Unusual Sesquiterpenes from Streptomyces olindensis DAUFPE 5622.

In nature, the vast majority of sesquiterpenes are produced by type I mechanisms, and glycosylated sesquiterpenes are rare in actinobacteria. Streptomyces olindensis DAUFPE 5622 produces the sesquiterpenes olindenones A-G, a new class of rearranged drimane sesquiterpenes. Olindenones B-D are oxygenated derivatives of olindenone A, while olindenones E-G are analogs glycosylated with dideoxysugars. 13C-isotope labeling studies demonstrated olindenone A biosynthesis occurs via the methylerythritol phosphate (MEP) pathway and suggested the rearrangement is only partially concerted. Based on the structures, one potential mechanism of olindenone A formation proceeds by cyclization of the linear terpenoid precursor, likely occurring via a terpene cyclase-mediated type II mechanism whereby the terminal alkene of the precursor is protonated, triggering carbocation-driven cyclization followed by rearrangement. Diphosphate hydrolysis may occur either before or after cyclization. Although a biosynthetic route is proposed, the terpene cyclase gene responsible for producing olindenones currently remains unidentified.

High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract.

INTRODUCTION: Many secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost. OBJECTIVES: The aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time. MATERIAL AND METHODS: In this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions. RESULTS: The proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes. CONCLUSION: The proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Data Base similarity (DBsimilarity) of natural products to aid compound identification on MS and NMR pipelines, similarity networking, and more.

INTRODUCTION: We developed Data Base similarity (DBsimilarity), a user-friendly tool designed to organize structure databases into similarity networks, with the goal of facilitating the visualization of information primarily for natural product chemists who may not have coding experience. METHOD: DBsimilarity, written in Jupyter Notebooks, converts Structure Data File (SDF) files into Comma-Separated Values (CSV) files, adds chemoinformatics data, constructs an MZMine custom database file and an NMRfilter candidate list of compounds for rapid dereplication of MS and 2D NMR data, calculates similarities between compounds, and constructs CSV files formatted into similarity networks for Cytoscape. RESULTS: The Lotus database was used as a source for Ginkgo biloba compounds, and DBsimilarity was used to create similarity networks including NPClassifier classification to indicate biosynthesis pathways. Subsequently, a database of validated antibiotics from natural products was combined with the G. biloba compounds to identify promising compounds. The presence of 11 compounds in both datasets points to possible antibiotic properties of G. biloba, and 122 compounds similar to these known antibiotics were highlighted. Next, DBsimilarity was used to filter the NPAtlas database (selecting only those with MIBiG reference) to identify potential antibacterial compounds using the ChEMBL database as a reference. It was possible to promptly identify five compounds found in both databases and 167 others worthy of further investigation. CONCLUSION: Chemical and biological properties are determined by molecular structures. DBsimilarity enables the creation of interactive similarity networks using Cytoscape. It is also in line with a recent review that highlights poor biological plausibility and unrealistic chromatographic behaviors as significant sources of errors in compound identification.

Forty years of the adrenal chromaffin cell through ISCCB meetings around the world.

