Implications of confounding from unmodeled interactions between explanatory variables when using latent variable regression models to make inferences.

With linear dependency between the explanatory variables, partial least squares (PLS) regression is commonly used for regression analysis. If the response variable correlates to a high degree with the explanatory variables, a model with excellent predictive ability can usually be obtained. Ranking of variable importance is commonly used to interpret the model and sometimes this interpretation guides further experimentation. For instance, when analyzing natural product extracts for bioactivity, an underlying assumption is that the highest ranked compounds represent the best candidates for isolation and further testing. A problem with this approach is that in most cases the number of compounds is larger than the number of samples (and usually much larger) and that the concentrations of the compounds correlate. Furthermore, compounds may interact as synergists or as antagonists. If the modelling process does not account for this possibility, the interpretation can be thoroughly wrong since unmodelled variables that strongly influence the response will give rise to confounding of a first order PLS model and send the experimenter on a wrong track. We show the consequences of this by a practical example from natural product research. Furthermore, we show that by including the possibility of interactions between explanatory variables, visualization using a selectivity ratio plot may provide model interpretation that can be used to make inferences.

Co-consuming green tea with raloxifene decreases raloxifene systemic exposure in healthy adult participants.

Green tea is a popular beverage worldwide. The abundant green tea catechin (-)-epigallocatechin gallate (EGCG) is a potent in vitro inhibitor of intestinal UDP-glucuronosyltransferase (UGT) activity (Ki ~2 µM). Co-consuming green tea with intestinal UGT drug substrates, including raloxifene, could increase systemic drug exposure. The effects of a well-characterized green tea on the pharmacokinetics of raloxifene, raloxifene 4'-glucuronide, and raloxifene 6-glucuronide were evaluated in 16 healthy adults via a three-arm crossover, fixed-sequence study. Raloxifene (60 mg) was administered orally with water (baseline), with green tea for 1 day (acute), and on the fifth day after daily green tea administration for 4 days (chronic). Unexpectedly, green tea decreased the geometric mean green tea/baseline raloxifene AUC0-96h ratio to ~0.60 after both acute and chronic administration, which is below the predefined no-effect range (0.75-1.33). Lack of change in terminal half-life and glucuronide-to-raloxifene ratios indicated the predominant mechanism was not inhibition of intestinal UGT. One potential mechanism includes inhibition of intestinal transport. Using established transfected cell systems, a green tea extract normalized to EGCG inhibited 10 of 16 transporters tested (IC50 , 0.37-12 µM). Another potential mechanism, interruption by green tea of gut microbe-mediated raloxifene reabsorption, prompted a follow-up exploratory clinical study to evaluate the potential for a green tea-gut microbiota-drug interaction. No clear mechanisms were identified. Overall, results highlight that improvements in current models and methods used to predict UGT-mediated drug interactions are needed. Informing patients about the risk of co-consuming green tea with raloxifene may be considered.

Goldenseal-Mediated Inhibition of Intestinal Uptake Transporters Decreases Metformin Systemic Exposure in Mice.

Goldenseal is a perennial plant native to eastern North America. A recent clinical study reported goldenseal decreased metformin Cmax and area under the blood concentration versus time curve (AUC) by 27% and 23%, respectively, but half-life and renal clearance were unchanged. These observations suggested goldenseal altered processes involved in metformin absorption. The underlying mechanism(s) remain(s) unknown. One mechanism for the decreased metformin systemic exposure is inhibition by goldenseal of intestinal uptake transporters involved in metformin absorption. Goldenseal extract and three goldenseal alkaloids (berberine, (-)-ß-hydrastine, hydrastinine) were tested as inhibitors of organic cation transporter (OCT) 3, plasma membrane monoamine transporter (PMAT), and thiamine transporter (THTR) 2 using human embryonic kidney 293 cells overexpressing each transporter. The goldenseal extract, normalized to berberine content, was the strongest inhibitor of each transporter (IC50: 4.9, 13.1, and 5.8 µM for OCT3, PMAT, and THTR2, respectively). A pharmacokinetic study in mice compared the effects of berberine, (-)-ß-hydrastine, goldenseal extract, and imatinib (OCT inhibitor) on orally administered metformin. Goldenseal extract and imatinib significantly decreased metformin Cmax by 31% and 25%, respectively, and had no effect on half-life. Berberine and (-)-ß-hydrastine had no effect on metformin pharmacokinetics, indicating neither alkaloid alone precipitated the interaction in vivo. A follow-up murine study involving intravenous metformin and oral inhibitors examined the contributions of basolateral enteric/hepatic uptake transporters to the goldenseal-metformin interaction. Goldenseal extract and imatinib had no effect on metformin AUC and half-life, suggesting lack of inhibition of basolateral enteric/hepatic uptake transporters. Results may have implications for patients taking goldenseal with drugs that are substrates for OCT3 and THTR2. SIGNIFICANCE STATEMENT: Goldenseal is used to self-treat respiratory infections and digestive disorders. We investigated potential mechanisms for the clinical pharmacokinetic interaction observed between goldenseal and metformin, specifically inhibition by goldenseal of intestinal uptake transporters (OCT3, PMAT, THTR2) involved in metformin absorption. Goldenseal extract inhibited all three transporters in vitro and decreased metformin systemic exposure in mice. These data may have broader implications for patients co-consuming goldenseal with other drugs that are substrates for these transporters.

