Search Results (844)

Fungal lytic polysaccharide monooxygenases (LPMOs) have revolutionized the field of biomass degradation by introducing an oxidative mechanism that complements traditional hydrolytic enzymes. These copper-dependent enzymes catalyze the cleavage of glycosidic bonds in recalcitrant polysaccharides such as cellulose, hemicellulose, and chitin, through the activation of molecular oxygen (O₂) or hydrogen peroxide (H₂O₂). Their catalytic versatility is intricately modulated by structural features, including the histidine brace active site, surface-binding loops, and, in some cases, appended carbohydrate-binding modules (CBMs). The oxidation pattern, whether at the C1, C4, or both positions, is dictated by subtle variations in loop architecture, amino acid microenvironments, and substrate interactions. LPMOs are embedded in a highly synergistic fungal enzymatic system, working alongside cellulases, hemicellulases, lignin-modifying enzymes, and oxidoreductases to enable efficient lignocellulose decomposition. Industrial applications of fungal LPMOs are rapidly expanding, with key roles in second-generation biofuels, biorefineries, textile processing, food and feed industries, and the development of sustainable biomaterials. Recent advances in genome mining, protein engineering, and heterologous expression are accelerating the discovery of novel LPMOs with improved functionalities. Understanding the balance between O₂- and H₂O₂-driven mechanisms remains critical for optimizing their catalytic efficiency while mitigating oxidative inactivation. As the demand for sustainable biotechnological solutions grows, this narrative review highlights how fungal LPMOs function as indispensable biocatalysts for the future of the Circular Bioeconomy and green industrial processes. Full article

During the course of genome mining initiatives, we identified a marine-derived Micromonospora, assigned here as strain WMMD956; the genome of WMMD956 appeared to contain a number of features associated with everninomicins, well-known antimicrobial orthosomycins. In addition, LCMS-based hierarchical clustering analysis and principal component analysis (hcapca) revealed that WMMD956 displayed an extreme degree of metabolomic and genomic novelty. Dereplication of high-resolution tandem mass spectrometry (HRMS/MS) and Global Natural Product Social molecular networking platform (GNPS) analysis of WMMD956 resulted in the identification of several analogs of the previously known everninomicin. Chemical structures were unambiguously confirmed by HR-ESI-MS, 1D and 2D NMR experiments, and the use of MS/MS data. The isolated metabolites, 1–3, were evaluated for their antibacterial activity against methicillin-resistant Staphalococcus aureus (MRSA). Full article

Prolonged expression of gene-editing components in CRISPR-modified plants can interfere with phenotypic analysis of target traits, increase the risk of off-target mutations, and lead to unnecessary metabolic burden. To mitigate these issues in peanut (Arachis hypogaea L.), callus-specific promoters were screened to restrict Cas9 expression to the callus stage, minimizing its activity in regenerated plants. In this study, six callus-specific genes in peanut were identified by mining RNA sequencing datasets and validating their expression profiles using quantitative reverse transcriptase PCR. The promoters of Arahy.H0FE8D, Arahy.WT3AEF, Arahy.I20Q6X, Arahy.ELJ55T, and Arahy.N9CMH4 were cloned and assessed for their expression activity. Beta-glucuronidase (GUS) histochemical staining confirmed that all five promoters were functional in peanut callus. Further investigation revealed their ability to drive cytosine base editing via a deaminase-nCas9 fusion protein, with all promoters successfully inducing precise base substitutions in peanut. Notably, P_Ah-H0FE8D, P_Ah-WT3AEF, P_Ah-ELJ55T, and P_Ah-N9CMH4 exhibited comparable or higher editing efficiencies than the commonly used cauliflower mosaic virus 35S promoter. These findings provide valuable tools for improving the biosafety of CRISPR-based genome editing in peanut breeding programs. Full article

