Search Results (101)

The human skin microbiome has gained considerable attention as a resource for the development of innovative probiotics for cosmetic purposes or promoting skin health. However, the evaluation of new probiotic strains to ensure their “generally recognized as safe” (GRAS) status remains challenging. Here, we have subjected the annotated draft genome sequences of four human skin-derived bacterial strains, namely Bacillus subtilis MBF10-19J, Micrococcus luteus MBF05-19J, Staphylococcus hominis MBF12-19J, and Staphylococcus warneri MBF02-19J, to bioinformatic analyses to detect the genes associated with important probiotic traits, as well as undesirable characteristics such as antibiotic resistance, virulence factors, and toxic metabolites. Each bacterium harbors at least one type of adhesin-encoding gene, while only S. hominis MBF12-19J and S. warneri MBF02-19J contain the putative genes encoding enzymes for metabolism improvement. In vitro assays, including antibiotic susceptibility and antimicrobial activity testing, revealed strain-specific safety characteristics that complement the genomic findings. With regard to antibiotic resistance determinants, S. hominis MBF12-19J showed the most favorable profile, S. warneri MBF02-19J and M. luteus MBF05-19J appeared suitable when used with appropriate caution, and B. subtilis MBF10-19J exhibited amoxicillin resistance, i.e., warrants careful evaluation. Further in vivo validation is needed to determine whether these strains do indeed comply with GRAS evaluation frameworks. Full article

Bacillus velezensis strain G2T39 is an endophytic bacterium previously isolated from Crotalaria retusa L., with evidenced biocontrol activity against Fusarium oxysporum f. sp. Cubense and Fusarium graminearum. In this study, it was shown that this strain also exhibited biocontrol activity against Colletotrichum gloeosporioides and Fusarium oxysporum f. sp. Vasinfectum, two important crop pathogens in tropical zones. Comprehensive phylogenetic and genomic analyses were performed to further characterize this strain. The genome of B. velezensis G2T39 consists of a single circular chromosome of 4,040,830 base pairs, with an average guanine–cytosine (GC) content of 46.35%. Both whole-genome-based phylogeny and average nucleotide identity (ANI) confirmed its identity as B. velezensis, being closely related to biocontrol and plant growth promotion Gram-positive model strains such as B. velezensis FZB42. Whole-genome annotation revealed 216 carbohydrate-active enzymes and 14 gene clusters responsible for secondary metabolite production, including surfactin, macrolactin, bacillaene, fengycin, bacillibactin, bacilysin, and difficidin. Genes involved in plant defense mechanisms were also identified. Additionally, G2T39 genome harbors multiple plant growth-promoting traits, such as genes associated with nitrogen metabolism (nifU, nifS, nifB, fixB, glnK) and a putative phosphate metabolism system (phyC, pst glpQA, ugpB, ugpC). Additional genes linked to biofilm formation, zinc solubilization, stress tolerance, siderophore production and regulation, nitrate reduction, riboflavin and nicotinamide synthesis, lactate metabolism, and homeostasis of potassium and magnesium were also identified. These findings highlight the genetic basis underlying the biocontrol capacity and plant growth-promoting properties of B. velezensis G2T39 and support its potential application as a sustainable bioinoculant in agriculture. Full article

Background: Comprehensive and accurate compound composition characterization in natural sources has high relevance in food and nutrition, health and medicine, environmental and agriculture research areas, though profiling of plant metabolites is a challenging task due to the structural complexity of natural products. This study delves into the identification and characterization of compounds within the Plantago genus, leveraging state-of-the-art analytical techniques. Methods: Utilizing an ultra-high-performance liquid chromatography (UHPLC) system in conjunction with Orbitrap™ IQ-X™ Tribrid™ mass spectrometer (MS), we employed a Phenyl-Hexyl HPLC column alongside optimized extraction protocols to analyze both husk and leaf samples. To maximize compound identification, we implemented data-dependent acquisition (DDA) methods including MS² (ddMS2), MS³ (ddMS3), AcquireX™ deep scan, and real-time library search (RTLS). Results: Our results demonstrate a significant increase in the number of putatively yet confidently assigned compounds, with 472 matches in P. lanceolata leaves and 233 in P. ovata husk identified through combined acquisition methods. The inclusion of an additional fragmentation level (MS³) noticeably enhanced the confidence in compound annotation, facilitating the differentiation of isomeric compounds. Furthermore, the application of low-energy fragmentation (10 normalized collision energy (NCE) for higher-energy collisional dissociation (HCD)) improved the detection and grouping of MS¹ fragments by 55% in positive mode and by 16% in negative mode, contributing to a more comprehensive analysis with minimal loss in compound identification. Conclusions: These advancements underscore the potential of our methodologies in expanding the chemical profile of plant materials, offering valuable insights into natural product analysis and dereplication of untargeted data. Full article