Staphylococcus epidermidis activates keratinocyte cytokine expression and promotes skin inflammation through the production of phenol-soluble modulins.

Staphylococcus epidermidis is a common microbe on human skin and has beneficial functions in the skin microbiome. However, under conditions of allergic inflammation, the abundance of S. epidermidis increases, establishing potential danger to the epidermis. To understand how this commensal may injure the host, we investigate phenol-soluble modulin (PSM) peptides produced by S. epidermidis that are similar to peptides produced by Staphylococcus aureus. Synthetic S. epidermidis PSMs induce expression of host defense genes and are cytotoxic to human keratinocytes. Deletion mutants of S. epidermidis lacking these gene products support these observations and further show that PSMs require the action of the EcpA bacterial protease to induce inflammation when applied on mouse skin with an intact stratum corneum. The expression of PSMδ from S. epidermidis is also found to correlate with disease severity in patients with atopic dermatitis. These observations show how S. epidermidis PSMs can promote skin inflammation.

From plant to cancer drug: lessons learned from the discovery of taxol.

Many researchers in the natural product sciences dream of discovering a successful drug. For almost all of us, this dream will never be realized. Among the heroes of our past, though, there is a team whose efforts led to the discovery of not one but two new drugs. Dr Monroe Wall and Dr Mansukh Wani isolated and solved the structures for taxol and camptothecin, plant-based compounds that continue to play a critical role in cancer therapy today. Since the 1960s and 1970s when Wall, Wani and collaborators did their seminal work, there have been tremendous technological advances in the natural product sciences. With access to most sophisticated technology, it might be expected that the rate of discovery of new drugs from plants and other sources would have sped up. However, this has not come to pass. Why is this? Is it that the promise of new drug candidates from plant-based sources has been exhausted? Has our fascination with new technologies and with the promise of the genomics revolution caused us to stop investing effort and resources in the practices that are proven to yield success? With this Viewpoint, we share the story of taxol's discovery, highlighting critical challenges that were overcome and considering their relevance to botanical natural products drug discovery today. We hope that consideration of lessons learned from the past will help fuel success by researchers currently studying plants with the goal of discovering promising therapeutic leads.

Translating Kratom-Drug Interactions: From Bedside to Bench and Back.

