.010.
Environmental enrichment cognitive improvement is accompanied by a decrease in brain metabolic activity. The HFHC group showed significantly lower CCO activity values than the NC group, with less metabolic activity in the infralimbic cortex (IL; p < 0.001), cingulated cortex (Cg, p < 0.001), dorsal striatum (dST, p < 0.001), accumbens shell (AcbS; p < 0.001), and perirhinal cortex (PRh; p = 0.002; Table 1). EE led to a decline in the CCO levels in the NC + EE and HFHC + EE groups. The NC + EE group displayed lower CCO levels than the NC group in the prefrontal cortex (p < 0.001), dorsal and ventral striatum (p < 0.001), thalamus (p < 0.001), and CA3 (p = 0.001) and DG (p < 0.001) hippocampal subregions. In addition, HFHC + EE animals also presented decreased CCO values compared to HFHC animals in the dorsal and ventral striatum (p < 0.001), anterodorsal thalamus (ADT; p < 0.001), basolateral amygdala (BLA; p = 0.006), dentate gryus (DG; p < 0.001), and CA3 (p = 0.001). Finally, HFHC + EE showed lower CCO values than NC + EE in the DG (p < 0.001). No differences were found between HFHC + EE and NC + EE in the prefrontal cortex, dorsal and ventral striatum, thalamus, amygdala, and perirhinal cortex.
Table 1
Brain oxidative metabolism in different groups subjected to NC and HFHC diets and EE.
The CCO values are expressed as mean ± SEM. The studied regions included the prefrontal cortex (prelimbic (PrL), infralimbic (IL) and cingulate (Cg) cortex), the dorsal striatum (dST), the ventral striatum (accumbens core (AcbC) and shell (AcbSh)), the thalamus (anteromedial nucleus (AMT), anterodorsal nucleus (ADT), and anteroventral nucleus (AVT)), the amygdala (central (CeA), basolateral (BLA) and lateral (LaA)), the dorsal hippocampus (dentate gyrus (DG), CA1 and CA3 areas), and the perirhinal (PRh) and entorhinal (Ent) cortices. Data were analysed through one-way ANOVA followed by Tukey’s test (*#&p < 0.05; * NC + EE and HFHC vs. NC; # HFHC + EE vs. HFHC; & HFHC + EE vs. NC + EE).
Region | NC | NC + EE | HFHC | HFHC + EE |
PrL | 28.526 ± 1.327 | *21.506 ± 1.501 | 21.815 ± 1.042 | * 19.999 ± 0.862 |
IL | 28.153 ± 1.109 | * 21.433 ± 1.323 | * 22.027 ± 0.939 | * 19.634 ± 0.930 |
Cg | 28.846 ± 1.333 | * 22.008 ± 1.283 | * 22.684 ± 1.164 | * 20.495 ± 0.791 |
dST | 28.040 ± 0.707 | * 22.115 ± 0.622 | * 23.078 ± 0.671 | *# 19.889 ± 0.784 |
AcbC | 35.734 ± 1.337 | * 26.434 ± 1.192 | 31.252 ± 0.903 | *# 22.246 ± 0.780 |
AcbSh | 39.684 ± 1.055 | * 29.814 ± 1.122 | * 34.000 ± 1.150 | *# 25.962 ± 0.693 |
AMT | 26.087 ± 1.280 | * 16.413 ± 2.136 | 22.203 ± 0.694 | * 17.540 ± 0.824 |
ADT | 37.683 ± 1.684 | * 28.188 ± 1.054 | 33.995 ± 1.348 | *# 25.138 ± 1.207 |
AVT | 31.661 ± 1.702 | * 22.988 ± 1.793 | 27.684 ± 1.193 | * 22.094 ± 0.700 |
CeA | 23.299 ± 0.984 | 19.247 ± 2.411 | 22.482 ± 1.040 | * 16.578 ± 1.151 |
BLA | 25.912 ± 1.338 | 23.639 ± 1.334 | 25.180 ± 0.988 | *# 19.254 ± 1.343 |
LaA | 20.135 ± 0.828 | 20.268 ± 2.077 | 20.049 ± 0.641 | 14.897 ± 1.085 |
DG | 34.185 ± 1.729 | * 27.210 ± 0.723 | 30.501 ± 0.954 | *#& 22.593 ± 0.770 |
CA1 | 20.905 ± 1.154 | 16.481 ± 1.709 | 17.978 ± 0.805 | * 14.541 ± 1.231 |
CA3 | 20.556 ± 1.127 | * 15.018 ± 1.583 | 18.396 ± 0.973 | *# 13.403 ± 1.072 |
PRh | 25.015 ± 1.240 | 15.018 ± 1.583 | * 18.891 ± 0.896 | * 17.205 ± 1.147 |
Ent | 21.212 ± 1.502 | 17.704 ± 1.836 | 17.312 ± 0.760 | 16.035 ± 1.391 |
