Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

Bioactive Polyphenolic Compounds from Propolis of Tetragonula carbonaria in the Gibberagee Region, New South Wales, Australia

Stingless bee propolis has emerged globally as a new source of bioactive molecules that can advance human health. However, limited research has been conducted on Australian stingless bee propolis. This study investigated the chemical composition and biological activity of the propolis produced by the stingless bees Tetragonula carbonaria from Gibberagee, a distinct region of New South Wales state in Australia. Using bioassay-guided fractionation, twelve compounds were isolated, including six A-ring methylated flavonoids. Nine of these compounds demonstrated strong scavenging activity against 2,2-diphenyl-1-picrylhydrazyl radicals, with five exhibiting greater potency than vitamin C. Chemical structures of seven additional minor flavonoids were determined through an intensive MS/MS data analysis. In silico screening of these 19 compounds revealed that all, except for gallic acid, displayed a higher binding affinity to α-glucosidase than the antidiabetic drug, voglibose. This study showed that the Gibberagee stingless bee propolis is a promising source for nutraceutical and cosmeceutical applications owing to its strong antioxidant and antidiabetic properties. The unique profile of A-ring C-methylated flavonoids potentially provides valuable insights into its botanical origin.

Nuance in the Narrative of a Brown Poison Frog: Environmental Alkaloids and Specialized Foraging in a Presumed Toxin-Free and Diet-Generalized Species

In poison frogs (Dendrobatidae), conspicuous colors have evolved repeatedly in tandem with high numbers and quantities of skin toxins (alkaloids). Here, we focus on an inconspicuously-colored species-Silverstoneia flotator-which has long been deemed toxin-free and thought to forage opportunistically on mites and ants. Both assumptions have received some empirical support, but there is also evidence that predators avoid S. flotator. In a Panamanian S. flotator population, we sampled invertebrates in frog diets and the surrounding environment (using Berlese and pitfall traps) and screened for skin, dietary, and environmental alkaloids using untargeted metabolomics. We found that while the frogs are opportunistic consumers of mites and ants, they display preferences at finer taxonomic scales (for symphypleonan springtails and Pheidole ants). We also annotated 64 skin compounds as alkaloids, 38 of which were present in the environment. One alkaloid present in the skin and environment is likely the highly potent epibatidine. While the average biosynthetic (class and superclass) diversity of alkaloids in a dorsal skin sample is higher than that of a ventral skin and environmental-but not dietary-sample, environmental samples diverge more in their alkaloids' biosynthetic diversities than do dietary or skin samples. The frogs consume a consistent set of alkaloids, forage in a variable chemical space, and possess diverse dorsal skin alkaloids. They might use finer-scale diet specialization to modulate the types, quantities, and numbers of alkaloids they ingest. We encourage further examination of inconspicuously-colored taxa to better understand the ecological importance of diet-acquired toxins and specialized diets in these organisms.

Metabolomics and Molecular Networking Approach for Exploring the Effect of Light Intensity and Quality on the Chemical Profile and Accumulation of Glucosinolates in Broccoli Microgreen

Light intensity is a crucial factor impacting the cost-efficiency of controlled environment agriculture (CEA). Broccoli microgreens were cultivated under different photosynthetic photon flux densities: 50, 100, and 150 μmol•m-2•s-1 with white light-emitting diodes (LEDs), and an additional far-red (FR) light supplement (20% of total photon flux density) at the 50 μmol•m-2•s-1 intensity. This study examines how low light intensity influences the chemical profile and glucosinolate accumulation in broccoli microgreens through both nontargeted and targeted metabolomics with molecular networking analysis. The analysis identified 28 glucosinolates and 23 phenolic compounds with targeted quantification of 12 glucosinolates. The results showed that FR light supplementation significantly increased the total glucosinolate content compared to white light-only treatments, while similar glucosinolate levels were found across the different white light intensities. These findings provide valuable insights for optimizing LED light intensity to enhance glucosinolate accumulation in broccoli microgreens, thus promoting more efficient energy use in CEA.

Structural annotation of full-scan MS data: A unified solution for LC-MS and MS imaging analyses

Public liquid chromatography-mass spectrometry (LC-MS) and MS imaging metabolomics data repositories contain millions of files, with over 40% of them consisting solely of MS1 (full-scan) information, creating a significant gap in data reuse potential due to limited annotation capabilities. Here, we present ms1-id, an open-source Python package providing a unified solution for structural annotation of full-scan MS data applicable to both LC-MS and MS imaging analyses. Our approach leverages in-source fragments to generate pseudo MS/MS spectra through correlation analysis in either chromatographic or spatial domains. We introduce precursor-tolerant reverse spectral matching that accommodates multiple ion forms simultaneously and peak intensity scaling that enables matching of low-energy in-source fragments against existing reference MS/MS libraries. Applied to inflammatory bowel disease cohorts and diverse MS imaging samples, our method uncovers metabolites previously overlooked in traditional analyses. This strategy effectively addresses a critical need in metabolomics data reuse by enabling level 2/3 structural annotation of MS1-only data, facilitating new biological insights from existing repository data that was previously only annotated at the molecular formula level.

Last Decade Insights in Exploiting Marine Microorganisms as Sources of New Bioactive Natural Products

Marine microorganisms have emerged as prolific sources of bioactive natural products, offering a large chemical diversity and a broad spectrum of biological activities. Over the past decade, significant progress has been made in discovering and characterizing these compounds, pushed by technological innovations in genomics, metabolomics, and bioinformatics. Furthermore, innovative isolation and cultivation approaches have improved the isolation of rare and difficult-to-culture marine microbes, leading to the identification of novel secondary metabolites. Advances in synthetic biology and metabolic engineering have further optimized natural product yields and the generation of novel compounds with improved bioactive properties. This review highlights key developments in the exploitation of marine bacteria, fungi, and microalgae for the discovery of novel natural products with potential applications in diverse fields, underscoring the immense potential of marine microorganisms in the growing Blue Economy sector.

FIORA: Local neighborhood-based prediction of compound mass spectra from single fragmentation events

Non-targeted metabolomics holds great promise for advancing precision medicine and biomarker discovery. However, identifying compounds from tandem mass spectra remains a challenging task due to the incomplete nature of spectral reference libraries. Augmenting these libraries with simulated mass spectra can provide the necessary references to resolve unmatched spectra, but generating high-quality data is difficult. In this study, we present FIORA, an open-source graph neural network designed to simulate tandem mass spectra. Our main contribution lies in utilizing the molecular neighborhood of bonds to learn breaking patterns and derive fragment ion probabilities. FIORA not only surpasses state-of-the-art fragmentation algorithms, ICEBERG and CFM-ID, in prediction quality, but also facilitates the prediction of additional features, such as retention time and collision cross section. Utilizing GPU acceleration, FIORA enables rapid validation of putative compound annotations and large-scale expansion of spectral reference libraries with high-quality predictions.

Integrated Biological and Chemical Investigation of Indonesian Marine Organisms Targeting Anti-Quorum-Sensing, Anti-Biofilm, Anti-Biofouling, and Anti-Biocorrosion Activities

Microorganisms play a significant role in biofouling and biocorrosion within the maritime industry. Addressing these challenges requires an innovative and integrated approach utilizing marine natural products with beneficial properties. A comprehensive screening of 173 non-toxic EtOAc and H₂O extracts derived from diverse marine organisms collected in Indonesian waters was conducted using a robust panel of assays. These included antimicrobial tests and classical biosurfactant assays (drop collapse and oil displacement), as well as anti-quorum-sensing (QS) and anti-biofilm assays. These screening efforts identified five active extracts with promising activities. Among these, EtOAc extracts of the marine tunicate Sigilina cf. signifera (0159-22e) and the marine sponge Lamellodysidea herbacea (0194-24c) demonstrated significant anti-biofouling activity against Perna indica and anti-biocorrosion performance (mpy 10.70 ± 0.70 for S. cf. signifera; 7.87 ± 0.86 for L. herbacea; 13.60 ± 1.70 for positive control Tetracorr CI-2915). Further chemical analyses of the active extracts, including LC-HR-MS/MS, MS-based molecular networking, and chemoinformatics, revealed the presence of both known and new bioactive compounds. These included tambjamines and polybrominated diphenyl ethers (PBDEs), which are likely contributors to the observed bioactivities. Subsequent investigations uncovered new anti-QS and anti-biofilm properties in synthetic and natural PBDEs 1-12 previously derived from L. herbacea. Among these, 8 exhibited the most potent anti-QS activity, with an IC50 value of 15 µM, while 4 significantly reduced biofilm formation at a concentration of 1 µM. This study highlights the potential of marine-derived compounds in addressing biofouling and biocorrosion challenges in a sustainable and effective manner.

