Dereplication of microbial metabolites through database search of mass spectra

Chronic Exposure to Petroleum-Derived Hydrocarbons Alters Human Skin Microbiome and Metabolome Profiles: A Pilot Study

Petroleum-derived substances, like industrial oils and grease, are ubiquitous in our daily lives. Comprised of petroleum hydrocarbons (PH), these substances can come into contact with our skin, potentially causing molecular disruptions and contributing to the development of chronic disease. In this pilot study, we employed mass spectrometry-based untargeted metabolomics and 16S rRNA gene sequencing analyses to explore these effects. Superficial skin samples were collected from subjects with and without chronic dermal exposure to PH at two anatomical sites: the fingers (referred to as the hand) and arms (serving as an intersubject variability control). Exposed hands exhibited higher bacterial diversity (Shannon and Simpson indices) and an enrichment of oil-degrading bacteria (ODB), including Dietzia, Paracoccus, and Kocuria. Functional prediction suggested enriched pathways associated with PH degradation in exposed hands vs non-exposed hands, while no differences were observed when comparing the arms. Furthermore, carboxylic acids, glycerophospholipids, organooxygen compounds, phenol ethers, among others, were found to be more abundant in exposed hands. We observed positive correlations among multiple ODB and xenobiotics, suggesting a chemical remodeling of the skin favorable for ODB thriving. Overall, our study offers insights into the complex dysregulation of bacterial communities and the chemical milieu induced by chronic dermal exposure to PH.

Plant peptides - redefining an area of ribosomally synthesized and post-translationally modified peptides

Covering 1965 to February 2024Plants are prolific peptide chemists and are known to make thousands of different peptidic molecules. These peptides vary dramatically in their size, chemistry, and bioactivity. Despite their differences, all plant peptides to date are biosynthesized as ribosomally synthesized and post-translationally modified peptides (RiPPs). Decades of research in plant RiPP biosynthesis have extended the definition and scope of RiPPs from microbial sources, establishing paradigms and discovering new families of biosynthetic enzymes. The discovery and elucidation of plant peptide pathways is challenging due to repurposing and evolution of housekeeping genes as both precursor peptides and biosynthetic enzymes and due to the low rates of gene clustering in plants. In this review, we highlight the chemistry, biosynthesis, and function of the known RiPP classes from plants and recommend a nomenclature for the recent addition of BURP-domain-derived RiPPs termed burpitides. Burpitides are an emerging family of cyclic plant RiPPs characterized by macrocyclic crosslinks between tyrosine or tryptophan side chains and other amino acid side chains or their peptide backbone that are formed by copper-dependent BURP-domain-containing proteins termed burpitide cyclases. Finally, we review the discovery of plant RiPPs through bioactivity-guided, structure-guided, and gene-guided approaches.

High-Throughput Mining of Novel Compounds from Known Microbes: A Boost to Natural Product Screening

Advanced techniques can accelerate the pace of natural product discovery from microbes, which has been lagging behind the drug discovery era. Therefore, the present review article discusses the various interdisciplinary and cutting-edge techniques to present a concrete strategy that enables the high-throughput screening of novel natural compounds (NCs) from known microbes. Recent bioinformatics methods revealed that the microbial genome contains a huge untapped reservoir of silent biosynthetic gene clusters (BGC). This article describes several methods to identify the microbial strains with hidden mines of silent BGCs. Moreover, antiSMASH 5.0 is a free, accurate, and highly reliable bioinformatics tool discussed in detail to identify silent BGCs in the microbial genome. Further, the latest microbial culture technique, HiTES (high-throughput elicitor screening), has been detailed for the expression of silent BGCs using 500-1000 different growth conditions at a time. Following the expression of silent BGCs, the latest mass spectrometry methods are highlighted to identify the NCs. The recently emerged LAESI-IMS (laser ablation electrospray ionization-imaging mass spectrometry) technique, which enables the rapid identification of novel NCs directly from microtiter plates, is presented in detail. Finally, various trending 'dereplication' strategies are emphasized to increase the effectiveness of NC screening.

Discovering type I cis-AT polyketides through computational mass spectrometry and genome mining with Seq2PKS

Type 1 polyketides are a major class of natural products used as antiviral, antibiotic, antifungal, antiparasitic, immunosuppressive, and antitumor drugs. Analysis of public microbial genomes leads to the discovery of over sixty thousand type 1 polyketide gene clusters. However, the molecular products of only about a hundred of these clusters are characterized, leaving most metabolites unknown. Characterizing polyketides relies on bioactivity-guided purification, which is expensive and time-consuming. To address this, we present Seq2PKS, a machine learning algorithm that predicts chemical structures derived from Type 1 polyketide synthases. Seq2PKS predicts numerous putative structures for each gene cluster to enhance accuracy. The correct structure is identified using a variable mass spectral database search. Benchmarks show that Seq2PKS outperforms existing methods. Applying Seq2PKS to Actinobacteria datasets, we discover biosynthetic gene clusters for monazomycin, oasomycin A, and 2-aminobenzamide-actiphenol.

Small molecule in situ resin capture provides a compound first approach to natural product discovery

Culture-based microbial natural product discovery strategies fail to realize the extraordinary biosynthetic potential detected across earth's microbiomes. Here we introduce Small Molecule In situ Resin Capture (SMIRC), a culture-independent method to obtain natural products directly from the environments in which they are produced. We use SMIRC to capture numerous compounds including two new carbon skeletons that were characterized using NMR and contain structural features that are, to the best of our knowledge, unprecedented among natural products. Applications across diverse marine habitats reveal biome-specific metabolomic signatures and levels of chemical diversity in concordance with sequence-based predictions. Expanded deployments, in situ cultivation, and metagenomics facilitate compound discovery, enhance yields, and link compounds to candidate producing organisms, although microbial community complexity creates challenges for the later. This compound-first approach to natural product discovery provides access to poorly explored chemical space and has implications for drug discovery and the detection of chemically mediated biotic interactions.

Cellulamides: A New Family of Marine-Sourced Linear Peptides from the Underexplored Cellulosimicrobium Genus

Bioprospecting the secondary metabolism of underexplored Actinomycetota taxa is a prolific route to uncover novel chemistry. In this work, we report the isolation, structure elucidation, and bioactivity screening of cellulamides A and B (1 and 2), two novel linear peptides obtained from the culture of the macroalga-associated Cellulosimicrobium funkei CT-R177. The host of this microorganism, the Chlorophyta Codium tomentosum, was collected in the northern Portuguese coast and, in the scope of a bioprospecting study focused on its associated actinobacterial community, strain CT-R177 was isolated, taxonomically identified, and screened for the production of antimicrobial and anticancer compounds. Dereplication of a crude extract of this strain using LC-HRMS(/MS) analysis unveiled a putative novel natural product, cellulamide A (1), that was isolated following mass spectrometry-guided fractionation. An additional analog, cellulamide B (2) was obtained during the chromatographic process and chemically characterized. The chemical structures of the novel linear peptides, including their absolute configurations, were elucidated using a combination of HRMS, 1D/2D NMR spectroscopy, and Marfey's analysis. Cellulamide A (1) was subjected to a set of bioactivity screenings, but no significant biological activity was observed. The cellulamides represent the first family of natural products reported from the Actinomycetota genus Cellulosimicrobium, showcasing not only the potential of less-explored taxa but also of host-associated marine strains for novel chemistry discovery.

