Background Given the clinical low efficient treatment based on mono-brain-target design in Alzheimer’s disease (AD) and an increasing emphasis on microbiome-gut-brain axis which was considered as a crucial pathway to affect the progress of AD along with metabolic changes, integrative metabolomic signatures and microbiotic community profilings were applied on the early age (2-month) and mature age (6-month) of presenilin1/2 conditional double knockout (PS cDKO) mice which exhibit a series of AD-like phenotypes, comparing with gender and age-matched C57BL/6 wild-type (WT) mice to clarify the relationship between microbiota and metabolomic changes during the disease progression of AD. Materials and methods Urinary and fecal samples from PS cDKO mice and gender-matched C57BL/6 wild-type (WT) mice both at age of 2 and 6 months were collected. Urinary metabolomic signatures were measured by the gas chromatography-time-of-flight mass spectrometer, as well as 16S rRNA sequence analysis was performed to analyse the microbiota composition at both ages. Furthermore, combining microbiotic functional prediction and Spearman’s correlation coefficient analysis to explore the relationship between differential urinary metabolites and gut microbiota. Results In addition to memory impairment, PS cDKO mice displayed metabolic and microbiotic changes at both of early and mature ages. By longitudinal study, xylitol and glycine were reduced at both ages. The disturbed metabolic pathways were involved in glycine, serine and threonine metabolism, glyoxylate and dicarboxylate metabolism, pentose and glucuronate interconversions, starch and sucrose metabolism, and citrate cycle, which were consistent with functional metabolic pathway predicted by the gut microbiome, including energy metabolism, lipid metabolism, glycan biosynthesis and metabolism. Besides reduced richness and evenness in gut microbiome, PS cDKO mice displayed increases in Lactobacillus, while decreases in norank_f_Muribaculaceae, Lachnospiraceae_NK4A136_group, Mucispirillum, and Odoribacter. Those altered microbiota were exceedingly associated with the levels of differential metabolites. Conclusions The urinary metabolomics of AD may be partially mediated by the gut microbiota. The integrated analysis between gut microbes and host metabolism may provide a reference for the pathogenesis of AD.

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Alzheimer’s disease (AD) is usually manifested in patients with dementia, accompanied by anxiety and other mental symptoms. Emerging evidence from humans indicates that people who suffer from anxiety in their early life are more likely to develop AD in later life. Mitochondria, the prominent organelles of energy production in the brain, have crucial physiological significance for the brain, requiring considerable energy to maintain its normal physiological activities. Net reactive oxygen species (ROS) was produced by mitochondrial impairment, in which oxidative stress is also included, and the production of ROS is mostly more than that of removal. In this paper, we propose that as a critical process in brain pathology, mitochondrial dysfunction caused by anxiety triggering oxidative stress might be a possible mechanism that links early life anxiety to AD in later life. Several pivotal physiological roles of mitochondria are reviewed, including functions regulating glucose homeostasis, which may disrupt in oxidative stress. Increased levels of oxidative stress are constantly shown in anxiety disorder patients, and antioxidant drugs have promise in treating anxiety. In the early stages of AD, mitochondrial dysfunction is concentrated around senile plaques, a landmark lesion composed of aggregated Aβ and Tau protein. In turn, the accumulated Aβ and Tau disrupts mitochondrial activity, and the tricky physiological processes of mitochondria might be significant to the course of AD. In the end, we conclude that mitochondria might present as one of the novel therapeutic targets to block oxidative stress in patients with anxiety disorders to prevent AD in the early stage.

AimThe treatment of Alzheimer’s disease (AD) is still a worldwide problem due to the unclear pathogenesis and lack of effective therapeutic targets. In recent years, metabolomic and gut microbiome changes in patients with AD have received increasing attention, and the microbiome–gut–brain (MGB) axis has been proposed as a new hypothesis for its etiology. Considering that electroacupuncture (EA) efficiently moderates cognitive deficits in AD and its mechanisms remain poorly understood, especially regarding its effects on the gut microbiota, we performed urinary metabolomic and microbial community profiling on EA-treated AD model mice, presenilin 1/2 conditional double knockout (PS cDKO) mice, to observe the effect of EA treatment on the gut microbiota in AD and find the connection between affected gut microbiota and metabolites.Materials and methodsAfter 30 days of EA treatment, the recognition memory ability of PS cDKO mice was evaluated by the Y maze and the novel object recognition task. Urinary metabolomic profiling was conducted with the untargeted GC-MS method, and 16S rRNA sequence analysis was applied to analyze the microbial community. In addition, the association between differential urinary metabolites and gut microbiota was clarified by Spearman’s correlation coefficient analysis.Key findingsIn addition to reversed cognitive deficits, the urinary metabolome and gut microbiota of PS cDKO mice were altered as a result of EA treatment. Notably, the increased level of isovalerylglycine and the decreased levels of glycine and threonic acid in the urine of PS cDKO mice were reversed by EA treatment, which is involved in glyoxylate and dicarboxylate metabolism, as well as glycine, serine, and threonine metabolism. In addition to significantly enhancing the diversity and richness of the microbial community, EA treatment significantly increased the abundance of the genus Mucispirillum, while displaying no remarkable effect on the other major altered gut microbiota in PS cDKO mice, norank_f_Muribaculaceae, Lactobacillus, and Lachnospiraceae_NK4A136 group. There was a significant correlation between differential urinary metabolites and differential gut microbiota.SignificanceElectroacupuncture alleviates cognitive deficits in AD by modulating gut microbiota and metabolites. Mucispirillum might play an important role in the underlying mechanism of EA treatment. Our study provides a reference for future treatment of AD from the MGB axis.

In recent years, many reports focus on the hepatotoxicity of Gynura segetum root extract (GSrE), but the interaction between GSrE and the gut microbiota is still unclear. This study investigated the mechanism of GSrE-induced hepatotoxicity of different doses and exposure durations by combining metabolomics and gut microbiota analysis. SD rats were divided into 3 groups: blank, low-dose (7.5 g/kg), and high-dose (15 g/kg) groups. Urine and feces samples were collected on day 0, day 10, and day 21. Metabolomics based on gas chromatography-mass spectrometry (GC-MS) was carried out to identify metabolites and metabolic pathways. 16S rDNA gene sequencing was applied to investigate the composition of gut microbiota before and after GSrE-induced hepatotoxicity. Finally, a correlation analysis of metabolites and gut microbiota was performed. Differential metabolites in urine and feces involved amino acids, carbohydrates, lipids, organic acids, and short chain fatty acids. Among them, L-valine, L-proline, DL-arabinose, pentanoic acid, D-allose, and D-glucose in urine and D-lactic acid and glycerol in fecal metabolites depended on the exposure of time and dose. In addition, 16S rDNA sequencing analysis revealed that GSrE-induced hepatotoxicity significantly altered the composition of gut microbiota, namely, f_Muribaculaceae_Unclassified, Lactobacillus, Bacteroides, Lachnospiraceae_NK4A136_group, f_Ruminococcaceae_Unclassified, Prevotellaceae_Ga6A1_group, and Escherichia-Shigella. The correlation analysis between gut microbiota and differential metabolites showed the crosstalk between the gut microbiota and metabolism in host involving energy, lipid, and amino acid metabolisms. In summary, our findings revealed that peripheral metabolism and gut microbiota disorders were time- and dose-related and the correlation between gut microbiota and metabolites in GSrE-induced hepatotoxicity.