Automated Detection of Natural Halogenated Compounds from LC-MS Profiles–Application to the Isolation of Bioactive Chlorinated Compounds from Marine-Derived Fungi

New benzophenone analogs from Nigrospora sphaerica and their inhibitory activity against PD-1/PD-L1 interactions

Four newly identified benzophenone analogs [nigrophenone A-D (1-4)] and a pyrrolidinone analog [nigropyrrolidinone (5)], alongside thirteen known congeners (6-18), were isolated from Nigrospora sphaerica. Transcriptome analysis revealed that 6 might have the potential to modulate T-cell immunity. Quantitative measurements of the binding affinities between eighteen natural molecules and the immunological checkpoint receptors PD-1 and PD-L1 were performed using Surface Plasmon Resonance (SPR). The results of SPR analysis showed that 1-18 have KD values ranging from 1.8 to 99.5 μM for PD-1 and from 10.6 to 99.5 μM for PD-L1. Competitive inhibition studies, employing SPR and ELISA assays, have indicated that compounds 6, 10, 15, and 18 are capable of inhibiting the PD-1/PD-L1 interaction. Additionally, compound 6 exhibited notable in vitro anticancer potency through the augmentation of activating signals and the upregulation of PD-1 expression on CD8+ T cells, concurrently elevating the secretion of IFN-γ and IL-2, thereby inhibiting the proliferation of LLC and MC38 cells and promoting MC38 apoptosis. Moreover, compound 6 modulates the PI3K/Akt pathway, which is a key downstream effector of the PD-1/PD-L1 axis. These compounds are considered promising candidates for more in-depth exploration because they could significantly inhibit PD-1/PD-L1 interactions in tumor immunotherapy.

Compendium of Metabolomic and Genomic Datasets for Cyanobacteria: Mined the Gap

Cyanobacterial blooms, producing toxic secondary metabolites, are becoming increasingly common phenomena in the face of rising global temperatures. They are the world's most abundant photosynthetic organisms, largely owing their success to a range of highly diverse and complex natural products possessing a broad spectrum of different bioactivities. Over 2600 compounds have been isolated from cyanobacteria thus far, and their characterisation has revealed unusual and useful chemistries and motifs including alkynes, halogens, and non-canonical amino acids. Genome sequencing of cyanobacteria lags behind natural product isolation, with only 19% of cyanobacterial natural products associated with a sequenced organism. Recent advances in meta(genomics) provide promise to narrow this gap and has also facilitated the uprise of combined genomic and metabolomic approaches, heralding a new era of discovery of novel compounds. Analyses of the datasets described within this manuscript reveal the asynchrony of current genomic and metabolomic data, highlight the chemical diversity of cyanobacterial natural products. Linked to this manuscript, we make these manually curated datasets freely accessible for the public to facilitate further research in this important area.

Chemo-Selective Single-Cell Metabolomics Reveals the Spatiotemporal Behavior of Exogenous Pollutants During Xenopus Laevis Embryogenesis

In-depth profiling of embryogenesis-associated endogenous and exogenous metabolic changes can reveal potential bio-effects resulting from human-made chemicals and underlying mechanisms. Due to the lack of potent tools for monitoring spatiotemporal distribution and bio-transformation behavior of dynamic metabolites at single-cell resolution, however, how and to what extent environmental chemicals may influence or interfere embryogenesis largely remain unclear. Herein, a zero-sample-loss micro-biopsy-based mass spectrometric platform is presented for quantitative, chemo-selective, high-coverage, and minimal-destructive profiling of development-associated cis-diol metabolites, which are critical for signal transduction and epigenome regulation, at both cellular level and tissue level of Xenopus laevis. Using this platform, three extraordinary findings that are otherwise hard to achieve are revealed: 1) there are characteristically different cis-diol metabolic signatures among oocytes, anterior and posterior part of tailbud-stage embryos; 2) halogenated cis-diols heavily accumulate at the posterior part of tailbud-stage embryos of Xenopus laevis; 3) dimethachlon, a kind of exogenous fungicide that is widely used as pesticide, may be bio-transformed and accumulated in vertebrate animals in environment. Thus, this study opens a new avenue to simultaneously monitoring intercellular and intraembryonic heterogeneity of endogenous and exogenous metabolites, providing new insights into metabolic remolding during embryogenesis and putting a warning on potential environmental risk.

