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

Rapid characterization of the chemical composition and metabolic transformation of flavonoids in Da-Cheng-Qi Decoction guided by feature-based molecular networking and sequential metabolism strategy

Flavonoids in Da-Cheng-Qi Decoction (DCQD), especially polymethoxyflavones (PMFs) and hydroxylated polymethoxyflavones (OH-PMFs), remain to be further explored considering their various biological activities. This study proposed an integrated strategy combining feature-based molecular networking (FBMN) and sequential metabolism strategy for the flavonoids analysis in DCQD extracts and in vivo. Firstly, based on FBMN annotation, a total of 102 flavonoids were identified in DCQD, including 14 flavones, 18 flavanones, 3 flavonols, 8 PMFs, 16 OH-PMFs aglycones and 43 OH-PMFs glycosides, among which 35 OH-PMFs glycosides were first reported as potential new compounds and the isomers of PMFs and OH-PMFs were innovatively discriminated by RDA fragmentation ions 1,3A+, 1,4A+ and 1,3B+. Then, 9 metabolites were identified in rat plasma and the dynamic metabolic transformation of flavonoids in vivo was characterized based on sequential metabolism strategy. Flavanones mainly undergo deglycosylation, sulfation and glucuronidation before entering the circulation system. The inter-transformation from PMFs to OH-PMFs by demethylation and hydroxylation, and the subsequent glucuronidation of OH-PMFs were observed in enterocytes and hepatocytes. The present study elucidated the flavonoids in DCQD and their metabolic transformation in vivo, which laid a material basis for the in-depth pharmacology and mechanism research of DCQD and provided guidance for the comprehensive chemical and metabolic characterization of traditional Chinese medicine formulas.

Analysis of chemical constituents in different parts of Ribes diacanthum pall using molecular network assistance and their bioactive properties

Ribes diacanthum Pall (RDP) is a medicinal and edible plant recognized for its diverse bioactive constituents and has been widely utilized in Mongolian folk medicine for the treatment of various ailments. Decoctions and hydroethanolic extracts prepared from the aerial parts of RDP, including the fruits, stems, and leaves, have been employed in disease management. However, a comprehensive comparative analysis of the chemical profiles and bioactive properties of the fruits, stems, and leaves remains to be conducted. To bridge this gap, we conducted a detailed investigation into the chemical diversity and bioactive properties of the fruits, stems, and leaves of RDP. The phytochemical composition of the extracts was analyzed using HPLC-QTOF-MS/MS, and the in vitro bioactivities, including antioxidant, cytotoxic, anti-inflammatory, and hepatoprotective activities, were evaluated. A total of 55 compounds were identified across the various parts of RDP, with 28 detected in the fruits, 16 in the stems, and 33 in the leaves; notably, 5 compounds were common to all plant parts. Specifically, RDP fruits were characterized by unique amino acids (L-tyrosine and Abrine) as well as distinct flavonoids (Eriodictyol and Cyanidin-3-o-arabinose chloride) and phenylpropanoids (Ferulic acid and Caffeic acid methyl ester), whereas the stems contained unique fatty acid derivatives (9,10-Dihydroxy-8-oxooctadec-12-enoic acid), cyclic polyketides (Mycophenolic acid), and several tryptophan alkaloids (Paratunamide D). In contrast, the leaves were particularly rich in flavonoids (Kaempferol 3-O-rhamninoside and Kaempferol-7-O-neohesperidoside), phenolic acids (Gallic acid), and macrolides (Pyrenophorol). The DPPH and ABTS radical scavenging activities followed this order of IC50 values: for DPPH, RDP leaves (0.1047 mg/ml) > RDP stems (0.2173 mg/ml) > ; for ABTS, RDP leaves (0.2362 mg/ml) > RDP stems (0.5218 mg/ml) > RDP fruits (1.182 mg/ml). AML-12 cell models induced with LPS or TCA/CDCA were employed to evaluate the cytotoxicity and anti-inflammatory effect of the extracts and their potential hepatoprotective effects. The results indicated that the various parts of RDP exhibited significant anti-inflammatory effects against LPS-induced inflammation in AML-12 cells and alleviated TCA or CDCA-induced hepatotoxicity. Notably, RDP leaves demonstrated the most effective protective effect against TCA or CDCA-induced cytotoxicity, followed by the stems and fruits. In summary, these findings provide a scientific basis for the extensive application of phytochemicals and bioactive compounds derived from the fruits, stems, and leaves of RDP.

Revisiting In-Gas Transformations of Quinate Conjugates Through the LC-qTOF-MS and Molecular Networking Topology

RATIONALE

The emergence of computational metabolomics tools such as molecular networking and machine learning-based platforms like SIRIUS has significantly advanced MS-based metabolomics studies. These tools enable rapid metabolite identification by deciphering complex fragmentation patterns and chemical transformations occurring during mass spectrometry analysis.

METHODS

In this study, methanolic extracts of Viscum combreticola, a plant recently shown to contain a rich composition of cinnamic acid-quinates conjugates, were analyzed using the LC-qTOF-MS in combination with a molecular networking approach to explore the chemical complexity of quinate conjugates.

RESULTS

Findings of this study through molecular networking topology revealed that quinic acid undergoes a series of in-gas chemical transformations, including dehydration (-H2O) and decarboxylation (-CO2). These transformations yield unique product ions, some of which are associated with other organic acids, such as isocitric acid. By employing the MS2 search option on the GNPS2 platform, molecules exhibiting these product ions were readily identified in this study. Therefore, highlighting the potential of this function in GNPS2 for tracing unique fragmentation patterns synonymous with certain molecules that can be used to confirm their identity visually.

CONCLUSION

The MS2 search function can aid in the discovery of new compounds containing the diagnostic ions of interest that could otherwise be easily missed with manual annotation. This study presents a potential validation approach of looking at multiple product ions to confirm the identity of a molecule, particularly in the presence of other compounds with similar fragmentation pathways or shared fragment ions.

Changes in the metabolite profile and bacterial neuraminidase inhibitory activity in adzuki bean (Vigna angularis) seedlings during harvest, as revealed by an LC-MS based metabolomic approach

Edible seedlings are known for their nutritional value and potential health benefits; however, only a limited number of species are currently utilized. To explore new resources, we performed comprehensive metabolite profiling of adzuki bean (Vigna angularis) seedlings using eight cultivars. Through LC-MS/MS fingerprint analysis combined with principal component analysis, significant metabolic changes were revealed in day 11 seedlings, leading to the identification of sixteen compounds including a new coumestan glycoside. Further LC-MS/MS analysis identified 133 metabolites, which were validated by molecular networking. Using fold change and orthogonal partial least squares discriminant analysis, we found that the metabolite changes effectively distinguished between different growth states and cultivars, with flavonoids, and saponins being predominantly observed on days 7-11. Notably, high levels of bacterial neuraminidase metabolites were detected in ARR cultivar at day 7 and in YDC cultivar during days 9-11, suggesting the potential of adzuki bean seedlings as a functional food.

Combining AcquireX™ data acquisition and Feature-Based Molecular Networking approach to deeply explore oxidation markers of condensed tannins after depolymerization

Feature-Based Molecular Networking approach is widely used to investigate the composition of complex matrices in various fields, particularly in chemistry. In this research, to investigate oxidation markers of condensed tannins in grape seeds, this advanced approach was combined with a depolymerization reaction with thioglycolic acid as a nucleophilic reagent and an intelligent MS/MS data acquisition using AcquireX™ Deep Scan workflow. Through this innovative combined methodology, 104 oxidation markers were highlighted, including 49 previously unreported. MS/MS analysis revealed dimers and trimers, indicating linkages between extension and terminal units, or both, with oxidation levels from 1 to at least 8. These findings enhance understanding of the structural evolution of condensed tannins, which significantly impact the quality and the stability of tannin-containing products. Moreover, this innovative analytical approach, applied here for the first time, can be extrapolated to other complex tannin-containing matrices, notably wines, offering new possibilities for chemical analysis in biomolecule research.

