Mice brain metabolomics after the exposure to a "chemical cocktail" and selenium supplementation through the gut-brain axis

Several environmental pollutants have been shown to damage brain and affect gut microbiota. Limited evidence is available about the impact of "chemical cocktails" (CC) of xenobiotics on brain metabolome and their possible influence in the gut-brain crosstalk. To this end, BALB/c mice were exposed to heavy metals (As, Hg, Cd) and pharmaceuticals (diclofenac and flumequine) under regular rodent diet or supplemented with selenium (Se). Selenium, an antioxidant well-known for its antagonism against the neurotoxicity of several pollutants, modulated several brain metabolic impairments caused by CC (e.g., brain levels of the excitatory amino acid N-acetyl aspartic acid) by influencing mainly the metabolisms of purine, glycosylate and dicarboxylate, glutamate, glycerophospholipid, alanine and aspartate. Numerous associations were obtained between brain metabolites and gut microbes and they changed after Se-supplementation (e.g., Lactobacillus was positively associated with a brain ceramide, phosphoserine, phosphocholine, vitamin D3 derivative, fatty acids, malic acid, amino acids, and urea after the exposure, but not after Se-supplementation). Our results showed numerous evidences about the impact of CC on brain metabolome, the potential role of Se as an antagonist and their impact on the gut-brain axis. Further research is needed to understand the complex mechanism of action implied on CC-brain-microbiota interactions.

Assessment of solid phase microextraction as a sample preparation tool for untargeted analysis of brain tissue using liquid chromatography-mass spectrometry

This work presents an evaluation of solid-phase microextraction (SPME) SPME in combination with liquid chromatography-high resolution mass spectrometry (LC-HRMS) as an analytical approach for untargeted brain analysis. The study included a characterization of the metabolite coverage provided by C18, mixed-mode (MM, with benzene sulfonic acid and C18 functionalities), and hydrophilic lipophilic balanced (HLB) particles as sorbents in SPME coatings after extraction from cow brain homogenate at static conditions. The effects of desorption solvent, extraction time, and chromatographic modes on the metabolite features detected were investigated. Method precision and absolute matrix effects were also assessed. Among the main findings of this work, it was observed that all three tested coating chemistries were able to provide comparable brain tissue information. HLB provided higher responses for polar metabolites; however, as these fibers were prepared in-house, higher inter-fiber relative standard deviations were also observed. C18 and HLB coatings offered similar responses with respect to lipid-related features, whereas MM and C18 provided the best results in terms of method precision. Our results also showed that the use of methanol is essential for effective desorption of non-polar metabolites. Using a reversed-phase chromatographic method, an average of 800 and 1200 brain metabolite features detected in positive and negative modes, respectively, met inter-fibre RSD values below 30% (n=4) after removal of fibre and solvent artefacts from the associated datasets. For features detected using a lipidomics method, a total of 900 and 1800 features detected using C18 fibers in positive and negative mode, respectively, met the same criteria. In terms of absolute matrix effects, the majority of the model metabolites tested showed values between 80 and 120%, which are within the acceptable range. Overall, the findings of this work lay the foundation for further optimization of parameters for SPME-LC-HRMS methods suitable for in vivo and ex vivo brain (and other tissue) untargeted studies, and support the applicability of this approach for non-destructive tissue metabolomics.

Comprehensive Investigation of Metabolic Changes Occurring in the Rat Brain Hippocampus after Fluoxetine Administration Using Two Complementary In Vivo Techniques: Solid Phase Microextraction and Microdialysis

Fluoxetine is among the most prescribed antidepressant drugs worldwide. Nevertheless, limited information is known about its definitive mechanism. Although in vivo examinations performed directly in related brain structures can provide more realistic, and therefore more insightful, knowledge regarding the mechanisms and efficacy of this drug, only a few techniques are applicable for in vivo monitoring of metabolic alterations in the brain following an inducement. Among them, solid phase microextraction (SPME) and microdialysis (MD) have emerged as ideal in vivo tools for extraction of information from biosystems. In this investigation, we scrutinized the capabilities of SPME and MD to detect ongoing changes in the brain following acute fluoxetine administration. Sequential in vivo samples were collected simultaneously from male rats' hippocampi using SPME and MD before drug administration in order to establish a baseline; then samples were collected again following fluoxetine administration for an investigation of small molecule alterations. Our results indicate that MD provides more comprehensive information for polar compounds, while SPME provides superior information with respect to lipids and other medium level polar molecules. Interestingly, in the lipidomic investigation, all dysregulated features were found to be membrane lipids and associated compounds. Moreover, in the metabolomic investigations, dysregulation of hippocampal metabolite levels associated with fatty acid transportation and purine metabolisms were among the most notable findings. Overall, our evaluation of the obtained data corroborates that, when used in tandem, SPME and MD are capable of providing comprehensive information regarding the effect of fluoxetine in targeted brain structures and further elucidating this drug's mechanisms of action in the brain.

