Prioritizing Natural Product Diversity in a Collection of 146 Bacterial Strains Based on Growth and Extraction Protocols

Accessing the specialized metabolome of actinobacteria from the bulk soil of Paullinia cupana Mart. on the Brazilian Amazon: a promising source of bioactive compounds against soybean phytopathogens

The Amazon rainforest, an incredibly biodiverse ecosystem, has been increasingly vulnerable to deforestation. Despite its undeniable importance and potential, the Amazonian microbiome has historically received limited study, particularly in relation to its unique arsenal of specialized metabolites. Therefore, in this study our aim was to assess the metabolic diversity and the antifungal activity of actinobacterial strains isolated from the bulk soil of Paullinia cupana, a native crop, in the Brazilian Amazon Rainforest. Extracts from 24 strains were subjected to UPLC-MS/MS analysis using an integrative approach that relied on the Chemical Structural and Compositional Similarity (CSCS) metric, GNPS molecular networking, and in silico dereplication tools. This procedure allowed the comprehensive understanding of the chemical space encompassed by these actinobacteria, which consists of features belonging to known bioactive metabolite classes and several unannotated molecular families. Among the evaluated strains, five isolates exhibited bioactivity against a panel of soybean fungal phytopathogens (Rhizoctonia solani, Macrophomina phaseolina, and Sclerotinia sclerotiorum). A focused inspection led to the annotation of pepstatins, oligomycins, hydroxamate siderophores and dorrigocins as metabolites produced by these bioactive strains, with potentially unknown compounds also comprising their metabolomes. This study introduces a pragmatic protocol grounded in established and readily available tools for the annotation of metabolites and the prioritization of strains to optimize further isolation of specialized metabolites. Conclusively, we demonstrate the relevance of the Amazonian actinobacteria as sources for bioactive metabolites useful for agriculture. We also emphasize the importance of preserving this biome and conducting more in-depth studies on its microbiota.

Rationally Minimizing Natural Product Libraries Using Mass Spectrometry

Natural product libraries are crucial to drug development, but large libraries drastically increase the time and cost during initial high throughput screens. Here, we developed a method that leverages liquid chromatography-tandem mass spectrometry spectral similarity to dramatically reduce library size, with minimal bioactive loss. This method offers a broadly applicable strategy for accelerated drug discovery with cost reductions, which enable implementation in resource-limited settings.

Metabolomics and Molecular Networking-Guided Screening of Bacillus-Derived Bioactive Compounds Against a Highly Lethal Vibrio Species

Microorganisms are important sources of bioactive natural products. However, the complexity of microbial metabolites and the low abundance of active compounds render the isolation and purification process laborious and inefficient. During our search for active substances capable of inhibiting the newly discovered highly lethal Vibrio strain vp-HL, we found that the fermentation broth of multiple Bacillus strains exhibited antibacterial activity. However, the substances responsible for the activity remained unclear. Metabolomics, molecular networking (MN), and the Structural similarity Network Annotation Platform for Mass Spectrometry (SNAP-MS) were employed in conjunction with bioactivity screening to predict the antibacterial compounds from Bacillus strains. The analysis of fractions, and their isolation, NMR-based annotation, and bioactivity evaluation of an amicoumacin compound partially confirmed the prediction from these statistical analyses. This work presents the potential of marine Bacillus in producing active substances against Vibrio species. Additionally, it highlighted the significance and feasibility of metabolomics and MN in the dereplication of compounds and the determination of isolation targets.

Dipeniroqueforins A-B and Peniroqueforin D: Eremophilane-Type Sesquiterpenoid Derivatives with Cytotoxic Activity from Penicillium roqueforti

Guided by the Global Natural Products Social (GNPS) molecular networking strategy, five undescribed eremophilane-type sesquiterpenoid derivatives (1-5) were isolated and identified from fungus Penicillium roqueforti, which was separated from the root soil of plant Hypericum beanii collected in Shennongjia Forestry District, Hubei Province. Dipeniroqueforins A-B (1-2), representing a lactam-type sesquiterpenoid skeleton with a highly symmetrical and homodimeric 5/6/6-6/6/5 hexacyclic system, are reported within the eremophilane-type family for the first time. Peniroqueforin D (5) represents the first example of a 1,2-seco eremophilane-type sesquiterpenoid derivative featuring an undescribed 7/6-fused ring system. The structures of these compounds were elucidated by various spectroscopic analyses, DP4+ probability analyses, ECD calculations, and single-crystal X-ray diffraction experiments. Furthermore, these isolates were evaluated for cytotoxicity, and the result uncovered that compound 1 displayed broad-spectrum activity. Further mechanistic study revealed that compound 1 could significantly upregulate the mRNA expression of genes related to the oxidative induction, leading to the abnormal ROS levels in tumor cells and ultimately causing tumor cell apoptosis.

OSMAC Method to Assess Impact of Culture Parameters on Metabolomic Diversity and Biological Activity of Marine-Derived Actinobacteria

Actinobacteria are known for their production of bioactive specialized metabolites, but they are still under-exploited. This study uses the "One Strain Many Compounds" (OSMAC) method to explore the potential of three preselected marine-derived actinobacteria: Salinispora arenicola (SH-78) and two Micromonospora sp. strains (SH-82 and SH-57). Various parameters, including the duration of the culture and the nature of the growth medium, were modified to assess their impact on the production of specialized metabolites. This approach involved a characterization based on chemical analysis completed with the construction of molecular networks and biological testing to evaluate cytotoxic and antiplasmodial activities. The results indicated that the influence of culture parameters depended on the studied species and also varied in relation with the microbial metabolites targeted. However, common favorable parameters could be observed for all strains such as an increase in the duration of the culture or the use of the A1 medium. For Micromonospora sp. SH-82, the solid A1 medium culture over 21 days favored a greater chemical diversity. A rise in the antiplasmodial activity was observed with this culture duration, with a IC50 twice as low as for the 14-day culture. Micromonospora sp. SH-57 produced more diverse natural products in liquid culture, with approximately 54% of nodes from the molecular network specifically linked to the type of culture support. Enhanced biological activities were also observed with specific sets of parameters. Finally, for Salinispora arenicola SH-78, liquid culture allowed a greater diversity of metabolites, but intensity variations were specifically observed for some metabolites under other conditions. Notably, compounds related to staurosporine were more abundant in solid culture. Consequently, in the range of the chosen parameters, optimal conditions to enhance metabolic diversity and biological activities in these three marine-derived actinobacteria were identified, paving the way for future isolation works.

Molecular Networking and Bioassay-Guided Preparation and Separation of Active Extract and Constituents from Vicia tenuifolia Roth

Molecular networking drove the selection of material from V. tenuifolia organs that targeted active flavonoid glycosides. To optimize the extraction process, the flowers of V. tenuifolia were used to produce an anti-inflammatory extract. The effects of variables-organic solvent ratio; extraction time; and temperature-were investigated by the response of anti-inflammatory activity. Bioactivities-guided experiments helped identify fractions with high total phenolic and flavonoid content as well as antioxidant potential. Furthermore, one new compound (1), 19 first isolated together, and two known compounds were obtained and identified from the active fraction of this plant. Among them, compounds (15 and 22) were first reported for nuclear magnetic resonance (NMR) data from this study. All the isolates were evaluated for their anti-inflammatory capacity throughout, modulating nitric oxide (NO), interleukin (IL)-1β, and IL-8 production. Active compounds were further investigated for their regulation and binding affinity to the inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) proteins by Western blot and in silico approaches, respectively. The findings of this study suggested that the developed extract method, active fraction, and pure components should be further investigated as promising candidates for treating inflammation and oxidation.