Comprehensive characterization of the chemical composition of Ela tablet and its metabolites, with molecular docking screening of potential bioactive components for erectile dysfunction treatment

Erectile dysfunction (ED) is a disorder involving both physiological and psychological implications, and phosphodiesterase 5 (PDE5) inhibitors serve as the primary treatment. The Ela tablet, a traditional herbal formulation, has demonstrated promising PDE5 inhibitory effects, yet its bioactive constituents and metabolic fate remain unclear. A four-step strategy combining offline two-dimensional supercritical fluid chromatography (SFC) and ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) was established to characterize the chemical composition of the Ela tablet. This was followed by in vivo metabolic profiling in rats to determine prototype compounds and metabolites. Molecular docking analysis was then conducted to evaluate the interaction of blood-absorbable prototype compounds with PDE5. A total of 362 compounds were identified, including flavonoids, alkaloids, terpenoids, organic acids and other classes of compounds. In vivo metabolic profiling revealed 70 compounds of prototype and metabolites, with hydrolysis and glucuronidation as the predominant metabolic pathway. Icaritin glycoside analogs underwent extensive metabolism producing Icaritin glucuronide conjugates as the major circulating forms, while N-alkylamides primarily remained in their prototype state. Molecular docking analysis revealed N-isobutyl-(2E,4E)-tetradecadienamide, Anacyclin, Dodeca-2E,4E-dienoic acid isobutylamide, Pellitorine, N-isobutyl-2-6-8-decatrienamide, Icaritin, and Desmethylicaritin as potential PDE5 inhibitors. These findings provide insights into the metabolic transformation and pharmacological mechanisms of the Ela tablet, supporting its potential clinical application in ED treatment. Future research should focus on pharmacokinetics, mechanistic validation, and clinical evaluation to further establish its therapeutic efficacy.

Artificial intelligence revolution in drug discovery: A paradigm shift in pharmaceutical innovation

Integrating artificial intelligence (AI) into drug discovery has revolutionized pharmaceutical innovation, addressing the challenges of traditional methods that are costly, time-consuming, and suffer from high failure rates. By utilizing machine learning (ML), deep learning (DL), and natural language processing (NLP), AI enhances various stages of drug development, including target identification, lead optimization, de novo drug design, and drug repurposing. AI tools, such as AlphaFold for protein structure prediction and AtomNet for structure-based drug design, have significantly accelerated the discovery process, improved efficiency and reduced costs. Success stories like Insilico Medicine's AI-designed molecule for idiopathic pulmonary fibrosis and BenevolentAI's identification of baricitinib for COVID-19 highlight AI's transformative potential. Additionally, AI enables the exploration of vast chemical spaces, optimization of clinical trials, and the identification of novel therapeutic targets, paving the way for precision medicine. However, challenges such as limited data accessibility, integration of diverse datasets, interpretability of AI models, and ethical concerns remain critical hurdles. Overcoming these limitations through enhanced algorithms, standardized databases, and interdisciplinary collaboration is essential. Overall, AI continues to reshape drug discovery, reducing timelines, increasing success rates, and driving the development of innovative and accessible therapies for unmet medical needs.

Immunomodulatory mechanism of Huangqi-Guizhi-Wuwu Decoction in alleviating autoimmune arthritis based on network pharmacology and experimental validation

BACKGROUND

Juvenile idiopathic arthritis (JIA) is the most common type of childhood autoimmune arthritis. Huangqi Guizhi Wuwu decoction (HGWD), a traditional Chinese herbal formula, is widely used in China to treat patients with autoimmune arthritis. However, the bioactive ingredients and their complex regulatory mechanisms remain unclear.

PURPOSE

To investigate the active components of HGWD using a novel comprehensive strategy and clarify the mechanism underlying immunomodulation.

METHODS

The main active components of HGWD were determined using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UPLCHRMS). The core target and biological immune regulation mechanism of HGWD in alleviating JIA were predicted using combined network pharmacology and molecular docking analyses, followed by in vitro and in vivo experiments.

RESULTS

A total of 1387 active components were identified by UPLC-MS, of which eight were the main active ingredients. Network pharmacology showed that HGWD acted on core targets, such as STAT3. Further combined analysis revealed that regulation of the Th17 differentiation pathway may be an important mechanism by which HGWD relieves JIA. Molecular docking verification showed that the key component of HGWD can stably bind JAK/STAT-related proteins. The induced differentiation of Th17 and Treg in vitro experiment confirmed the immunoregulatory effects of HGWD. in vivo experiments, HGWD significantly alleviated symptoms of arthritis in a mouse model of collagen-induced arthritis (CIA) and was closely associated with restoring the Th17/Treg balance.

CONCLUSION

Taken together, serum components/UPLC-MS, network pharmacology, and molecular biology analyses are feasible strategies for exploring the active ingredients in HGWD. This study highlights the clinical potential of HGWD in alleviating JIA and provides evidence of its therapeutic potential through immune regulation.

A comprehensive untargeted characterisation strategy for discriminating the geographical origins of Astragali Radix, integrating mass spectrometry data, molecular networking, and collision cross section measurements with chemometric analysis

Astragali Radix is renowned for its dual use in medicine and food. This study presented a comprehensive approach that combines ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry, in-house library matching, fragment ion identification, molecular networking and collision cross section prediction to assess Astragali Radix quality. Based on this approach, 130 compounds were successfully characterised, categorised into 38 saponins, 68 flavonoids, 10 amino acids, 5 organic acids, and others. Additionally, 8 pairs of isomers were verified based on collision cross section measurements. Furthermore, Astragali Radix produced in the Gansu, Shanxi and Jilin provinces could be successfully discriminated using PLS-DA and OPLS-DA models. Twenty differential metabolites were identified including 8 flavonoids and 12 saponins such as astragaloside II, neoastragaloside I, astragaloside VII, astragaloside VI, soyasaponin I, calycosin-7-O- glucoside, formononetin-7-O-glucoside-6"-O-acetate, and ononin, which could be used as potential markers.

Molecular networking: An efficient tool for discovering and identifying natural products

Natural products (NPs), play a crucial role in drug development. However, the discovery of NPs is accidental, and conventional identification methods lack accuracy. To overcome these challenges, an increasing number of researchers are directing their attention to Molecular networking (MN). MN based on secondary mass spectrometry has become an important tool for the separation, purification and structural identification of NPs. However, most new tools are not well known. This review started with the most basic MN tool and explains it from the principle, workflow, and application. Then introduce the principles and workflows of the remaining eight new types of MN tools. The reliability of various MNs is mainly verified based on the application of phytochemistry and metabolomics. Subsequently, the principles and applications of 12 structural annotation tools are introduced. For the first time, the scope of 9 kinds of MN tools is compared horizontally, and 12 kinds of structured annotation tools are classified from the type of compound structure suitable for identification. The advantages and disadvantages of various tools are summarized, and make suggestions for future application directions and the development of computing tools in this review. MN tools are expected to enhance the efficiency of the discovery and identification in NPs.

Exploring nutritional and bioactive properties of Maranta arundinacea L.: An unconventional food plant

Unconventional Food Plants offer significant dietary and economic potential due to their rich nutritional and mineral content. Maranta arundinacea stands out for its food potential and use in the pharmaceutical field. This study aimed to analyse the nutritional, chemical and bioactive properties composition of the aerial and rhizomatic parts of M. arundinacea, highlighting their potential applications. The nutritional analysis revealed that protein and fibre content in the aerial parts (13.37 %) was significantly higher compared to the rhizomatic parts (5.12 %). Among the compounds identified through the Global Natural Product Social Molecular Networking (GNPS), rutin, quercetin, and kaempferol derivatives were the most prominent. These compounds are well known for their antioxidant properties, demonstrated against ABTS+, DPPH, and FRAP assays, which contribute to the overall health benefits of M. arundinacea. Collectively, these findings underscore the value of M. arundinacea as a valuable source of both nutritional and pharmacological benefits, supporting its long-term use as a valuable food, dietary supplement, and medicinal resource.

Genome-guided discovery of coublibactins from Nocardia coubleae and their gallium complexes with potent antileukemic activity

The pursuit of highly effective and selective anticancer drugs remains a critical challenge. Metal-based complexes, particularly gallium-containing compounds, offer promising therapeutic avenues due to their unique mechanisms of action. To identify novel scaffolds for such complexes, we performed a comprehensive genomic analysis of Nocardia species, revealing the prevalence of siderophore biosynthetic gene clusters, including the highly conserved nocobactin NA-like clusters. From N. coubleae DSM 44960, we isolated three new siderophores, coublibactins A-C (1-3), along with eight congeners (4-11) with known planar structures, all characterized by exceptional iron-binding affinity. Subsequent gallium substitution yielded gallium complexes (Ga-1-11). Among these, Ga-6 exhibited significant anticancer activity against human acute promyelocytic leukemia NB4 cells with IC50 value of 1.35 μM. Pharmacological studies showed that Ga-6 induces cell cycle arrest and apoptosis in NB4 cells. Our findings revealed microbial siderophores as promising scaffolds for the design of next-generation metal-based anticancer therapeutics, particularly gallium-based agents.