The goal of this study is to develop an efficient machine learning framework for designing high-hardness multi-metal nitride coatings, overcoming the limitations of traditional trial-and-error methods. The development of multicomponent metal nitride hard coatings via multi-arc ion plating remains a significant challenge due to the vast compositional search space. Although theoretical studies in macroscopic, mesoscopic, and microscopic domains exist, these often focus on idealized models and lack effective coupling across scales, leading to time-consuming and labor-intensive traditional methods. With advancements in materials genomics and data mining, machine learning has become a powerful tool in material discovery. In this work, we construct a compositional search space for multicomponent nitrides based on electronic configuration, valence electron count, electronegativity, and oxidation states of metal elements in unary nitrides. The search space is further constrained by FCC crystal structure and hardness theory. By incorporating a feature library with micro-, meso-, and macro-structural characteristics and using clustering analysis with theoretical intermediate variables, the model enriches dataset information and enhances predictive accuracy by reducing experimental errors. This model is successfully applied to design multicomponent metal nitride coatings using a literature-derived database of 233 entries. Experimental validation confirms the model’s predictions, and clustering is used to minimize experimental and data errors, yielding a strong agreement between predicted optimal molar ratios of metal elements and nitrogen and measured hardness performance. Of the 100 Vickers hardness (HV) predictions made by the model using input features like molar ratios of metal elements (e.g., Ti, Al, Cr, Zr) and atomic size mismatch, 82 exceeded the dataset’s maximum hardness, with the best sample achieving a prediction accuracy of 91.6% validated against experimental measurements. This approach offers a robust strategy for designing high-performance coatings with optimized hardness. Full article

Hyaluronic acid (HA) is a key extracellular matrix component of vertebrates, where it mediates cell adhesion, immune regulation, and tissue remodeling through its interaction with specific receptors. Although HA has been detected in a few invertebrate species, the lack of fundamental components of the molecular HA pathway poses relevant objections about its functional role in these species. Mining genomic and transcriptomic data, we considered the conservation of the gene locus encoding for the extracellular link protein (XLINK) in marine mussels as well as its expression patterns. Structural and phylogenetic analyses were undertaken to evaluate possible similarities with vertebrate orthologs and to infer the origin of this gene in invertebrates. Biochemical analysis was used to quantify HA in tissues of Mytilus galloprovincialis. As a result, we confirm that the mussel can produce HA (up to 1.02 ng/mg in mantle) and that its genome encodes two XLINK gene loci. These loci are conserved in Mytilidae species and show a complex evolutionary path. Mussel XLINK genes appeared to be expressed during developmental stages in three mussel species, ranking in the top 100 expressed genes in M. trossulus at 17 h post-fertilization. In conclusion, the presence of HA and an active gene with the potential to bind HA suggests that mussels have the potential to synthesize and use HA and are among the few invertebrates encoding this gene. Full article

Background: Glioblastoma (GBM) is one of the most challenging malignancies in all of neoplasms. These malignancies are associated with unfavorable clinical outcomes and significantly compromised patient wellbeing. The immunological landscape within the tumor microenvironment (TME) plays a critical role in determining GBM prognosis. By mining data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and correlating them with immune responses in the TME, genes associated with the immune microenvironment with potential prognostic value were obtained. Method: We selected GSE16011 as the training set. Gene expression profiles were substrates scored by both ESTIMATE and xCell, and immune cell subpopulations in GBM were analyzed by CIBERSORT. Gene expression profiles associated with low immune scores were performed by lasso regression, Cox analysis and random forest (RF) to identify a prognostic model for the multiple genes associated with immune infiltration in GBM. Then we constructed a nomogram to optimize the prognostic model using GSE7696 and TCGA-GBM as validation sets and evaluated these data for gene mutation and gene enrichment analysis. Result: The prognostic correlation between the six genes (MEOX2, PHYHIP, RBBP8, ST18, TCF12, and THRB) and GBM was finally found by lasso regression, Cox regression, and RF, and the online database obtained that all six genes were differentially expressed in GBM. Therefore, a prognostic correlation model was constructed based on the six genes. Kaplan–Meier (KM) survival analysis showed that this prognostic model had excellent prognostic ability. Conclusions: Prognostic models based on tumor microenvironment and immune score stratification and the construction of related genes have potential applications for prognostic analysis of GBM patients. Full article