LC-MS/MS-Guided Molecular Networking for Targeted Discovery of Undescribed and Bioactive Ophiobolins from Bipolaris eleusines

An integrated purification procedure through the LC-MS/MS-based molecular networking strategy combined with bioactive evaluation was first ushered for discovering bioactive ophiobolins from Bipolaris eleusines. Ophiobolins were mainly dispersed in five clusters, which were classified based on different ring systems and functional groups. Nine undescribed ophiobolins (1-6 and 9-11) and an undescribed natural product (8) along with two known analogs (7 and 12) were isolated in target. The undescribed structures were characterized by HR-ESI-MS, NMR spectra, and X-ray diffraction experiments. Compounds 3-12 exhibited strong phytotoxic effects on green foxtails by producing visible lesions, and compounds 1-10 and 12 displayed different levels of cytotoxic activities against cancer cell lines B16, Hep G2, and MCF-7, from which the possible structure-activity relationships were then suggested. The results have supported that bioactivity-guided molecular networking is an efficient strategy to expedite the discovery of undescribed bioactive natural products.

Case Studies in Molecular Network-Guided Marine Biodiscovery

In reviewing a selection of recent case studies from our laboratory, we revealed some lessons learned and benefits accrued from the application of mass spectrometry (MS/MS) molecular networking in the field of marine sponge natural products. Molecular networking proved pivotal to our discovery of many new natural products and even new classes of natural product, some of which were opaque to alternate dereplication and prioritization strategies. Case studies included the discovery of: (i) trachycladindoles, an exceptionally rare class of bioactive indole alkaloid previously only known from a single southern Australia sample of Trachycladus laevispirulifer; (ii) dysidealactams, an unprecedented class of sesquiterpene glycinyl-lactam and glycinyl-imide from a Dysidea sp., a sponge genera often discounted as having been exhaustively studied; (iii) cacolides, an unprecedented family of sesterterpene α-methyl-γ-hydroxybutenolides from a Cacospongia sp., all too easily mischaracterized and deprioritized during dereplication as a well-known class of sponge sesterterpene tetronic acids; and (iv) thorectandrins, a new class of indole alkaloid which revealed unexpected insights into the chemical and biological properties of the aplysinopsins, one of the earliest and more extensively reported class of sponge natural products.

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.

Prioritization of Microorganisms Isolated from the Indian Ocean Sponge Scopalina hapalia Based on Metabolomic Diversity and Biological Activity for the Discovery of Natural Products

Despite considerable advances in medicine and technology, humanity still faces many deadly diseases such as cancer and malaria. In order to find appropriate treatments, the discovery of new bioactive substances is essential. Therefore, research is now turning to less frequently explored habitats with exceptional biodiversity such as the marine environment. Many studies have demonstrated the therapeutic potential of bioactive compounds from marine macro- and microorganisms. In this study, nine microbial strains isolated from an Indian Ocean sponge, Scopalina hapalia, were screened for their chemical potential. The isolates belong to different phyla, some of which are already known for their production of secondary metabolites, such as the actinobacteria. This article aims at describing the selection method used to identify the most promising microorganisms in the field of active metabolites production. The method is based on the combination of their biological and chemical screening, coupled with the use of bioinformatic tools. The dereplication of microbial extracts and the creation of a molecular network revealed the presence of known bioactive molecules such as staurosporin, erythromycin and chaetoglobosins. Molecular network exploration indicated the possible presence of novel compounds in clusters of interest. The biological activities targeted in the study were cytotoxicity against the HCT-116 and MDA-MB-231 cell lines and antiplasmodial activity against Plasmodium falciparum 3D7. Chaetomium globosum SH-123 and Salinispora arenicola SH-78 strains actually showed remarkable cytotoxic and antiplasmodial activities, while Micromonospora fluostatini SH-82 demonstrated promising antiplasmodial effects. The ranking of the microorganisms as a result of the different screening steps allowed the selection of a promising strain, Micromonospora fluostatini SH-82, as a premium candidate for the discovery of new drugs.

Temperature-dependent mycotoxins production investigation in Alternaria infected cherry by ultra-high performance liquid chromatography and Orbitrap high resolution mass spectrometry

For temperature-dependent Alternaria mycotoxins production analysis, cherry samples were inoculated with Alternaria sp. and incubated at two different temperatures (4 °C and 25 °C). Six Alternaria mycotoxins, including altenuene (ALT), alternariol monomethyl ether (AME), alternariol (AOH), altertoxin-I (ATX-I), tenuazonic acid (TeA), and tentoxin (TEN), in cherries were detected with integrated visible data-processing tools. Maximum concentration of these mycotoxins reached 71,862.2 μg/kg at 25 °C. Notably, considerable amount of TeA (290.4 μg/kg) was detected at 4 °C, which indicated that low temperature is not a safe storage condition for fruits. A total of 102 compounds were detected with a neutral loss of 162.0528 Da, and TeA-glucose was identified in this work. Based on MS/MS cosine similarity, products were verified and annotated with feature based molecular networking (FBMN) in global natural products social networking (GNPS). The results showed Alternaria mycotoxins in cherry samples were mainly demethylation, hydrogenation, and dehydration. This work revealed the production of Alternaria mycotoxins in cherries under different storage temperature, which will provide theoretical basis for the control of mycotoxin contamination in food commodities.

iPRESTO: Automated discovery of biosynthetic sub-clusters linked to specific natural product substructures

Microbial specialised metabolism is full of valuable natural products that are applied clinically, agriculturally, and industrially. The genes that encode their biosynthesis are often physically clustered on the genome in biosynthetic gene clusters (BGCs). Many BGCs consist of multiple groups of co-evolving genes called sub-clusters that are responsible for the biosynthesis of a specific chemical moiety in a natural product. Sub-clusters therefore provide an important link between the structures of a natural product and its BGC, which can be leveraged for predicting natural product structures from sequence, as well as for linking chemical structures and metabolomics-derived mass features to BGCs. While some initial computational methodologies have been devised for sub-cluster detection, current approaches are not scalable, have only been run on small and outdated datasets, or produce an impractically large number of possible sub-clusters to mine through. Here, we constructed a scalable method for unsupervised sub-cluster detection, called iPRESTO, based on topic modelling and statistical analysis of co-occurrence patterns of enzyme-coding protein families. iPRESTO was used to mine sub-clusters across 150,000 prokaryotic BGCs from antiSMASH-DB. After annotating a fraction of the resulting sub-cluster families, we could predict a substructure for 16% of the antiSMASH-DB BGCs. Additionally, our method was able to confirm 83% of the experimentally characterised sub-clusters in MIBiG reference BGCs. Based on iPRESTO-detected sub-clusters, we could correctly identify the BGCs for xenorhabdin and salbostatin biosynthesis (which had not yet been annotated in BGC databases), as well as propose a candidate BGC for akashin biosynthesis. Additionally, we show for a collection of 145 actinobacteria how substructures can aid in linking BGCs to molecules by correlating iPRESTO-detected sub-clusters to MS/MS-derived Mass2Motifs substructure patterns. This work paves the way for deeper functional and structural annotation of microbial BGCs by improved linking of orphan molecules to their cognate gene clusters, thus facilitating accelerated natural product discovery.

