Genomic analysis of the Streptomyces sp. LV42-5 isolated from industrial mine dumps in Sheptytskyi

In the 21st century, the world is facing persistent global problems that have led to 193 countries to agree on the 17 Sustainable Development Goals (SDGs). The United Nations introduced these goals in 2015 to find solutions that could help end poverty, promote prosperity and protect the planet (United Nations, 2016a). In this brief perspective, we will discuss the potential role of Streptomyces in achieving those SDGs, focusing it in the current strategies applied for discovering novel compounds and in some of the problems that must be faced (Figure 1). Members of the genus Streptomyces are filamentous Gram-positive bacteria belonging to the phylum Actinobacteria. They are ubiquitous microorganisms mainly found in soil but they can also inhabit other niches like seawater or deserts, or living associated with other organisms (Sivalingam et al., 2019). Streptomyces is mainly known for its ability to produce a wide array of bioactive secondary metabolites, which have several interesting applications in different fields (Alam et al., 2022; Demain & Sanchez, 2009; Donald et al., 2022). One of the problems that most concern the United Nations is the existence of a growing demand for food in today's world (Food security information network, 2023). In this context, Streptomyces could play a relevant role in achieving SDG 2 (zero hunger, improved nutrition and sustainable agriculture) and SDG 1 (end poverty). Streptomyces produces several metabolites with significant commercial relevance in enhancing the nutritional value of human food and animal feed, such as vitamins like cobalamin (Rex et al., 2022). Additionally, there is an increasing need for enzymes in the global market (Grand View Research, 2023). Streptomyces due to its wide metabolic potential is used for the sustainable biotechnological production of a broad assortment of enzymes such as proteases, xylanases, amylases, lipases, keratinases, cellulases, dextranases and chitinases among others (Fernandes de Souza et al., 2022; Kumar et al., 2020). These enzymes have applications in several fields, and advantages not only in terms of energy consumption, stability, substrate specificity, purity or reaction efficiency but also in ecological and waste generation, thus contributing to the achievement of sustainable industrialization and innovation (SDG 9) and promoting responsible production and consumption (SDG 12). An example of enzymes with ecological applications is the degradation of lignocellulose and dye decolourization by detergent-stable peroxidases and laccases (Cuebas-Irizarry & Grunden, 2024). These enzymes can be potentially used to treat wastewater resulting from human activities like textile and paper industries, which cause environmental pollution and wastes that affect life below water (SDG 14). Another promising application of Streptomyces is its use to obtain energy from waste resources, what contributes to the pursuit of affordable and clean energy (SDG 7) and climate action (SDG 13). For instance, Muthusamy et al. (2019) were able to produce bioethanol from different agro-residues using an S. olivaceus strain isolated from a mangrove sample. Streptomyces also contributes to the preservation of life on land (SDG 15) because they play a crucial role in sustainable agriculture and plant growth due to its participation in soil fertility (Hozzein et al., 2019). They contribute to phosphate and potassium biosolubilization, nitrogen supply to ecosystems, to stablish beneficial symbiosis with other rhizosphere microorganisms and to produce biocontrol agents such as phytohormones, antimicrobials, antifungals, pesticides, bioherbicides and insecticides (Boubekri et al., 2022; Li et al., 2021). Furthermore, the use of Streptomyces is considered an eco-friendly and promising technology for bioremediation of contaminants like pesticides and heavy metals because they can degrade organic and inorganic compounds more efficiently and safely than chemical agents (Jagannathan et al., 2021). Nevertheless, the greatest contribution throughout history of Streptomyces is as producer of bioactive compounds with applications in clinical, veterinary and agricultural fields, being the most important microbial source of bioactive compounds (Donald et al., 2022). In this context, this microorganism is an incredible force for achieving good health and well-being (SDG 3). During the so-called Golden Age of antibiotic discovery Streptomyces provided humanity with antibiotics, antifungal, anti-parasitic, immunosuppressive agents and antitumor compounds, many of them currently used in clinical (Demain & Sanchez, 2009). Subsequently, limitations in classical search techniques and depletion of traditional habitats