Mass spectrometry of natural products: current, emerging and future technologies

Direct Identification of α-Bisabolol Enantiomers in an Essential Oil Using a Combined Ion Mobility-Mass Spectrometry/Quantum Chemistry Approach

Enantiomer-specific identification of chiral molecules in natural extracts is a challenging task, as many routine analytical techniques fail to provide selectivity in multicomponent mixtures. Here we describe an alternative approach, based on the combination of ion mobility-mass spectrometry (IM-MS) and quantum chemistry (QM), for the direct enantiomers differentiation in crude essential oils. The identification of α-bisabolol enantiomers contained in the raw essential oil (EO) from the Corsican Xanthium italicum fruits is reported as a proof-of-concept. Accordingly, IM-MS experiments performed in Ag+-doped methanol revealed the presence of both (+)- and (-)-α-bisabolol in the EO, while molecular simulations provided the structures of the two α-bisabolol enantiomer silver(I) adducts.

Knowledge-based in silico fragmentation and annotation of mass spectra for natural products with MassKG

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) is a potent analytical technique utilized for identifying natural products from complex sources. However, due to the structural diversity, annotating LC-MS/MS data of natural products efficiently remains challenging, hindering the discovery process of novel active structures. Here, we introduce MassKG, an algorithm that combines a knowledge-based fragmentation strategy and a deep learning-based molecule generation model to aid in rapid dereplication and the discovery of novel NP structures. Specifically, MassKG has compiled 407,720 known NP structures and, based on this, generated 266,353 new structures using chemical language models for the discovery of potential novel compounds. Furthermore, MassKG demonstrates exceptional performance in spectra annotation compared to state-of-the-art algorithms. To enhance usability, MassKG has been implemented as a web server for annotating tandem mass spectral data (MS/MS, MS2) with a user-friendly interface, automatic reporting, and fragment tree visualization. Lastly, the interpretive capability of MassKG is comprehensively validated through composition analysis and MS annotation of Panax notoginseng, Ginkgo biloba, Codonopsis pilosula, and Astragalus membranaceus. MassKG is now accessible at https://xomics.com.cn/masskg.

Targeted isolation of antiviral cinnamoylphloroglucinol-terpene adducts from Cleistocalyx operculatus by building blocks-based molecular networking approach

The building blocks-based molecular network (BBMN) strategy was applied to the phytochemical investigation of Cleistocalyx operculatus, leading to the targeted isolation of eighteen novel cinnamoylphloroglucinol-terpene adducts (CPTAs) with diverse skeleton types (cleistoperones A-R, 1-18). Their structures including absolute configurations were determined by extensive spectroscopic methods, quantum chemical calculations, and single-crystal X-ray crystallographic experiments. Cleistoperone A (1), consisting of a cinnamoylphloroglucinol motif and two linear monoterpene moieties, represents an unprecedented macrocyclic CPTA, whose densely functionalized tricyclo[15.3.1.03,8]heneicosane bridge ring skeleton contains an enolizable β,β'-triketone system and two different kinds of stereogenic elements (including five point and three planar chiralities). Cleistoperones B and C (2 and 3) are two new skeletal CPTAs with an unusual coupling pattern between the (nor)monoterpene moiety and the cinnamoyl chain of the cinnamoylphloroglucinol unit. Cleistoperone D (4) possesses an unprecedented cage-like 6/6/6/4/6-fused heteropentacyclic scaffold. The plausible biosynthetic pathways for 1-18 were also proposed. Notably, compounds 1, 4, 7, 8, and 18 exhibited significant antiviral activity against respiratory syncytial virus (RSV). The most potent one, cleistoperone A (1) with IC50 value of 1.71 ± 0.61 μmol/L, could effectively inhibit virus replication via affecting the Akt/mTOR/p70S6K signaling pathway.

New Cytotoxic γ-Lactam Alkaloids from the Mangrove-Derived Fungus Talaromyces hainanensis sp. nov. Guided by Molecular Networking Strategy

The fungus Talaromyces hainanensis, isolated from the mangrove soil, was characterized as a novel species by morphology observation and phylogenetic analyses. Four new γ-lactam alkaloids talaroilactams A-D (1-4) and two reported compounds harzianic acid (5) and isoharzianic acid (6) were identified from the fungus T. hainanensis WHUF0341, assisted by OSMAC along with molecular networking approaches. Their structures were determined through ECD calculations and spectroscopic analyses. Moreover, the biosynthetic route of 1-4 was also proposed. Compound 1 displayed potent cytotoxicity against HepG2 cell lines, with an IC50 value of 10.75 ± 1.11 μM. In addition, network pharmacology was employed to dissect the probable mechanisms contributing to the antihepatocellular carcinoma effects of compound 1, revealing that cytotoxicity was mainly associated with proteolysis, negative regulation of autophagy, inflammatory response, and the renin-angiotensin system. These results not only expanded the chemical space of natural products from the mangrove associated fungi but also afforded promising lead compounds for developing the antihepatocellular carcinoma agents.

B. Trivella D. NP3 MS Workflow: An Open-Source Software System to Empower Natural Product-Based Drug Discovery Using Untargeted Metabolomics

Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.

Unveiling the fungal color palette: pigment analysis of Fusarium solani species complex and Curvularia verruculosa clinical isolates

Fungal species in the Nectriaceae, such as Fusarium spp. (Hypocreales: Nectriaceae), are etiologic agents of hyalohyphomycosis capable of producing violaceous or yellowish pigments under certain conditions, while Curvularia spp. (Pleosporales: Pleosporaceae) are agents of phaeohyphomycosis and typically produce melanin in their cell walls. In nectriaceous and pleosporaceous fungi, these pigments are mainly constituted by polyketides (e.g., azaphilones, naphthoquinones, and hydroxyanthraquinones). Considering the importance of pigments synthesized by these genera, this work focused on the selective extraction of pigments produced by eight Fusarium solani species complex and one Curvularia verruculosa isolate recovered from dermatomycosis specimens, their separation, purification, and posterior chemical analysis. The pigments were characterized through spectral and acid-base analysis, and their maximum production time was determined. Moreover, spectral identification of isolates was carried out to approach the taxonomic specificity of pigment production. Herein we describe the isolation and characterization of three acidic pigments, yellowish and pinkish azaphilones (i.e., coaherin A and sclerotiorin), and a purplish xanthone, reported for the first time in the Nectriaceae and Pleosporaceae, which appear to be synthesized in a species-independent manner, in the case of fusaria.

