Microbial strain prioritization using metabolomics tools for the discovery of natural products

Comparative metabolomics study on the secondary metabolites of the red alga, Corallina officinalis and its associated endosymbiotic fungi

Marine endosymbionts have gained remarkable interest in the last three decades in terms of natural products (NPs) isolated thereof, emphasizing the chemical correlations with those isolated from the host marine organism. The current study aimed to conduct comparative metabolic profiling of the marine red algae Corallina officinalis, and three fungal endosymbionts isolated from its inner tissues namely, Aspergillus nidulans, A. flavipes and A. flavus. The ethyl acetate (EtOAc) extracts of the host organism as well as the isolated endosymbionts were analyzed using ultra-high performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-MS/MS)in both positive and negative ion modes, applying both full scan (FS) and all ion fragmentation (AIF) modes. Extensive interpretation of the LC-MS/MS spectra had led to the identification of 76 metabolites belonging to different phytochemical classes including alkaloids, polyketides, sesquiterpenes, butyrolactones, peptides, fatty acids, isocoumarins, quinones, among others. Metabolites were tentatively identified by comparing the accurate mass and fragmentation pattern with metabolites previously reported in the literature, as well as bioinformatics analysis using GNPS. A relationship between the host C. officinalis and its endophytes (A. flavus, A. nidulans, and A. flavipes) was discovered. C. officinalis shares common metabolites with at least one of the three endosymbiotic fungi. Some metabolites have been identified in endophytes and do not exist in their host. Multivariate analysis (MVA) revealed discrimination of A. flavipes from Corallina officinalis and other associated endophytic Aspergillus fungi (A. flavus and A. nidulans).

Multivariate analysis for data mining to characterize poultry house environment in winter

The processing and analysis of massive high-dimensional datasets are important issues in precision livestock farming (PLF). This study explored the use of multivariate analysis tools to analyze environmental data from multiple sensors located throughout a broiler house. An experiment was conducted to collect a comprehensive set of environmental data including particulate matter (TSP, PM10, and PM2.5), ammonia, carbon dioxide, air temperature, relative humidity, and in-cage and aisle wind speeds from 60 locations in a typical commercial broiler house. The dataset was divided into 3 growth phases (wk 1-3, 4-6, and 7-9). Spearman's correlation analysis and principal component analysis (PCA) were used to investigate the latent associations between environmental variables resulting in the identification of variables that played important roles in indoor air quality. Three cluster analysis methods; k-means, k-medoids, and fuzzy c-means cluster analysis (FCM), were used to group the measured parameters based on their environmental impact in the broiler house. In general, the Spearman and PCA results showed that the in-cage wind speed, aisle wind speed, and relative humidity played critical roles in indoor air quality distribution during broiler rearing. All 3 clustering methods were found to be suitable for grouping data, with FCM outperforming the other 2. Using data clustering, the broiler house spaces were divided into 3, 2, and 2 subspaces (clusters) for wk 1 to 3, 4 to 6, and 7 to 9, respectively. The subspace in the center of the house had a poorer air quality than other subspaces.

Strain-specific metabolomic diversity of Lactiplantibacillus plantarum under aerobic and anaerobic conditions

The chemotaxonomic diversity of 20 Lactiplantibacillus plantarum strains was investigated using non-targeted metabolite profiling under different culture conditions. Multivariate and metabolic pathway analyses based on GC-MS and LC-MS/MS datasets showed that amino acid metabolism, especially 2-hydroxy acids, was enriched under aerobic conditions (AE), whereas fatty acid & sugar metabolism was increased under anaerobic conditions (AN). Based on the metabolite profiles, L. plantarum strains were clustered into three main groups (A, B, and C). Overall, 79 and 83 significantly discriminant metabolites were characterized as chemical markers of AE and AN growth conditions, respectively. Notably, alcohols were more abundant in group A whereas amino acids, peptides, purines, and pyrimidines were significantly higher in group C. 2-hydroxy acids and oxylipins biosynthesized through amino acid and fatty acid metabolism, respectively, were more abundant in groups A and B. Furthermore, we observed a strong correlation between the chemical diversity of L. plantarum groups and their antioxidant activity from metabolite extracts. We propose a non-targeted metabolomic workflow to comprehensively characterize the chemodiversity of L. plantarum strain under different culture conditions, which may help reveal specific biomarkers of individual strains depending on the culture conditions.

Structural identification of pyridinopyrone compounds with anti-neuroinflammatory activity from streptomyces sulphureus DSM 40104

This study investigated the chemical composition and biosynthesis pathway of compounds produced by Streptomyces sulphureus DSM 40104. With the guild of molecular networking analysis, we isolated and identified six uncommon structural characteristics of compounds, including four newly discovered pyridinopyrones. Based on genomic analysis, we proposed a possible hybrid NRPS-PKS biosynthesis pathway for pyridinopyrones. Notably, this pathway starts with the use of nicotinic acid as the starting unit, which is a unique feature. Compounds 1-3 exhibited moderate anti-neuroinflammatory activity against LPS-induced BV-2 cell inflammation. Our study demonstrates the diversity of polyene pyrone compounds regarding their chemical structure and bioactivity while providing new insights into their biosynthesis pathway. These findings may lead to the development of new treatments for inflammation-related diseases.

The use of nitrogen-15 in microbial natural product discovery and biosynthetic characterization

This mini-review covers the use of nitrogen-15 in bacterial and fungal natural product discovery and biosynthetic characterization from 1970 to 2022. Nitrogen is an important element in a number of bioactive and structurally intriguing natural products including alkaloids, non-ribosomal peptides, and hybrid natural products. Nitrogen-15 can be detected at natural abundance utilizing two-dimensional nuclear magnetic resonance and mass spectrometry. Additionally, it is a stable isotope that can be added to growth media for both filamentous fungi and bacteria. With stable isotope feeding, additional two-dimensional nuclear magnetic resonance and mass spectrometry strategies have become available, and there is a growing trend to use nitrogen-15 stable isotope feeding for the biosynthetic characterization of natural products. This mini-review will catalog the use of these strategies, analyze the strengths and weaknesses of the different approaches, and suggest future directions for the use of nitrogen-15 in natural product discovery and biosynthetic characterization.