Environmental enrichment has an effect on microbiota composition and bacterial metabolism. To assess the effect of the environmental enrichment (EE) implementation on the gut microbiota, we studied the gut microbiome profile of the NC + EE and HFHC + EE groups, by comparing them with the profiles of the control groups (NC and HFHC) and with each other. We first studied how EE affects microbial diversity within the communities by calculating the Chao1 (richness estimator) and Shannon’s index (richness and evenness estimator). We confirmed significantly (p < 0.000) less bacterial diversity in the HFHC group compared to the NC group, as previously described in the characterization of the NASH animal model used [3], and we observed an increase in bacterial diversity in the NC + EE group compared to the NC group (p < 0.01). However, EE did not affect the bacterial diversity in the HFHC + EE group, which was significantly lower (also for evenness) than in the NC + EE group (p < 0.000) (Fig. 2a).
Next, we assessed the gut microbiota composition in each group of rats. When comparing the NC and HFHC groups, the pattern was substantially different (Additional file 1: Supplementary Figure S1), in agreement with previous studies [3]. The main differences were found in the greater abundance of Lactobacillaceae and Ruminococacceae in the NC groups compared to the HFHC groups, which harboured a greater abundance of Enterobacteriaceae, Bacteroidaceae, or Peptostreptococcaceae. Then, in order to explore how EE could affect the different phylotypes on the microbiota, we applied a linear discriminant analysis effect size (LEfSe) method at the family level to investigate the taxa most likely to explain differences in abundances across the groups. When we compared the four animal groups: NC, NC + EE, HFHC, HFHC + EE, the results identified statistically significant increased abundance of Micrococcaceae, Christensenellaceae, and Ruminococcaceae in the NC + EE group compared to the rest of the groups, and increased abundance of different families belonging to the Firmicutes phyla and Akkermansiaceae as the most differential microorganisms in the HFHC + EE when compared with the other three groups (Fig. 2b).
To explore the metabolic implications of the microbial differences observed after EE implementation, we analysed the main SCFAs and branched-chain fatty acids (BCFAs) derived from the bacterial metabolism. First, when comparing the HFHC group and the NC group, we confirmed the previous observations [3], where the main SCFAs (acetate, p < 0.01; propionate, p < 0.05; and butyrate, p < 0.01) showed statistically significant lower concentrations in the HFHC group. Then, the comparisons of NC + EE and HFHC + EE with their control groups (NC and HFHC, respectively) did not show any significant differences in acetate, propionate, butyrate, or valerate, even though a decreasing tendency was observed after EE. On the other hand, the concentrations of the BCFAs iso-butyric (p < 0.05) and iso-valeric (n.s.) were lower in NC + EE and HFHC + EE, compared to NC and HFHC, respectively (Fig. 2c).
Box-and-whiskers (median and IRQ range) represent comparisons of alpha-diversity of gut microbiota using Chao1 and Shannon indexes among the groups studied, compared using a one-way ANOVA followed by Tukey’s test (* comparison with all the groups; # comparison with HFHC+EE group; $ comparison with HFHC and HFHC+EE groups). *#$p<0.01. b Gut microbiota composition. Taxonomic cladogram obtained from LEfSe analysis (LDA scores > 2 and significance of p<0.05 as determined by Wilcoxon’s signed-rank test) showing bacterial taxa with differential abundance among the groups studied. Red indicates differential abundances in the HFHC group; green indicates differential abundances in the HFHC+EE group; blue indicates differential abundances in the NC group; purple indicates differential abundances in the NC+EE group. c SCFA and BCFAs. Bar charts (mean±SEM) represent comparison of the SCFA and BCFA levels (mM) compared using the Kruskal-Wallis test followed by Dunn’s analysis (* comparison with HFHC and HFHC+EE groups; # comparison with NC+EE group; $ comparison with NC+EE and HFHC+EE groups). *#$p<0.05.