Metabolomic Diversity in Microbial Mats Under Different Environmental Conditions: A Tool to Test Microbial Ecosystem Chemical Change

Microbial mats are microbial communities capable of recycling the essential elements of life and considered to be the oldest evidence of microbial communities on Earth. Due to their uniqueness and limited sampling material, analyzing their metabolomic profile in different seasons or conditions is challenging. In this study, microbial mats from a small pond in the Cuatro Cienegas Basin in Coahuila, Mexico, were collected in wet and dry seasons. In addition to these samples, mesocosm experiments from the wet samples were set. These mats are elastic and rise after heavy rainfall by forming gas domes structures known as "Archean domes", by the outgassing of methanogenic bacteria, archaea, and sulfur bacteria. Extracts from all mats and mesocosms were subjected to untargeted mass spectrometry-based metabolomics and molecular networking analysis. Interestingly, each mat showed high chemical diversity that may be explained by the temporal dynamic processes in which they were sampled.

Insight into the chemical compositions of Anhua dark teas derived from identical tea materials: A multi-omics, electronic sensory, and microbial sequencing analysis

Anhua dark teas (DTs), including Tianjian tea, Qianliang tea, Hei brick tea, and Fu brick tea, are unique fermented teas from China's Anhua County; yet their chemical composition differences remain unclear. Herein, metabolomics, volatolomics, and electronic sensory assessments were employed to analyze and compare chemical compositions and sensory characteristics of five types of Anhua DTs. All of these teas were derived from identical tea materials. Chemical compositions differed significantly among Anhua DTs, with Tianjian tea remarkable. Long-lasting fermentation and complex processing methods led to transformation of multiple compounds, particularly catechins. Eighteen volatile compounds with OVA > 1 were key aroma contributors in Anhua DTs. Internal transcribed spacer and 16S ribosomal DNA sequencing showed that Eurotium, Pseudomonas, and Bacillus are dominant microorganisms in Anhua DTs. Furthermore, this study unveiled notable differences in chemical compositions between Anhua DTs and five other traditional types of tea. This research enhances our understanding of Anhua DTs processing.

Charting the Cannabis plant chemical space with computational metabolomics

INTRODUCTION

The chemical classification of Cannabis is typically confined to the cannabinoid content, whilst Cannabis encompasses diverse chemical classes that vary in abundance among all its varieties. Hence, neglecting other chemical classes within Cannabis strains results in a restricted and biased comprehension of elements that may contribute to chemical intricacy and the resultant medicinal qualities of the plant.

OBJECTIVES

Thus, herein, we report a computational metabolomics study to elucidate the Cannabis metabolic map beyond the cannabinoids.

METHODS

Mass spectrometry-based computational tools were used to mine and evaluate the methanolic leaf and flower extracts of two Cannabis cultivars: Amnesia haze (AMNH) and Royal dutch cheese (RDC).

RESULTS

The results revealed the presence of different chemical compound classes including cannabinoids, but extending it to flavonoids and phospholipids at varying distributions across the cultivar plant tissues, where the phenylpropnoid superclass was more abundant in the leaves than in the flowers. Therefore, the two cultivars were differentiated based on the overall chemical content of their plant tissues where AMNH was observed to be more dominant in the flavonoid content while RDC was more dominant in the lipid-like molecules. Additionally, in silico molecular docking studies in combination with biological assay studies indicated the potentially differing anti-cancer properties of the two cultivars resulting from the elucidated chemical profiles.

CONCLUSION

These findings highlight distinctive chemical profiles beyond cannabinoids in Cannabis strains. This novel mapping of the metabolomic landscape of Cannabis provides actionable insights into plant biochemistry and justifies selecting certain varieties for medicinal use.

Shifts in the functional capacity and metabolite composition of the gut microbiome during recovery from enteric infection

While enteric pathogens have been widely studied for their roles in causing foodborne infection, their impacts on the gut microbial community have yet to be fully characterized. Previous work has identified notable changes in the gut microbiome related to pathogen invasion, both taxonomically and genetically. Characterization of the metabolic landscape during and after enteric infection, however, has not been explored. Consequently, we investigated the metabolome of paired stools recovered from 60 patients (cases) during and after recovery from enteric bacterial infections (follow-ups). Shotgun metagenomics was applied to predict functional microbial pathways combined with untargeted metametabolomics classified by Liquid Chromatography Mass Spectrometry. Notably, cases had a greater overall metabolic capacity with significantly higher pathway richness and evenness relative to the follow-ups (p<0.05). Metabolic pathways related to central carbon metabolism, amino acid metabolism, and lipid and fatty acid biosynthesis were more highly represented in cases and distinct signatures for menaquinone production were detected. By contrast, the follow-up samples had a more diverse metabolic landscape with enhanced richness of polar metabolites (p<0.0001) and significantly greater richness, evenness, and overall diversity of nonpolar metabolites (p<0.0001). Although many metabolites could not be annotated with existing databases, a marked increase in certain clusters of metabolites was observed in the follow-up samples when compared to the case samples and vice versa. These findings suggest the importance of key metabolites in gut health and recovery and enhance understanding of metabolic fluctuations during enteric infections.

Essentials in the acquisition, interpretation, and reporting of plant metabolite profiles

Plant metabolite profiling reveals the diversity of secondary or specialized metabolites in the plant kingdom with its hundreds of thousands of species. Specialized plant metabolites constitute a vast class of chemicals posing significant challenges in analytical chemistry. In order to be of maximum scientific relevance, reports dealing with these compounds and their source species must be transparent, make use of standards and reference materials, and be based on correctly and traceably identified plant material. Essential aspects in qualitative plant metabolite profiling include: (i) critical review of previous literature and a reasoned sampling strategy; (ii) transparent plant sampling with wild material documented by vouchers in public herbaria and, optimally, seed banks; (iii) if possible, inclusion of generally available reference plant material; (iv) transparent, documented state-of-the art chemical analysis, ideally including chemical reference standards; (v) testing for artefacts during preparative extraction and isolation, using gentle analytical methods; (vi) careful chemical data interpretation, avoiding over- and misinterpretation and taking into account phytochemical complexity when assigning identification confidence levels, and (vii) taking all previous scientific knowledge into account in reporting the scientific data. From the current stage of the phytochemical literature, selected comments and suggestions are given. In the past, proposed revisions of botanical taxonomy were sometimes based on metabolite profiles, but this approach ("chemosystematics" or "chemotaxonomy") is outdated due to the advent of DNA sequence-based phylogenies. In contrast, systematic comparisons of plant metabolite profiles in a known phylogenetic framework remain relevant. This approach, known as chemophenetics, allows characterizing species and clades based on their array of specialized metabolites, aids in deducing the evolution of biosynthetic pathways and coevolution, and can serve in identifying new sources of rare and economically interesting natural products.

Decylprodigiosin: a new member of the prodigiosin family isolated from a seaweed-associated Streptomyces

Bioprospecting actinobacterial secondary metabolism from untapped marine sources may lead to the discovery of biotechnologically-relevant compounds. While studying the diversity and bioactive potential of Actinomycetota associated with Codium tomentosum, a green seaweed collected in the northern Portuguese cost, strain CT-F61, identified as Streptomyces violaceoruber, was isolated. Its extracts displayed a strong anticancer activity on breast carcinoma T-47D and colorectal carcinoma HCT116 cells, being effective as well against a panel of human and fish pathogenic bacteria. Following a bioactivity-guided isolation pipeline, a new analogue of the red-pigmented family of the antibiotics prodigiosins, decylprodigiosin (1), was identified and chemically characterized. Despite this family of natural products being well-known for a long time, we report a new analogue and the first evidence for prodigiosins being produced by a seaweed-associated actinomycete.

Harnessing the potential: advances in cyanobacterial natural product research and biotechnology

Covering: 2000 to 2023Cyanobacteria produce a variety of bioactive natural products that can pose a threat to humans and animals as environmental toxins, but also have potential for or inspire pharmaceutical use. As oxygenic phototrophs, cyanobacteria furthermore hold great promise for sustainable biotechnology. Yet, the necessary tools for exploiting their biotechnological potential have so far been established only for a few model strains of cyanobacteria, while large untapped biosynthetic resources are hidden in slow-growing cyanobacterial genera that are difficult to access by genetic techniques. In recent years, several approaches have been developed to circumvent the bottlenecks in cyanobacterial natural product research. Here, we summarize current progress that has been made in unlocking or characterizing cryptic metabolic pathways using integrated omics techniques, orphan gene cluster activation, use of genetic approaches in original producers, heterologous expression and chemo-enzymatic techniques. We are mainly highlighting genomic mining concepts and strategies towards high-titer production of cyanobacterial natural products from the last 10 years and discuss the need for further research developments in this field.