Constructing a Myxobacterial Natural Product Database to Facilitate NMR-Based Metabolomics Bioprospecting of Myxobacteria

Myxobacteria are fascinating prokaryotes featuring a potent capacity for producing a wealth of bioactive molecules with intricate chemical topology as well as intriguing enzymology, and thus it is critical to developing an efficient pipeline for bioprospecting. Herein, we construct the database MyxoDB, the first public compendium solely dedicated to myxobacteria, which enabled us to provide an overview of the structural diversity and taxonomic distribution of known myxobacterial natural products. Moreover, we demonstrated that the cutting-edge NMR-based metabolomics was effective to differentiate the biosynthetic priority of myxobacteria, whereby MyxoDB could greatly streamline the dereplication of multifarious known compounds and accordingly speed up the discovery of new compounds. This led to the rapid identification of a class of linear di-lipopeptides (archangimins) and a rare rearranged sterol (corasterol) that were endowed with unique chemical architectures and/or biosynthetic enzymology. We also showcased that NMR-based metabolomics, MyxoDB, and genomics can also work concertedly to accelerate the targeted discovery of a polyketidic compound pyxipyrrolone C. All in all, this study sets the stage for the discovery of many more novel natural products from underexplored myxobacterial resources.

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.

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

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

Marine bioactive compounds as antibiofilm agent: a metabolomic approach

The ocean is a treasure trove of both living and nonliving creatures, harboring incredibly diverse group of organisms. A plethora of marine sourced bioactive compounds are discovered over the past few decades, many of which are found to show antibiofilm activity. These are of immense clinical significance since the formation of microbial biofilm is associated with the development of high antibiotic resistance. Biofilms are also responsible to bring about problems associated with industries. In fact, the toilets and wash-basins also show degradation due to development of biofilm on their surfaces. Antimicrobial resistance exhibited by the biofilm can be a potent threat not only for the health care unit along with industries and daily utilities. Various recent studies have shown that the marine members of various kingdom are capable of producing antibiofilm compounds. Many such compounds are with unique structural features and metabolomics approaches are essential to study such large sets of metabolites. Associating holobiome metabolomics with analysis of their chemical attribute may bring new insights on their antibiofilm effect and their applicability as a substitute for conventional antibiotics. The application of computer-aided drug design/discovery (CADD) techniques including neural network approaches and structured-based virtual screening, ligand-based virtual screening in combination with experimental validation techniques may help in the identification of these molecules and evaluation of their drug like properties.

Discovering New Natural Products Using Metabolomics-Based Approaches

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

Metabolomic Strategy to Characterize the Profile of Secondary Metabolites in Aspergillus aculeatus DL1011 Regulated by Chemical Epigenetic Agents

Chemical epigenetic regulation (CER) is an effective method to activate the silent pathway of fungal secondary metabolite synthesis. However, conventional methods for CER study are laborious and time-consuming. In the meantime, the overall profile of the secondary metabolites in the fungi treated by the CER reagent is not well characterized. In this study, suberohydroxamic acid (SBHA), a histone deacetylase inhibitor, was added to a culture of Aspergillus aculeatus DL1011 and a new strategy based on LC-MS/MS analysis integrated with various metabolomic tools (MetaboAnalyst, MS-DIAL, SIRIUS and GNPS) was developed to characterize the profile of induced metabolites. As a result, 13.6%, 29.5% and 27.2% of metabolites were identified as newly biosynthesized, increasing and decreasing in abundance by CER, respectively. The structures of the 18 newly induced secondary metabolites were further identified by the new strategy to demonstrate that 72.2% of them (1 novel compound and 12 known compounds) were first discovered in A. aculeatus upon SBHA treatment. The accuracy of the new approach was confirmed by purification and NMR data analysis of major newly biosynthesized secondary metabolites. The bioassay showed that the newly biosynthesized compounds, roseopurpurin analogues, showed selective activities against DPPH scavenging, cytotoxicity and SHP1 inhibition. Our research demonstrated that CER was beneficial for changing the secondary metabolic profile of fungi and was an effective means of increasing the diversity of active metabolites. Our work also supplied a metabolomic strategy to characterize the profile changes and determine the newly induced compounds in the secondary metabolites of fungi treated with the chemical epigenetic regulator.

Targeted Metabolomics and High-Throughput RNA Sequencing-Based Transcriptomics Reveal Massive Changes in the Streptomyces venezuelae NRRL B-65442 Metabolism Caused by Ethanol Shock