This multidisciplinary study investigates Piper rivinoides, a Brazilian medicinal species, focusing on its chemical composition and antimycobacterial potential. UHPLC-HRMS/MS of leaves, stems, branches, and roots revealed 58 compounds, including neolignans, lignanamides, triterpenes, flavonoids, and carotenoids. Fourteen metabolites, notably benzofuran neolignans and pentacyclic triterpenes are annotated here for the first time. Quantitative analyses by HPLC-DAD-UV showed that eupomatenoid-5, eupomatenoid-6, and conocarpan were most abundant in leaves, reaching amounts approximately twice those found in branches and stems and about ten times higher than in roots, supporting the optimal defense theory and organ-specific accumulation of bioactive metabolites. Biological assays against Mycobacterium tuberculosis strains H37Rv and M299 revealed strong inhibitory activity for the leaf extract and isolated neolignans. Eupomatenoid-5 and eupomatenoid-6 achieved inhibition comparable to rifampicin, with low MIC₅₀ values, while conocarpan exhibited moderate activity. Antimycobacterial effects were more pronounced against the H37Rv strain, although relevant inhibition was also observed for the hypervirulent M299 strain. These findings highlight P. rivinoides as a rich source of benzofuran neolignans and promising antimycobacterial properties. The integration of advanced mass spectrometric analyses with bioassays demonstrates the value of combining chemical and biological approaches to uncover novel natural products. The putative identification of new neolignans and triterpenes, along with the confirmation of potent antimycobacterial activity, provides a robust foundation for further studies on biosynthesis, structure–activity relationships, and potential biotechnological applications. Full article

Background/Objectives: Natural products containing hydroxyanthracene derivatives (HADs) such as Cascara (Rhamnus purshiana), Frangula (Rhamnus frangula), Rhubarb (Rheum palmatum), and Senna (Cassia angustifolia) have long been used for their laxative properties, but also raise safety concerns due to reported genotoxic and carcinogenic potential. Most studies have focused on quantifying HADs, whereas the broader secondary metabolite landscape of these herbal drugs remains underexplored. We aimed to generate an untargeted metabolomic fingerprint of these four species and to explore their chemical diversity using AI-based structural classification. Methods: Four commercial botanical raw materials were extracted with 60% methanol and analysed by UPLC–HRMS/MS in positive and negative ion modes. Features were processed in Compound Discoverer and annotated by accurate mass and MS/MS matching against spectral databases, then assigned to structural classes using a graph neural network classifier. Multivariate analyses (PCA, HCA) were used to compare metabolic patterns across species. Results: In total, 93, 83, 83 and 51 metabolites were annotated in cascara, frangula, rhubarb, and senna, respectively, spanning flavonoids, anthraquinones, phenylpropanoids and other classes. Only four flavonoids were shared by all species, indicating marked biochemical divergence. Several putatively species-enriched features were observed, including pavine in cascara and frangula, vicenin-2 in senna, and piceatannol in rhubarb. Senna displayed the most distinct metabolic profile, whereas cascara and frangula clustered closely. Conclusions: This work provides a chemistry-centred metabolomic fingerprint of four HAD-containing herbal drugs using graph-based neural networks for natural product classification, supporting future studies on the pharmacological potential, bioavailability and safety of their metabolites. Full article