This historical review focuses on the evolution of the knowledge accumulated during the last two centuries on the biology of the adrenal medulla gland and its chromaffin cells (CCs). The review emerged in the context of a series of meetings that started on the Spanish island of Ibiza in 1982 with the name of the International Symposium on Chromaffin Cell Biology (ISCCB). Hence, the review is divided into two periods namely, before 1982 and from this year to 2022, when the 21st ISCCB meeting was just held in Hamburg, Germany. The first historical period extends back to 1852 when Albert Kölliker first described the fine structure and function of the adrenal medulla. Subsequently, the adrenal staining with chromate salts identified the CCs; this was followed by the establishment of the embryological origin of the adrenal medulla, and the identification of adrenaline-storing vesicles. By the end of the nineteenth century, the basic morphology, histochemistry, and embryology of the adrenal gland were known. The twentieth century began with breakthrough findings namely, the experiment of Elliott suggesting that adrenaline was the sympathetic neurotransmitter, the isolation of pure adrenaline, and the deciphering of its molecular structure and chemical synthesis in the laboratory. In the 1950s, Blaschko isolated the catecholamine-storing vesicles from adrenal medullary extracts. This switched the interest in CCs as models of sympathetic neurons with an explosion of studies concerning their functions, i.e., uptake of catecholamines by chromaffin vesicles through a specific coupled transport system; the identification of several vesicle components in addition to catecholamines including chromogranins, ATP, opioids, and other neuropeptides; the calcium-dependence of the release of catecholamines; the underlying mechanism of exocytosis of this release, as indicated by the co-release of proteins; the cross-talk between the adrenal cortex and the medulla; and the emission of neurite-like processes by CCs in culture, among other numerous findings. The 1980s began with the introduction of new high-resolution techniques such as patch-clamp, calcium probes, marine toxins-targeting ion channels and receptors, confocal microscopy, or amperometry. In this frame of technological advances at the Ibiza ISCCB meeting in 1982, 11 senior researchers in the field predicted a notable increase in our knowledge in the field of CCs and the adrenal medulla; this cumulative knowledge that occurred in the last 40 years of history of the CC is succinctly described in the second part of this historical review. It deals with cell excitability, ion channel currents, the exocytotic fusion pore, the handling of calcium ions by CCs, the kinetics of exocytosis and endocytosis, the exocytotic machinery, and the life cycle of secretory vesicles. These concepts together with studies on the dynamics of membrane fusion with super-resolution imaging techniques at the single-protein level were extensively reviewed by top scientists in the field at the 21st ISCCB meeting in Hamburg in the summer of 2022; this frontier topic is also briefly reviewed here. Many of the concepts arising from those studies contributed to our present understanding of synaptic transmission. This has been studied in physiological or pathophysiological conditions, in CCs from animal disease models. In conclusion, the lessons we have learned from CC biology as a peripheral model for brain and brain disease pertain more than ever to cutting-edge research in neurobiology. In the 22nd ISCCB meeting in Israel in 2024 that Uri Asheri is organizing, we will have the opportunity of seeing the progress of the questions posed in Ibiza, and on other questions that undoubtedly will arise.

A Secretory Vesicle Failure in Parkinson's Disease Occurs in Human Platelets.

OBJECTIVE: The presence of elevated dopamine (DA) and its major metabolites in the cytosol of neurons has been associated with their vulnerability in Parkinson's disease (PD). Over 99% of the cell's amines are confined to secretory vesicles (SVs), making these structures fundamental in the regulation of cytosolic DA levels. SVs of platelets use similar, if not the same mechanisms to accumulate serotonin in SVs as dopaminergic neurons do to store DA. Hence, any functional defects in platelets probably mirrors events in DA neurons. METHODS: We have isolated fresh platelets from the blood of 75 PD patients, 116 matched controls and 24 patients with Parkinsonism, assaying serotonin handling (basal content, accumulation, secretion and spontaneous leakage). RESULTS: We found a dramatic decrease in the serotonin content and uptake by SVs, as well as decreased thrombin-induced release by platelets from PD patients but not in those from most Parkinsonism cases. Platelets from PD patients also failed to retain serotonin in SVs. INTERPRETATION: These findings indicate a functional impairment in the handling of amines by SVs in PD patients. This defect may serve as a biomarker of PD, and the approach described here may be potentially used for the subclinical detection of PD and to establish a platform to assay disease modifying drugs. ANN NEUROL 2022.

Quantum Chemistry Calculations for Metabolomics.

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Advances in Microbial NMR Metabolomics.

Confidently, nuclear magnetic resonance (NMR) is the most informative technique in analytical chemistry and its use as an analytical platform in metabolomics is well proven. This chapter aims to present NMR as a viable tool for microbial metabolomics discussing its fundamental aspects and applications in metabolomics using some chosen examples.

NMR as a tool for compound identification in mixtures.

INTRODUCTION: Natural products and metabolomics are intrinsically linked through efforts to analyze complex mixtures for compound annotation. Although most studies that aim for compound identification in mixtures use MS as the main analysis technique, NMR has complementary advances that are worth exploring for enhanced structural confidence. OBJECTIVE: This review aimed to showcase a portfolio of the main tools available for compound identification using NMR. MATERIALS AND METHODS: COLMAR, SMART-NMR, MADByTE, and NMRfilter are presented using examples collected from real samples from the perspective of a natural product chemist. Data are also made available through Zenodo so that readers can test each case presented here. CONCLUSION: The acquisition of 1 H NMR, HSQC, TOCSY, HSQC-TOCSY, and HMBC data for all samples and fractions from a natural products study is strongly suggested. The same is valid for MS analysis to create a bridged analysis between both techniques in a complementary manner. The use of NOAH supersequences has also been suggested and demonstrated to save NMR time.

