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Multi-Omics Integration to Reveal the Mechanism of Hepatotoxicity Induced by Dictamnine.

ABSTRACT: Herb-induced liver injury (HILI) has become a great concern worldwide due to the widespread usage of herbal products. Among these products is Dictamni Cortex (DC), a well-known Traditional Chinese Medicine (TCM), widely used to treat chronic dermatosis. Dictamni Cortex has drawn increasing attention because of its hepatotoxicity caused by the hepatotoxic component, dictamnine. However, the potential hepatotoxicity mechanism of dictamnine remains unclear. Therefore, this study aimed to use the multi-omics approach (transcriptomic, metabolomic, and proteomic analyses) to identify genes, metabolites, and proteins expressions associated with dictamnine-induced hepatotoxicity. A study on mice revealed that a high dose of dictamnine significantly increases serum aspartate aminotransferase (AST) activity, total bilirubin (TBIL), and direct bilirubin (DBIL) levels, the relative liver weight and liver/brain weight ratio in female mice (P < 0.05 and P < 0.01), compared to the normal control group. Liver histologic analysis further revealed a high dose of dictamnine on female mice caused hepatocyte vesicular steatosis characterized by hepatocyte microvesicles around the liver lobules. The expressed genes, proteins, and metabolites exhibited strong associations with lipid metabolism disorder and oxidative stress. Dictamnine caused increased oxidative stress and early hepatic apoptosis via up-regulation of glutathione S transferase a1 (GSTA1) and Bax/Bcl-2 ratio and down-regulation of the antioxidative enzymes superoxide dismutase (SOD), catalase, and glutathione peroxidase 1 (GPx-1). Besides, the up-regulation of Acyl-CoA synthetase long-chain family member 4 (ACSL4) and down-regulation of acetyl-coa acetyltransferase 1 (ACAT1) and fatty acid binding protein 1 (FABP-1) proteins were linked to lipid metabolism disorder. In summary, dictamnine induces dose-dependent hepatotoxicity in mice, which impairs lipid metabolism and aggravates oxidative stress.

SUBMITTER: Tu C

PROVIDER: S-EPMC8476863 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: The mechanisms responsible for calorie restriction (CR)-induced improvement in insulin sensitivity (IS) have not been fully elucidated. Greater insight can be achieved through deep biological phenotyping of subjects undergoing CR, and integration of big data. Materials and Methods: An integrative approach was applied to investigate associations between change in IS and factors from host, microbiota, and lifestyle after a 6-week CR period in 27 overweight or obese adults (ClinicalTrials.gov: NCT01314690). Partial least squares regression was used to determine associations of change (week 6 - baseline) between IS markers and lifestyle factors (diet and physical activity), subcutaneous adipose tissue (sAT) gene expression, metabolomics of serum, urine and feces, and gut microbiota composition. ScaleNet, a network learning approach based on spectral consensus strategy (SCS, developed by us) was used for reconstruction of biological networks. Results: A spectrum of variables from lifestyle factors (10 nutrients), gut microbiota (10 metagenomics species), and host multi-omics (metabolic features: 84 from serum, 73 from urine, and 131 from feces; and 257 sAT gene probes) most associated with IS were identified. Biological network reconstruction using SCS, highlighted links between changes in IS, serum branched chain amino acids, sAT genes involved in endoplasmic reticulum stress and ubiquitination, and gut metagenomic species (MGS). Linear regression analysis to model how changes of select variables over the CR period contribute to changes in IS, showed greatest contributions from gut MGS and fiber intake. Conclusion: This work has enhanced previous knowledge on links between host glucose homeostasis, lifestyle factors and the gut microbiota, and has identified potential biomarkers that may be used in future studies to predict and improve individual response to weight-loss interventions. Furthermore, this is the first study showing integration of the wide range of data presented herein, identifying 115 variables of interest with respect to IS from the initial input, consisting of 9,986 variables. Clinical Trial Registration: clinicaltrials.gov (NCT01314690).

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Multi-Omics Integration to Reveal the Mechanism of Hepatotoxicity Induced by Dictamnine.

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