The species Streptomyces venezuelae is represented by several distinct strains with variable abilities to biosynthesize structurally diverse secondary metabolites. In this work, we examined the effect of ethanol shock on the transcriptome and metabolome of Streptomyces venezuelae NRRL B-65442 using high-throughput RNA sequencing (RNA-seq) and high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS). Ethanol shock caused massive changes in the gene expression profile, differentially affecting genes for secondary metabolite biosynthesis and central metabolic pathways. Most of the data from the transcriptome analysis correlated well with the metabolome changes, including the overproduction of jadomycin congeners and a downshift in the production of desferrioxamines, legonoxamine, foroxymithin, and a small cryptic ribosomally synthesized peptide. Some of the metabolome changes, such as the overproduction of chloramphenicol, could not be explained by overexpression of the cognate biosynthetic genes but correlated with the expression profiles of genes for precursor biosynthesis. Changes in the transcriptome were also observed for several genes known to play a role in stress response in other bacteria and included at least 10 extracytoplasmic function σ factors. This study provides important new insights into the stress response in antibiotic-producing bacteria and will help to understand the complex mechanisms behind the environmental factor-induced regulation of secondary metabolite biosynthesis. IMPORTANCE Streptomyces spp. are filamentous Gram-positive bacteria known as versatile producers of secondary metabolites, of which some have been developed into human medicines against infections and cancer. The genomes of these bacteria harbor dozens of gene clusters governing the biosynthesis of secondary metabolites (BGCs), of which most are not expressed under laboratory conditions. Detailed knowledge of the complex regulation of BGC expression is still lacking, although certain growth conditions are known to trigger the production of previously undetected secondary metabolites. In this work, we investigated the effect of ethanol shock on the production of secondary metabolites by Streptomyces venezuelae and correlated these findings with the expression of cognate BGCs and primary metabolic pathways involved in the generation of cofactors and precursors. The findings of this study set the stage for the rational manipulation of bacterial genomes aimed at enhanced production of industrially important bioactive natural products.

LC-PDA-MS/MS-Based Dereplication Guided Isolation of a New Optical Isomer of 19,20-Epoxycytochalasin-N and Its Cytotoxic Activity

The Rosellinia sanctae-cruciana extract was subjected to detailed liquid chromatography tandem mass spectrometry studies. A total of 38 peaks were annotated to m/z 508.26, m/z 510.28, m/z 524.26, m/z 526.28, m/z 540.26, m/z 542.27, and m/z 584.28 [M + H]+. The accurate mass, mutually supported UV/vis spectra, and database search identified these compounds as cytochalasins. Systematic dereplication helped identify a peak at m/z 540.26 [M + H]+ as the new compound. Further, the identified compound was purified by high-performance liquid chromatography and characterized by 2D NMR to be 19,20-epoxycytochalasin N1, a new optical isomer of 19,20-epoxycytochalasin-N. It exhibited substantial cytotoxicity with IC50 values ranging from 1.34 to 19.02 μM. This study shows a fast approach for dereplicating and identifying novel cytochalasin metabolites in crude extracts.

Genome Mining and Metabolomics Unveil Pseudonochelin: A Siderophore Containing 5-Aminosalicylate from a Marine-Derived Pseudonocardia sp. Bacterium

Pseudonochelin (1), a siderophore from a marine-derived Pseudonocardia sp. bacterium, was discovered using genome mining and metabolomics technologies. A 5-aminosalicylic acid (5-ASA) unit, not previously found in siderophore natural products, was identified in 1. Annotation of a putative psn biosynthetic gene cluster combined with bioinformatics and isotopic enrichment studies enabled us to propose the biosynthesis of 1. Moreover, 1 was found to display in vitro and in vivo antibacterial activity in an iron-dependent fashion.

A secondary metabolite drives intraspecies antagonism in a gut symbiont that is inhibited by cell-wall acetylation

The mammalian microbiome encodes numerous secondary metabolite biosynthetic gene clusters; yet, their role in microbe-microbe interactions is unclear. Here, we characterized two polyketide synthase gene clusters (fun and pks) in the gut symbiont Limosilactobacillus reuteri. The pks, but not the fun, cluster encodes antimicrobial activity. Forty-one of 51 L. reuteri strains tested are sensitive to Pks products; this finding was independent of strains' host origin. Sensitivity to Pks was also established in intraspecies competition experiments in gnotobiotic mice. Comparative genome analyses between Pks-resistant and -sensitive strains identified an acyltransferase gene (act) unique to Pks-resistant strains. Subsequent cell-wall analysis of wild-type and act mutant strains showed that Act acetylates cell-wall components, providing resistance to Pks-mediated killing. Additionally, pks mutants lost their competitive advantage, while act mutants lost their Pks resistance in in vivo competition assays. These findings provide insight into how closely related gut symbionts can compete and co-exist in the gastrointestinal tract.

Automated Microbial Library Generation Using the Bioinformatics Platform IDBac

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

Metabolomics on the study of marine organisms

BACKGROUND

Marine ecosystems are hosts to a vast array of organisms, being among the most richly biodiverse locations on the planet. The study of these ecosystems is very important, as they are not only a significant source of food for the world but also have, in recent years, become a prolific source of compounds with therapeutic potential. Studies of aspects of marine life have involved diverse fields of marine science, and the use of metabolomics as an experimental approach has increased in recent years. As part of the "omics" technologies, metabolomics has been used to deepen the understanding of interactions between marine organisms and their environment at a metabolic level and to discover new metabolites produced by these organisms.

AIM OF REVIEW

This review provides an overview of the use of metabolomics in the study of marine organisms. It also explores the use of metabolomics tools common to other fields such as plants and human metabolomics that could potentially contribute to marine organism studies. It deals with the entire process of a metabolomic study, from sample collection considerations, metabolite extraction, analytical techniques, and data analysis. It also includes an overview of recent applications of metabolomics in fields such as marine ecology and drug discovery and future perspectives of its use in the study of marine organisms.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The review covers all the steps involved in metabolomic studies of marine organisms including, collection, extraction methods, analytical tools, statistical analysis, and dereplication. It aims to provide insight into all aspects that a newcomer to the field should consider when undertaking marine metabolomics.

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

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

Bacillimidazoles A-F, Imidazolium-Containing Compounds Isolated from a Marine Bacillus

Chemical investigations of a marine sponge-associated Bacillus revealed six new imidazolium-containing compounds, bacillimidazoles A-F (1-6). Previous reports of related imidazolium-containing natural products are rare. Initially unveiled by timsTOF (trapped ion mobility spectrometry) MS data, extensive HRMS and 1D and 2D NMR analyses enabled the structural elucidation of 1-6. In addition, a plausible biosynthetic pathway to bacillimidazoles is proposed based on isotopic labeling experiments and invokes the highly reactive glycolytic adduct 2,3-butanedione. Combined, the results of structure elucidation efforts, isotopic labeling studies and bioinformatics suggest that 1-6 result from a fascinating intersection of primary and secondary metabolic pathways in Bacillus sp. WMMC1349. Antimicrobial assays revealed that, of 1-6, only compound six displayed discernible antibacterial activity, despite the close structural similarities shared by all six natural products.

