Pepticinnamins N, O, and P, Nonribosomal Peptides from the Soil-Derived Streptomyces mirabilis P8-A2.

Cinnamoyl moiety containing nonribosomal peptides represented by pepticinnamin E are a growing family of natural products isolated from different Streptomyces species and possess diverse bioactivities. The soil bacterium Streptomyces mirabilis P8-A2 harbors a cryptic pepticinnamin biosynthetic gene cluster, producing azodyrecins as major products. Inactivation of the azodyrecin biosynthetic gene cluster by CRISPR-BEST base editing led to the activation and production of pepticinnamin E (1) and its analogues, pepticinnamins N, O, and P (2-4), the structures of which were determined by detailed NMR spectroscopy, HRMS data, and Marfey's reactions. These new compounds did not show a growth inhibitory effect against the LNCaP and C4-2B prostate cancer lines, respectively.

teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering.

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.

Biosynthesis of the Azoxy Compound Azodyrecin from Streptomyces mirabilis P8-A2.

Azoxy compounds are a distinctive group of bioactive secondary metabolites characterized by a unique RN═N+(O-)R moiety. The azoxy moiety is present in various classes of metabolites that exhibit various biological activities. The enzymatic mechanisms underlying azoxy bond formation remain enigmatic. Azodyrecins are cytotoxic azoxy metabolites produced by Streptomyces mirabilis P8-A2. Here, we cloned and confirmed the putative azd biosynthetic gene cluster through CATCH cloning followed by expression and production of azodyrecins in two heterologous hosts, S. albidoflavus J1074 and S. coelicolor M1146, respectively. We explored the function of 14 enzymes in azodyrecin biosynthesis through gene knockout using CRISPR-Cas9 base editing in the native producer, S. mirabilis P8-A2. The key intermediates were analyzed in the mutants through MS/MS fragmentation studies, revealing azoxy bond formation via the conversion of hydrazine to an azo compound followed by further oxygenation. Enzymes involved in modifications of the precursor could be postulated based on their predicted function and the intermediates identified in the knockout strains. Moreover, the distribution of the azoxy biosynthetic gene clusters across Streptomyces spp. genomes is explored, highlighting the presence of these clusters in over 20% of the Streptomyces spp. genomes and revealing that azoxymycin and valanimycin are scarce, while azodyrecin and KA57A-like clusters are widely distributed across the phylogenetic tree.

Dilarmycins A-C, Calcium-Dependent Lipopeptide Antibiotics with a Non-canonical Ca2+-Binding Motif.

Genome analysis of strain Streptomyces sp. CA-278952 revealed a biosynthetic gene cluster encoding a putative lipopeptide with a sequence containing an Asp-Gly-Glu-Ala motif. We envisioned that this motif could mimic the canonical Asp-X-Asp-Gly sequence found in previously reported calcium-dependent lipopeptide antibiotics. Chemical investigation of the producing strain led to the discovery of three novel lipodepsipeptides, dilarmycins A-C. The calcium-dependent antibacterial activity of the new compounds was confirmed against the Gram-positive pathogens methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus.

The antiSMASH database version 4: additional genomes and BGCs, new sequence-based searches and more.

Many microorganisms produce natural products that are frequently used in the development of medicines and crop protection agents. Genome mining has evolved into a prominent method to access this potential. antiSMASH is the most popular tool for this task. Here we present version 4 of the antiSMASH database, providing biosynthetic gene clusters detected by antiSMASH 7.1 in publicly available, dereplicated, high-quality microbial genomes via an interactive graphical user interface. In version 4, the database contains 231 534 high quality BGC regions from 592 archaeal, 35 726 bacterial and 236 fungal genomes and is available at https://antismash-db.secondarymetabolites.org/.

Commensal production of a broad-spectrum and short-lived antimicrobial peptide polyene eliminates nasal Staphylococcus aureus.

Antagonistic bacterial interactions often rely on antimicrobial bacteriocins, which attack only a narrow range of target bacteria. However, antimicrobials with broader activity may be advantageous. Here we identify an antimicrobial called epifadin, which is produced by nasal Staphylococcus epidermidis IVK83. It has an unprecedented architecture consisting of a non-ribosomally synthesized peptide, a polyketide component and a terminal modified amino acid moiety. Epifadin combines a wide antimicrobial target spectrum with a short life span of only a few hours. It is highly unstable under in vivo-like conditions, potentially as a means to limit collateral damage of bacterial mutualists. However, Staphylococcus aureus is eliminated by epifadin-producing S. epidermidis during co-cultivation in vitro and in vivo, indicating that epifadin-producing commensals could help prevent nasal S. aureus carriage. These insights into a microbiome-derived, previously unknown antimicrobial compound class suggest that limiting the half-life of an antimicrobial may help to balance its beneficial and detrimental activities.