Kratom is a botanical natural product belonging to the coffee family, with stimulant effects at low doses and opioid-like effects at higher doses. During the last two decades, kratom has been purported as a safer alternative to pharmaceutical and illicit drugs to self-manage pain and opioid withdrawal symptoms. Kratom alkaloids, typically mitragynine, have been detected in biologic samples from overdose deaths. These deaths are often observed in combination with other drugs and are suspected to result from polyintoxications. This review focuses on the potential for kratom to precipitate pharmacokinetic interactions with object drugs involved in these reported polyintoxications. The legal status, chemistry, pharmacology, and toxicology are also summarized. The aggregate in vitro and clinical data identified kratom and select kratom alkaloids as modulators of cytochrome P450 (P450) enzyme activity, notably as inhibitors of CYP2D6 and CYP3A, as well as P-glycoprotein-mediated efflux activity. These inhibitory effects could increase the systemic exposure to co-consumed object drugs, which may lead to adverse effects. Collectively, the evidence to date warrants further evaluation of potential kratom-drug interactions using an iterative approach involving additional mechanistic in vitro studies, well designed clinical studies, and physiologically based pharmacokinetic modeling and simulation. This critical information is needed to fill knowledge gaps regarding the safe and effective use of kratom, thereby addressing ongoing public health concerns. SIGNIFICANCE STATEMENT: The botanical kratom is increasingly used to self-manage pain and opioid withdrawal symptoms due to having opioid-like effects. The legal status, chemistry, pharmacology, toxicology, and drug interaction potential of kratom are reviewed. Kratom-associated polyintoxications and in vitro-in vivo extrapolations suggest that kratom can precipitate pharmacokinetic drug interactions by inhibiting CYP2D6, CYP3A, and P-glycoprotein. An iterative approach that includes clinical studies and physiologically based pharmacokinetic modeling and simulation is recommended for further evaluation of potential unwanted kratom-drug interactions.

What was old is new again: Phenotypic screening of a unique fungal library yields pyridoxatin, a promising lead against extensively resistant Acinetobacter baumannii (AB5075).

Due to the emergence of resistance, the World Health Organization considers Gram-negative pathogen Acinetobacter baumannii a top priority for therapeutic development. Using this priority pathogen and a phenotypic, agar plate-based assay, a unique library of extracts from 2,500 diverse fungi was screened for antimicrobial activity against a highly virulent, drug-resistant strain of A. baumannii (AB5075). The most potent hit from this screen was an extract from the fungus Tolypocladium sp., which was found to produce pyridoxatin. Another active extract from the fungi Trichoderma deliquescens was characterized and yielded trichokonin VII and trichokonin VIII. Evaluation of pyridoxatin against A. baumannii (AB5075) in a broth microdilution assay revealed a minimum inhibitory concentration (MIC) of 38 µM, compared to the known antibiotic levofloxacin with MIC of 28 µM. Mass spectrometry, Marfey's analysis and nuclear magnetic resonance spectroscopy analyses confirmed the structures of trichokonins VII and VIII to be consistent with previous reports. In an in vivo Galleria mellonella model, pyridoxatin tested at 150 mg/kg exhibited minimal toxicity (90% survival) and promising antimicrobial efficacy (50% survival) after 5 days. Trichokonins VII and VIII tested at 150 mg/kg were toxic to G. mellonella, with 20% survival and 40% survival after 5 days, respectively. The findings of this project suggest that pyridoxatin may serve as a lead compound for the development of antimicrobials against A. baumannii. They also demonstrate the value of the phenotypic screening approach employed herein.

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.

Modulation of in Vitro SARS-CoV-2 Infection by Stephania tetrandra and Its Alkaloid Constituents.

Botanical natural products have been widely consumed for their purported usefulness against COVID-19. Here, six botanical species from multiple sources and 173 isolated natural product compounds were screened for blockade of wild-type (WT) SARS-CoV-2 infection in human 293T epithelial cells overexpressing ACE-2 and TMPRSS2 protease (293TAT). Antiviral activity was demonstrated by an extract from Stephania tetrandra. Extract fractionation, liquid chromatography-mass spectrometry (LC-MS), antiviral assays, and computational analyses revealed that the alkaloid fraction and purified alkaloids tetrandrine, fangchinoline, and cepharanthine inhibited WT SARS-CoV-2 infection. The alkaloids and alkaloid fraction also inhibited the delta variant of concern but not WT SARS-CoV-2 in VeroAT cells. Membrane permeability assays demonstrate that the alkaloids are biologically available, although fangchinoline showed lower permeability than tetrandrine. At high concentrations, the extract, alkaloid fractions, and pure alkaloids induced phospholipidosis in 293TAT cells and less so in VeroAT cells. Gene expression profiling during virus infection suggested that alkaloid fraction and tetrandrine displayed similar effects on cellular gene expression and pathways, while fangchinoline showed distinct effects on cells. Our study demonstrates a multifaceted approach to systematically investigate the diverse activities conferred by complex botanical mixtures, their cell-context specificity, and their pleiotropic effects on biological systems.

Clinical Assessment of the Drug Interaction Potential of the Psychotropic Natural Product Kratom.