Metabolic effects of repeated ketamine administration in the rat brain

Ketamine is a popular recreational drug used in club and dance music settings. Evidence suggests that chronic or repeated ketamine use could induce neurological and psychological harm, while the mechanisms underlying ketamine's effects on the nervous system are still unclear. The aim of this study was to explore the metabolic changes that occur in the prefrontal cortex (PFC), hippocampus (Hip) and striatum of rats with repeated ketamine exposure and withdrawal intervention and to identify the potential metabolic pathways influenced by ketamine. An untargeted ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS)-based metabolomics method coupled with multivariate and univariate statistical analysis was applied to analyze the metabolic profiles of the PFC, Hip, and striatum and to identify metabolite alterations. The pathway analysis tool in MetaboAnalyst was subsequently applied for pathway predictions. A total of 79, 54 and 58 changed metabolites were identified in the PFC, Hip and striatum, respectively, after repeated ketamine exposure. Pathway analysis indicated that purine metabolism and glycerophospholipid metabolism were the main pathways disturbed by ketamine in all three brain regions. After one week of withdrawal intervention, most changed metabolites in the Hip and striatum had been restored to control levels, while the metabolite alterations in the PFC were persistent. These results revealed that repeated ketamine exposure significantly changed purine metabolism and glycerophospholipid metabolism in the PFC, Hip and striatum, which might be involved in the neurotoxic effects of ketamine. Additionally, this study also identified that the PFC, rather than the Hip or striatum, was more likely to be the target region of the long-term effects of ketamine.

Integrated network pharmacology and brain metabolomics to analyze the mechanism of Dihuang Yinzi intervention in Alzheimer's disease

Ethnopharmacological relevance

Alzheimer's disease (AD) is an incurable neurodegenerative disease that has become one of the most important diseases threatening global public health security. Dihuang Yinzi (DHYZ) is a traditional Chinese medicine that has been widely used for the treatment of AD and has significant therapeutic effects, but its specific mechanism of action is still unclear.The aim of the study is to investigate the specific mechanism of DHYZ in treating AD based on brain metabolomics and network pharmacology.

Materials and methods

In this study, the classic APPswe/PS1E9 (APP/PS1) mice were selected as the AD animal model, and the mechanism of DHYZ was studied. The learning and memory ability of mice was detected by Y-maze test, and the ultrastructure of neural cells in the brain of the mice was observed by transmission electron microscope (TEM). Then, the mechanism of DHYZ intervention in AD was analyzed by constructing network pharmacology, and combined with brain metabolomics based on ultra performance liquid chromatography-mass spectrometry (UPLC-MS) to detect differential metabolic markers and their metabolic pathways. In addition, a joint analysis of differential metabolites and potential targets for DHYZ treatment of AD is conducted to deeply explore the relationship between key targets, differential metabolites, and metabolic pathways.

Results

After 30 days of DHYZ treatment, the spatial work and reference memory ability of APP/PS1 mice were significantly improved, the structure of mitochondria and synapses in the neurons of the brain were basically normal. 202 potential targets for DHYZ treatment of AD were screened through network pharmacology, and after enrichment analysis, these targets showed correlation with redox reactions, mitochondrial and synaptic functional pathways. And 7 differential metabolites were identified in brain metabolomics are Nicotinic acid, N-Formyl-L-glutamic acid, 5-(2-Hydroxyethyl)-4-methylthiazole, D-Gulono-1,4-lactone, Norepinephrine, 3-Methylotrophicacid, Palmitic acid. These differential metabolites mainly involve nicotinite and nicotinamide metabolism, pertussis, cAMP signaling pathway, cysteine and methionine metabolism. Notablely, through matching analysis of targets and metabolites, a total of 20 genes were found to match Nicotinic acid, 51 genes were found to match norepinephrine, and 14 genes intersected with the two metabolites, enrichment analysis of the intersected genes showed that neuroactive light receptor interaction, serotonergic synapse, and cAMP signaling were significantly affected, which is consistent with previous network pharmacology results.

Conclusion

This study identified the main chemical ingredients of DHYZ intervention in AD may originated from Polygala tenuifolia Wild, Dendrobium nobile Line and Ophiogon japonicus (L.f) Ker-Gawl. Combined with Y Maze, TEM and brain metabolomics, revealed that DHYZ can improve the learning and memory abilities and brain pathological morphology of APP/PS1 mice by regulating nicotinic acid, 3-Methylthiopropionic acid, pertussis and their metabolic pathways, including nicotinate and nicotinamide metabolism, cAMP signaling pathway and cysteine and methionine metabolism. In short, this study provides a new research foundation and direction for the treatment of AD with traditional Chinese medicine.