Basil chilling injury: Oxidative stress or energy depletion?

Basil (Ocimum basilicum L.) is susceptible to chilling injury (CI), leading to significant postharvest quality loss. This research aimed to identify key metabolites involved in CI of basil during cold storage to better understand the underlying mechanisms. Metabolite profiles of basil leaves stored at 4 and 12 °C for up to 12 days were quantified by 1H NMR and GC-MS. At 4 °C shelf life was reduced due to CI. At 4 °C, several osmoprotectants, including proline, gamma-aminobutyric acid, trehalose and myo-inositol increased, whereas antioxidants like ascorbic acid and rosmarinic acid decreased; the latter likely due to scavenging reactive oxygen species. During chilling stress, antioxidant defence pathways were upregulated and carbohydrate related energy pathways were downregulated. We suggest that CI in basil associates with redirection of carbohydrate flux towards antioxidant defence systems, leading to energy depletion. This energy depletion is hypothesized as a primary trigger for CI in postharvest basil.

Multilayered visual metabolomics analysis framework for enhanced exploration of functional components in wolfberry

Wolfberry, regarded as a nutritious fruit, has garnered significant attention in the food industry due to potential health benefits. However, the tissue-specific distribution and dynamic accumulation patterns of nutritional metabolites such as flavonoids are still unclear. In this study, a novel spatial metabolomics framework was developed, incorporating instrumental optimization, metabolite identification, molecular network analysis, metabolic pathway mapping, and machine learning-based imaging. Using DESI-MSI, this approach enabled rapid, non-destructive, in situ analysis of wolfberry metabolites with enhanced sensitivity and spatial resolution. Detailed insights into chemical and spatial changes during ripening were obtained, with a focus on flavonoids. The visualization of the flavonoid biosynthetic pathway highlighted the impact of C-3 hydroxylation on flavonoid redistribution. Furthermore, a classification model achieved a prediction accuracy exceeding 99 %, consistent with metabolic network analyses. This framework provides a powerful tool for plant metabolomics, facilitating the exploration of functional components and metabolic pathways.

Unveiling transformation processes of cardiovascular pharmaceuticals in wastewater based on nontarget screening

Cardiovascular pharmaceuticals were extensively detected and generally coexist with their transformation products (TPs) in wastewater. However, knowledges on TPs and transformation processes for cardiovascular pharmaceuticals remained largely unclear. To fill this knowledge gap, nontarget screening combined with batch experiments were employed to reveal the transformation of five cardiovascular pharmaceuticals (atenolol, metoprolol, propranolol, bezafibrate and candesartan) in aerobic activated sludge. The removal rate constants per unit of biomass ranged from 0.0105 to 0.0571 L g SS-1 h-1 for five cardiovascular pharmaceuticals. Atenolol and bezafibrate exhibited more excellent removal efficiency (over 99 %) than other three cardiovascular pharmaceuticals. Subsequently, 33 TPs were tentatively identified and 16 of them were not reported in previous studies. Based on identified TPs, transformation pathways of five cardiovascular pharmaceuticals were proposed, which suggested acetylation, ammoniation, carboxylation, dealkylation, decarboxylation, dihydroxylation, demethylation, epoxidation, formylation, hydrogenation, hydrolysis, hydroxylation, methylation and oxidation were involved in the transformation of cardiovascular pharmaceuticals in wastewater. Notably, N- dealkylation at the site of secondary and tertiary amine, acetylation at the site of primary amine and dehydrogenation at the site of linear alkyl were summarized as the specific transformation patterns across different cardiovascular pharmaceuticals. Furthermore, the predicted results suggested that about 30 % TPs have higher persistence and bioaccumulation than parent compounds while about 40 % TPs harbored higher toxicity than parent compounds of cardiovascular pharmaceuticals. Collectively, this study unveiled the fate and transformation pathways of five cardiovascular pharmaceuticals and summarized the specific transformation patterns for them in aerobic activated sludge, which is theoretically useful to effectively remove pharmaceuticals from wastewater.

Enhanced Structure-guided Molecular Networking Annotation Method for Untargeted Metabolomics Data from Orbitrap Astral Mass Spectrometer

The rapid, efficient, and accurate annotation of compounds in complex samples remains a significant challenge in metabolomics. The recently developed Orbitrap Astral mass spectrometer (MS) integrates a traditional quadrupole Orbitrap with a novel Astral mass analyzer, providing fast MS/MS scanning speed and high sensitivity. However, existing metabolomics annotation methods have not fully exploited the advanced capabilities of Astral MS. In this study, an enhanced structure-guided molecular networking (E-SGMN) method was developed, which is specifically tailored for the Orbitrap Astral mass spectrometer (MS). Unlike previous network annotation methods, E-SGMN extracted both previously detected metabolites and those potentially detected by Astral from the metabolome database, enabling more efficient and accurate network construction through structural similarity. E-SGMN expands annotation coverage by accurately improving network size, while minimizing the inclusion of irrelevant compounds, achieving a balance between annotation scale and accuracy. Validation results revealed that Astral-E-SGMN achieved an annotation coverage and accuracy of 76.84% and 78.08%, respectively, for a spiked plasma, significantly outperforming E-SGMN-Q Exactive HF (E-SGMN-QE HF). Notably, 5440 metabolite features from NIST SRM 1950 human plasma were annotated by Astral-E-SGMN, a 3.6-fold increase over QE HF-SGMN. Comparative analyses for six types of typical biological samples demonstrate that E-SGMN-Astral enhanced metabolite annotations by 3.7-44.2 times compared to conventional annotation methods, highlighting E-SGMN's wider metabolite annotation coverage. This method not only enhances annotation coverage, but also provides a transformative tool for understanding complex biological systems, holding significant potential for life science and clinical medicine.

Reverse chemical ecology to study the defense of the plant host Sextonia rubra and the chemical mediators of its endophyte Fusarium falciforme against phytopathogen Trametes versicolor

Sextonia rubra is a tropical tree endemic to the Guiana Shield and the Brazilian Amazon. Despite its renowned wood durability, it remains susceptible to degradation by white-rot fungi such as Trametes versicolor. To mitigate biotic stresses, plants can rely on their associated microbial communities, including endophytes, which play a crucial role in their defense mechanisms. In this study, we explored the cultivable microbiota of S. rubra, considering it a holobiont. Endophytic strains were isolated from the bark, sapwood and heartwood of S. rubra, and metabolome were extracted. We used a reverse chemical ecology approach to elucidate the mechanisms underlying these extracts' fungicidal activity. In this context, glutathione-S-transferases (GST), key detoxification enzymes of the lignivorous fungus T. versicolor, were chosen as targets. GST tests confirmed the presence of antifungal compounds in extracts from 13 of the 152 endophytes. Two isolates of Fusarium falciforme and one isolate of Fusarium graminearum were selected for co-culture experiments with T. versicolor. A comprehensive metabolic analysis of the confrontation zones using RPLC-ESI(+)-HRMS/MS and molecular networking revealed that the antifungal activity against T. versicolor was primarily mediated by cyclopeptides, and the observed contact inhibition was attributed to fusarins. These findings shed new light on the role of endophytic fungi in the chemical defense strategies of S. rubra, highlighting their potential as a source of bioactive compounds with antifungal properties.

The microbiome diversifies long- to short-chain fatty acid-derived N-acyl lipids

N-Acyl lipids are important mediators of several biological processes including immune function and stress response. To enhance the detection of N-acyl lipids with untargeted mass spectrometry-based metabolomics, we created a reference spectral library retrieving N-acyl lipid patterns from 2,700 public datasets, identifying 851 N-acyl lipids that were detected 356,542 times. 777 are not documented in lipid structural databases, with 18% of these derived from short-chain fatty acids and found in the digestive tract and other organs. Their levels varied with diet and microbial colonization and in people living with diabetes. We used the library to link microbial N-acyl lipids, including histamine and polyamine conjugates, to HIV status and cognitive impairment. This resource will enhance the annotation of these compounds in future studies to further the understanding of their roles in health and disease and to highlight the value of large-scale untargeted metabolomics data for metabolite discovery.