Enhanced correlation-based linking of biosynthetic gene clusters to their metabolic products through chemical class matching

BACKGROUND

It is well-known that the microbiome produces a myriad of specialised metabolites with diverse functions. To better characterise their structures and identify their producers in complex samples, integrative genome and metabolome mining is becoming increasingly popular. Metabologenomic co-occurrence-based correlation scoring methods facilitate the linking of metabolite mass fragmentation spectra (MS/MS) to their cognate biosynthetic gene clusters (BGCs) based on shared absence/presence patterns of metabolites and BGCs in paired omics datasets of multiple strains. Recently, these methods have been made more readily accessible through the NPLinker platform. However, co-occurrence-based approaches usually result in too many candidate links to manually validate. To address this issue, we introduce a generic feature-based correlation method that matches chemical compound classes between BGCs and MS/MS spectra.

RESULTS

To automatically reduce the long lists of potential BGC-MS/MS spectrum links, we match natural product (NP) ontologies previously independently developed for genomics and metabolomics and developed NPClassScore: an empirical class matching score that we also implemented in the NPLinker platform. By applying NPClassScore on three paired omics datasets totalling 189 bacterial strains, we show that the number of links is reduced by on average 63% as compared to using a co-occurrence-based strategy alone. We further demonstrate that 96% of experimentally validated links in these datasets are retained and prioritised when using NPClassScore.

CONCLUSION

The matching genome-metabolome class ontologies provide a starting point for selecting plausible candidates for BGCs and MS/MS spectra based on matching chemical compound class ontologies. NPClassScore expedites genome/metabolome data integration, as relevant BGC-metabolite links are prioritised, and researchers are faced with substantially fewer proposed BGC-MS/MS links to manually inspect. We anticipate that our addition to the NPLinker platform will aid integrative omics mining workflows in discovering novel NPs and understanding complex metabolic interactions in the microbiome. Video Abstract.

Microbial Metabolites Annotation by Mass Spectrometry-Based Metabolomics

Since the discovery of penicillin, microbial metabolites have been extensively investigated for drug discovery purposes. In the last decades, microbial derived compounds have gained increasing attention in different fields from pharmacognosy to industry and agriculture. Microbial metabolites in microbiomes present specific functions and can be associated with the maintenance of the natural ecosystems. These metabolites may exhibit a broad range of biological activities of great interest to human purposes. Samples from either microbial isolated cultures or microbiomes consist of complex mixtures of metabolites and their analysis are not a simple process. Mass spectrometry-based metabolomics encompass a set of analytical methods that have brought several improvements to the microbial natural products field. This analytical tool allows the comprehensively detection of metabolites, and therefore, the access of the chemical profile from those biological samples. These analyses generate thousands of mass spectra which is challenging to analyse. In this context, bioinformatic metabolomics tools have been successfully employed to accelerate and facilitate the investigation of specialized microbial metabolites. Herein, we describe metabolomics tools used to provide chemical information for the metabolites, and furthermore, we discuss how they can improve investigation of microbial cultures and interactions.

Metabologenomics analysis of Pseudomonas sp. So3.2b, an Antarctic strain with bioactivity against Rhizoctonia solani

Introduction

Phytopathogenic fungi are a considerable concern for agriculture, as they can threaten the productivity of several crops worldwide. Meanwhile, natural microbial products are acknowledged to play an important role in modern agriculture as they comprehend a safer alternative to synthetic pesticides. Bacterial strains from underexplored environments are a promising source of bioactive metabolites.

Methods

We applied the OSMAC (One Strain, Many Compounds) cultivation approach, in vitro bioassays, and metabolo-genomics analyses to investigate the biochemical potential of Pseudomonas sp. So3.2b, a strain isolated from Antarctica. Crude extracts from OSMAC were analyzed through HPLC-QTOF-MS/MS, molecular networking, and annotation. The antifungal potential of the extracts was confirmed against Rhizoctonia solani strains. Moreover, the whole-genome sequence was studied for biosynthetic gene clusters (BGCs) identification and phylogenetic comparison.

Results and Discussion

Molecular networking revealed that metabolite synthesis has growth media specificity, and it was reflected in bioassays results against R. solani. Bananamides, rhamnolipids, and butenolides-like molecules were annotated from the metabolome, and chemical novelty was also suggested by several unidentified compounds. Additionally, genome mining confirmed a wide variety of BGCs present in this strain, with low to no similarity with known molecules. An NRPS-encoding BGC was identified as responsible for producing the banamides-like molecules, while phylogenetic analysis demonstrated a close relationship with other rhizosphere bacteria. Therefore, by combining -omics approaches and in vitro bioassays, our study demonstrates that Pseudomonas sp. So3.2b has potential application to agriculture as a source of bioactive metabolites.

MS/MS-Based Molecular Networking: An Efficient Approach for Natural Products Dereplication

Natural products (NPs) have historically played a primary role in the discovery of small-molecule drugs. However, due to the advent of other methodologies and the drawbacks of NPs, the pharmaceutical industry has largely declined in interest regarding the screening of new drugs from NPs since 2000. There are many technical bottlenecks to quickly obtaining new bioactive NPs on a large scale, which has made NP-based drug discovery very time-consuming, and the first thorny problem faced by researchers is how to dereplicate NPs from crude extracts. Remarkably, with the rapid development of omics, analytical instrumentation, and artificial intelligence technology, in 2012, an efficient approach, known as tandem mass spectrometry (MS/MS)-based molecular networking (MN) analysis, was developed to avoid the rediscovery of known compounds from the complex natural mixtures. Then, in the past decade, based on the classical MN (CLMN), feature-based MN (FBMN), ion identity MN (IIMN), building blocks-based molecular network (BBMN), substructure-based MN (MS2LDA), and bioactivity-based MN (BMN) methods have been presented. In this paper, we review the basic principles, general workflow, and application examples of the methods mentioned above, to further the research and applications of these methods.

Good practices and recommendations for using and benchmarking computational metabolomics metabolite annotation tools

BACKGROUND

Untargeted metabolomics approaches based on mass spectrometry obtain comprehensive profiles of complex biological samples. However, on average only 10% of the molecules can be annotated. This low annotation rate hampers biochemical interpretation and effective comparison of metabolomics studies. Furthermore, de novo structural characterization of mass spectral data remains a complicated and time-intensive process. Recently, the field of computational metabolomics has gained traction and novel methods have started to enable large-scale and reliable metabolite annotation. Molecular networking and machine learning-based in-silico annotation tools have been shown to greatly assist metabolite characterization in diverse fields such as clinical metabolomics and natural product discovery.

AIM OF REVIEW

We highlight recent advances in computational metabolite annotation workflows with a special focus on their evaluation and comparison with other tools. Whilst the progress is substantial and promising, we also argue that inconsistencies in benchmarking different tools hamper users from selecting the most appropriate and promising method for their research. We summarize benchmarking strategies of the different tools and outline several recommendations for benchmarking and comparing novel tools.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on recent advances in mass spectral library-based and machine learning-supported metabolite annotation workflows. We discuss large-scale library matching and analogue search, the current bloom of mass spectral similarity scores, and how molecular networking has changed the field. In addition, the potentials and challenges of machine learning-supported metabolite annotation workflows are highlighted. Overall, recent developments in computational metabolomics have started to fundamentally change metabolomics workflows, and we expect that as a community we will be able to overcome current method performance ambiguities and annotation bottlenecks.

