Oligomycin-producing Streptomyces sp. newly isolated from Swiss soils efficiently protect Arabidopsis thaliana against Botrytis cinerea.

Botrytis cinerea is a necrotrophic phytopathogen able to attack more than 200 different plant species causing strong yield losses worldwide. Many synthetic fungicides have been developed to control this disease, resulting in the rise of fungicide-resistance B. cinerea strains. The aim of this study was to identify Streptomyces strains showing antagonistic activity against B. cinerea to contribute to plant protection in an environmentally friendly way. We isolated 15 Actinomycete strains from 9 different Swiss soils. The culture filtrates of three isolates showing antifungal activity inhibited spore germination and delayed mycelial growth of B. cinerea. Infection experiments showed that Arabidopsis thaliana plants were more resistant to this pathogen after leaf treatment with the Streptomyces filtrates. Bioassay-guided isolation of the active compounds revealed the presence of germicidins A and B as well as of oligomycins A, B, and E. While germicidins were mostly inactive, oligomycin B reduced the mycelial growth of B. cinerea significantly. Moreover, all three oligomycins inhibited this fungus' spore germination, suggesting that these molecules might contribute to the Streptomyces's ability to protect plants against infection by the broad host-pathogen Botrytis cinerea. IMPORTANCE: This study reports the isolation of new Streptomyces strains with strong plant-protective potential mediated by their production of specialized metabolites. Using the broad host range pathogenic fungus Botrytis cinerea, we demonstrate that the cell-free filtrate of selected Streptomyces isolates efficiently inhibits different developmental stages of the fungus, including mycelial growth and the epidemiologically relevant spore germination. Beyond in vitro experiments, the strains and their metabolites also efficiently protected plants against the disease caused by this pathogen. This work further identifies oligomycins as active compounds involved in the observed antifungal activity of the strains. This work shows that we can harness the natural ability of soil-borne microbes and of their metabolites to efficiently fight other microbes responsible for significant crop losses. This opens the way to the development of environmentally friendly health protection measures for crops of agronomical relevance, based on these newly isolated strains or their metabolic extracts containing oligomycins.

plantMASST - Community-driven chemotaxonomic digitization of plants.

Understanding the distribution of hundreds of thousands of plant metabolites across the plant kingdom presents a challenge. To address this, we curated publicly available LC-MS/MS data from 19,075 plant extracts and developed the plantMASST reference database encompassing 246 botanical families, 1,469 genera, and 2,793 species. This taxonomically focused database facilitates the exploration of plant-derived molecules using tandem mass spectrometry (MS/MS) spectra. This tool will aid in drug discovery, biosynthesis, (chemo)taxonomy, and the evolutionary ecology of herbivore interactions.

Comprehensive mass spectrometric metabolomic profiling of a chemically diverse collection of plants of the Celastraceae family.

Natural products exhibit interesting structural features and significant biological activities. The discovery of new bioactive molecules is a complex process that requires high-quality metabolite profiling data to properly target the isolation of compounds of interest and enable their complete structural characterization. The same metabolite profiling data can also be used to better understand chemotaxonomic links between species. This Data Descriptor details a dataset resulting from the untargeted liquid chromatography-mass spectrometry metabolite profiling of 76 natural extracts of the Celastraceae family. The spectral annotation results and related chemical and taxonomic metadata are shared, along with proposed examples of data reuse. This data can be further studied by researchers exploring the chemical diversity of natural products. This can serve as a reference sample set for deep metabolome investigation of this chemically rich plant family.

A Sample-Centric and Knowledge-Driven Computational Framework for Natural Products Drug Discovery.

The ENPKG framework organizes large heterogeneous metabolomics data sets as a knowledge graph, offering exciting opportunities for drug discovery and chemodiversity characterization.

microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data.

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

Comparative genomic and metabolomic study of three Streptomyces sp. differing in biological activity.