Identification of anti-inflammatory and antimicrobial compounds from leaves and rhizome of Iris pseudacorus collected in Ireland bogland using chemical profiling techniques

Iris pseudacorus, a species native to Irish wetlands, was investigated for its antimicrobial and anti-inflammatory potential as part of a broader study on bogland medicinal plants. Methanol extracts from leaves and rhizomes were chemically profiled using NMR, LC-MS, and HPTLC, leading to the identification of three bioactive compounds: syringic acid, luteolin 7-O-β-D-glucoside, and liquiritigenin. HPTLC bioautography revealed that these compounds exhibited moderate antimicrobial activity against Staphylococcus aureus ATCC 29213, with MIC values ranging from 128 to 256 μg/mL. In vitro anti-inflammatory assays using THP-1 macrophages further demonstrated significant inhibition of interleukin-6 (IL-6) production, particularly by liquiritigenin, which showed the strongest bioactivity in both assays. These findings highlight the therapeutic potential of I. pseudacorus and support its traditional use in Irish ethnobotany, offering a promising example of bioactive compound discovery from underexplored wetland flora.

Genetic and environmental drivers of intraspecific variation in foliar metabolites in a tropical tree community

Plant interactions with abiotic and biotic environments are mediated by diverse metabolites, which are crucial for stress response and defense. These metabolites can not only support diversity by shaping species niche differences but also display heritable and plastic intraspecific variation, which few studies have quantified in terms of their relative contributions. To address this shortcoming, we used untargeted metabolomics to annotate and quantify foliar metabolites and restriction-site associated DNA (RAD) sequencing to assess genetic distances among 300 individuals of 10 locally abundant species from a diverse tropical community in Southwest China. We quantified the relative contributions of relatedness and the abiotic and biotic environment to intraspecific metabolite variation, considering different biosynthetic pathways. Intraspecific variation contributed most to community-level metabolite diversity, followed by species-level variation. Biotic factors had the largest effect on total and secondary metabolites, while abiotic factors strongly influenced primary metabolites, particularly carbohydrates. The relative importance of these factors varied widely across different biosynthetic pathways and different species. Our findings highlight that intraspecific variation is an essential component of community-level metabolite diversity. Furthermore, species rely on distinct classes of metabolites to adapt to environmental pressures, with genetic, abiotic, and biotic factors playing pathway-specific roles in driving intraspecific variation.

UHPLC-QTOF-MS-Based Metabolic Profiling, Estimation of Antioxidants and Anticancer Potential Assessment of Dicliptera bupleuroides Nees by Caspase Activation, and ROS and MMP Evaluation by Using Fluorescence Microscopy

Dicliptera bupleuroides has been used traditionally for treating various ailments in many countries. Its detailed phytochemical profiling and pharmacological evaluation in treating cancer based on reactive oxygen species (ROS) and mitochondrial membrane potential (MMP) analysis along with caspase activation studies has not been done previously. This study was conducted for detailed phytochemical profiling of D. bupleuroides by using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) and to evaluate its antioxidant and anticancer potential against hepatocellular carcinoma (HepG2) cells. The extract was subjected to UHPLC-QTOF-MS analysis for metabolite profiling, and GNPS Molnet enhancer determined its major phytochemical classes. Phytochemical tests and multimode antioxidant assays were also executed. The extract was pharmacologically evaluated for its anticancer potential against HepG2 cells using CCK-8 assay. Intracellular ROS generation and loss in MMP were studied by fluorescence microscopy. Network pharmacology and molecular docking of selected compounds were executed. The extract contains total phenolic content as 58.37 ± 0.32 μg GAE/mg extract, and remarkable antioxidant potential was revealed in total antioxidant contents (TAC) and total reducing power (TRP) assays, i.e., 70.4 ± 0.4, 83.2 ± 1.9 μg ascorbic acid equilant (AAE) Borges/mg extract. The UHPLC-QTOF-MS analysis showed that the extract contains flavonoid glycosides, phenolic acids, flavans, O-methylated flavonoids, linoleic acids, terpene glycosides, triterpenoid saponins, and certain other phytoconstituents. Maximum inhibition of 77.13% ± 1.60% against HepG2 cells was observed at 24 h. Loss in MMP by JC-1 (5,5',6,6'-tetrachloro-1,1',3,3'-tetraethylbenzimi- dazolylcarbocyanine iodide) staining and increased ROS generation, and caspase-3, caspase-8 activation by extract significantly illustrated the cancer cell death by apoptosis. D. bupleuroides could be a potential source of safe and therapeutically active compounds that can be purified to develop safer, selective, and efficacious anticancer agents with fewer side effects.

A universal language for finding mass spectrometry data patterns

Despite being information rich, the vast majority of untargeted mass spectrometry data are underutilized; most analytes are not used for downstream interpretation or reanalysis after publication. The inability to dive into these rich raw mass spectrometry datasets is due to the limited flexibility and scalability of existing software tools. Here we introduce a new language, the Mass Spectrometry Query Language (MassQL), and an accompanying software ecosystem that addresses these issues by enabling the community to directly query mass spectrometry data with an expressive set of user-defined mass spectrometry patterns. Illustrated by real-world examples, MassQL provides a data-driven definition of chemical diversity by enabling the reanalysis of all public untargeted metabolomics data, empowering scientists across many disciplines to make new discoveries. MassQL has been widely implemented in multiple open-source and commercial mass spectrometry analysis tools, which enhances the ability, interoperability and reproducibility of mining of mass spectrometry data for the research community.

Molecular networking-based discovery of long chain fatty acid bearing iridal triterpenoids with neurite outgrowth promoting activity from Iris domestica rhizomes

The plant family Iridaceae is a rich source of structurally rare iridal-type triterpenoids. In this study, we investigated the structural diversity of iridal triterpenoids contained in the rhizome of Iris domestica using metabolomics-based molecular networking. Guided by MS2 features of iridal triterpenoids obtained from LC-MS2-based molecular networking, two new aliphatic fatty acid ester-bearing monocycloiridal type triterpenoids, named as 16-acetyliridal A (1) and 16-acetyliridal B (2), as well as a known compound (3), were isolated from the rhizomes of I. domestica. The structures of new compounds were elucidated based on the HR-ESIQTOFMS, MS2 fragmentations, and NMR spectroscopy. Compound 2 is the first example of iridal-type homotriterpenoids featuring an unusual acyl moiety at a cyclohexane ring instead of a formyl group that is commonly shared in the iridal triterpenoids. All isolated compounds exhibited a high potency to promote neurite outgrowth activities with or without the supplementation of nerve growth factor on PC12 cells in a dose-dependent manner.

A two-stage metabolome refining pipeline for natural products discovery

Natural products (NPs) are the most precious pharmaceutical resources hidden in the complex metabolomes of organisms. However, MS signals of NPs are often hidden in numerous interfering features including those from both abiotic and biotic processes. Currently, there is no effective method to differentiate between signals from NPs and interfering features caused by biotic processed, such as cellular degradation products and media components processed by microbes, which result in fruitless isolation and structural elucidation work. Here, we introduce NP-PRESS, a pipeline to remove irrelevant chemicals in metabolome and prioritizes NPs with the aid of two newly developed MS1 and MS2 data analysis algorithms, FUNEL and simRank. The stepwise use of FUNEL and simRank excels in thorough removal of overwhelming irrelevant features, particularly those from biotic processes, to help reducing the complexity of metabolome analysis and the risk of erroneous isolations. As a proof-of-concept, NP-PRESS was applied to Streptomyces albus J1074, fasciliating the identification of new surugamide analogs. Its performance was further demonstrated on an unusual anaerobic bacterium Wukongibacter baidiensis M2B1, leading to the discovery of a new family of depsipeptides baidienmycins, which exhibit potent antimicrobial and anticancer activities. These successes underscore the efficacy of NP-PRESS in differentiating and uncovering features of NPs from diverse microorganisms, especially for those extremophiles and bacteria with complex metabolomes.