Untargeted Metabolomics and Targeted Phytohormone Profiling of Sweet Aloes (Euphorbia neriifolia) from Guyana: An Assessment of Asthma Therapy Potential in Leaf Extracts and Latex

Background/Objectives:Euphorbia neriifolia is a succulent plant from the therapeutically rich family of Euphorbia comprising 2000 species globally. E. neriifolia is used in Indigenous Guyanese asthma therapy. Methods: To investigate E. neriifolia's therapeutic potential, traditionally heated leaf, simple leaf, and latex extracts were evaluated for phytohormones and therapeutic compounds. Full scan, data-dependent acquisition, and parallel reaction monitoring modes via liquid chromatography Orbitrap mass spectrometry were used for screening. Results: Pathway analysis of putative features from all extracts revealed a bias towards the phenylpropanoid, terpenoid, and flavonoid biosynthetic pathways. A total of 850 compounds were annotated using various bioinformatics tools, ranging from confidence levels 1 to 3. Lipids and lipid-like molecules (34.35%), benzenoids (10.24%), organic acids and derivatives (12%), organoheterocyclic compounds (12%), and phenylpropanoids and polyketides (10.35%) dominated the contribution of compounds among the 13 superclasses. Semi-targeted screening revealed 14 out of 16 literature-relevant therapeutic metabolites detected, with greater upregulation in traditional heated extracts. Targeted screening of 39 phytohormones resulted in 25 being detected and quantified. Simple leaf extract displayed 4.4 and 45 times greater phytohormone levels than traditional heated leaf and latex extracts, respectively. Simple leaf extracts had the greatest nucleotide and riboside cytokinin and acidic phytohormone levels. In contrast, traditional heated extracts exhibited the highest free base and glucoside cytokinin levels and uniquely contained methylthiolated and aromatic cytokinins while lacking acidic phytohormones. Latex samples had trace gibberellic acid levels, the lowest free base, riboside, and nucleotide levels, with absences of aromatic, glucoside, or methylthiolated cytokinin forms. Conclusions: In addition to metabolites with possible therapeutic value for asthma treatment, we present the first look at cytokinin phytohormones in the species and Euphorbia genus alongside metabolite screening to present a comprehensive assessment of heated leaf extract used in Indigenous Guyanese asthma therapy.

SimMS: a GPU-accelerated cosine similarity implementation for tandem mass spectrometry

MOTIVATION

Untargeted metabolomics involves a large-scale comparison of the fragmentation pattern of a mass spectrum against a database containing known spectra. Given the number of comparisons involved, this step can be time-consuming.

RESULTS

In this work, we present a GPU-accelerated cosine similarity implementation for Tandem Mass Spectrometry (MS), with an approximately 1000-fold speedup compared to the MatchMS reference implementation, without any loss of accuracy. This improvement enables repository-scale spectral library matching for compound identification without the need for large compute clusters. This impact extends to any spectral comparison-based methods such as molecular networking approaches and analogue search.

AVAILABILITY AND IMPLEMENTATION

All code, results, and notebooks supporting are freely available under the MIT license at https://github.com/pangeAI/simms/.

Entropy Similarity-Driven Transformation Reaction Molecular Networking Reveals Transformation Pathways and Potential Risks of Emerging Contaminants in Wastewater: The Example of Sartans

The transformation pathways and risks of emerging contaminants (ECs) in wastewater remain unclear due to the limited throughput of nontarget screening. In this study, an improved method called entropy similarity-driven transformation reaction molecular networking (ESTRMN) was developed to identify transformation products (TPs) in wastewater. In detail, entropy similarity was the most effective algorithm for identifying parent-product spectrum pairs and a threshold of 0.5 for it was determined with the guarantee of high specificity. Additionally, a TP structure database predicted according to known structures and reactions was established to assist in identification. Sartan is one of the most commonly used angiotensin II receptor blocker antihypertensive drugs. Take sartans as an example, 69 TPs of sartans with confidence levels above 3 were identified by ESTRMN, 43 of which were newly discovered. The most common reactions included hydroxylation, hydrolysis, and oxidation, resulting in the majority of sartan TPs exhibiting higher persistence, mobility, and toxicity (PMT) than their parents. The concentration of 75% sartans and TPs increased after treatment in a WWTP, and the overall risk has not been effectively mitigated. This study emphasizes the role of ESTRMN in incorporating TPs of ECs into environmental monitoring protocols and risk assessment frameworks for wastewater management.

Actinomycetota isolated from the sponge Hymeniacidon perlevis as a source of novel compounds with pharmacological applications: diversity, bioactivity screening, and metabolomic analysis

AIMS

To combat health conditions, such as multi-resistant bacterial infections, cancer, and metabolic diseases, new drugs need to be urgently found and, in this respect, marine Actinomycetota have a high potential to produce secondary metabolites with pharmacological importance. We aimed to study the cultivable Actinomycetota community associated with a marine sponge from the Portuguese coast, Hymeniacidon perlevis, and investigate the potential of the retrieved isolates to produce compounds with antimicrobial, anticancer and anti-obesity properties.

METHODS AND RESULTS

The analysis of the 16S rRNA gene revealed 79 Actinomycetota isolates affiliated with 12 genera-Brachybacterium, Dietzia, Glutamicibacter, Gordonia, Micrococcus, Micromonospora, Nocardia, Nocardiopsis, Paenoartrhobacter, Rhodococcus, Streptomyces, and Tsukamurella, most of which affiliated with the genus Streptomyces. The screening of antimicrobial activity revealed 13 strains, all belonging to the Streptomyces genus, capable of inhibiting the growth of Candida albicans, Bacillus subtilis, or Staphylococcus aureus. Forty-three extracts exhibited cytotoxic activity against at least one tested cell line (HepG2, HCT-116, and hCMEC-D3). Three extracts that were active against the two cancer cell lines tested, did not reduce the viability of the non-cancer endothelial cell line, hCMEC-D3. One Gordonia strain exhibited anti-obesity activity, revealed by its ability to reduce the neutral lipids in zebrafish larvae. Mass spectrometry-based dereplication analysis of active extracts identified several compounds associated with known Actinomycetota natural products. Nonetheless, five clusters contained metabolites that did not match any annotated natural products, suggesting they may represent new bioactive molecules.

CONCLUSIONS

This work contributed to increase the knowledge on the diversity and bioactive potential of Actinomycetota associated with H. perlevis.

A comparative metabolomics analysis of Açaí (Euterpe oleracea Mart.) fruit, food powder, and botanical dietary supplement extracts

INTRODUCTION

Euterpe oleracea Mart. (açaí) is a botanical of interest to many who seek functional foods that provide antioxidant and anti-inflammatory properties. Cancer patients are increasingly taking botanical dietary supplements containing açaí to complement their conventional therapeutics, which may lead to serious adverse events. Before testing our açaí extracts in vitro for botanical-drug interactions, the goal is to chemically characterize our extracts for compounds whose biological activity in açaí is unknown.

OBJECTIVE

The objective of this work was to develop a chemical fingerprinting method for untargeted characterization of açaí samples from a variety of sources, including food products and botanical dietary supplement capsules, made with multiple extraction solvents.

METHODS

An optimized LC-MS method was generated for in-depth untargeted fingerprinting of chemical constituents in açaí extracts. Statistical analysis models were used to describe relationships between the açaí extracts based on molecular features found in both positive and negative mode ESI.

RESULTS

In an attempt to elucidate the differences in metabolites among açaí extracts from different cultivars, we identified or tentatively identified 173 metabolites from the 16 extracts made from 6 different sources. Of these compounds, there are 138 reported in açaí for the first time. Statistical models showed similar yet distinct differences between the extracts tested based on the polarity of compounds present and the origin of the source material.

CONCLUSION

A high-resolution mass spectrometry method was generated that allowed us to greatly characterize 16 complex extracts made from different sources of açaí with different extraction solvent polarities.

Computational metabolomics reveals overlooked chemodiversity of alkaloid scaffolds in Piper fimbriulatum

Plant specialized metabolites play key roles in diverse physiological processes and ecological interactions. Identifying structurally novel metabolites, as well as discovering known compounds in new species, is often crucial for answering broader biological questions. The Piper genus (Piperaceae family) is known for its special phytochemistry and has been extensively studied over the past decades. Here, we investigated the alkaloid diversity of Piper fimbriulatum, a myrmecophytic plant native to Central America, using a metabolomics workflow that combines untargeted LC-MS/MS analysis with a range of recently developed computational tools. Specifically, we leverage open MS/MS spectral libraries and metabolomics data repositories for metabolite annotation, guiding isolation efforts toward structurally new compounds (i.e., dereplication). As a result, we identified several alkaloids belonging to five different classes and isolated one novel seco-benzylisoquinoline alkaloid featuring a linear quaternary amine moiety which we named fimbriulatumine. Notably, many of the identified compounds were never reported in Piperaceae plants. Our findings expand the known alkaloid diversity of this family and demonstrate the value of revisiting well-studied plant families using state-of-the-art computational metabolomics workflows to uncover previously overlooked chemodiversity. To contextualize our findings within a broader biological context, we employed a workflow for automated mining of literature reports of the identified alkaloid scaffolds and mapped the results onto the angiosperm tree of life. By doing so, we highlight the remarkable alkaloid diversity within the Piper genus and provide a framework for generating hypotheses on the biosynthetic evolution of these specialized metabolites. Many of the computational tools and data resources used in this study remain underutilized within the plant science community. This manuscript demonstrates their potential through a practical application and aims to promote broader accessibility to untargeted metabolomics approaches.

