Mycobacterium tuberculosis Inhibitors Based on Arylated Quinoline Carboxylic Acid Backbones with Anti-Mtb Gyrase Activity.

New antitubercular agents with either a novel mode of action or novel mode of inhibition are urgently needed to overcome the threat of drug-resistant tuberculosis (TB). The present study profiles new arylated quinoline carboxylic acids (QCAs) having activity against replicating and non-replicating Mycobacterium tuberculosis (Mtb), the causative agent of TB. Thus, the synthesis, characterization, and in vitro screening (MABA and LORA) of 48 QCAs modified with alkyl, aryl, alkoxy, halogens, and nitro groups in the quinoline ring led to the discovery of two QCA derivatives, 7i and 7m, adorned with C-2 2-(naphthalen-2-yl)/C-6 1-butyl and C-2 22-(phenanthren-3-yl)/C-6 isopropyl, respectively, as the best Mtb inhibitors. DNA gyrase inhibition was shown to be exhibited by both, with QCA 7m illustrating better activity up to a 1 µM test concentration. Finally, a docking model for both compounds with Mtb DNA gyrase was developed, and it showed a good correlation with in vitro results.

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.

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.

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.

Mycobacterium tuberculosis and cholinesterase inhibitors from Voacanga globosa.

Globospiramine (1), a new spirobisindole alkaloid possessing an Aspidosperma-Aspidosperma skeleton, together with deoxyvobtusine (2), deoxyvobtusine lactone (3), vobtusine lactone (4) and lupeol (5), were isolated and identified from Voacanga globosa through a bioassay-guided purification. The gross structure and absolute stereochemistry of 1 were established by circular dichroism spectroscopy, HR-MS and unambiguous NMR spectroscopic experiments. In addition, a new biogenetic pathway for the formation of the spiro-Aspidosperma-Aspidosperma skeleton is proposed. Alkaloid 1 showed potent antituberculosis activity against Mycobacterium tuberculosis H(37)Rv as evidenced in microplate Alamar blue assay (MIC = 4 µg/mL) and low-oxygen recovery assay (LORA (MIC = 5.2 µg/mL). The bisindole alkaloids also exhibited promising activity against acetylcholinesterase and, especially butyrylcholinesterase, with deoxyvobtusine (2) (IC(50) = 6.2 µM) as the most strongly inhibiting compound. This study extends the variety of alkaloid structural platforms which exhibit antimycobacterial and anticholinesterase activity.