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At least 19 recordsLinked to original sources

PubMed2026

In silico genome mining and characterization of putative horse feces-derived bacterial phytases as potential monogastric animal feed additive candidates.

Phytic acid exerts a significant antinutritional effect in poultry, swine, and fish, which can be mitigated by supplementing monogastric feeds with efficient microbial phytases. Accordingly, mining bacterial genomes for novel phytases represents a strategic computational approach to identifying candidates for improving monogastric animal nutrition. In this study, 162 bacterial genomes associated with horse feces were systematically mined using an in silico pipeline to identify and characterize putative phytases.A total of 69 non-redundant sequences were identified and classified as histidine acid phytase (HAPhy) or protein tyrosine phosphatase-like phytase (PTPLPhy). HAPhys were detected in the genomes of Escherichia coli, Klebsiella pneumoniae, Salmonella enterica, Acinetobacter baumannii, and Cutibacterium equinum, whereas PTPLPhys were found in K. pneumoniae, Limosilactobacillus reuteri, Pediococcus acidilactici, Bifidobacterium pseudolongum, and Prescottella equi. Principal component analysis identified glucose-1-phosphatase (CAJ1242485.1) and bifunctional acid phosphatase (NHR17779.1) as the HAPhy candidates exhibiting the most favorable predicted physicochemical properties for potential feed applications. Similarly, among the PTPLPhys, protein tyrosine phosphatase (UNQ40438.1) and a hypothetical protein (CAJ1246072.1) showed the most favorable computational profiles. Biosafety analysis identified potential virulence factors, indicating that sources should be screened prior to feed application. High-quality AlphaFold2 models were obtained for these phytases (90.9-97.2). Molecular docking analysis showed that NHR17779.1 exhibited the strongest binding to phytic acid, whereas CAJ1246072.1 demonstrated the weakest interaction. Overall, this study identifies the horse fecal microbiota as a diverse source of putative phytases that may serve as promising targets for genetic and protein engineering; however, further in vitro and in vivo studies are essential to validate the enzymatic activity and industrial efficacy of these computational candidates.

Bacterial phytase↗

PubMed2025

Genome mining based on transcriptional regulatory networks uncovers a novel locus involved in desferrioxamine biosynthesis.

Bacteria produce a plethora of natural products that are in clinical, agricultural and biotechnological use. Genome mining has uncovered millions of biosynthetic gene clusters (BGCs) that encode their biosynthesis, the vast majority of them lacking a clear product or function. Thus, a major challenge is to predict the bioactivities of the molecules these BGCs specify, and how to elicit their expression. Here, we present an innovative strategy whereby we harness the power of regulatory networks combined with global gene expression patterns to predict BGC functions. Bioinformatic analysis of all genes predicted to be controlled by the iron master regulator DmdR1 combined with co-expression data, led to identification of the novel operon desJGH that plays a key role in the biosynthesis of the iron overload drug desferrioxamine (DFO) B in Streptomyces coelicolor. Deletion of either desG or desH strongly reduces the biosynthesis of DFO B, while that of DFO E is enhanced. DesJGH most likely act by changing the balance between the DFO precursors. Our work shows the power of harnessing regulation-based genome mining to functionally prioritize BGCs, accelerating the discovery of novel bioactive molecules.

Deferoxamine↗

PubMed2025

Seq2Saccharide: Discovering Oligosaccharides and Aminoglycosides Natural Products by Integrating Computational Mass Spectrometry and Genome Mining.

Natural oligosaccharides and aminoglycosides are important sources of new drug candidates, especially in the development of antibiotics. In the past, discovering novel saccharides has been time-consuming and costly. However, the rapid expansion of high-throughput data, including genomic and mass spectrometry data sets, has greatly increased opportunities for natural saccharide discovery. Yet, due to the complex biosynthesis pathways of saccharides, no existing method can predict their structures with high precision. To address this, we introduce Seq2Saccharide, a tool designed to automate saccharide natural product discovery by integrating both genomic and mass spectrometry data. To enhance accuracy, Seq2Saccharide predicts hundreds or thousands of putative structures for each gene cluster. The correct structure is then identified from these predictions using a mass spectral search. Benchmarks against saccharides in the MiBIG database show that Seq2Saccharide outperforms existing methods in predicting the structure of saccharides. Furthermore, mass spectrometry analysis indicates that the variable search module can correct mispredictions from genome mining. By searching genomic and mass spectrometry data of microbial strains, Seq2Saccharide correctly identified the biosynthetic gene cluster for the polysaccharide oligosaccharide trestatin B.