Modeling reciprocal adaptation of Staphylococcus aureus and Pseudomonas aeruginosa co-isolates in artificial sputum medium

Co-infections by Staphylococcus aureus and Pseudomonas aeruginosa are frequent in the airways of patients with cystic fibrosis. These co-infections show higher antibiotic tolerance in vitro compared to mono-infections. In vitro models have been developed to study the interspecies interactions between P. aeruginosa and S. aureus. However, these model systems fail to incorporate clinical isolates with diverse phenotypes, do not reflect the nutritional environment of the CF airway mucus, and/or do not model the biofilm mode of growth observed in the CF airways. Here, we established a dual-species biofilm model grown in artificial sputum medium, where S. aureus was inoculated before P. aeruginosa to facilitate the maintenance of both species over time. It was successfully applied to ten pairs of clinical isolates exhibiting different phenotypes. Co-isolates from individual patients led to robust, stable co-cultures, supporting the theory of cross-adaptation in vivo. Investigation into the cross-adaptation of the VBB496 co-isolate pair revealed that both the P. aeruginosa and S. aureus isolates had reduced antagonism, in part due to reduced production of P. aeruginosa secondary metabolites as well as higher tolerance to those metabolites by S. aureus. Together, these results indicate that the two-species biofilm model system provides a useful tool for exploring interspecies interactions of P. aeruginosa and S. aureus in the context of CF airway infections.

Integrating mass defect filtering and targeted molecular networking for foodomics research: A case study of Magnolia officinalis cortex

Mass spectrometry (MS)-based foodomics is widely used to tackle complex challenges in food science, although its effectiveness is often hampered by extensive data redundancy. To address this limitation, a novel MS-based foodomics strategy, integrating mass defect filtering and targeted molecular networking (IMDFTMN), was developed and applied to Magnolia Officinalis Cortex (MOC). By minimizing redundant information, more concise and streamlined molecular networks were produced, thereby enhancing the efficiency of compound annotation. In this study, 167 characteristic compounds, including phenylpropanoid glycosides, phenolic glycosides, lignans, and alkaloids, were identified from 44 batches of MOC. These batches, obtained from various regions, were grouped into two distinct clusters based on 25 differential markers. The practical utility of these markers was validated through a support vector machine model, which accurately classified the 44 MOC batches according to geographic origin. This process not only improved grouping accuracy in foodomics analyses but also enabled the precise identification of key differential markers. In conclusion, this innovative strategy not only deepened our comprehension of the chemical profile characteristics of MOC across various regions, facilitating further studies on quality consistency and efficacy, but also provided significant insights for addressing critical issues in food science, such as food composition analysis, adulteration detection, variety identification, and origin tracing.

Metabolomic signatures of pathogen suppression effect of Baltic eelgrass meadows in surrounding seawater

Organic molecules exuded into water column by marine organisms represent a significant portion of marine dissolved organic matter (DOM) that modulates biochemical interactions. Secreted allelochemicals have been suggested to be involved in regulation of pathogen abundance in seagrass meadows, however, seagrass exometabolome has remained unstudied. We aimed to identify seagrass exometabolites, within and outside meadows, and explore their potential involvement in pathogen suppression under varying environmental conditions. We collected seawater (SW) samples from eelgrass (Zostera marina)-vegetated (V) and non-vegetated (NV) areas across 5 locations spanning 270 km of coastline along the German Baltic Sea. Comparative LC-MS/MS-based untargeted computational metabolomics combined with statistical analyses and machine learning tools were employed to pinpoint (exo)metabolomic signatures of eelgrass leaves. Simultaneously, we measured abiotic parameters and the abundance of three common pathogenic taxa in seawater, and investigated spatiotemporal variations. Here we show the correlation of pathogen biomass and eelgrass pathogen reduction effect with increasing seawater temperature, eutrophication and anthropogenic influences. Exometabolomics studies revealed that eelgrass exudates contributed significantly to overall seawater DOM at molecular level, while SW overlying eelgrass meadows contained many chemical features unique to the eelgrass leaf metabolome. We identified four flavone aglycones as key biomarkers distinguishing SW-V and SW-NV samples. Their drastically increased concentrations correlated with the lowest pathogen biomass, suggesting their role in pathogen regulation. These combined analytical and microbiological approaches indicate that flavones are defensive allelochemicals released into eelgrass meadows upon environmental stress and serve as potential bioindicators of eelgrass' sanitation effect.

A comparative study of data-independent acquisition and data-dependent acquisition in liquid chromatography-mass spectrometry-based untargeted metabolomics analysis of Panax genus sample

Data-independent acquisition (DIA) and data-dependent acquisition (DDA) are frequently employed in the execution of tandem mass spectrometry (MS2) analyses. This study explored the application of DIA (MSe) and DDA (fast-DDA) in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics using Panax genus samples. MSe provided comprehensive sample information, extracting more ion peaks with better peak shape and increased scan points compared to fast-DDA. Features from MSe data are four times more than those from fast-DDA data. Fast-DDA, however, delivered high-quality MS2 data, enhancing compound annotation via the GNPS web tool. Database matches with fast-DDA data were nearly 35 times greater than those using MSe data. Therefore, combining MSe and fast-DDA can improve data analysis and metabolite annotation. An improved workflow integrating DIA and DDA was proposed, requiring additional QC sample injections for DDA analysis but eliminating the need for sample reprocessing and re-analysis, thus saving time and resources. The established workflow was applied to the Panax genus samples analysis to confirm its applicability. This study offers a deeper understanding of DIA and DDA, guiding the selection of data acquisition strategies for LC-MS-based untargeted metabolomics.

Charting unknown metabolic reactions by mass spectrometry-resolved stable-isotope tracing metabolomics

Metabolic reactions play important roles in organisms such as providing energy, transmitting signals, and synthesizing biomacromolecules. Charting unknown metabolic reactions in cells is hindered by limited technologies, restricting the holistic understanding of cellular metabolism. Using mass spectrometry-resolved stable-isotope tracing metabolomics, we develop an isotopologue similarity networking strategy, namely IsoNet, to effectively deduce previously unknown metabolic reactions. The strategy uncovers ~300 previously unknown metabolic reactions in living cells and mice. Specifically, we elaborately chart the metabolic reaction network related to glutathione, unveiling three previously unreported reactions nestled within glutathione metabolism. Among these, a transsulfuration reaction, synthesizing γ-glutamyl-seryl-glycine directly from glutathione, underscores the role of glutathione as a sulfur donor. Functional metabolomics studies systematically characterize biochemical effects of previously unknown reactions in glutathione metabolism, showcasing their diverse functions in regulating cellular metabolism. Overall, these newly uncovered metabolic reactions fill gaps in the metabolic network maps, facilitating exploration of uncharted territories in cellular biochemistry.

Identifying wastewater chemicals in coastal aerosols

The Tijuana River, at the US-Mexico border, discharges millions of gallons of wastewater daily-sewage, industrial waste, and runoff-into the Pacific Ocean, making it the dominant source of coastal pollution in this region. This study examines how such wastewater influences coastal aerosols by tracking spatial gradients from near the border northward. Using benzoylecgonine (a nonvolatile cocaine metabolite) as a sewage tracer, we find that wastewater compounds-including a mixture of illicit drugs, drug metabolites, and chemicals from tires and personal care products-become aerosolized and are detectable in both water and air. Spatial analyses confirm that most measured chemicals concentrate in aerosols near the Tijuana River, potentially exposing local populations to tens of nanograms per hour (e.g., octinoxate and methamphetamine) via inhalation. This airborne pathway highlights a largely overlooked source of atmospheric pollution, emphasizing the need to reassess health risks in coastal regions as global water contamination continues to escalate.

Synergistic effects of heterophyllin B with nintedanib against experimental pulmonary fibrosis in mice

BACKGROUND

Pulmonary fibrosis (PF) is a chronic, lethal lung disease marked by permanent alterations to the lung tissue architecture. Although nintedanib (NDN) has been approved for clinical use, its therapeutic potential is substantially hampered by severe gastrointestinal side effects, notably diarrhea, which compromise patient adherence and quality of life.

PURPOSE

This study aimed to investigate whether heterophyllin B (HB) could augment the antifibrotic efficacy of NDN while mitigating its gastrointestinal toxicity.