Akkermansia muciniphila, as a probiotic treatment, restores cognition deficits. Slight changes were found in the body weights of the groups throughout the 14 weeks of the administration of the diet because the HFHC + LGG group gained more weight than the NC group (p = 0.038); significant differences were observed across weeks (p < 0.001), as expected (Fig. 3a). The normal increase in weight was accompanied by the absence of locomotor deficits in all groups (p = 0.092; Fig. 3b). On the object recognition test, the experimental groups did not show significant differences between e1 and e2 (NC: p = 0.153; HFHC + PBS: p = 0.565; HFHC + LGG: p = 0.157; HFHC + AKK: p = 0.642) while performing the novel object recognition test. Indeed, the NC group was able to discriminate between a previously encountered object when d1 and d2 were statistically higher than zero (d1: p < 0.001; d2: p < 0.001). However, the HFHC + PBS group was not able to discriminate the new object (d1: p = 1.000; d2: p = 1.000). After the administration of probiotics (AKK or LGG), the HFHC + LGG group was still unable to recognise the new object (d1: p = 1.000; d2: p = 1.000), but the HFHC + AKK group was able to do so (d1: p = 0.010; d2: p = 0.010). When we compared the discrimination ratio between the groups, we found that NC and HFHC + AKK showed significantly higher d2 than HFHC + PBS and HFHC + LGG (p < 0.001). These results showed that HFHC + PBS displayed an object recognition impairment that was not recovered by the administration of LGG, but it was reversed by AKK (Fig. 3c).
Finally, when we evaluated the efficacy of probiotic administration on a relevant prefrontal dependent task such as spatial working memory, we found that the HFHC + LGG group was unable to execute the task (p = 0.486), as well as the HFHC + PBS group (p = 0.103). However, the HFHC + AKK group performed the task (p = 0.019) as correctly as the NC group, and they were able to remember the position of the platform because they showed a statistically significant lower retention latency compared to the sample trials (p = 0.003). When we compared the mean latencies in each trial between groups, we observed that, whereas the sample latencies were statistically similar, (p = 0.798), the retention latencies differed (p = 0.003) because they were significantly higher in HFHC + PBS and HFHC + LGG than in NC and HFHC + AKK (Fig. 3d). These results highlight the efficacy of A. muciniphila CIP107961 as a probiotic treatment to reverse impaired spatial working memory, compared to other probiotics such as L. rhamnosus GG.
Two-way ANOVA (Group x Week) was used to assess weight gain. Slight significant changes in body weight between groups were found throughout the 14 weeks of the administration of the diet because the HFHC+LGG group gained more weight than the NC group; significant differences across the weeks were also revealed. *p<0.05. b Locomotor function evaluation measured on Rotarod-accelerod test. Bar charts (mean±SEM) represent the maximum speed (rpm) of the animals on the rod, compared using the Kruskal-Wallis test. There were no statistically significant differences between groups. c Novel object recognition test. Bar charts (mean±SEM) represent the discrimination ratio (d2) between the new object and the one previously observed. Mann–Whitney’s U test for independent samples (* comparison with zero) and one-way ANOVA followed by Tukey’s test (# comparison of NC, HFHC+PBS, HFHC+LGG and HFHC+AKK d2 value) were used. The NC group was able to recognise the new object; whereas HFHC+PBS and HFHC+LGG were not able to discriminate it, HFHC+AKK showed a recovered novel object recognition ability. #p<0.05, **p≤0.010, ***p<0.001. d Spatial working memory test. Bar charts (mean±SEM) represent the average latency on sample and retention trials. Two-tailed paired t-tests (* comparison with its respective sample) and one-way ANOVA followed by Tukey’s test (# comparison between NC, HFHC+PBS, HFHC+LGG, and HFHC+AKK) were used. The NC group remembered the position of the platform on the retention trial; whereas HFHC+PBS and HFHC+LGG were not able to remember it, HFHC+AKK displayed recovered spatial working memory. *#p<0.05, **p≤0.010.
Akkermansia muciniphila restores brain metabolic activity to normal. When we explored the brain metabolic activity underlying these cognitive changes, we first found that the HFHC + PBS group showed significantly lower levels of CCO activity than the NC group in the prefrontal cortex (p < 0.001), dorsal and ventral striatum (p < 0.001), amygdala nuclei such as CeA (p = 0.004), BLA (p = 0.014), hippocampus (p ≤ 0.007), and PRh (p < 0.001; Table 2).