Aminoglycosides↗

PubMed2026

Genome mining and metabolomics unveil new napyradiomycin antibiotics from Streptomyces sp. 0H2M.

Napyradiomycins are a family of meroterpenoid natural products known for their promising antibiotic activities. In this study, four new napyradiomycins derivatives were identified, SF2415B4 (1), SF2415B5 (2), SF2415B6 (3), and SF2415B7 (4) from Streptomyces sp. 0H2M, alongside a known molecule, A80915A (5) through the synergy between genome mining and metabolomics analysis. Their structures were elucidated through a combination of spectroscopic and spectrometric analyses, including HRMS-ESI, NMR, and DP4+. Genome sequencing identified a putative biosynthetic gene cluster, and subsequent analyses revealed a distinct biosynthetic pathway with an unprecedented tailoring mechanism mediated by novel hydroxylases and halogenases. Biological assays demonstrated significant activity against Bacillus subtilis, Bacillus cereus and methicillin-resistant Staphylococcus aureus due to perturbation of cell membrane integrity, and minimum inhibitory concentration (MIC) values ranged from 0.24 to 30.7 μM. Additionally, in vitro cytotoxicity experiments indicated that compounds 2-5 very mildly inhibited the viability of human non-small cell lung cancer (NSCLC) cell line A549 in a concentration-dependent manner, with IC50 values of 16.7, 39.1, 65.0, and 32.8 μM, respectively. Moreover, they were shown to induce apoptosis and autophagy in A549 cells, evidenced by increased levels of cleaved PARP, decreased expression of anti-apoptotic proteins (Bcl-2, Bcl-xL, and Survivin), and accumulation of LC3-II. These findings offer new insights into the natural product chemistry in Streptomyces and the pharmacology of napyradiomycin class antibiotics.

Streptomyces↗

PubMed2026

Integration of genome mining and HiTES reveals secondary metabolic potential in marine-derived Aspergillus sp. WHUF0304.

AIMS: Marine-derived Aspergillus species are prolific producers of bioactive secondary metabolites, yet the majority of their biosynthetic gene clusters (BGCs) remain silent. This study aimed to integrate genome mining with high-throughput elicitor screening (HiTES) to unlock the metabolic potential of Aspergillus sp. WHUF0304 and identify elicitors that promote the accumulation of previously undetected metabolites. METHODS AND RESULTS: A high-quality genome of Aspergillus sp. WHUF0304 was assembled and annotated using multiple functional databases, revealing substantial secondary metabolic potential. antiSMASH analysis identified diverse BGCs, including NRPS/indole-related clusters potentially associated with indole diketopiperazine biosynthesis. A HiTES-inspired elicitor screening strategy was then applied to evaluate 42 small molecules for their ability to alter the metabolite profile of this strain. Among the tested elicitors, fluconazole was identified as the optimal inducer, triggering the production of several indole diketopiperazine-related differential metabolites. Subsequent activity-guided isolation led to the identification of a bioactive indole diketopiperazine dimer, cristatumin E, which exhibited antibacterial activity against Escherichia coli and Bacillus subtilis with minimum inhibitory concentrations (MICs) of 32 µg mL-1 and 256 µg mL-1, respectively. CONCLUSIONS: These findings demonstrate that integrating genomic and functional approaches effectively activates silent BGCs in marine fungi. The fluconazole-associated accumulation and subsequent isolation of cristatumin E, a bioactive indole diketopiperazine dimer, highlight the potential of elicitor-mediated activation to expand the detectable metabolite profile of Aspergillus sp. WHUF0304.

Aspergillus↗

PubMed2026

Genome mining reveals an architecturally expanded pyoluteorin-associated biosynthetic gene cluster and a divergent flavin-dependent halogenase-like sequence in deep-sea Pseudomonas Aeruginosa from the Gulf of Guinea.