Exploring the Diversity and Antibacterial Potentiality of Cultivable Actinobacteria from the Soil of the Saxaul Forest in Southern Gobi Desert in Mongolia

Saxaul (Haloxylon ammodendron) is the most widespread plant community in the Gobi Desert in Mongolia, which plays important roles in wind control, sand fixation and water conservation. Investigations of soil-derived actinobacteria inhabiting in the saxaul forest in Gobi Desert in Mongolia have been scarce. In this study, biodiversity of culturable actinobacteria isolated from soil of the saxaul forest in Southern Gobi Aimak (Southern Gobi Province) of Mongolia was characterized and their potential to produce compounds with antibacterial activities was assessed. A total of 172 actinobacterial strains were recovered by culture-based approaches and were phylogenetically affiliated into 22 genera in 13 families of seven orders. Forty-nine actinobacterial isolates were selected to evaluate the antibacterial activities and their underlying mechanism of action was screened by means of a dual-fluorescent reporter assay (pDualrep2). Twenty-three isolates exhibited antagonistic activity against at least one of the tested pathogens, of which two Streptomyces strains can attenuate protein translation by ribosome stalling. Combinational strategies based on modern metabolomics, including bioassay-guided thin-layer chromatography (TLC), UPLC-QTOF-MS/MS based structural annotation and enhanced molecular networking successfully annotated chloramphenicol, althiomycin and granaticin and their derivatives as the antibacterial compounds from extracts in three Streptomyces strains, respectively. This work demonstrates that UPLC-MS/MS-based structural identification and enhanced molecular networking are effective strategies to rapidly illuminate the bioactive chemicals in the microbial extracts. Meanwhile, our results show that the saxaul forest in Mongolia Gobi Desert is a prospective source for discovering novel actinobacteria and biologically active compounds.

Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family

Natural products produced by plants are one of the most investigated natural sources, which substantially contributed to the development of the natural products field. Even though these compounds are widely explored, the literature still lacks comprehensive investigations aiming to explore the evolution of secondary metabolites produced by plants, especially if classical methodologies are employed. The development of sensitive hyphenated techniques and computational tools for data processing has enabled the study of large datasets, being valuable assets for chemosystematic studies. Here, we describe a strategy for chemotaxonomic investigations using the Malpighiaceae botanical family as a model. Our workflow was based on MS/MS untargeted metabolomics, spectral searches, and recently described in silico classification tools, which were mapped into the latest molecular phylogeny accepted for this family. The metabolomic analysis revealed that different ionization modes and extraction protocols significantly impacted the chemical profiles, influencing the chemotaxonomic results. Spectral searches within public databases revealed several clades or genera-specific molecular families, being potential chemical markers for these taxa, while the in silico classification tools were able to expand the Malpighiaceae chemical space. The classes putatively annotated were used for ancestral character reconstructions, which recovered several classes of metabolites as homoplasies (i.e., non-exclusive) or synapomorphies (i.e., exclusive) for all sampled clades and genera. Our workflow combines several approaches to perform a comprehensive evolutionary chemical study. We expect it to be used on further chemotaxonomic investigations to expand chemical knowledge and reveal biological insights for compounds classes in different biological groups.

Metabolomics Tools Assisting Classic Screening Methods in Discovering New Antibiotics from Mangrove Actinomycetia in Leizhou Peninsula

Mangrove actinomycetia are considered one of the promising sources for discovering novel biologically active compounds. Traditional bioactivity- and/or taxonomy-based methods are inefficient and usually result in the re-discovery of known metabolites. Thus, improving selection efficiency among strain candidates is of interest especially in the early stage of the antibiotic discovery program. In this study, an integrated strategy of combining phylogenetic data and bioactivity tests with a metabolomics-based dereplication approach was applied to fast track the selection process. A total of 521 actinomycetial strains affiliated to 40 genera in 23 families were isolated from 13 different mangrove soil samples by the culture-dependent method. A total of 179 strains affiliated to 40 different genera with a unique colony morphology were selected to evaluate antibacterial activity against 12 indicator bacteria. Of the 179 tested isolates, 47 showed activities against at least one of the tested pathogens. Analysis of 23 out of 47 active isolates using UPLC-HRMS-PCA revealed six outliers. Further analysis using the OPLS-DA model identified five compounds from two outliers contributing to the bioactivity against drug-sensitive A. baumannii. Molecular networking was used to determine the relationship of significant metabolites in six outliers and to find their potentially new congeners. Finally, two Streptomyces strains (M22, H37) producing potentially new compounds were rapidly prioritized on the basis of their distinct chemistry profiles, dereplication results, and antibacterial activities, as well as taxonomical information. Two new trioxacarcins with keto-reduced trioxacarcinose B, gutingimycin B (16) and trioxacarcin G (20), together with known gutingimycin (12), were isolated from the scale-up fermentation broth of Streptomyces sp. M22. Our study demonstrated that metabolomics tools could greatly assist classic antibiotic discovery methods in strain prioritization to improve efficiency in discovering novel antibiotics from those highly productive and rich diversity ecosystems.

Advancements in capturing and mining mass spectrometry data are transforming natural products research

Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.

Development of an agar-plug cultivation system for bioactivity assays of actinomycete strain collections

Natural products are an important source of lead compounds for the development of drug substances. Actinomycetes have been valuable especially for the discovery of antibiotics. Increasing occurrence of antibiotic resistance among bacterial pathogens has revived the interest in actinomycete natural product research. Actinobacteria produce a different set of natural products when cultivated on solid growth media compared with submersed culture. Bioactivity assays involving solid media (e.g. agar-plug assays) require manual manipulation of the strains and agar plugs. This is less convenient for the screening of larger strain collections of several hundred or thousand strains. Thus, the aim of this study was to develop a 96-well microplate-based system suitable for the screening of actinomycete strain collections in agar-plug assays. We developed a medium-throughput cultivation and agar-plug assay workflow that allows the convenient inoculation of solid agar plugs with actinomycete spore suspensions from a strain collection, and the transfer of the agar plugs to petri dishes to conduct agar-plug bioactivity assays. The development steps as well as the challenges that were overcome during the development (e.g. system sterility, handling of the agar plugs) are described. We present the results from one exemplary screening campaign targeted to identify compounds inhibiting Agr-based quorum sensing where the workflow was used successfully. We present a novel and convenient workflow to combine agar diffusion assays with microtiter-plate-based cultivation systems in which strains can grow on a solid surface. This workflow facilitates and speeds up the initial medium throughput screening of natural product-producing actinomycete strain collections against monitor strains in agar-plug assays.

Structure-based molecular networking for the target discovery of novel germicidin derivatives from the sponge-associated streptomyces sp. 18A01

Four new α-pyrone derivatives, named germicidins P-S (1-4) along with nine known analogues (5-13) were discovered from the sponge-associated Streptomyces sp. 18A01 guided by Global Natural Products Social (GNPS) molecular networking, the LC-DAD-MS profile, and hexokinase II (HK2) inhibitory activity. The structures of 1-13 were elucidated by analysis of their HRMS, optical rotation, and NMR spectroscopic data. The absolute configurations of germicidin P (1) and germicidin Q (2) were determined on the basis of comparisons of experimental and theoretically calculated ECD spectra. Bioactivities of the isolated compounds were assayed against human HK2. The bioassay results showed that compounds 1-4 and 11-13 exhibited significant inhibitory activities against HK2, with IC₅₀ values ranging from 5.1 to 11.0 μM. A molecular docking simulation demonstrated that these germicidins were docked in the inner active site tunnel of HK2. Interestingly, the amino residue Arg91 has a better binding affinity and efficacy than the amino residue Asn89 in the process of HK2 binding to the ligands, resulting in better hexokinase inhibitory activity. This result provided a valuable perspective for better understanding their HK2 inhibition activity.