Hirsutinolide- and Cadinanolide-type Sesquiterpene Lactones from Lessingianthus rubricaulis (Vernonieae, Asteraceae)

Sesquiterpene lactones are an important class of secondary metabolites frequently isolated from Lessingianthus genus that present a variety of biological properties, such as antimalarial, anti-inflammatory, antileishmanial, antitrypanosomal and anticancer. The limited phytochemical studies and the importance of this class of compounds isolated from Lessingianthus led us to study this genus. In this work, we focused on the phytochemical investigation and dereplication based on UHPLC-HRMS/MS and molecular networking of L. rubricaulis. Chemical investigation resulted in the isolation of several hirsutinolide-type sesquiterpene lactones including a new hirsutinolide derivative, 8,10α-hydroxy-1,13-bis-O-methylhirsutinolide, besides a cadinanolide and flavonoids. The dereplication study resulted in the identification of three known flavonoids, six known hirsutinolides and two known cadinanolides. Moreover, a fragmentation pathway for cadinanolide-type sesquiterpene lactones was proposed. These results contribute to chemotaxonomic studies and demonstrates the potential of Lessingianthus genus.

SpectraX: A Straightforward Tool for Principal Component Analysis-Based Spectral Analysis

The analysis of complex spectra is an important component of direct/ambient mass spectrometry (MS) applications such as natural product screening. Unlike chromatography-based metabolomics or proteomics approaches, which rely on software and algorithms, the work of spectral screening is mostly performed manually in the initial stages of research and relies heavily on the experience of the analyst. As a result, throughput and spectral screening reliability are problematic when dealing with large amounts of data. Here, we present SpectraX, a MATLAB-based application, which can analyze MS spectra and quickly locate m/z features from them. Principal component analysis (PCA) is used to analyze the data set, and scoring plots are presented to help in understanding the clustering of data. The algorithm uses mass to charge (m/z) features to produce a list of potential natural products.

Succession of microbial community composition and secondary metabolism during marine biofilm development

In nature, secondary metabolites mediate interactions between microorganisms residing in complex microbial communities. However, the degree to which community dynamics can be linked to secondary metabolite potential remains largely unknown. In this study, we address the relationship between community succession and secondary metabolism variation. We used 16S and 18S rRNA gene and adenylation domain amplicon sequencing, genome-resolved metagenomics, and untargeted metabolomics to track the taxons, biosynthetic gene clusters, and metabolome dynamics in situ of microorganisms during marine biofilm succession over 113 days. Two phases were identified during the community succession, with a clear shift around Day 29, where the alkaloid secondary metabolites, pseudanes, were also detected. The microbial secondary metabolite potential changed between the phases, and only a few community members, including Myxococotta spp., were responsible for the majority of the biosynthetic gene cluster potential in the early succession phase. In the late phase, bryozoans and benthic copepods were detected, and the microbial nonribosomal peptide potential drastically decreased in association with a reduction in the relative abundance of the prolific secondary metabolite producers. Conclusively, this study provides evidence that the early succession of the marine biofilm community favors prokaryotes with high nonribosomal peptide synthetase potential. In contrast, the late succession is dominated by multicellular eukaryotes and a reduction in bacterial nonribosomal peptide synthetase potential.

OrbiFragsNets. A tool for automatic annotation of orbitrap MS2 spectra using networks grade as selection criteria

We introduce OrbiFragsNets, a tool for automatic annotation of MS2 spectra generated by Orbitrap instruments, as well as the concepts of chemical consistency and fragments networks. OrbiFragsNets takes advantage of the specific confidence interval for each peak in every MS2 spectrum, which is an unclear idea across the high-resolution mass spectrometry literature. The spectrum annotations are expressed as fragments networks, a set of networks with the possible combinations of annotations for the fragments. The model behind OrbiFragsNets is briefly described here and explained in detail in the constantly updated manual available in the GitHub repository. This new approach in MS2 spectrum de novo automatic annotation proved to perform as good as well established tools such as RMassBank and SIRIUS.•A new approach on automatic annotation of Orbitrap MS2 spectra is introduced.•Possible spectrum annotation are described as independent consistent networks, with annotations for each fragment as nodes, and annotations for the mass difference between fragments as edges.•Annotation process is described as the selection of the most connected fragments network.

Validation of a Method for Anacardic Acid Quantification in Cashew Peduncles via High-Performance Liquid Chromatography Coupled to a Diode-Array Detector

The cashew peduncle has a high nutritional value and contains a wide variety of phenolic compounds. Among these, anacardic acids (AnAc) are biologically active components; however, they influence the cashew juice flavor and, consequently, its acceptance. This study validates a high-performance liquid chromatography method for quantifying the AnAc present in cashew peduncles, using a C₁₈ reverse-phase column and a diode-array detector. The calibration curve obtained showed satisfactory precision for intraday (CV = 0.20%) and interday (CV = 0.29%) quantification, linearity (y = 2333.5x + 2956.2; r² = 0.9979), repeatability with respect to retention time (CV = 0.45%) and area (CV = 0.30%), and selectivity, and possessed detection and quantification limits of 0.18 and 0.85 µg·mL^-1, respectively. Different cashew clones containing AnAc were extracted and analyzed using the proposed method. A recovery of >90% was achieved using two sequential extractions. The total AnAc content ranged from 128.35 to 217.00 mg·100 g^-1 in peduncle samples obtained from five different cashew clones.

Mass calibrants for positive chemical ionization-high resolution mass spectrometry (CI-HRMS) for the identification of unknown compounds using accurate mass measurements

Gas Chromatography-Electron Ionization-Mass Spectrometry (GC-EI-MS) is still the most routinely performed method for metabolite profiling as compared to other hyphenated techniques. But when it comes to identification of unknown compounds, information on the molecular weight is not readily available because the molecular ion is not always found with electron ionization (EI). Thus, the use of chemical ionization (CI) is envisaged that commonly produces the molecular ion; in combination with accurate mass measurement, this technique would further allow for calculation of sum formulas of those compounds. However, for proper accuracy of analysis, a mass calibrant is needed. We set out to find a commercially available reference material with mass peaks that would qualify the substance as mass calibrant under CI conditions. Six commercially available mass calibrants, FC 43, PFK, Ultramark 1621, Ultramark 3200F, Triton X-100, and PEG 1000, were tested under CI conditions to understand their fragmentation behavior. Our findings indicate that Ultramark 1621 and PFK best fit the expectations of a mass calibrant for HRMS analysis whereby PFK provided a fragmentation pattern similar to EI outcomes thus enabling the use of mass reference tables commonly provided within commercial mass spectrometers. On the other hand, Ultramark 1621 is a mixture of fluorinated phosphazines that shows stable fragment intensities.

InSpectra - A platform for identifying emerging chemical threats

Non-target analysis (NTA) employing high-resolution mass spectrometry (HRMS) coupled with liquid chromatography is increasingly being used to identify chemicals of biological relevance. HRMS datasets are large and complex making the identification of potentially relevant chemicals extremely challenging. As they are recorded in vendor-specific formats, interpreting them is often reliant on vendor-specific software that may not accommodate advancements in data processing. Here we present InSpectra, a vendor independent automated platform for the systematic detection of newly identified emerging chemical threats. InSpectra is web-based, open-source/access and modular providing highly flexible and extensible NTA and suspect screening workflows. As a cloud-based platform, InSpectra exploits parallel computing and big data archiving capabilities with a focus for sharing and community curation of HRMS data. InSpectra offers a reproducible and transparent approach for the identification, tracking and prioritisation of emerging chemical threats.