Chemical Profile of Ocotea delicata (Lauraceae) Using Ultra High-Performance Liquid Chromatography-High-Resolution Mass Spectrometry-Global Natural Products Social Molecular Networking Workflow

Ocotea, the largest genus in the Lauraceae family, encompasses numerous species of scientific interest. However, most Ocotea species have only been described morphologically. This study used an untargeted metabolomics workflow with UHPLC-HRMS and GNPS-FBMN to provide the first chemical evaluation of the polar specialized metabolites of O. delicata leaves. Leaves from three O. delicata specimens were extracted using ultrasound-assisted extraction with 70% ethanol. Among the examined samples, 44 metabolites, including alkaloids and flavonoids, were identified. In contrast to other Ocotea species, O. delicata has a wider diversity of kaempferol derivatives than quercetin. The biomass of the specimens showed a significant correlation with the chemical profile. The similarity among specimens was mostly determined by the concentrations of quinic acid, kaempferol glycosides, and boldine. The evaluated specimens exhibited chemical features similar to those of species classified as New World Ocotea, with the coexistence of aporphine and benzylisoquinoline alkaloids.

Importance of quorum sensing crosstalk in the brown alga Saccharina latissima epimicrobiome

Brown macroalgae are colonized by diverse microorganisms influencing the physiology of their host. However, cell-cell interactions within the surface microbiome (epimicrobiome) are largely unexplored, despite the significance of specific chemical mediators in maintaining host-microbiome homeostasis. In this study, by combining liquid chromatography coupled to mass spectrometry (LC-MS) analysis and bioassays, we demonstrated that the widely diverse fungal epimicrobiota of the brown alga Saccharina latissima can affect quorum sensing (QS), a type of cell-cell interaction, as well as bacterial biofilm formation. We also showed the ability of the bacterial epimicrobiota to form and inhibit biofilm growth, as well as to activate or inhibit QS pathways. Overall, we demonstrate that QS and anti-QS compounds produced by the epimicrobiota are key metabolites in these brown algal epimicrobiota communities and highlight the importance of exploring this epimicrobiome for the discovery of new bioactive compounds, including potentially anti-QS molecules with antifouling properties.

Genomic insights and anti-phytopathogenic potential of siderophore metabolome of endolithic Nocardia mangyaensis NH1

Actinobacteria are one of the predominant groups that successfully colonize and survive in various aquatic, terrestrial and rhizhospheric ecosystems. Among actinobacteria, Nocardia is one of the most important agricultural and industrial bacteria. Screening and isolation of Nocardia related bacteria from extreme habitats such as endolithic environments are beneficial for practical applications in agricultural and environmental biotechnology. In this work, bioinformatics analysis revealed that a novel strain Nocardia mangyaensis NH1 has the capacity to produce structurally varied bioactive compounds, which encoded by non-ribosomal peptide synthases (NRPS), polyketide synthase (PKS), and post-translationally modified peptides (RiPPs). Among NRPS, five gene clusters have a sequence homology with clusters encoding for siderophore synthesis. We also show that N. mangyaensis NH1 accumulates both catechol- and hydroxamate-type siderophores simultaneously under iron-deficient conditions. Untargeted LC-MS/MS analysis revealed a variety of metabolites, including siderophores, lipopeptides, cyclic peptides, and indole-3-acetic acid (IAA) in the culture medium of N. mangyaensis NH1 grown under iron deficiency. We demonstrate that four CAS (chrome azurol S)-positive fractions display variable affinity to metals, with a high Fe3+ chelating capability. Additionally, three of these fractions exhibit antioxidant activity. A combination of iron scavenging metabolites produced by N. mangyaensis NH1 showed antifungal activity against several plant pathogenic fungi. We have shown that the pure culture of N. mangyaensis NH1 and its metabolites have no adverse impact on Arabidopsis seedlings. The ability of N. mangyaensis NH1 to produce siderophores with antifungal, metal-chelating, and antioxidant properties, when supplemented with phytohormones, has the potential to improve the release of macro- and micronutrients, increase soil fertility, promote plant growth and development, and enable the production of biofertilizers across diverse soil systems.

Antidiabetic Potential of a Trimeric Anthranilic Acid Peptide Isolated from Malbranchea flocciformis

Compound 3, a trimeric anthranilic acid peptide, and another three metabolites were isolated from an organic extract from the culture medium of Malbranchea flocciformis ATCC 34530. The chemical structure proposed previously for 3 was unequivocally assigned via synthesis and X-ray diffraction analysis. Tripeptide 3 showed insulinotropic properties by decreasing the postprandial peak in healthy and hyperglycemic mice. It also increased glucose-induced insulin secretion in INS-1E at 5 μM, specifically at higher glucose concentrations. These results revealed that 3 might act as an insulin sensitizer and a non-classical insulin secretagogue. Altogether, these findings are in harmony with the in vivo oral glucose tolerance test and acute oral hypoglycemic assay. Finally, the chemical composition of the extract was established by the Global Natural Products Social Molecular Network platform. Phylogenetic analysis using the internal transcribed spacer region revealed that M. flocciformis ATCC 34530 is related to the Malbrancheaceae.

A multi-module structure labelled molecular network orients the chemical profiles of traditional Chinese medicine prescriptions: Xiaoyao San, as an example

Ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) technology has emerged as a crucial tool for identifying components in traditional Chinese medicine (TCM). However, the characterization of the chemical profiles of TCM prescriptions (TCMPs) which often consist of multiple herbal medicines and contain diverse structural types, presents several challenges, such as component overlapping and time-consuming. In this study, a novel strategy known as the multi-module structure labelled molecular network (MSLMN), which integrates molecular networking, database annotation, and cluster analysis techniques, has been successfully proposed, which facilitates the identification of chemical constituents by leveraging a high-structural similarity ion list derived from the MSLMN. It has been effectively applied to analyze the chemical profile of Xiaoyao San (XYS), a classical TCMP. Through the MSLMN method, a total of 302 chemical constituents were identified, covering nine structural types in XYS. Furthermore, a validated and quantitative analytical method using UHPLC-QqQ-MS/MS technology was developed for 31 identified chemicals, encompassing all eight herbal medicines present in XYS, and the developed analytical approach was applied to investigate the content distribution across 40 different batches of commercially available XYS. In total, the proposed strategy has practical significance for improving the insight into the chemical profile of XYS and serves as a valuable approach for handling complex system data based on UHPLC-MS, particularly for TCMPs.

Resistance towards and biotransformation of a Pseudomonas-produced secondary metabolite during community invasion

The role of antagonistic secondary metabolites produced by Pseudomonas protegens in suppression of soil-borne phytopathogens has been clearly documented. However, their contribution to the ability of P. protegens to establish in soil and rhizosphere microbiomes remains less clear. Here, we use a four-species synthetic community (SynCom) in which individual members are sensitive towards key P. protegens antimicrobial metabolites (DAPG, pyoluteorin, and orfamide A) to determine how antibiotic production contributes to P. protegens community invasion and to identify community traits that counteract the antimicrobial effects. We show that P. protegens readily invades and alters the SynCom composition over time, and that P. protegens establishment requires production of DAPG and pyoluteorin. An orfamide A-deficient mutant of P. protegens invades the community as efficiently as wildtype, and both cause similar perturbations to community composition. Here, we identify the microbial interactions underlying the absence of an orfamide A mediated impact on the otherwise antibiotic-sensitive SynCom member, and show that the cyclic lipopeptide is inactivated and degraded by the combined action of Rhodococcus globerulus D757 and Stenotrophomonas indicatrix D763. Altogether, the demonstration that the synthetic community constrains P. protegens invasion by detoxifying its antibiotics may provide a mechanistic explanation to inconsistencies in biocontrol effectiveness in situ.

