Interaction Metabolomics to Discover Synergists in Natural Product Mixtures.

Mass spectrometry metabolomics has become increasingly popular as an integral aspect of studies to identify active compounds from natural product mixtures. Classical metabolomics data analysis approaches do not consider the possibility that interactions (such as synergy) could occur between mixture components. With this study, we developed "interaction metabolomics" to overcome this limitation. The innovation of interaction metabolomics is the inclusion of compound interaction terms (CITs), which are calculated as the product of the intensities of each pair of features (detected ions) in the data matrix. Herein, we tested the utility of interaction metabolomics by spiking known concentrations of an antimicrobial compound (berberine) and a synergist (piperine) into a set of inactive matrices. We measured the antimicrobial activity for each of the resulting mixtures against Staphylococcus aureus and analyzed the mixtures with liquid chromatography coupled to high-resolution mass spectrometry. When the data set was processed without CITs (classical metabolomics), statistical analysis yielded a pattern of false positives. However, interaction metabolomics correctly identified berberine and piperine as the compounds responsible for the synergistic activity. To further validate the interaction metabolomics approach, we prepared mixtures from extracts of goldenseal (Hydrastis canadensis) and habañero pepper (Capsicum chinense) and correctly correlated synergistic activity of these mixtures to the combined action of berberine and several capsaicinoids. Our results demonstrate the utility of a conceptually new approach for identifying synergists in mixtures that may be useful for applications in natural products research and other research areas that require comprehensive mixture analysis.

Correlative metabologenomics of 110 fungi reveals metabolite-gene cluster pairs.

Natural products research increasingly applies -omics technologies to guide molecular discovery. While the combined analysis of genomic and metabolomic datasets has proved valuable for identifying natural products and their biosynthetic gene clusters (BGCs) in bacteria, this integrated approach lacks application to fungi. Because fungi are hyper-diverse and underexplored for new chemistry and bioactivities, we created a linked genomics-metabolomics dataset for 110 Ascomycetes, and optimized both gene cluster family (GCF) networking parameters and correlation-based scoring for pairing fungal natural products with their BGCs. Using a network of 3,007 GCFs (organized from 7,020 BGCs), we examined 25 known natural products originating from 16 known BGCs and observed statistically significant associations between 21 of these compounds and their validated BGCs. Furthermore, the scalable platform identified the BGC for the pestalamides, demystifying its biogenesis, and revealed more than 200 high-scoring natural product-GCF linkages to direct future discovery.

Chalcones from Angelica keiskei (ashitaba) inhibit key Zika virus replication proteins.

Zika virus (ZIKV) is a dangerous human pathogen and no antiviral drugs have been approved to date. The chalcones are a group of small molecules that are found in a number of different plants, including Angelica keiskei Koidzumi, also known as ashitaba. To examine chalcone anti-ZIKV activity, three chalcones, 4-hydroxyderricin (4HD), xanthoangelol (XA), and xanthoangelol-E (XA-E), were purified from a methanol-ethyl acetate extract from A. keiskei. Molecular and ensemble docking predicted that these chalcones would establish multiple interactions with residues in the catalytic and allosteric sites of ZIKV NS2B-NS3 protease, and in the allosteric site of the NS5 RNA-dependent RNA-polymerase (RdRp). Machine learning models also predicted 4HD, XA and XA-E as potential anti-ZIKV inhibitors. Enzymatic and kinetic assays confirmed chalcone inhibition of the ZIKV NS2B-NS3 protease allosteric site with IC50s from 18 to 50 µM. Activity assays also revealed that XA, but not 4HD or XA-E, inhibited the allosteric site of the RdRp, with an IC50 of 6.9 µM. Finally, we tested these chalcones for their anti-viral activity in vitro with Vero cells. 4HD and XA-E displayed anti-ZIKV activity with EC50 values of 6.6 and 22.0 µM, respectively, while XA displayed relatively weak anti-ZIKV activity with whole cells. With their simple structures and relative ease of modification, the chalcones represent attractive candidates for hit-to-lead optimization in the search of new anti-ZIKV therapeutics.

Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities.

Covering: 2010 to 2021Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.

An interpreted atlas of biosynthetic gene clusters from 1,000 fungal genomes.