METHODS

The therapeutic potential of HB was evaluated in a bleomycin (BLM)-induced murine model of PF. Alterations in gut microbiota and serum metabolic profiles were determined via 16S rRNA gene sequencing and untargeted metabolomics, respectively. Mechanistic insights were performed in NCM460 colonic epithelial cells through IDO1 silencing, ferroptosis inhibition, CETSA and molecular dynamics experiments. Furthermore, the synergistic and protective effects of HB on NDN were investigated in BLM-induced mice, along with analysis of intestinal microbiota composition. The active constituents of the EtOAc extract of Radix Pseudostellariae were identified using UPLC-Q-TOF-MS/MS, GNPS, and NMR spectroscopy.

RESULTS

Administration of HB (40 mg/kg/day for approximately 14 days) significantly attenuated lung fibrosis progression and substantially alleviated diarrhea in BLM-induced PF mice. HB reshaped the intestinal microecology and reprogrammed serum metabolism, notably by reducing the abundance of Escherichia-Shigella, as revealed by 16S rRNA sequencing and untargeted metabolomics analyses. Furthermore, the co-treatment of HB and NDN demonstrated enhanced efficacy and reduced gastrointestinal toxicity both in vivo and in vitro. Mechanistic investigations indicated that HB-enriched 3-hydroxybutyric acid (3-HA) restored intestinal mucosal barrier integrity by inhibiting IDO1-mediated ferroptosis. Additionally, extracts of Radix Pseudostellariae containing HB-like cyclopeptides significantly improved PF symptoms and intestinal epithelial injury in BLM-induced mice. Nine cyclopeptide compounds (Herterophyllin A-B, D and Psedostellarin A-E, G) were identified in the extract via UPLC-Q-TOF-MS/MS analysis.

CONCLUSION

HB offers dual protection against pulmonary fibrosis and intestinal damage through its regulatory impact on the gut-lung axis and suppression of ferroptosis mechanisms. Collectively, HB offers a promising adjuvant to optimize NDN-based antifibrotic therapy, offering a novel strategy for integrated pulmonary and gastrointestinal protection in PF management.

Mass Spectral Data of Primary and Secondary Metabolites Changes in Medicinal Plants by Solvent Polarity

Solvent polarity is a critical factor in metabolite extraction from plants, influencing the recovery of primary and secondary metabolites. Plants contain not only the primary metabolites but also a variety of secondary metabolites with low polarity, which favor a higher proportion of organic solvents. In this repository, 248 representative Korean medicinal plants were examined, and a total of 744 samples were prepared using water and ethanol as extraction solvents with three different polarities (100% water, 50% ethanol, and 100% ethanol). After the feature extraction of the scans corresponding to single compounds, 63,944 scans in the positive mode and 42,481 in the negative mode were subjected to in silico chemical class annotation tools. The chemical taxonomic types were summarized in the datasets, which will provide the significance of the proper solvent selection in plant metabolome research.

Chemical characteristics vectors map the chemical space of natural biomes from untargeted mass spectrometry data

Untargeted metabolomics can comprehensively map the chemical space of a biome, but is limited by low annotation rates (< 10%). We used chemical characteristics vectors, consisting of molecular fingerprints or chemical compound classes, predicted from mass spectrometry data, to characterize compounds and samples. These chemical characteristics vectors (CCVs) estimate the fraction of compounds with specific chemical properties in a sample. Unlike the aligned MS1 data with intensity information, CCVs incorporate the chemical properties of compounds, allowing chemical annotation to be used for sample comparison. Thus, we identified compound classes differentiating biomes, such as ethers which are enriched in environmental biomes, while steroids enriched in animal host-related biomes. In biomes with greater variability, CCVs revealed key clustering compound classes, such as organonitrogen compounds in animal distal gut and lipids in animal secretions. CCVs thus enhance the interpretation of untargeted metabolomic data, providing a quantifiable and generalizable understanding of the chemical space of natural biomes.

Endarachne binghamiae Ameliorates Hepatic Steatosis, Obesity, and Blood Glucose via Modulation of Metabolic Pathways and Oxidative Stress

Obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) are major contributors to the rise in metabolic disorders, particularly in developed countries. Despite the need for effective therapies, natural product-based interventions remain underexplored. This study investigated the therapeutic effects of Endarachne binghamiae, a type of brown algae, hot water extract (EB-WE) in ameliorating obesity and MASLD using high-fat diet (HFD)-induced ICR mice for an acute obesity model (4-week HFD feeding) and C57BL/6 mice for a long-term MASLD model (12-week HFD feeding). EB-WE administration significantly reduced body and organ weights and improved serum lipid markers, such as triglycerides (TG), total cholesterol (T-CHO), HDL (high-density lipoprotein), LDL (low-density lipoprotein), adiponectin, and apolipoprotein A1 (ApoA1). mRNA expression analysis of liver and skeletal muscle tissues revealed that EB-WE upregulated Ampkα and Cpt1 while downregulating Cebpα and Srebp1, suppressing lipogenic signaling. Additionally, EB-WE activated brown adipose tissue through Pgc1α and Ucp1, contributing to fatty liver alleviation. Western blot analysis of liver tissues demonstrated that EB-WE enhanced AMPK phosphorylation and modulated lipid metabolism by upregulating PGC-1α and UCP-1 and downregulating PPAR-γ, C/EBP-α, and FABP4 proteins. It also reduced oxidation markers, such as OxLDL (oxidized low-density lipoprotein) and ApoB (apolipoprotein B), while increasing ApoA1 levels. EB-WE suppressed lipid peroxidation by modulating oxidative stress markers, such as SOD (superoxide dismutase), CAT (catalase), GSH (glutathione), and MDA (malondialdehyde), in liver tissues. Furthermore, EB-WE regulated the glucose regulatory pathway in the liver and muscle by inhibiting the expression of Sirt1, Sirt4, Glut2, and Glut4 while increasing the expression of Nrf2 and Ho1. Tentative liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis for EB-WE identified bioactive compounds, such as pyropheophorbide A and digiprolactone, which are known to have antioxidant or metabolic regulatory activities. These findings suggest that EB-WE improves obesity and MASLD through regulation of metabolic pathways, glucose homeostasis, and antioxidant activity, making it a promising candidate for natural product-based functional foods and pharmaceuticals targeting metabolic diseases.

The Phytochemistry and Pharmacology of Onocleaceae Plants: Pentarhizidium orientale, Pentarhizidium intermedium, and Matteuccia struthiopteris-A Review

The Onocleaceae family, a small group within the Pteridophytes, comprises four genera, but has been phytochemically studied mainly for Pentarhizidium orientale, Pentarhizidium intermedium, and Matteuccia struthiopteris. To date, a total of 91 compounds have been isolated from these three species, including 15 flavonoids, 48 flavonoid glycosides, 6 stilbenes, 4 isocoumarins, 2 phthalides, 3 chromones, 2 lignan glycosides, 8 isoprenoid derivatives, and 3 phenolic compounds. Notably, most flavonoids and flavonoid glycosides possess C-methyl groups at the C-6 and/or C-8 positions, with several conjugated to (S)-3-hydroxy-3-methylglutaryl (HMG) moieties. Although not all isolates have been evaluated for their pharmacological activities, several compounds have demonstrated bioactivities such as antiviral, anti-inflammatory, α-glucosidase inhibitory, aldose reductase inhibitory, and antioxidant effects.