have led to the rediscovery of known compounds or the identification of a scarce number of compounds with new scaffolds. This, together with the high costs to develop new compounds for clinical and other uses, resulted in a drastic decline in the discovery of new drugs and the withdrawal of these research departments from some big pharma companies (Genilloud, 2017). Nevertheless, recent screening new approaches, such as the use of pathogenic bacteria conditionally expressing antisense RNA of essential genes, have led to discovering new antibiotics like platensimycin (Figure 2) (Genilloud, 2017). In addition, screening antibiotic active molecules for other activities identified a number of useful natural products (NPs), including some with antitumor activity such as actinomycin D (Figure 2) (Demain & Vaishnav, 2011). Subsequently, advances in -omics and sequencing methods, and the development of synthetic and genomic manipulation techniques in Streptomyces in the last decades, have led to the emergence of new strategies in drug discovery, such as genome mining and combinatorial biosynthesis. These approaches represent promising strategies for discovering novel bioactive NPs, in many cases with high structural diversity. Additionally, these strategies were improved when combined with the isolation of new Streptomyces strains from low explored environments, which produce structurally diverse bioactive NPs with potential clinical applications (Alam et al., 2022; Chen et al., 2021; Donald et al., 2022; Lacey & Rutledge, 2022; Qin et al., 2017; Quinn et al., 2020). Noteworthy, the antibacterial anti-Gram positive chaxalactin (Figure 2) (Castro et al., 2018) produced by Streptomyces leuwenhoeeki from the Atacama desert; or cervimycins produced by Streptomyces tendae strain HKI 0179 from the ancient Italian cave Grotta dei Cervi, with antibacterial activity anti-MRSA, anti-VRE and anti- S. aureus EfS4 (Herold et al., 2005). Notably, in recent years, marine environments have been a prolific source of new NPs with a variety of bioactivities (Alves et al., 2018; Chen et al., 2021; Choudhary et al., 2017; Dharmaraj, 2010; Donald et al., 2022; Yang et al., 2020). Examples include the antibacterial anthracimycin B, produced by Streptomyces cyaneofuscatus M-169 from the Cantabrian sea (Rodríguez et al., 2018); or the cytotoxic neo-actinomycin A produced by Streptomyces sp. IMB094 from a marine sediment (Wang et al., 2017). Another unusual habitat where Streptomyces strains are found is in symbiotic associations with plants, fungi, vertebrates or invertebrate animals, both marine and terrestrial. In these associations, they appear to be a nutritional resource, or to play a protective role for the host against pathogens, parasites or predators, by producing antibiotic compounds (Barka et al., 2016; Batey et al., 2020; Chen et al., 2021; Donald et al., 2022; Qin et al., 2011; Seipke et al., 2012). In this context, it is worth highlighting the role played by some volatile compounds (VOCs) produced by Streptomyces such as geosmine, as an attractant for soil-dwelling arthropods like springtails, to localize them as a food source. In turn, springtails facilitates the dispersal of Streptomyces spores to other niches by these arthropods (Becher et al., 2020). One of the most widespread example is the symbiotic relationship with insects. Thus, new antifungal compounds such as mycangimycins (Scott et al., 2008) or frontalamides A and B (Blodgett et al., 2010) have been isolated. Both are produced by symbiotic Streptomyces strains found in the southern pine beetle (SPB) Dendroctonus frontalis. Another example are the new formicamycins antibiotics (Figure 2) that have shown promising anti-MRSA and VRE activities, which are produced by Streptomyces formicae KY5, isolated from African ants of the Tetraponera genus (Qin et al., 2017). As it has been mentioned before, genome mining has become a useful tool for discovering natural products from the early 2000s (Baltz, 2021; Lee et al., 2020). It can be defined as the set of bioinformatics tools used to detect secondary metabolite biosynthesis gene clusters (smBGCs) and their possible functional and chemical interactions (Albarano et al., 2020). Genome mining has shown that each Streptomyces species possesses about 30 smBGCs, what has supported the hypothesis that most Streptomyces biodiversity is yet to be exploited for NPs discovery (Baltz, 2019; Belknap et al., 2020). In recent years, this strategy has enabled the identification of potentially new secondary metabolites encoded by smBGCs. For example, the antitumor chaxapeptin, identified by mining a S. leuwenhoeeki strain isolated from the Atacama desert (Castro et al., 2018); the antituberculous atratumycin, produced by S. atratus SCSIO ZH16 from the South China Sea (Sun et al., 2019); the new cytotoxic peptide curacozole (Figure 2), isolated from Streptomyces curacoi (Kaweewan et al., 2019); or largimycins, new leinamycin-like compounds identified by mining S. argillaceus (Becerril et al., 2020). Nonetheless, despite some successful examples that can be found in the literature, the enormous diversity of smBGCs identified by genome mining is only partially translated to discovering new bioactive NPs, and identifying and characterizing compounds encoded by these predicted smBGCs still requires substantial laboratory work. Thus, the smBGC can be expressed or low-expressed but the predicted encoded compounds is not detected under standard laboratory conditions (cryptic products), or the smBGC identified is not expressed and the product is unobserved (silent BGC with a cryptic product). All of these scenarios exemplify 'Known Unknowns' secondary metabolites (Hoskisson & Seipke, 2020). Therefore, a key issue for being successful using genome mining as an approach is to find strategies to turn on or to increase the expression of these silent or low expressed smBGCs. For this purpose, there are several genetic strategies that have been used like overexpression of positive regulators; inactivation of negative regulators; heterologous expression of the smBGC; or the insertion of a strong promoter upstream of BGC operons (Olano, García, et al., 2014). Other strategies to alleviate challenge of identifying the cryptic products are OSMAC (one strain of many compounds) (Pan et al., 2019); mimicking the ecological environment of the producer (Cuervo et al., 2022); redirecting precursors to the target biosynthesis pathway (Kallifidas et al., 2018); engineering global regulators (Cuervo et al., 2023); or ribosome engineering (Zhu et al., 2019). Nevertheless, we have to keep in mind that one of the major bottlenecks in drug discovery throughout history was the constant rediscovery of known compounds. From this perspective, some smart bioinformatics genome mining approaches can increase the chances to identifying unknown smBGCs encoding new compounds with potentially clinical applications. For example, several strategies have been used in recent years like mining for resistance genes (Culp et al., 2020), or for Streptomyces Antibiotic Regulatory Protein genes (Ye et al., 2023). Additionally, searching genes involved in the biosynthesis of unusual functional groups has also been used as an approach to select new smBGCs, such as targeting halogenases genes (Prado-Alonso et al., 2022); DNA regions in Polyketide Synthases encoding the didomain DUF–SH specific for sulfur incorporation (Pan et al., 2017); C-terminal thioester reductase (TR) domains and ϖ-transaminases (Awodi et al., 2017); or piperazate synthase encoding genes (García-Gutiérrez et al., 2024; Morgan et al., 2020). Another important application of genome mining is as reservoir of genetic sets and devices for being used in combinatorial biosynthesis strategies. This method squeezes the maximum of synthetic biology techniques, by using different genetic engineering strategies to generate smBGCs with novel gene combinations. These would encode novel biosynthetic pathways that potentially could direct the biosynthesis of new natural products with different or improved properties. Combinatorial biosynthesis encompasses several strategies such as combination of native biosynthetic genes and genes from other smBGCs, expression of genes from other smBGCs into mutants blocked at specific biosynthetic steps, mutasynthesis based on the use of different biosynthetic precursors, or all of the above strategies combined to obtain new structural units (Olano et al., 2009). This method has been successfully used for the biosynthesis of new derivatives of a wide variety of compounds like terpenes (Tang et al., 2022), non ribosomal peptides (Ruijne & Kuipers, 2021), RiPPs (ribosomal synthesized and post-translationally modified peptides) (Sardar & Schmidt, 2016), polyketides (Wang et al., 2022) or nucleosides (Niu et al., 2017). An interesting example was the generation of the new glycosylated analog demycarosyl-3D-β-D-digitoxosylmithramycin SK (Figure 2), derived from mithramycin (Núñez et al., 2012). Production of this compound was achieved by providing the capability to synthesize D-digitoxose to a S. argillaceus strain mutated in a ketoreductase gene of the mithramycin BGC. This analog showed high antitumor activity and less toxicity than the parental compound, and among others, it is able to suppress EWS-FLI1 activity suggesting a potential development in clinical (Osgood et al., 2016). Another example was the production of epirubicin (Figure 2), a less cardiotoxic doxorubicin derivative, which initially was produced by semisynthesis. A new method was designed for its