Fungi are prolific producers of natural products, compounds which have had a large societal impact as pharmaceuticals, mycotoxins, and agrochemicals. Despite the availability of over 1,000 fungal genomes and several decades of compound discovery efforts from fungi, the biosynthetic gene clusters (BGCs) encoded by these genomes and the associated chemical space have yet to be analyzed systematically. Here, we provide detailed annotation and analyses of fungal biosynthetic and chemical space to enable genome mining and discovery of fungal natural products. Using 1,037 genomes from species across the fungal kingdom (e.g., Ascomycota, Basidiomycota, and non-Dikarya taxa), 36,399 predicted BGCs were organized into a network of 12,067 gene cluster families (GCFs). Anchoring these GCFs with reference BGCs enabled automated annotation of 2,026 BGCs with predicted metabolite scaffolds. We performed parallel analyses of the chemical repertoire of fungi, organizing 15,213 fungal compounds into 2,945 molecular families (MFs). The taxonomic landscape of fungal GCFs is largely species specific, though select families such as the equisetin GCF are present across vast phylogenetic distances with parallel diversifications in the GCF and MF. We compare these fungal datasets with a set of 5,453 bacterial genomes and their BGCs and 9,382 bacterial compounds, revealing dramatic differences between bacterial and fungal biosynthetic logic and chemical space. These genomics and cheminformatics analyses reveal the large extent to which fungal and bacterial sources represent distinct compound reservoirs. With a >10-fold increase in the number of interpreted strains and annotated BGCs, this work better regularizes the biosynthetic potential of fungi for rational compound discovery.

In the fungus where it happens: History and future propelling Aspergillus nidulans as the archetype of natural products research.

In 1990 the first fungal secondary metabolite biosynthetic gene was cloned in Aspergillus nidulans. Thirty years later, >30 biosynthetic gene clusters (BGCs) have been linked to specific natural products in this one fungal species. While impressive, over half of the BGCs in A. nidulans remain uncharacterized and their compounds structurally and functionally unknown. Here, we provide a comprehensive review of past advances that have enabled A. nidulans to rise to its current status as a natural product powerhouse focusing on the discovery and annotation of secondary metabolite clusters. From genome sequencing, heterologous expression, and metabolomics to CRISPR and epigenetic manipulations, we present a guided tour through the evolution of technologies developed and utilized in the last 30 years. These insights provide perspective to future efforts to fully unlock the biosynthetic potential of A. nidulans and, by extension, the potential of other filamentous fungi.

Heterologous Expression of the Unusual Terreazepine Biosynthetic Gene Cluster Reveals a Promising Approach for Identifying New Chemical Scaffolds.

Advances in genome sequencing have revitalized natural product discovery efforts, revealing the untapped biosynthetic potential of fungi. While the volume of genomic data continues to expand, discovery efforts are slowed due to the time-consuming nature of experiments required to characterize new molecules. To direct efforts toward uncharacterized biosynthetic gene clusters most likely to encode novel chemical scaffolds, we took advantage of comparative metabolomics and heterologous gene expression using fungal artificial chromosomes (FACs). By linking mass spectral profiles with structural clues provided by FAC-encoded gene clusters, we targeted a compound originating from an unusual gene cluster containing an indoleamine 2,3-dioxygenase (IDO). With this approach, we isolate and characterize R and S forms of the new molecule terreazepine, which contains a novel chemical scaffold resulting from cyclization of the IDO-supplied kynurenine. The discovery of terreazepine illustrates that FAC-based approaches targeting unusual biosynthetic machinery provide a promising avenue forward for targeted discovery of novel scaffolds and their biosynthetic enzymes, and it also represents another example of a biosynthetic gene cluster "repurposing" a primary metabolic enzyme to diversify its secondary metabolite arsenal.IMPORTANCE Here, we provide evidence that Aspergillus terreus encodes a biosynthetic gene cluster containing a repurposed indoleamine 2,3-dioxygenase (IDO) dedicated to secondary metabolite synthesis. The discovery of this neofunctionalized IDO not only enabled discovery of a new compound with an unusual chemical scaffold but also provided insight into the numerous strategies fungi employ for diversifying and protecting themselves against secondary metabolites. The observations in this study set the stage for further in-depth studies into the function of duplicated IDOs present in fungal biosynthetic gene clusters and presents a strategy for accessing the biosynthetic potential of gene clusters containing duplicated primary metabolic genes.