Biogeographic patterns of biosynthetic potential and specialized metabolites in marine sediments

While the field of microbial biogeography has largely focused on the contributions of abiotic factors to community patterns, the potential influence of biotic interactions in structuring microbial communities, such as those mediated by the production of specialized metabolites, remains largely unknown. Here, we examined the relationship between microbial community structure and specialized metabolism at local spatial scales in marine sediment samples collected from the Long-Term Ecological Research (LTER) site in Moorea, French Polynesia. By employing a multi-omic approach to characterize the taxonomic, functional, and specialized metabolite composition within sediment communities, we find that biogeographic patterns were driven by local scale processes (e.g., biotic interactions) and largely independent of dispersal limitation. Specifically, we observed high variation in biosynthetic potential (based on Bray-Curtis dissimilarity) between samples, even within 1 m² plots, that reflected uncharacterized chemical space associated with site-specific metabolomes. Ultimately, connecting biosynthetic potential to community metabolomes facilitated the in situ detection of natural products and revealed new insights into the complex metabolic dynamics associated with sediment microbial communities. Our study demonstrates the potential to integrate biosynthetic genes and metabolite production into assessments of microbial community dynamics.

Bacterial transcriptional response to labile exometabolites from photosynthetic picoeukaryote Micromonas commoda

Dissolved primary production released into seawater by marine phytoplankton is a major source of carbon fueling heterotrophic bacterial production in the ocean. The composition of the organic compounds released by healthy phytoplankton is poorly known and difficult to assess with existing chemical methods. Here, expression of transporter and catabolic genes by three model marine bacteria (Ruegeria pomeroyi DSS-3, Stenotrophomonas sp. SKA14, and Polaribacter dokdonensis MED152) was used as a biological sensor of metabolites released from the picoeukaryote Micromonas commoda RCC299. Bacterial expression responses indicated that the three species together recognized 38 picoeukaryote metabolites. This was consistent with the Micromonas expression of genes for starch metabolism and synthesis of peptidoglycan-like intermediates. A comparison of the hypothesized Micromonas exometabolite pool with that of the diatom Thalassiosira pseudonana CCMP1335, analyzed previously with the same biological sensor method, indicated that both phytoplankton released organic acids, nucleosides, and amino acids, but differed in polysaccharide and organic nitrogen release. Future ocean conditions are expected to favor picoeukaryotic phytoplankton over larger-celled microphytoplankton. Results from this study suggest that such a shift could alter the substrate pool available to heterotrophic bacterioplankton.

Metabolomics and Genomics Enable the Discovery of a New Class of Nonribosomal Peptidic Metallophores from a Marine Micromonospora

Although microbial genomes harbor an abundance of biosynthetic gene clusters, there remain substantial technological gaps that impair the direct correlation of newly discovered gene clusters and their corresponding secondary metabolite products. As an example of one approach designed to minimize or bridge such gaps, we employed hierarchical clustering analysis and principal component analysis (hcapca, whose sole input is MS data) to prioritize 109 marine Micromonospora strains and ultimately identify novel strain WMMB482 as a candidate for in-depth "metabologenomics" analysis following its prioritization. Highlighting the power of current MS-based technologies, not only did hcapca enable the discovery of one new, nonribosomal peptide bearing an incredible diversity of unique functional groups, but metabolomics for WMMB482 unveiled 16 additional congeners via the application of Global Natural Product Social molecular networking (GNPS), herein named ecteinamines A-Q (1-17). The ecteinamines possess an unprecedented skeleton housing a host of uncommon functionalities including a menaquinone pathway-derived 2-naphthoate moiety, 4-methyloxazoline, the first example of a naturally occurring Ψ[CH2NH] "reduced amide", a methylsulfinyl moiety, and a d-cysteinyl residue that appears to derive from a unique noncanonical epimerase domain. Extensive in silico analysis of the ecteinamine (ect) biosynthetic gene cluster and stable isotope-feeding experiments helped illuminate the novel enzymology driving ecteinamine assembly as well the role of cluster collaborations or "duets" in producing such structurally complex agents. Finally, ecteinamines were found to bind nickel, cobalt, zinc, and copper, suggesting a possible biological role as broad-spectrum metallophores.

Advances in Mass Spectrometry-Metabolomics Based Approaches

Highly selective and sensitive analytical techniques are necessary for microbial metabolomics due to the complexity of the microbial sample matrix. Hence, mass spectrometry (MS) has been successfully applied in microbial metabolomics due to its high precision, versatility, sensitivity, and wide dynamic range. The different analytical tools using MS have been employed in microbial metabolomics investigations and can contribute to the discovery or accelerate the search for bioactive substances. The coupling with chromatographic and electrophoretic separation techniques has resulted in more efficient technologies for the analysis of microbial compounds occurring in trace levels. This book chapter describes the current advances in the application of mass spectrometry-based metabolomics in the search for new biologically active agents from microbial sources; the development of new approaches for in silico annotation of natural products; the different technologies employing mass spectrometry imaging to deliver more comprehensive analysis and elucidate the metabolome involved in ecological interactions as they enable visualization of the spatial dispersion of small molecules. We also describe other ambient ionization techniques applied to the fingerprint of microbial natural products and modern techniques such as ion mobility mass spectrometry used to microbial metabolomic analyses and the dereplication of natural microbial products through MS.

Artificial intelligence in microbial natural product drug discovery: current and emerging role

Covering: up to the end of 2022Microorganisms are exceptional sources of a wide array of unique natural products and play a significant role in drug discovery. During the golden era, several life-saving antibiotics and anticancer agents were isolated from microbes; moreover, they are still widely used. However, difficulties in the isolation methods and repeated discoveries of the same molecules have caused a setback in the past. Artificial intelligence (AI) has had a profound impact on various research fields, and its application allows the effective performance of data analyses and predictions. With the advances in omics, it is possible to obtain a wealth of information for the identification, isolation, and target prediction of secondary metabolites. In this review, we discuss drug discovery based on natural products from microorganisms with the help of AI and machine learning.