As viromics advances, the diversity and ecological significance of RNA viruses in global ecosystems are gaining growing recognition. Nevertheless, studies on RNA viruses in wildlife, especially non-model avian species, are still relatively scarce. This study employed viral metagenomics to systematically characterize the gut RNA viromes of three widely distributed corvid species on the Qinghai–Tibet Plateau: the Red-billed chough (Pyrrhocorax pyrrhocorax), Daurian jackdaw (Coloeus dauuricus), and Rook (Corvus frugilegus). These three corvid species are closely associated with human-inhabited areas on the Qinghai–Tibet Plateau and display distinctive scavenging behaviors that may lower their exposure to environmental pathogens while concurrently elevating their risk of viral infection, rendering them key targets for viral surveillance and research into zoonotic disease transmission. The analysis annotated viral communities into 4 phyla and 8 classes, with Pisuviricota and Kitrinoviricota emerging as the predominant phyla in all samples. Alpha diversity analysis indicated no significant differences among groups, while beta diversity showed significant compositional differences. KEGG annotation revealed that enriched functional pathways were mainly concentrated in “Global and overview maps”, “Drug resistance: antimicrobial”, and “Biosynthesis of other secondary metabolites”. Furthermore, 4 antibiotic resistance genes and 13 putative virulence factor genes were identified. Phylogenetic analysis further indicated that several identified viruses have the potential for cross-species transmission, underscoring the pivotal role of wild birds in viral ecosystems and disease spread. This study uncovered multi-faceted features of the gut RNA viromes in the three crow species, spanning structural, functional, and evolutionary dimensions. These results offer novel perspectives on the viromes of wild corvids and their potential contributions to viral emergence and dissemination in the Qinghai–Tibet Plateau ecosystem. Full article

Bacillus cereus AS_3 and Bacillus cereus AS_5 are bacterial endophytes isolated from sterilized leaves of the medical plant Alectra sessiliflora, which were previously identified using 16S rRNA sequencing. Here, we present the whole-genome sequencing and annotation of strains AS_3 and AS_5, the first genome report of Bacillus cereus strains from A. sessiliflora. The genome of strain AS_3 has 59 contigs, 5 503 542 bp draft circular chromosome, an N₅₀ of 211,274 bp, and an average G+C content of 35.2%; whereas strain AS_5 has 38 contigs, 5,510,121 bp draft circular chromosome, an N₅₀ of 536,033 bp, and an average G+C content of 35.2%. A total of 5679 protein-coding genes, 62 genes coding for RNAs, and 122 pseudogenes in the strain AS_3 genome were identified by the National Center for Biotechnology Information Prokaryotic Annotation pipeline, whereas a total of 5688 gene protein-coding genes were identified in AS_5, with 60 genes coding for RNAs and 120 pseudogenes. Phenotypic analysis and whole-genome sequencing analysis showed that AS_3 and AS_5 share similar characteristics, including Gram-positive, motile, rod-shaped, and endospore-forming have shown a high sequence similarity with Bacillus cereus, type strain ATCC 14579^T. Strains AS_3 and AS_5 had genomic digital DNA–DNA hybridization (dDDH) with the type strain Bacillus cereus ATCC 14579^T of 85.8% and 86%, respectively, and average nucleotide identities (ANIs) of 98% and 98.01%, respectively. Phylogenomic analysis confirmed that strains AS_3 and AS_5 share very similar genomic and phenotypic characteristics, and are closely related to the type strain Bacillus cereus type strain ATCC 14579^T, supporting their classification within the Bacillus cereus species. A total of 10 secondary metabolite gene clusters, including siderophore type petrobactin, terpene type molybdenum cofactor, non-ribosomal peptide synthetase (NRPS) type bacillibactin, and β-lactone type fengycin, were predicted using AntiSMASH software (version 5.0). Putative genes potentially involved in bioremediation and endophytic lifestyle were identified in the genome analysis. Genome sequencing of Bacillus cereus AS_3 and Bacillus cereus AS_5 has provided genomic information and demonstrated potential biotechnological applications. Full article

Dapagliflozin, a sodium-glucose cotransporter 2 inhibitor, treats type 2 diabetes by blocking renal glucose reabsorption and promoting urinary glucose excretion. This mechanism lowers blood glucose concentrations independently of insulin. The resulting caloric loss also contributes to weight reduction. Although these effects are well documented in patients with diabetes, their magnitude and underlying mechanisms in healthy individuals remain poorly understood. Background/Objectives: We investigated metabolic alterations after a single 10 mg dose of dapagliflozin in healthy adults with normal body-mass indices (BMIs) using untargeted metabolomics. Methods: Thirteen healthy volunteers completed this study. Plasma was collected before and 24 h after dosing. Untargeted metabolic profiling was performed with ultra-high-performance liquid chromatography–quadrupole time-of-flight/mass spectrometry. Results: Twenty-five endogenous metabolites were annotated; ten were putatively identified. Eight metabolites increased significantly, whereas two decreased. Up-regulated metabolites included phosphatidylcholine (PC) species (PC O-36:5, PC 36:3), phosphatidylserine (PS) species (PS 40:2, PS 40:3, PS 36:1, PS 40:4), lysophosphatidylserine 22:1, and uridine. Dehydroepiandrosterone sulfate and bilirubin were down-regulated. According to the Human Metabolome Database, these metabolites participate in glycerophospholipid, branched-chain amino acid, pyrimidine, and steroid-hormone metabolism. Conclusions: Dapagliflozin may affect pathways related to energy metabolism and homeostasis beyond glucose regulation. These data provide a reference for future investigations into energy balance and metabolic flexibility in metabolic disorders. Full article