Bioprospection of the Antarctic Diatoms Craspedostauros ineffabilis IMA082A and Craspedostauros zucchelli IMA088A

In extreme environments such as Antarctica, a diverse range of organisms, including diatoms, serve as essential reservoirs of distinctive bioactive compounds with significant implications in pharmaceutical, cosmeceutical, nutraceutical, and biotechnological fields. This is the case of the new species Craspedostauros ineffabilis IMA082A and Craspedostauros zucchellii IMA088A Trentin, Moschin, Lopes, Custódio and Moro (Bacillariophyta) that are here explored for the first time for possible biotechnological applications. For this purpose, a bioprospection approach was applied by preparing organic extracts (acetone and methanol) from freeze-dried biomass followed by the evaluation of their in vitro antioxidant properties and inhibitory activities on enzymes related with Alzheimer's disease (acetylcholinesterase: AChE, butyrylcholinesterase: BChE), Type 2 diabetes mellitus (T2DM, α-glucosidase, α-amylase), obesity (lipase) and hyperpigmentation (tyrosinase). Extracts were then profiled by ultra-high-performance liquid chromatography-mass spectrometry (UPLC-HR-MS/MS), while the fatty acid methyl ester (FAME) profiles were established by gas chromatography-mass spectrometry (GC-MS). Our results highlighted strong copper chelating activity of the acetone extract from C. ineffabilis and moderate to high inhibitory activities on AChE, BChE, α-amylase and lipase for extracts from both species. The results of the chemical analysis indicated polyunsaturated fatty acids (PUFA) and their derivatives as the possible compounds responsible for the observed activities. The FAME profile showed saturated fatty acids (SFA) as the main group and methyl palmitoleate (C16:1) as the predominant FAME in both species. Overall, our results suggest both Antarctic strains as potential sources of interesting molecules with industrial applications. Further studies aiming to investigate unidentified metabolites and to maximize growth yield and natural compound production are required.

Lake Avernus Has Turned Red: Bioindicator Monitoring Unveils the Secrets of "Gates of Hades"

Lake Avernus is a volcanic lake located in southern Italy. Since ancient times, it has inspired numerous myths and legends due to the occurrence of singular phenomena, such as coloring events. Only recently has an explanation been found for them, i.e., the recurring color change over time is due to the alternation of cyanobacterial blooms that are a consequence of natural nutrient inputs as well as pollution resulting from human activities. This current report specifically describes the red coloring event that occurred on Lake Avernus in March 2022, the springtime season in this region of Italy. Our innovative multidisciplinary approach, the 'Fast Detection Strategy' (FDS), was devised to monitor cyanobacterial blooms and their toxins. It integrates remote sensing data from satellites and drones, on-site sampling, and analytical/bioinformatics analyses into a cohesive information flow. Thanks to FDS, we determined that the red color was attributable to a bloom of Planktothrix rubescens, a toxin-producing cyanobacterium. Here, we report the detection and identification of 14 anabenopeptins from this P. rubescens strain, seven of which are known and seven are newly reported herein. Moreover, we explored the mechanisms and causes behind this cyclic phenomenon, confirming cyanobacteria's role as reliable indicators of environmental changes. This investigation further validates FDS's effectiveness in detecting and characterizing cyanobacterial blooms and their associated toxins, expanding its potential applications.

Integrating Taxonomic and Chemical Diversity of Mangrove-Associated Ascomycetes to Discover or Repurpose Bioactive Natural Products

Natural product reisolation is a bottleneck when discovering new bioactive chemical entities from nature. To overcome this issue, multi-informative approaches integrating several layers of data have been applied with promising results. In this study, integration of taxonomy, nontargeted metabolomics, and bioactivity information resulted in the selection of Scytalidium sp. IQ-074 and Diaporthe sp. IQ-053 to isolate new natural products active against hPTP1B1-400 and repurpose others as antibiotics. Strain IQ-074 was selected based on the hypothesis that investigating poorly studied and highly metabolic taxa could lead to the isolation of new chemical entities. A chemical investigation of IQ-074 resulted in the isolation of papyracillic acid A (14), 7-deoxypapyracillic acid A (15a and 15b), and linear polyketides scytalpolyols A-D (16-19). Compound 17 inhibited hPTP1B1-400 with a half-maximal inhibitory concentration of 27.0 ± 1.7 μM. Diaporthe sp. IQ-053 was selected based on its antibacterial properties against pathogenic strains. Its chemical investigation yielded dothiorelones A (20) and I (21), cytosporones B (22) and C (23), pestalotiopsone B (24), and diaporthalasin (25). Compounds 22 and 25 inhibited the growth of Staphylococcus aureus and Staphylococcus epidermidis 42R and moderately inhibited the growth of Acinetobacter baumannii A564, a pandrug-resistant bacterium.

Metabolomics and Microbiomics Insights into Differential Surface Fouling of Three Macroalgal Species of Fucus (Fucales, Phaeophyceae) That Co-Exist in the German Baltic Sea

The brown algal genus Fucus provides essential ecosystem services crucial for marine environments. Macroalgae (seaweeds) release dissolved organic matter, hence, are under strong settlement pressure from micro- and macrofoulers. Seaweeds are able to control surface epibionts directly by releasing antimicrobial compounds onto their surfaces, and indirectly by recruiting beneficial microorganisms that produce antimicrobial/antifouling metabolites. In the Kiel Fjord, in the German Baltic Sea, three distinct Fucus species coexist: F. vesiculosus, F. serratus, and F. distichus subsp. evanescens. Despite sharing the same habitat, they show varying fouling levels; F. distichus subsp. evanescens is the least fouled, while F. vesiculosus is the most fouled. The present study explored the surface metabolomes and epiphytic microbiota of these three Fucus spp., aiming to uncover the factors that contribute to the differences in the fouling intensity on their surfaces. Towards this aim, algal surface metabolomes were analyzed using comparative untargeted LC-MS/MS-based metabolomics, to identify the marker metabolites influencing surface fouling. Their epiphytic microbial communities were also comparatively characterized using high-throughput amplicon sequencing, to pinpoint the differences in the surface microbiomes of the algae. Our results show that the surface of the least fouling species, F. distichus subsp. evanescens, is enriched with bioactive compounds, such as betaine lipids MGTA, 4-pyridoxic acid, and ulvaline, which are absent from the other species. Additionally, it exhibits a high abundance of the fungal genera Mucor and Alternaria, along with the bacterial genus Yoonia-Loktanella. These taxa are known for producing antimicrobial/antifouling compounds, suggesting their potential role in the observed fouling resistance on the surface of the F. distichus subsp. evanescens compared to F. serratus and F. vesiculosus. These findings provide valuable clues on the differential surface fouling intensity of Fucus spp., and their importance in marine chemical defense and fouling dynamics.

Activity labelled molecular networking fuels the antioxidation active molecules profile of Ginger

Ginger has been used as consumed food spice and folk medicine in daily life for thousands of years in various regions of the world. Considerable antioxidation is one of the major activities for Ginger to exhibit health-promoting effects. In this study, a bioinformatic workflow was developed to generate activity labelled molecular networking (ALMN) to fuel the antioxidation active molecules profile of Ginger. In ALMN, antioxidation activity data, which was defined as correlation (r and p value) between the relative abundance of a molecule in fractions and the activity level of each fraction, was labelled to feature-based molecular network to profile out antioxidation active molecules visually. Fragmentation tree was further computed as a complementary way to conduct high confidence structure annotations of antioxidation active molecules. Consequently, 48 molecules were prioritized as antioxidation active molecules from 11,720 metabolite molecules of Ginger in a systematical way.