Accelerating the discovery of alkyl halide-derived natural products using halide depletion

Even in the genomic era, microbial natural product discovery workflows can be laborious and limited in their ability to target molecules with specific structural features. Here we leverage an understanding of biosynthesis to develop a workflow that targets the discovery of alkyl halide-derived natural products by depleting halide anions, a key biosynthetic substrate for enzymatic halogenation, from microbial growth media. By comparing the metabolomes of bacterial cultures grown in halide-replete and deficient media, we rapidly discovered the nostochlorosides, the products of an orphan halogenase-encoding gene cluster from Nostoc punctiforme ATCC 29133. We further found that these products, a family of unusual chlorinated glycolipids featuring the rare sugar gulose, are polymerized via an unprecedented enzymatic etherification reaction. Together, our results highlight the power of leveraging an understanding of biosynthetic logic to streamline natural product discovery.

ChloroDBPFinder: Machine Learning-Guided Recognition of Chlorinated Disinfection Byproducts from Nontargeted LC-HRMS Analysis

High-resolution mass spectrometry (HRMS) is a prominent analytical tool that characterizes chlorinated disinfection byproducts (Cl-DBPs) in an unbiased manner. Due to the diversity of chemicals, complex background signals, and the inherent analytical fluctuations of HRMS, conventional isotopic pattern (37Cl/35Cl), mass defect, and direct molecular formula (MF) prediction are insufficient for accurate recognition of the diverse Cl-DBPs in real environmental samples. This work proposes a novel strategy to recognize Cl-containing chemicals based on machine learning. Our hierarchical machine learning framework has two random forest-based models: the first layer is a binary classifier to recognize Cl-containing chemicals, and the second layer is a multiclass classifier to annotate the number of Cl present. This model was trained using ∼1.4 million distinctive MFs from PubChem. Evaluated on over 14,000 unique MFs from NIST20, this machine learning model achieved 93.3% accuracy in recognizing Cl-containing MFs (Cl-MFs) and 92.9% accuracy in annotating the number of Cl for Cl-MFs. Furthermore, the trained model was integrated into ChloroDBPFinder, a standalone R package for the streamlined processing of LC-HRMS data and annotating both known and unknown Cl-containing compounds. Tested on existing Cl-DBP data sets related to aspartame chlorination in tap water, our ChloroDBPFinder efficiently extracted 159 Cl-containing DBP features and tentatively annotated the structures of 10 Cl-DBPs via molecular networking. In another application of a chlorinated humic substance, ChloroDBPFinder extracted 79 high-quality Cl-DBPs and tentatively annotated six compounds. In summary, our proposed machine learning strategy and the developed ChloroDBPFinder provide an advanced solution to identifying Cl-containing compounds in nontargeted analysis of water samples. It is freely available on GitHub (https://github.com/HuanLab/ChloroDBPFinder).

Discovery of Modified Metabolites, Secondary Metabolites, and Xenobiotics by Structure-Oriented LC-MS/MS

Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.

Nontarget Insights into the Fate of Cl-/Br-Containing DOM in Leachate during Membrane Treatment

Halogenated organic compounds in wastewater are persistent and bioaccumulative contaminants of great concern, but few are known at the molecular level. Herein, we focus on nontarget screening of halogenated dissolved organic matter (DOM) in highly concentrated organic matrices of waste leachates and their concentrates. Solid-phase extraction (SPE) was optimized before capturing halogenated signatures via HaloSeeker 2.0 software on mining full-scan high-resolution mass spectrometry (HRMS) fingerprints. This study identified 438 Cl-/Br-containing DOM formulas in 21 leachates and membrane concentrates. Among them, 334 formulas were achieved via SPE with mixed-sorbent cartridges (mixed-SPE), surpassing the 164 formulas achieved through Bond Elut PPL cartridges (PPL-SPE). Herein, only four samples identified via PPL-SPE exhibited a resolution of >50% for extracted Cl-/Br-containing DOM by either SPE. The halogenated DOM constituted 6.87% of the total DOM mass features. Nevertheless, more abundant adsorbable organic halogens deciphered waste leachates and highly concentrated waste streams as reservoirs for halogenated contaminants. Remarkably, 75.7-98.1% of Cl-/Br-containing DOM in primary membrane concentrates remained stable through the secondary membrane treatment, indicating the persistence of these unknown contaminants even post-treatment.

Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective

Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made. In this review, the basic principles on recognition of environmental organic pollutants are overviewed. Complementary analytical methodologies (i.e., quantitative structure-activity relationship prediction, mass spectrometric nontarget screening, and effect-directed analysis) and experimental platforms are briefly described. The stages of technique development and/or essential parts of the analytical workflow for each of the methodologies are then reviewed. Finally, plausible technique paths and applications of the future nontarget screening methods, interdisciplinary techniques for achieving toxicant identification, and burgeoning strategies on risk assessment of chemical cocktails are discussed.

Heterologous Expression and Biochemical Characterization of a New Chloroperoxidase Isolated from the Deep-Sea Hydrothermal Vent Black Yeast Hortaea werneckii UBOCC-A-208029

The initiation of this study relies on a targeted genome-mining approach to highlight the presence of a putative vanadium-dependent haloperoxidase-encoding gene in the deep-sea hydrothermal vent fungus Hortaea werneckii UBOCC-A-208029. To date, only three fungal vanadium-dependent haloperoxidases have been described, one from the terrestrial species Curvularia inaequalis, one from the fungal plant pathogen Botrytis cinerea, and one from a marine derived isolate identified as Alternaria didymospora. In this study, we describe a new vanadium chloroperoxidase from the black yeast H. werneckii, successfully cloned and overexpressed in a bacterial host, which possesses higher affinity for bromide (Km = 26 µM) than chloride (Km = 237 mM). The enzyme was biochemically characterized, and we have evaluated its potential for biocatalysis by determining its stability and tolerance in organic solvents. We also describe its potential three-dimensional structure by building a model using the AlphaFold 2 artificial intelligence tool. This model shows some conservation of the 3D structure of the active site compared to the vanadium chloroperoxidase from C. inaequalis but it also highlights some differences in the active site entrance and the volume of the active site pocket, underlining its originality.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.

Naturally Occurring Organohalogen Compounds-A Comprehensive Review

The present volume is the third in a trilogy that documents naturally occurring organohalogen compounds, bringing the total number-from fewer than 25 in 1968-to approximately 8000 compounds to date. Nearly all of these natural products contain chlorine or bromine, with a few containing iodine and, fewer still, fluorine. Produced by ubiquitous marine (algae, sponges, corals, bryozoa, nudibranchs, fungi, bacteria) and terrestrial organisms (plants, fungi, bacteria, insects, higher animals) and universal abiotic processes (volcanos, forest fires, geothermal events), organohalogens pervade the global ecosystem. Newly identified extraterrestrial sources are also documented. In addition to chemical structures, biological activity, biohalogenation, biodegradation, natural function, and future outlook are presented.

Discovering New Natural Products Using Metabolomics-Based Approaches

The incessant search for new natural molecules with biological activities has forced researchers in the field of chemistry of natural products to seek different approaches for their prospection studies. In particular, researchers around the world are turning to approaches in metabolomics to avoid high rates of re-isolation of certain compounds, something recurrent in this branch of science. Thanks to the development of new technologies in the analytical instrumentation of spectroscopic and spectrometric techniques, as well as the advance in the computational processing modes of the results, metabolomics has been gaining more and more space in studies that involve the prospection of natural products. Thus, this chapter summarizes the precepts and good practices in the metabolomics of microbial natural products using mass spectrometry and nuclear magnetic resonance spectroscopy, and also summarizes several examples where this approach has been applied in the discovery of bioactive molecules.

Halogenation in Fungi: What Do We Know and What Remains to Be Discovered?