production consisting in expressing avrE or eryBIV from the avermectin and erythromycin gene clusters into a S. peucetius doxorubicin non-producer mutant (Demain & Vaishnav, 2011). To summarize the current state of the art we can highlight a study carried out by Malmierca et al. (2018, 2020), which illustrates the combination of different chromatographic, genome mining, nutritional and combinatorial biosynthesis approaches, as an effective strategy for identifying new NPs. This research was conducted on Streptomyces strains isolated from symbiotic associations with leaf cutters ants of the Attini tribe. These ants maintain close association with Streptomyces that produce bioactive compounds, including antifungals and inhibitors of Escovopsis weberi, a parasitic microfungus of their mutualistic Basidiomycete fungi (Seipke et al., 2011). Malmierca et al. mined those Streptomyces genomes searching for smBGCs encoding glycosylated secondary metabolites, since many therapeutically relevant drugs contain sugar moieties (Salas & Méndez, 2007). By a combination of genome mining, PCR screening, metabolites dereplication, as well as genetic and nutritional approaches, they identified two novel compounds of the cervimycins family (sipanmycin A and B), and two novel members of the warkmycin family (Malmierca et al., 2018). Also, by combinatorial biosynthesis, expressing plasmids for the biosynthesis of deoxysugars into the sipanmycin producer Streptomyces CS149, they generated six different derivatives with altered glycosylation patterns (Malmierca et al., 2020). Recent research, some of them summarized in this Editorial article suggest that Streptomyces remains the leading producer of bioactive compounds. This article emphasizes the contribution of these microorganisms to achieving SDG3. Moreover, recent years have seen the implementation of new methods that have revitalized the discovery of new natural products, accentuating the promising potential of Streptomyces. Even though, despite the discovery of new Streptomyces species and the identification of a large number of hypothetical smBGCs through genome mining research, only a small fraction of them have been characterized so far. This is mainly due to the limitations of these methods. For example, culturing new Streptomyces species from extreme environments under laboratory conditions is usually a challenge, as well as the heterologous expression of smBGCs, which is difficult and time-consuming. Related to genome mining, one of the major issues is the quality of genomic sequences. Most of the sequences in public databases are in draft form. Although incomplete genome sequences may be adequate for assembling many small, non-repetitive secondary metabolites smBGCs, they are unsuitable for large smBGCs like those encoding NRPS or type I PKS. These enzymes are typically involved in the biosynthesis of most compounds identified in drug discovery programs. Consequently, their encoding genes are often predicted to be scattered through several contigs, making challenging to identify the corresponding smBGCs (Baltz, 2021). Another drawback is that although powerful methods for the prediction of product structure from sequences exist, like antiSMASH (Blin et al., 2023), PRISM (Skinnider et al., 2020) or MIBiG (Terlouw et al., 2023) among others, they still have a relative high rate of false positives and generally are limited to identify smBGCs related to known ones. Moreover, once hypothetical smBGCs have been located, it remains a huge challenge to activate them. Additionally, predicting smBGCs is worthless without linking them to their final product and/or expected biological activities (Lee et al., 2020; Olano, Méndez, & Salas, 2014; Ren et al., 2017). On the other hand, it is interesting to note that although the new strategies developed in Streptomyces have shown the potential to discover pharmaceutically important drugs, they have not been successfully integrated into pharmaceutical company pipelines. This could be due to several factors, such as low throughput fermentation, challenges in natural product optimization, and declining return on investment (Baltz, 2021; Ward & Allenby, 2018). Miriam Rodríguez: Writing – original draft; writing – review and editing. Lorena Cuervo: Writing – original draft. Laura Prado-Alonso: Writing – original draft. María Soledad González-Moreno: Writing – original draft. Carlos Olano: Writing – review and editing; funding acquisition. Carmen Méndez: Writing – review and editing; funding acquisition. This work was granted by a grant from the Spanish Ministry of Science and Innovation (PID2020-113062RB-100) to CM, and by a grant from the Spanish Ministry of Science, Innovation, and Universities to CO (RTI2018-093562-B-I00). The authors declare no competing financial interest.