Rapid isolation of cytotoxic daphnane diterpenoids from Daphne altaica Pall. using MS-DIAL

Daphnane diterpenoids occurring in plants of the Thymelaeaceae are the focus of natural product drug discovery because of the wide range of their therapeutically biological activities. Considering the limited occurrence in some plants of the Thymelaeaceae, it is imperative to design a strategy for the target isolation of daphnane diterpenoids. In this study, a strategy was developed to filter the data using MZmine, generate the molecular network using the Global Natural Product Social Molecular Network Platform (GNPS), and determine the retention time of target compounds using MS-DIAL. Under the guidance of the approach which integrates the analysis of LC-MS/MS, compounds 1-5, representative diterpenoids from Daphne altaica Pall., were isolated. Their structures were determined through detailed spectroscopic analyses and ECD calculations. The growth-inhibitory activities of the isolated compounds against MCF-7, A549, and HepG2 cell lines was examined. Notably, compound 1 demonstrated the most noticeable cytotoxicity, exhibiting potent growth inhibition activities against A549 and HepG2 cells with IC50 values of 2.89 μM and 5.30 μM, respectively. Further morphological and staining analyses corroborated that compound 1 induced apoptosis in A549 and HepG2 cells, highlighting its potential as a bioactive agent.

Presence of polyketide synthases and nonribosomal peptide synthetase in culturable bacteria associated with Aplysina fulva and Aplysina caissara (Porifera)

Culture-dependent and -independent studies have provided access to symbiont genes and the functions they play for host sponges. Thus, this work investigates the diversity, presence of genes of pharmacological interest, biological activities and metabolome of the bacteria isolated from the sponges Aplysina caissara and Aplysina fulva collected on the southwestern Atlantic Coast. The genes for Polyketide Synthases types I and II and Nonribosomal Peptide Synthetases were screened in more than 200 bacterial strains obtained, from which around 40% were putatively novel. Twenty-two were positive for at least one of the genes screened. Among them, 12 exhibited antimicrobial activities and one inhibited the proliferation of cancer cells. The metabolic profiles of the 22 strains were analyzed by liquid chromatography with tandem mass spectrometry and molecular network. The Global Natural Products Social Molecular Networking MolNetEnhancer workflow provided a more comprehensive understanding of the metabolic profiles. The results revealed the existence of a wide range of metabolites, however more than half of the compounds could not be identified. It was further observed that the metabolic diversity among the strains varied primarily due to the cultivation medium used. Together the results obtained here revealed the pharmacological potential of the bacteria isolated from Aplysina species.

Recent advances in precision nutrition and cardiometabolic diseases

A growing body of research on nutrition omics has led to recent advances in cardiovascular disease epidemiology and prevention. Within the PREDIMED trial, significant associations between diet-related metabolites and cardiovascular disease were identified, which were subsequently replicated in independent cohorts. Some notable metabolites identified include plasma levels of ceramides, acyl-carnitines, branched-chain amino acids, tryptophan, urea cycle pathways, and the lipidome. These metabolites and their related pathways have been associated with incidence of both cardiovascular disease and type 2 diabetes. Future directions in precision nutrition research include: a) developing more robust multimetabolomic scores to predict long-term risk of cardiovascular disease and mortality; b) incorporating more diverse populations and a broader range of dietary patterns; and c) conducting more translational research to bridge the gap between precision nutrition studies and clinical applications.

Microbial Community Metabolism of Coral Reef Exometabolomes Broadens the Chemodiversity of Labile Dissolved Organic Matter

Dissolved organic matter (DOM) comprises diverse compounds with variable bioavailability across aquatic ecosystems. The sources and quantities of DOM can influence microbial growth and community structure with effects on biogeochemical processes. To investigate the chemodiversity of labile DOM in tropical reef waters, we tracked microbial utilisation of over 3000 untargeted mass spectrometry ion features exuded from two coral and three algal species. Roughly half of these features clustered into over 500 biologically labile spectral subnetworks annotated to diverse structural superclasses, including benzenoids, lipids, organic acids, heterocyclics and phenylpropanoids, comprising on average one-third of the ion richness and abundance within each chemical class. Distinct subsets of these labile compounds were exuded by algae and corals during the day and night, driving differential microbial growth and substrate utilisation. This study expands the chemical diversity of labile marine DOM with implications for carbon cycling in coastal environments.

Chemical Profiling and Quality Evaluation of Gualou-Xiebai Herbal Pair by Liquid Chromatography-Tandem Mass Spectrometry With Feature-Based Molecular Network and High-Performance Liquid Chromatography With Charged Aerosol Detector

Gualou-Xiebai (GX), a traditional Chinese herbal pair, is often used in the treatment of cardiovascular diseases. However, the investigation into the components of GX is not comprehensive enough. In order to obtain the chemical profile of GX, a method that combined mass spectrometry with a feature-based molecular network was utilized for the identification of its complex constituents. In total, 121 compounds were annotated and four potential new compounds were inferred. In addition, an optimized fingerprint analysis method using high-performance liquid chromatography coupled with a charged aerosol detector was established, which was further validated and implemented for the simultaneous quantification of 17 ingredients in GX, including the semi-quantitative analysis of 13 allium saponins and the quantitative analysis of four fatty acids. This method achieved the detection of no ultraviolet absorption constituents in GX. The results have an important impact on revealing the chemical basis of GX and lay a foundation for further quality assessment.

Targeted and untargeted discovery of UV filters and emerging contaminants with environmental risk assessment on the Northwestern Mediterranean coast

Marine ecosystems, particularly coastal areas, are becoming increasingly vulnerable to pollution from human activities. Persistent organic pollutants and contaminants of emerging concern (CECs) are recognized as significant threats to both human and environmental health. Our study aimed to identify the molecules present in the seawater of two bathing areas in the Western Mediterranean Sea. Polar Organic Chemical Integrative Samplers were employed for passive sampling of UV filters and other contaminants in the seawater. The concentrations of UV filters bemotrizinol (BEMT), benzophenone-3 (BP3), diethylamino hydroxybenzoyl hexyl benzoate (DHHB), octyl triazone (ET), and octocrylene (OC) were measured at these bathing sites during the summer of 2022. In addition, non-targeted chemical analysis was used to complement the list of pollutants in the sampling areas, leading to the identification of 53 contaminants and three natural products. Dodecyltrimethylammonium (DTA) and tetradecyltrimethylammonium (TTA) ions, 1,3-diphenylguanidine (DPG), N,N-diethyl-m-toluamide (DEET), and crystal violet (CV) were successfully quantified. Risk assessments showed that DEET, DPG, and BP3 present low environmental risks at the detected concentrations, while CV, DTA, and TTA pose medium to high risks, warranting further investigation. OC was found to pose a significant risk to marine biodiversity, as its environmental concentrations exceeded predicted no-effect concentration values. Overall, this study highlights the complexity of environmental pollution in coastal bathing areas and underscores the urgent need for comprehensive risk assessments to safeguard marine life and public health.

Seasonal changes in bay water column properties and their influence on the distribution of dissolved and particulate substances along the south coast of Curaçao (Caribbean Sea)

As endpoints of watersheds, bays concentrate erosion- and human-derived substances such as dissolved inorganic nutrients and pollutants. We investigated the water movement and biogeochemistry of two bays in Curaçao: Piscadera Bay and Spaanse Water, during the dry (May 2022 and 2023) and wet seasons (November 2021 and 2023). Bay-ocean exchange was limited during the dry season, enhancing nutrient concentrations in the bays. The wet season showed increased mixing between bay and offshore water. Extreme rainfall from the 2023 El Niño event led to heavy runoff and wastewater influx, particularly in Piscadera Bay, where enriched δ15N and total xenobiotic concentrations were over 1.5 times higher than in the dry season. Elevated δ15N and δ13C values reflected greater terrestrial influence in Piscadera Bay. These findings show how extreme weather, likely under future climate scenarios, can enhance nutrient and pollutant export from bays to reefs.