An Integrated Molecular Networking and Docking Approach to Characterize the Metabolome of Helichrysum splendidum and Its Pharmaceutical Potentials

South Africa is rich in diverse medicinal plants, and it is reported to have over 35% of the global Helichrysum species, many of which are utilized in traditional medicine. Various phytochemical studies have offered valuable insights into the chemistry of Helichrysum plants, hinting at bioactive components that define the medicinal properties of the plant. However, there are still knowledge gaps regarding the size and diversity of the Helichrysum chemical space. As such, continuous efforts are needed to comprehensively characterize the phytochemistry of Helichrysum, which will subsequently contribute to the discovery and exploration of Helichrysum-derived natural products for drug discovery. Thus, reported herein is a computational metabolomics work to comprehensively characterize the metabolic landscape of the medicinal herb Helichrysum splendidum, which is less studied. Metabolites were methanol-extracted and analyzed on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) system. Spectral data were mined using molecular networking (MN) strategies. The results revealed that the metabolic map of H. splendidum is chemically diverse, with chemical superclasses that include organic polymers, benzenoids, lipid and lipid-like molecules, alkaloids, and derivatives, phenylpropanoids and polyketides. These results point to a vastly rich chemistry with potential bioactivities, and the latter was demonstrated through computationally assessing the binding of selected metabolites with CDK-2 and CCNB1 anti-cancer targets. Molecular docking results showed that flavonoids (luteolin, dihydroquercetin, and isorhamnetin) and terpenoids (tiliroside and silybin) interact strongly with the CDK-2 and CCNB1 targets. Thus, this work suggests that these flavonoid and terpenoid compounds from H. splendidum are potentially anti-cancer agents through their ability to interact with these proteins involved in cancer pathways and progression. As such, these actionable insights are a necessary step for further exploration and translational studies for H. splendidum-derived compounds for drug discovery.

Establishment of a transparent soil system to study Bacillus subtilis chemical ecology

Bacterial secondary metabolites are structurally diverse molecules that drive microbial interaction by altering growth, cell differentiation, and signaling. Bacillus subtilis, a Gram-positive soil-dwelling bacterium, produces a wealth of secondary metabolites, among them, lipopeptides have been vastly studied by their antimicrobial, antitumor, and surfactant activities. However, the natural functions of secondary metabolites in the lifestyles of the producing organism remain less explored under natural conditions, i.e. in soil. Here, we describe a hydrogel-based transparent soil system to investigate B. subtilis chemical ecology under controllable soil-like conditions. The transparent soil matrix allows the growth of B. subtilis and other isolates gnotobiotically and under nutrient-controlled conditions. Additionally, we show that transparent soil allows the detection of lipopeptides production and dynamics by HPLC-MS, and MALDI-MS imaging, along with fluorescence imaging of 3-dimensional bacterial assemblages. We anticipate that this affordable and highly controllable system will promote bacterial chemical ecology research and help to elucidate microbial interactions driven by secondary metabolites.

Bioprospecting for the soil-derived actinobacteria and bioactive secondary metabolites on the Western Qinghai-Tibet Plateau

Introduction

The increase in incidence of multidrug-resistant bacteria and the inadequacy of new antimicrobial drugs have led to a widespread outbreak of bacterial antimicrobial resistance. To discover new antibiotics, biodiversity, and novelty of culturable actinobacteria dwelled in soil of the Western Qinghai-Tibet Plateau were investigated. By integrating antibacterial assay with omics tools, Amycolatopsis sp. A133, a rare actinobacterial strain and its secondary metabolites were further studied.

Method

Culture-dependent method was used to obtain actinobacterial strains from two soil samples collected from Ali region in Qinghai-Tibet Plateau. The cultural extractions of representative strains were assayed against "ESKAPE" pathogens by paper-disk diffusion method and the double fluorescent protein reporter "pDualrep2" system. An Amycolatopsis strain coded as A133 was prioritized and its secondary metabolites were further analyzed and annotated by omics tools including antiSMASH and GNPS (Global Natural Social Molecular Networking). The predicted rifamycin analogs produced by Amycolatopsis sp. A133 were isolated and identified by chromatographic separation, such as Sephadex LH-20 and HPLC, and spectral analysis, such as NMR and UPLC-HRESI-MS/MS, respectively.

Results

A total of 406 actinobacteria strains affiliated to 36 genera in 17 families of 9 orders were isolated. Out of 152 representative strains, 63 isolates exhibited antagonistic activity against at least one of the tested pathogens. Among them, 7 positive strains were identified by the "pDualrep2" system as either an inhibitor of protein translation or DNA biosynthesis. The cultural broth of Amycolatopsis sp. A133 exhibited a broader antimicrobial activity and can induce expression of TurboRFP. The secondary metabolites produced by strain A133 was annotated as rifamycins and zampanolides by antiSMASH and GNPS analysis. Five members of rifamycins, including rifamycin W, protorifamycin I, rifamycin W-M1, proansamycin B, and rifamycin S, were purified and identified. Rifamycin W-M1, was found as a new member of the naturally occurring rifamycin group of antibiotics.

Discussion

Assisted by omics tools, the successful and highly efficient discovery of rifamycins, a group of clinically used antibiotics from actinobacteria in Ali area encouraged us to devote more energy to explore new antibiotics from the soils on the Western Tibetan Plateau.

Evaluation of the biological responses of silver nanoparticles synthesized using Pelargonium x hortorum extract

Silver nanoparticles (AgNPs) are one of the widely studied nanomaterials for diverse biomedical applications, in particular, as antimicrobial agents to kill bacteria, fungi, and viruses. In this report, AgNPs were synthesized using a geranium (Pelargonium x hortorum) leaves extract and tested for their antimicrobial and cytotoxic activity and reactive oxygen species (ROS) production. Using green biosynthesis, the leaves extract was employed as a reducing and stabilizing agent. Synthesis parameters like reaction time and precursor (silver nitrate AgNO3) volume final were modified, and the products were tested against Streptococcus mutans. For the first time, the metabolomic analysis of extract, we have identified more than 50 metabolites. The UV-Vis analysis showed a peak ranging from 410-430 nm, and TEM confirmed their nearly spherical morphology for all NPs. The antimicrobial activity of the NPs revealed a minimum inhibitory concentration (MIC) of 10 μg mL-1. Concerning cytotoxicity, a dose-time-dependent effect was observed with a 50% cellular cytotoxicity concentration (CC50) of 4.51 μg mL-1 at 24 h. Interestingly, the cell nuclei were visualized using fluorescence microscopy, and no significant changes were observed. These results suggest that synthesized spherical AgNPs are promising potential candidates for medical applications.

Unlocking Potentially Therapeutic Phytochemicals in Capadulla (Doliocarpus dentatus) from Guyana Using Untargeted Mass Spectrometry-Based Metabolomics

Doliocarpus dentatus is thought to have a wide variety of therapeutic phytochemicals that allegedly improve libido and cure impotence. Although a few biomarkers have been identified with potential antinociceptive and cytotoxic properties, an untargeted mass spectrometry-based metabolomics approach has never been undertaken to identify therapeutic biofingerprints for conditions, such as erectile dysfunction, in men. This study executes a preliminary phytochemical screening of the woody vine of two ecotypes of D. dentatus with renowned differences in therapeutic potential for erectile dysfunction. Liquid chromatography-mass spectrometry-based metabolomics was used to screen for flavonoids, terpenoids, and other chemical classes found to contrast between red and white ecotypes. Among the metabolite chemodiversity found in the ecotype screens, using a combination of GNPS, MS-DIAL, and SIRIUS, approximately 847 compounds were annotated at levels 2 to 4, with the majority of compounds falling under lipid and lipid-like molecules, benzenoids and phenylpropanoids, and polyketides, indicative of the contributions of the flavonoid, shikimic acid, and terpenoid biosynthesis pathways. Despite the extensive annotation, we report on 138 tentative compound identifications of potentially therapeutic compounds, with 55 selected compounds at a level-2 annotation, and 22 statistically significant therapeutic biomarkers, the majority of which were polyphenols. Epicatechin methyl gallate, catechin gallate, and proanthocyanidin A2 had the greatest significant differences and were also relatively abundant among the red and white ecotypes. These putatively identified compounds reportedly act as antioxidants, neutralizing damaging free radicals, and lowering cell oxidative stress, thus aiding in potentially preventing cellular damage and promoting overall well-being, especially for treating erectile dysfunction (ED).