Streptomyces alleviate abiotic stress in plant by producing pteridic acids.

Soil microbiota can confer fitness advantages to plants and increase crop resilience to drought and other abiotic stressors. However, there is little evidence on the mechanisms correlating a microbial trait with plant abiotic stress tolerance. Here, we report that Streptomyces effectively alleviate drought and salinity stress by producing spiroketal polyketide pteridic acid H (1) and its isomer F (2), both of which promote root growth in Arabidopsis at a concentration of 1.3 nM under abiotic stress. Transcriptomics profiles show increased expression of multiple stress responsive genes in Arabidopsis seedlings after pteridic acids treatment. We confirm in vivo a bifunctional biosynthetic gene cluster for pteridic acids and antimicrobial elaiophylin production. We propose it is mainly disseminated by vertical transmission and is geographically distributed in various environments. This discovery reveals a perspective for understanding plant-Streptomyces interactions and provides a promising approach for utilising beneficial Streptomyces and their secondary metabolites in agriculture to mitigate the detrimental effects of climate change.

Complete, circular genome sequence of a Bosea sp. isolate from soil.

Here, we report the complete, circular genome sequence of a potential novel species from the underexplored Alphaproteobacterial genus Bosea. Bosea sp. NBC_00550 was isolated from a soil sample collected in Lyngby, Denmark. We explore the biosynthetic potential of Bosea sp. NBC_00550 and compare it with that of other Bosea species.

Systems Analysis of Highly Multiplexed CRISPR-Base Editing in Streptomycetes.

CRISPR tools, especially Cas9n-sgRNA guided cytidine deaminase base editors such as CRISPR-BEST, have dramatically simplified genetic manipulation of streptomycetes. One major advantage of CRISPR base editing technology is the possibility to multiplex experiments in genomically instable species. Here, we demonstrate scaled up Csy4 based multiplexed genome editing using CRISPR-mcBEST in Streptomyces coelicolor. We evaluated the system by simultaneously targeting 9, 18, and finally all 28 predicted specialized metabolite biosynthetic gene clusters in a single experiment. We present important insights into the performance of Csy4 based multiplexed genome editing at different scales. Using multiomics analysis, we investigated the systems wide effects of such extensive editing experiments and revealed great potentials and important bottlenecks of CRISPR-mcBEST. The presented analysis provides crucial data and insights toward the development of multiplexed base editing as a novel paradigm for high throughput engineering of Streptomyces chassis and beyond.

Properties of Multidrug-Resistant Mutants Derived from Heterologous Expression Chassis Strain Streptomyces albidoflavus J1074.

Streptomyces albidoflavus J1074 is a popular platform to discover novel natural products via the expression of heterologous biosynthetic gene clusters (BGCs). There is keen interest in improving the ability of this platform to overexpress BGCs and, consequently, enable the purification of specialized metabolites. Mutations within gene rpoB for the ß-subunit of RNA polymerase are known to increase rifampicin resistance and augment the metabolic capabilities of streptomycetes. Yet, the effects of rpoB mutations on J1074 remained unstudied, and we decided to address this issue. A target collection of strains that we studied carried spontaneous rpoB mutations introduced in the background of the other drug resistance mutations. The antibiotic resistance spectra, growth, and specialized metabolism of the resulting mutants were interrogated using a set of microbiological and analytical approaches. We isolated 14 different rpoB mutants showing various degrees of rifampicin resistance; one of them (S433W) was isolated for the first time in actinomycetes. The rpoB mutations had a major effect on antibiotic production by J1074, as evident from bioassays and LC-MS data. Our data support the idea that rpoB mutations are useful tools to enhance the ability of J1074 to produce specialized metabolites.

Complete Genome Sequences of the Two Strains Methylorubrum extorquens NBC_00036 and NBC_00404.

Here, we report the complete genome sequences of Methylorubrum extorquens NBC_00036 and Methylorubrum extorquens NBC_00404. The genomes were sequenced using the Oxford Nanopore Technologies MinION and Illumina NovaSeq systems. Both genomes are circular, with sizes of 5,661,342 bp and 5,869,086 bp, respectively.

antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures and visualisation.