Recent advances in precision nutrition and cardiometabolic diseases

A growing body of research on nutrition omics has led to recent advances in cardiovascular disease epidemiology and prevention. Within the PREDIMED trial, significant associations between diet-related metabolites and cardiovascular disease were identified, which were subsequently replicated in independent cohorts. Some notable metabolites identified include plasma levels of ceramides, acyl-carnitines, branched-chain amino acids, tryptophan, urea cycle pathways, and the lipidome. These metabolites and their related pathways have been associated with incidence of both cardiovascular disease and type 2 diabetes. Future directions in precision nutrition research include: a) developing more robust multimetabolomic scores to predict long-term risk of cardiovascular disease and mortality; b) incorporating more diverse populations and a broader range of dietary patterns; and c) conducting more translational research to bridge the gap between precision nutrition studies and clinical applications.

Navigating the challenges of engineering composite specialized metabolite pathways in plants

Plants are a valuable source of diverse specialized metabolites with numerous applications. However, these compounds are often produced in limited quantities, particularly under unfavorable ecological conditions. To achieve sufficient levels of target metabolites, alternative strategies such as pathway engineering in heterologous systems like microbes (e.g., bacteria and fungi) or cell-free systems can be employed. Another approach is plant engineering, which aims to either enhance the native production in the original plant or reconstruct the target pathway in a model plant system. Although increasing metabolite production in the native plant is a promising strategy, these source plants are often exotic and pose significant challenges for genetic manipulation. Effective pathway engineering requires comprehensive prior knowledge of the genes and enzymes involved, as well as the precursor, intermediate, branching, and final metabolites. Thus, a thorough elucidation of the biosynthetic pathway is closely linked to successful metabolic engineering in host or model systems. In this review, we highlight recent advances in strategies for biosynthetic pathway elucidation and metabolic engineering. We focus on efforts to engineer complex, multi-step pathways that require the expression of at least eight genes for transient and three genes for stable transformation. Reports on the engineering of complex pathways in stably transformed plants remain relatively scarce. We discuss the major hurdles in pathway elucidation and strategies for overcoming them, followed by an overview of achievements, challenges, and solutions in pathway reconstitution through metabolic engineering. Recent advances including computer-based predictions offer valuable platforms for the sustainable production of specialized metabolites in plants.

Optimized production of concanamycins using a rational metabolic engineering strategy

Plecomacrolides, such as concanamycins and bafilomycins, are potent and specific inhibitors of vacuolar-type ATPase. Concanamycins are 18-membered macrolides with promising therapeutic potential against multiple diseases, including viral infection, osteoporosis, and cancer. Due to the complexity of their total synthesis, the production of concanamycins is only achieved through microbial fermentation. However, the low titers of concanamycin A and its analogs in the native producing strains are a significant bottleneck for scale-up, robust structure-activity relationship studies, and drug development. To address this challenge, we designed a library of engineered Streptomyces strains for the overproduction of concanamycin A-C by combining the overexpression of target regulatory genes with the optimization of fermentation media. Integration of two endogenous regulators from the concanamycin biosynthetic gene cluster (cms) and one heterologous regulatory gene from the bafilomycin biosynthetic gene cluster significantly increased production of concanamycin A and its less abundant analog concanamycin B in Streptomyces eitanensis. The highest titers reported to date were observed in the engineered S. eitanensis DHS10676, which produced over 900 mg/L of concanamycin A and 300 mg/L of concanamycin B. Heterologous overexpression of the identified target regulatory genes across a panel of Streptomyces spp. harboring a putative concanamycin biosynthetic gene cluster confirmed its identity, and significantly improved concanamycin A production in all tested strains. Strain engineering, optimization of fermentation, and extraction purification protocols enabled swift access to these structurally complex plecomacrolides for semi-synthetic medicinal chemistry-based approaches. Together, this work established a platform for robust overproduction of concanamycin analogs across species.

Untargeted Metabolomics Analysis Reveals Differential Accumulation of Flavonoids Between Yellow-Seeded and Black-Seeded Rapeseed Varieties

Rapeseed (Brassica napus) is an important oilseed crop and yellow-seeded and black-seeded varieties have different metabolite profiles, which determines the quality and edibility of their oil. In this study, we performed a non-targeted metabolomics analysis of seeds from four rapeseed varieties at eight developmental stages. This analysis identified 4540 features, of which 366 were annotated as known metabolites. The content of these metabolites was closely related to seed developmental stage, with the critical period for seed metabolite accumulation being between 10 and 20 days after pollination. Through a comparative analysis, we identified 18 differentially abundant flavonoid features between yellow-seeded and black-seeded rapeseed varieties. By combining the flavonoid data with transcriptome data, we constructed a gene regulatory network that may reflect the accumulation of differentially abundant flavonoid features. Finally, we predicted 38 unknown features as being flavonoid features through molecular networking. These results provide valuable metabolomics information for the breeding of yellow-seeded rapeseed varieties.

Intraspecific variability within Karlodinium armiger (Dinophyceae) on a toxicological and metabolomic level

The species Karlodinium armiger occasionally co-occurs with Karlodinium veneficum during harmful algal blooms. The only toxin of this species described so far is karmitoxin, a highly ichthyotoxic compound very similar to the karlotoxins produced by K. veneficum. However, information on K. armiger is limited and based on a single Mediterranean strain (K-0668), with few studies investigating its toxicity. Given the high intraspecific variability known in K. veneficum, it was a significant achievement when two additional strains of K. armiger (MD-D6 and MD-D7) were isolated from the Labrador Sea in 2017, enabling comparative studies within this species. The toxicity of these three strains was assessed using the fish gill cell line RTgill-W1 and the cryptophyte Rhodomonas salina. An untargeted metabolomics approach using high-resolution tandem mass spectrometry, along with a computational workflow, provided insights into the metabolomic differences between the strains. Despite being cultivated under identical conditions, the metabolomic profiles and toxicological properties were distinct, even between MD-D6 and MD-D7, which were isolated from the same water sample. While MD-D7 did not exhibit significant toxicity, MD-D6 showed high toxicity and lytic potential, similar to K-0668. Interestingly, karmitoxin was only detected in K-0668, and neither karlotoxins nor any known analogs were detected in any strain. Within this comprehensive workflow, some molecules were found in MD-D6 that share the same chemical space as karmitoxin, making them interesting targets for further research. In conclusion, this study evaluated the toxicological and metabolic variability in three different strains of K. armiger and identified some putative toxin candidates in MD-D6.

Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics

The rediscovery of known drug classes represents a major challenge in natural products drug discovery. Compound rediscovery inhibits the ability of researchers to explore novel natural products and wastes significant amounts of time and resources. This study introduces a novel machine learning framework that can effectively characterize the bioactivity of natural products by leveraging liquid chromatography tandem mass spectrometry and untargeted metabolomics analysis. This accelerates natural product drug discovery by addressing the challenge of dereplicating previously discovered bioactive compounds. Utilizing the SIRIUS 5 metabolomics software suite and in-silico-generated fragmentation spectra, we have trained a ML model capable of predicting a compound's drug class. This approach enables the rapid identification of bioactive scaffolds from LC-MS/MS data, even without reference experimental spectra. The model was trained on a diverse set of molecular fingerprints generated by SIRIUS 5 to effectively classify compounds based on their core pharmacophores. Our model robustly classified 21 diverse bioactive drug classes, achieving accuracies greater than 93% on experimental spectra. This study underscores the potential of ML combined with MFPs to dereplicate bioactive natural products based on pharmacophore, streamlining the discovery process and expediting improved methods of isolating novel antibacterial and antifungal agents.

Otitiglycomycins A and B: Glycolipids from the Strain Nocardia otitidiscavarum 20S-13 with Antiviral Activity against Zika Virus

The Zika virus (ZIKV), an emerging orthoflavivirus, presents a significant public health threat due to its rapid dissemination and association with severe neurological complications. The urgent need for effective antiviral agents has driven research into novel bioactive compounds derived from unique natural sources. Microorganisms inhabiting extreme environments are particularly promising for such discoveries due to their potential to produce unique metabolites. In this study, we explored microorganisms from the underexplored French Polynesian microbial mats known as "Kopara" to identify new bioactive natural products. Using a molecular networking-based dereplication strategy, we investigated various culture and extraction techniques of the strain Nocardia otitidiscaviarum 20-S13, leading to the discovery of two novel glycoglycerolipids, otitiglycomycins A and B (1 and 2). Structure elucidation of these compounds was achieved through NMR spectroscopy, X-ray crystallography, and TDDFT-specific rotation prediction. We found that otitiglycomycin A (1), but not otitiglycomycin B (2), suppresses ZIKV infection at non cytotoxic concentrations without effects on cell viability. Time-of-drug addition assays along with virus inactivation and binding assays demonstrated that 1 neutralizes ZIKV infectivity by preventing the virus from attaching to the host cell membrane.