The Streptomyces genus is known to produce many specialized metabolites of value for medicine, but the potential of these metabolites in agronomy remains largely unexplored. In this study, we investigated three phylogenetically closely related Streptomyces strains (B5, B91, and B135) isolated from three distinct soil samples in Sudan. Despite belonging to the same species, these strains exhibited different ranges of Phytophthora infestans inhibition. The objective of this work was to identify the active compound(s) responsible for the inhibition of P. infestans and of other plant pathogens by comparing the genomes and metabolomes of the three strains which showed distinct activity patterns: B5 was the strongest inhibitor of oomycetes, B5 and B91 both inhibited most fungi and B135 was the only strain showing antibacterial activity. Our comparative genomic and metabolomic analysis identified borrelidin as the bioactive compound underlying B5's strong anti-oomycete activity and highlighted a few other metabolites as putative candidates underlying the strains' antifungal and antibacterial activities. This study illustrates the power of comparative genomics and metabolomics on phylogenetically closely related strains of differing activities to highlight bioactive compounds that could contribute to new sustainable crop protection strategies.

Leaf metabolic traits reveal hidden dimensions of plant form and function.

The metabolome is the biochemical basis of plant form and function, but we know little about its macroecological variation across the plant kingdom. Here, we used the plant functional trait concept to interpret leaf metabolome variation among 457 tropical and 339 temperate plant species. Distilling metabolite chemistry into five metabolic functional traits reveals that plants vary on two major axes of leaf metabolic specialization-a leaf chemical defense spectrum and an expression of leaf longevity. Axes are similar for tropical and temperate species, with many trait combinations being viable. However, metabolic traits vary orthogonally to life-history strategies described by widely used functional traits. The metabolome thus expands the functional trait concept by providing additional axes of metabolic specialization for examining plant form and function.

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data.

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health.

Biodiversity: the overlooked source of human health.

Biodiversity is the measure of the variation of lifeforms in a given ecological system. Biodiversity provides ecosystems with the robustness, stability, and resilience that sustains them. This is ultimately essential for our survival because we depend on the services that natural ecosystems provide (food, fresh water, air, climate, and medicine). Despite this, human activity is driving an unprecedented rate of biodiversity decline, which may jeopardize the life-support systems of the planet if no urgent action is taken. In this article we show why biodiversity is essential for human health. We raise our case and focus on the biomedicine services that are enabled by biodiversity, and we present known and novel approaches to promote biodiversity conservation.

Comparative metabolomic study of fungal foliar endophytes and their long-lived host Astrocaryum sciophilum: a model for exploring the chemodiversity of host-microbe interactions.

Introduction: In contrast to the dynamics observed in plant/pathogen interactions, endophytic fungi have the capacity to establish enduring associations within their hosts, leading to the development of a mutually beneficial relationship that relies on specialized chemical interactions. Research indicates that the presence of endophytic fungi has the ability to significantly modify the chemical makeup of the host organism. Our hypothesis proposes the existence of a reciprocal exchange of chemical signals between plants and fungi, facilitated by specialized chemical processes that could potentially manifest within the tissues of the host. This research aimed to precisely quantify the portion of the cumulative fungal endophytic community's metabolome detectable within host leaves, and tentatively evaluate its relevance to the host-endophyte interplay. The understory palm Astrocaryum sciophilum (Miq.) Pulle was used as a interesting host plant because of its notable resilience and prolonged life cycle, in a tropical ecosystem. Method: Using advanced metabolome characterization, including UHPLC-HRMS/MS and molecular networking, the study explored enriched metabolomes of both host leaves and 15 endophytic fungi. The intention was to capture a metabolomic "snapshot" of both host and endophytic community, to achieve a thorough and detailed analysis. Results and discussion: This approach yielded an extended MS-based molecular network, integrating diverse metadata for identifying host- and endophyte-derived metabolites. The exploration of such data (>24000 features in positive ionization mode) enabled effective metabolome comparison, yielding insights into cultivable endophyte chemodiversity and occurrence of common metabolites between the holobiont and its fungal communities. Surprisingly, a minor subset of features overlapped between host leaf and fungal samples despite significant plant metabolome enrichment. This indicated that fungal metabolic signatures produced in vitro remain sparingly detectable in the leaf. Several classes of primary metabolites were possibly shared. Specific fungal metabolites and/or compounds of their chemical classes were only occasionally discernible in the leaf, highlighting endophytes partial contribution to the overall holobiont metabolome. To our knowledge, the metabolomic study of a plant host and its microbiome has rarely been performed in such a comprehensive manner. The general analytical strategy proposed in this paper seems well-adapted for any study in the field of microbial- or microbiome-related MS and can be applied to most host-microbe interactions.