Oral formulations prepared from the leaves of the kratom (Mitragyna speciosa) plant are increasingly used for their opioid-like effects to self-manage opioid withdrawal and pain. Calls to US poison centers involving kratom exposures increased >50-fold from 2011-2017, one-third of which reported concomitant use of kratom with drugs of abuse. Many of these drugs are eliminated primarily via cytochrome P450 (CYP) 3A and CYP2D6, raising concerns for potential adverse pharmacokinetic kratom-drug interactions. The impact of a single low dose of kratom tea (2 g) on the pharmacokinetics of the CYP3A probe midazolam (2.5 mg) and CYP2D6 probe dextromethorphan (30 mg) were assessed in 12 healthy adult participants after oral administration. Kratom showed no effect on dextromethorphan area under the plasma concentration time-curve (AUC) and maximum concentration (Cmax ; geometric mean ratio (90% confidence interval) 0.99 (0.83-1.19) and 0.96 (0.78-1.19), respectively) but a modest increase in midazolam AUC and Cmax (1.39 (1.23-1.57) and 1.50 (1.32-1.70), respectively). Lack of change in midazolam half-life (1.07 (0.98-1.17)) suggested that kratom primarily inhibited intestinal CYP3A. This inference was further supported by a physiologically based pharmacokinetic drug interaction model using the abundant alkaloid mitragynine, a relatively potent CYP3A time-dependent inhibitor in vitro (KI , ~4 µM; kinact , ~0.07 min-1 ). This work is the first to clinically evaluate the pharmacokinetic drug interaction potential of kratom. Co-consuming kratom with certain drugs extensively metabolized by CYP3A may precipitate serious interactions. These data fill critical knowledge gaps about the safe use of this increasingly popular natural product, thereby addressing ongoing public health concerns.

How Low Can You Go? Selecting Intensity Thresholds for Untargeted Metabolomics Data Preprocessing.

Untargeted mass spectrometry (MS) metabolomics is an increasingly popular approach for characterizing complex mixtures. Recent studies have highlighted the impact of data preprocessing for determining the quality of metabolomics data analysis. The first step in data processing with untargeted metabolomics requires that signal thresholds be selected for which features (detected ions) are included in the dataset. Analysts face the challenge of knowing where to set these thresholds; setting them too high could mean missing relevant features, but setting them too low could result in a complex and unwieldy dataset. This study compared data interpretation for an example metabolomics dataset when intensity thresholds were set at a range of feature heights. The main observations were that low signal thresholds (1) improved the limit of detection, (2) increased the number of features detected with an associated isotope pattern and/or an MS-MS fragmentation spectrum, and (3) increased the number of in-source clusters and fragments detected for known analytes of interest. When the settings of parameters differing in intensities were applied on a set of 39 samples to discriminate the samples through principal component analyses (PCA), similar results were obtained with both low- and high-intensity thresholds. We conclude that the most information-rich datasets can be obtained by setting low-intensity thresholds. However, in the cases where only a qualitative comparison of samples with PCA is to be performed, it may be sufficient to set high thresholds and thereby reduce the complexity of the data processing and amount of computational time required.

The Ubiquitous Human Skin Commensal Staphylococcus hominis Protects against Opportunistic Pathogens.

Staphylococcus hominis is frequently isolated from human skin, and we hypothesize that it may protect the cutaneous barrier from opportunistic pathogens. We determined that S. hominis makes six unique autoinducing peptide (AIP) signals that inhibit the major virulence factor accessory gene regulator (agr) quorum sensing system of Staphylococcus aureus. We solved and confirmed the structures of three novel AIP signals in conditioned medium by mass spectrometry and then validated synthetic AIP activity against all S. aureus agr classes. Synthetic AIPs also inhibited the conserved agr system in a related species, Staphylococcus epidermidis. We determined the distribution of S. hominis agr types on healthy human skin and found S. hominis agr-I and agr-II were highly represented across subjects. Further, synthetic AIP-II was protective in vivo against S. aureus-associated dermonecrotic or epicutaneous injury. Together, these findings demonstrate that a ubiquitous colonizer of human skin has a fundamentally protective role against opportunistic damage. IMPORTANCE Human skin is home to a variety of commensal bacteria, including many species of coagulase-negative staphylococci (CoNS). While it is well established that the microbiota as a whole maintains skin homeostasis and excludes pathogens (i.e., colonization resistance), relatively little is known about the unique contributions of individual CoNS species to these interactions. Staphylococcus hominis is the second most frequently isolated CoNS from healthy skin, and there is emerging evidence to suggest that it may play an important role in excluding pathogens, including Staphylococcus aureus, from colonizing or infecting the skin. Here, we identified that S. hominis makes 6 unique peptide inhibitors of the S. aureus global virulence factor regulation system (agr). Additionally, we found that one of these peptides can prevent topical or necrotic S. aureus skin injury in a mouse model. Our results demonstrate a specific and broadly protective role for this ubiquitous, yet underappreciated skin commensal.