Cyclodepsipeptides and Fatty Acid Lactones from the Freshwater-Derived Fungus, Talaromyces gwangjuensis, and Their Potential as Autophagy Activators

Autophagy is a primary cellular mechanism that entails the degradation and recycling of impaired or redundant cellular constituents. It plays an essential role in maintaining cellular health and homeostasis. Dysfunction in autophagy has been implicated in a wide range of diseases, including cancer, cardiovascular diseases, and neurodegenerative diseases. A total of 200 fungal extracts were screened for their ability to modulate autophagy in HEK293A cells, a human kidney cell line stably expressing GFP-tagged LC3, a marker of autophagy. A potential autophagy regulator extract was identified from the freshwater-derived fungus, Talaromyces gwangjuensis. Through the implementation of Feature-Based Molecular Networking (FBMN), seven cyclodepsipeptides (1-7) and four lactone derivatives (8-11) were isolated from the bioactive fractions. The chemical structure of the newly isolated compounds, arthrichitins E-H (1-4) and gwangjupones A-D (8-11), were elucidated using 1D and 2D NMR spectroscopy, Marfey's analysis, J-based configuration analysis, ECD, and DP4+ probability calculations. Compounds 1, 4, and 6 were found to stimulate autophagic flux in IMR90 cells infected with an adeno-associated virus carrying an mCherry-GFP-LC3 construct, highlighting their potential as autophagy activators.

A guide to reverse metabolomics-a framework for big data discovery strategy

Untargeted metabolomics is evolving into a field of big data science. There is a growing interest within the metabolomics community in mining tandem mass spectrometry (MS/MS)-based data from public repositories. In traditional untargeted metabolomics, samples to address a predefined question are collected and liquid chromatography with MS/MS data are generated. We then identify metabolites associated with a phenotype (for example, disease versus healthy) and elucidate or validate their structural details (for example, molecular formula, structural classification, substructure or complete structural annotation or identification). In reverse metabolomics, we start with MS/MS spectra for known or unknown molecules. These spectra are used as search terms to search public data repositories to discover phenotype-relevant information such as organ/biofluid distribution, disease condition, intervention status (for example, pre- and postintervention), organisms (for example, mammals versus others), geography and any other biologically relevant associations. Here we guide the reader through a four-part process: (1) obtaining the MS/MS spectra of interest (Universal Spectrum Identifier) and (2) Mass Spectrometry Search Tool searches to find the files associated with the MS/MS that are in available databases, (3) using the Reanalysis Data User Interface framework to link the files with their metadata and (4) validating the observations. Parts 1-3 could take from hours to days depending on the method used for collecting MS/MS spectra. For example, we use MS/MS spectra from three small molecules: phenylalanine-cholic acid (a microbially conjugated bile acid), phenylalanine-C4:0 and histidine-C4:0 (two N-acyl amides). We leverage the Global Natural Products Social Molecular Networking-based framework to explore the microbial producers of these molecules and their associations with health conditions and organ distributions in humans and rodents.

Genome mining and metabolite profiling illuminate the taxonomy status and the cytotoxic activity of a mangrove-derived Microbacterium alkaliflavum sp. nov

The genus Microbacterium in the phylum Actinomycetota contains over 100 species to date that little is known about their bioactive metabolites production. In this study, a mangrove sediment-derived strain B2969T was identified as a novel type strain within the genus Microbacterium due to the low 16S rRNA gene sequence similarity (< 99%), and low overall genome relatedness indices (ANI, 75.4%-79.5%; dDDH, 18.5%-22.7%, AAI, 68.7%-76.3%; POCP, 48.3%-65.0%) with the validly named species of the genus. The type strain B2969T (= MCCC 1K099113T = JCM 36707 T) is proposed to represent Microbacterium alkaliflavum sp. nov.. The crude extracts of strain B2969T showed weak cytotoxicity against NPC cell lines TW03 and 5-8F, with IC50 values of ranging from 3.5 µg/µL to 2.4 µg/µL respectively. Genome analysis of strain B2969T found 8 clusters of genes responsible for secondary metabolite biosynthesis, including cytotoxic compounds desferrioxamines. In addition, the application of liquid chromatography tandem mass spectrometry (LC-MS/MS)-based molecular networking strategy led to the identification of 10 compounds with potent cytotoxic activity in ethyl acetate extracts of strain B2969T. Results from the cytotoxicity assay, genome mining, and metabolite profiling based on LC-MS/MS analysis revealed its ability to produce bioactive compounds.BackgroundMangrove ecosystems are largely unexplored sources of Actinomycetota, which represent potential important reservoirs of bioactive compounds. The genus Microbacterium in the phylum Actinomycetota contains over 100 species to date that little is known about their bioactive metabolites production. In this study, a novel species, namely B2969T, within the genus Microbacterium that showed cytotoxicity against nasopharyngeal carcinoma (NPC) cell lines was isolated from mangrove sediments. Genome mining and metabolic profiling analyses were explored here to assess its biosynthetic potential of metabolites with cytotoxic properties.ResultsHere, a mangrove sediment-derived strain B2969T was identified as a novel species within the genus Microbacterium due to the low 16S rRNA gene sequence similarity (< 99.0%), and low overall genome relatedness indices (ANI, 75.4%-79.5%; dDDH, 18.5%-22.7%, AAI, 68.7%-76.3%; POCP, 48.3%-65.0%) with the type strains of this genus. We proposed that strain B2969T represents a new species, in which the name Microbacterium alkaliflavum sp. nov. is proposed. The strain showed weak cytotoxicity against NPC cell lines TW03 and 5-8F, with IC50 values of ranging from 3.512 µg/µL to 2.428 µg/µL respectively. Genome analysis of strain B2969T found 8 clusters of genes responsible for secondary metabolite biosynthesis, including desferrioxamines. In addition, the application of liquid chromatography tandem mass spectrometry (LC-MS/MS)-based molecular networking strategy led to the identification of 10 potent cytotoxic compounds in ethyl acetate extracts of strain B2969T.ConclusionsThis study confirmed the taxonomy status of type strain B2969T (= MCCC 1K099113T = JCM 36707 T) within the genus Microbacterium, in which the name Microbacterium alkaliflavum sp. nov.. Results from the cytotoxicity assay, genome mining, and metabolite profiling based on LC-MS/MS analysis revealed its ability to produce bioactive substances, providing sufficient evidence for the potential of Microbacterium species in the discovery of novel pharmaceuticals.

Aqueous and Ethanol Extracts of Acacia sieberiana (Fabaceae) Stem Bark Reverse the Pain-Depression Dyad in Mice Through Modulation of Catecholamines, Proinflammatory Cytokines, and Oxidative Stress

Rationale and Objective: The pain-depression dyad is highly prevalent and has reciprocal psychological and behavioral effects, leading to poor quality of life, increased disability, and challenging therapeutic outcomes. In an attempt to find better substances that can target pain-depression comorbidity, we examined the effect of aqueous (AE) and ethanol (EE) extracts from Acacia sieberiana (A. sieberiana) stem bark on reserpinized mice (female and male Swiss albino mice aged 2-3 months). Methods: The dyad was induced with 3 injections (Days 1-3) of reserpine (1 mg/kg/day, s.c.). Then, animals were treated (Days 4-8) with plant extracts (25, 50 and 100 mg/kg/day, p.o.) or L-tryptophane (100 mg/kg/day, i.p.). Pain-like (tactile and cold allodynia) and depression-like (pole, tail suspension, and force swimming tests) behavioral parameters were evaluated on Days 4 and 8. On Day 9, animals were sacrificed for the quantification of acetylcholinesterase activity, oxidative stress parameters, total catecholamines, dopamine, serotonin, IL-1β, and TNF-α levels in the brain or spinal cord. IL-1β and TNF-α were also assayed in the serum. The acute toxicity and phytochemical analysis of EE were conducted. Results: Reserpine-induced tactile and cold allodynia, depression-like behavior, increased serum IL-1β and TNF-α, brain acetylcholinesterase activity, and decreased catecholamine concentration were all reversed by AE and EE. Plant extracts significantly increased dopamine levels and reduced oxidative stress in the brain and/or spinal cord. No significant effect was observed on brain serotonin and TNF-α. EE elicited the best pharmacological activity and was nontoxic. LC-MS/MS molecular networking phytochemical analysis identified 5 compounds with high certainty including piperine, aurantiamide acetate, and asperphenamate. Conclusion: AE and EE are effective against pain and depression. Their pharmacological activities might be related to the modulation of inflammation, oxidative stress and catecholamine, and the presence of bioactive natural products.