Chemical Evaluation of the Effects of Storage Conditions on the Botanical Goldenseal using Marker-based and Metabolomics Approaches.

Hydrastis canadensis, commonly known as goldenseal, is a botanical native to the southeastern United States that has been used for the treatment of infection. The activity of goldenseal is often attributed to the presence of alkaloids (cyclic, nitrogen-containing compounds) present within its roots. Chemical components of botanical supplements like goldenseal may face degradation if not stored properly. The purpose of the research was to analyze the stability of known and unknown metabolites of H. canadensis during exposure to different storage conditions using mass spectrometry. Three abundant metabolites of H. canadensis, berberine, canadine, and hydrastine, were chosen for targeted analysis, and the stability of unknown metabolites was evaluated using untargeted metabolomics. The analysis and evaluation of H. canadensis samples were performed utilizing LC-MS and Principal Component Analysis (PCA). The research project focused on identifying the chemical changes in the metabolite content of H. canadensis under different temperature conditions (40°C ± 5°C, 20°C ± 5°C , and 4°C ± 5°C), different light:dark (hr:hr) cycles (16:8, 12:12, and 0:24), and different sample conditions (powdered roots versus whole roots) over a six month period. The results of this 6-month study revealed that the storage conditions evaluated had no significant effects on the chemical composition of H. canadensis roots. Hence, as long as H. canadensis roots are stored within the storage conditions tested in the study, no significant changes in chemical compositions of metabolites are expected.

Targeted and untargeted analysis of secondary metabolites to monitor growth and quorum sensing inhibition for methicillin-resistant Staphylococcus aureus (MRSA).

Drug resistant infections are an increasing problem world-wide, responsible for an estimated 700,000 annual mortalities. The use of antibiotics to treat such infections has resulted in the development of resistant bacterial pathogens such as methicillin-resistant Staphylococcus aureus (MRSA). One potential alternative strategy for treating drug resistant bacterial infections is to inhibit the production of toxins, thereby making the bacteria less harmful to the host, a so called "anti-virulence" approach. In MRSA, the agr quorum sensing system is one of the major regulators of toxin production, and quorum sensing inhibitors that target this system are a promising anti-virulence strategy. With this study, we developed a method that enables the activity of quorum sensing inhibitors to be measured using ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS). This method is an improvement over existing methods because it can be employed to distinguish antimicrobial activity from quorum sensing inhibition activity based on the UPLC-MS data. This is possible by simultaneously tracking production of metabolites regulated by the agr quorum sensing system (AIP-I and formylated δ-toxin) and a metabolite that appears not to be agr regulated under the conditions of this study (aureusimine B). The newly developed method provides more nuanced indication of how metabolite production changes over time and in response to quorum sensing or growth inhibition than is possible with commonly employed spectroscopic methods.

Processing, Export, and Identification of Novel Linear Peptides from Staphylococcus aureus.

Staphylococcus aureus can colonize the human host and cause a variety of superficial and invasive infections. The success of S. aureus as a pathogen derives from its ability to modulate its virulence through the release, sensing of and response to cyclic signaling peptides. Here we provide, for the first time, evidence that S. aureus processes and secretes small linear peptides through a specialized pathway that converts a lipoprotein leader into an extracellular peptide signal. We have identified and confirmed the machinery for each step and demonstrate that the putative membrane metalloprotease Eep and the EcsAB transporter are required to complete the processing and secretion of the peptides. In addition, we have identified several linear peptides, including the interspecies signaling molecule staph-cAM373, that are dependent on this processing and secretion pathway. These findings are particularly important because multiple Gram-positive bacteria rely on small linear peptides to control bacterial gene expression and virulence.IMPORTANCE Here, we provide evidence indicating that S. aureus secretes small linear peptides into the environment via a novel processing and secretion pathway. The discovery of a specialized pathway for the production of small linear peptides and the identification of these peptides leads to several important questions regarding their role in S. aureus biology, most interestingly, their potential to act as signaling molecules. The observations in this study provide a foundation for further in-depth studies into the biological activity of small linear peptides in S. aureus.

Simplify: A Mass Spectrometry Metabolomics Approach to Identify Additives and Synergists from Complex Mixtures.