The isolation of water-soluble natural products - challenges, strategies and perspectives

Covering period: up to 2019Water-soluble natural products constitute a relevant group of secondary metabolites notably known for presenting potent biological activities. Examples are aminoglycosides, β-lactam antibiotics, saponins of both terrestrial and marine origin, and marine toxins. Although extensively investigated in the past, particularly during the golden age of antibiotics, hydrophilic fractions have been less scrutinized during the last few decades. This review addresses the possible reasons on why water-soluble metabolites are now under investigated and describes approaches and strategies for the isolation of these natural compounds. It presents examples of several classes of hydrosoluble natural products and how they have been isolated. Novel stationary phases and chromatography techniques are also reviewed, providing a perspective towards a renaissance in the investigation of water-soluble natural products.

Integrating perspectives in actinomycete research: an ActinoBase review of 2020-21

Last year ActinoBase, a Wiki-style initiative supported by the UK Microbiology Society, published a review highlighting the research of particular interest to the actinomycete community. Here, we present the second ActinoBase review showcasing selected reports published in 2020 and early 2021, integrating perspectives in the actinomycete field. Actinomycetes are well-known for their unsurpassed ability to produce specialised metabolites, of which many are used as therapeutic agents with antibacterial, antifungal, or immunosuppressive activities. Much research is carried out to understand the purpose of these metabolites in the environment, either within communities or in host interactions. Moreover, many efforts have been placed in developing computational tools to handle big data, simplify experimental design, and find new biosynthetic gene cluster prioritisation strategies. Alongside, synthetic biology has provided advances in tools to elucidate the biosynthesis of these metabolites. Additionally, there are still mysteries to be uncovered in understanding the fundamentals of filamentous actinomycetes' developmental cycle and regulation of their metabolism. This review focuses on research using integrative methodologies and approaches to understand the bigger picture of actinomycete biology, covering four research areas: i) technology and methodology; ii) specialised metabolites; iii) development and regulation; and iv) ecology and host interactions.

Mass Spectrometry-Based Network Analysis Reveals New Insights Into the Chemodiversity of 28 Species in Aspergillus section Flavi

Aspergillus section Flavi includes some of the most famous mycotoxin producing filamentous fungi known to mankind. In recent years a number of new species have been included in section Flavi, however these species have been much less studied from a chemical point of view. In this study, we explored one representative strain of a total of 28 fungal species in section Flavi by systematically evaluating the relationship between taxonomy and secondary metabolites with LC-MS/MS analysis for the first time and dereplication through an in-house database and the Global Natural Product Social Molecular Networking (GNPS) platform. This approach allowed rapid identification of two new cyclopiazonic acid producers (A. alliaceus and A. arachidicola) and two new tenuazonic acid producers (A. arachidicola and A. leporis). Moreover, for the first time we report species from section Flavi to produce fumifungin and sphingofungins B-D. Altogether, this study emphasizes that the chemical diversity of species in genus Aspergillus section Flavi is larger than previously recognized, and especially that understudied species are prolific producers of important mycotoxins such as fumi- and sphingofungins not previously reported from this section. Furthermore, our work demonstrates Global Natural Product Social (GNPS) Molecular Networking as a powerful tool for large-scale chemotaxonomic analysis of closely related species in filamentous fungi.

Elicitation of Streptomyces lunalinharesii secondary metabolism through co-cultivation with Rhizoctonia solani

The concern regarding the emergence of phytopathogens strains which are resistant to conventional agrochemicals has given support to the search for alternatives on the use of chemical pesticides in agriculture. In this context, microorganisms are considered as promising sources of useful natural compounds and actinobacteria are particularly relevant since they are known to produce several bioactive metabolites. The objective of this work was to investigate the production of secondary metabolites with antifungal activity by a strain of the actinobacteria Streptomyces lunalinharesii (A54A) under axenic conditions and in co-cultivation with the phytopathogen Rhizoctonia solani. Tests to evaluate antifungal activity of the extracts indicated the presence of diffusable molecules capable of inhibiting the growth of R. solani produced by S. lunalinharesii, especially when in the presence of the fungus during fermentation. Metabolomic analyzes allowed the putative annotation of the bioactive compounds desferrioxamine E and anisomycin, in addition to the evaluation of the metabolic profile of the isolate when grown in axenic mode and in co-cultivation, while statistical analyzes enabled the comparison of such profiles and the identification of metabolites produced in greater relative quantities in the elicitation condition. Such methodologies provided the selection of unknown features with high bioactive potential for dereplication, and several metabolites of S. lunalinharesii possibly represent novel compounds.

Insight into chemical basis of traditional Chinese medicine based on the state-of-the-art techniques of liquid chromatography-mass spectrometry

Traditional Chinese medicine (TCM) has been an indispensable source of drugs for curing various human diseases. However, the inherent chemical diversity and complexity of TCM restricted the safety and efficacy of its usage. Over the past few decades, the combination of liquid chromatography with mass spectrometry has contributed greatly to the TCM qualitative analysis. And novel approaches have been continuously introduced to improve the analytical performance, including both the data acquisition methods to generate a large and informative dataset, and the data post-processing tools to extract the structure-related MS information. Furthermore, the fast-developing computer techniques and big data analytics have markedly enriched the data processing tools, bringing benefits of high efficiency and accuracy. To provide an up-to-date review of the latest techniques on the TCM qualitative analysis, multiple data-independent acquisition methods and data-dependent acquisition methods (precursor ion list, dynamic exclusion, mass tag, precursor ion scan, neutral loss scan, and multiple reaction monitoring) and post-processing techniques (mass defect filtering, diagnostic ion filtering, neutral loss filtering, mass spectral trees similarity filter, molecular networking, statistical analysis, database matching, etc.) were summarized and categorized. Applications of each technique and integrated analytical strategies were highlighted, discussion and future perspectives were proposed as well.

Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions

Specialised metabolites from microbial sources are well-known for their wide range of biomedical applications, particularly as antibiotics. When mining paired genomic and metabolomic data sets for novel specialised metabolites, establishing links between Biosynthetic Gene Clusters (BGCs) and metabolites represents a promising way of finding such novel chemistry. However, due to the lack of detailed biosynthetic knowledge for the majority of predicted BGCs, and the large number of possible combinations, this is not a simple task. This problem is becoming ever more pressing with the increased availability of paired omics data sets. Current tools are not effective at identifying valid links automatically, and manual verification is a considerable bottleneck in natural product research. We demonstrate that using multiple link-scoring functions together makes it easier to prioritise true links relative to others. Based on standardising a commonly used score, we introduce a new, more effective score, and introduce a novel score using an Input-Output Kernel Regression approach. Finally, we present NPLinker, a software framework to link genomic and metabolomic data. Results are verified using publicly available data sets that include validated links.