BACKGROUND: Marine deep-sea environments harbour microorganisms with extraordinary biosynthetic potential, yet their secondary metabolite repertoires remain largely uncharacterised. RESULTS: This study reports the isolation, phenotypic characterisation, and whole-genome analysis of Pseudomonas aeruginosa strain E1, recovered from deep Atlantic seawater (Gulf of Guinea, ~2500 m depth), which exhibits antifungal activity against multidrug-resistant Candida parapsilosis. Three presumptive P. aeruginosa isolates (E1, E17, and E44) showed > 99% 16S rRNA gene sequence identity to P. aeruginosa reference sequences, while whole-genome dDDH analysis of strain E1 yielded 95.2% (95% CI: 93.6-96.4%; formula d4) relative to the P. aeruginosa type strain DSM 50071ᵀ (= ATCC 10145ᵀ), supporting its species-level assignment. Antifungal screening and PCR-based detection of flavin-dependent halogenase genes identified strain E1 as the primary candidate for genomic investigation. Illumina whole-genome sequencing produced a 6.33 Mb draft genome assembly (113 contigs, 5862 protein-coding genes, 66.4% GC content). Genome mining with antiSMASH 8.0 identified 27 biosynthetic gene clusters (BGCs) spanning nonribosomal peptide synthetase (NRPS), polyketide synthase (PKS), phenazine, terpene, and metallophore pathways. Region 7.1 of strain E1 harbours a predicted 50.8 kb pyoluteorin-associated BGC, comprising 34 genes, substantially larger than its terrestrial counterpart (~ 22 kb, ~ 17 genes), and featuring nine transport genes and three regulatory elements. Phylogenetic analysis resolved three halogenase genes: ctg7_146 showed 98.7% amino acid identity to PltA, and ctg7_149 showed 99.2% amino acid identity to PltM, supporting their annotation as PltA-like and PltM-like components of the predicted pyoluteorin biosynthetic pathway. Among the characterised reference enzymes included in this analysis, ctg7_143 showed the highest amino acid identity to PltM from P. fluorescens Pf-5. However, the identity remained low at approximately 30.4%, supporting its placement as a divergent FDH-like sequence rather than a close PltM orthologue. CONCLUSION: This study provides the first comprehensive genomic characterisation of a pyoluteorin-BGC-harbouring marine P. aeruginosa strain, demonstrating conservation of the core biosynthetic machinery alongside an expanded transport architecture and a divergent FDH-like sequence that may represent a candidate for future biochemical investigation. These findings expand current knowledge of FDH-like sequence diversity in deep-sea bacteria and support further investigation of Gulf of Guinea microorganisms as a potential source of biosynthetic and enzymatic diversity.

Multigene Family↗

PubMed2026

Discovery of Glycosylated β-Amino Acid-Containing Macrolactams from Nonomuraea sp. 0L2P via Genome Mining.

β-Amino acid-containing macrolactams (β-AACMs) are a class of bioactive natural products characterized by nitrogen-containing starter units within polyketide-derived macrocycles. Here, we report four previously undescribed macrolactams, gruelactams A-D (1-4), from Nonomuraea sp. 0L2P, discovered through an integrated approach combining genome mining, 15N-labeling, and antibacterial screening. Their planar structures were elucidated by comprehensive spectroscopic analyses, including 1D and 2D NMR and HRESI-MS, and their configurations were partially assigned based on ROESY data and bioinformatic analysis. Genome sequencing and antiSMASH analysis identified a putative type I polyketide synthase (PKS) biosynthetic gene cluster, enabling the proposal of a biosynthetic pathway. Bioactivity assays showed that gruelactam D (4) exhibits antibacterial activity against Bacillus cereus and Staphylococcus aureus, with MIC values of 8 and 16 μg/mL, respectively. These findings expand the chemical diversity of β-AACMs and demonstrate the utility of genome-guided approaches for discovering bioactive natural products from rare actinomycetes.

Anti-Bacterial Agents↗

PubMed2026

Computational mass spectrometry and genome mining guided discovery of metallophores produced by Microbulbifer.