Uncaria rhynchophylla, a medicinal plant extensively used in traditional Chinese medicine, is an important plant source of terpenoid indole alkaloids (TIAs), but the mechanism of TIA biosynthesis at molecular level remains unclear. Geraniol synthase (GES) serves as a crucial enzyme in catalyzing the formation of geraniol from geranyl pyrophosphate (GPP) in various plants, but the functional characterization of the GES gene in U. rhynchophylla has not been investigated. In this study, a GES was identified and characterized through genome mining and bioinformatic analysis. Functional validation was performed via a protein catalysis experiment, transient expression in Nicotiana benthamiana, and methyl jasmonate (MeJA) induction experiments. The full-length UrGES gene was 1761 bp, encoding a protein product of 586 amino acids with an estimated 67.5 kDa molecular weight. Multiple sequence alignments and phylogenetic analysis placed UrGES within the terpene synthase g (TPS-g) subfamily, showing high similarity to known GESs from other plants. Enzymatic assays confirmed that recombinant UrGES catalyzed GPP conversion to a single product of geraniol. The transient expression of UrGES resulted in geraniol accumulation in N. benthamiana, further confirming its function in vivo. UrGES expression was observed in leaves, stems, and roots, where leaves had the highest transcript levels. Moreover, MeJA treatment significantly upregulated UrGES expression, which positively correlated with an increase in alkaloid content. This study functionally characterizes UrGES as a geraniol synthase in U. rhynchophylla, contributing to the current knowledge of the TIA biosynthetic pathway. These findings may offer insights for future metabolic engineering aiming to enhance TIA yields for pharmaceutical and industrial applications. Full article

Anaerobes, the oldest evolutionary life forms, have been unexplored for their potential to produce secondary metabolites due to the difficulties observed in their cultivation. Antimicrobials derived from anaerobic bacteria are an emerging and valuable source of novel therapeutic agents. The urgent need for new antimicrobial agents due to rising antibiotic resistance has prompted an investigation into anaerobic bacteria. The conventional method of antimicrobial discovery is based on cultivation and extraction methods. Antibacterial and antifungal substances are produced by anaerobic bacteria, but reports are limited due to oxygen-deficient growth requirements. The genome mining approach revealed the presence of biosynthetic gene clusters involved in various antimicrobial compound synthesis. Thus, the current review is focused on antimicrobials derived from anaerobes to unravel the potential of anaerobic bacteria as an emerging valuable source of therapeutic agents. These substances frequently consist of peptides, lipopeptides, and other secondary metabolites. Many of these antimicrobials have distinct modes of action that may be able to go around established resistance pathways. To this effect, we discuss diverse antimicrobial compounds produced by anaerobic bacteria, their biosynthesis, heterologous production, and activity. The findings suggest that anaerobic bacteria harbor significant biosynthetic potential, warranting further exploration through recombinant production for developing new antibiotics. Full article

The ongoing threat of antimicrobial-resistant pathogens has intensified the need for new antimicrobial agents, making the discovery of novel natural products crucial. This study focuses on the isolation and characterization of a novel Streptomyces species from the Anjar region in Lebanon, an area rich in microbial diversity that is largely unexplored for its biotechnological potential. Soil samples were collected and processed, leading to the isolation of Streptomyces strain ANJ10. Comprehensive morphological, physiological, and genomic analyses were conducted, including whole-genome sequencing (WGS) to identify biosynthetic gene clusters (BGCs) and broth microdilution (BMD) assays to evaluate antimicrobial activity. The ANJ10 genome revealed 42 BGCs, significantly more than the average number in Streptomyces species, suggesting a high potential for secondary metabolite production. Phylogenetic analysis confirmed ANJ10 as a novel species, and BMD assays demonstrated its strong antimicrobial activity against several gram-negative pathogens, specifically, Acinetobacter baumannii. These findings underscore the potential of this strain as a significant source of new antimicrobial compounds, reinforcing the importance of exploring underexploited environments like Lebanon for microbial bioprospecting. Full article