Coupling Mass Spectral and Genomic Information to Improve Bacterial Natural Product Discovery Workflows

Bacterial natural products possess potent bioactivities and high structural diversity and are typically encoded in biosynthetic gene clusters. Traditional natural product discovery approaches rely on UV- and bioassay-guided fractionation and are limited in terms of dereplication. Recent advances in mass spectrometry, sequencing and bioinformatics have led to large-scale accumulation of genomic and mass spectral data that is increasingly used for signature-based or correlation-based mass spectrometry genome mining approaches that enable rapid linking of metabolomic and genomic information to accelerate and rationalize natural product discovery. In this mini-review, these approaches are presented, and discovery examples provided. Finally, future opportunities and challenges for paired omics-based natural products discovery workflows are discussed.

The need to innovate sample collection and library generation in microbial drug discovery: a focus on academia

The question of whether culturable microorganisms will continue to be a viable source of new drug leads is inherently married to the strategies used to collect samples from the environment, the methods used to cultivate microorganisms from these samples, and the processes used to create microbial libraries. An academic microbial natural products (NP) drug discovery program with the latest innovative chromatographic and spectroscopic technology, high-throughput capacity, and bioassays will remain at the mercy of the quality of its microorganism source library. This viewpoint will discuss limitations of sample collection and microbial strain library generation practices. Additionally, it will offer suggestions to innovate these areas, particularly through the targeted cultivation of several understudied bacterial phyla and the untargeted use of mass spectrometry and bioinformatics to generate diverse microbial libraries. Such innovations have potential to impact downstream therapeutic discovery, and make its front end more informed, efficient, and less reliant on serendipity. This viewpoint is not intended to be a comprehensive review of contributing literature and was written with a focus on bacteria. Strategies to discover NPs from microbial libraries, including a variety of genomics and "OSMAC" style approaches, are considered downstream of sample collection and library creation, and thus are out of the scope of this viewpoint.

Planomonospora: A Metabolomics Perspective on an Underexplored Actinobacteria Genus

Despite an excellent track record, microbial drug discovery suffers from high rates of rediscovery. Better workflows for the rapid investigation of complex extracts are needed to increase throughput and to allow early prioritization of samples. In addition, systematic characterization of poorly explored strains is seldomly performed. Here, we report a metabolomic study of 72 isolates belonging to the rare actinomycete genus Planomonospora, using a workflow of commonly used open access tools to investigate its secondary metabolites. The results reveal a correlation of chemical diversity and strain phylogeny, with classes of metabolites exclusive to certain phylogroups. We were able to identify previously reported Planomonospora metabolites, including the ureylene-containing oligopeptide antipain, the thiopeptide siomycin including new congeners, and the ribosomally synthesized peptides sphaericin and lantibiotic 97518. In addition, we found that Planomonospora strains can produce the siderophore desferrioxamine or a salinichelin-like peptide. Analysis of the genomes of three newly sequenced strains led to the detection of 59 gene cluster families, of which three were connected to products found by LC-MS/MS profiling. This study demonstrates the value of metabolomic studies to investigate poorly explored taxa and provides a first picture of the biosynthetic capabilities of the genus Planomonospora.

Fungal natural products galaxy: Biochemistry and molecular genetics toward blockbuster drugs discovery

Secondary metabolites synthesized by fungi have become a precious source of inspiration for the design of novel drugs. Indeed, fungi are prolific producers of fascinating, diverse, structurally complex, and low-molecular-mass natural products with high therapeutic leads, such as novel antimicrobial compounds, anticancer compounds, immunosuppressive agents, among others. Given that these microorganisms possess the extraordinary capacity to secrete diverse chemical scaffolds, they have been highly exploited by the giant pharma companies to generate small molecules. This has been made possible because the isolation of metabolites from fungal natural sources is feasible and surpasses the organic synthesis of compounds, which otherwise remains a significant bottleneck in the drug discovery process. Here in this comprehensive review, we have discussed recent studies on different fungi (pathogenic, non-pathogenic, commensal, and endophytic/symbiotic) from different habitats (terrestrial and marines), the specialized metabolites they biosynthesize, and the drugs derived from these specialized metabolites. Moreover, we have unveiled the logic behind the biosynthesis of vital chemical scaffolds, such as NRPS, PKS, PKS-NRPS hybrid, RiPPS, terpenoids, indole alkaloids, and their genetic mechanisms. Besides, we have provided a glimpse of the concept behind mycotoxins, virulence factor, and host immune response based on fungal infections.

Targeted Isolation of Asperheptatides from a Coral-Derived Fungus Using LC-MS/MS-Based Molecular Networking and Antitubercular Activities of Modified Cinnamate Derivatives

Under the guidance of MS/MS-based molecular networking, four new cycloheptapeptides, namely, asperheptatides A-D (1-4), were isolated together with three known analogues, asperversiamide A-C (5-7), from the coral-derived fungus Aspergillus versicolor. The planar structures of the two major compounds, asperheptatides A and B (1 and 2), were determined by comprehensive spectroscopic data analysis. The absolute configurations of the amino acid residues were determined by advanced Marfey's method. The two structurally related trace metabolites, asperheptatides C and D (3 and 4), were characterized by ESI-MS/MS fragmentation methods. A series of new derivatives (8-26) of asperversiamide A (5) were semisynthesized. The antitubercular activities of 1, 2, and 5-26 against Mycobacterium tuberculosis H37Ra were also evaluated. Compounds 9, 13, 23, and 24 showed moderate activities with MIC values of 12.5 μM, representing a potential new class of antitubercular agents.

Diversity, Bioactivity Profiling and Untargeted Metabolomics of the Cultivable Gut Microbiota of Ciona intestinalis

It is widely accepted that the commensal gut microbiota contributes to the health and well-being of its host. The solitary tunicate Ciona intestinalis emerges as a model organism for studying host-microbe interactions taking place in the gut, however, the potential of its gut-associated microbiota for marine biodiscovery remains unexploited. In this study, we set out to investigate the diversity, chemical space, and pharmacological potential of the gut-associated microbiota of C. intestinalis collected from the Baltic and North Seas. In a culture-based approach, we isolated 61 bacterial and 40 fungal strains affiliated to 33 different microbial genera, indicating a rich and diverse gut microbiota dominated by Gammaproteobacteria. In vitro screening of the crude microbial extracts indicated their antibacterial (64% of extracts), anticancer (22%), and/or antifungal (11%) potential. Nine microbial crude extracts were prioritized for in-depth metabolome mining by a bioactivity- and chemical diversity-based selection procedure. UPLC-MS/MS-based metabolomics combining automated (feature-based molecular networking and in silico dereplication) and manual approaches significantly improved the annotation rates. A high chemical diversity was detected where peptides and polyketides were the predominant classes. Many compounds remained unknown, including two putatively novel lipopeptides produced by a Trichoderma sp. strain. This is the first study assessing the chemical and pharmacological profile of the cultivable gut microbiota of C. intestinalis.