Anti-cervical cancer mechanism of bioactive compounds from Alangium platanifolium based on the 'compound-target-disease' network

In this study, we analyzed the chemical compositions of Alangium platanifolium (Sieb. et Zucc.) Harms (AP) using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) non-targeted plant metabolomics integration MolNetEnhancer strategy. A total of 75 compounds, including flavonoids, alkaloids, terpenes, C21 steroids, among others, were identified by comparing accurate mass-to-charge ratios, MS2 cleavage fragments, retention times, and MolNetenhancer-integrated analytical data, and the cleavage rules of the characteristic compounds were analyzed. A total of 125 potential cervical cancer (CC) therapeutic targets were obtained through Gene Expression Omnibus (GEO) data mining, differential analysis, and database screening. Hub targets were obtained by constructing protein-protein interaction (PPI) networks and CytoNCA topology analysis, including SRC, STAT3, TP53, PIK3R1, MAPK3, and PIK3CA. According to Gene ontology (GO) analysis, AP was primarily against CC by influencing gland development, oxidative stress processes, serine/threonine kinase, and tyrosine kinase activity. Enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that the PI3K/AKT and MAPK signaling pathways play a crucial role in AP treatment for CC. The compound-target-pathway (C-T-P) network revealed that quercetin, methylprednisolone, and caudatin may play key roles in the treatment of CC. The results of molecular docking revealed that the core compound could bind significantly to the core target. In this study, the compounds in AP were systematically analyzed qualitatively, and the core components, core targets, and mechanisms of action of AP in the treatment of CC were screened through a combination of network pharmacology tools. Providing a scientific reference for the therapeutic material basis and quality control of AP.

Structural Diversity and Biological Activity of Cyanopeptolins Produced by Nostoc edaphicum CCNP1411

Cyanopeptolins (CPs) are one of the most commonly occurring class of cyanobacterial nonribosomal peptides. For the majority of these compounds, protease inhibition has been reported. In the current work, the structural diversity of cyanopeptolins produced by Nostoc edaphicum CCNP1411 was explored. As a result, 93 CPs, including 79 new variants, were detected and structurally characterized based on their mass fragmentation spectra. CPs isolated in higher amounts were additionally characterized by NMR. To the best of our knowledge, this is the highest number of cyanopeptides found in one strain. The biological assays performed with the 34 isolated CPs confirmed the significance of the amino acid located between Thr and the unique 3-amino-6-hydroxy-2-piperidone (Ahp) on the activity of the compounds against serine protease and HeLa cancer cells.

Metabolome-guided genome mining of RiPP natural products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a chemically diverse class of metabolites. Many RiPPs show potent biological activities that make them attractive starting points for drug development. A promising approach for the discovery of new classes of RiPPs is genome mining. However, the accuracy of genome mining is hampered by the lack of signature genes shared across different RiPP classes. One way to reduce false-positive predictions is by complementing genomic information with metabolomics data. In recent years, several new approaches addressing such integrative genomics and metabolomics analyses have been developed. In this review, we provide a detailed discussion of RiPP-compatible software tools that integrate paired genomics and metabolomics data. We highlight current challenges in data integration and identify opportunities for further developments targeting new classes of bioactive RiPPs.

Application of feature-based molecular networking and MassQL for the MS/MS fragmentation study of depsipeptides

The Feature-based Molecular Networking (FBMN) is a well-known approach for mapping and identifying structures and analogues. However, in the absence of prior knowledge about the molecular class, assessing specific fragments and clusters requires time-consuming manual validation. This study demonstrates that combining FBMN and Mass Spec Query Language (MassQL) is an effective strategy for accelerating the decoding mass fragmentation pathways and identifying molecules with comparable fragmentation patterns, such as beauvericin and its analogues. To accomplish this objective, a spectral similarity network was built from ESI-MS/MS experiments of Fusarium oxysporum at various collision energies (CIDs) and paired with a MassQL search query for conserved beauvericin ions. FBMN analysis revealed that sodiated and protonated ions clustered differently, with sodiated adducts needing more collision energy and exhibiting a distinct fragmentation pattern. Based on this distinction, two sets of particular fragments were discovered for the identification of these hexadepsipeptides: ([M + H]+) m/z 134, 244, 262, and 362 and ([M + Na]+) m/z 266, 284 and 384. By using these fragments, MassQL accurately found other analogues of the same molecular class and annotated beauvericins that were not classified by FBMN alone. Furthermore, FBMN analysis of sodiated beauvericins at 70 eV revealed subclasses with distinct amino acid residues, allowing distinction between beauvericins (beauvericin and beauvericin D) and two previously unknown structural isomers with an unusual methionine sulfoxide residue. In summary, our integrated method revealed correlations between adduct types and fragmentation patterns, facilitated the detection of beauvericin clusters, including known and novel analogues, and allowed for the differentiation between structural isomers.

The Cytotoxic Properties of Extreme Fungi's Bioactive Components-An Updated Metabolic and Omics Overview

Fungi are the most diverse living organisms on planet Earth, where their ubiquitous presence in various ecosystems offers vast potential for the research and discovery of new, naturally occurring medicinal products. Concerning human health, cancer remains one of the leading causes of mortality. While extensive research is being conducted on treatments and their efficacy in various stages of cancer, finding cytotoxic drugs that target tumor cells with no/less toxicity toward normal tissue is a significant challenge. In addition, traditional cancer treatments continue to suffer from chemical resistance. Fortunately, the cytotoxic properties of several natural products derived from various microorganisms, including fungi, are now well-established. The current review aims to extract and consolidate the findings of various scientific studies that identified fungi-derived bioactive metabolites with antitumor (anticancer) properties. The antitumor secondary metabolites identified from extremophilic and extremotolerant fungi are grouped according to their biological activity and type. It became evident that the significance of these compounds, with their medicinal properties and their potential application in cancer treatment, is tremendous. Furthermore, the utilization of omics tools, analysis, and genome mining technology to identify the novel metabolites for targeted treatments is discussed. Through this review, we tried to accentuate the invaluable importance of fungi grown in extreme environments and the necessity of innovative research in discovering naturally occurring bioactive compounds for the development of novel cancer treatments.

HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

A metabologenomics approach to unlock the metabolome of the novel Antarctic deep-sea isolate Lacinutrix shetlandiensis sp. nov. WUR7

The South Shetland Trough, Antarctica, is an underexplored region for microbiological and biotechnological exploitation. Herein, we describe the isolation and characterization of the novel bacterium Lacinutrix shetlandiensis sp. nov. WUR7 from a deep-sea environment. We explored its chemical diversity via a metabologenomics approach, wherein the OSMAC strategy was strategically employed to upregulate cryptic genes for secondary metabolite production. Based on hybrid de novo whole genome sequencing and digital DNA-DNA hybridization, isolate WUR7 was identified as a novel species from the Gram-negative genus Lacinutrix. Its genome was mined for the presence of biosynthetic gene clusters with limited results. However, extensive investigation of its metabolism uncovered an unusual tryptophan decarboxylase with high sequence homology and conserved structure of the active site as compared to ZP_02040762, a highly specific tryptophan decarboxylase from Ruminococcus gnavus. Therefore, WUR7's metabolism was directed toward indole-based alkaloid biosynthesis by feeding it with L-tryptophan. As expected, its metabolome profile changed dramatically, by triggering the extracellular accumulation of a massive array of metabolites unexpressed in the absence of tryptophan. Untargeted LC-MS/MS coupled with molecular networking, followed along with chemoinformatic dereplication, allowed for the annotation of 10 indole alkaloids, belonging to β-carboline, bisindole, and monoindole classes, alongside several unknown alkaloids. These findings guided us to the isolation of a new natural bisindole alkaloid 8,9-dihydrocoscinamide B (1), as the first alkaloid from the genus Lacinutrix, whose structure was elucidated on the basis of extensive 1D and 2D NMR and HR-ESIMS experiments. This comprehensive strategy allowed us to unlock the previously unexploited metabolome of L. shetlandiensis sp. nov. WUR7.