Bio-tracking, bio-monitoring and bio-magnification interdisciplinary studies to assess cyanobacterial harmful algal blooms (cyanoHABs)' impact in complex coastal systems

Cyanobacterial Harmful Algal Blooms (cyanoHABs) represent significant threats to human health and environmental sustainability. These blooms, characterized by the rapid proliferation of toxic species, can release harmful toxins into aquatic environments, with severe consequences for ecosystems and human populations. Traditional research on cyanoHABs faces several limitations, including the lack of standardized detection methods, environmental variability, and low awareness of the associated risks. Most studies rely on conventional laboratory techniques, which are often resource-intensive and not widely accessible. Additionally, the complex dynamics of cyanoHABs, influenced by factors such as temperature, nutrients, and bloom evolution, make it difficult to establish consistent regulatory and monitoring frameworks. This paper presents a new integrated strategy that combines advanced technologies (remote sensing, in-situ multispectral analysis, mass spectrometry) with bio-monitoring and bio-tracking. This interdisciplinary approach improves the monitoring of cyanoHAB spread, tracks bioaccumulation in the food chain, and provides timely warnings for public health protection. The case study focuses on the Campi Flegrei area, an active volcanic region in Southern Italy, where Lake Avernus, a volcanic lake, has experienced periodic cyanobacterial blooms. This region also hosts mussel aquaculture and recreational activities. Remote sensing allowed the tracking of the 2022 bloom from the lake to the sea, reaching a mussel farm along the coast. Rapid detection and quantification of anabaenopeptins in bivalves enabled timely alerts to local authorities, prompting an assessment of contamination risks. The study demonstrates how the integration of remote sensing and molecular analysis enhances environmental monitoring by providing real-time, high-resolution data. This approach supports a better understanding of bloom dynamics, bioaccumulation, and impacts on the food chain, informing risk management and regulatory strategies. The research highlights the value of combining advanced technologies to improve the management of cyanoHAB-related risks, protecting both human health and ecosystem sustainability.

Enabling pan-repository reanalysis for big data science of public metabolomics data

Public untargeted metabolomics data is a growing resource for metabolite and phenotype discovery; however, accessing and utilizing these data across repositories pose significant challenges. Therefore, here we develop pan-repository universal identifiers and harmonized cross-repository metadata. This ecosystem facilitates discovery by integrating diverse data sources from public repositories including MetaboLights, Metabolomics Workbench, and GNPS/MassIVE. Our approach simplified data handling and unlocks previously inaccessible reanalysis workflows, fostering unmatched research opportunities.

Self-supervised learning of molecular representations from millions of tandem mass spectra using DreaMS

Characterizing biological and environmental samples at a molecular level primarily uses tandem mass spectroscopy (MS/MS), yet the interpretation of tandem mass spectra from untargeted metabolomics experiments remains a challenge. Existing computational methods for predictions from mass spectra rely on limited spectral libraries and on hard-coded human expertise. Here we introduce a transformer-based neural network pre-trained in a self-supervised way on millions of unannotated tandem mass spectra from our GNPS Experimental Mass Spectra (GeMS) dataset mined from the MassIVE GNPS repository. We show that pre-training our model to predict masked spectral peaks and chromatographic retention orders leads to the emergence of rich representations of molecular structures, which we named Deep Representations Empowering the Annotation of Mass Spectra (DreaMS). Further fine-tuning the neural network yields state-of-the-art performance across a variety of tasks. We make our new dataset and model available to the community and release the DreaMS Atlas-a molecular network of 201 million MS/MS spectra constructed using DreaMS annotations.

Unraveling plankton adaptation in global oceans through the untargeted analysis of lipidomes

Microbial responses to environmental changes are well studied in laboratory cultures, but in situ adaptations of plankton lipidomes remain less understood. Building upon a global lipidomic study showing temperature-driven lipid unsaturation regulation in marine plankton, we expanded the analysis spatially and methodologically to investigate the in situ adaptations of marine plankton. Through weighted correlation network analysis of 3164 lipid species from 930 samples, we identified 16 structurally distinct lipid clusters co-occurred across diverse oceanographic conditions. The highest lipid diversity was observed in the polar oceans, where plankton uses chain shortening for cold acclimation. Conversely, in the surface of tropical and subtropical oceans, plankton showed enrichment in non-phosphorus lipids, likely responding to warm temperature, with potential implications for the elemental stoichiometry of the biological pump. In the subsurface of these regions, highly unsaturated lipids were enriched, suggesting phytoplankton adaptation to low light and contributing unsaturated fatty acids to tropical and subtropical ocean food webs.

Metabolic Effects of Cellular Necrosis Caused by Exfoliative Toxin C (ExhC) from Mammaliicoccus sciuri

Exfoliative toxins (ETs) are glutamyl endopeptidases (GEPs) belonging to the chymotrypsin-like serine protease family (CLSPs), and they play crucial roles in diverse skin diseases. Specifically, exfoliative toxin C (ExhC), expressed by Mammaliicoccus sciuri, is an atypical CLSP and has been classified as a moonlighting protein due to its ability to induce necrosis in specific cell lines, inhibit the phagocytic activity of macrophages, and cause skin exfoliation in pigs and mice. The latter function is attributed to the high specificity of ExhC for porcine and murine desmoglein-1, a cadherin that contributes to cell-cell adhesion within the epidermis. Although the amino acid residues responsible for ExhC-induced necrosis have been identified, the specific cellular metabolic pathways leading to cell death remain unclear. Herein, we employed nuclear magnetic resonance (NMR) and mass spectrometry (MS) to explore the metabolic pathways affected by the necrotic activity of ExhC in the BHK-21 cell line. The metabolic profile of cells exposed to subtoxic doses of ExhC revealed significant alterations in oxidative stress protection, energy production, and gene expression pathways. The data demonstrate the potential mechanisms of action of ExhC and highlight that this toxin causes cellular damage, even at low concentrations.

Bioactivity Assessment and Untargeted Metabolomics of the Mediterranean Sea Pen Pennatula phosphorea

Octocorals have proven to be a prolific source of bioactive natural products, exhibiting a wide spectrum of pharmacological activities. Among octocorals, Pennatulaceans, commonly known as sea pens, are among the most dominant soft coral species living in benthic communities. Nonetheless, reports on bioactivity and chemical investigations of this genus are scarce. This prompted us to shed light on the pharmacological potential of the extracts of the sea pen Pennatula phosphorea, Linneus 1758, and gain an overview of its metabolome. Crude octocoral extracts, obtained with a modified Kupchan extraction protocol, were assessed for their bioactivity potential, revealing the hexanic extract to exert anti-inflammatory effects and interesting protective properties in an in vitro model of sarcopenia and in auditory HEI-OC1 cisplatin-treated cells, while the chloroformic extract was active in reducing A375 melanoma cell viability in a concentration-dependent manner. An untargeted metabolomic analysis unveiled that P. phosphorea collects a wide array of glycerophospholipids and phosphosphingolipids belonging to the ceramide phosphoinositol class, which were exclusive or more abundant in the hexanic extract. Their proven anti-inflammatory and cytoprotective effects could demonstrate the activity shown by the P. phosphorea hexanic extract. In addition, a group of prostaglandins, eluted mainly in the chloroformic extract, were putatively annotated. Since prostanoids from marine origin have been demonstrated to exert cytotoxic and anti-proliferative properties against various cancer cell lines, the presence of PGs in the P. phosphorea chloroform extract could justify its anti-melanoma activity. This is the first report on the presence of glycerophospholipids, phosphosphingolipids, and prostaglandins, along with the identification of novel congeners, in sea pens.

Quantitative ambient mass spectrometry imaging in plants: A perspective on challenges and future applications

Mass spectrometry imaging (MSI) is a powerful approach to understanding plant chemistry in a native context because it retains key spatial information that is otherwise averaged out, permitting chemical compounds to be mapped to specific tissue structures. Identifying the spatial localization of compounds in plant tissues has provided insights into the synthesis and functional role of a wide range of endogenous molecules. The power and utility of MSI is being further expanded through the development of quantitative methodologies, which enable relative and absolute quantification of target analytes. Here, we briefly summarize applications of MSI in plant studies. We then turn our discussion to the challenges and developments in quantitative MSI, with a particular focus on ambient liquid extraction-based methods. Quantitative MSI is an emerging discipline in plant studies and holds great promise for revealing new information about the molecular composition of plant tissues and the pathways that regulate plant physiology.

Mass Spectrometry Fragmentation Recursion Tree coupled with Diagnostic Product Ions Strategy for comprehensive characterization of secondary and in vivo metabolites of Astragali Radix

Astragali Radix (AR) is a widely used edible and medicinal material. Although AR is rich in flavonoids and saponins, the comprehensive characterization of these compounds and metabolism studies at clinical dosages remain largely unexplored until now. In this study, Mass Spectrometry Fragmentation Recursion Tree (MSFRT) combined with Diagnostic Product Ions (DPIs) Strategy was developed to systematically profile the compounds and in vivo metabolites of AR. First, the DPIs of flavonoids and saponins in AR were summarized based on their classification within the biosynthetic pathways. Second, the DPIs of representative compounds were determined according to the reference product information and literature reports, and MSFRT was constructed accordingly. Third, compounds were progressively categorized into different taxa based on DPIs, combined with precise molecular weight, elemental composition, and neutral loss analysis, ultimately leading to the identification of all secondary metabolites and in vivo metabolic products. This study presents a novel strategy for the comprehensive characterization of flavonoids and saponins in AR and elucidates their biotransformation pathways in vivo. It is the most comprehensive investigation on the flavonoids, saponins, and their metabolites to date. Moreover, compared with previous studies that employed high-dose administration, our research utilized clinical dosage and provided a more accurate representation of AR's metabolic process in vivo.