In fields ranging from environmental toxicology to drug discovery, it is critical to identify how multiple chemical compounds interact to perturb biological systems. Isolation-based approaches fail to incorporate multiconstituent interactions, such as synergy. We have developed an approach called "Simplify", which identifies mixture constituents that interact to achieve biological effects. Simplify combines biological and mass spectrometric data sets and uses an "activity index" to predict mixture interactions. Using the plant Salvia miltiorrhiza as a case study, we employed Simplify to identify four individual constituents that contribute to antimicrobial activity, three additives and one synergist. Our study is the first to enable identification of unknown synergists prior to isolating them, demonstrating the ability of the Simplify workflow to predict key contributors to the biological effect of a complex mixture. While utilized for natural products discovery in this study, this approach is expected to prove useful across multiple disciplines that rely on mixture analysis.

Synergy and antagonism in natural product extracts: when 1 + 1 does not equal 2.

Covering: 2000 to 2019 According to a 2012 survey from the Centers for Disease Control and Prevention, approximately 18% of the U.S. population uses natural products (including plant-based or botanical preparations) for treatment or prevention of disease. The use of plant-based medicines is even more prevalent in developing countries, where for many they constitute the primary health care modality. Proponents of the medicinal use of natural product mixtures often claim that they are more effective than purified compounds due to beneficial "synergistic" interactions. A less-discussed phenomenon, antagonism, in which effects of active constituents are masked by other compounds in a complex mixture, also occurs in natural product mixtures. Synergy and antagonism are notoriously difficult to study in a rigorous fashion, particularly given that natural products chemistry research methodology is typically devoted to reducing complexity and identifying single active constituents for drug development. This report represents a critical review with commentary about the current state of the scientific literature as it relates to studying combination effects (including both synergy and antagonism) in natural product extracts. We provide particular emphasis on analytical and Big Data approaches for identifying synergistic or antagonistic combinations and elucidating the mechanisms that underlie their interactions. Specific case studies of botanicals in which synergistic interactions have been documented are also discussed. The topic of synergy is important given that consumer use of botanical natural products and associated safety concerns continue to garner attention by the public and the media. Guidance by the natural products community is needed to provide strategies for effective evaluation of safety and toxicity of botanical mixtures and to drive discovery in botanical natural product research.

Mapping the Fungal Battlefield: Using in situ Chemistry and Deletion Mutants to Monitor Interspecific Chemical Interactions Between Fungi.

Fungi grow in competitive environments, and to cope, they have evolved strategies, such as the ability to produce a wide range of secondary metabolites. This begs two related questions. First, how do secondary metabolites influence fungal ecology and interspecific interactions? Second, can these interspecific interactions provide a way to "see" how fungi respond, chemically, within a competitive environment? To evaluate these, and to gain insight into the secondary metabolic arsenal fungi possess, we co-cultured Aspergillus fischeri, a genetically tractable fungus that produces a suite of mycotoxins, with Xylaria cubensis, a fungus that produces the fungistatic compound and FDA-approved drug, griseofulvin. To monitor and characterize fungal chemistry in situ, we used the droplet-liquid microjunction-surface sampling probe (droplet probe). The droplet probe makes a microextraction at defined locations on the surface of the co-culture, followed by analysis of the secondary metabolite profile via liquid chromatography-mass spectrometry. Using this, we mapped and compared the spatial profiles of secondary metabolites from both fungi in monoculture versus co-culture. X. cubensis predominantly biosynthesized griseofulvin and dechlorogriseofulvin in monoculture. In contrast, under co-culture conditions a deadlock was formed between the two fungi, and X. cubensis biosynthesized the same two secondary metabolites, along with dechloro-5'-hydroxygriseofulvin and 5'-hydroxygriseofulvin, all of which have fungistatic properties, as well as mycotoxins like cytochalasin D and cytochalasin C. In contrast, in co-culture, A. fischeri increased the production of the mycotoxins fumitremorgin B and verruculogen, but otherwise remained unchanged relative to its monoculture. To evaluate that secondary metabolites play an important role in defense and territory establishment, we co-cultured A. fischeri lacking the master regulator of secondary metabolism laeA with X. cubensis. We found that the reduced secondary metabolite biosynthesis of the ΔlaeA strain of A. fischeri eliminated the organism's ability to compete in co-culture and led to its displacement by X. cubensis. These results demonstrate the potential of in situ chemical analysis and deletion mutant approaches for shedding light on the ecological roles of secondary metabolites and how they influence fungal ecological strategies; co-culturing may also stimulate the biosynthesis of secondary metabolites that are not produced in monoculture in the laboratory.