Polychlorinated cyclopentenes from a marine derived Periconia sp. (strain G1144).

Studies on an organic extract of a marine fungus, Periconia sp. (strain G1144), led to the isolation of three halogenated cyclopentenes along with the known and recently reported rhytidhyester D; a series of spectrometric and spectroscopic techniques were used to elucidate these structures. Interestingly, two of these compounds represent tri-halogenated cyclopentene derivatives, which have been observed only rarely from Nature. The relative and absolute configurations of the compounds were established via mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, Mosher's esters method, optical rotation and GIAO NMR calculations, including correlation coefficient calculations and the use of both DP4+ and dJ DP4 analyses. Several of the isolated compounds were tested for activity in anti-parasitic, antimicrobial, quorum sensing inhibition, and cytotoxicity assays and were shown to be inactive.

Kratom (Mitragyna speciosa) Validation: Quantitative Analysis of Indole and Oxindole Alkaloids Reveals Chemotypes of Plants and Products.

Many consumers are turning to kratom (Mitragyna speciosa) to self-manage pain and opioid addiction. In the United States, an array of capsules, powders, and loose-leaf kratom products are readily available. Additionally, several online sites supply live kratom plants. A prerequisite to establishing quality control and quality assurance standards for the kratom industry, or understanding how alkaloid levels effect clinical outcomes, is the identification and quantitation of major and minor alkaloid constituents within available products and preparations. To this end, an ultra-high performance liquid chromatography-high resolution mass spectrometry method was developed for the analysis of 8 indole alkaloids (7-hydroxymitragynine, ajmalicine, paynantheine, mitragynine, speciogynine, isopaynantheine, speciociliatine, and mitraciliatine) and 6 oxindole alkaloids (isomitraphylline, isospeciofoleine, speciofoline, corynoxine A, corynoxeine, and rhynchophylline) in US-grown kratom plants and commercial products. These commercial products shared a qualitatively similar alkaloid profile, with 12 - 13 detected alkaloids and high levels of the indole alkaloid mitragynine (13.9 ± 1.1 - 270 ± 24 mg/g). The levels of the other major alkaloids (paynantheine, speciociliatine, speciogynine, mitraciliatine, and isopaynantheine) and the minor alkaloids varied in concentration from product to product. The alkaloid profile of US-grown M. speciosa "Rifat" showed high levels of the indole alkaloid speciogynine (7.94 ± 0.83 - 11.55 ± 0.18 mg/g) and quantifiable levels of isomitraphylline (0.943 ± 0.033 - 1.47 ± 0.18 mg/g). Notably, the alkaloid profile of a US-grown M. speciosa seedling was comparable to the commercial products with a high level of mitragynine (15.01 ± 0.20 mg/g). This work suggests that there are several M. speciosa chemotypes.

Clinical Pharmacokinetic Assessment of Kratom (Mitragyna speciosa), a Botanical Product with Opioid-like Effects, in Healthy Adult Participants.