Metabolomic- and Molecular Networking-Based Exploration of the Chemical Responses Induced in Citrus sinensis Leaves Inoculated with Xanthomonas citri.

Citrus canker, caused by the bacterium Xanthomonas citri subsp. citri (X. citri), is a plant disease affecting Citrus crops worldwide. However, little is known about defense compounds in Citrus. Here, we conducted a mass spectrometry-based metabolomic approach to obtain an overview of the chemical responses of Citrus leaves to X. citri infection. To facilitate result interpretation, the multivariate analyses were combined with molecular networking to identify biomarkers. Metabolite variations among untreated and X. citri-inoculated Citrus samples under greenhouse conditions highlighted induced defense biomarkers. Notably, the plant tryptophan metabolism pathway was activated, leading to the accumulation of N-methylated tryptamine derivatives. This finding was subsequently confirmed in symptomatic leaves in the field. Several tryptamine derivatives showed inhibitory effects in vitro against X. citri. This approach has enabled the identification of new chemically related biomarker groups and their dynamics in the response of Citrus leaves to Xanthomonas infection.

Inventa: A computational tool to discover structural novelty in natural extracts libraries.

Collections of natural extracts hold potential for the discovery of novel natural products with original modes of action. The prioritization of extracts from collections remains challenging due to the lack of a workflow that combines multiple-source information to facilitate the data interpretation. Results from different analytical techniques and literature reports need to be organized, processed, and interpreted to enable optimal decision-making for extracts prioritization. Here, we introduce Inventa, a computational tool that highlights the structural novelty potential within extracts, considering untargeted mass spectrometry data, spectral annotation, and literature reports. Based on this information, Inventa calculates multiple scores that inform their structural potential. Thus, Inventa has the potential to accelerate new natural products discovery. Inventa was applied to a set of plants from the Celastraceae family as a proof of concept. The Pristimera indica (Willd.) A.C.Sm roots extract was highlighted as a promising source of potentially novel compounds. Its phytochemical investigation resulted in the isolation and de novo characterization of thirteen new dihydro-ß-agarofuran sesquiterpenes, five of them presenting a new 9-oxodihydro-ß-agarofuran base scaffold.

MEMO: Mass Spectrometry-Based Sample Vectorization to Explore Chemodiverse Datasets.

In natural products research, chemodiverse extracts coming from multiple organisms are explored for novel bioactive molecules, sometimes over extended periods. Samples are usually analyzed by liquid chromatography coupled with fragmentation mass spectrometry to acquire informative mass spectral ensembles. Such data is then exploited to establish relationships among analytes or samples (e.g., via molecular networking) and annotate metabolites. However, the comparison of samples profiled in different batches is challenging with current metabolomics methods since the experimental variation-changes in chromatographical or mass spectrometric conditions - hinders the direct comparison of the profiled samples. Here we introduce MEMO-MS2 BasEd SaMple VectOrization-a method allowing to cluster large amounts of chemodiverse samples based on their LC-MS/MS profiles in a retention time agnostic manner. This method is particularly suited for heterogeneous and chemodiverse sample sets. MEMO demonstrated similar clustering performance as state-of-the-art metrics considering fragmentation spectra. More importantly, such performance was achieved without the requirement of a prior feature alignment step and in a significantly shorter computational time. MEMO thus allows the comparison of vast ensembles of samples, even when analyzed over long periods of time, and on different chromatographic or mass spectrometry platforms. This new addition to the computational metabolomics toolbox should drastically expand the scope of large-scale comparative analysis.

Targeted Isolation of Antibiotic Brominated Alkaloids from the Marine Sponge Pseudoceratina durissima Using Virtual Screening and Molecular Networking.

Many targeted natural product isolation approaches rely on the use of pre-existing bioactivity information to inform the strategy used for the isolation of new bioactive compounds. Bioactivity information can be available either in the form of prior assay data or via Structure Activity Relationship (SAR) information which can indicate a potential chemotype that exhibits a desired bioactivity. The work described herein utilizes a unique method of targeted isolation using structure-based virtual screening to identify potential antibacterial compounds active against MRSA within the marine sponge order Verongiida. This is coupled with molecular networking-guided, targeted isolation to provide a novel drug discovery procedure. A total of 12 previously reported bromotyrosine-derived alkaloids were isolated from the marine sponge species Pseudoceratina durissima, and the compound, (+)-aeroplysinin-1 (1) displayed activity against the MRSA pathogen (MIC: <32 µg/mL). The compounds (1−3, 6 and 9) were assessed for their central nervous system (CNS) interaction and behavioral toxicity to zebrafish (Danio rerio) larvae, whereby several of the compounds were shown to induce significant hyperactivity. Anthelmintic activity against the parasitic nematode Haemonchus contorutus was also evaluated (2−4, 6−8).