When the animals were treated with A. muciniphila CIP107961, their brain metabolic activity equalled that of the NC group in most of the regions previously affected by HFHC, such as the prefrontal cortex, dorsal striatum, amygdala, hippocampus, and perirhinal cortex. In line with this, HFHC + AKK showed an increased CCO value in the dorsal striatum (dST, p < 0.001), central amygdala (CeA, p = 0.004), and basolateral amygdala (BLA, p = 0.014), compared to HFHC + PBS. However, the HFHC + AKK group also showed lower CCO levels than the NC group in the infralimbic cortex (IL, p < 0.001), ventral striatum (p < 0.001), and dentate gyrus (DG, p < 0.001).
Regarding L. rhamnosus GG administration, we found that the HFHC + LGG group maintained decreased levels of CCO, compared to the NC group, in the prefrontal cortex (p < 0.001), dorsal and ventral striatum (p < 0.001), thalamic nuclei such as anteromedial nucleus (AMT, p = 0.016), hippocampus (p ≤ 0.007), and perirhinal cortex (PRh, p < 0.001). More importantly, HFHC + LGG did not display significant differences in CCO levels compared to HFHC + PBS.
When comparing the two probiotic treatments, we observed that the HFHC + AKK group showed statistically significant higher CCO values than the HFHC + LGG group in the prefrontal cortex (p < 0.001) and dST (p < 0.001). These results point out that the decreased CCO shown by HFHC + PBS cannot be recovered with LGG administration, whereas the opposite effect was found when applying AKK. More importantly, A. muciniphila CIP107961 was able to reverse the HFHC-associated decrease in CCO activity in most of the brain regions previously affected by the HFHC diet.
Table 2
Brain oxidative metabolism in experimental groups subjected to PBS, LGG and AKK. The CCO values are expressed as mean ± SEM. The studied regions included the prefrontal cortex (prelimbic (PrL), infralimbic (IL) and cingulate (Cg) cortex), the dorsal striatum (dST), the ventral striatum (accumbens core (AcbC) and shell (AcbSh)), the thalamus (anteromedial nucleus (AMT), anterodorsal nucleus (ADT), and anteroventral nucleus (AVT)), the amygdala (central (CeA), basolateral (BLA) and lateral (LaA)), the dorsal hippocampus (dentate gyrus (DG), CA1 and CA3 areas), and the perirhinal (PRh) and entorhinal (Ent) cortices. Data were analysed through one-way ANOVA followed by Tukey’s test (*#&p < 0.05; * HFHC + PBS vs. HFHC + LGG and HFHC + AKK vs. NC; # HFHC + LGG and HFHC + AKK vs. HFHC + PBS; & HFHC + AKK vs. HFHC + LGG).
Region | NC | HFHC + PBS | HFHC + LGG | HFHC + AKK |
PrL | 28.526 ± 1.327 | * 22.244 ± 1.336 | * 20.738 ± 0.403 | & 25.929 ± 1.079 |
IL | 28.153 ± 1.109 | * 21.897 ± 0.998 | * 19.785 ± 0.510 | * & 24.277 ± 1.112 |
Cg | 28.846 ± 1.333 | * 22.650 ± 0.991 | * 22.101 ± 0.545 | & 26.131 ± 1.077 |
dST | 28.040 ± 0.707 | * 22.484 ± 0.878 | * 22.844 ± 0.473 | #& 26.125 ± 0.775 |
AcbC | 35.734 ± 1.337 | * 26.777 ± 0.920 | * 24.850 ± 0.786 | * 28.662 ± 1.185 |
AcbSh | 39.684 ± 1.055 | * 30.770 ± 1.405 | * 29.465 ± 1.298 | * 31.602 ± 1.731 |
AMT | 26.087 ± 1.280 | 22.187 ± 0.556 | * 21.189 ± 0.815 | 23.501 ± 0.897 |
ADT | 37.683 ± 1.684 | 35.689 ± 1.132 | 34.485 ± 0.999 | 37.131 ± 0.992 |
AVT | 31.661 ± 1.702 | 27.654 ± 1.206 | 27.254 ± 0.856 | 29.324 ± 0.708 |
CeA | 23.299 ± 0.984 | * 18.874 ± 0.849 | 20.607 ± 0.456 | # 22.133 ± 0.827 |
BLA | 25.912 ± 1.338 | * 21.297 ± 1.131 | 22.484 ± 0.400 | ·# 25.123 ± 0.628 |
LaA | 20.135 ± 0.828 | 18.128 ± 0.688 | 19.400 ± 0.342 | 20.002 ± 0.889 |
DG | 34.185 ± 1.729 | * 28.133 ± 1.170 | * 25.733 ± 0.726 | * 29.408 ± 0.964 |
CA1 | 20.905 ± 1.154 | * 17.692 ± 0.686 | * 16.905 ± 0.442 | 17.929 ± 0.695 |
CA3 | 20.556 ± 1.127 | * 16.890 ± 0.274 | * 16.615 ± 0.237 | 17.787 ± 0.669 |
PRh | 25.015 ± 1.240 | *20.272 ± 0.405 | * 18.797 ± 0.554 | 19.835 ± 0.510 |