Data Fusion-based Discovery (DAFdiscovery) pipeline to aid compound annotation and bioactive compound discovery across diverse spectral data.

INTRODUCTION: Data Fusion-based Discovery (DAFdiscovery) is a pipeline designed to help users combine mass spectrometry (MS), nuclear magnetic resonance (NMR), and bioactivity data in a notebook-based application to accelerate annotation and discovery of bioactive compounds. It applies Statistical Total Correlation Spectroscopy (STOCSY) and Statistical HeteroSpectroscopy (SHY) calculation in their data using an easy-to-follow Jupyter Notebook. METHOD: Different case studies are presented for benchmarking, and the resultant outputs are shown to aid natural products identification and discovery. The goal is to encourage users to acquire MS and NMR data from their samples (in replicated samples and fractions when available) and to explore their variance to highlight MS features, NMR peaks, and bioactivity that might be correlated to accelerated bioactive compound discovery or for annotation-identification studies. RESULTS: Different applications were demonstrated using data from different research groups, and it was shown that DAFdiscovery reproduced their findings using a more straightforward method. CONCLUSION: DAFdiscovery has proven to be a simple-to-use method for different situations where data from different sources are required to be analyzed together.

A pilot study for fragment identification using 2D NMR and deep learning.

This paper presents a proof of concept of a method to identify substructures in 2D NMR spectra of mixtures using a bespoke image-based convolutional neural network application. This is done using HSQC and HMBC spectra separately and in combination. The application can reliably detect substructures in pure compounds, using a simple network. Results indicate that it can work for mixtures when trained on pure compounds only. HMBC data and the combination of HMBC and HSQC show better results than HSQC alone in this pilot study.

Exploring correlations between MS and NMR for compound identification using essential oils: A pilot study.

INTRODUCTION: In this era of 'omics' technology in natural products studies, the complementary aspects of mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques must be taken into consideration. The advantages of using both analytical platforms are reflected in a higher confidence of results especially when using replicated samples where correlation approaches can be used to statistically link results from MS to NMR. OBJECTIVES: Demonstrate the use of Statistical Total Correlation (STOCSY) for linking results from MS and NMR data to reach higher confidence in compound identification. METHODOLOGY: Essential oil samples of Melaleuca alternifolia and M. rhaphiophylla (Myrtaceae) were used as test objects. Aliquots of 10 samples were collected for GC-MS and NMR data acquisition [proton (1 H)-NMR, and carbon-13 (13 C)-NMR as well as two-dimensional (2D) heteronuclear single quantum correlation (HSQC), heteronuclear multiple-bond correlation (HMBC), and HSQC-total correlated spectroscopy (TOCSY) NMR]. The processed data was imported to Matlab where STOCSY was applied. RESULTS: STOCSY calculations led to the confirmation of the four main constituents of the sample-set. The identification of each was accomplished using; MS spectra, retention time comparison, 13 C-NMR data, and scalar correlations of the 2D NMR spectra. CONCLUSION: This study provides a pipeline for high confidence in compound identification using a set of essential oils samples as test objects for demonstration.

One hundred years from Otto Loewi experiment, a dream that revolutionized our view of neurotransmission.

One hundred years ago, a 4-page paper published in the Pflüger's Archiv fur die Gesamte Physiologie des Menschen und der Tiere dramatically changed our view on synaptic transmission. The paper reported an ingenious, yet straightforward experiment made by Professor Otto Loewi in 1920 and published in 1921, which constitutes the first clear-cut proof for the chemical nature of transmission of the nerve impulse from nerve to muscle. The approach to this experiment was, however, tortuous and long.

DIY Universal Fraction Collector.

