Physiologically based pharmacokinetic model predictions of natural product-drug interactions between goldenseal, berberine, imatinib and bosutinib.

PURPOSE: This study implements a physiologically based pharmacokinetic (PBPK) modelling approach to predict the effect of hydrastine and berberine, two major alkaloids present in goldenseal extract, on pharmacokinetics of imatinib and bosutinib. METHODS: PBPK models of hydrastine and berberine were developed in the Simcyp Simulator (version 17), integrating prior in vitro knowledge and published clinical pharmacokinetic data. The models account for reversible and irreversible (mechanism-based) inhibition of CYP3A enzymes as well as inhibition of the P-glycoprotein transporter. Inhibitory potencies of hydrastine and berberine on imatinib and bosutinib were estimated based on in vitro inhibition of metabolite formation. RESULTS: The PBPK models provided reliable estimates on the magnitude of interactions due to co-administration of goldenseal extract or high-dose berberine on substrates of CYP3A enzymes (midazolam, indinavir and cyclosporine) and P-glycoprotein (digoxin). PBPK simulations predicted a moderate twofold increase (5th to 95th percentiles of prediction of 1.4-3.1) in systemic exposure (AUC) of bosutinib when co-administered with clinically relevant doses of goldenseal extract. A high dose of berberine (300 mg thrice daily) was also expected to affect bosutinib exposure, albeit to a lesser extent than that predicted with goldenseal (AUC ratio of 1.3, 5th to 95th percentile: 1.1-1.6). Conversely, the corresponding effects on imatinib exposure are unlikely to be of clinical importance (predicted AUC ratios of 1.0-1.2). CONCLUSION: PBPK model-based predictions highlighted potential clinically significant interactions between goldenseal extract and bosutinib, but not imatinib. Dose adjustment may need to be considered if co-administration is desirable. These findings should be confirmed with optimally designed controlled drug interaction studies.

Hierarchical Action of Mulberry miR156 in the Vegetative Phase Transition.

The vegetative phase transition is a prerequisite for flowering in angiosperm plants. Mulberry miR156 has been confirmed to be a crucial factor in the vegetative phase transition in Arabidopsis thaliana. The over-expression of miR156 in transgenic Populus × canadensis dramatically prolongs the juvenile phase. Here, we find that the expression of mno-miR156 decreases with age in all tissues in mulberry, which led us to study the hierarchical action of miR156 in mulberry. Utilizing degradome sequencing and dual-luciferase reporter assays, nine MnSPLs were shown to be directly regulated by miR156. The results of yeast one-hybrid and dual-luciferase reporter assays also revealed that six MnSPLs could recognize the promoter sequences of mno-miR172 and activate its expression. Our results demonstrate that mno-miR156 performs its role by repressing MnSPL/mno-miR172 pathway expression in mulberry. This work uncovered a miR156/SPLs/miR172 regulation pathway in the development of mulberry and fills a gap in our knowledge about the molecular mechanism of vegetative phase transition in perennial woody plants.

Composite score analysis for unsupervised comparison and network visualization of metabolomics data.

Metabolomics-based approaches are becoming increasingly popular to interrogate the chemical basis for phenotypic differences in biological systems. Successful metabolomics studies employ multivariate data analysis to compare large and highly complex datasets. A primary tool for unsupervised statistical analyses, principal component analysis (PCA), relies on the selection of a subsection of a maximum of three components from a larger model to visually represent similarity. The use of only three principal components limits the comprehensiveness of the model and can mask discrimination between samples. We have developed a new statistical metric, the composite score (CS), as a univariate statistic that incorporates multiple principal components to calculate a correlation matrix that enables quantitative comparisons of sample similarity between samples within one dataset based upon measured metabolome profiles. Composite score values were tabulated using profiles of complex extracts of dietary supplements from the plant Hydrastis canadensis (goldenseal) as a case study. Several outliers were unambiguously identified, and a PCA composite score network was developed to provide a graphical representation of the composite score matrix. Comparison with visualization using PCA score plots or dendrograms from hierarchical clustering analysis (HCA) demonstrates the utility of the composite score to as a tool for metabolomics studies that seek to quantify similarity among samples. An R-script for the calculation of composite score has been made available.

Botanical metabolite ions extraction from full electrospray ionization mass spectrometry using high-dimensional penalized regression.

INTRODUCTION: Mass spectrometric data analysis of complex biological mixtures can be a challenge due to its vast datasets. There is lack of data treatment pipelines to analyze chemical signals versus noise. These tasks, so far, have been up to the discretion of the analysts. OBJECTIVES: The aim of this work is to demonstrate an analytical workflow that would enhance the confidence in metabolomics before answering biological questions by serial dilution of botanical complex mixture and high-dimensional data analysis. Furthermore, we would like to provide an alternative approach to a univariate p-value cutoff from t-test for blank subtraction procedure between negative control and biological samples. METHODS: A serial dilution of complex mixture analysis under electrospray ionization was proposed to study firsthand chemical complexity of metabolomics. Advanced statistical models using high-dimensional penalized regression were employed to study both the concentration and ion intensity relationship and the ion-ion relationship per second of retention time sub dataset. The multivariate analysis was carried out with a tool built in-house, so called metabolite ions extraction and visualization, which was implemented in R environment. RESULTS: A test case of the medicinal plant goldenseal (Hydrastis canandensis L.), showed an increase in metabolome coverage of features deemed as "important" by a multivariate analysis compared to features deemed as "significant" by a univariate t-test. For an illustration, the data analysis workflow suggested an unexpected putative compound, 20-hydroxyecdysone. This suggestion was confirmed with MS/MS acquisition and literature search. CONCLUSION: The multivariate analytical workflow selects "true" metabolite ions signals and provides an alternative approach to a univariate p-value cutoff from t-test, thus enhancing the data analysis process of metabolomics.