The genus Streptomyces is known to harbor numerous biosynthetic gene clusters (BGCs) of potential utility in synthetic biology applications. However, it is often difficult to link uncharacterized BGCs with the secondary metabolites they produce. Proteomining refers to the strategy of identifying active BGCs by correlating changes in protein expression with the production of secondary metabolites of interest. In this study, we devised a shotgun proteomics-based workflow to identify active BGCs during fermentation when a variety of compounds are being produced. Mycelia harvested during the non-producing growth phase served as the background. Proteins that were differentially expressed were clustered based on the proximity of the genes in the genome to highlight active BGCs systematically from label-free quantitative proteomics data. Our software tool is easy-to-use and requires only 1 point of comparison where natural product biosynthesis was significantly different. We tested our proteomining clustering method on three Streptomyces species producing different compounds. In Streptomyces coelicolor A3(2), we detected the BGCs of calcium-dependent antibiotic, actinorhodin, undecylprodigiosin, and coelimycin P1. In Streptomyces chrestomyceticus BCC24770, 7 BGCs were identified. Among them, we independently re-discovered the type II PKS for albofungin production previously identified by genome mining and tedious heterologous expression experiments. In Streptomyces tenebrarius, 5 BGCs were detected, including the known apramycin and tobramycin BGC as well as a newly discovered caerulomycin A BGC in this species. The production of caerulomycin A was confirmed by LC-MS and the inactivation of the caerulomycin A BGC surprisingly had a significant impact on the secondary metabolite regulation of S. tenebrarius. In conclusion, we developed an unbiased, high throughput proteomics-based method to complement genome mining methods for the identification of biosynthetic pathways in Streptomyces sp.

Actinomycetota have been widely described as valuable sources for the acquisition of secondary metabolites. Most microbial metabolites are produced via metabolic pathways encoded by biosynthetic gene clusters (BGCs). Although many secondary metabolites are not essential for the survival of bacteria, they play an important role in their adaptation and interactions within microbial communities. This is how bacteria isolated from extreme environments such as Antarctica could facilitate the discovery of new BGCs with biotechnological potential. This study aimed to isolate rare Actinomycetota strains from Antarctic soil and sediment samples and identify their metabolic potential based on genome mining and exploration of biosynthetic gene clusters. To this end, the strains were sequenced using Illumina and Oxford Nanopore Technologies platforms. The assemblies were annotated and subjected to phylogenetic analysis. Finally, the BGCs present in each genome were identified using the antiSMASH tool, and the biosynthetic diversity of the Micrococcaceae family was evaluated. Taxonomic annotation revealed that seven strains were new and two were previously reported in the NCBI database. Additionally, BGCs encoding type III polyketide synthases (T3PKS), beta-lactones, siderophores, and non-ribosomal peptide synthetases (NRPS) have been identified, among others. In addition, the sequence similarity network showed a predominant type of BGCs in the family Micrococcaceae, and some genera were distinctly grouped. The BGCs identified in the isolated strains could be associated with applications such as antimicrobials, anticancer agents, and plant growth promoters, among others, positioning them as excellent candidates for future biotechnological applications and innovations.Key points• Novel Antarctic rare Actinomycetota strains were isolated from soil and sediments• Genome-based taxonomic affiliation revealed seven potentially novel species• Genome mining showed metabolic potential for novel natural products

The genus Streptomyces have been highly regarded for their important source of natural products. Combined with the technology of genome sequencing and mining, we could identify the active ingredients from fermentation broth quickly. Here, we report on Streptomyces sp. strain fd1-xmd, which was isolated from a soil sample collected in Shanghai. Interestingly, the fermentation broth derived from this strain demonstrated broad-spectrum antimicrobial activity against gram-positive bacteria, gram-negative bacteria, and eukaryotes. To identify the antimicrobial substances and their biosynthetic gene clusters, we sequenced the fd1-xmd strain and obtained a genome 7,929,999bp in length. The average GC content of the chromosome was 72.5mol%. Knockout experiments demonstrated that out of eight biosynthetic gene clusters we could identify, two are responsible for the biosynthesis of the antibiotics streptothricin (ST) and tunicamycin (TM). The ST biosynthetic gene cluster from fd1-xmd was verified via successful heterologous expression in Streptomyces coelicolor M1146. ST production had a yield of up to 0.5g/L after the optimization of culture conditions. This study describes a novel producer of ST and TM and outlines the complete process undertaken for Streptomyces sp. strain fd1-xmd genome mining.