Novel Alkaloids from Marine Actinobacteria: Discovery and Characterization

The marine environment is an excellent resource for natural products with therapeutic potential. Its microbial inhabitants, often associated with other marine organisms, are specialized in the synthesis of bioactive secondary metabolites. Similar to their terrestrial counterparts, marine Actinobacteria are a prevalent source of these natural products. Here, we discuss 77 newly discovered alkaloids produced by such marine Actinobacteria between 2017 and mid-2021, as well as the strategies employed in their elucidation. While 12 different classes of alkaloids were unraveled, indoles, diketopiperazines, glutarimides, indolizidines, and pyrroles were most dominant. Discoveries were mainly based on experimental approaches where microbial extracts were analyzed in relation to novel compounds. Although such experimental procedures have proven useful in the past, the methodologies need adaptations to limit the chance of compound rediscovery. On the other hand, genome mining provides a different angle for natural product discovery. While the technology is still relatively young compared to experimental screening, significant improvement has been made in recent years. Together with synthetic biology tools, both genome mining and extract screening provide excellent opportunities for continued drug discovery from marine Actinobacteria.

Advances in Biosynthesis of Natural Products from Marine Microorganisms

Natural products play an important role in drug development, among which marine natural products are an underexplored resource. This review summarizes recent developments in marine natural product research, with an emphasis on compound discovery and production methods. Traditionally, novel compounds with useful biological activities have been identified through the chromatographic separation of crude extracts. New genome sequencing and bioinformatics technologies have enabled the identification of natural product biosynthetic gene clusters in marine microbes that are difficult to culture. Subsequently, heterologous expression and combinatorial biosynthesis have been used to produce natural products and their analogs. This review examines recent examples of such new strategies and technologies for the development of marine natural products.

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.

Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities

Covering: 2010 to 2021Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.

Sponge-associated sp. RM66 metabolome induction with N-acetylglucosamine: Antibacterial, antifungal and anti-trypanosomal activities

The marine sponge Amphimedon sp., collected from Hurghada (Egypt) was investigated for its sponge-derived actinomycetes diversity. Nineteen actinomycetes were cultivated and phylogenetically identified using 16S rDNA gene sequencing were carried out. The strains belong to genera Kocuria, Dietzia, Micrococcus, Microbacterium and Streptomyces. Many silent biosynthetic genes clusters were investigated using genome sequencing of actinomycete strains and has revealed in particular the genus Streptomyces that has indicated their exceptional capacity for the secondary metabolites production that not observed under classical cultivation conditions. In this study, the effect of N-acetylglucosamine on the metabolome of Streptomyces sp. RM66 was investigated using three actinomycetes media (ISP2, M1 and MA). In total, twelve extracts were produced using solid and liquid fermentation approaches. Liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS) data were analysed using metabolomics tools to compare natural product production across all crude extracts. Our study highlighted the elicitation effect of N-acetylglucosamine on the secondary metabolite profiles of Streptomyces sp. RM66. These results highlight the of N-acetylglucosamine application as an elicitor to induce the cryptic metabolites and for increasing the chemical diversity. All the twelve extracts were tested for their antibacterial activity was tested against Staphylococcus aureus NCTC 8325, antifungal activity against Candida albicans 5314 (ATCC 90028) and anti-trypanosomal activity against Trypanosoma brucei brucei. Extract St1 showed the most potent one with activities 2.3, 3.2 and 4.7 ug/ml as antibacterial, antifungal and anti-trypanosomal, respectively.

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

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

Biochemical characteristics and membrane fouling behaviors of soluble microbial products during the lifecycle of Escherichia coli

The complexity of production process and chemical compositions of soluble microbial products (SMPs) largely limits the understanding of membrane fouling in membrane bioreactors (MBRs). Herein, we used a model single-strain Escherichia coli to better understand the chemical natures of SMPs and their roles in membrane fouling. The effects of carbon source and growth phase on the chemical compositions of SMPs were identified at both the compound and molecular levels by using advanced techniques including excitation emission matrix and parallel factor analysis (EEM-PARAFAC), size exclusion chromatography coupled with organic carbon detection (LC-OCD), and untargeted ultra-performance liquid chromatography - Q-Exactive - mass spectrometry (UPLC-Q-Exactive-MS). Subsequently, the roles of SMPs in the propensity of membrane fouling during ultrafiltration (UF) were studied. The results showed that the chemical compositions and fouling potentials of SMPs were carbon source- and growth phase-dependent. In the exponential phase, SMPs mainly consisted of utilization-associated products (UAPs) and remaining substrates. As the microorganism progressed into the stationary and senescent phases, UAPs and biomass-associated products (BAPs) were the main components, respectively. The SMP contents generated in glucose medium were higher than those generated in acetate medium, and higher abundances of humic fluorescent components were observed in glucose-fed SMPs. Van Krevelen diagrams of the UPLC-MS results revealed that acetate-fed SMPs contained more carboxylic-rich alicyclic molecules, peptides-like, aromatic, and carbohydrates-like components than glucose-fed SMPs in the stationary and senescent phases. These components played a significant role in irreversible membrane fouling, as evidenced in UF experiments. Standard blocking and cake filtration were the main fouling mechanisms for the filtration of SMPs collected in the exponential and stationary/senescent phases, respectively. Our findings highlight linkages between SMP compositions and membrane fouling at both the compound and molecular levels and suggest that both the carbon source and growth phase strongly determine the production potential, chemical nature, and fouling behavior of SMPs.

