Bioconversion variation of ginsenoside CK mediated by human gut microbiota from healthy volunteers and colorectal cancer patients

In vivo pharmacokinetics of ginsenoside compound K mediated by gut microbiota

Ginsenoside Compound K (GCK) is the main metabolite of natural protopanaxadiol ginsenosides with diverse pharmacological effects. Gut microbiota contributes to the biotransformation of GCK, while the effect of gut microbiota on the pharmacokinetics of GCK in vivo remains unclear. To illustrate the role of gut microbiota in GCK metabolism in vivo, a systematic investigation of the pharmacokinetics of GCK in specific pathogen free (SPF) and pseudo-germ-free (pseudo-GF) rats were conducted. Pseudo-GF rats were treated with non-absorbable antibiotics. Liquid chromatography tandem mass spectrometry (LC-MS/MS) was validated for the quantification of GCK in rat plasma. Compared with SPF rats, the plasma concentration of GCK significantly increased after the gut microbiota depleted. The results showed that GCK absorption slowed down, Tmax delayed by 3.5 h, AUC0-11 increased by 1.3 times, CLz/F decreased by 0.6 times in pseudo-GF rats, and Cmax was 1.6 times higher than that of normal rats. The data indicated that gut microbiota played an important role in the pharmacokinetics of GCK in vivo.

Gene regulatory network inference based on causal discovery integrating with graph neural network

Gene regulatory network (GRN) inference from gene expression data is a significant approach to understanding aspects of the biological system. Compared with generalized correlation‐based methods, causality‐inspired ones seem more rational to infer regulatory relationships. We propose GRINCD, a novel GRN inference framework empowered by graph representation learning and causal asymmetric learning, considering both linear and non‐linear regulatory relationships. First, high‐quality representation of each gene is generated using graph neural network. Then, we apply the additive noise model to predict the causal regulation of each regulator‐target pair. Additionally, we design two channels and finally assemble them for robust prediction. Through comprehensive comparisons of our framework with state‐of‐the‐art methods based on different principles on numerous datasets of diverse types and scales, the experimental results show that our framework achieves superior or comparable performance under various evaluation metrics. Our work provides a new clue for constructing GRNs, and our proposed framework GRINCD also shows potential in identifying key factors affecting cancer development.

Biotransformation differences of ginsenoside compound K mediated by the gut microbiota from diabetic patients and healthy subjects

Many natural products can be bio-converted by the gut microbiota to influence pertinent efficiency. Ginsenoside compound K (GCK) is a potential anti-type 2 diabetes (T2D) saponin, which is mainly bio-transformed into protopanaxadiol (PPD) by the gut microbiota. Studies have shown that the gut microbiota between diabetic patients and healthy subjects are significantly different. Herein, we aimed to characterize the biotransformation of GCK mediated by the gut microbiota from diabetic patients and healthy subjects. Based on 16S rRNA gene sequencing, the results indicated the bacterial profiles were considerably different between the two groups, especially Alistipes and Parabacteroides that increased in healthy subjects. The quantitative analysis of GCK and PPD showed that gut microbiota from the diabetic patients metabolized GCK slower than healthy subjects through liquid chromatography tandem mass spectrometry (LC-MS/MS). The selected strain A. finegoldii and P. merdae exhibited a different metabolic capability of GCK. In conclusion, the different biotransformation capacity for GCK may impact its anti-diabetic potency.