The genus Streptomyces is recognized as a source of secondary metabolites (SMs) with applications in medicine, industry, and agriculture. This study presents the description and characterization of a new Streptomyces species, isolated from sediments of the Madeira River in the Brazilian Amazon. Four strains (CPAA MAD 27, CPAA MAD 39, CPAA MAD 42, and CPAA MAD 51) were obtained from sampling sites distributed along the river. The strains were analyzed for morphological, phenotypic, and biochemical characteristics, as well as their potential for SM production using genome mining. Phylogenetic and phylogenomic analyses indicated that Streptomyces murinus is the most closely related species; however, the dDDH value of 55% and ANI of 94%, combined with biochemical analysis, support the proposal of the isolates as a new species, herein named Streptomyces amazonensis. This species exhibits adaptability to diverse environmental conditions, growing across a wide range of pH values (4–11) and temperatures (15–40 °C), with optimal growth at 35 °C and pH 8, and utilizing various carbon sources, including L-arabinose, unlike S. murinus. Genomic analysis revealed 39 to 46 biosynthetic gene clusters (BGCs) per strain, related to polyketides, nonribosomal peptides, and ribosomally synthesized and post-translationally modified peptides (RiPPs). Notably, BGCs showed high similarity to thioligamide (antitumor) and tetracenomycin (antibiotic) metabolites. Additionally, numerous BGCs with matches in the MIBiG database were identified, suggesting genomic potential related to the biosynthesis of molecules of scientific interest. This discovery expands our understanding of Amazonian microbial diversity and offers new prospects for the bioprospecting of natural products, highlighted by the unexplored biosynthetic potential of S. amazonensis for the development of new natural compounds.

In silico genome mining of potential novel biosynthetic gene clusters for drug discovery from Burkholderia bacteria

BackgroundStreptomyces is renowned for its robust biosynthetic capacity in producing medically relevant natural products. However, the majority of natural products biosynthetic gene clusters (BGCs) either yield low amounts of natural products or remain cryptic under standard laboratory conditions. Various heterologous production hosts have been engineered to address these challenges, and yet the successful activation of BGCs has still been limited. In our search for a valuable addition to the heterologous host panel, we identified the strain Streptomyces sp. A4420, which exhibited rapid initial growth and a high metabolic capacity, prompting further exploration of its potential.ResultsWe engineered a polyketide-focused chassis strain based on Streptomyces sp. A4420 (CH strain) by deleting 9 native polyketide BGCs. The resulting metabolically simplified organism exhibited consistent sporulation and growth, surpassing the performance of most existing Streptomyces based chassis strains in standard liquid growth media. Four distinct polyketide BGCs were chosen and expressed in various heterologous hosts, including the Streptomyces sp. A4420 wild-type and CH strains, alongside Streptomyces coelicolor M1152, Streptomyces lividans TK24, Streptomyces albus J1074, and Streptomyces venezuelae NRRL B-65442. Remarkably, only the Streptomyces sp. A4420 CH strain demonstrated the capability to produce all metabolites under every condition outperforming its parental strain and other tested organisms. To enhance visualization and comparison of the tested strains, we developed a matrix-like analysis involving 15 parameters. This comprehensive analysis unequivocally illustrated the significant potential of the new strain to become a popular heterologous host.ConclusionOur engineered Streptomyces sp. A4420 CH strain exhibits promising attributes for the heterologous expression of natural products with a focus on polyketides, offering an alternative choice in the arsenal of heterologous production strains. As genomics and cloning strategies progress, establishment of a diverse panel of heterologous production hosts will be crucial for expediting the discovery and production of medically relevant natural products derived from Streptomyces.