The LOTUS initiative for open knowledge management in natural products research.

Contemporary bioinformatic and chemoinformatic capabilities hold promise to reshape knowledge management, analysis and interpretation of data in natural products research. Currently, reliance on a disparate set of non-standardized, insular, and specialized databases presents a series of challenges for data access, both within the discipline and for integration and interoperability between related fields. The fundamental elements of exchange are referenced structure-organism pairs that establish relationships between distinct molecular structures and the living organisms from which they were identified. Consolidating and sharing such information via an open platform has strong transformative potential for natural products research and beyond. This is the ultimate goal of the newly established LOTUS initiative, which has now completed the first steps toward the harmonization, curation, validation and open dissemination of 750,000+ referenced structure-organism pairs. LOTUS data is hosted on Wikidata and regularly mirrored on https://lotus.naturalproducts.net. Data sharing within the Wikidata framework broadens data access and interoperability, opening new possibilities for community curation and evolving publication models. Furthermore, embedding LOTUS data into the vast Wikidata knowledge graph will facilitate new biological and chemical insights. The LOTUS initiative represents an important advancement in the design and deployment of a comprehensive and collaborative natural products knowledge base.

Comparison of Illicit Drug Seizures Products of Natural Origin Using a Molecular Networking Approach.

Drug powder composition analysis is of particular interest in forensic investigations to identify illicit substance content, cutting agents and impurities. Powder profiling is difficult to implement due to multiple analytical methods requirement and remains a challenge for forensic toxicology laboratories. Furthermore, visualization tools allowing seizure products identification appear to be under-used to date. The aim of this study is to present the utility of molecular networking for the composition establishment of natural origin drugs. A powder suspected to contain heroin and three powders suspected to contain cocaine obtained from law enforcement agency seizures were analyzed using untargeted screening by liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS/MS). Molecular networking and metabolite annotation applied to suspected heroin sample allowed rapid confirmation of its illicit content (heroin), the identification of structurally related major impurities (6-monoacetylmorphine, 6-monoacetylcodeine, noscapine, and papaverine), as well as cutting agents (acetaminophen and caffeine). The cocaine powder profiling allowed the comparison of its constituents in a semi-quantitative manner (cocaine, benzoylecgonine, trans/cis-cinnamoylcocaine, trimethoxycocaine, hexanoylecgonine methylester, caffeine, hydroxyzine, levamisole, and phenacetin), bringing additional information for their identification, including geographically sourcing of natural product and their putative place in the supply chain. Although this approach does not replace the profiling techniques used by forensic laboratories, the use of molecular networks provides a visual overview of structurally related constituents which aids the comparison and investigation of seizure powders. Molecular networks offers here an ideal way to depict structurally related and unrelated compounds in these often complex mixtures of chemicals.

Metabolomics in Ecology and Bioactive Natural Products Discovery: Challenges and Prospects for a Comprehensive Study of the Specialised Metabolome.

Metabolomics is playing an increasingly prominent role in chemical ecology and in the discovery of bioactive natural products (NPs). The identification of metabolites is a common/central objective in both research fields. NPs have significant biological properties and play roles in multiple chemical-ecological interactions. Classically, in pharmacognosy, their chemical structure is determined after a complex process of isolating and interpreting spectroscopic data. With the advent of powerful analytical techniques such as liquid chromatography-mass spectrometry (LC-MS) the annotation process of the specialised metabolome of plants and microorganisms has improved considerably. In this article, we summarise the possibilities opened by these advances and illustrate how we harnessed them in our own research to automate annotations of NPs and target the isolation of key compounds. In addition, we are also discussing the analytical and computational challenges associated with these emerging approaches and their perspective.

Open and reusable annotated mass spectrometry dataset of a chemodiverse collection of 1,600 plant extracts.