Mechanism study of goldenseal-associated DNA damage.

Goldenseal has been used for the treatment of a wide variety of ailments including gastrointestinal disturbances, urinary tract disorders, and inflammation. The five major alkaloid constituents in goldenseal are berberine, palmatine, hydrastine, hydrastinine, and canadine. When goldenseal was evaluated by the National Toxicology Program (NTP) in the standard 2-year bioassay, goldenseal induced an increase in liver tumors in rats and mice; however, the mechanism of goldenseal-associated liver carcinogenicity remains unknown. In this study, the toxicity of the five goldenseal alkaloid constituents was characterized, and their toxic potencies were compared. As measured by the Comet assay and the expression of γ-H2A.X, berberine, followed by palmatine, appeared to be the most potent DNA damage inducer in human hepatoma HepG2 cells. Berberine and palmatine suppressed the activities of both topoisomerase (Topo) I and II. In berberine-treated cells, DNA damage was shown to be directly associated with the inhibitory effect of Topo II, but not Topo I by silencing gene of Topo I or Topo II. In addition, DNA damage was also observed when cells were treated with commercially available goldenseal extracts and the extent of DNA damage was positively correlated to the berberine content. Our findings suggest that the Topo II inhibitory effect may contribute to berberine- and goldenseal-induced genotoxicity and tumorigenicity.

Clinical assessment of CYP2D6-mediated herb-drug interactions in humans: effects of milk thistle, black cohosh, goldenseal, kava kava, St. John's wort, and Echinacea.

Cytochrome P450 2D6 (CYP2D6), an important CYP isoform with regard to drug-drug interactions, accounts for the metabolism of approximately 30% of all medications. To date, few studies have assessed the effects of botanical supplementation on human CYP2D6 activity in vivo. Six botanical extracts were evaluated in three separate studies (two extracts per study), each incorporating 16 healthy volunteers (eight females). Subjects were randomized to receive a standardized botanical extract for 14 days on separate occasions. A 30-day washout period was interposed between each supplementation phase. In study 1, subjects received milk thistle (Silybum marianum) and black cohosh (Cimicifuga racemosa). In study 2, kava kava (Piper methysticum) and goldenseal (Hydrastis canadensis) extracts were administered, and in study 3 subjects received St. John's wort (Hypericum perforatum) and Echinacea (Echinacea purpurea). The CYP2D6 substrate, debrisoquine (5 mg), was administered before and at the end of supplementation. Pre- and post-supplementation phenotypic trait measurements were determined for CYP2D6 using 8-h debrisoquine urinary recovery ratios (DURR). Comparisons of pre- and post-supplementation DURR revealed significant inhibition (approximately 50%) of CYP2D6 activity for goldenseal, but not for the other extracts. Accordingly, adverse herb-drug interactions may result with concomitant ingestion of goldenseal supplements and drugs that are CYP2D6 substrates.

In vivo effects of goldenseal, kava kava, black cohosh, and valerian on human cytochrome P450 1A2, 2D6, 2E1, and 3A4/5 phenotypes.

OBJECTIVES: Phytochemical-mediated modulation of cytochrome P450 (CYP) activity may underlie many herb-drug interactions. Single-time point phenotypic metabolic ratios were used to determine whether long-term supplementation of goldenseal ( Hydrastis canadensis ), black cohosh ( Cimicifuga racemosa ), kava kava ( Piper methysticum ), or valerian ( Valeriana officinalis ) extracts affected CYP1A2, CYP2D6, CYP2E1, or CYP3A4/5 activity. METHODS: Twelve healthy volunteers (6 women) were randomly assigned to receive goldenseal, black cohosh, kava kava, or valerian for 28 days. For each subject, a 30-day washout period was interposed between each supplementation phase. Probe drug cocktails of midazolam and caffeine, followed 24 hours later by chlorzoxazone and debrisoquin (INN, debrisoquine), were administered before (baseline) and at the end of supplementation. Presupplementation and postsupplementation phenotypic trait measurements were determined for CYP3A4/5, CYP1A2, CYP2E1, and CYP2D6 by use of 1-hydroxymidazolam/midazolam serum ratios (1-hour sample), paraxanthine/caffeine serum ratios (6-hour sample), 6-hydroxychlorzoxazone/chlorzoxazone serum ratios (2-hour sample), and debrisoquin urinary recovery ratios (8-hour collection), respectively. The content of purported "active" phytochemicals was determined for each supplement. RESULTS: Comparisons of presupplementation and postsupplementation phenotypic ratio means revealed significant inhibition (approximately 40%) of CYP2D6 (difference, -0.228; 95% confidence interval [CI], -0.268 to -0.188) and CYP3A4/5 (difference, -1.501; 95% CI, -1.840 to -1.163) activity for goldenseal. Kava produced significant reductions (approximately 40%) in CYP2E1 only (difference, -0.192; 95% CI, -0.325 to -0.060). Black cohosh also exhibited statistically significant inhibition of CYP2D6 (difference, -0.046; 95% CI, -0.085 to -0.007), but the magnitude of the effect (approximately 7%) did not appear to be clinically relevant. No significant changes in phenotypic ratios were observed for valerian. CONCLUSIONS: Botanical supplements containing goldenseal strongly inhibited CYP2D6 and CYP3A4/5 activity in vivo, whereas kava inhibited CYP2E1 and black cohosh weakly inhibited CYP2D6. Accordingly, serious adverse interactions may result from the concomitant ingestion of goldenseal supplements and drugs that are CYP2D6 and CYP3A4/5 substrates. Kava kava and black cohosh may interact with CYP2E1 and CYP2D6 substrates, respectively. Valerian appears to be less likely to produce CYP-mediated herb-drug interactions.