Opportunities and Limitations for Untargeted Mass Spectrometry Metabolomics to Identify Biologically Active Constituents in Complex Natural Product Mixtures.

Compounds derived from natural sources represent the majority of small-molecule drugs utilized today. Plants, owing to their complex biosynthetic pathways, are poised to synthesize diverse secondary metabolites that selectively target biological macromolecules. Despite the vast chemical landscape of botanicals, drug discovery programs from these sources have diminished due to the costly and time-consuming nature of standard practices and high rates of compound rediscovery. Untargeted metabolomics approaches that integrate biological and chemical data sets potentially enable the prediction of active constituents early in the fractionation process. However, data acquisition and data processing parameters may have major impacts on the success of models produced. Using an inactive botanical mixture spiked with known antimicrobial compounds, untargeted mass spectrometry-based metabolomics data were combined with bioactivity data to produce selectivity ratio models subjected to a variety of data acquisition and data processing parameters. Selectivity ratio models were used to identify active constituents that were intentionally added to the mixture, along with an additional antimicrobial compound, randainal (5), which was masked by the presence of antagonists in the mixture. These studies found that data-processing approaches, particularly data transformation and model simplification tools using a variance cutoff, had significant impacts on the models produced, either masking or enhancing the ability to detect active constituents in samples. The current study highlights the importance of the data processing step for obtaining reliable information from metabolomics models and demonstrates the strengths and limitations of selectivity ratio analysis to comprehensively assess complex botanical mixtures.

Analytical methods for the study of bioactive compounds from medicinally used Echinacea species.

Echinacea purpurea (L.) Moench, Echinacea angustifolia DC. var. angustifolia and Echinacea pallida (Nutt.) Nutt. are frequently used as medicinal plants and their preparations are among the most widely used herbal medicines. The extracts from these species have shown a highly complex chemical composition, including polar compounds (caffeic acid derivatives, CADs), non-polar compounds (alkylamides and acetylenic secondary metabolites; essential oil) and high molecular weight constituents (polysaccharides and glycoproteins). All these chemical classes of compounds have demonstrated to possess interesting biological activities. In the light of all the above, this paper is focused on the analytical techniques, including sample preparation tools and chromatographic procedures, for the chemical analysis of bioactive compounds in medicinally used Echinacea species. Since sample preparation is considered to be a crucial step in the development of analytical methods for the determination of constituents present in herbal preparations, the strength and weakness of different extraction techniques are discussed. As regards the analysis of compounds present in Echinacea plant material and derivatives, the application of different techniques, mainly HPLC, HPLC-ESI-MS, HPLC-ESI-MS/MS, HPCE, HPTLC and GC, is discussed in detail. The strength, weakness and applicability of the different separation tools are stated.

Hierarchical cluster analysis of technical replicates to identify interferents in untargeted mass spectrometry metabolomics.

Mass spectral data sets often contain experimental artefacts, and data filtering prior to statistical analysis is crucial to extract reliable information. This is particularly true in untargeted metabolomics analyses, where the analyte(s) of interest are not known a priori. It is often assumed that chemical interferents (i.e. solvent contaminants such as plasticizers) are consistent across samples, and can be removed by background subtraction from blank injections. On the contrary, it is shown here that chemical contaminants may vary in abundance across each injection, potentially leading to their misidentification as relevant sample components. With this metabolomics study, we demonstrate the effectiveness of hierarchical cluster analysis (HCA) of replicate injections (technical replicates) as a methodology to identify chemical interferents and reduce their contaminating contribution to metabolomics models. Pools of metabolites with varying complexity were prepared from the botanical Angelica keiskei Koidzumi and spiked with known metabolites. Each set of pools was analyzed in triplicate and at multiple concentrations using ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS). Before filtering, HCA failed to cluster replicates in the data sets. To identify contaminant peaks, we developed a filtering process that evaluated the relative peak area variance of each variable within triplicate injections. These interferent peaks were found across all samples, but did not show consistent peak area from injection to injection, even when evaluating the same chemical sample. This filtering process identified 128 ions that appear to originate from the UPLC-MS system. Data sets collected for a high number of pools with comparatively simple chemical composition were highly influenced by these chemical interferents, as were samples that were analyzed at a low concentration. When chemical interferent masses were removed, technical replicates clustered in all data sets. This work highlights the importance of technical replication in mass spectrometry-based studies, and presents a new application of HCA as a tool for evaluating the effectiveness of data filtering prior to statistical analysis.