In nature, living organisms produce a wide variety of specialized metabolites to perform many biological functions. Among these specialized metabolites, some carry halogen atoms on their structure, which can modify their chemical characteristics. Research into this type of molecule has focused on how organisms incorporate these atoms into specialized metabolites. Several families of enzymes have been described gathering metalloenzymes, flavoproteins, or S-adenosyl-L-methionine (SAM) enzymes that can incorporate these atoms into different types of chemical structures. However, even though the first halogenation enzyme was discovered in a fungus, this clade is still lagging behind other clades such as bacteria, where many enzymes have been discovered. This review will therefore focus on all halogenation enzymes that have been described in fungi and their associated metabolites by searching for proteins available in databases, but also by using all the available fungal genomes. In the second part of the review, the chemical diversity of halogenated molecules found in fungi will be discussed. This will allow the highlighting of halogenation mechanisms that are still unknown today, therefore, highlighting potentially new unknown halogenation enzymes.

Xanthones and benzophenones isolated from the endophytic fungus Penicillium sp. ct-28 of Corydlis tomentella and their cytotoxic activity

One new xanthone, griseophenexanthone A (1), one new benzophenone, digriseophene A (2), and 14 previously reported compounds were isolated from the culture of Penicillium sp. ct-28, an endophytic fungus of Corydlis tomentella. The structures of the isolated compounds were identified by an extensive analysis of HRESIMS, 1D and 2D NMR. MTT assay showed that six xanthones (1 and 3-7) significantly inhibited cell proliferation in four cancer cell lines, with IC₅₀ values ranging from 18.12 ± 2.42 to 85.55 ± 7.66 μM. Our results showed that slight structural changes led to obvious activity differences among these compounds. We also investigated the effects of the six xanthones on cell cycle and apoptosis in human hepatoma HepG2 cells. Compound 7 caused cell cycle arrest at G1 phase, compounds 5 and 6 caused cell cycle arrest at S phase, whereas compounds 1, 3 and 4 had no effects on cell cycle distribution. All six xanthones induced apoptosis in dose-dependent manners in HepG2 cells accompanied by degradation of PARP and activation of caspase 3. The structure-activity relationship analysis revealed that the effects of these xanthones on cell cycle and apoptosis in HepG2 cells were closely related to the substituent groups on their skeleton. Our studies provide novel insights for the structural optimization of xanthones in the development of new anticancer drugs.

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.

Untargeted Metabolite Profiling of Antimicrobial Compounds in the Brown Film of Lentinula edodes Mycelium via LC-MS/MS Analysis

The brown film (BF) of Lentinula edodes mycelium has been reported to exert biological activities during mushroom cultivation; however, to date, there is limited information on its chemical composition. In this study, untargeted metabolomics analysis was performed via liquid chromatography-mass spectrometry (LC-MS), and the results were used to screen the antimicrobial compounds. A total of 236 differential metabolites were found among the BF stages compared with the white hyphal stage. Among them, five important antimicrobial metabolites related to antimicrobial activities, namely, 6-deoxyerythronolide B, tanikolide, hydroxyanthraquinone, benzylideneacetone, and 9-OxooTrE, were present at high levels in the BF samples. The score plots of the principal component analysis indicated that the samples from four time points could be classified into two groups. This study provided a comprehensive profile of the antimicrobial compounds produced during BF formation and partly clarified the antibacterial and antifungal mechanism of the BF of L. edodes mycelium.

Metabolomic tools used in marine natural product drug discovery

Introduction: The marine environment is a very promising resource for natural product research, with many of these reaching the market as new drugs, especially in the field of cancer therapy as well as the drug discovery pipeline for new antimicrobials. Exploitation for bioactive marine compounds with unique structures and novel bioactivity such as the isoquinoline alkaloid; trabectedin, the polyether macrolide; halichondrin B, and the peptide; dolastatin 10, requires the use of analytical techniques, which can generate unbiased, quantitative, and qualitative data to benefit the biodiscovery process. Metabolomics has shown to bridge this understanding and facilitate the development of new potential drugs from marine sources and particularly their microbial symbionts.Areas covered: In this review, articles on applied secondary metabolomics ranging from 1990-2018 as well as to the last quarter of 2019 were probed to investigate the impact of metabolomics on drug discovery for new antibiotics and cancer treatment.Expert opinion: The current literature review highlighted the effectiveness of metabolomics in the study of targeting biologically active secondary metabolites from marine sources for optimized discovery of potential new natural products to be made accessible to a R&D pipeline.