Iron is an essential component of cellular biology. Thus, iron's low bioavailability is a key evolutionary pressure guiding microbial dynamics in the marine environment. Among marine bacteria, Microbulbifer is a chemically underexplored and functionally versatile bacterial genus, which is commonly associated with sponges, algae, corals, and sediments. Previously, genome analyses have revealed that Microbulbifer spp. can degrade polymers and synthesize natural products. Despite their recognized potential to produce secondary metabolites, siderophores are yet to be identified in Microbulbifer, and their iron acquisition strategies remain largely unknown. Here, we developed a comprehensive mass spectrometry-based query language code to determine siderophore production by Microbulbifer spp. in mono- and mixed cultures. Using this workflow, we discovered a new metallophore, which we named bulbichelin, as well as a suite of previously unreported petrobactins containing an unprecedented longer chain length acylation on the central spermidine moiety. We applied genome mining methods to describe the biosynthesis of these compounds. Using metal infusion mass spectrometry, we show that bulbichelins bind a variety of metals. Notably, neither of these compounds were produced in a co-culture of Microbulbifer with coral-derived pathogen Vibrio coralliilyticus Cn52-H1. Understanding how siderophores shape interspecies interactions between Microbulbifer spp. and other marine organisms will aid in unraveling the chemical and catalytic versatility of this genus and adaptation in nutrient deplete marine environment.

MassQL↗

PubMed2026

Systematic Genome Mining of Peptide Metallophore Pathways Uncovers Novel Dibenzo-α-Pyrone Siderophores in Streptomyces sp. HB-R818.

Metallophores are metal-chelating natural products that enable microorganisms to acquire essential metal ions and mediate processes such as iron uptake, quorum sensing, and interspecies competition. Metallophores also display potent antimicrobial and anticancer activities, highlighting their biomedical and biotechnological potential. Despite Streptomyces being prolific producers of bioactive metabolites, their metallophore pathways remain largely unexplored. Here, we systematically mined 519 reference Streptomyces genomes to elucidate the distribution, diversity, and structural features of metallophores and identified a new metallophore biosynthetic gene cluster (BGC) (ser) from sponge-derived Streptomyces sp. HB-R818. Using a metabologenomics-based strategy, five new siderophore analogs serobactins A-E (1-5) and known enterobactin (6) were isolated. These compounds show potential to inhibit tumor invasion and feature a unique dibenzo-α-pyrone scaffold in structure, formed through the cyclization of an extra 2,3-dihydroxybenzoic acid with 2,3-dihydroxybenzoyl serine. The BGC (ser) was validated by the nonribosomal peptide synthetase gene knockout; the biosynthesis of 1-6 was proposed.

Siderophores↗

PubMed2026

Integrated Genome Mining and Bioactivity-Guided Isolation of Antimicrobial Peptides from Bacillus amyloliquefaciens BS4.

Bacterial resistance remains a critical global health challenge, driving the continuous search for novel antimicrobial agents. Bacillus amyloliquefaciens is a recognized repository of bioactive metabolites; however, its full biosynthetic potential requires integrated genomic and experimental validation. This study characterized the antimicrobial profile of B. amyloliquefaciens BS4 through a hybrid pipeline. Genome sequencing and de novo assembly revealed a 3.9 Mb chromosome with a G + C content of 46.14%. Functional annotation identified 3,887 coding sequences, including pathways for siderophore biosynthesis and a complete bacilysin biosynthetic cluster. BGC analysis using antiSMASH v7.1.0 and BAGEL4 identified 18 biosynthetic gene clusters, while similarity network analysis via BiG-SCAPE highlighted unique singleton BGCs, indicating untapped biosynthetic diversity. Although in silico screening via Macrel predicted two putative cationic antimicrobial peptides (AMPs), bioactivity-guided purification utilizing sequential RP-HPLC, and de novo sequencing revealed a distinct set of four active peptides. Notably, three of these sequences were identified as fragments derived from the BclA exosporium protein family, highlighting the structural proteome as a non-canonical source of antimicrobials. The purified fractions exhibited activity against M. luteus and E. coli, while displaying no significant hemolytic activity or cytotoxicity, even above the MIC values. Molecular docking further supported the interaction of these candidates with bacterial targets. Overall, this hybrid strategy effectively uncovers the antimicrobial complexity of BS4, revealing 'cryptic' peptide candidates with therapeutic potential.