Ent | 21.212 ± 1.502 | 17.752 ± 0.405 | 17.348 ± 0.368 | 18.844 ± 1.051 |
Probiotics do not induce major rearrangements in the faecal microbiota. To assess the effect of two different probiotics on the NASH-associated cognitive disturbances, we first analysed the effect of the administration of the strains by oral gavage on the gut microbiota in the gavage feeding groups (HFHC + AKK, HFHC + LGG, and HFHC + PBS [control group]), also including the NC group (no gavage) as external control. Miseq sequencing produced an average of ~ 63,000 filtered partial sequences per sample, and it showed the biggest differences at the diversity and compositional levels between the NC group and the other three NASH groups (Fig. 4a, Additional file 1: Supplementary Figure S2a), confirming the strong effect of diet (control vs. HFHC diet). The analyses of the SCFAs followed the same trend (Additional file 1: Supplementary Figure S2b). These results are in concordance with our previous observations in the NASH [3] animal model. Thus, by focusing more on the specific effect of the two probiotics on the gut microbiota, we observed that the administration of both bacteria led to a unique change in the microbial composition at the phylum level, by significantly decreasing Bacteroidetes, compared to placebo administration (PBS) (p = 0.016 HFHC + LGG vs. HFHC + PBS; p = 0.018 HFHC + AKK vs. HFHC + PBS). At lower taxonomical levels, applying a linear discriminant analysis effect size (LEfSe) method, we observed that only a few families and genus suffered differential changes in their abundance depending on the probiotic administration. LGG produces, among others, a statistically significant increase in the relative abundance of Christensenellaceae, Ruminococcaceae, Peptococcaceae, and Lactobacillus (Fig. 4b). In the HFHC + AKK group, we observed higher abundance mainly in Faecalibacterium, Prevotella 9, and the Ruminococcus UCG005 group (Fig. 4b). Changes in the concentration of the Lactobacillus and Akkermansia genus were validated by qPCR, confirming higher levels of the Lactobacillus genus in the HFHC + LGG group and no differences in the Akkermansia genus across the groups (Fig. 4c). On the other hand, the Chao1 index showed statistically higher alpha-diversity in the HFHC + AKK group when compared with the HFHC + PBS group (p < 0.05); however, the Shannon index did not show any significant differences among the groups (Fig. 4d). These results indicate that probiotics can affect microbial diversity, but they did not induce major rearrangements of the faecal microbiota.
Average relative abundance of gut microbiota at the family level from NC, HFHC+PBS, HFHC+LGG, and HFHC+AKK groups. Bacterial taxa representing less than 0.5% of the total abundance are included in Others. b Gut microbiota differences. Results of LEfSe analysis (LDA scores > 2 and significance of p<0.05 as determined by Wilcoxon’s signed-rank test) showing significantly different taxa among the HFHC+PBS, HFHC+LGG, HFHC+AKK groups. Red indicates differential abundance in the HFHC+AKK group; green indicates differential abundance in the HFHC+LGG group; blue indicates differential abundance in the NC+PBS group. Bacterial taxa representing less than 0.5% of the total abundance are included in Others. c qPCR concentration. Bar charts (mean±SEM) represent comparison of Lactobacillus and Akkermansia genus concentration analysed by qPCR (log10 cells/g faeces), compared using the Kruskal-Wallis test followed by Dunn’s analysis (*p<0.05, comparison with all the groups). d Bacterial diversity. Box-and-whiskers (median and IRQ range) represent comparison of alpha-diversity of gut microbiota using Chao1 and Shannon indexes among groups, compared using a one-way ANOVA followed by Tukey’s test (*p<0.05, comparison with HFHC+PBS group).