Structural diversity, biosynthesis, and health-promoting properties of brown algal meroditerpenoids

Marine algae that constitute hundreds of millions of tons of biomass are the oldest representatives of the plant kingdom. Recently, there has been growing interest in the utilization of algae as sustainable feedstocks for natural products with an economic value. Among these natural products are the meroditerpenoids, which are renowned for their protective effects against oxidative stress, inflammation, cancer, obesity, diabetes, and neurodegenerative disorders. Meroditerpenoids have a mixed biosynthetic origin and display a wide range of structural diversity. Their basic structure consists of a ring system bearing a diterpenoid side chain. Structural variations are observed in terms of the functional groups and saturation/cyclization of the diterpenoid side chain. This review classifies algal meroditerpenoids as plastoquinones, chromanols, chromenes, chromones, cyclic meroditerpenoids, nahocols, and isonahocols and examines their potential applications in functional foods and biopharmacology. Their lipid solubility, low molecular weight, and propensity to cross the blood-brain barrier places meroditerpenoids as potential drug candidates. There is growing interest in the study of algal meroterpenoids, and recent research has reported the structure of several new meroterpenoids and their biological activities. Further research is needed to extend the use of algal meroditerpenoids in preclinical trials. Understanding the mechanism of their biosynthesis will allow the development of de novo biosynthesis and biomimetic synthesis strategies for the industrial-scale production of meroditerpenoids and their synthetic derivatives to aid pharmaceutical research. This review is the first to summarize up-to-date information on all brown algae-derived meroditerpenoids.

Strategy of combining offline 2D LC-MS with LC-DIA-MS/MS to accurately identify chemical compounds and for quality control of Dioscorea septemloba Thunb

INTRODUCTION

Dioscorea septemloba Thunb. (DST), the rhizome of Dioscorea spongiosa J. Q. Xi, M. Mizuno et W. L. Zhao or Fuzhou Dioscorea futschauensis Uline ex R. Kunth, has multiple biological activities.

OBJECTIVES

We aimed to comprehensively characterize the chemical composition of DST and develop a quality control method.

METHODS

Based on a UHPLC/Q-Orbitrap-MS platform, we developed an offline 2D LC-MS method (HILIC×RPLC) to characterize the chemical constituents in the 75% ethanol extract of DST at first. Secondly, a data-independent acquisition mode (DIA) was further established to conduct rapid qualitative analysis of compounds in DST from different habitats. Then, six differential compounds were screened out and selected as quantitative markers by UPLC-QQQ-MS to evaluate the content of DST from different habitats.

RESULTS

In total, 137 compounds were identified in DST by combining offline 2D LC-MS with LC-DIA-MS/MS. Then, simultaneous targeted/non-targeted scanning technology was established based on the precursor ion list. Finally, six compounds, including dioscin, gracillin, pseduoprotodioscin, pseudoprotogracillin, protodioscin, and protogracillin, were accurately determined. The method validation showed a good linear relationship in the concentration range investigated (R² > 0.999). The average recovery ranged from 86% to 107.5%, and LOD and LOQ were between 0.01 and 0.40 μg·mL^-1 .

CONCLUSION

Our strategy integrating offline 2D LC-MS and the DIA mode could effectively separate and identify compounds from DST, indicating it can be used in subsequent compounds characterization studies. At the same time, the quality of DST was comprehensively and systematically evaluated.

Molecular networking-guided strategy for the pharmacokinetic study of herbal medicines: Cudrania tricuspidata leaf extracts

In this study, the pharmacokinetic profiles of the bioactive components in the leaf extract of the medicinal herb, Cudrania tricuspidate, were investigated using an MS/MS-based molecular networking system. To identify the major active components of the C. tricuspidate leaf extract (CLE), HPLC-DAD analysis was conducted with a standard mixture of six flavonoids (rutin, isoquercitrin, nicotiflorin, kaempferol 3-O-glucoside, quercetin, and kaempferol). The unknown peaks were determined via molecular networking analysis using the mass dataset obtained by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). For the subsequent pharmacokinetic study, CLE (1 g/kg) was orally administered to rats, and plasma samples were collected. The product ion mass data of plasma samples using LC-QTOF/MS were obtained and subjected to molecular networking analysis. The resulting molecular networking map indicated that the glucuronide metabolites of quercetin and kaempferol were the major circulating species. Accordingly, quercetin and kaempferol were determined following β-glucuronidase treatment, and their pharmacokinetic parameters were calculated. These findings indicate that the proposed molecular network-based approaches are potential and efficient methods for the pharmacokinetic study of herbal medicines.

Microbial metabolites in the marine carbon cycle

One-quarter of photosynthesis-derived carbon on Earth rapidly cycles through a set of short-lived seawater metabolites that are generated from the activities of marine phytoplankton, bacteria, grazers and viruses. Here we discuss the sources of microbial metabolites in the surface ocean, their roles in ecology and biogeochemistry, and approaches that can be used to analyse them from chemistry, biology, modelling and data science. Although microbial-derived metabolites account for only a minor fraction of the total reservoir of marine dissolved organic carbon, their flux and fate underpins the central role of the ocean in sustaining life on Earth.

Growth-stage-related shifts in diatom endometabolome composition set the stage for bacterial heterotrophy

Phytoplankton-derived metabolites fuel a large fraction of heterotrophic bacterial production in the global ocean, yet methodological challenges have limited our understanding of the organic molecules transferred between these microbial groups. In an experimental bloom study consisting of three heterotrophic marine bacteria growing together with the diatom Thalassiosira pseudonana, we concurrently measured diatom endometabolites (i.e., potential exometabolite supply) by nuclear magnetic resonance (NMR) spectroscopy and bacterial gene expression (i.e., potential exometabolite uptake) by metatranscriptomic sequencing. Twenty-two diatom endometabolites were annotated, with nine increasing in internal concentration in the late stage of the bloom, eight decreasing, and five showing no variation through the bloom progression. Some metabolite changes could be linked to shifts in diatom gene expression, as well as to shifts in bacterial community composition and their expression of substrate uptake and catabolism genes. Yet an overall low match indicated that endometabolome concentration was not a good predictor of exometabolite availability, and that complex physiological and ecological interactions underlie metabolite exchange. Six diatom endometabolites accumulated to higher concentrations in the bacterial co-cultures compared to axenic cultures, suggesting a bacterial influence on rates of synthesis or release of glutamate, arginine, leucine, 2,3-dihydroxypropane-1-sulfonate, glucose, and glycerol-3-phosphate. Better understanding of phytoplankton metabolite production, release, and transfer to assembled bacterial communities is key to untangling this nearly invisible yet pivotal step in ocean carbon cycling.

Automated Microbial Library Generation Using the Bioinformatics Platform IDBac

Libraries of microorganisms have served as a cornerstone of therapeutic drug discovery, though the continued re-isolation of known natural product chemical entities has remained a significant obstacle to discovery efforts. A major contributing factor to this redundancy is the duplication of bacterial taxa in a library, which can be mitigated through the use of a variety of DNA sequencing strategies and/or mass spectrometry-informed bioinformatics platforms so that the library is created with minimal phylogenetic, and thus minimal natural product overlap. IDBac is a MALDI-TOF mass spectrometry-based bioinformatics platform used to assess overlap within collections of environmental bacterial isolates. It allows environmental isolate redundancy to be reduced while considering both phylogeny and natural product production. However, manually selecting isolates for addition to a library during this process was time intensive and left to the researcher's discretion. Here, we developed an algorithm that automates the prioritization of hundreds to thousands of environmental microorganisms in IDBac. The algorithm performs iterative reduction of natural product mass feature overlap within groups of isolates that share high homology of protein mass features. Employing this automation serves to minimize human bias and greatly increase efficiency in the microbial strain prioritization process.