As privileged structures, natural products often display potent biological activities. However, the discovery of novel bioactive scaffolds is often hampered by the chemical complexity of the biological matrices they are found in. Large natural extract collections are thus extremely valuable for their chemical novelty potential but also complicated to exploit in the frame of drug-discovery projects. In the end, it is the pure chemical substances that are desired for structural determination purposes and bioactivity evaluation. Researchers interested in the exploration of large and chemodiverse extract collections should thus establish strategies aiming to efficiently tackle such chemical complexity and access these structures. Establishing carefully crafted digital layers documenting the spectral and chemical complexity as well as bioactivity results of natural extracts collections can help prioritize time-consuming but mandatory isolation efforts. In this note, we report the results of our initial exploration of a collection of 1,600 plant extracts in the frame of a drug-discovery effort. After describing the taxonomic coverage of this collection, we present the results of its liquid chromatography high-resolution mass spectrometric profiling and the exploitation of these profiles using computational solutions. The resulting annotated mass spectral dataset and associated chemical and taxonomic metadata are made available to the community, and data reuse cases are proposed. We are currently continuing our exploration of this plant extract collection for drug-discovery purposes (notably looking for novel antitrypanosomatids, anti-infective and prometabolic compounds) and ecometabolomics insights. We believe that such a dataset can be exploited and reused by researchers interested in computational natural products exploration.

Combination of Pseudo-LC-NMR and HRMS/MS-Based Molecular Networking for the Rapid Identification of Antimicrobial Metabolites From Fusarium petroliphilum.

An endophytic fungal strain isolated from a seagrass endemic to the Mediterranean Sea (Posidonia oceanica) was studied in order to identify its antimicrobial constituents and further characterize the composition of its metabolome. It was identified as Fusarium petroliphilum by in-depth phylogenetic analyses. The ethyl acetate extract of that strain exhibited antimicrobial activities and an ability to inhibit quorum sensing of Staphylococcus aureus. To perform this study with a few tens of mg of extract, an innovative one-step generic strategy was devised. On one side, the extract was analyzed by UHPLC-HRMS/MS molecular networking for dereplication. On the other side, semi-preparative HPLC using a similar gradient profile was used for a single-step high-resolution fractionation. All fractions were systematically profiled by 1H-NMR. The data were assembled into a 2D contour map, which we call "pseudo-LC-NMR," and combined with those of UHPLC-HRMS/MS. This further highlighted the connection within structurally related compounds, facilitated data interpretation, and provided an unbiased quantitative profiling of the main extract constituents. This innovative strategy led to an unambiguous characterization of all major specialized metabolites of that extract and to the localization of its bioactive compounds. Altogether, this approach identified 22 compounds, 13 of them being new natural products and six being inhibitors of the quorum sensing mechanism of S. aureus and Pseudomonas aeruginosa. Minor analogues were also identified by annotation propagation through the corresponding HRMS/MS molecular network, which enabled a consistent annotation of 27 additional metabolites. This approach was designed to be generic and applicable to natural extracts of the same polarity range.

Alkyl-Quinolones derivatives as potential biomarkers for Pseudomonas aeruginosa infection chronicity in Cystic Fibrosis.

In Cystic Fibrosis (CF), a rapid and standardized definition of chronic infection would allow a better management of Pseudomonas aeruginosa (Pa) infections, as well as a quick grouping of patients during clinical trials allowing better comparisons between studies. With this purpose, we compared the metabolic profiles of 44 in vitro cultures of Pa strains isolated from CF patients at different stages of infection in order to identify metabolites differentially synthetized according to these clinical stages. Compounds produced and secreted by each strain in the supernatant of a liquid culture were analysed by metabolomic approaches (UHPLC-DAD-ESI/QTOF, UV and UPLC-Orbitrap, MS). Multivariate analyses showed that first colonization strains could be differentiated from chronic colonization ones, by producing notably more Alkyl-Quinolones (AQs) derivatives. Especially, five AQs were discriminant: HQC5, HQNOC7, HQNOC7:1, db-PQS C9 and HQNOC9:1. However, the production of HHQ was equivalent between strain types. The HHQ/HQNOC9:1 ratio was then found to be significantly different between chronic and primo-colonising strains by using both UV (p = 0.003) and HRMS data (p = 1.5 × 10-5). Our study suggests that some AQ derivatives can be used as biomarkers for an improved management of CF patients as well as a better definition of the clinical stages of Pa infection.