Bifidobacterium is a predominant probiotic in animals that is associated with host intestinal health. The protective mechanisms of the Bifidobacterium animalis (B. animalis) strain, specifically those related to functional gene–host interactions in intestinal homeostasis, remain poorly elucidated. This study reports the complete genome sequence and characterization of a B. animalis strain isolated from wild pig feces, which comprised a single circular chromosome (1,944,022 bp; GC content 60.49%) with 1567 protein-coding genes, and the B. animalis strain had certain acid resistance, bile salt resistance, gastrointestinal fluid tolerance, and antibacterial characteristics. Genomic annotation revealed three putative genomic islands and two CRISPR-Cas systems. Functional characterization identified genes encoding carbohydrate-active enzymes (CAZymes) and associated metabolic pathways, indicating that this strain can degrade complex dietary carbohydrates and synthesize bioactive metabolites for gut homeostasis. Although the antibiotic resistance genes were predicted, phenotypic assays demonstrated discordant resistance patterns, indicating complex regulatory networks. This study indicated the genomic basis of Bifidobacterium–host crosstalk in intestinal protection, providing a framework for developing novel probiotic interventions. Full article

In recent decades, heavy metal pollution has become a significant environmental stress factor. Plants are characterized by high biochemical plasticity and can adjust their metabolism to ensure survival under a changing environment. Here we report, to our knowledge, the first gas chromatography-mass spectrometry (GC-MS)-based metabolomics study of Zn-induced stress responses in Amaranthus caudatus plants. The study was performed with root and leaf aqueous methanolic extracts after their lyophilization and sequential derivatization with methoxylamine hydrochloride and N-methyl-N-(trimethylsilyl)trifluoroacetamide. In total, 419 derivatives were detected in the samples, and 144 of them could be putatively annotated. The metabolic shifts in seven-week-old A. caudatus plants in response to a seven-day treatment with 300 µmol/L ZnSO₄·7H₂O in nutrient solution were organ-specific and more pronounced in roots. Most of the responsive metabolites were up-regulated and dominated by sugars and sugar acids. The revealed effects could be attributed to the involvement of these metabolites in osmotic regulation, antioxidant protection and Zn²⁺ complexation. A 59-fold up-regulation of gluconic acid in roots distinctly indicated enhanced glucose oxidation due to oxidative stress upon the Zn treatment. Gluconic acid might be further employed in Zn²⁺ complexation. Pronounced Zn-induced up-regulation of salicylic acid in roots and shoots suggested a key role of this hormone in stress signaling and activation of Zn stress tolerance mechanisms. Overall, our study provides the first insight into the general trends of Zn-induced biochemical rearrangements and main adaptive metabolic shifts in A. caudatus. Full article

Colonization of plant tissues by bacterial endophytes might lead to qualitative and quantitative changes in secondary metabolites (SMs). In this work, in vitro co-culture experiments were performed using cell suspensions of the medicinal plant Alkanna tinctoria and eight of its bacterial endophytes. An untargeted metabolomics approach using Ultra-High-Performance Liquid Chromatography High-Resolution Mass Spectrometry (UHPLC-HRMS) was employed to investigate plant–microbe interactions. Hierarchical clustering analysis and principal component analysis highlighted significant modifications of specific regulation patterns in SM production, caused by bacterial endophytes. The annotation step lead to the identification of 32 stimulated compounds in A. tinctoria cell suspensions. Among them, 3′-hydroxy-14-hydroxyshikonofuran H (5), 8′-decarboxy-rosmarinic acid (18), 8‴-decarboxy-salvianolic B (23), 8″-8‴-didecarboxy-salvianolic acid B (26) were putatively identified for the first time. Our findings highlight that employing selected microbial inoculants under controlled conditions can be an effective strategy for enhancing or stimulating the production of specific high-value metabolites. Full article