Metabolomic study of marine Streptomyces sp.: Secondary metabolites and the production of potential anticancer compounds

Resorting to a One Strain Many Compounds (OSMAC) approach, the marine Streptomyces sp. BRB081 strain was grown in six different media settings over 1, 2, 3 or 7 days. Extractions of mycelium and broth were conducted separately for each media and cultivation period by sonication using methanol/acetone 1:1 and agitation with ethyl acetate, respectively. All methanol/acetone and ethyl acetate crude extracts were analysed by HPLC-MS/MS and data treatment was performed through GNPS platform using MZmine 2 software. In parallel, the genome was sequenced, assembled and mined to search for biosynthetic gene clusters (BGC) of secondary metabolites using the AntiSMASH 5.0 software. Spectral library search tool allowed the annotation of desferrioxamines, fatty acid amides, diketopiperazines, xanthurenic acid and, remarkably, the cyclic octapeptides surugamides. Molecular network analysis allowed the observation of the surugamides cluster, where surugamide A and the protonated molecule corresponding to the B-E isomers, as well as two potentially new analogues, were detected. Data treatment through MZmine 2 software allowed to distinguish that the largest amount of surugamides was obtained by cultivating BRB081 in SCB medium during 7 days and extraction of culture broth. Using the same data treatment, a chemical barcode was created for easy visualization and comparison of the metabolites produced overtime in all media. By genome mining of BRB081 four regions of biosynthetic gene clusters of secondary metabolites were detected supporting the metabolic data. Cytotoxic evaluation of all crude extracts using MTT assay revealed the highest bioactivity was also observed for extracts obtained in the optimal conditions as those for surugamides production, suggesting these to be the main active compounds herein. This method allowed the identification of compounds in the crude extracts and guided the selection of best conditions for production of bioactive compounds.

Integration of LC/MS-based molecular networking and classical phytochemical approach allows in-depth annotation of the metabolome of non-model organisms - The case study of the brown seaweed Taonia atomaria

Untargeted LC-MS based metabolomics is a useful approach in many research areas such as medicine, systems biology, environmental sciences or even ecology. In such an approach, annotation of metabolomes of non-model organisms remains a significant challenge. In this study, an analytical workflow combining a classical phytochemical approach, using the isolation and the full characterization of the chemical structure of natural products, together with the use of MS/MS-based molecular networking with various levels of restrictiveness was developed. This protocol was applied to the marine brown seaweed Taonia atomaria, a cosmopolitan algal species, and allowed to annotate more than 200 metabolites. First, the algal organic crude extracts were fractionated by flash-chromatography and the chemical structure of eight of the main chemical constituents of this alga were fully characterized by means of spectroscopic methods (1D and 2D NMR, HRMS). These compounds were further used as chemical standards. In a second step, the main fractions of the algal extracts were analyzed by UHPLC-MS/MS and the resulting data were uploaded to the Global Natural Products Social Molecular Networking platform (GNPS) to create several molecular networks (MNs). A first MN (MN-1) was built with restrictive parameters and allowed the creation of clusters composed by nodes with highly similar MS/MS spectra. Then, using database hits and chemical standards as "seed" nodes and/or similarity between MS/MS fragmentation pattern, the main clusters were easily annotated as common glycerolipids and phospholipids, much rare lipids -such as acylglycerylhydroxymethyl-N,N,N-trimethyl-ß-alanines or fulvellic acid derivatives- but also new glycerolipids bearing a terpene moiety. Lastly, the use of less and less constrained MNs allowed to further increase the number of annotated metabolites.

Combined MS/MS-NMR Annotation Guided Discovery of Iris lactea var. chinensis Seed as a Source of Viral Neuraminidase Inhibitory Polyphenols

In this study, the chemical diversity of polyphenols in Iris lactea var. chinensis seeds was identified by combined MS/MS-NMR analysis. Based on the annotated chemical profile, the isolation of stilbene oligomers was conducted, and consequently, stilbene oligomers (1-10) were characterized. Of these, compounds 1 and 2 are previously undescribed stilbene dimer glycoside (1) and tetramer glycoside (2), respectively. Besides, to evaluate this plant seed as a rich source of stilbene oligomers, we quantified three stilbene oligomers of I. lactea var. chinensis seeds. The contents of three major stilbene oligomers—trans-ε-viniferin (3), vitisin A (6), and vitisin B (9)—in I. lactea var. chinensis seeds were quantified as 2.32 (3), 4.95 (6), and 1.64 (9) mg/g dry weight (DW). All the isolated compounds were tested for their inhibitory activities against influenza neuraminidase. Compound 10 was found to be active with the half maximal inhibitory concentration (IC₅₀) values at 4.76 μM. Taken together, it is concluded that I. lactea var. chinensis seed is a valuable source of stilbene oligomers with a human health benefit.

Hydroxy-neo-Clerodanes and 5,10-seco-neo-Clerodanes from Salvia decora

Preliminary analysis of the mass spectrometric (MS) and NMR spectroscopic data of the primary fractions from the biologically active extract of Salvia decora revealed spectra that are characteristic for neo-clerodane-type diterpenoids. MS-guided isolation of the bioactive fractions led to the isolation of three new chemical entities, including two hydroxy-neo-clerodanes (1 and 2) and one acylated 5,10-seco-neo-clerodane (3), along with three known diterpenoids (4-6), ursolic acid (7), and eupatorin (8). The structures of the new compounds were established by analysis of the 1D and 2D NMR and MS data, whereas their absolute configuration was deduced using a combination of experimental and theoretical ECD data and confirmed by X-ray crystallography (1 and 4). Furthermore, compounds 1, 3, 4, and 6-8 were evaluated as hPTP1B_1-400 (human protein tyrosine phosphatase) inhibitors, where 7 showed the best activity, with an IC₅₀ value in the lower μM range. Additionally, compound 7 was evaluated as an α-glucosidase inhibitor. The affinity constant of the 7-hPTP1B_1-400 complex was determined by quenching fluorescence experiments (k_a = 1.3 × 10⁴ M^-1), while the stoichiometry ratio (1:1 protein-ligand) was determined by a continuous variation method.

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.

Staring into the void: demystifying microbial metabolomics

Metabolites give us a window into the chemistry of microbes and are split into two subclasses: primary and secondary. Primary metabolites are required for life whereas secondary metabolites have historically been classified as those appearing after exponential growth and are not necessarily needed for survival. Many microbial species are estimated to produce hundreds of metabolites and can be affected by differing nutrients. Using various analytical techniques, metabolites can be directly detected in order to elucidate their biological significance. Currently, a single experiment can produce anywhere from megabytes to terabytes of data. This big data has motivated scientists to develop informatics tools to help target specific metabolites or sets of metabolites. Broadly, it is imperative to identify clear biological questions before embarking on a study of metabolites (metabolomics). For instance, studying the effect of a transposon insertion on phenazine biosynthesis in Pseudomonas is a very different from asking what molecules are present in a specific banana-derived strain of Pseudomonas. This review is meant to serve as a primer for a 'choose your own adventure' approach for microbiologists with limited mass spectrometry expertise, with a strong focus on liquid chromatography mass spectrometry based workflows developed or optimized within the past five years.

Reproducible molecular networking of untargeted mass spectrometry data using GNPS

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.

An enumeration of natural products from microbial, marine and terrestrial sources

The discovery of a new drug is a multidisciplinary and very costly task. One of the major steps is the identification of a lead compound, i.e. a compound with a certain degree of potency and that can be chemically modified to improve its activity, metabolic properties, and pharmacokinetics profiles. Terrestrial sources (plants and fungi), microbes and marine organisms are abundant resources for the discovery of new structurally diverse and biologically active compounds. In this chapter, an attempt has been made to quantify the numbers of known published chemical structures (available in chemical databases) from natural sources. Emphasis has been laid on the number of unique compounds, the most abundant compound classes and the distribution of compounds in terrestrial and marine habitats. It was observed, from the recent investigations, that ~500,000 known natural products (NPs) exist in the literature. About 70 % of all NPs come from plants, terpenoids being the most represented compound class (except in bacteria, where amino acids, peptides, and polyketides are the most abundant compound classes). About 2,000 NPs have been co-crystallized in PDB structures.