Finally, the levels of the main SCFAs did not show differences between the probiotic groups and the HFHC + PBS group, with the only exception of acetate, which was lower in the probiotic groups (p < 0.01, HFHC + LGG vs. HFHC + PBS; p < 0.05, HFHC + AKK vs. HFHC + PBS) (Additional file 1: Supplementary Figure S2c).
Cognitive recovery is equally improved by environmental enrichment and Akkermansia muciniphila. No locomotor dysfunction has been found in any experimental group (p = 0.310; Fig. 5a). Both treatments, environmental enrichment and the administration of A. muciniphila CIP107961, were able to improve novel object recognition in HFHC animals. When we compared the discrimination ratio (d2) between HFHC + PBS, HFHC + EE, and HFHC + AKK to observe if there was a differential effect, we found that HFHC + EE and HFHC + AKK presented a higher d2 value than HFHC + PBS (p = 0.013), but the d2 value did not differ significantly between the HFHC + EE and HFHC + AKK groups. Thus, environmental enrichment and AKK administration were equally successful in reversing the novel object recognition impairment caused by the HFHC diet (Fig. 5b).
Regarding spatial working memory, we previously showed that EE and AKK improved the performance of HFHC animals. When comparing the mean latencies of HFHC + PBS, HFHC + EE, and HFHC + AKK, we observed that, whereas there were no statistically significant differences in the sample trials (p = 0.647), both HFHC + EE and HFHC + AKK showed lower retention latencies than HFHC + PBS (p = 0.004). However, retention latencies between HFHC + EE and HFHC + AKK were not significantly different. Thus, EE and AKK administration were both equally effective in restoring spatial working memory in the HFHC condition (Fig. 5c).
Bar charts (mean±SEM) represent the maximum speed (rpm) of the animals on the rod, compared using the Kruskal-Wallis test. There were no statistically significant differences between groups. b Novel object recognition test. Bar charts (mean±SEM) represent the discrimination ratio (d2) between the new object and the one previously observed. Mann–Whitney’s U test for independent samples (* comparison with zero) and the Kruskal-Wallis test followed by Tukey’s analysis (# comparison of HFHC+PBS, HFHC+EE and HFHC+AKK for d2 value) were used. HFHC+EE and HFHC+AKK showed improved recognition of a novel object in comparison with HFHC+PBS animals, but no differences were found between them. #p<0.05, **p≤0.010. c Spatial working memory test. Bar charts (mean±SEM) represent the average latency on the sample and retention trials. Two-tailed paired t-tests (* comparison with its respective sample) and one-way ANOVA followed by Tukey’s test (# comparison between HFHC+PBS, HFHC+EE and HFHC+AKK) were used. HFHC+EE and HFHC+AKK displayed improved performance on the spatial working memory task, in comparison with HFHC+PBS, but no differences were found between them. *#p<0.05, **p≤0.010.
Environmental enrichment and Akkermansia muciniphila have differential effects on brain metabolic activity. Next, we compared CCO values in the HFHC + PBS, HFHC + EE, and HFHC + AKK groups in order to discover whether there was a differential treatment effect on brain metabolism. We first observed that HFHC + EE displayed lower CCO levels than HFHC + PBS in the accumbens core (AcbC, p < 0.001), thalamus (p < 0.001), lateral amygdala (LaA, p = 0.002), DG (p < 0.001), and CA3 (p = 0.001). However, the opposite results were found in the HFHC + AKK group, where the CCO values were higher
than in the HFHC + PBS group in the cingulate cortex (Cg, p = 0.002), dST (p < 0.001), and BLA (p = 0.003).
Second, we found that HFHC + AKK showed higher CCO levels than HFHC + EE in the prefrontal cortex (p ≤ 0.014), dorsal and ventral striatum (p ≤ 0.024), thalamus (p < 0.001), amygdala (p ≤ 0.003), hippocampus (p ≤ 0.026), and PRh (p = 0.004) (Table 3). Thus, these results highlight that even if environmental enrichment and A. muciniphila CIP107961 lead to similar cognitive improvement, the brain metabolic modifications underlying this amelioration are different.