Mass spectrometry-based metabolomic analysis as a tool for quality control of natural complex products

Metabolomics is an area of intriguing and growing interest. Since the late 1990s, when the first Omic applications appeared to study metabolite's pool ("metabolome"), to understand new aspects of the global regulation of cellular metabolism in biology, there have been many evolutions. Currently, there are many applications in different fields such as clinical, medical, agricultural, and food. In our opinion, it is clear that developments in metabolomics analysis have also been driven by advances in mass spectrometry (MS) technology. As natural complex products (NCPs) are increasingly used around the world as medicines, food supplements, and substance-based medical devices, their analysis using metabolomic approaches will help to bring more and more rigor to scientific studies and industrial production monitoring. This review is intended to emphasize the importance of metabolomics as a powerful tool for studying NCPs, by which significant advantages can be obtained in terms of elucidation of their composition, biological effects, and quality control. The different approaches of metabolomic analysis, the main and basic techniques of multivariate statistical analysis are also briefly illustrated, to allow an overview of the workflow associated with the metabolomic studies of NCPs. Therefore, various articles and reviews are illustrated and commented as examples of the application of MS-based metabolomics to NCPs.

Global analysis of the biosynthetic chemical space of marine prokaryotes

BACKGROUND

Marine prokaryotes are a rich source of novel bioactive secondary metabolites for drug discovery. Recent genome mining studies have revealed their great potential to bio-synthesize novel secondary metabolites. However, the exact biosynthetic chemical space encoded by the marine prokaryotes has yet to be systematically evaluated.

RESULTS

We first investigated the secondary metabolic potential of marine prokaryotes by analyzing the diversity and novelty of the biosynthetic gene clusters (BGCs) in 7541 prokaryotic genomes from cultivated and single cells, along with 26,363 newly assembled medium-to-high-quality genomes from marine environmental samples. To quantitatively evaluate the unexplored biosynthetic chemical space of marine prokaryotes, the clustering thresholds for constructing the biosynthetic gene cluster and molecular networks were optimized to reach a similar level of the chemical similarity between the gene cluster family (GCF)-encoded metabolites and molecular family (MF) scaffolds using the MIBiG database. The global genome mining analysis demonstrated that the predicted 70,011 BGCs were organized into 24,536 mostly new (99.5%) GCFs, while the reported marine prokaryotic natural products were only classified into 778 MFs at the optimized clustering thresholds. The number of MF scaffolds is only 3.2% of the number of GCF-encoded scaffolds, suggesting that at least 96.8% of the secondary metabolic potential in marine prokaryotes is untapped. The unexplored biosynthetic chemical space of marine prokaryotes was illustrated by the 88 potential novel antimicrobial peptides encoded by ribosomally synthesized and post-translationally modified peptide BGCs. Furthermore, a sea-water-derived Aquimarina strain was selected to illustrate the diverse biosynthetic chemical space through untargeted metabolomics and genomics approaches, which identified the potential biosynthetic pathways of a group of novel polyketides and two known compounds (didemnilactone B and macrolactin A 15-ketone).

CONCLUSIONS

The present bioinformatics and cheminformatics analyses highlight the promising potential to explore the biosynthetic chemical diversity of marine prokaryotes and provide valuable knowledge for the targeted discovery and biosynthesis of novel marine prokaryotic natural products. Video Abstract.

Toxicological effects of cyanobacterial metabolites on zebrafish larval development

Freshwater cyanobacteria are known worldwide for their potential to produce toxins. However, these organisms are also found in marine, terrestrial and extreme environments and produce unique compounds, other than toxins. Nevertheless, their effects on biological systems are still barely known. This work tested extracts of different cyanobacterial strains against zebrafish (Danio rerio) larvae and analyzed their metabolomic profiles using liquid chromatography combined with mass spectrometry. Strains Desertifilum tharense, Anagnostidinema amphibium, and Nostoc sp. promoted morphological abnormalities such as pericardial edema, edema in the digestive system region, curvature of the tail and spine in zebrafish larvae in vivo. In contrast, Microcystis aeruginosa and Chlorogloeopsis sp. did not promote such changes. Metabolomics revealed unique compounds belonging to the classes of terpenoids, peptides, and linear lipopeptides/microginins in the nontoxic strains. The toxic strains were shown to contain unique compounds belonging to the classes of cyclic peptides, amino acids and other peptides, anabaenopeptins, lipopeptides, terpenoids, and alkaloids and derivatives. Other unknown compounds were also detected, highlighting the rich structural diversity of secondary metabolites produced by cyanobacteria. The effects of cyanobacterial metabolites on living organisms, mainly those related to potential human and ecotoxicological risks, are still poorly known. This work highlights the diverse, complex, and unique metabolomic profiles of cyanobacteria and the biotechnological potential and associated risks of exposure to their metabolites.

Small Molecule in situ Resin Capture - A Compound First Approach to Natural Product Discovery

Microbial natural products remain an important resource for drug discovery. Yet, commonly employed discovery techniques are plagued by the rediscovery of known compounds, the relatively few microbes that can be cultured, and laboratory growth conditions that do not elicit biosynthetic gene expression among myriad other challenges. Here we introduce a culture independent approach to natural product discovery that we call the Small Molecule In situ Resin Capture (SMIRC) technique. SMIRC exploits in situ environmental conditions to elicit compound production and represents a new approach to access poorly explored chemical space by capturing natural products directly from the environments in which they are produced. In contrast to traditional methods, this compound-first approach can capture structurally complex small molecules across all domains of life in a single deployment while relying on Nature to provide the complex and poorly understood environmental cues needed to elicit biosynthetic gene expression. We illustrate the effectiveness of SMIRC in marine habitats with the discovery of numerous new compounds and demonstrate that sufficient compound yields can be obtained for NMR-based structure assignment. Two new compound classes are reported including one novel carbon skeleton that possesses a functional group not previously observed among natural products and a second that possesses potent biological activity. We introduce expanded deployments, in situ cultivation, and metagenomics as methods to facilitate compound discovery, enhance yields, and link compounds to producing organisms. This compound first approach can provide unprecedented access to new natural product chemotypes with broad implications for drug discovery.

Proteomic identification of beer brewing products in the ground layer of Danish Golden Age paintings

The application of mass spectrometry-based proteomics to artworks provides accurate and detailed characterization of protein-based materials used in their production. This is highly valuable to plan conservation strategies and reconstruct the artwork's history. In this work, the proteomic analysis of canvas paintings from the Danish Golden Age led to the confident identification of cereal and yeast proteins in the ground layer. This proteomic profile points to a (by-)product of beer brewing, in agreement with local artists' manuals. The use of this unconventional binder can be connected to the workshops within the Royal Danish Academy of Fine Arts. The mass spectrometric dataset generated from proteomics was also processed with a metabolomics workflow. The spectral matches observed supported the proteomic conclusions, and, in at least one sample, suggested the use of drying oils. These results highlight the value of untargeted proteomics in heritage science, correlating unconventional artistic materials with local culture and practices.