Bacillus amyloliquefaciens BS4↗

PubMed2024

Genome mining for new enediyne antibiotics.

Enediyne antibiotics epitomize nature's chemical creativity. They contain intricate molecular architectures that are coupled with potent biological activities involving double-stranded DNA scission. The recent explosion in microbial genome sequences has revealed a large reservoir of novel enediynes. However, while hundreds of enediyne biosynthetic gene clusters (BGCs) can be detected, less than two dozen natural products have been characterized to date as many clusters remain silent or sparingly expressed under standard laboratory growth conditions. This review focuses on four distinct strategies, which have recently enabled discoveries of novel enediynes: phenotypic screening from rare sources, biosynthetic manipulation, genomic signature-based PCR screening, and DNA-cleavage assays coupled with activation of silent BGCs via high-throughput elicitor screening. With an abundance of enediyne BGCs and emerging approaches for accessing them, new enediyne natural products and further insights into their biogenesis are imminent.

Enediynes↗

PubMed2026

Genome mining of alkaliphilic cyanobacterial consortia: identification of biosynthetic gene clusters in Sodalinema and associated heterotrophs.

Alkaline soda lakes are high-pH environments that host specialized microbial communities with potential for biotechnology and natural product discovery. We characterized three Sodalinema-dominated cyanobacterial consortia enriched from Canadian soda lakes over 510 days. Using hybrid metagenomic sequencing and metatranscriptomics across pH, alkalinity, and temperature gradients, we reconstructed high-quality metagenome-assembled genomes and assessed functional activity. All consortia converged toward cyanobacteria dominance and exhibited temperature optima between 21°C and 30°C. Phylogenetic analysis placed Sodalinema genomes within a distinct clade affiliated with Candidatus Sodalinema alkaliphilum. Genomic analysis indicated complete biosynthetic pathways for vitamin B5, vitamin B7, and the molybdenum cofactor, but incomplete pathways for vitamins B1, B9, and B12, consistent with patterns observed in Sodalinema yuhuli. Metatranscriptomic profiles showed increased expression of genes involved in phycocyanin and carotenoid biosynthesis at pH 10.2 relative to pH 8.5. Biosynthetic gene cluster analysis revealed that most secondary metabolic potential resided in heterotrophic community members. Roseinatronobacter encoded pathways for N-acyl homoserine lactones, osmoprotectants, betalactones, and prodigiosin, while Alkalimonas, Wenzhouxiangella, and members of the Kiloniellales encoded clusters for lanthipeptides, cyclodipeptides, hydrogen cyanide, and pyrroloquinoline quinone. These findings indicate functional partitioning within the consortia and highlight the contribution of heterotrophs to secondary metabolism.IMPORTANCEAlkaline soda lakes contain microbial communities adapted to high pH that remain underexplored for biotechnology. This study focuses on Sodalinema, a filamentous cyanobacterium that dominates enriched consortia from Canadian soda lakes, and its associated heterotrophic partners. We show that while Sodalinema drives primary productivity, heterotrophic bacteria encode most of the pathways for antimicrobial and signaling compounds. These interactions may support community stability and defense against competing microorganisms. By linking genomic potential with gene expression, this work identifies alkaline cyanobacterial consortia as a source of bioactive compounds and provides a framework for exploring extremophilic microbial communities for natural product discovery.

Sodalinema↗

PubMed2024

Bioinformatics pipeline for the systematic mining genomic and proteomic variation linked to rare diseases: The example of monogenic diabetes.

Monogenic diabetes is characterized as a group of diseases caused by rare variants in single genes. Like for other rare diseases, multiple genes have been linked to monogenic diabetes with different measures of pathogenicity, but the information on the genes and variants is not unified among different resources, making it challenging to process them informatically. We have developed an automated pipeline for collecting and harmonizing data on genetic variants linked to monogenic diabetes. Furthermore, we have translated variant genetic sequences into protein sequences accounting for all protein isoforms and their variants. This allows researchers to consolidate information on variant genes and proteins linked to monogenic diabetes and facilitates their study using proteomics or structural biology. Our open and flexible implementation using Jupyter notebooks enables tailoring and modifying the pipeline and its application to other rare diseases.