Ion Mobility-Coupled Mass Spectrometry for Metallophore Detection

Metal chelating small molecules (metallophores) play significant roles in microbial interactions and bacterial survival; however, current methods to identify metallophores are limited by low sensitivity, a lack of metal selectivity, and/or complicated data analysis. To overcome these limitations, we developed a novel approach for detecting metallophores in natural product extracts using ion mobility-coupled mass spectrometry (IM-MS). As a proof of concept, marine bacterial extracts containing known metallophores were analyzed by IM-MS with and without added metals, and the data were compared between conditions to identify metal-binding metabolites. Ions with changes in both mass and mobility were specific to metallophores, enabling their identification within these complex extracts. Additionally, we compared the use of direct infusion (DI) and liquid chromatography (LC) separation with IM-MS. For most samples, DI outperformed LC by minimizing the time required for data collection and simplifying analysis. However, for some samples, LC improved the detection of metallophores likely by reducing ion suppression. IM-MS was then used to identify 10 metallophores in an extract from a marine Micromonospora sp. Overall, incorporating IM-MS facilitated the rapid detection of metal-binding natural products in complex bacterial extracts through the comparison of mass and mobility data in the presence and absence of metals.

Identification of Bioactive Metabolites of Capirona macrophylla by Metabolomic Analysis, Molecular Docking, and In Vitro Antiparasitic Assays

Capirona macrophylla is a Rubiaceae known as "mulateiro". Ethnobotanical extracts have been used for skin treatment and in the management of leishmaniasis and malaria.

OBJECTIVES

The metabolites in aqueous extracts from wood bark, leaves, and stems were identified, and their in silico docking and in vitro cellular efficacy against Leishmania amazonensis and Plasmodium falciparum were evaluated.

METHODS

The extracts were analyzed by UHPLC/HRMSn using untargeted metabolomics approach with MSDial, MSFinder, and GNPS software for metabolite identification and spectra clustering. The most abundant metabolites underwent molecular docking using AutoDock via PyRx, targeting the dihydroorotate dehydrogenase from Leishmania and P. falciparum, and evaluated through molecular dynamics simulations using Gromacs. In vitro biological assays were conducted on 60 HPLC-fractions against these parasites.

RESULTS

Metabolomics analysis identified 5100 metabolites in ESI+ and 2839 in ESI- spectra among the "mulateiro" samples. GNPS clustering highlighted large clusters of quercetin and chlorogenic acid groups. The most abundant metabolites were isofraxidin, scopoletin, 5(S)-5-carboxystrictosidine, loliolide, quercetin, quinic acid, caffeoylquinic acid (and isomers), chlorogenic acid, neochlorogenic acid, tryptophan, N-acetyltryptophan, epicatechin, procyanidin, and kaempferol-3-O-robinoside-7-O-rhamnoside. Molecular docking pointed to 3,4-dicaffeoylquinic acid and kaempferol as promising inhibitors. The in vitro assays yielded four active HPLC-fractions against L. amazonensis with IC50 values ranging from 175.2 μg/mL to 194.8 μg/mL, and fraction G29 showed an IC50 of 119.8 μg/mL against P. falciparum.

CONCLUSIONS

The ethnobotanical use of "mulateiro" wood bark tea as an antimalarial and antileishmanial agent was confirmed through in vitro assays. We speculate that these activities are attributed to linoleic acids and quinic acids.

Secondary Metabolite Biosynthesis Potential of Streptomyces Spp. from the Rhizosphere of Leontopodium nivale Subsp. alpinum

Bacteria of the phylum Actinomycetota, particularly those of the genus Streptomyces, are prolific producers of secondary metabolites (SMs), many of which have been developed into antibiotics, immunosuppressants, and cancer therapeutics. With high rediscovery rates, the attention has shifted to Streptomyces from unique ecological niches for the discovery of new SMs. The plant rhizosphere is one such niche, characterized by complex chemical interactions between the plant and its rhizobiome, which can elicit the production of SMs in Streptomyces. In the present study, 18 Streptomyces strains were previously isolated from the rhizosphere of the rare alpine medicinal plant Leontopodium nivale subsp. alpinum were investigated for their capacity to produce secondary metabolites. Genomes of these strains were analyzed for the presence of SM biosynthetic gene clusters (BGCs). In total, 551 BGCs were detected, of which 217 could not be linked to known SMs. These isolates were cultivated in different media known to support the production of SMs, and 15 out of the 54 methanolic extracts from these cultures exhibited antimicrobial activities. Subsequent liquid chromatography-mass spectrometry analyses of the bioactive extracts led to a putative identification of 69 known SMs as well as 16 potentially new molecules. The results of this study may provide a basis for the discovery of unique molecules with the potential to be developed as drugs against a variety of human diseases.

Severe acute respiratory syndrome coronavirus 2 infection unevenly impacts metabolism in the coronal periphery of the lungs

SARS-CoV-2, the virus responsible for COVID-19, is a highly contagious virus that can lead to hospitalization and death. COVID-19 is characterized by its involvement in the lungs, particularly the lower lobes. To improve patient outcomes and treatment options, a better understanding of how SARS-CoV-2 impacts the body, particularly the lower respiratory system, is required. In this study, we sought to understand the spatial impact of COVID-19 on the lungs of mice infected with mouse-adapted SARS2-N501YMA30. Overall, infection caused a decrease in fatty acids, amino acids, and most eicosanoids. When analyzed by segment, viral loads were highest in central lung tissue, while metabolic disturbance was highest in peripheral tissue. Infected peripheral lung tissue was characterized by lower levels of fatty acids and amino acids when compared to central lung tissue. This study highlights the spatial impacts of SARS-CoV-2 and helps explain why peripheral lung tissue is most damaged by COVID-19.

Phosphorylated glycosphingolipids are commonly detected in Caenorhabditis elegans lipidomes

INTRODUCTION

The identification of lipids is a cornerstone of lipidomics, and due to the specific characteristics of lipids, it requires dedicated analysis workflows. Identifying novel lipids and lipid species for which no reference spectra are available is tedious and often involves a lot of manual work. Integrating high-resolution mass spectrometry with enhancements from chromatographic and ion mobility separation enables the in-depth investigation of intact lipids.

OBJECTIVES

We investigated phosphorylated glycosphingolipids from the nematode Caenorhabditis elegans, a biomedical model organism, and aimed to identify different species from this class of lipids, which have been described in one particular publication only. We checked if these lipids can be detected in lipid extracts of C. elegans.

METHODS

We used UHPLC-UHR-TOF-MS and UHPLC-TIMS-TOF-MS in combination with dedicated data analysis to check for the presence of phosphorylated glycosphingolipids. Specifically, candidate features were identified in two datasets using Mass Spec Query Language (MassQL) to search fragmentation data. The additional use of retention time (RT) and collisional cross section (CCS) information allowed to filter false positive annotations.

RESULTS

As a result, we detected all previously described phosphorylated glycosphingolipids and novel species as well as their biosynthetic precursors in two different lipidomics datasets. MassQL significantly speeds up the process by saving time that would otherwise be spent on manual data investigations. In total over 20 sphingolipids could be described.

CONCLUSION

MassQL allowed us to search for phosphorylated glycosphingolipids and their potential biosynthetic precursors systematically. Using orthogonal information such as RT and CCS helped filter false positive results. With the detection in two different datasets, we demonstrate that these sphingolipids are a general part of the C. elegans lipidome.

Multi-omics analysis of the correlation between surface microbiome and metabolome in Saccharina latissima (Laminariales, Phaeophyceae)

The microbiome of Saccharina latissima, an important brown macroalgal species in Europe, significantly influences its health, fitness, and pathogen resistance. Yet, comprehensive studies on the diversity and function of microbial communities (bacteria, eukaryotes, and fungi) associated with this species are lacking. Using metabarcoding, we investigated the epimicrobiota of S. latissima and correlated microbial diversity with metabolomic patterns (liquid chromatography coupled to tandem mass spectrometry). Specific epibacterial and eukaryotic communities inhabit the S. latissima surface, alongside a core microbiota, while fungal communities show lower and more heterogeneous diversity. Metabolomic analysis revealed a large diversity of mass features, including putatively annotated fatty acids, amino derivatives, amino acids, and naphthofurans. Multiple-factor analysis linked microbial diversity with surface metabolome variations, driven mainly by fungi and bacteria. Two taxa groups were identified: one associated with bacterial consortia and the other with fungal consortia, each correlated with specific metabolites. This study demonstrated a core bacterial and eukaryotic microbiota associated with a core metabolome and highlighted interindividual variations. Annotating the surface metabolome using Natural Products databases suggested numerous metabolites potentially involved in interspecies chemical interactions. Our findings establish a link between microbial community structure and function, identifying two microbial consortia potentially involved in the chemical defense of S. latissima.