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.

Metabolomic profiling, biological evaluation of Aspergillus awamori, the river Nile-derived fungus using epigenetic and OSMAC approaches

LC-HRMS-based metabolomics approach was applied to the river Nile-derived fungus Aspergillus awamori after its fermentation on four different media and using four epigenetic modifiers as elicitors. Thereafter, a comprehensive multivariate statistical analysis such as PCA, PLS-DA and OPLS-DA were employed to explain the generated metabolomic data (1587 features). PCA showed that the fungus displayed a unique chemical profile in each medium or elicitor. Additionally, PLS-DA results revealed the upregulated metabolites under each of these conditions. Results indicated that both rice and malt dextrose agar were recognized as the best media in terms of secondary metabolites diversity and showed better profiles than the four applied epigenetic modifiers, of which nicotinamide was the best secondary metabolite elicitor. Testing the antibacterial and cytotoxic effects of all A. awamori-derived extracts revealed that using epigenetic modifiers can induce antimicrobial metabolites against S. aureus and E. coli, whereas using rice, malt dextrose or nicotinamide can induce groups of cytotoxic metabolites. OPLS-DA results assisted in the putative identification of the induced metabolites that could be responsible for these observed inhibitory activities. This study highlighted how powerful the OSMAC approach in maximizing of the chemical diversity of a single organism. Furthermore, it revealed the power of metabolomics in tracing, profiling and categorizing such chemical diversity and even targeting the possible bioactive candidates which require further scaling up studies in the future.

LC-HRMS-based metabolomics approach was applied to the river Nile-derived fungus Aspergillus awamori after its fermentation on four different media and using four epigenetic modifiers as elicitors.

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.

A marine microbiome antifungal targets urgent-threat drug-resistant fungi

New antifungal drugs are urgently needed to address the emergence and transcontinental spread of fungal infectious diseases, such as pandrug-resistant Candida auris. Leveraging the microbiomes of marine animals and cutting-edge metabolomics and genomic tools, we identified encouraging lead antifungal molecules with in vivo efficacy. The most promising lead, turbinmicin, displays potent in vitro and mouse-model efficacy toward multiple-drug-resistant fungal pathogens, exhibits a wide safety index, and functions through a fungal-specific mode of action, targeting Sec14 of the vesicular trafficking pathway. The efficacy, safety, and mode of action distinct from other antifungal drugs make turbinmicin a highly promising antifungal drug lead to help address devastating global fungal pathogens such as C. auris.

hcapca: Automated Hierarchical Clustering and Principal Component Analysis of Large Metabolomic Datasets in R

Microbial natural product discovery programs face two main challenges today: rapidly prioritizing strains for discovering new molecules and avoiding the rediscovery of already known molecules. Typically, these problems have been tackled using biological assays to identify promising strains and techniques that model variance in a dataset such as PCA to highlight novel chemistry. While these tools have shown successful outcomes in the past, datasets are becoming much larger and require a new approach. Since PCA models are dependent on the members of the group being modeled, large datasets with many members make it difficult to accurately model the variance in the data. Our tool, hcapca, first groups strains based on the similarity of their chemical composition, and then applies PCA to the smaller sub-groups yielding more robust PCA models. This allows for scalable chemical comparisons among hundreds of strains with thousands of molecular features. As a proof of concept, we applied our open-source tool to a dataset with 1046 LCMS profiles of marine invertebrate associated bacteria and discovered three new analogs of an established anticancer agent from one promising strain.

On the Risks of Phylogeny-Based Strain Prioritization for Drug Discovery: Streptomyces lunaelactis as a Case Study

Strain prioritization for drug discovery aims at excluding redundant strains of a collection in order to limit the repetitive identification of the same molecules. In this work, we wanted to estimate what can be unexploited in terms of the amount, diversity, and novelty of compounds if the search is focused on only one single representative strain of a species, taking Streptomyces lunaelactis as a model. For this purpose, we selected 18 S. lunaelactis strains taxonomically clustered with the archetype strain S. lunaelactis MM109^T. Genome mining of all S. lunaelactis isolated from the same cave revealed that 54% of the 42 biosynthetic gene clusters (BGCs) are strain specific, and five BGCs are not present in the reference strain MM109^T. In addition, even when a BGC is conserved in all strains such as the bag/fev cluster involved in bagremycin and ferroverdin production, the compounds produced highly differ between the strains and previously unreported compounds are not produced by the archetype MM109^T. Moreover, metabolomic pattern analysis uncovered important profile heterogeneity, confirming that identical BGC predisposition between two strains does not automatically imply chemical uniformity. In conclusion, trying to avoid strain redundancy based on phylogeny and genome mining information alone can compromise the discovery of new natural products and might prevent the exploitation of the best naturally engineered producers of specific molecules.

Research Tales from the Clardy Laboratory: Function-Driven Natural Product Discovery

Over the past 70 years, the search for small molecules from nature has transformed biomedical research: natural products are the basis for half of all pharmaceuticals; the quest for total synthesis of natural products fueled development of methodologies for organic synthesis; and their biosynthesis presented unprecedented biochemical transformations, expanding our chemo-enzymatic toolkit. Initially, the discovery of small molecules was driven by bioactivity-guided fractionation. However, this approach yielded the frequent rediscovery of already known metabolites. As a result, focus shifted to identifying novel scaffolds through either structure-first methods or genome mining, relegating function as a secondary concern. Over the past two decades, the laboratory of Jon Clardy has taken an alternative route and focused on an ecology-driven, function-first approach in pursuit of uncovering bacterial small molecules with biological activity. In this review, we highlight several examples that showcase this ecology-first approach. Though the highlighted systems are diverse, unifying themes are (1) to understand how microbes interact with their host or environment, (2) to gain insights into the environmental roles of microbial metabolites, and (3) to explore pharmaceutical potential from these ecologically relevant metabolites.