Humans↗

PubMed2025

Resistance Gene-Guided Discovery of a Fungal Spirotetramate as an Acetolactate Synthase Inhibitor.

Biosynthetic gene clusters (BGCs) of bioactive natural products occasionally encode resistant versions of the proteins they inhibit, offering opportunities for resistance gene-guided genome mining to uncover natural products with predictable modes of action. In this study, we developed a genome mining tool designed to identify fungal BGCs harboring putative resistance genes. Applying this tool to approximately 2500 fungal genomes, we identified a BGC designated as the pts cluster, which encodes an acetolactate synthase (ALS) homologue. Functional characterization of the pts cluster resulted in the identification of pterrespiramide A (1), featuring unique spirotetramate and cis-decalin moieties. Consistent with the predicted activity, 1 was confirmed as an ALS inhibitor and exhibited both antifungal and herbicidal activities. This study illuminates the potential of resistance gene-guided genome mining as a powerful strategy for accelerating the discovery of previously undescribed bioactive natural products.

Acetolactate Synthase↗

PubMed2026

Genomic exploration and in silico prioritization of putative COX-2-targeting metabolites from Streptomyces sp. VITGV156 (MCC 4965).

INTRODUCTION: Streptomyces species represent an important source of bioactive natural products, yet systematic genome-guided prioritization of metabolites targeting cyclooxygenase-2 (COX-2/PTGS2) remains limited. This study aimed to investigate the biosynthetic potential of Streptomyces sp. VITGV156 (MCC 4965) using an integrated genome mining and computational drug discovery pipeline. METHODS: Whole-genome sequencing, functional annotation, antiSMASH v7.0.1-based biosynthetic gene cluster (BGC) prediction, LC-MS/MS metabolomic profiling, SwissADME analysis, target prediction, disease association mapping, molecular docking against PTGS2 (PDB: 5IKR), and PASS bioactivity prediction were performed to prioritize putative bioactive metabolites. RESULTS: Genome analysis identified 29 predicted biosynthetic gene clusters, including clusters associated with geosmin, ectoine, albaflavenone, hopene, coelichelin, and SapB, together with several cryptic clusters exhibiting low similarity to known pathways. LC-MS/MS metabolomic profiling provided experimental support for active secondary metabolite production under the cultivation conditions employed. Computational prioritization identified PTGS2 (COX-2) as a biologically relevant target. Molecular docking demonstrated favorable binding affinities and interaction profiles for several predicted metabolites within the PTGS2 catalytic pocket. PASS analysis further suggested potential anticancer-related biological activities that require experimental validation. DISCUSSION: These findings demonstrate the utility of integrating genome mining, metabolomic profiling, and computational drug discovery for prioritizing natural-product candidates. Streptomyces sp. VITGV156 (MCC 4965) represents a promising source of biosynthetic diversity and provides a genome-guided framework for identifying putative COX-2-targeting natural products for future experimental validation rather than confirming metabolite production or biological activity.

COX-2 (PTGS2)↗

PubMed2026

Comparative genomics reveals hidden biosynthetic diversity in Streptomyces spp. and metal-dependent regulatory features associated with untapped specialized metabolites.