Automated Isotopic Profile Deconvolution for High Resolution Mass Spectrometric Data (APGC-QToF) from Biological Matrices

An isotopic profile matching algorithm, the isotopic profile deconvoluted chromatogram (IPDC), was developed to screen for a wide variety of organic compounds in high-resolution mass spectrometry (HRMS) data acquired from instruments with resolution power as low as 22 000 fwhm. The algorithm initiates the screening process by generating a series of C/Br/Cl/S isotopic patterns consistent with the profiles of approximately 3 million molecular formulas for compounds with potentially persistent, bioaccumulative, and toxic (PBT) properties. To evaluate this algorithm, HRMS data were screened using these seed profiles to isolate relevant chlorinated and/or brominated compounds. Data reduction techniques included mass defect filtering and retention time prediction from estimated boiling points predicted using molecular formulas and reasonable elemental conformations. A machine learning classifier was also developed using spectrometric and chromatographic variables to minimize false positives. A scoring system was developed to rank candidate molecular formulas for an isotopic feature. The IPDC algorithm was applied to a Lake Michigan lake trout extract analyzed by atmospheric pressure gas chromatography-quadrupole time-of-flight (APGC-QToF) mass spectrometry in positive and negative modes. The IPDC algorithm detected isotopic features associated with legacy contaminants and a series of unknown halogenated features. The IPDC algorithm resolved 313 and 855 halogenated features in positive and negative modes, respectively, in Lake Michigan lake trout.

From genomics to metabolomics, moving toward an integrated strategy for the discovery of fungal secondary metabolites

Fungal secondary metabolites are defined by bioactive properties that ensure adaptation of the fungus to its environment. Although some of these natural products are promising sources of new lead compounds especially for the pharmaceutical industry, others pose risks to human and animal health. The identification of secondary metabolites is critical to assessing both the utility and risks of these compounds. Since fungi present biological specificities different from other microorganisms, this review covers the different strategies specifically used in fungal studies to perform this critical identification. Strategies focused on the direct detection of the secondary metabolites are firstly reported. Particularly, advances in high-throughput untargeted metabolomics have led to the generation of large datasets whose exploitation and interpretation generally require bioinformatics tools. Then, the genome-based methods used to study the entire fungal metabolic potential are reported. Transcriptomic and proteomic tools used in the discovery of fungal secondary metabolites are presented as links between genomic methods and metabolomic experiments. Finally, the influence of the culture environment on the synthesis of secondary metabolites by fungi is highlighted as a major factor to consider in research on fungal secondary metabolites. Through this review, we seek to emphasize that the discovery of natural products should integrate all of these valuable tools. Attention is also drawn to emerging technologies that will certainly revolutionize fungal research and to the use of computational tools that are necessary but whose results should be interpreted carefully.

HaloSeeker 1.0: A User-Friendly Software to Highlight Halogenated Chemicals in Nontargeted High-Resolution Mass Spectrometry Data Sets

In the present work, we address the issue of nontargeted screening of organohalogenated chemicals in complex matrixes. A global strategy aiming to seek halogenated signatures in full-scan high-resolution mass spectrometry (HRMS) fingerprints was developed. The resulting all-in-one user-friendly application, HaloSeeker 1.0, was developed to promote the accessibility of associated in-house bioinformatics tools to a large audience. The ergonomic web user interface avoids any interactions with the coding component while allowing interactions with the data, including peak detection (features), deconvolution, and comprehensive accompanying manual review for chemical formula assignment. HaloSeeker 1.0 was successfully applied to a marine sediment HRMS data set acquired on a liquid chromatography-heated electrospray ionization [LC-HESI(-)] Orbitrap instrument ( R = 140 000 at m/z 200). Among the 4532 detected features, 827 were paired and filtered in 165 polyhalogenated clusters. HaloSeeker was also compared to three similar tools and showed the best performances. HaloSeeker's ability to filter and investigate halogenated signals was demonstrated and illustrated by a potential homologue series with C₁₂H _xBr _yCl _zO₂ as a putative general formula.