Harnessing Functional Food Sources: Deriving Anti-Inflammatory and Antibacterial Naphthalene Derivatives from the Edible Bulbs of Eleutherine bulbosa

The red bulbs of Eleutherine bulbosa, commonly used as a daily dietary ingredient in cooking, are well-known for their rich nutritional profile and potential medicinal properties. This study focused on identifying bioactive components from E. bulbosa by a bioactivity-guided approach combined with global natural products' social molecular networking, which led to the characterization of 12 new naphthalene derivatives, eleuthalenes A-L (1-12), and 22 known analogues. The structures of these compounds were determined through spectroscopic data, X-ray crystallography, and quantum chemical calculations. The anti-inflammatory and antibacterial activities of these compounds were evaluated, with some demonstrating significant anti-inflammatory and moderate antibacterial activities. Further studies revealed that the most potent compound 5 displayed an anti-inflammatory effect in LPS-induced RAW 264.7 cells by suppressing the NF-κB/MAPK and activating Nrf2/Keap1 signaling pathways. The results suggested that bioactive naphthalene derivatives are the major pharmacodynamic substances of E. bulbosa.

Molecular Structure Discovery for Untargeted Metabolomics Using Biotransformation Rules and Global Molecular Networking

Although untargeted mass spectrometry-based metabolomics is crucial for understanding life's molecular underpinnings, its effectiveness is hampered by low annotation rates of the generated tandem mass spectra. To address this issue, we introduce a novel data-driven approach, Biotransformation-based Annotation Method (BAM), that leverages molecular structural similarities inherent in biochemical reactions. BAM operates by applying biotransformation rules to known "anchor" molecules, which exhibit high spectral similarity to unknown spectra, thereby hypothesizing and ranking potential structures for the corresponding "suspect" molecule. BAM's effectiveness is demonstrated by its success in annotating query spectra in a global molecular network comprising hundreds of millions of spectra. BAM was able to assign correct molecular structures to 24.2% of examined anchor-suspect cases, thereby demonstrating remarkable advancement in metabolite annotation.

Multi-omic signatures of host response associated with presence, type, and outcome of enterococcal bacteremia

Despite the prevalence and severity of enterococcal bacteremia (EcB), the mechanisms underlying systemic host responses to the disease remain unclear. Here, we present an extensive study that profiles molecular differences in plasma from EcB patients using an unbiased multi-omics approach. We performed shotgun proteomics and metabolomics on 105 plasma samples, including those from EcB patients and healthy volunteers. Comparison between healthy volunteer and EcB-infected patient samples revealed significant disparities in proteins and metabolites involved in the acute phase response, inflammatory processes, and cholestasis. Several features distinguish these two groups with remarkable accuracy. Cross-referencing EcB signatures with those of Staphylococcus aureus bacteremia revealed shared reductions in cholesterol metabolism proteins and differing responses in platelet alpha granule and neutrophil-associated proteins. Characterization of Enterococcus isolates derived from patients facilitated a nuanced comparison between EcB caused by Enterococcus faecalis and Enterococcus faecium, uncovering reduced immunoglobulin abundances in E. faecium cases and features capable of distinguishing the underlying microbe. Leveraging extensive patient metadata, we now have identified features associated with mortality or survival, revealing significant multi-omic differences and pinpointing histidine-rich glycoprotein and fetuin-B as features capable of distinguishing survival status with excellent accuracy. Altogether, this study aims to culminate in the creation of objective risk stratification algorithms-a pivotal step toward enhancing patient management and care. To facilitate the exploration of this rich data source, we provide a user-friendly interface at https://gonzalezlab.shinyapps.io/EcB_multiomics/.

IMPORTANCE

Enterococcus infections have emerged as the second most common nosocomial infection, with enterococcal bacteremia (EcB) contributing to thousands of patient deaths annually. To address a lack of detailed understanding regarding the specific systemic response to EcB, we conducted a comprehensive multi-omic evaluation of the systemic host response observed in patient plasma. Our findings reveal significant features in the metabolome and proteome associated with the presence of infection, species differences, and survival outcome. We identified features capable of discriminating EcB infection from healthy states and survival from mortality with excellent accuracy, suggesting potential practical clinical utility. However, our study also established that systemic features to distinguish Enterococcus faecalis from Enterococcus faecium EcB show only a moderate degree of discriminatory accuracy, unlikely to significantly improve upon current diagnostic methods. Comparisons of differences in the plasma proteome relative to healthy samples between bacteremia caused by Enterococcus and Staphylococcus aureus suggest the presence of bacteria-specific responses alongside conserved inflammatory reactions.

Comparative metabolomics reveals streptophenazines with anti-methicillin-resistant Staphylococcus aureus activity derived from Streptomyces albovinaceus strain WA10-1-8 isolated from Periplaneta americana

BACKGROUND

Streptophenazines, a class of phenazine compounds with a variety of alkyl side chains and activity against methicillin-resistant Staphylococcus aureus (MRSA), are mainly derived from soil or marine microbial secondary metabolites. However, the discovered phenazine compounds still do not meet the needs of the development of anti-MRSA lead compounds. Here, we examined secondary metabolites of Streptomyces albovinaceus WA10-1-8 isolated from Periplaneta americana, for streptophenazines with anti-MRSA activity.

RESULTS

In this study, a guidance method combining high-performance liquid chromatography-ultraviolet (HPLC-UV) with molecular networking analysis was used to isolate and identify a series of streptophenazines (A-T) from S. albovinaceus WA10-1-8. Among them, a new streptophenazine containing a dihydroxyalkyl chain structure named streptophenazine T was isolated and identified for the first time. The results of bioactivity assays showed that streptophenazine T had anti-MRSA activity with a minimum inhibitory concentration (MIC) of 150.23 µM, while the MICs of streptophenazine A, B, G, and F were 37.74-146.12 µM.

CONCLUSIONS

This study was the first to report multiple streptophenazine compounds with anti-MRSA activity expressed by Streptomyces isolated from insect niches. These results provided a valuable reference for future exploration of new streptophenazine compounds with activity against drug-resistant bacteria.

What Happens Inside the Germinating Grain After Microbial Decontamination by Pulsed Electric Field? Data-Driven Multi-Omics Helps Find the Answer

Pulsed electric field (PEF) has previously been recognized as a method of gentle food processing, and its use has been shown to be helpful in reducing the levels of toxigenic Fusarium micromycetes developed during malting. The aim of this study was to describe the effects of PEF on gene expression and metabolite production at the pre-finishing stage of barley malting by using a novel multi-omics data-driven approach. The study helps to uncover the processes occurring in the germinated grain and discusses the up-/downregulation of genes and metabolites in relation to fungal infection and/or PEF-induced abiotic stress. Among the factors upregulated by PEF and previously described as supportive against Fusarium diseases, we identified the increased expression of genes encoding vegetative gp1-like protein, which positively correlated with flavonoids, (methylsulfanyl)prop-2-enoates, triterpenoid glycosides, and indole alkaloids. On the other hand, some genes associated with barley resistance to fungal infection were also overexpressed in the untreated control (in particular, genes encoding ethylene response factor 3-like, putrescine hydroxycinnamoyltransferase 3-like, and dirigent protein 21-like). This study provides the first 'data-driven' basic research results that contribute to the understanding of the role of PEF as an effective fungal decontamination strategy and allows the formulation of new hypotheses related to Fusarium pathogen crosstalk.

ClusterApp to visualize, organize, and navigate metabolomics data

Background

Clustering analysis is a foundational step in exploratory data analysis workflows, with dimensionality reduction methods commonly used to visualize multidimensional data in lower-dimensional spaces and infer sample clustering. Principal Component Analysis (PCA) is widely applied in metabolomics but is often suboptimal for clustering visualization. Metabolomics data often require specialized manipulations such as blank removal, quality control adjustments, and data transformations that demand efficient visualization tools. However, the lack of user-friendly tools for clustering without computational expertise presents a challenge for metabolomics researchers. ClusterApp addresses this gap as a web application that performs Principal Coordinate Analysis (PCoA), expanding clustering alternatives in metabolomics. Built on a QIIME 2 Docker image, it enables PCoA computation and Emperor plot visualization. The app supports data input from GNPS, GNPS2, or user-provided spreadsheets. Freely available, ClusterApp can be locally installed as a Docker image or integrated into Jupyter notebooks, offering accessibility and flexibility to diverse users.