Streptomyces strains are known for their capability to produce a lot of different compounds with various bioactivities. Cultivation under different conditions often leads to the production of new compounds. Therefore, production cultures of the strains are extracted with ethyl acetate and the crude extracts are analyzed by HPLC. Furthermore, the extracts are tested for their bioactivity by different assays. For structure elucidation the compound of interest is purified by a combination of different chromatography methods.Genome sequencing coupled with genome mining allows the identification of a natural product biosynthetic gene cluster using different computer programs. To confirm that the correct gene cluster has been identified, gene inactivation experiments have to be performed. The resulting mutants are analyzed for the production of the particular natural product. Once the correct gene cluster has been inactivated, the strain should fail to produce the compound.The workflow is shown for the antibacterial compound polyketomycin produced by Streptomyces diastatochromogenes Tü6028. Around ten years ago, when genome sequencing was still very expensive, the cloning and identification of a gene cluster was a very time-consuming process. Fast genome sequencing combined with genome mining accelerates the trial of cluster identification and opens up new ways to explore biosynthesis and to generate novel natural products by genetic methods. The protocol described in this paper can be assigned to any other compound derived from a Streptomyces strain or another microorganism.

Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways. Microbial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including streptothricins, borrelidin, two novel lipopeptides, and one unknown antibiotic from Streptomyces rochei Sal35. The transfer, expression, and screening of the library were all performed in a high-throughput way, so that this approach is scalable and adaptable to industrial automation for next-generation antibiotic discovery.

Genome mining is revolutionizing natural products discovery efforts. The rapid increase in available genomes demands comprehensive computational platforms to effectively extract biosynthetic knowledge encoded across bacterial pangenomes. Here, we present BGCFlow, a novel systematic workflow integrating analytics for large-scale genome mining of bacterial pangenomes. BGCFlow incorporates several genome analytics and mining tools grouped into five common stages of analysis such as:(i) data selection, (ii) functional annotation, (iii) phylogenetic analysis, (iv) genome mining, and (v) comparative analysis. Furthermore, BGCFlow provides easy configuration of different projects, parallel distribution, scheduled job monitoring, an interactive database to visualize tables, exploratory Jupyter Notebooks, and customized reports. Here, we demonstrate the application of BGCFlow by investigating the phylogenetic distribution of various biosynthetic gene clusters detected across 42 genomes of the Saccharopolyspora genus, known to produce industrially important secondary/specialized metabolites. The BGCFlow-guided analysis predicted more accurate dereplication of BGCs and guided the targeted comparative analysis of selected RiPPs. The scalable, interoperable, adaptable, re-entrant,and reproducible nature of the BGCFlow will provide an effective novel way to extract the biosynthetic knowledge fromthe ever-growing genomic datasets of biotechnologically relevant bacterial species.

The genome sequencing and mining of microorganisms from unexplored and extreme environments has become important in the process of identifying novel biosynthetic pathways. In the present study, the biosynthetic potential of Paenibacillus sp. strains 23TSA30-6 and 28ISP30-2 was investigated. Both strains were isolated from the deep oligotrophic Krubera-Voronja Cave and were found to be highly active against both Gram-positive and Gram-negative bacteria. Genome mining revealed a high number of biosynthetic gene clusters in the cave strains: 21 for strain 23TSA30-6 and 19 for strain 28ISP30-2. Single clusters encoding the biosynthesis of phosphonate, terpene, and siderophore, as well as a single trans-AT polyketide synthase/non-ribosomal peptide synthetase, were identified in both genomes. The most numerous clusters were assigned to the biosynthetic pathways of non-ribosomal peptides and ribosomally synthesized and post-translationally modified peptides. Although four non-ribosomal peptide synthetase gene clusters were predicted to be involved in the biosynthesis of known compounds (fusaricidin, polymyxin B, colistin A, and tridecaptin) of the genus Paenibacillus, discrepancies in the structural organization of the clusters, as well as in the substrate specificity of some adenylation domains, were detected between the reference pathways and the clusters in our study. Among the clusters involved in the biosynthesis of ribosomally synthesized peptides, only one was predicted to be involved in the biosynthesis of a known compound: paenicidin B. Most biosynthetic gene clusters in the genomes of the cave strains showed a low similarity with the reference pathways and were predicted to represent novel biosynthetic pathways. In addition, the cave strains differed in their potential to encode the biosynthesis of a few unique, previously unknown compounds (class II lanthipeptides and three non-ribosomal peptides). The phenotypic characterization of proteinaceous and volatile compounds produced by strains 23TSA30-6 and 28ISP30-2 was also performed, and the results were compared with those of genome mining.