Microorganisms produce small bioactive compounds as part of their secondary or specialised metabolism. Often, such metabolites have antimicrobial, anticancer, antifungal, antiviral or other bio-activities and thus play an important role for applications in medicine and agriculture. In the past decade, genome mining has become a widely-used method to explore, access, and analyse the available biodiversity of these compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' (https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free to use web server and as a standalone tool under an OSI-approved open source licence. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in archaea, bacteria, and fungi. Here, we present the updated version 7 of antiSMASH. antiSMASH 7 increases the number of supported cluster types from 71 to 81, as well as containing improvements in the areas of chemical structure prediction, enzymatic assembly-line visualisation and gene cluster regulation.

UmetaFlow: an untargeted metabolomics workflow for high-throughput data processing and analysis.

Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for untargeted metabolomics that combines algorithms for data pre-processing, spectral matching, molecular formula and structural predictions, and an integration to the GNPS workflows Feature-Based Molecular Networking and Ion Identity Molecular Networking for downstream analysis. UmetaFlow is implemented as a Snakemake workflow, making it easy to use, scalable, and reproducible. For more interactive computing, visualization, as well as development, the workflow is also implemented in Jupyter notebooks using the Python programming language and a set of Python bindings to the OpenMS algorithms (pyOpenMS). Finally, UmetaFlow is also offered as a web-based Graphical User Interface for parameter optimization and processing of smaller-sized datasets. UmetaFlow was validated with in-house LC-MS/MS datasets of actinomycetes producing known secondary metabolites, as well as commercial standards, and it detected all expected features and accurately annotated 76% of the molecular formulas and 65% of the structures. As a more generic validation, the publicly available MTBLS733 and MTBLS736 datasets were used for benchmarking, and UmetaFlow detected more than 90% of all ground truth features and performed exceptionally well in quantification and discriminating marker selection. We anticipate that UmetaFlow will provide a useful platform for the interpretation of large metabolomics datasets.

Crossiellidines A-F, Unprecedented Pyrazine-Alkylguanidine Metabolites with Broad-Spectrum Antibacterial Activity from Crossiella sp.

Crosiellidines are intriguing pyrazine-alkylguanidine metabolites isolated from the minor actinomycete genus Crossiella. Their structures present an unprecedented 2-methoxy-3,5,6-trialkyl pyrazine scaffold and uncommon guanidine prenylations, including an exotic O-prenylated N-hydroxyguanidine moiety. The novel substitution pattern of the 2-methoxypyrazine core inaugurates a new class of naturally occurring pyrazine compounds, the biosynthetic implications of which are discussed herein. Isotopic feeding and genome analysis allowed us to propose a biosynthetic pathway from arginine. The crossiellidines exhibited remarkable, broad-spectrum antibacterial activity.

Identification and heterologous expression of the globomycin biosynthetic gene cluster.

Globomycin is a cyclic lipodepsipeptide originally isolated from several Streptomyces species which displays strong and selective antibacterial activity against Gram-negative pathogens. Its mode of action is based on the competitive inhibition of the lipoprotein signal peptidase II (LspA), which is absent in eukaryotes and considered an attractive target for the development of new antibiotics. Despite its interesting biological properties, the gene cluster encoding its biosynthesis has not yet been identified. In this study we employed a genome-mining approach in the globomycin-producing Streptomyces sp. CA-278952 to identify a candidate gene cluster responsible for its biosynthesis. A null mutant was constructed using CRISPR base editing where production was abolished, strongly suggesting its involvement in the biosynthesis. The putative gene cluster was then cloned and heterologously expressed in Streptomyces albus J1074 and Streptomyces coelicolor M1146, therefore unambiguously linking globomycin and its biosynthetic gene cluster. Our work paves the way for the biosynthesis of new globomycin derivatives with improved pharmacological properties.

Extraction and Oxford Nanopore sequencing of genomic DNA from filamentous Actinobacteria.

Actinomycetota (Actinobacteria) is an ecologically and industrially important phylum which is challenging to extract pure high-molecular-weight (HMW) DNA from. This protocol provides a parallelized, cost-effective, and straightforward approach for consistently extracting pure HMW DNA using modified non-toxic commercial kits suitable for higher throughput applications. We further provide a workflow for sequencing and assembly of complete genomes using an optimized Oxford Nanopore rapid barcoding protocol and Illumina data error correction.

High-quality genome-scale metabolic network reconstruction of probiotic bacterium Escherichia coli Nissle 1917.