In vitro α-glucosidase inhibition by Brazilian medicinal plant extracts characterised by ultra-high performance liquid chromatography coupled to mass spectrometry

Aiming at finding natural sources of antidiabetics agents, 15 extracts from Brazilian medicinal plants of the Atlantic Forest and Amazon region were tested against α-glucosidase enzyme. Plants were selected based on the taxonomic relationships with genera including several species with antidiabetic activity. In this screening, the extracts obtained from the flowers of Hyptis monticola and the leaves of Lantana trifolia and Lippia origanoides resulted endowed with promising anti-α-glucosidase activity. The extracts from H. monticola and from L. origanoides collected in two different areas, were characterised by ultra-high performance liquid chromatography coupled to mass spectrometry. Bioassay-guided fractionation led to the identification of several enzyme inhibiting compounds, among them the mechanism of action of naringenin and pinocembrin was investigated. The two L. origanoides extracts showed differences in bioactivity and in the phytochemical profiles. The fractionation of the extract from H. monticola led to a partial loss of the inhibitory effect.

Future Directions for the Discovery of Natural Product-Derived Immunomodulating Drugs

Drug discovery from natural sources is going through a renaissance, having spent many decades in the shadow of synthetic molecule drug discovery, despite the fact that natural product-derived compounds occupy a much greater chemical space than those created through synthetic chemistry methods. With this new era comes new possibilities, not least the novel targets that have emerged in recent times and the development of state-of-the-art technologies that can be applied to drug discovery from natural sources. Although progress has been made with some immunomodulating drugs, there remains a pressing need for new agents that can be used to treat the wide variety of conditions that arise from disruption, or over-activation, of the immune system; natural products may therefore be key in filling this gap. Recognising that, at present, there is no authoritative article that details the current state-of-the-art of the immunomodulatory activity of natural products, this in-depth review has arisen from a joint effort between the International Union of Basic and Clinical Pharmacology (IUPHAR) Natural Products and Immunopharmacology, with contributions from a Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation number of world-leading researchers in the field of natural product drug discovery, to provide a "position statement" on what natural products has to offer in the search for new immunomodulatory argents. To this end, we provide a historical look at previous discoveries of naturally occurring immunomodulators, present a picture of the current status of the field and provide insight into the future opportunities and challenges for the discovery of new drugs to treat immune-related diseases.

Renewed interests in the discovery of bioactive actinomycete metabolites driven by emerging technologies

Actinomycetes are prolific sources of bioactive molecules. Traditional workflows including bacterial isolation, fermentation, metabolite identification and structure elucidation have resulted in high rates of natural product rediscovery in recent years. Recent advancements in multi-omics techniques have uncovered cryptic gene clusters within the genomes of actinomycetes, potentially introducing vast resources for the investigation of bioactive molecules. While developments in culture techniques have allowed for the fermentation of difficult-to-culture actinomycetes, high-throughput metabolite screening has offered plenary tools to accelerate hits discovery. A variety of new bioactive molecules have been isolated from actinomycetes of unique environmental origins, such as endophytic and symbiotic actinomycetes. Synthetic biology and genome mining have also emerged as new frontiers for the discovery of bioactive molecules. This review covers the highlights of recent developments in actinomycete-derived natural product drug discovery.

Accurate Identification of Bioactive Meliaceae Limonoids by UHPLC-MS/MS Based Structure-Fragment Relationships (SFRs)

Limonoids are bioactive plant specialized metabolites found in the Meliaceae family. The basic limonoids, i.e., azadiradione, epoxyazadiradione, and gedunin have been exploited for various bioactivities and therefore are the potential drug leads for tomorrow. However, their low abundance, structural similarity, and lack of adequate mass fragmentation data have hampered their accurate identification and quantification from various sources. In the present study, basic limonoids such as azadirone, azadiradione, epoxyazadiradione, and gedunin isolated from Neem were utilized for the synthesis of their derivatives and isotopologs. A total of 30 one compounds were used in this study among which five were isolated, two were biotransformed, and 24 were synthesized. Among the synthesized compounds nine are novel compounds including six deuterated analogs/isotopologs which are (1,3-²H)-1,2-dihydro-3β-hydroxyazadiradione (9), (1,3,16-²H)-1,2-dihydro-3β-16β-dihydroxyazadiradione (10), 3β-hydroxyazadiradione (11), 3β-16β-dihydroxyazadiradione (12), (3-²H)-3β-hydroxyazadiradione (13), (3,16-²H)-3β-16β-dihydroxyazadiradione (14), (1,3,7-²H)-1,2-dihydro-3β-hydroxy-7-deacetylazadiradione (15), 1,2,20,21,22,23-hexahydroazadiradione (17), and (1,3-²H)-1,2-dihydro-3β-hydroxygedunin (29). These limonoids along with their semisynthesized derivatives were subjected to ultra high performance liquid chromatography mass spectrometry (UHPLC-MS/MS) and the fragmentation pathway was established based on structure-fragment relationships (SFRs), utilizing high resolution MS/MS data. We have developed a most reliable and easily reproducible protocol describing in depth analysis of SFRs based on the structural modifications and synthesis of isotopologs. Also, the MS/MS fragment library of these basic limonoids generated in this study acts as a fingerprint for accurate identification and quantification of limonoids by MS/MS analysis in various plant tissue extracts, phytopharmaceutical formulations and biological samples.

Meeting report of the fourth annual Tri-Service Microbiome Consortium symposium

The Tri-Service Microbiome Consortium (TSMC) was founded to enhance collaboration, coordination, and communication of microbiome research among U.S. Department of Defense (DoD) organizations. The annual TSMC symposium is designed to enable information sharing between DoD scientists and leaders in the field of microbiome science, thereby keeping DoD consortium members informed of the latest advances within the microbiome community and facilitating the development of new collaborative research opportunities. The 2020 annual symposium was held virtually on 24-25 September 2020. Presentations and discussions centered on microbiome-related topics within four broad thematic areas: (1) Enabling Technologies; (2) Microbiome for Health and Performance; (3) Environmental Microbiome; and (4) Microbiome Analysis and Discovery. This report summarizes the presentations and outcomes of the 4th annual TSMC symposium.