Metabolomic-guided discovery of cyclic nonribosomal peptides from Xylaria ellisii sp. nov., a leaf and stem endophyte of Vaccinium angustifolium

Fungal endophytes are sources of novel bioactive compounds but relatively few agriculturally important fruiting plants harboring endophytes have been carefully studied. Previously, we identified a griseofulvin-producing Xylaria species isolated from Vaccinium angustifolium, V. corymbosum, and Pinus strobus. Morphological and genomic analysis determined that it was a new species, described here as Xylaria ellisii. Untargeted high-resolution LC-MS metabolomic analysis of the extracted filtrates and mycelium from 15 blueberry isolates of this endophyte revealed differences in their metabolite profiles. Toxicity screening of the extracts showed that bioactivity was not linked to production of griseofulvin, indicating this species was making additional bioactive compounds. Multivariate statistical analysis of LC-MS data was used to identify key outlier features in the spectra. This allowed potentially new compounds to be targeted for isolation and characterization. This approach resulted in the discovery of eight new proline-containing cyclic nonribosomal peptides, which we have given the trivial names ellisiiamides A-H. Three of these peptides were purified and their structures elucidated by one and two-dimensional nuclear magnetic resonance spectroscopy (1D and 2D NMR) and high-resolution tandem mass spectrometry (HRMS/MS) analysis. The remaining five new compounds were identified and annotated by high-resolution mass spectrometry. Ellisiiamide A demonstrated Gram-negative activity against Escherichia coli BW25113, which is the first reported for this scaffold. Additionally, several known natural products including griseofulvin, dechlorogriseofulvin, epoxy/cytochalasin D, zygosporin E, hirsutatin A, cyclic pentapeptides #1–2 and xylariotide A were also characterized from this species.

Bioassay- and metabolomics-guided screening of bioactive soil actinomycetes from the ancient city of Ihnasia, Egypt

Literature surveys, taxonomical differences, and bioassay results have been utilized in the discovery of new natural products to aid in Actinomycetes isolate-selection. However, no or less investigation have been done on establishing the differences in metabolomic profiles of the isolated microorganisms. The study aims to utilise bioassay- and metabolomics-guided tools that included dereplication study and multivariate analysis of the NMR and mass spectral data of microbial extracts to assist the selection of isolates for scaling-up the production of antimicrobial natural products. A total of 58 actinomycetes were isolated from different soil samples collected from Ihnasia City, Egypt and screened for their antimicrobial activities against indicator strains that included Bacillus subtilis, Escherichia coli, methicillin-resistant Staphylococcus aureus and Candida albicans. A number of 25 isolates were found to be active against B. subtilis and/or to at least one of the tested indicator strains. Principal component analyses showed chemical uniqueness for four outlying bioactive actinomycetes extracts. In addition, Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) and dereplication study led us to further select two outlying anti-MRSA active isolates MS.REE.13 and 22 for scale-up work. MS.REE.13 and 22 exhibited zones of inhibition at 19 and 13 mm against MRSA, respectively. A metabolomics-guided approach provided the steer to target the bioactive metabolites (P<0.01) present in a crude extract or fraction even at nanogram levels but it was a challenge that such low-yielding bioactive natural products would be feasible to isolate. Validated to occur only on the active side of OPLS-DA loadings plot, the isolated compounds exhibited medium to weak antibiotic activity with MIC values between 250 and 800 μM. Two new compounds, P_24306 (C₁₀H₁₃N₂) and N_12799 (C₁₈H₃₂O₃) with MICs of 795 and 432 μM, were afforded from the scale-up of MS.REE. 13 and 22, respectively.

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.

Phallusialides A-E, Pyrrole-Derived Alkaloids Discovered from a Marine-Derived Micromonospora sp. Bacterium Using MS-Based Metabolomics Approaches

Integrating MS-based metabolomics approaches, LC-MS-PCA and molecular networking enabled the targeted isolation of five new pyrrole-derived alkaloids, phallusialides A-E (1-5), from a marine-derived Micromonospora sp. bacterium. The structures of 1-5 were elucidated by analysis of their HRMS, MS/MS, and NMR spectroscopic data. The absolute configuration of phallusialide A (1) was determined on the basis of comparisons of experimental and theoretically calculated ECD spectra. Compounds 1 and 2 exhibited antibacterial activity against methicillin resistant S. aureus (MRSA) and E. coli, with MIC values of 32 and 64 μg/mL, respectively, whereas 3-5 showed no antibacterial activity even at 256 μg/mL, yielding important SAR insights for this class of compounds.

Composite score analysis for unsupervised comparison and network visualization of metabolomics data

Metabolomics-based approaches are becoming increasingly popular to interrogate the chemical basis for phenotypic differences in biological systems. Successful metabolomics studies employ multivariate data analysis to compare large and highly complex datasets. A primary tool for unsupervised statistical analyses, principal component analysis (PCA), relies on the selection of a subsection of a maximum of three components from a larger model to visually represent similarity. The use of only three principal components limits the comprehensiveness of the model and can mask discrimination between samples. We have developed a new statistical metric, the composite score (CS), as a univariate statistic that incorporates multiple principal components to calculate a correlation matrix that enables quantitative comparisons of sample similarity between samples within one dataset based upon measured metabolome profiles. Composite score values were tabulated using profiles of complex extracts of dietary supplements from the plant Hydrastis canadensis (goldenseal) as a case study. Several outliers were unambiguously identified, and a PCA composite score network was developed to provide a graphical representation of the composite score matrix. Comparison with visualization using PCA score plots or dendrograms from hierarchical clustering analysis (HCA) demonstrates the utility of the composite score to as a tool for metabolomics studies that seek to quantify similarity among samples. An R-script for the calculation of composite score has been made available.