Results

To demonstrate the data preprocessing techniques available in ClusterApp, we analyzed two Liquid Chromatography coupled to Tandem Mass Spectrometry (LC-MS/MS) metabolomics datasets: one exploring metabolomic differences in mouse tissue samples and another investigating coral life history stages. Among the dissimilarity measures available, the Bray-Curtis measure effectively highlighted key metabolomic variations and patterns across both datasets. Targeted filtering significantly enhanced data reliability by retaining biologically relevant features, 10,617 in the coral dataset and 7,341 in the mouse dataset while eliminating noise. The combination of Total Ion Current (TIC) normalization and auto-scaling improved clustering resolution, revealing distinct separations in tissue types and life stages. ClusterApp's flexible features, such as customizable blank removal and group selection, provided tailored analyses, enhancing visualization and interpretation of metabolomic profiles.

Conclusion

ClusterApp addresses the need for accessible, dynamic tools for exploratory data analysis in metabolomics. By coupling data transformation capabilities with PCoA on multiple dissimilarity matrices, it provides a versatile solution for clustering analysis. Its web interface and Docker-based deployment offer flexibility, accommodating a wide range of use cases through graphical or programmatic interactions. ClusterApp empowers researchers to uncover meaningful patterns and relationships in metabolomics data without requiring cumbersome data manipulation or advanced bioinformatics expertise.

Bulbillosins A - E, azaphilones from Tengochaetabulbillosa sp. nov. (Chaetomiaceae), a root endophyte of the Chinese medicinal plant Astertataricus

Astertataricus is a plant used in Traditional Chinese Medicine. From its roots, we isolated four endophytic fungi strains. After mass spectrometry analysis and subsequent molecular networking and dereplication, one of the strain's extracts showed a cluster of yet undescribed natural products. Additionally, the extract was found to be lethal for the nematode Caenorhabditiselegans and cytotoxic against eukaryotic cell lines. The fungal strain was characterized by morphological and molecular studies, allowing its description as a new species in the genus Tengochaeta (Chaetomiaceae), Tengochaetabulbillosa. After cultivation and extraction of the strain, the major secondary metabolites were isolated. Structure elucidation based on nuclear magnetic resonance spectroscopy and high-resolution tandem mass spectrometry revealed these compounds to be five new azaphilones. Additionally, the localization of these azaphilones in the host plant was studied by mass spectrometry imaging of different plant tissues, revealing that they were mainly localized in the aerial parts of the plant. The main compound, bulbillosin A, was evaluated for its activity against sixty cancer cell lines, revealing a differential cytotoxicity profile.

An expanded database of high-resolution MS/MS spectra for lichen-derived natural products

The history of lichen compound identification has long relied on techniques such as spot tests and TLC, which have been surpassed in sensitivity and accuracy by modern metabolomic techniques such as high-resolution MS/MS. In 2019, Olivier-Jimenez et al. released the Lichen DataBase (LDB), a library containing the Q-TOF MS/MS spectra of 251 metabolites on the MetaboLights and GNPS platforms, that has been widely used for the identification of lichen-derived unknowns. To increase the compound coverage, we have generated the Orbitrap MS/MS spectra of a further 534 lichen-derived compounds from the metabolite library of Jack Elix, housed at the CANB herbarium (Canberra, Australia). This included 399 unique metabolites that are not in the LDB, bringing the total number combined to 650. Technical validation was achieved by investigating the compounds in three Australian lichen extracts using the Library Search and Molecular Networking tools on the GNPS platform. This update provides a much larger database for lichen compound identification, which we envisage will allow refining the lichen chemotaxonomy framework and contribute to compound discovery.

mpactR: an R adaptation of the metabolomics peak analysis computational tool (MPACT) for use in reproducible data analysis pipelines

mpactR automates pre-processing of liquid chromatography-tandem mass spectrometry (LC-MS/MS) data from microbiological samples to correct mispicked peaks, resolve inter-sample variation in abundance across technical replicates, account for in-source ion fragmentation, and remove background noise to yield high-quality mass spectrometry features. The package is available through CRAN and GitHub.

Approaches for GC-HRMS Screening of Organic Microcontaminants: GC-APCI-IMS-QTOF versus GC-EI-QOrbitrap

This study explores the capabilities of GC-APCI-IMS-QTOF MS and GC-EI-QOrbitrap MS in screening applications and different strategies for wide-scope screening of organic microcontaminants using target suspect and nontarget approaches. On one side, GC-APCI-IMS-QTOF MS excels at preserving molecular information and adds ion mobility separation, facilitating screening through the list of componentized features containing accurate mass, retention time, CCS, and fragmentation data. On the other side, the extensive and robust fragmentation of GC-EI-QOrbitrap MS allows the application of different strategies for target and nontarget approaches using the NIST library spectra. Our findings revealed that GC-EI-QOrbitrap MS is more sensitive in target approaches. Automated workflows for suspect screening in GC-APCI-IMS-QTOF MS minimize false annotations but face challenges with false negatives due to in-source fragmentation and limitations when using in silico fragmentation tools. Conversely, a nontarget approach in GC-EI-QOrbitrap MS can reliably identify unknowns but results in more false annotations in complex matrices. This work highlights the strengths and limitations of each system and guides for their optimal application for wide-scope screening in environmental and food safety applications.

Discovery of Peptidic Siderophore Degradation by Screening Natural Product Profiles in Marine-Derived Bacterial Mono- and Cocultures

Coral reefs are hotspots of marine biodiversity, which results in the synthesis of a wide variety of compounds with unique molecular scaffolds, and bioactivities, rendering reefs an ecosystem of interest. The chemodiversity stems from the intricate relationships between inhabitants of the reef, as the chemistry produced partakes in intra- and interspecies communication, settlement, nutrient acquisition, and defense. However, the coral reefs are declining at an unprecedented rate due to climate change, pollution, and increased incidence of pathogenic diseases. Among pathogens, Vibrio spp. bacteria are key players resulting in high mortality. Thus, alternative strategies such as application of beneficial bacteria isolated from disease-resilient species are being explored to lower the burden of pathogenic species. Here, we apply coculturing of a coral-derived pathogenic species of Vibrio and beneficial bacteria and leverage recent advancements in untargeted metabolomics to discover engineerable beneficial traits. By chasing chemical change in coculture, we report Microbulbifer spp.-mediated degradation of amphibactins, produced by Vibrio spp. bacteria to sequester iron. Additional biochemical experiments revealed that the degradation occurs in the peptide backbone and requires the enzyme fraction of Microbulbifer. A reduction in iron affinity is expected due to the loss of one Fe(III) binding moiety. Therefore, we hypothesize that this degradation shapes community behaviors as it pertains to iron acquisition, a limiting nutrient in the marine environment, and survival. Furthermore, Vibrio sp. bacteria suppressed natural product synthesis by beneficial bacteria. Understanding biochemical mechanisms behind these interactions will enable engineering probiotic bacteria capable of lowering pathogenic burdens during heat waves and incidence of disease.

Revisiting the potential of natural products in antimycobacterial therapy: advances in drug discovery and semisynthetic solutions

Natural products have been pivotal in treating mycobacterial infections with early antibiotics such as streptomycin, forming the foundation of tuberculosis therapy. However, the emergence of multidrug-resistant and extensively drug-resistant Mycobacterium species has intensified the need for novel antimycobacterial agents. In this review, we revisit the historical contributions of natural products to antimycobacterial drug discovery and highlight recent advances in the field. We assess the application of molecular networking and the exploration of unculturable bacteria in identifying new antimycobacterial compounds such as amycobactin and levesquamides. We also highlight the role of semisynthesis in optimizing natural products, exemplified by sequanamycins and spectinomycin analogs that evade M. tuberculosis' intrinsic resistance. Finally, we discuss emerging technologies that are promising to accelerate the discovery and development of next-generation antimycobacterial therapies. Despite ongoing challenges, these innovative approaches offer renewed hope in addressing the growing crisis of drug-resistant mycobacterial infections.

Microbial and chemical diversity analysis reveals greater heterogeneity of Liubao tea than ripen Pu-erh tea

Liubao tea and ripen Pu-erh tea are representatives of dark tea in southern China. The two dark teas are famous for unique flavors, but confusingly different in development status of tea industry. In this study, microbial DNA amplification sequencing and mass spectrometry-based untargeted metabolomics were applied to observe significant differences in microbial community structure and metabolite profile between the two teas. The Shannon indices of fungi and metabolites in Liubao tea are higher than those in ripen Pu-erh tea. The dominant bacterial and fungal genera, as well as microbial biomarkers of Liubao tea and ripen Pu-erh tea were identified. The combined statistical and molecular networking analysis shows flavan-3-ols as the discriminating features between metabolite profiles of the two dark teas in level of metabolite family. More importantly, the α and β diversity analysis reveals higher pairwise Shannon index differences and Canberra distances of both microbes and metabolites in Liubao tea than those in ripen Pu-erh tea, indicating greater heterogeneity, or lower quality stability of Liubao tea products. These findings illustrate way to improve protocols of Liubao tea processing, and show urgency of involving molecular networking in workflow of metabolomics research.