Colorimetric Detection of Carcinogenic Alkylating Fumigants on Nylon-6 Nanofibrous Membrane. Part I: Investigation of 4-( p-Nitrobenzyl)pyridine as a "New" Sensing Agent with Ultrahigh Sensitivity

Alkylating fumigants are widely used in agricultural production for the control of soil-borne pests, but the acute toxicity and carcinogenicity of these chemicals pose a health threat to farm workers, as well as residents. A nanofibrous membrane-based colorimetric sensor relying on the nucleophilic substitution reaction of 4-( p-nitrobenzyl)pyridine (NBP) is introduced for the convenient and portable detection of alkylating fumigants. Comparing with the traditional use of NBP in detecting alkylating agents, this sensor system achieves a parts per billion level detection sensitivity toward alkylating fumigant gases without a high-temperature incubation or the addition of extra bases. The mechanisms of the detection reaction and the detection sensitivities of different fumigants were studied with computational methods, and the results comprehensively prove the proposed optimized detection mechanisms. The detection limit of methyl iodide, methyl bromide, and 1,3-dichloropropene successfully reaches to the limiting exposure concentrations (PEL or REL) with a naked-eye detectable color difference within 5 min with a dynamic detection procedure. The designed sensing system is promising for a real-time monitoring of the air quality related to alkylating fumigants in the environment, especially in agricultural and industrial areas.

Metabolomics-Driven Discovery of Meroterpenoids from a Mussel-Derived Penicillium ubiquetum

Penicillium ubiquetum MMS330 isolated from the blue mussel Mytilus edulis collected on the Loire estuary in France was here investigated. As very few secondary metabolites have been documented for this species, its metabolome was studied following the OSMAC approach to enhance as many biosynthetic pathways as possible. Interestingly, HPLC-HRMS based hierarchical clustering analysis together with MS/MS molecular networking highlighted the selective overproduction of some structurally related compounds when the culture was performed on seawater CYA (Czapek Yeast extract Agar) medium. Mass-guided purification from large scale cultivation on this medium led to the isolation of nine meroterpenoids including two new analogues, 22-deoxyminiolutelide A (1) and 4-hydroxy-22-deoxyminiolutelide B (2), together with seven known compounds (3-9). The structures of 1 and 2 were elucidated on the basis of HR-ESIMS and NMR spectroscopic data analysis. Furthermore, NMR signals of 22-deoxyminiolutelide B (3) were reassigned.

Nitrosopyridine Probe To Detect Polyketide Natural Products with Conjugated Alkenes: Discovery of Novodaryamide and Nocarditriene

An optimized nitroso-based probe that facilitates the discovery of conjugated alkene-containing natural products in unprocessed extracts was developed. It chemoselectively reacts with conjugated olefins via a nitroso-Diels-Alder cyclization to yield derivatives with a distinct chromophore and an isotopically unique bromine atom that can be rapidly identified using liquid chromatography/mass spectrometry and a bioinformatics tool called MeHaloCoA (Marine Halogenated Compound Analysis). The probe is ideally employed when genome-mining techniques identify strains containing polyketide gene clusters with two or more repeating KS-AT-DH-KR-ACP domain sequences, which are required for the biosynthesis of conjugated alkenes. Comparing the reactivity and spectral properties of five brominated arylnitroso reagents with model compounds spiramycin, bufalin, rapamycin, and rifampicin led to the identification of 5-bromo-2-nitrosopyridine as the most suitable probe structure. The utility of the dienophile probe was then demonstrated in bacterial extracts. Tylactone, novodaryamide and daryamide A, piperazimycin A, and the saccharamonopyrones A and B were cleanly labeled in extracts from their respective bacterial producers, in high regioselectivity but with varying degrees of diastereoselectivity. Further application of the method led to the discovery of a new natural product called nocarditriene, containing an unprecedented epoxy-2,3,4,5-tetrahydropyridine structure, from marine-derived Nocardiopsis strain CNY-503.