Increasing use of the botanical kratom to self-manage opioid withdrawal and pain has led to increased kratom-linked overdose deaths. Despite these serious safety concerns, rigorous fundamental pharmacokinetic knowledge of kratom in humans remains lacking. We assessed the pharmacokinetics of a single low dose (2 g) of a well-characterized kratom product administered orally to six healthy participants. Median concentration-time profiles for the kratom alkaloids examined were best described by a two-compartment model with central elimination. Pronounced pharmacokinetic differences between alkaloids with the 3S configuration (mitragynine, speciogynine, paynantheine) and alkaloids with the 3R configuration (mitraciliatine, speciociliatine, isopaynantheine) were attributed to differences in apparent intercompartmental distribution clearance, volumes of distribution, and clearance. Based on noncompartmental analysis of individual concentration-time profiles, the 3S alkaloids exhibited a shorter median time to maximum concentration (1-2 vs. 2.5-4.5 h), lower area under the plasma concentration-time curve (430-490 vs. 794-5120 nM × h), longer terminal half-life (24-45 vs. ~12-18 h), and higher apparent volume of distribution during the terminal phase (960-12,700 vs. ~46-130 L) compared to the 3R alkaloids. Follow-up mechanistic in vitro studies suggested differential hepatic/intestinal metabolism, plasma protein binding, blood-to-plasma partitioning, and/or distribution coefficients may explain the pharmacokinetic differences between the two alkaloid types. This first comprehensive pharmacokinetic characterization of kratom alkaloids in humans provides the foundation for further research to establish safety and effectiveness of this emerging botanical product.

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.

More Than Just a Weed: An Exploration of the Antimicrobial Activity of Rumex crispus using a Multivariate Data Analysis Approach.

Plants have a long history of use for their medicinal properties. The complexity of botanical extracts presents unique challenges and necessitates the application of innovative approaches to correctly identify and quantify bioactive compounds. For this study, we used untargeted metabolomics to explore the antimicrobial activity of Rumex crispus (yellow dock), a member of the Polygonaceae family used as an herbal remedy for bacterial infections. Ultra-performance liquid chromatography coupled with high resolution mass-spectrometry (UPLC-MS) was used to identify and quantify the known antimicrobial compound emodin. In addition, we used biochemometric approaches to integrate data measuring antimicrobial activity from R. crispus root starting material and fractions against methicillin-resistant Staphylococcus aureus (MRSA) with UPLC-MS data. Our results support the hypothesis that multiple constituents, including the anthraquinone emodin, contribute to the antimicrobial activity of R. crispus against MRSA.

Benefiting from big data in natural products: importance of preserving foundational skills and prioritizing data quality.

Systematic, large-scale, studies at the genomic, metabolomic, and functional level have transformed the natural product sciences. Improvements in technology and reduction in cost for obtaining spectroscopic, chromatographic, and genomic data coupled with the creation of readily accessible curated and functionally annotated data sets have altered the practices of virtually all natural product research laboratories. Gone are the days when the natural products researchers were expected to devote themselves exclusively to the isolation, purification, and structure elucidation of small molecules. We now also engage with big data in taxonomic, genomic, proteomic, and/or metabolomic collections, and use these data to generate and test hypotheses. While the oft stated aim for the use of large-scale -omics data in the natural products sciences is to achieve a rapid increase in the rate of discovery of new drugs, this has not yet come to pass. At the same time, new technologies have provided unexpected opportunities for natural products chemists to ask and answer new and different questions. With this viewpoint, we discuss the evolution of big data as a part of natural products research and provide a few examples of how discoveries have been enabled by access to big data. We also draw attention to some of the limitations in our existing engagement with large datasets and consider what would be necessary to overcome them.

Interlaboratory Comparison of Untargeted Mass Spectrometry Data Uncovers Underlying Causes for Variability.

Despite the value of mass spectrometry in modern natural products discovery workflows, it remains very difficult to compare data sets between laboratories. In this study we compared mass spectrometry data for the same sample set from two different laboratories (quadrupole time-of-flight and quadrupole-Orbitrap) and evaluated the similarity between these two data sets in terms of both mass spectrometry features and their ability to describe the chemical composition of the sample set. Somewhat surprisingly, the two data sets, collected with appropriate controls and replication, had very low feature overlap (25.7% of Laboratory A features overlapping 21.8% of Laboratory B features). Our data clearly demonstrate that differences in fragmentation, charge state, and adduct formation in the ionization source are a major underlying cause for these differences. Consistent with other recent literature, these findings challenge the conventional wisdom that electrospray ionization mass spectrometry (ESI-MS) yields a simple one-to-one correspondence between analytes in solution and features in the data set. Importantly, despite low overlap in feature lists, principal component analysis (PCA) generated qualitatively similar PCA plots. Overall, our findings demonstrate that comparing untargeted metabolomics data between laboratories is challenging, but that data sets with low feature overlap can yield the same qualitative description of a sample set using PCA.