The genus Streptomyces is one of the richest sources of bioactive natural products; however, a substantial proportion of its biosynthetic gene clusters (BGCs) remain cryptic and their metabolic products are unresolved. Advances in genome mining and computational prediction now enable comprehensive exploration of this hidden biosynthetic repertoire. In this study, whole-genome sequencing and comparative genomic analyses were performed on three three newly isolated Streptomyces strains to evaluate their specialized metabolic potential. Genome assemblies were annotated and systematically analyzed using antiSMASH, DeepBGC, GECCO, and PRISM to identify, cross-validate, and functionally characterize BGCs while predicting their associated secondary metabolite scaffolds. Taxonomic analyses based on Average Nucleotide Identity (ANI), phylogenomics, and BLAST identified the isolates as Streptomyces thinghirensis, Streptomyces novocaesareae, and Streptomyces griseorubens. Applying the consensus framework across the three Streptomyces genomes yielded 43 cryptic BGCs, lacking close similarity to reference BGCs in the MIBiG database, of which 26 were classified as HIGH, 10 as MEDIUM, and 7 as LOW confidence. Notably, numerous BGCs exhibited low abundance to characterized reference clusters, indicating a high potential for previously undescribed biosynthetic pathways and novel metabolite scaffolds. Comparative analyses further revealed strain-specific biosynthetic architectures together with putative metal-responsive regulatory systems; Fur, Zur, and Nur, which were frequently associated with specialized metabolite biosynthetic loci. Collectively, these findings demonstrate the effectiveness of integrated genome-mining strategies for prioritizing cryptic biosynthetic gene clusters and highlight the remarkable biosynthetic potential of newly identified Streptomyces isolates as a source of novel natural products.

comparative genomics↗

PubMed2026

Two Saccharopolyspora isolates from archaeological excavation sites: polyphasic taxonomy, biosynthetic potential, bioactivity profiling and description of Saccharopolyspora antiqui sp. nov.

Archaeological excavation sites represent underexplored microbial habitats with the potential to recover taxonomically and biotechnologically valuable actinomycetes. In this study, two Saccharopolyspora strains, 5N708T and 5N102, were isolated from soil samples collected from the Gaziantep-Doliche-Dülük and Bitlis-Ahlat-Selçuklu Cemetery archaeological excavation sites in Türkiye. A polyphasic taxonomic approach, including 16S rRNA gene sequencing, phylogenetic and phylogenomic analyses, average nucleotide identity, digital DNA-DNA hybridization, phenotypic characterization, and chemotaxonomic analyses, showed that strain 5N708T represents a novel species of the genus Saccharopolyspora, for which the name Saccharopolyspora antiqui sp. nov. is proposed, whereas strain 5N102 was assigned to Saccharopolyspora elongata. Both isolates were further evaluated for their antimicrobial, antioxidant, and cytotoxic activities, and their biosynthetic potential was investigated by genome mining. Both strains showed activity against Staphylococcus aureus, with strain 5N708T producing the larger inhibition zone. Strain 5N102 exhibited markedly stronger antioxidant activity than strain 5N708T in radical scavenging, ferric reducing antioxidant power, and reducing power assays. In contrast, strain 5N708T showed more promising cytotoxic activity, with relative selectivity toward MIA PaCa-2 pancreatic cancer cells compared with HEK293 cells after prolonged incubation. Genome mining revealed multiple biosynthetic gene clusters in both isolates, supporting their capacity to produce secondary metabolites. These findings indicate that archaeological soils are promising reservoirs of taxonomically novel and biologically active Saccharopolyspora strains.

Saccharopolyspora↗

PubMed2026

High-level terpene production via a novel Actinomycetota-derived MVA pathway in E. coli.

The heterologous production of terpene in microbial hosts is often limited by inefficient and unstable pathway expression, creating a major bottleneck for industrial-scale synthesis. While E. coli as a chassis offers significant advantages, such as rapid growth, ease of cultivation, and genetic tractability. Its endogenous supply of terpenoid precursors remains a critical constraint, fundamentally restricting high-yield production. To address this challenge, we developed a genomically integrated Mevalonate (MVA) pathway from Actinomycetota in E. coli BL21(DE3) to enhance terpene precursor supply. Our approach began with an in silico multi-layer global genome mining analysis of 25,261 Actinomycetota genomes to identify a series of MVA pathway enzymes with potentially high catalytic efficiency, created a high-efficiency chassis E. coli MVA platform (ecMVA-1 and ecMVA-2) for terpene precursor synthesis. Its functionality was validated by testing eight distinct TSs. Among them, the fermentation of artemisinin precursor amorphadiene using a 5-liter bioreactor yielded 947.80 mg/L. These results indicated that E. coli (MVA) is well-suited for TS studies in the laboratory as well as holding significant promise for industrial applications. In addition, this in silico approach offers a new perspective for metabolic engineering and provides potential reservoir of diverse chassis for the industrial production of terpenoid-derived compounds.

Actinomycetota↗