Nontarget Discovery of Antimicrobial Transformation Products in Wastewater Based on Molecular Networks

Antimicrobial transformation products (ATPs) in the environment have raised extensive concerns in recent years due to their potential health risks. However, only a few ATPs have been investigated, and most of the transformation pathways of antimicrobials have not been completely elucidated. In this study, we developed a nontarget screening strategy based on molecular networks to detect and identify ATPs in pharmaceutical wastewater. We identified 52 antimicrobials and 49 transformation products (TPs) with a confidence level of three or above. Thirty of the TPs had not been previously reported in the environment. We assessed whether TPs could be classified as persistent, mobile, and toxic (PMT) substances based on recent European criteria for industrial substances. Owing to poor experimental data, definitive PMT classifications could not be established for novel ATPs. PMT assessment based on structurally predictive physicochemical properties revealed that 47 TPs were potential PMT substances. These results provide evidence that novel ATPs should be the focus of future research.

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

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

Biogeographic patterns of biosynthetic potential and specialized metabolites in marine sediments

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

Peptidomics

Peptides are biopolymers, typically consisting of 2-50 amino acids. They are biologically produced by the cellular ribosomal machinery or by non-ribosomal enzymes and, sometimes, other dedicated ligases. Peptides are arranged as linear chains or cycles, and include post-translational modifications, unusual amino acids and stabilizing motifs. Their structure and molecular size render them a unique chemical space, between small molecules and larger proteins. Peptides have important physiological functions as intrinsic signalling molecules, such as neuropeptides and peptide hormones, for cellular or interspecies communication, as toxins to catch prey or as defence molecules to fend off enemies and microorganisms. Clinically, they are gaining popularity as biomarkers or innovative therapeutics; to date there are more than 60 peptide drugs approved and more than 150 in clinical development. The emerging field of peptidomics comprises the comprehensive qualitative and quantitative analysis of the suite of peptides in a biological sample (endogenously produced, or exogenously administered as drugs). Peptidomics employs techniques of genomics, modern proteomics, state-of-the-art analytical chemistry and innovative computational biology, with a specialized set of tools. The complex biological matrices and often low abundance of analytes typically examined in peptidomics experiments require optimized sample preparation and isolation, including in silico analysis. This Primer covers the combination of techniques and workflows needed for peptide discovery and characterization and provides an overview of various biological and clinical applications of peptidomics.

Polypharmacology-Labeled Molecular Networking: An Analytical Technology Workflow for Accelerated Identification of Multiple Bioactive Constituents in Complex Extracts

Discovery of sustainable and benign-by-design drugs to combat emerging health pandemics calls for new analytical technologies to explore the chemical and pharmacological properties of Nature's unique chemical space. Here, we present a new analytical technology workflow, polypharmacology-labeled molecular networking (PLMN), where merged positive and negative ionization tandem mass spectrometry-based molecular networking is linked with data from polypharmacological high-resolution inhibition profiling for easy and fast identification of individual bioactive constituents in complex extracts. The crude extract of Eremophila rugosa was subjected to PLMN analysis for the identification of antihyperglycemic and antibacterial constituents. Visually easy-interpretable polypharmacology scores and polypharmacology pie charts as well as microfractionation variation scores of each node in the molecular network provided direct information about each constituent's activity in the seven assays included in this proof-of-concept study. A total of 27 new non-canonical nerylneryl diphosphate-derived diterpenoids were identified. Serrulatane ferulate esters were shown to be associated with antihyperglycemic and antibacterial activities, including some showing synergistic activity with oxacillin in clinically relevant (epidemic) methicillin-resistant Staphylococcus aureus strains and some showing saddle-shaped binding to the active site of protein-tyrosine phosphatase 1B. PLMN is scalable in the number and types of assays included and thus holds potential for a paradigm shift toward polypharmacological natural-products-based drug discovery.

MAW: the reproducible Metabolome Annotation Workflow for untargeted tandem mass spectrometry

Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking. Here, we present an automated and reproducible Metabolome Annotation Workflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS²) input data pre-processing, spectral and compound database matching with computational classification, and in silico annotation. MAW takes the LC-MS² spectra as input and generates a list of putative candidates from spectral and compound databases. The databases are integrated via the R package Spectra and the metabolite annotation tool SIRIUS as part of the R segment of the workflow (MAW-R). The final candidate selection is performed using the cheminformatics tool RDKit in the Python segment (MAW-Py). Furthermore, each feature is assigned a chemical structure and can be imported to a chemical structure similarity network. MAW is following the FAIR (Findable, Accessible, Interoperable, Reusable) principles and has been made available as the docker images, maw-r and maw-py. The source code and documentation are available on GitHub ( https://github.com/zmahnoor14/MAW ). The performance of MAW is evaluated on two case studies. MAW can improve candidate ranking by integrating spectral databases with annotation tools like SIRIUS which contributes to an efficient candidate selection procedure. The results from MAW are also reproducible and traceable, compliant with the FAIR guidelines. Taken together, MAW could greatly facilitate automated metabolite characterization in diverse fields such as clinical metabolomics and natural product discovery.

Assessing the Effectiveness of Chemical Marker Extraction from Amazonian Plant Cupuassu (Theobroma grandiflorum) by PSI-HRMS/MS and LC-HRMS/MS

Employing a combination of liquid chromatography electrospray ionization and paper spray ionization high-resolution tandem mass spectrometry, extracts from cupuassu (Theobroma grandiflorum) pulp prepared with either water, methanol, acetonitrile or combinations thereof were subjected to metabolite fingerprinting. Among the tested extractors, 100% methanol extracted preferentially phenols and cinnamic acids derivatives, whereas acetonitrile and acetonitrile/methanol were more effective in extracting terpenoids and flavonoids, respectively. And while liquid chromatography- mass spectrometry detected twice as many metabolites as paper spray ionization tandem mass spectrometry, the latter proved its potential as a screening technique. Comprehensive structural annotation showed a high production of terpenes, mainly oleanane triterpene derivatives. of the mass spectra Further, five major metabolites with known antioxidant activity, namely catechin, citric acid, epigallocatechin-3′-glucuronide, 5,7,8-trihydroxyflavanone, and asiatic acid, were subjected to molecular docking analysis using the antioxidative enzyme peroxiredoxin 5 (PRDX5) as a model receptor. Based on its excellent docking score, a pharmacophore model of 5,7,8-trihydroxyflavanone was generated, which may help the design of new antioxidants.

Cost-effective hybrid long-short read assembly delineates alternative GC-rich Streptomyces hosts for natural product discovery

With the advent of rapid automated in silico identification of biosynthetic gene clusters (BGCs), genomics presents vast opportunities to accelerate natural product (NP) discovery. However, prolific NP producers, Streptomyces, are exceptionally GC-rich (>80%) and highly repetitive within BGCs. These pose challenges in sequencing and high-quality genome assembly which are currently circumvented via intensive sequencing. Here, we outline a more cost-effective workflow using multiplex Illumina and Oxford Nanopore sequencing with hybrid long-short read assembly algorithms to generate high quality genomes. Our protocol involves subjecting long read-derived assemblies to up to 4 rounds of polishing with short reads to yield accurate BGC predictions. We successfully sequenced and assembled 8 GC-rich Streptomyces genomes whose lengths range from 7.1 to 12.1 Mb with a median N50 of 8.2 Mb. Taxonomic analysis revealed previous misrepresentation among these strains and allowed us to propose a potentially new species, Streptomyces sydneybrenneri. Further comprehensive characterization of their biosynthetic, pan-genomic and antibiotic resistance features especially for molecules derived from type I polyketide synthase (PKS) BGCs reflected their potential as alternative NP hosts. Thus, the genome assemblies and insights presented here are envisioned to serve as gateway for the scientific community to expand their avenues in NP discovery.