Fraction collectors are common pieces of equipment that are essential for the activity of many biochemistry, pharmacology, and drug discovery laboratories. However, these devices are not very versatile when it comes to tailoring them to specific needs, such as different size collection tubes, sequences of tube exchange, or parallel collection. In addition, these systems are relatively expensive, especially for small laboratories or for those in less developed countries. The emergence of 3D printers and the availability of cheap, popular electronic control devices are changing the way laboratory equipment can be made and designed. Here, we describe how to build your own fraction collector, indicating all the elements and providing the full instructions needed to make a fraction collector that can be adapted to almost any kind of rack and tubes (3D files, the parts required, the electronic circuits, and the software). This device can be used in complex protocols, adapted to liquid chromatography and for parallel collection from perfused tissues. The total cost of the whole device is around €100.

Biomonitoring Assessment of Toxic and Trace Elements in Sterechinus neumayeri Sea Urchins from the Comandante Ferraz Station in Antarctica.

In the present study, sea urchin Sterechinus neumayeri tissues were used for the passive biomonitoring of toxic and trace elements at the Comandante Ferraz Station, Antarctica and compared to a pristine region (Botany). As, Ba, Br, Ca, Co, Cr, Fe, K, Na, Rb, Sc, Se and Zn concentrations were determined by instrumental neutron activation analysis (INAA), while toxic metals (Cd, Hg, Ni and Pb), and Cu were determined by atomic absorption spectrometry (GF-AAS). The findings were compared to other organisms commonly applied for biomonitoring purposes and to the sediment concentrations of each sampling region. Urchins from the Ferraz Station area presented higher Br, Co, Cr, Cs, K, Se and Zn levels than the pristine location. The results obtained herein suggest S. neumayeri can be applied to the biomonitoring of Cr and Zn. The present study also contributes to knowledge of the mineral composition of the sea urchin S. neumayeri.

Adrenergic chromaffin cells are adrenergic even in the absence of epinephrine.

Adrenal chromaffin cells release epinephrine (EPI) and norepinephrine (NE) into the bloodstream as part of the homeostatic response to situations like stress. Here we utilized EPI-deficient mice generated by knocking out (KO) the phenylethanolamine N-methyltransferase (Pnmt) gene. These Pnmt-KO mice were bred to homozygosis but displayed no major phenotype. The lack of EPI was partially compensated by an increase in NE, suggesting that EPI storage was optimized in adrenergic cells. Electron microscopy showed that despite the lack of EPI, chromaffin granules retain their shape and general appearance. This indicate that granules from adrenergic or noradrenergic cells preserve their characteristics even though they contain only NE. Acute insulin injection largely reduced the EPI content in wild-type animals, with a minimal reduction in NE, whereas there was only a partial reduction in NE content in Pnmt-KO mice. The analysis of exocytosis by amperometry revealed a reduction in the quantum size (-30%) and Imax (-21%) of granules in KO cells relative to the wild-type granules, indicating a lower affinity of NE for the granule matrix of adrenergic cells. As amperometry cannot distinguish between adrenergic or noradrenergic cells, it would suggest even a larger reduction in the affinity for the matrix. Therefore, our results demonstrate that adrenergic cells retain their structural characteristics despite the almost complete absence of EPI. Furthermore, the chromaffin granule matrix from adrenergic cells is optimized to accumulate EPI, with NE being a poor substitute. Open Science: This manuscript was awarded with the Open Materials Badge For more information see: https://cos.io/our-services/open-science-badges/.

Combining the lack of chromogranins with chronic L-DOPA treatment affects motor activity in mice.

We have tested whether the lack of chromogranins (Cgs) A and B could provoke CNS disorders when combined with an excess of dopamine. We chronically treated (over 6 months) mice lacking both chromogranins A and B (Cgs-KO) with a low oral dosage of L-DOPA/benserazide (10/2.5 mg/kg). Motor performance in the rota-rod test, open field activity, and metabolic cages indicated a progressive impairment in motor coordination in these mice, and an increase in rearing behavior, which was accompanied by an increase in DA within the substantia nigra. We conclude that mild chronic L-DOPA treatment does not produce nigro-striatal toxicity that could be associated with parkinsonism, neither in control nor Cgs-KO mice. Rather, Cgs-KO mice exhibit behaviors compatible with an amphetamine-like effect, probably caused by the excess of catecholamines in the CNS.

Applying NMR compound identification using NMRfilter to match predicted to experimental data.