Gut Microbial and Associated Metabolite Markers for Colorectal Cancer Diagnosis

Globally, colorectal cancer (CRC) is the second most common cause of mortality worldwide. Considerable evidence indicates that dysbiosis of the gut microbial community and its metabolite secretions play a fundamental role in advanced adenoma (ADA) and CRC development and progression. This study is a systematic review that aims to assess the clinical association between gut microbial markers and/or gut and circulating metabolites with ADA and CRC. Five electronic databases were searched by four independent reviewers. Only controlled trials that compared ADA and/or CRC with healthy control (HC) using either untargeted (16s rRNA gene or whole genome sequencing) or targeted (gene-based real-time PCR) identification methods for gut microbiome profile, or untargeted or targeted metabolite profiling approaches from the gut or serum/plasma, were eligible. Three independent reviewers evaluated the quality of the studies using the Cochrane Handbook for Systematic Reviews of Interventions. Twenty-four studies were eligible. We identified strong evidence of two microbial markers Fusobacterium and Porphyromonas for ADA vs. CRC, and nine microbial markers Lachnospiraceae-Lachnoclostridium, Ruminococcaceae-Ruminococcus, Parvimonas spp., Parvimonas micra, Enterobacteriaceae, Fusobacterium spp., Bacteroides, Peptostreptococcus-Peptostreptococcus stomatis, Clostridia spp.-Clostridium hylemonae, Clostridium symbiosum, and Porphyromonas-Porphyromonas asaccharolytica for CRC vs. HC. The remaining metabolite marker evidence between the various groups, including ADA vs. HC, ADA vs. HC, and CRC vs. HC, was not of sufficient quality to support additional findings. The identified gut microbial markers can be used in a panel for diagnosing ADA and/or CRC. Further research in the metabolite markers area is needed to evaluate the possibility to use in diagnostic or prognostic markers for colorectal cancer.

Alteration of gut microbiome and correlated amino acid metabolism are associated with acute myelocytic leukemia carcinogenesis

BACKGROUND

The aim of this study is to investigate the profiles of gut microbiota and metabolites in acute myelocytic leukemia (AML) patients treated with/without chemotherapy.

METHODS

Herein, high-throughput 16S rRNA gene sequencing was performed to analysis gut microbiota profiles, and liquid chromatography and mass spectrometry were performed to analysis metabolites profiles. The correlation between gut microbiota biomarkers identified by LEfSe and differentially expressed metabolites were determined by spearman association analysis.

RESULTS

The results showed the distinguished gut microbiota and metabolites profiles between AML patients and control individuals or AML patients treated with chemotherapy. Compared to normal populations, the ratio of Firmicutes to Bacteroidetes was increased at the phylum level than that in AML patients, and LEfSe analysis identified Collinsella and Coriobacteriaceae as biomarkers of AML patients. Differential metabolite analysis indicated that, compared to AML patients, numerous differential amino acids and analogs could be observed in control individuals and AML patients treated with chemotherapy. Interestingly, spearman association analysis demonstrated that plenty of bacteria biomarkers shows statistical correlations with differentially expressed amino acid metabolites. In addition, we found that both Collinsella and Coriobacteriaceae demonstrate remarkable positive correlation with hydroxyprolyl-hydroxyproline, prolyl-tyrosine, and tyrosyl-proline.

CONCLUSION

In conclusion, our present study investigated the role of the gut-microbiome-metabolome axis in AML and revealed the possibility of AML treatment by gut-microbiome-metabolome axis in the further.

Effect of ginsenoside compound K on alleviating colitis via modulating gut microbiota

BACKGROUND

Ginsenoside compound K (GC-K) potentially alleviates ulcerative colitis involved in gut microbiota, which is significantly associated with the occurrence and development of colitis. However, the effect and mechanism of GC-K on anti-colitis in relation to gut microbiota are not clear. This study focused on the prevention and mechanism of GC-K on Dextran sulfate sodium (DSS)-induced colitis of mice pertinent to gut microbiota.

METHODS

DSS was used to establish a chronic colitis mouse model. Body weight analysis, colon length measurement, HE staining, and inflammatory factors levels were processed in animal experiments. Flow cytometry was employed to analyze Th17/Treg cells in the mouse spleen and blood. 16S rRNA sequencing was utilized to analyze gut microbiota. Fecal microbiota transplantation (FMT) experiment was employed to verify the anti-colitis efficacy of GC-K by reshaping gut microbiota.