Streptomyces sp. BV410 isolate from chamomile rhizosphere soil efficiently produces staurosporine with antifungal and antiangiogenic properties

Applying a bioactivity‐guided isolation approach, staurosporine was separated and identified as the active principle in the culture extract of the new isolate Streptomyces sp. BV410 collected from the chamomile rhizosphere. The biotechnological production of staurosporine by strain BV410 was optimized to yield 56 mg/L after 14 days of incubation in soy flour–glucose–starch–mannitol‐based fermentation medium (JS). The addition of FeSO₄ significantly improved the staurosporine yield by 30%, while the addition of ZnSO₄ significantly reduced staurosporine yield by 62% in comparison with the starting conditions. Although staurosporine was first isolated in 1977 from Lentzea albida (now Streptomyces staurosporeus) and its potent kinase inhibitory effect has been established, here, the biological activity of this natural product was assessed in depth in vivo using a selection of transgenic zebrafish (Danio rerio) models, including Tg(fli1:EGFP) with green fluorescent protein‐labeled endothelial cells allowing visualization and monitoring of blood vessels. This confirmed a remarkable antiangiogenic activity of the compound at doses of 1 ng/ml (2.14 nmol/L) which is below doses inducing toxic effects (45 ng/ml; 75 nmol/L). A new, efficient producing strain of commercially significant staurosporine has been described along with optimized fermentation conditions, which may lead to optimization of the staurosporine scaffold and its wider applicability.

Water-Soluble Glutamic Acid Derivatives Produced in Culture by Penicillium solitum IS1-A from King George Island, Maritime Antarctica

A new method of screening was developed to generate 770 organic and water-soluble fractions from extracts of nine species of marine sponges, from the growth media of 18 species of marine-derived fungi, and from the growth media of 13 species of endophytic fungi. The screening results indicated that water-soluble fractions displayed significant bioactivity in cytotoxic, antibiotic, anti-Leishmania, anti-Trypanosoma cruzi, and inhibition of proteasome assays. Purification of water-soluble fractions from the growth medium of Penicillium solitum IS1-A provided the new glutamic acid derivatives solitumine A (1), solitumine B (2), and solitumidines A-D (3-6). The structures of compounds 1-6 have been established by analysis of spectroscopic data, chemical derivatizations, and vibrational circular dichroism calculations. Although no biological activity could be observed for compounds 1-6, the new structures reported for 1-6 indicate that the investigation of water-soluble natural products represents a relevant strategy in finding new secondary metabolites.

Signalling and Bioactive Metabolites from Streptomyces sp. RK44

Streptomyces remains one of the prolific sources of structural diversity, and a reservoir to mine for novel natural products. Continued screening for new Streptomyces strains in our laboratory led to the isolation of Streptomyces sp. RK44 from the underexplored areas of Kintampo waterfalls, Ghana, Africa. Preliminary screening of the metabolites from this strain resulted in the characterization of a new 2-alkyl-4-hydroxymethylfuran carboxamide (AHFA) 1 together with five known compounds, cyclo-(L-Pro-Gly) 2, cyclo-(L-Pro-L-Phe) 3, cyclo-(L-Pro-L-Val) 4, cyclo-(L-Leu-Hyp) 5, and deferoxamine E 6. AHFA 1, a methylenomycin (MMF) homolog, exhibited anti-proliferative activity (EC₅₀ = 89.6 µM) against melanoma A2058 cell lines. This activity, albeit weak is the first report amongst MMFs. Furthermore, the putative biosynthetic gene cluster (ahfa) was identified for the biosynthesis of AHFA 1. DFO-E 6 displayed potent anti-plasmodial activity (IC₅₀ = 1.08 µM) against P. falciparum 3D7. High-resolution electrospray ionization mass spectrometry (HR ESIMS) and molecular network assisted the targeted-isolation process, and tentatively identified six AHFA analogues, 7–12 and six siderophores 13–18.

Current status and contemporary approaches to the discovery of antitumor agents from higher plants

Higher plant constituents have afforded clinically available anticancer drugs. These include both chemically unmodified small molecules and their synthetic derivatives currently used or those in clinical trials as antineoplastic agents, and an updated summary is provided. In addition, botanical dietary supplements, exemplified by mangosteen and noni constituents, are also covered as potential cancer chemotherapeutic agents. Approaches to metabolite purification, rapid dereplication, and biological evaluation including analytical hyphenated techniques, molecular networking, and advanced cellular and animal models are discussed. Further, enhanced and targeted drug delivery systems for phytochemicals, including micelles, nanoparticles and antibody drug conjugates (ADCs) are described herein.

Molecular networking-based for the target discovery of potent antiproliferative polycyclic macrolactam ansamycins from Streptomyces cacaoi subsp. asoensis

Molecular networking-based for the target discovery of potent antiproliferative polycyclic macrolactam ansamycins.

Identification of Antimicrobial Compounds from Sandwithia guyanensis-Associated Endophyte Using Molecular Network Approach

The emergence of multidrug resistant bacterial pathogens and the increase of antimicrobial resistance constitutes a major health challenge, leading to intense research efforts being focused on the discovery of novel antimicrobial compounds. In this study, endophytes were isolated from different parts of Sandwithia guyanensis plant (leaves, wood and latex) belonging to the Euphorbiaceae family and known to produce antimicrobial compounds, and chemically characterised using Molecular Network in order to discover novel antimicrobial molecules. One fungal endophyte extract obtained from S. guyanensis latex showed significant antimicrobial activity with Minimal Inhibitory Concentration on methicillin-resistant Staphylococcus aureus at 16 µg/mL. The chemical investigation of this fungus (Lecanicillium genus) extract led to the isolation of 5 stephensiolides compounds, four of which demonstrated antibacterial activity. Stephensiolide I and G showed the highest antibacterial activity on MRSA with a MIC at 4 and 16 µg/mL respectively.

Innovative omics-based approaches for prioritisation and targeted isolation of natural products - new strategies for drug discovery

Covering: 2013 to 2019 The exploration of the chemical diversity of extracts from various biological sources has led to major drug discoveries. Over the past two decades, despite the introduction of advanced methodologies for natural product (NP) research (e.g., dereplication and high content screening), successful accounts of the validation of NPs as lead therapeutic candidates have been limited. In this context, one of the main challenges faced is related to working with crude natural extracts because of their complex composition and the inadequacies of classical bioguided isolation studies given the pace of high-throughput screening campaigns. In line with the development of metabolomics, genomics and chemometrics, significant advances in metabolite profiling have been achieved and have generated high-quality massive genome and metabolome data on natural extracts. The unambiguous identification of each individual NP in an extract using generic methods remains challenging. However, the establishment of structural links among NPs via molecular network analysis and the determination of common features of extract composition have provided invaluable information to the scientific community. In this context, new multi-informational-based profiling approaches integrating taxonomic and/or bioactivity data can hold promise for the discovery and development of new bioactive compounds and return NPs back to an exciting era of development. In this article, we examine recent studies that have the potential to improve the efficiency of NP prioritisation and to accelerate the targeted isolation of key NPs. Perspectives on the field's evolution are discussed.