INTRODUCTION: Metabolomics is the approach of choice to guide the understanding of biological systems and its molecular intricacies, but compound identification is yet a bottleneck to be overcome. OBJECTIVE: To assay the use of NMRfilter for confidence compound identification based on chemical shift predictions for different datasets. RESULTS: We found comparable results using the lead tool COLMAR and NMRfilter. Then, we successfully assayed the use of HMBC to add confidence to the identified compounds. CONCLUSIONS: NMRfilter is currently under development to become a stand-alone interactive software for high-confidence NMR compound identification and this communication gathers part of its application capabilities.

Comprehensive Metabolome Analysis of Fermented Aqueous Extracts of Viscum album L. by Liquid Chromatography-High Resolution Tandem Mass Spectrometry.

Fermented aqueous extracts of Viscum album L. are widely used for cancer treatment in complementary medicine. The high molecular weight compounds viscotoxins and lectins are considered to be the main active substances in the extracts. However, a vast number of small molecules (≤1500 Da) is also expected to be present, and few studies have investigated their identities. In this study, a comprehensive metabolome analysis of samples of fermented aqueous extracts of V. album from two host tree species (Malus domestica and Pinus sylvestris), both prepared by two pharmaceutical manufacturing processes, was performed by liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS). A total of 212 metabolites were putatively annotated, including primary metabolites (e.g., amino acids, organic acids, etc.) and secondary metabolites (mostly phenolic compounds). A clear separation between V. album samples according to the host tree species, but not due to manufacturing processes, was observed by principal component analysis. The biomarkers responsible for this discrimination were assessed by partial least squares-discriminant analysis. Because V. album extracts from different host trees have different clinical applications, the present work highlights the possibility of characterizing the metabolome for identification and traceability of V. album fermented aqueous extracts.

An integrated approach for mixture analysis using MS and NMR techniques.

We suggest an improved software pipeline for mixture analysis. The improvements include combining tandem MS and 2D NMR data for a reliable identification of the constituents in an algorithm based on network analysis aiming for a robust and reliable identification routine. An important part of this pipeline is the use of open-data repositories, although it is not totally reliant on them. The NMR identification step emphasizes robustness and is less sensitive towards changes in data acquisition and processing than existing methods. The process starts with LC-ESI-MSMS based molecular network dereplication using data from the GNPS collaborative collection. We identify closely related structures by propagating structure elucidation through edges in the network. Those identified compounds are added on top of a candidate list for the following NMR filtering method that predicts HSQC and HMBC NMR data. The similarity of the predicted spectra of the set of closely related structures to the measured spectra of the mixture sample is taken as one indication of the most likely candidates for its compounds. The other indication is the match of the spectra to clusters built by a network analysis from the spectra of the mixture. The sensitivity gap between NMR and MS is anticipated and it will be reflected naturally by the eventual identification of fewer compounds, but with a higher confidence level, after the NMR analysis step. The contributions of the paper are an algorithm combining MS and NMR spectroscopy and a robust nJCH network analysis to explore the complementary aspects of both techniques. This delivers good results, even if a perfect computational separation of the compounds in the mixture is not possible. All of the scripts are freely available to aid studies such as with plants, marine organisms, and microorganism natural product chemistry and metabolomics, as those are the driving forces for this project.

Preparative mass-spectrometry profiling of minor concentrated metabolites in Salicornia gaudichaudiana Moq by high-speed countercurrent chromatography and off-line electrospray mass-spectrometry injection.

Salicornia species have just been introduced to the European market as a vegetable named 'samphire', 'green asparagus', or 'sea asparagus'. Due to its increasing attention, and associated value, minor compounds of Salicornia gaudichaudiana Moq were investigated. The use of countercurrent chromatography and mass spectrometry enabled the search for known, as well as potentially novel natural products. Their identification was achieved based on molecular weights and mass-spectrometric fragmentation data. Low detection limits enabled the visualization of all compounds with their identification in almost real time close to the preparative countercurrent chromatography experiment. A list of known natural products from Salicornia genus guided the identification process of compounds occurring in Salicornia gaudichaudiana Moq by tandem mass spectrometry fragment comparison. The natural product classes were divided into four groups: chlorogenic acid derivatives; flavonoid derivatives; pentacyclic triterpenoid saponins; and other compounds.