Integration of Biochemometrics and Molecular Networking to Identify Antimicrobials in Angelica keiskei.

Botanical medicines have been utilized for centuries, but it remains challenging to identify bioactive constituents from complex botanical extracts. Bioassay-guided fractionation is often biased toward abundant or easily isolatable compounds. To comprehensively evaluate active botanical mixtures, methods that allow for the prioritization of active compounds are needed. To this end, a method integrating bioassay-guided fractionation, biochemometric selectivity ratio analysis, and molecular networking was devised and applied to Angelica keiskei to comprehensively evaluate its antimicrobial activity against Staphylococcus aureus. This approach enabled the identification of putative active constituents early in the fractionation process and provided structural information for these compounds. A subset of chalcone analogs were prioritized for isolation, yielding 4-hydroxyderricin (1, minimal inhibitory concentration [MIC] ≤ 4.6 µM, IC50 = 2.0 µM), xanthoangelol (2, MIC ≤ 4.0 µM, IC50 = 2.3) and xanthoangelol K (4, IC50 = 168 µM). This approach allowed for the identification of a low-abundance compound (xanthoangelol K) that has not been previously reported to possess antimicrobial activity and facilitated a more comprehensive understanding of the compounds responsible for A. keiskei's antimicrobial activity.

Phytochemical Analysis and Antimicrobial Efficacy of Macleaya cordata against Extensively Drug-Resistant Staphylococcus aureus.

The antibiotic resistant threat is continuing to grow, due in part to the overuse of antibiotics in livestock feed. Many nations in Europe have banned the use of antibiotics in feed, leading to higher rates of infection in livestock animals and reduced productivity for the food market. Increasingly, researchers are looking into the efficacy of phytopreparations to replace antibiotics in feed, allowing for increased animal health without the development of resistance. Macleaya cordata, or Chinese plume poppy, shows promise as a food additive. To evaluate the antimicrobial efficacy of this plant, we tested in vitro activity of M. cordata extract, as well as pure compounds sanguinarine and chelerythrine against wild-type, methicillin-resistant, and multiply-resistant strains of Staphylococcus aureus (SA1199, AH1263, and IA116, respectively). Combination tests to evaluate synergy, additivity, and antagonism within the extract were also completed for the first time. Sanguinarine and chelerythrine showed complete growth inhibition of all strains of S. aureus at concentrations ranging from 3-10 µg/mL, and were equal in activity or were more potent than the reference compound chloramphenicol. Combination studies of pure sanguinarine and chelerythrine with M. cordata extract revealed additivity or indifference of mixture components with these compounds. Because sanguinarine and chelerythrine represent the major active constituents of M. cordata, the pooled amounts of these two compounds may be useful for establishing potency for quality control purposes. This is the first report of activity of chelerythrine and sanguinarine against methicillin-resistant S. aureus AH1263 and multiply-resistant S. aureus IA116, and illustrates the promise of M. cordata extract as an alternative to antibiotics in feed additives.

A Review of the Medicinal Uses and Pharmacology of Ashitaba.

Angelica keiskei Koidzumi, or ashitaba, is a popular botanical medicine in Japan containing diverse bioactive components including prenylated chalcones, linear and angular coumarins, and flavanones. This review provides an overview of the current knowledge of ashitaba metabolites and their biological activities to prioritize future studies. Ashitaba is purported to possess cytotoxic, antidiabetic, antioxidative, anti-inflammatory, antihypertensive, and antimicrobial properties. Although many in vitro studies have been conducted on ashitaba's chemical constituents, the in vivo efficacy and clinical relevance of this plant has yet to be confirmed for most of these activities. Here we describe the chemical composition of ashitaba and present the pharmacological effects of this botanical as supported by the current literature. The experimental results demonstrate promise for the medical use of ashitaba, but considerable work needs to be done to understand the mechanisms of action of its metabolites. Additionally, in vivo and clinical trials as well as additional studies on less abundant bioactive compounds are warranted.