An Isotopic Ratio Outlier Analysis Approach for Global Metabolomics of Biosynthetically Talented Actinomycetes

Actinomycetes are powerhouses of natural product biosynthesis. Full realization of this biosynthetic potential requires approaches for recognizing novel metabolites and determining mediators of metabolite production. Herein, we develop an isotopic ratio outlier analysis (IROA) ultra-high performance liquid chromatography-mass spectrometry (UHPLC/MS) global metabolomics strategy for actinomycetes that facilitates recognition of novel metabolites and evaluation of production mediators. We demonstrate this approach by determining impacts of the iron chelator 2,2′-bipyridyl on the Nocardiopsis dassonvillei metabolome. Experimental and control cultures produced metabolites with isotopic carbon signatures that were distinct from corresponding “standard” culture metabolites, which were used as internal standards for LC/MS. This provided an isotopic MS peak pair for each metabolite, which revealed the number of carbon atoms and relative concentrations of metabolites and distinguished biosynthetic products from artifacts. Principal component analysis (PCA) and random forest (RF) differentiated bipyridyl-treated samples from controls. RF mean decrease accuracy (MDA) values supported perturbation of metabolites from multiple amino acid pathways and novel natural products. Evaluation of bipyridyl impacts on the nocazine/XR334 diketopiperazine (DKP) pathway revealed upregulation of amino acid precursors and downregulation of late stage intermediates and products. These results establish IROA as a tool in the actinomycete natural product chemistry arsenal and support broad metabolic consequences of bipyridyl.

A metabolomics-guided approach to discover Fusarium graminearum metabolites after removal of a repressive histone modification

Many secondary metabolites are produced by biosynthetic gene clusters (BGCs) that are repressed during standard growth conditions, which complicates the discovery of novel bioactive compounds. In the genus Fusarium, many BGCs reside in chromatin enriched for trimethylated histone 3 lysine 27 (H3K27me3), a modification correlated with transcriptional gene silencing. Here we report on our progress in assigning metabolites to genes by using a strain lacking the H3K27 methyltransferase, Kmt6. To guide isolation efforts, we coupled genetics to multivariate analysis of liquid chromatography-mass spectrometry (LCMS) data from both wild type and kmt6, which allowed identification of compounds previously unknown from F. graminearum. We found low molecular weight, amino acid-derived metabolites (N-ethyl anthranilic acid, N-phenethylacetamide, N-acetyltryptamine). We identified one new compound, protofusarin, as derived from fusarin biosynthesis. Similarly, we isolated large amounts of fusaristatin A, gibepyrone A, and fusarpyrones A and B, simply by using the kmt6 mutant, instead of having to optimize growth media. To increase the abundance of metabolites underrepresented in wild type, we generated kmt6 fus1 double mutants and discovered tricinolone and tricinolonoic acid, two new sesquiterpenes belonging to the tricindiol class. Our approach allows rapid visualization and analyses of the genetically induced changes in metabolite production, and discovery of new molecules by a combination of chemical and genetic dereplication. Of 22 fungal metabolites identified here, 10 compounds had not been reported from F. graminearum before. We show that activating silent metabolic pathways by mutation of a repressive chromatin modification enzyme can result in the discovery of new chemistry even in a well-studied organism, and helps to connect new or known small molecules to the BGCs responsible for their production.

Microbial Diversity and Chemical Multiplicity of Culturable, Taxonomically Similar Bacterial Symbionts of the Leaf-Cutting Ant Acromyrmex coronatus

Insects are a highly diverse group, exploit a wide range of habitats, and harbor bacterial symbionts of largely unknown diversity. Insect-associated bacterial symbionts are underexplored but promising sources of bioactive compounds. The community of culturable bacteria associated with the leaf-cutting ant Acromyrmex coronatus (Fabricius) and the diversity of their metabolites produced were investigated. Forty-six phylotypes belonging to Actinobacteria, Firmicutes, and Proteobacteria were identified. The chemical profiles of 65 isolates were further analyzed by LC-MS/MS, and principal components analysis (PCA) was used to group the isolates according to their chemical profiles. Historically, selection of bacterial strains for drug discovery has been based on phenotypic and/or genotypic traits. Use of such traits may well impede the discovery of new compounds; in this study, several indistinguishable phylotypes cultured in identical nutritional and environmental conditions produced completely different chemical profiles. Our data also demonstrated the wide chemical diversity to be explored in insect-associated symbionts.

LC-HRMS-Database Screening Metrics for Rapid Prioritization of Samples to Accelerate the Discovery of Structurally New Natural Products

In order to accelerate the isolation and characterization of structurally new or novel secondary metabolites, it is crucial to develop efficient strategies that prioritize samples with greatest promise early in the workflow so that resources can be utilized in a more efficient and cost-effective manner. We have developed a metrics-based prioritization approach using exact LC-HRMS, which uses data for 24 618 marine natural products held in the PharmaSea database. Each sample was evaluated and allocated a metric score by a software algorithm based on the ratio of new masses over the total (sample novelty), ratio of known masses over the total (chemical novelty), number of peaks above a defined peak area threshold (sample complexity), and peak area (sample diversity). Samples were then ranked and prioritized based on these metric scores. To validate the approach, eight marine sponges and six tunicate samples collected from the Fiji Islands were analyzed, metric scores calculated, and samples targeted for isolation and characterization of new compounds. Structures of new compounds were elucidated by spectroscopic techniques, including 1D and 2D NMR, MS, and MS/MS. Structures were confirmed by computer-assisted structure elucidation methods (CASE) using the ACD/Structure Elucidator Suite.