A novel actinobacterial strain, designated E54^T, was isolated from a hyper-arid desert soil sample collected from the Kumtagh Desert in Dunhuang, Gansu Province, China. Phylogenetic analysis based on 16S rRNA gene sequences placed strain E54^T within the genus Lentzea, showing highest similarity to Lentzea waywayandensis DSM 44232^T (98.9%) and Lentzea flava NBRC 15743^T (98.5%). However, whole-genome comparisons revealed that the average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between E54^T and these related strains were below the thresholds for species delineation. Strain E54^T exhibited typical morphological characteristics of the genus Lentzea, forming a branched substrate. It grew optimally at 28–30 °C, pH 7.0–9.0, and tolerated up to 10% NaCl. The cell wall contained meso-diaminopimelic acid, the predominant menaquinone was MK-9(H₄), and major fatty acids included iso-C_16:0. The polar lipid profile comprised diphosphatidyl glycerol, phosphatidyl ethanolamine, phosphatidyl inositol, hydroxyphosphatidyl ethanolamine, and an unidentified lipid. The characteristic amino acid type of the cell wall was meso-DAP. Whole-cell hydrolysis experiments revealed the characteristic cell wall sugar fractions: ribose and galactose. The genome of strain E54^T is approximately 8.0 Mb with a DNA G+C content of 69.38 mol%. Genome mining revealed 39 biosynthetic gene clusters (BGCs), including non-ribosomal peptide synthetases (NRPS), polyketide synthases (PKS), terpenes, and siderophores. Comparative antiSMASH-based genome analysis across 38 Lentzea strains further demonstrated the genus’ remarkable biosynthetic diversity. NRPS and type I PKS (T1PKS) were the most prevalent BGC types, indicating a capacity to synthesize structurally complex and pharmacologically relevant metabolites. Together, these findings underscore the untapped biosynthetic potential of the genus Lentzea and support the proposal of strain E54^T as a novel species. The strain E54^T (=JCM 34936^T = GDMCC 4.216^T) should represent a novel species, for which the name Lentzea xerophila sp. nov. is proposed. Full article

Strain 53B2 was isolated from a commercial maize (Zea mays L.) field located in the Yaqui Valley, Mexico. Its draft genome comprises 5,844,085 bp, with a G + C content of 37.5%, an N50 of 602,122 bp, an L50 of 4, and a total of 129 contigs. Genome-based taxonomic affiliation showed this strain belonged to Priestia megaterium. Genome annotation revealed 6394 coding DNA sequences (CDSs), organized into 332 subsystems. Among these, several CDSs were associated with traits relevant to plant growth promotion, including categories such as iron acquisition and metabolism (40 CDSs) and secondary metabolism (6 CDSs), among others. In vitro metabolic assays supported genomic predictions, confirming the strain’s ability to produce IAA, solubilize phosphate, and tolerate abiotic stress. Additionally, greenhouse trials demonstrated that inoculation with Priestia megaterium 53B2 significantly enhanced plant growth parameters (p ≤ 0.05) versus uninoculated control: stem height increased by 22.8%, root length by 35.7%, stem and root fresh weights by 39.6% and 66.1%, and stem and root dry weights by 33.7% and 44.7%, respectively. This first report on the beneficial potential of Priestia megaterium 53B2 highlights its potential as a sustainable bioinoculant for maize cultivation. Full article

The discovery of new microbial metabolites is essential to combat the alarming rise in antimicrobial resistance and to meet emerging medical needs. This work critically reviews current strategies for identifying antimicrobial compounds, emphasizing the potential of microorganisms as a rich source of bioactive secondary metabolites. This review explores innovative methods, such as investigating extreme environments where adverse conditions favor the emergence of unique metabolites; developing techniques, like the iChip, to cultivate previously uncultivable bacteria; using metagenomics to analyze complex samples that are difficult to isolate; and integrates artificial intelligence to accelerate genomic mining, structural prediction, and drug discovery optimization processes. The importance of overcoming current challenges, such as replicating findings, low research investment, and the lack of adapted collection technologies, is also emphasized. Additionally, this work analyzes the crucial role of bacterial resistance and the necessity of a holistic approach involving new technologies, sustained investment, and interdisciplinary collaboration. This work emphasizes not only the current state of metabolite discovery but also the challenges that must be addressed to ensure a continuous flow of new therapeutic molecules in the coming decades. Full article