Alternaria Mycotoxins: An Overview of Toxicity, Metabolism, and Analysis in Food

The genus Alternaria is widely distributed in the environment. Numerous species of the genus Alternaria can produce a variety of toxic secondary metabolites, called Alternaria mycotoxins. In this review, natural occurrence, toxicity, metabolism, and analytical methods are introduced. The contamination of these toxins in foodstuffs is ubiquitous, and most of these metabolites present genotoxic and cytotoxic effects. Moreover, Alternaria toxins are mainly hydroxylated to catechol metabolites and combined with sulfate and glucuronic acid in in vitro arrays. A more detailed summary of the metabolism of Alternaria toxins is presented in this work. To effectively detect and determine the mycotoxins in food, analytical methods with high sensitivity and good accuracy are also reviewed. This review will guide the formulation of maximum residue limit standards in the future, covering both toxicity and metabolic mechanism of Alternaria toxins.

Soybean Metabolomics Based in Mass Spectrometry: Decoding the Plant's Signaling and Defense Responses under Biotic Stress

Metabolomics is an omics technology that is extremely valuable to analyze all small-molecule metabolites in organisms. Recent advances in analytical instrumentation, such as mass spectrometry combined with data processing tools, chemometrics, and spectral data libraries, allow plant metabolomics studies to play a fundamental role in the agriculture field and food security. Few studies are found in the literature using the metabolomics approach in soybean plants on biotic stress. In this review, we provide a new perspective highlighting the potential of metabolomics-based mass spectrometry for soybean in response to biotic stress. Furthermore, we highlight the response and adaptation mechanisms of soybean on biotic stress about primary and secondary metabolism. Consequently, we provide subsidies for further studies of the resistance and improvement of the crop.

Structural Analysis of Diastereomeric Cardiac Glycosides and Their Genins Using Ultraperformance Liquid Chromatography-Tandem Mass Spectrometry

Ultraperformance liquid chromatography coupled with electrospray ionization tandem mass spectrometry (UPLC-ESI-MS/MS) is an economical and indispensable tool in natural product research to investigate novel metabolites, biomarker discovery, chemical diversity exploration, and structure elucidation. In this study, the structural analysis of 38 naturally occurring cardiac glycosides (CGs) in various tissues of Nerium oleander was achieved by the extensive use of mass spectrometry. The chemical diversity of CGs was described on the basis of characteristic MS/MS fragmentation patterns, accurate mass measurement, and published scientific information on CGs from Nerium oleander. It was observed that only six genins, viz., Δ¹⁶anhydrogitoxigenin, Δ¹⁶adynerigenin, gitoxigenin, oleandrigenin, digitoxigenin, and adynerigenine, produce 38 diverse chemical structures of CGs. Among them, 20 were identified as diastereomers having a difference in a sugar (l-oleandrose, β-d-diginose, and β-d-sarmentose) unit. However, the differentiation of diastereomeric CGs was not possible by only MS/MS fragments. Thus, the diastereomer's chromatographic elution order was assigned on the basis of the relative retention time (RRt) of two reference standards (odoroside A and oleandrin) among their diastereomers. Besides this, the in-source fragmentation of CGs and the MS/MS of m/z 325 and 323 disaccharide daughter ions also exposed the intrinsic structure information on the sugar units. The daughter ions m/z 162, 145, 113, 95, and 85 in MS/MS spectra indicated the abundance of l-oleandrose, β-d-diginose, and β-d-sarmentose sugars. At the same time, m/z 161, 143, 129, and 87 product ions confirmed the presence of a β-d-digitalose unit. As a result, the UPLC-ESI/TQD system was successfully utilized for the structure characterization of CGs in Nerium oleander tissues.

Synergizing the potential of bacterial genomics and metabolomics to find novel antibiotics

Antibiotic development based on natural products has faced a long lasting decline since the 1970s, while both the speed and the extent of antimicrobial resistance (AMR) development have been severely underestimated. The discovery of antimicrobial natural products of bacterial and fungal origin featuring new chemistry and previously unknown mode of actions is increasingly challenged by rediscovery issues. Natural products that are abundantly produced by the corresponding wild type organisms often featuring strong UV signals have been extensively characterized, especially the ones produced by extensively screened microbial genera such as streptomycetes. Purely synthetic chemistry approaches aiming to replace the declining supply from natural products as starting materials to develop novel antibiotics largely failed to provide significant numbers of antibiotic drug leads. To cope with this fundamental issue, microbial natural products science is being transformed from a 'grind-and-find' study to an integrated approach based on bacterial genomics and metabolomics. Novel technologies in instrumental analytics are increasingly employed to lower detection limits and expand the space of detectable substance classes, while broadening the scope of accessible and potentially bioactive natural products. Furthermore, the almost exponential increase in publicly available bacterial genome data has shown that the biosynthetic potential of the investigated strains by far exceeds the amount of detected metabolites. This can be judged by the discrepancy between the number of biosynthetic gene clusters (BGC) encoded in the genome of each microbial strain and the number of secondary metabolites actually detected, even when considering the increased sensitivity provided by novel analytical instrumentation. In silico annotation tools for biosynthetic gene cluster classification and analysis allow fast prioritization in BGC-to-compound workflows, which is highly important to be able to process the enormous underlying data volumes. BGC prioritization is currently accompanied by novel molecular biology-based approaches to access the so-called orphan BGCs not yet correlated with a secondary metabolite. Integration of metabolomics, in silico genomics and molecular biology approaches into the mainstream of natural product research will critically influence future success and impact the natural product field in pharmaceutical, nutritional and agrochemical applications and especially in anti-infective research.

Identification of Bioactive Compounds from Marine Natural Products and Exploration of Structure-Activity Relationships (SAR)

Marine natural products (MNPs) have been an important and rich source for antimicrobial drug discovery and an effective alternative to control drug resistant infections. Herein, we report bioassay guided fractionation of marine extracts from sponges Lendenfeldia, Ircinia and Dysidea that led us to identify novel compounds with antimicrobial properties. Tertiary amines or quaternary amine salts: aniline 1, benzylamine 2, tertiary amine 3 and 4, and quaternary amine salt 5, along with three known compounds (6-8) were isolated from a crude extract and MeOH eluent marine extracts. The antibiotic activities of the compounds, and their isolation as natural products have not been reported before. Using tandem mass spectrometry (MS) analysis, potential structures of the bioactive fractions were assigned, leading to the hit validation of potential compounds through synthesis, and commercially available compounds. This method is a novel strategy to overcome insufficient quantities of pure material (NPs) for drug discovery and development which is a big challenge for pharmaceutical companies. The antibacterial screening of the marine extracts has shown several of the compounds exhibited potent in-vitro antibacterial activity, especially against methicillin-resistant Staphylococcus aureus (MRSA) with minimum inhibitory concentration (MIC) values between 15.6 to 62.5 microg mL-1. Herein, we also report structure activity relationships of a diverse range of commercial structurally similar compounds. The structure-activity relationships (SAR) results demonstrate that modification of the amines through linear chain length, and inclusion of aromatic rings, modifies the observed antimicrobial activity. Several commercially available compounds, which are structurally related to the discovered molecules, showed broad-spectrum antimicrobial activity against different test pathogens with a MIC range of 50 to 0.01 µM. The results of cross-referencing antimicrobial activity and cytotoxicity establish that these compounds are promising potential molecules, with a favourable therapeutic index for antimicrobial drug development. Additionally, the SAR studies show that simplified analogues of the isolated compounds have increased bioactivity.

