Integrated spatial metabolomics and network pharmacology to explore the pharmacodynamic substances and mechanism of Radix ginseng-Schisandra chinensis Herb Couple on Alzheimer's disease.

Radix ginseng and Schisandra chinensis have been extensively documented in traditional Chinese medicine (TCM) for their potential efficacy in treating dementia. However, the precise mechanism of their therapeutic effects remains to be fully elucidated. In this study, air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) and network pharmacology are used to investigate the pharmacodynamics and mechanism underlying the herbal combination consisting of Radix ginseng-Schisandra chinensis (RS) in a rodent model for Alzheimer's disease (AD). Brain histopathological findings suggested that RS attenuates hippocampal damage in AD mice, making this combination a potential AD treatment. Twenty-eight biomarkers were identified by spatial metabolomics analysis, which are intricately linked to neuroinflammation, neurotransmitter imbalance, energy deficiency, oxidative stress, and aberrant fatty acid metabolism in AD. The total extract of RS (TE) affected 22 of these biomarkers, with the small molecule components of RS (SN) significantly influencing 19 and the large molecule components of RS (PR) impacting 14. Nine small molecule components are likely to dominate the pharmacodynamics of RS. We constructed a target interaction network based on the corresponding bioactivities that revealed relationships amongst 11 key biomarkers, 8 active ingredients and 12 critical targets. This research illustrates the immense potential of spatial metabolomics and network pharmacology in the study of TCM, revealing the targets and mechanisms underlying herbal formulas.

Untargeted and spatial-resolved metabolomics characterize serum and tissue-specific metabolic reprogramming in acute kidney injury.

Background: Acute kidney injury (AKI) is one of the most common clinical emergencies characterized by rapid progression, difficulty in early diagnosis, and high mortality. Currently, there are no effective AKI early diagnostic methods and treatments. Therefore, identifying new mechanisms of AKI have become urgent for development new targets for early diagnosis and treatment of AKI in the current clinical setting. Methods: In this study, systematic analysis and comparison of serum metabolic profiles of clinical AKI patients, chronic kidney disease (CKD) patients, and healthy subjects were performed using untargeted metabolomics. Moreover, the first spatial metabolomic analysis of kidney tissues in an AKI mouse model using MALDI-TOF MS technology was conducted. Differentially expressed metabolites were identified using a comprehensive, publicly available database. The metabolic data obtained were evaluated using principal component analysis, (orthogonal) partial least squares discriminant analysis, and metabolic pathway analysis to explore the unique serum metabolic profile of the patients, as well as to characterize the spatial distribution of differential metabolites in the kidneys of AKI mice. Results: Significant changes in the metabolite levels of amino acids, carnitine, and lipids were observed in the AKI and CKD groups versus the healthy population, suggesting that kidney injury may lead to abnormalities in various metabolic pathways, such as amino acids, fatty acids, and lipids. The significant difference between the AKI and CKD groups were found for the first time in these indexes including amino acid, carnitine, fatty acid, and lipid levels. Additionally, spatial metabolomics results revealed that amino acid, carnitine, organic acid, and fatty acid metabolites were more likely significantly altered in the renal cortex, while lipid metabolites were both differentially distributed in the cortex and medulla of the AKI group. Conclusion: Abnormalities in the serum metabolism of amino acids, carnitine, and lipids in patients with kidney diseases, such as AKI and CKD, are closely associated with the physiological dysfunction of kidney injury. Metabolic differences between patients with AKI and CKD were compared for the first time, showing that fatty acid oxidative inhibition was more severe in patients with AKI. Furthermore, spatial metabolomics has revealed metabolic reprogramming with tissue heterogeneity in AKI mice model. Our study provides valuable information in the molecular pathological features of AKI in the kidney tissues.