Background/Objectives: The neurotrophic tropomyosin receptor kinase (NTRK) genes NTRK1, NTRK2, and NTRK3 encode tyrosine kinase receptors, and their fusion genes are known as the oncogenic driver genes for cancer. This study aimed to compare the diagnostic ability of NTRK fusion among five types of multi-cancer genome profiling tests (multi-CGP tests) and determine a useful multi-CGP test for NTRK fusion, recorded in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database in Japan. This study aimed to compare the diagnostic results for NTRK fusions among the five different CGP tests. Methods: A total of 88,688 tumor cases were enrolled in the C-CAT profiling database from 2019 to 2024. The detection frequency of NTRK fusion genes was compared to the results for five multi-CGP tests: NCC Oncopanel, FoundationOne CDx (F1), FoundationOne Liquid (F1L), GenMineTOP (GMT), and Guardant360. Results: NTRK fusion genes were detected in 175 (0.20%) of the 88,688 total cases. GMT, which is equipped with RNA sequencing function, frequently detected NTRK fusion genes (20 of 2926 cases; 0.68%) in comparison with the other four multi-CGP tests that do not have RNA sequencing analysis. GMT showed significantly (p < 0.05) higher diagnostic ability for NTRK fusions compared with the other four multi-CGP tests. Especially, NTRK2 fusion was significantly (p < 0.001) more highly determined by GMT than it was by the other four multi-CGP tests. The detection rates for FGFR1 and FGFR3 were significantly higher in GMT than in other multi-CGP tests. In contrast, the detection rates of the ALK and RET fusion genes were significantly higher in F1L. Conclusions: GMT, which is equipped with RNA sequencing analysis, might show a useful diagnostic ability for NTRK fusions, especially for NTRK2 fusion genes. Full article

Staphylococcus pseudintermedius, an opportunistic pathogen of veterinary and zoonotic concern, harbors diverse biosynthetic gene clusters (BGCs) that may contribute to its ecological fitness and virulence. In this study, we performed a comparative genomic analysis of 6815 S. pseudintermedius isolates. Using Roary, we identified core and accessory genomes, revealing the subtilosin A gene (sboA) as part of the accessory genome, present in a subset of S. pseudintermedius isolates from clinical (n = 657), environmental (n = 1031), and unclassified sources (n = 487). AntiSMASH v8.0.0 analysis confirmed the presence of subtilosin A BGCs annotated as a sactipeptide with low similarity confidence to Bacillus subtilis subsp. spizizenii ATCC 6633 subtilosin A cluster. Further characterization using BAGEL4 identified multiple genes homologous to the Bacillus subtilis subtilosin A biosynthetic machinery (sbo-albABCDEFG), although albB, albG, and sboX were not annotated, raising questions about cluster completeness and functionality. BLAST v2.12.0 analysis of the full BGC identified by BAGEL4, revealing high conservation (99.6–100% pairwise identity) of gene content and order in 395 clinical, 593 environmental, and 417 unclassified S. pseudintermedius isolates. Incomplete clusters were identified in 763 clinical, 942 environmental, and 201 unclassified S. pseudintermedius isolates. The discrepancy between the number of isolates containing sboA and those harboring the full cluster may reflect evolutionary divergence or could be attributed to limitations in assembly quality. The functional implications of the identified cluster in S. pseudintermedius remain to be elucidated; however, its potential role in conferring competitive fitness by inhibiting closely related species is supported by previous findings in other staphylococci. Full article

Spore-forming Bacilli have been explored due to their potential biotechnological features and applications in human health and functional food research. This study focuses on the genetic and phenotypical characterization of the functional probiotic properties of Bacillus velezensis P45, a strain isolated from fish intestines. B. velezensis P45 exhibited antimicrobial activity against Gram-positive and Gram-negative pathogens and demonstrated strong autoaggregation and biofilm formation properties in vitro. The strain also showed tolerance to gastrointestinal conditions and ability to metabolize and adhere to mucin. In silico analysis confirmed the absence of virulence factors and antibiotic resistance genes, reinforcing its safety as a probiotic candidate. Genome mining revealed the presence of genes related to adhesion, such as fibronectin-binding protein and enolases, and for the synthesis of secondary metabolites, including the antimicrobial lipopeptides fengycin, surfactin, and bacillibactin. In addition, phylogenetic comparison using the yloA (rqcH) gene associated with gut adhesion clustered strain P45 with other probiotic Bacillus and B. velezensis strains, while separating it from pathogenic bacteria. Thus, the strain B. velezensis P45 could be a valuable candidate as a probiotic due to its functional properties and safety. Full article