MicroED in natural product and small molecule research

Covering: 2013 to 2020The electron cryo-microscopy (cryo-EM) method Microcrystal Electron Diffraction (MicroED) allows the collection of high-resolution structural data from vanishingly small crystals that appear like amorphous powders or very fine needles. Since its debut in 2013, data collection and analysis schemes have been fine-tuned, and there are currently close to 100 structures determined by MicroED. Although originally developed to study proteins, MicroED is also very powerful for smaller systems, with some recent and very promising examples from the field of natural products. Herein, we review what has been achieved so far and provide examples of natural product structures, as well as demonstrate the expected future impact of MicroED to the field of natural product and small molecule research.

Bacterial pathogens: threat or treat (a review on bioactive natural products from bacterial pathogens)

Covering: up to the second quarter of 2020 Threat or treat? While pathogenic bacteria pose significant threats, they also represent a huge reservoir of potential pharmaceuticals to treat various diseases. The alarming antimicrobial resistance crisis and the dwindling clinical pipeline urgently call for the discovery and development of new antibiotics. Pathogenic bacteria have an enormous potential for natural products drug discovery, yet they remained untapped and understudied. Herein, we review the specialised metabolites isolated from entomopathogenic, phytopathogenic, and human pathogenic bacteria with antibacterial and antifungal activities, highlighting those currently in pre-clinical trials or with potential for drug development. Selected unusual biosynthetic pathways, the key roles they play (where known) in various ecological niches are described. We also provide an overview of the mode of action (molecular target), activity, and minimum inhibitory concentration (MIC) towards bacteria and fungi. The exploitation of pathogenic bacteria as a rich source of antimicrobials, combined with the recent advances in genomics and natural products research methodology, could pave the way for a new golden age of antibiotic discovery. This review should serve as a compendium to communities of medicinal chemists, organic chemists, natural product chemists, biochemists, clinical researchers, and many others interested in the subject.

Diagnostic fragmentation-assisted mass spectral networking coupled with in silico dereplication for deep annotation of steroidal alkaloids in medicinal Fritillariae Bulbus

Fully understanding the chemicals in an herbal medicine remains a challenging task. Molecular networking (MN) allows to organize tandem mass spectrometry (MS/MS) data in complex samples by mass spectral similarity, which yet suffers from low coverage and accuracy of compound annotation due to the size limitation of available databases and differentiation obstacle of similar chemical scaffolds. In this work, an enhanced MN-based strategy named diagnostic fragmentation-assisted molecular networking coupled with in silico dereplication (DFMN-ISD) was introduced to overcome these obstacles: the rule-based fragmentation patterns provide insights into similar chemical scaffolds, the generated in silico candidates based on metabolic reactions expand the available natural product databases, and the in silico annotation method facilitates the further dereplication of candidates by computing their fragmentation trees. As a case, this approach was applied to globally profile the steroidal alkaloids in Fritillariae bulbus, a commonly used antitussive and expectorant herbal medicine. Consequently, a total of 325 steroidal alkaloids were discovered, including 106 cis-D/E-cevanines, 142 trans-D/E-cevanines, 29 jervines, 23 veratramines, and 25 verazines. And 10 of them were confirmed by available reference standards. Approximately 70% of the putative steroidal alkaloids have never been reported in previous publications, demonstrating the benefit of DFMN-ISD approach for the comprehensive characterization of chemicals in a complex plant organism.

Genome mining strategies for ribosomally synthesised and post-translationally modified peptides

Genome mining is a computational method for the automatic detection and annotation of biosynthetic gene clusters (BGCs) from genomic data. This approach has been increasingly utilised in natural product (NP) discovery due to the large amount of sequencing data that is now available. Ribosomally synthesised and post-translationally modified peptides (RiPPs) are a class of structurally complex NP with diverse bioactivities. RiPPs have recently been shown to occupy a much larger expanse of genomic and chemical space than previously appreciated, indicating that annotation of RiPP BGCs in genomes may have been overlooked in the past. This review provides an overview of the genome mining tools that have been specifically developed to aid in the discovery of RiPP BGCs, which have been built from an increasing knowledgebase of RiPP structures and biosynthesis. Given these recent advances, the application of targeted genome mining has great potential to accelerate the discovery of important molecules such as antimicrobial and anticancer agents whilst increasing our understanding about how these compounds are biosynthesised in nature.

Linking biosynthetic and chemical space to accelerate microbial secondary metabolite discovery

Secondary metabolites can be viewed as a chemical language, facilitating communication between microorganisms. From an ecological point of view, this metabolite exchange is in constant flux due to evolutionary and environmental pressures. From a biomedical perspective, the chemistry is unsurpassed for its antibiotic properties. Genome sequencing of microorganisms has revealed a large reservoir of Biosynthetic Gene Clusters (BGCs); however, linking these to the secondary metabolites they encode is currently a major bottleneck to chemical discovery. This linking of genes to metabolites with experimental validation will aid the elicitation of silent or cryptic (not expressed under normal laboratory conditions) BGCs. As a result, this will accelerate chemical dereplication, our understanding of gene transcription and provide a comprehensive resource for synthetic biology. This will ultimately provide an improved understanding of both the biosynthetic and chemical space. In recent years, integrating these complex metabolomic and genomic data sets has been achieved using a spectrum of manual and automated approaches. In this review, we cover examples of these approaches, while addressing current challenges and future directions in linking these data sets.

Bioactive Secondary Metabolites from Trichoderma spp. against Phytopathogenic Fungi

Phytopathogenic fungi, causing significant economic and production losses, are becoming a serious threat to global food security. Due to an increase in fungal resistance and the hazardous effects of chemical fungicides to human and environmental health, scientists are now engaged to explore alternate non-chemical and ecofriendly management strategies. The use of biocontrol agents and their secondary metabolites (SMs) is one of the potential approaches used today. Trichoderma spp. are well known biocontrol agents used globally. Many Trichoderma species are the most prominent producers of SMs with antimicrobial activity against phytopathogenic fungi. Detailed information about these secondary metabolites, when grouped together, enhances the understanding of their efficient utilization and further exploration of new bioactive compounds for the management of plant pathogenic fungi. The current literature provides the information about SMs of Trichoderma spp. in a different context. In this review, we summarize and group different antifungal SMs of Trichoderma spp. against phytopathogenic fungi along with a comprehensive overview of some aspects related to their chemistry and biosynthesis. Moreover, a brief overview of the biosynthesis pathway, action mechanism, and different approaches for the analysis of SMs and the factors affecting the regulation of SMs in Trichoderma is also discussed.

