期刊
JOURNAL OF TRANSLATIONAL MEDICINE
卷 19, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s12967-021-03032-9
关键词
Alzheimer's disease; PS cDKO mice; Metabolomics; Gut microbiota; 16S rRNA sequencing
资金
- General Program of National Natural Science Foundation of China [81773927]
- Innovation Project for Undergraduates of Shanghai University of Traditional Chinese Medicine [2020SHUTCM134]
- Natural Science Foundation of Shanghai [21ZR1460900]
PS cDKO mice show metabolic and microbiotic changes at both early and mature ages, with disturbed metabolic pathways involving glycine, serine and threonine metabolism, glyoxylate and dicarboxylate metabolism, pentose and glucuronate interconversions, starch and sucrose metabolism, and citrate cycle. The altered gut microbiota, including increases in Lactobacillus and decreases in norank_f_Muribaculaceae, Lachnospiraceae_NK4A136_group, Mucispirillum, and Odoribacter, are associated with differential metabolite levels.
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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