BACKGROUND: Escherichia coli Nissle 1917 (EcN) is a probiotic bacterium used to treat various gastrointestinal diseases. EcN is increasingly being used as a chassis for the engineering of advanced microbiome therapeutics. To aid in future engineering efforts, our aim was to construct an updated metabolic model of EcN with extended secondary metabolite representation. RESULTS: An updated high-quality genome-scale metabolic model of EcN, iHM1533, was developed based on comparison with 55 E. coli/Shigella reference GEMs and manual curation, including expanded secondary metabolite pathways (enterobactin, salmochelins, aerobactin, yersiniabactin, and colibactin). The model was validated and improved using phenotype microarray data, resulting in an 82.3% accuracy in predicting growth phenotypes on various nutrition sources. Flux variability analysis with previously published 13C fluxomics data validated prediction of the internal central carbon fluxes. A standardised test suite called Memote assessed the quality of iHM1533 to have an overall score of 89%. The model was applied by using constraint-based flux analysis to predict targets for optimisation of secondary metabolite production. Modelling predicted design targets from across amino acid metabolism, carbon metabolism, and other subsystems that are common or unique for influencing the production of various secondary metabolites. CONCLUSION: iHM1533 represents a well-annotated metabolic model of EcN with extended secondary metabolite representation. Phenotype characterisation and the iHM1533 model provide a better understanding of the metabolic capabilities of EcN and will help future metabolic engineering efforts.

Long-Read Metagenome-Assembled Genomes Improve Identification of Novel Complete Biosynthetic Gene Clusters in a Complex Microbial Activated Sludge Ecosystem.

Microorganisms produce a wide variety of secondary/specialized metabolites (SMs), the majority of which are yet to be discovered. These natural products play multiple roles in microbiomes and are important for microbial competition, communication, and success in the environment. SMs have been our major source of antibiotics and are used in a range of biotechnological applications. In silico mining for biosynthetic gene clusters (BGCs) encoding the production of SMs is commonly used to assess the genetic potential of organisms. However, as BGCs span tens to over 200 kb, identifying complete BGCs requires genome data that has minimal assembly gaps within the BGCs, a prerequisite that was previously only met by individually sequenced genomes. Here, we assess the performance of the currently available genome mining platform antiSMASH on 1,080 high-quality metagenome-assembled bacterial genomes (HQ MAGs) previously produced from wastewater treatment plants (WWTPs) using a combination of long-read (Oxford Nanopore) and short-read (Illumina) sequencing technologies. More than 4,200 different BGCs were identified, with 88% of these being complete. Sequence similarity clustering of the BGCs implies that the majority of this biosynthetic potential likely encodes novel compounds, and few BGCs are shared between genera. We identify BGCs in abundant and functionally relevant genera in WWTPs, suggesting a role of secondary metabolism in this ecosystem. We find that the assembly of HQ MAGs using long-read sequencing is vital to explore the genetic potential for SM production among the uncultured members of microbial communities. IMPORTANCE Cataloguing secondary metabolite (SM) potential using genome mining of metagenomic data has become the method of choice in bioprospecting for novel compounds. However, accurate biosynthetic gene cluster (BGC) detection requires unfragmented genomic assemblies, which have been technically difficult to obtain from metagenomes until very recently with new long-read technologies. Here, we determined the biosynthetic potential of activated sludge (AS), the microbial community used in resource recovery and wastewater treatment, by mining high-quality metagenome-assembled genomes generated from long-read data. We found over 4,000 BGCs, including BGCs in abundant process-critical bacteria, with no similarity to the BGCs of characterized products. We show how long-read MAGs are required to confidently assemble complete BGCs, and we determined that the AS BGCs from different studies have very little overlap, suggesting that AS is a rich source of biosynthetic potential and new bioactive compounds.

Identification of the Biosynthetic Gene Cluster for Pyracrimycin A, an Antibiotic Produced by Streptomyces sp.

Actinomycetes make a wealth of complex, structurally diverse natural products, and a key challenge is to link them to their biosynthetic gene clusters and delineate the reactions catalyzed by each of the enzymes. Here, we report the biosynthetic gene cluster for pyracrimycin A, a set of nine genes that includes a core nonribosomal peptide synthase (pymB) that utilizes serine and proline as precursors and a monooxygenase (pymC) that catalyzes Baeyer-Villiger oxidation. The cluster is similar to the one for brabantamide A; however, pyracrimycin A biosynthesis differs in that feeding experiments with isotope-labeled serine and proline suggest that a ring opening reaction takes place and a carbon is lost from serine downstream of the oxidation reaction. Based on these data, we propose a full biosynthesis pathway for pyracrimycin A.

Complete Genome Sequence of the Collinolactone Producer Streptomyces sp. Strain Gö40/10.

The actinomycete Streptomyces sp. strain Gö40/10 has the potential to produce a range of secondary metabolites, one of which is collinolactone, a compound with neuroprotective properties and potential for pharmaceutical applications. The genome was sequenced with Oxford Nanopore Technologies MinION and Illumina MiSeq systems and consists of a single 9,635,564-nucleotide linear chromosome.