RESULTS

GC-K significantly relieved colitis-related symptoms due to decreased disease activity index (DAI) scores, spleen weight, and increased colon length. Additionally, the tight junction proteins were increased, and the pro-inflammatory cytokines, such as TNF-α, IL-6, IL-1β and IL-17, were decreased after GC-K treatment. Furthermore, Bacteroides spp. significantly increased after modeling. Moreover, FMT experiments confirmed that GC-K-driven gut microbiota greatly relieved DSS-induced colitis.

CONCLUSION

GC-K alleviated colitis via the modulation of gut microbiota.

Influences of Gastrointestinal Microbiota Dysbiosis on Serum Proinflammatory Markers in Epithelial Ovarian Cancer Development and Progression

GI microbiota has been implicated in producing the inflammatory tumor microenvironment of several cancers. Women with ovarian cancer often report GI-related symptoms at diagnosis although minimal is known about the possible GI bacteria that may trigger pro-tumorigenic immune responses in early EOC. The purpose of this study was to investigate the influences of GI microbiota dysbiosis on serum inflammatory markers during EOC utilizing a rodent model. This experimental design consisted of C57BL/6 mice randomly assigned to either the microbiota dysbiosis group (n = 6) or control group (n = 5). The CD7BL/6 mice assigned to the microbiota dysbiosis group were administered a mixture of broad-spectrum antibiotics (bacitracin and neomycin) for 2 weeks. Both groups were injected intraperitoneally with mouse ovarian epithelial cells that induce ovarian tumorigenesis. Levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) were assessed in the serum, and the composition of the GI microbiota in fecal samples was measured using 16S rRNA gene sequencing. Overall CRP serum levels were significantly lower and TNFα levels were significantly higher in the microbiota dysbiosis group compared to the control group. The abundances of microbiota that correlated with CRP serum levels in the combined groups were genus Parabacteroides, Roseburia, and Emergencia and species Ruminococcus faecis, Parabacteroides distasonis, Roseburia Faecis, and Emergencia timonensis. This study provides evidence to support for further investigation of the GI microbial profiles in patients at risk of EOC.

Ginsenoside compound K inhibits the proliferation, migration and invasion of Eca109 cell via VEGF-A/Pi3k/Akt pathway

OBJECTIVE

Esophageal cancer, one of the most common cancers in the upper digestive tract and is one of the leading cancer-related mortality worldwide. Accumulating studies found that Ginsenoside compound K (CK) has significantly anti-tumor effects, especially in the suppression of proliferation, migration, as well as invasion in various human cancers. While the effects of Ginsenoside CK in esophageal cancer have not been well studied. In our present study, we aim to explore the functions and mechanisms of Ginsenoside CK in the progression of esophageal cancer cells (Eca109).

METHODS

Cell Counting Kit-8 (CCK-8), wound healing, transwell and flow cytometry assays were applied to analyze the effects of Ginsenoside CK in the progression of Eca109 cell, western blot assay was used to investigate the potential downstream signaling pathway after Ginsenoside CK treatment.

RESULTS

Our study found that Ginsenoside CK can suppress cell proliferation, migration and invasion of Eca109 cell. Furthermore, the flow cytometry showed that Ginsenoside CK increased of apoptosis rates in Eca109 cell. The western blot results indicated that Ginsenoside CK decreased the expression of VEGF-A, P-Pi3k and P-Akt proteins. Moreover, the knockdown of VEGF-A gene could suppress cell proliferation, migration, invasion and induce apoptosis in Eca109 cell, and the expression of P-Pi3k and P-Akt proteins were significantly downregulated.

CONCLUSIONS

Our study suggests that Ginsenoside CK inhibits the proliferation, migration, invasion, and induced apoptosis of Eca109 cell by blocking VEGF-A/Pi3k/Akt signaling pathway.