Study on the protective effect of berberine treatment on sepsis based on gut microbiota and metabolomic analysis

Berberine alleviates neuroinflammation by downregulating NFκB/LCN2 pathway in sepsis-associated encephalopathy: network pharmacology, bioinformatics, and experimental validation

BACKGROUND

Sepsis refers to a systemic inflammatory response caused by infection, involving multiple organs. Sepsis-associated encephalopathy (SAE), as one of the most common complications in patients with severe sepsis, refers to the diffuse brain dysfunction caused by sepsis without central nervous system infection. However, there is no clear diagnostic criteria and lack of specific diagnostic markers.

METHODS

The main active ingredients of coptidis rhizoma(CR) were identified from TCMSP and SwissADME databases. SwissTargetPrediction and PharmMapper databases were used to obtain targets of CR. OMIM, DisGeNET and Genecards databases were used to explore targets of SAE. Limma differential analysis was used to identify the differential expressed genes(DEGs) in GSE167610 and GSE198861 datasets. WGCNA was used to identify feature module. GO and KEGG enrichment analysis were performed using Metascape, DAVID and STRING databases. The PPI network was constructed by STRING database and analyzed by Cytoscape software. AutoDock and PyMOL software were used for molecular docking and visualization. Cecal ligation and puncture(CLP) was used to construct a mouse model of SAE, and the core targets were verified in vivo experiments.

RESULTS

277 common targets were identified by taking the intersection of 4730 targets related to SAE and 509 targets of 9 main active ingredients of CR. 52 common DEGs were mined from GSE167610 and GSE198861 datasets. Among the 25,864 DEGs in GSE198861, LCN2 showed the most significant difference (logFC = 6.9). GO and KEGG enrichment analysis showed that these 52 DEGs were closely related to "inflammatory response" and "innate immunity". A network containing 38 genes was obtained by PPI analysis, among which LCN2 ranked the first in Degree value. Molecular docking results showed that berberine had a well binding affinity with LCN2. Animal experiments results showed that berberine could inhibit the high expression of LCN2,S100A9 and TGM2 induced by CLP in the hippocampus of mice, as well as the high expression of inflammatory factors (TNFα, IL-6 and IL-1β). In addition, berberine might reduce inflammation and neuronal cell death by partially inhibiting NFκB/LCN2 pathway in the hippocampus of CLP models, thereby alleviating SAE.

CONCLUSION

Overall, Berberine may exert anti-inflammatory effects through multi-ingredients, multi-targets and multi-pathways to partially rescue neuronal death and alleviate SAE.

Berberine improved the microbiota in lung tissue of colon cancer and reversed the bronchial epithelial cell changes caused by cancer cells

Objective

The lung is a common organ for colon cancer metastasis, and the objective of this experiment was to explore the protective effect of berberine on lung tissue or alveolar epithelial cells induced by colon cancer.

Methods

Thirty-six BALB/c nude mice were used to establish a xenograft model of colon cancer with the HT29 cell line and were treated with berberine and probiotics. Human bronchial epithelial BEAS-2B cells were induced by conditioned medium (CM) from the colon cancer cell lines HT29 and RKO and were treated with berberine. Lung tissues were collected to detect the changes in the microbiota using 16S rDNA sequencing and the expression of inflammatory cytokines. The expression of E-cadherin and N-cadherin in BEAS-2B cells was detected by cellular immunofluorescence. The changes in cell proliferation were detected by the CCK-8 assay. Western blotting was used to detect E-cadherin, N-cadherin, collagen I, fibronectin, PDGF-β, and RAD51 expression in BEAS-2B cells.

Results

The richness and evenness of the microbiota in the lung tissues of mice with colon cancer were significantly lower than those of the control group. Berberine significantly increased the abundances of Bacteroidetes, Bacteroidia, Bacteroidales, Lactobacillaceae, Lactobacillus and Acinetobacter in the lung tissue of mice with colon cancer, with reduced abundances of Actinobacteria, Bacillales, Staphylococcaceae and Staphylococcus. Berberine or probiotics significantly increased the alpha diversity of the lung microbiota. Compared with probiotics, berberine significantly enhanced the abundance of microbiota involved in the metabolism of lysosomes, flavone and flavonol biosynthesis, glycosaminoglycan degradation, and glycosphingolipid biosynthesis-ganglio. Berberine increased IL-6 and IL-10 and decreased IL-17 and IFN-γ expression in lung tissue (P > 0.05), but berberine-probiotics significantly decreased IL-17 and IFN-γ and increased IL-10 expression (P < 0.05). Colon cancer cells could not induce BEAS-2B proliferation but decreased the expression of the epithelial marker E-cadherin and altered the expression of extracellular matrix-related proteins (collagen I, fibronectin, and PDGF-β), which were reversed by berberine. Berberine increased RAD51 expression in BEAS-2B cells, which had been decreased by HT29 and RKO CM treatment.

Conclusion

Berberine can selectively regulate the abundance of some microbiomes of lung tissue in colon cancer, improve the inflammatory response in lung tissue, and antagonize the cancerous stimulation of colon cancer cells to lung tissue cells by regulating the bronchial epithelial cell phenotype, extracellular matrix remodelling and the expression of the repair gene RAD51.