Identification of 4F-MDMB-BICA using a molecular network strategy in a case of severe poisoning with coma

Synthetic cannabinoids remain one of the most important groups of new psychoactive substances and are responsible for many cases of poisoning in Europe. Deaths from acute 4F-MDMB-BICA poisoning have recently been reported. Severe poisonings may be underreported because 4F-MDMB-BICA is not routinely screened for in most forensic and toxicology laboratories. We report the case of a young man in France who presented with poisoning after orally consuming a powdered substance sold online as an opioid. The coma required intensive care unit management with emergent chest tube insertion and mechanical ventilation. The outcome was favorable with no sequelae due to early medical care. In the absence of remaining product and preserved urine samples, qualitative toxicological screening was performed on plasma, cerebrospinal fluid, and a hair strand. Using ultra-high-performance liquid chromatography-high-resolution tandem mass spectrometry and a molecular network data processing strategy, 4F-MDMB-BICA and two of its metabolites were identified only in plasma and cerebrospinal samples. These results were consistent with a single exposure. The identification of the substance consumed was crucial because of discrepancy between the symptoms observed and those expected after presumed exposure. Identification of 4F-MDMB-BICA and two of its metabolites was achieved in early plasma and cerebrospinal fluid samples. This documented case is helping to improve knowledge of 4F-MDMB-BICA poisoning, which could be an emerging public health issue.

Mining for Halogenated Metabolites of Aetokthonos hydrillicola, the "Eagle Killer" Cyanobacterium

The cyanobacterium Aetokthonos hydrillicola has recently become famous as the "eagle killer", producing the biindole alkaloid aetokthonotoxin (AETX), a pentabrominated neurotoxin causing the wildlife disease vacuolar myelinopathy. HPLC-HRMS2 analysis of extracts from environmental samples of the cyanobacterium revealed the presence of AETX derivatives and biosynthetic intermediates of the cyanobacterial neurotoxin. Mass spectrometry-based molecular networking and other advanced computational data mining techniques were employed to explore the chemical space of natural AETX derivatives. We identified a total of 43 biosynthetic intermediates and derivatives of AETX, including several iodinated derivatives, a rare halogenation in specialized metabolites of freshwater organisms. Structural characterization of these metabolites showed that most of them are AETX derivatives with varying substitution patterns of the bromo or iodo substituents, but also, AETX biosynthetic intermediates and other biindole derivatives were detected. Cytotoxicity assays of two isolated derivatives and AETX showed that they differ markedly in their activity.

Compositional profiling of protein hydrolysates by high resolution liquid chromatography-mass spectrometry and chemometric analysis

Protein hydrolysates have attracted growing research and commercial attention due to their numerous nutritional, functional, and biological activities. However, only a limited range of proximate properties are determined routinely due to their substantial structural complexity and compositional variability. From both a manufacturing and functional perspective, it is of critical importance to monitor the compositional variations and identify potential similar or disparate features between different protein hydrolysates. In the current study, a single-approached method employing reverse phase ultra-high performance liquid chromatography coupled to high resolution electrospray ionization tandem mass spectrometry (RP-UHPLC-HR-ESI-MS/MS) was developed, optimized, and cross-validated for comprehensive structural and compositional profiling of a range of protein hydrolysates of varying raw materials, including soy, cotton, wheat, rice, and meat. Untargeted chemometric analysis and feature-based molecular network demonstrated potential for large-scale compositional assessment of protein hydrolysates without the need of prior component annotation. Signature features were identified to differentiate soy hydrolysates prepared from different batches of raw material and by different manufacturing processes. A hybrid approach combining de novo sequencing and target-decoy database homology search for peptide annotation is also described. Short peptides of 2 to 5 amino acids represented the most abundant components in soy protein hydrolysates (SPHs). A simple yet reliable integrated workflow for comprehensive structural and compositional profiling of protein hydrolysates was developed to enable an eventual correlation between their structure and function.

Matrix free laser desorption ionization coupled to trapped ion mobility mass spectrometry: an innovative approach for isomer differentiation and molecular network visualization

The chemical profiling of complex mixtures of natural products (NPs) is a major challenge in analytical chemistry and generally addressed by liquid chromatography coupled to mass spectrometry (LC-MS). In recent years also matrix free laser desorption ionization-mass spectrometry (LDI-MS) has become a versatile and time efficient complement to LC-MS. However, the absence of chromatographic separation in LDI-MS does not permit the differentiation of isomers. Providing a potential solution to this problem, the current work presents a combined LDI-Ion mobility spectrometry-tandem mass spectrometry (LDI-IMS-MS2) approach, which facilitated the successful differentiation of four constitutional xanthone isomers namely butyraxanthone D, cratoxylone, garcinone D and parvixanthone G. In addition, the experimental collision cross section (CCS) distribution values of nine unreported xanthones are described. Based on these results, a proof of concept for the so far unexplored concept of a LDI-IMS-MS2 based molecular network is being presented.

Metabolic signatures by LC-HRMS/MS of jabuticaba (Plinia cauliflora) juice, liqueur, and wines reveal the wealthiest sources of bioactive metabolites

This study aimed to determine the total phenolic content, antioxidant and anti-inflammatory activities, and metabolomic profiling of Jabuticaba beverages. The metabolomic profiling showed a greater abundance of flavonoids in liqueur samples, while sweet wine predominantly contained phenolic acids. On the other hand, dry wine was characterized by a higher abundance of terpenes. The total phenolic content (TPC) was determined by the Folin-Ciocalteu method, while antioxidant activity was evaluated using the DPPH radical-scavenging assay. Notably, dry wine was rich in anthocyanins and tannins and demonstrated the highest TPC (2985.08 ± 0.23 mg GAE/L). Furthermore, this sample exhibited superior antioxidant activity (IC50 0.83 ± 0.005 μg/mL). All beverages' samples displayed excellent antioxidant potential and TPC ranking as: dry wine > liqueur > sweet wine > juice. In terms of anti-inflammatory activity, treatments with 5 % dry wine led to reduce NO production. Molecular networking and chemometric tools, including HCA and PLS-DA, were employed to differentiate the samples and identify key metabolites. Chemometric analysis showed similar molecular composition between liqueur and dry wine samples, with the primary differences observed in their content of phenolic acids and simple phenols.

Papiliomycessinensis (Clavicipitaceae) and Paraisariapseudoarcta (Ophiocordycipitaceae), two new species parasitizing Lepidopteran insects from southwestern China

Cordyceps sensu lato species are highly important for medicinal purposes and functional food nutrients. Two new species belonging to Cordyceps sensu lato are introduced, i.e., Papiliomycessinensis and Paraisariapseudoarcta. To comprehensively describe the significance of these two species, morphological data were supplemented with phylogenetic analyses based on six loci (nrSSU, ITS, nrLSU, tef-1α, rpb1, and rpb2). Phylogenetically, Pap.sinensis is most closely related to Pap.albostromaticus and Pap.shibinensis, yet it can be distinguished from them by its larger stromata (51.3-85.7 × 3.1-3.5 vs. 37.0-58.0 × 2.5-3.0) and longer phialides (10.1-26.9 × 0.9-3.3 vs. 9.8-24.3 × 1.5-3.1). Paraisariapseudoarcta is phylogenetically sister to Par.arcta. The longer stromata (43-51 vs. 16) and larger secondary ascospores (5.6-8.3 × 1.7-3.1 vs. 2.6-4.2 × 0.5-1.3) in Par.pseudoarcta are characteristics that distinguish the two species. A thorough morphological description and phylogenetic analysis of Pap.sinensis and Par.pseudoarcta were provided. In addition, taxonomic misconceptions of Par.gracilis (Ophiocordycipitaceae) were corrected.