Effect of pulsed light on postharvest disease control-related metabolomic variation in melon (Cucumis melo) artificially inoculated with Fusarium pallidoroseum

Pulsed light, as a postharvest technology, is an alternative to traditional fungicides, and can be used on a wide variety of fruit and vegetables for sanitization or pathogen control. In addition to these applications, other effects also are detected in vegetal cells, including changes in metabolism and secondary metabolite production, which directly affect disease control response mechanisms. This study aimed to evaluate pulsed ultraviolet light in controlling postharvest rot, caused by Fusarium pallidoroseum in 'Spanish' melon, in natura, and its implications in disease control as a function of metabolomic variation to fungicidal or fungistatic effects. The dose of pulsed light (PL) that inhibited F. pallidoroseum growth in melons (Cucumis melo var. Spanish) was 9 KJ m-2. Ultra-performance liquid chromatography (UPLC) coupled to a quadrupole-time-of-flight (QTOF) mass analyzer identified 12 compounds based on tandem mass spectrometry (MS/MS) fragmentation patterns. Chemometric analysis by Principal Components Analysis (PCA) and Orthogonal Partial Least Squared Discriminant Analysis (OPLS-DA) and corresponding S-Plot were used to evaluate the changes in fruit metabolism. PL technology provided protection against postharvest disease in melons, directly inhibiting the growth of F. pallidoroseum through the upregulation of specific fruit biomarkers such as pipecolic acid (11), saponarin (7), and orientin (3), which acted as major markers for the defense system against pathogens. PL can thus be proposed as a postharvest technology to prevent chemical fungicides and may be applied to reduce the decay of melon quality during its export and storage.

Genome mining as a biotechnological tool for the discovery of novel marine natural products

Compared to terrestrial environments, the oceans harbor a variety of environments, creating higher biodiversity, which gives marine natural products a high occurrence of significant biology and novel chemistry. However, traditional bioassay-guided isolation and purification strategies are severely limiting the discovery of additional novel natural products from the ocean. With an increasing number of marine microorganisms being sequenced, genome mining is gradually becoming a powerful tool to retrieve novel marine natural products. In this review, we have summarized genome mining approaches used to analyze key enzymes of biosynthetic pathways and predict the chemical structure of new gene clusters by introducing successful stories that used genome mining strategy to identify new marine-derived compounds. Furthermore, we also put forward challenges for genome mining techniques and their proposed solutions. The detailed analysis of the genome mining strategy will help researchers to understand this novel technique and its application. With the development of a genome sequence, genome mining strategies will be applied more widely, which will drive rapid development in the field of marine natural product development.

Targeted Isolation of Lignans from Trachelospermum asiaticum Using Molecular Networking and Hierarchical Clustering Analysis

High-resolution-mass-spectrometry (HR-MS) methods rapidly provide extensive structural information for the isolation of metabolites in natural products. However, they may occasionally provide more information than required and interfere with the targeted analysis of natural products. In this study, we aimed to selectively isolate lignans from Trachelospermum asiaticum by applying the Global Natural Product Social Molecular Networking (GNPS) platform and hierarchical clustering analysis (HCA). T. asiaticum, which contains lignans, triterpenoids and flavonoids that possess various biological activities, was analyzed in a data-dependent acquisition (DDA) analysis mode using HR-MS. The preprocessed MS spectra were applied not only to GNPS for molecular networking but also to HCA based on similarity patterns between two nodes. The combination of these two methods reliably helped in the targeted isolation of lignan-type metabolites, which are expected to possess potent anti-cancer or anti-inflammatory activities.

LC-MS/MS based molecular networking approach for the identification of cocoa phenolic metabolites in human urine

Dietary phenolic compounds are often transformed by gut microbiota prior to absorption. This transformation may modify their structures, producing novel gut flora metabolites associated with numerous health benefits. Traditional mass spectrometry (MS) based approaches for assessing dietary exposure of cocotea (cocoa, coffee and tea) products provided very little information about the modification and fate of dietary phenolics after ingestion, mainly due to limitation of complex sample nature and their data analyses. Mass spectrometry techniques are well-suited to a high-throughput characterization of natural products, however, analyzing MS based data of complex biological matrix is still considered a challenge. In order to overcome such limitations and simplify the analysis of complex MS data, a cocotea based human trial was conducted where MS based molecular networking approach was implemented. To demonstrate the utility of this approach in one of the specific cocotea diets, we have applied it to a diverse collection of human (n = 15) urine samples, who consumed cocoa rich in polyphenols over a 48-h period. This approach illustrated the power of the new strategy, allowing the rapid identification of new analogues of cocoa metabolites after human consumption. Analysis of human urine samples after cocoa consumption revealed (by assignment of unknown metabolites based on the network similarities) that monomeric flavanols are mainly absorbed and transformed directly into their glucuronide and sulfated moieties. Subsequently, the hydroxy and methoxy phenyl-g-velerolactone as well as their smaller metabolites (such as hydroxyphenyl valeric acids, hydroxy and methoxy phenyl propionic acids and their derivates) are indicative of bacterial metabolism of cocoa major flavanols. For the first time, our study exemplifies and highlight the implementation of MS based molecular networking approach in illustrating the tracking of various structural motifs of ingested cocoa phenolics in human based study.

Identification of Secondary Metabolites from Aspergillus pachycristatus by Untargeted UPLC-ESI-HRMS/MS and Genome Mining

Aspergillus pachycristatus is an industrially important fungus for the production of the antifungal echinocandin B and is closely related to model organism A. nidulans. Its secondary metabolism is largely unknown except for the production of echinocandin B and sterigmatocystin. We constructed mutants for three genes that regulate secondary metabolism in A. pachycristatus NRRL 11440, and evaluated the secondary metabolites produced by wild type and mutants strains. The secondary metabolism was explored by metabolic networking of UPLC-HRMS/MS data. The genes and metabolites of A. pachycristatus were compared to those of A.nidulans FGSC A4 as a reference to identify compounds and link them to their encoding genes. Major differences in chromatographic profiles were observable among the mutants. At least 28 molecules were identified in crude extracts that corresponded to nine characterized gene clusters. Moreover, metabolic networking revealed the presence of a yet unexplored array of secondary metabolites, including several undescribed fellutamides derivatives. Comparative reference to its sister species, A. nidulans, was an efficient way to dereplicate known compounds, whereas metabolic networking provided information that allowed prioritization of unknown compounds for further metabolic exploration. The mutation of global regulator genes proved to be a useful tool for expanding the expression of metabolic diversity in A. pachycristatus.