Table 3
Brain oxidative metabolism in HFHC groups subjected to PBS, AKK and EE. The CCO values are expressed as mean ± SEM. The studied regions included the prefrontal cortex (prelimbic (PrL), infralimbic (IL) and cingulate (Cg) cortex), the dorsal striatum (dST), the ventral striatum (accumbens core (AcbC) and shell (AcbSh)), the thalamus (anteromedial nucleus (AMT), anterodorsal nucleus (ADT), and anteroventral nucleus (AVT)), the amygdala (central (CeA), basolateral (BLA) and lateral (LaA)), the dorsal hippocampus (dentate gyrus (DG), CA1 and CA3 areas), and the perirhinal (PRh) and entorhinal (Ent) cortices. Data were analysed through one-way ANOVA followed by Tukey’s test (*#p < 0.05; * HFHC + EE and HFHC + AKK vs. HFHC + PBS; # HFHC + AKK vs. HFHC + EE).
Region | HFHC + PBS | HFHC + EE | HFHC + AKK |
PrL | 22.244 ± 1.336 | 19.999 ± 0.862 | # 25.929 ± 1.079 |
IL | 21.897 ± 0.998 | 19.634 ± 0.930 | # 24.277 ± 1.112 |
Cg | 22.650 ± 0.991 | 20.495 ± 0.791 | *# 26.131 ± 1.077 |
dST | 22.484 ± 0.878 | 19.889 ± 0.784 | *# 26.125 ± 0.775 |
AcbC | 26.777 ± 0.920 | * 22.246 ± 0.780 | # 28.662 ± 1.185 |
AcbSh | 30.770 ± 1.405 | 25.962 ± 0.693 | # 31.602 ± 1.731 |
AMT | 22.187 ± 0.556 | * 17.540 ± 0.824 | # 23.501 ± 0.897 |
ADT | 35.689 ± 1.132 | * 25.138 ± 1.207 | # 37.131 ± 0.992 |
AVT | 27.654 ± 1.206 | * 22.094 ± 0.700 | # 29.324 ± 0.708 |
CeA | 18.874 ± 0.849 | 16.578 ± 1.151 | # 22.133 ± 0.827 |
BLA | 21.297 ± 1.131 | 19.254 ± 1.343 | *# 25.123 ± 0.628 |
LaA | 18.128 ± 0.688 | * 14.897 ± 1.085 | # 20.002 ± 0.889 |
DG | 28.133 ± 1.170 | * 22.593 ± 0.770 | # 29.408 ± 0.964 |
CA1 | 17.692 ± 0.686 | 14.541 ± 1.231 | # 17.929 ± 0.695 |
CA3 | 16.890 ± 0.274 | * 13.403 ± 1.072 | # 17.787 ± 0.669 |
PRh | 20.272 ± 0.405 | 17.205 ± 1.147 | # 19.835 ± 0.510 |
Ent | 17.752 ± 0.405 | 16.035 ± 1.391 | 18.844 ± 1.051 |
Environmental enrichment and Akkermansia muciniphila differentially influence microbiota. Our previous results showed that both environmental enrichment implementation and administration of A. muciniphila CIP107961 improved novel object recognition, spatial working memory performance, and changes in the brain metabolism in HFHC animals. Both interventions also produced slight changes in the microbial composition compared to their control groups, as we explained above. When comparing the microbial composition of HFHC + EE and HFHC + AKK, noteworthy differences were found (Fig. 6); however, this could be explained by initial background differences in the faecal microbiota composition of the litters before treatment (HFHC + EE and HFHC + AKK) (76.29% − 68.65% of the relative abundance of Firmicutes, respectively; 13.56% − 17.92% of Proteobacteria; 9.21% − 9.33% of Bacteroidetes; 0.40% − 3. 78% of Verrucomicrobia; 0.37% – 0.33% of Actinobacteria). On the other hand, when comparing HFHC + AKK vs. HFHC + PBS, we observed that the probiotic did not induce a major community-wide compositional change, compared to the corresponding control group (HFHC + PBS). Only some previously mentioned changes were observed in the HFHC + AKK group.
Average relative abundance of prevalent microbiota at the family level from HFHC+EE, HFHC+PBS, HFHC+AKK groups. Bacterial taxa representing less than 0.5% of the total abundance are included in Others.
Regarding the levels of the main SCFAs, only propionate showed different concentrations between HFHC + EE and the HFHC + AKK and HFHC + PBS groups; and in the BCFA, iso-butyrate reached higher concentrations in the HFHC + AKK group, compared to the placebo group and the HFHC + EE group (Additional file 1: Supplementary Figure S3).