Computational Methodologies in the Exploration of Marine Natural Product Leads

Computational methodologies are assisting the exploration of marine natural products (MNPs) to make the discovery of new leads more efficient, to repurpose known MNPs, to target new metabolites on the basis of genome analysis, to reveal mechanisms of action, and to optimize leads. In silico efforts in drug discovery of NPs have mainly focused on two tasks: dereplication and prediction of bioactivities. The exploration of new chemical spaces and the application of predicted spectral data must be included in new approaches to select species, extracts, and growth conditions with maximum probabilities of medicinal chemistry novelty. In this review, the most relevant current computational dereplication methodologies are highlighted. Structure-based (SB) and ligand-based (LB) chemoinformatics approaches have become essential tools for the virtual screening of NPs either in small datasets of isolated compounds or in large-scale databases. The most common LB techniques include Quantitative Structure–Activity Relationships (QSAR), estimation of drug likeness, prediction of adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, similarity searching, and pharmacophore identification. Analogously, molecular dynamics, docking and binding cavity analysis have been used in SB approaches. Their significance and achievements are the main focus of this review.

Marine natural products

Covering: 2016. Previous review: Nat. Prod. Rep., 2017, 34, 235-294This review covers the literature published in 2016 for marine natural products (MNPs), with 757 citations (643 for the period January to December 2016) referring to compounds isolated from marine microorganisms and phytoplankton, green, brown and red algae, sponges, cnidarians, bryozoans, molluscs, tunicates, echinoderms, mangroves and other intertidal plants and microorganisms. The emphasis is on new compounds (1277 in 432 papers for 2016), together with the relevant biological activities, source organisms and country of origin. Reviews, biosynthetic studies, first syntheses, and syntheses that led to the revision of structures or stereochemistries, have been included.

Marine-Derived Penicillium Species as Producers of Cytotoxic Metabolites

Since the discovery of penicillin, Penicillium has become one of the most attractive fungal genera for the production of bioactive molecules. Marine-derived Penicillium has provided numerous excellent pharmaceutical leads over the past decades. In this review, we focused on the cytotoxic metabolites * (* Cytotoxic potency was referred to five different levels in this review, extraordinary (IC₅₀/LD₅₀: <1 μM or 0.5 μg/mL); significant (IC₅₀/LD₅₀: 1~10 μM or 0.5~5 μg/mL); moderate (IC₅₀/LD₅₀: 10~30 μM or 5~15 μg/mL); mild (IC₅₀/LD₅₀: 30~50 μM or 15~25 μg/mL); weak (IC₅₀/LD₅₀: 50~100 μM or 25~50 μg/mL). The comparative potencies of positive controls were referred when they were available). produced by marine-derived Penicillium species, and on their cytotoxicity mechanisms, biosyntheses, and chemical syntheses.

Dynamic Cluster Analysis: An Unbiased Method for Identifying A + 2 Element Containing Compounds in Liquid Chromatographic High-Resolution Time-of-Flight Mass Spectrometric Data

Dynamic cluster analysis (DCA) is an automated, unbiased technique which can identify Cl, Br, S, and other A + 2 element containing metabolites in liquid chromatographic high-resolution mass spectrometric data. DCA is based on three features, primarily the previously unutilized A + 1 to A + 2 isotope cluster spacing which is a strong classifier in itself but improved with the addition of the monoisotopic mass, and the well-known A:A+2 intensity ratio. Utilizing only the A + 1 to A + 2 isotope cluster spacing and the monoisotopic mass it was possible to filter a chromatogram for metabolites which contain Cl, Br, and S. Screening simulated isotope patterns of the Antibase Natural Products Database it was determined that the A + 1 to A + 2 isotope cluster spacing can be used to correctly classify 97.4% of molecular formulas containing these elements, only misclassifying a few metabolites which were either over 2800 u or metabolites which contained other A + 2 elements, such as Cu, Ni, Mg, and Zn. It was determined that with an interisotopic mass accuracy of 1 ppm, in a fully automated process, using all three parameters, it is possible to specifically filter a chromatogram for S containing metabolites with monoisotopic masses less than 825 u. Furthermore, it was possible to specifically filter a chromatogram for Cl and Br containing metabolites with monoisotopic masses less than 1613 u. Here DCA is applied on (i) simulated isotope patterns of the Antibase natural products databases, (ii) LC-QTOF data of reference standards, and (iii) LC-QTOF data of crude extracts of 10 strains of laboratory grown cultures of the microalga Prymnesium parvum where it identified known metabolites of the prymnesin series as well as over 20 previously undescribed prymnesin-like molecular features.