Cyanobacterial blooms are becoming increasingly frequent and intense worldwide, often dominated by Microcystis aeruginosa, a species capable of producing a wide array of bioactive metabolites beyond microcystins. This study evaluates the ecotoxicological potential of a non-microcystin-producing strain, M. aeruginosa CCIBt3106, using acute immobilization assays with three microcrustacean species: Daphnia similis, Artemia salina, and Parhyale hawaiensis. Biomass was extracted using solvents of varying polarity, and selected extracts (aqueous and 50% methanol) were further fractionated and analyzed via high-resolution liquid chromatography–tandem mass spectrometry (HR-LC-MS/MS). Significant toxicity was observed in D. similis and P. hawaiensis, with EC₅₀ values ranging from 660 to 940 µg mL⁻¹. Metabolomic profiling revealed the presence of chemically diverse metabolite classes, including peptides, polyketides, and fatty acyls, with putative annotations linked to known bioactivities. These findings demonstrate that cyanobacterial strains lacking microcystins can still produce complex metabolite mixtures capable of inducing species-specific toxic effects under environmentally relevant exposure levels. Overall, the results highlight the need to expand ecotoxicological assessments and monitoring frameworks to include non-microcystin cyanobacterial metabolites and strains in water quality management. Full article

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. Full article

Background/Objectives: Liquid chromatography coupled with mass spectrometry (LC-MS) is a commonly used platform for many metabolomics studies. However, metabolite annotation has been a major bottleneck in these studies in part due to the limited publicly available spectral libraries, which consist of tandem mass spectrometry (MS/MS) data acquired from just a fraction of known compounds. Application of deep learning methods is increasingly reported as an alternative to spectral matching due to their ability to map complex relationships between molecular fingerprints and mass spectrometric measurements. The objectives of this study are to investigate deep learning methods for molecular fingerprint based on MS/MS spectra and to rank putative metabolite IDs according to similarity of their known and predicted molecular fingerprints. Methods: We trained three types of deep learning methods to model the relationships between molecular fingerprints and MS/MS spectra. Prior to training, various data processing steps, including scaling, binning, and filtering, were performed on MS/MS spectra obtained from National Institute of Standards and Technology (NIST), MassBank of North America (MoNA), and Human Metabolome Database (HMDB). Furthermore, selection of the most relevant m/z bins and molecular fingerprints was conducted. The trained deep learning models were evaluated on ranking putative metabolite IDs obtained from a compound database for the challenges in Critical Assessment of Small Molecule Identification (CASMI) 2016, CASMI 2017, and CASMI 2022 benchmark datasets. Results: Feature selection methods effectively reduced redundant molecular and spectral features prior to model training. Deep learning methods trained with the truncated features have shown comparable performances against CSI:FingerID on ranking putative metabolite IDs. Conclusion: The results demonstrate a promising potential of deep learning methods for metabolite annotation. Full article

Wild soybean, which has many desirable traits, such as adaptability to climate change-related stresses, is a valuable resource for expanding the narrow genetic diversity of cultivated soybeans. Plants require roots to adapt to different environments and optimize water and nutrient uptake to support growth and facilitate the storage of metabolites; however, it is challenging and costly to evaluate root traits under field conditions. Previous studies of quantitative trait loci (QTL) have been mainly based on cultivated soybean populations. In this study, an interspecific mapping population from a cross between wild soybean ‘PI483463’ and cultivar ‘Hutcheson’ was used to investigate QTLs associated with root traits using image data. Our results showed that 39 putative QTLs were distributed across 10 chromosomes (chr.). Seventeen of these were clustered in regions on chr. 8, 14, 15, 16, and 17, accounting for 19.92% of the phenotypic variation. We identified five significant QTL clusters influencing root-related traits, such as total root length, surface area, lateral total length, and number of tips, across five chr., with favorable alleles from both wild and cultivated soybeans. Furthermore, we identified eight candidate genes controlling these traits based on functional annotation. These genes were highly expressed in root tissues and directly or indirectly affected soybean root growth, development, and stress responses. Our results provide valuable insights for breeders aiming to optimize soybean root traits and leveraging genetic diversity from wild soybean species to develop varieties with improved root morphological traits, ultimately enhancing overall plant growth, productivity, and resilience. Full article