Chemistry of the Secondary Metabolites of Termites

Isolation, structure determination, synthesis, and biochemistry of the low-molecular-weight compounds of the secretion of exocrine glands of termites are described, with an emphasis on pheromones and defensive compounds.

Gut Microbial and Metabolic Responses to Salmonella enterica Serovar Typhimurium and Candida albicans

The gut microbiota is increasingly recognized for playing a critical role in human health and disease, especially in conferring resistance to both virulent pathogens such as Salmonella, which infects 1.2 million people in the United States every year (E. Scallan, R. M. Hoekstra, F. J. Angulo, R. V. Tauxe, et al., Emerg Infect Dis 17:7–15, 2011, https://doi.org/10.3201/eid1701.P11101), and opportunistic pathogens like Candida, which causes an estimated 46,000 cases of invasive candidiasis each year in the United States (Centers for Disease Control and Prevention, Antibiotic Resistance Threats in the United States, 2013, 2013). Using a gnotobiotic mouse model, we investigate potential changes in gut microbial community structure and function during infection using metagenomics and metabolomics. We observe that changes in the community and in biosynthetic gene cluster potential occur within 3 days for the virulent Salmonella enterica serovar Typhimurium, but there are minimal changes with a poorly colonizing Candida albicans. In addition, the metabolome shifts depending on infection status, including changes in glutathione metabolites in response to Salmonella infection, potentially in response to host oxidative stress.

The gut microbiota confers resistance to pathogens of the intestinal ecosystem, yet the dynamics of pathogen-microbiome interactions and the metabolites involved in this process remain largely unknown. Here, we use gnotobiotic mice infected with the virulent pathogen Salmonella enterica serovar Typhimurium or the opportunistic pathogen Candida albicans in combination with metagenomics and discovery metabolomics to identify changes in the community and metabolome during infection. To isolate the role of the microbiota in response to pathogens, we compared mice monocolonized with the pathogen, uninfected mice “humanized” with a synthetic human microbiome, or infected humanized mice. In Salmonella-infected mice, by 3 days into infection, microbiome community structure and function changed substantially, with a rise in Enterobacteriaceae strains and a reduction in biosynthetic gene cluster potential. In contrast, Candida-infected mice had few microbiome changes. The LC-MS metabolomic fingerprint of the cecum differed between mice monocolonized with either pathogen and humanized infected mice. Specifically, we identified an increase in glutathione disulfide, glutathione cysteine disulfide, inosine 5’-monophosphate, and hydroxybutyrylcarnitine in mice infected with Salmonella in contrast to uninfected mice and mice monocolonized with Salmonella. These metabolites potentially play a role in pathogen-induced oxidative stress. These results provide insight into how the microbiota community members interact with each other and with pathogens on a metabolic level.

Metabolomic profiling and biological investigation of the marine sponge-derived bacterium Rhodococcus sp. UA13

INTRODUCTION

Marine sponge-associated actinomycetes are potent sources of bioactive natural products of pharmaceutical significance. They also contributed to the discovery of several clinically relevant antimicrobials.

OBJECTIVE

To apply the non-targeted metabolomics approach in chemical profiling of the sponge-derived bacterium Rhodococcus sp. UA13, formerly recovered from the Red Sea sponge Callyspongia aff. Implexa, along with testing for the anti-infective potential of its different fractions.

METHODOLOGY

Metabolomic analysis of the crude extract was carried out using liquid chromatography with high resolution electrospray ionisation mass spectrometry (LC-HR-ESI-MS) for dereplication purposes. Besides, the three major fractions (ethyl acetate, methanol, and n-butanol) obtained by chromatographic fractionation of the crude extract were evaluated for their anti-infective properties.

RESULTS

A variety of metabolites, mostly peptides, were characterised herein for the first time from the genus Rhodococcus. Among the tested samples, the n-butanol fraction showed potent inhibitory activities against Staphylococcus aureus, Candida albicans, and Trypanosoma brucei brucei with IC₅₀ values of 9.3, 6.7, and 8.7 μg/mL, respectively, whereas only the ethyl acetate fraction was active against Chlamydia trachomatis (IC₅₀  = 18.9 μg/mL). In contrast, both fractions did not exert anti-infective actions against Enterococcus faecalis and Leishmania major, whereas the methanol fraction was totally inactive against all the tested organisms.

CONCLUSION

This study showed the helpfulness of the established procedure in metabolic profiling of marine actinomycetes using liquid chromatography mass spectrometry (LC-MS) data, which aids in reducing the complex isolation steps during their chemical characterisation. The anti-infective spectrum of their metabolites is also interestingly relevant to future drug development.

Mechanistic consideration of the photochemical transformation of domoic acid (algal toxin) in DOM-Rich brackish water

Domoic acid (DA) is a neurotoxin generated by several diatom species in harmful algae blooms (HABs). We report the photo-induced transformation products (TPs) and degradation mechanisms of DA in dissolved organic matter (DOM)-rich freshwater and brackish water. High-resolution quadrupole time-of-flight mass spectrometry (QTOF-MS) and the multivariate statistical strategy orthogonal partial least-squares discriminant analysis (OPLS-DA) identified 36 and 23 potential TPs in DOM-rich freshwater and brackish water, respectively. The main reactive sites of DA are the conjugated double bond and proline ring. Isomerization is the predominant transformation pathway induced by excited-state triplet DOM (³DOM^∗). The second-order rate constant of the isomerization reaction was measured as (3.8 ± 0.2) × 10⁸ M^-1 s^-1. The inverse correlation between the dissolved oxygen (DO) concentration and the rate of photo-induced DA isomerization was revealed. Furthermore, under halide-present conditions, halide radicals are mainly responsible for the differentiation of products by quenching hydroxyl radicals and generating unique organic peroxide products. Our results indicated that halide radicals could be important in the photochemical transformation of organic contaminants in high saline environments.