By culturing microorganisms under standard laboratory conditions, most biosynthetic gene clusters (BGCs) are not expressed, and thus, the products are not produced. To explore this biosynthetic potential, we developed a novel “semi-targeted” approach focusing on activating “silent” BGCs by concurrently introducing a group of regulator genes into streptomycetes of the Tübingen strain collection. We constructed integrative plasmids containing two classes of regulatory genes under the control of the constitutive promoter ermE*p (cluster situated regulators (CSR) and Streptomyces antibiotic regulatory proteins (SARPs)). These plasmids were introduced into Streptomyces sp. TÜ17, Streptomyces sp. TÜ10 and Streptomyces sp. TÜ102. Introduction of the CSRs-plasmid into strain S. sp. TÜ17 activated the production of mayamycin A. By using the individual regulator genes, we proved that Aur1P, was responsible for the activation. In strain S. sp. TÜ102, the introduction of the SARP-plasmid triggered the production of a chartreusin-like compound. Insertion of the CSRs-plasmid into strain S. sp. TÜ10 resulted in activating the warkmycin-BGC. In both recombinants, activation of the BGCs was only possible through the simultaneous expression of aur1PR3 and griR in S. sp. TÜ102 and aur1P and pntR in of S. sp. TÜ10.

The exploration of microbial genomes through next-generation sequencing (NGS) and genome mining has transformed the discovery of natural products, revealing an immense reservoir of previously untapped chemical diversity. Bacteria remain a prolific source of specialized metabolites with potential applications in medicine and biotechnology. Here, we present a protocol to access novel biosynthetic gene clusters (BGCs) that encode natural products from soil bacteria. The protocol uses a combination of Oxford Nanopore Technology (ONT) sequencing, de novo genome assembly, antiSMASH for BGC identification, and transformation-associated recombination (TAR) for cloning the BGCs. We used this protocol to allow the detection of large BGCs at a relatively fast and low-cost DNA sequencing. The protocol can be applied to diverse bacteria, provided that sufficient high-molecular-weight DNA can be obtained for long-read sequencing. Moreover, this protocol enables subsequent cloning of uncharacterized BGCs into a genome engineering-ready vector, illustrating the capabilities of this powerful and cost-effective strategy.Key features• This protocol enables bioprospection through cloning of a novel BGC identified in an ONT bacterial draft genome.• A combination of ONT sequencing, antiSMASH, and TAR cloning can be used to clone BGCs from bacteria into a vector.• Cost-effective strategy for the discovery of BGCs of diverse natural product classes, including nonribosomal peptides, polyketides, and RiPPs.• Overnight sequencing in-house using cheap and easy-to-use instruments such as MinION, which allows multiplexing.

Microbial natural products are a cornerstone of drug discovery, offering structurally diverse molecules with potent biological activities. Historically, soil-derived Actinobacteria have been the primary source of clinically relevant antibiotics, yet rising multidrug resistance and the redundancy of terrestrial compounds have necessitated exploration of alternative environments, particularly marine ecosystems. Marine Actinomycetes and fungi have emerged as prolific producers of novel metabolites, including compounds with antibacterial, antifungal, anticancer, and anti-inflammatory activities. Cyanobacteria and microalgae further expand the chemical repertoire by producing unique bioactive metabolites and high-value nutraceuticals. Despite this potential, the majority of microbial biodiversity remains uncultured due to the “Great Plate Count Anomaly,” and many biosynthetic gene clusters are silent under standard laboratory conditions. Innovative approaches such as One Strain Many Compounds (OSMAC), co-cultivation, genome mining, metabologenomics, and molecular networking have improved access to these cryptic metabolites. Additionally, in situ cultivation techniques, high-throughput screening, and synthetic biology enable the discovery and optimization of bioactive molecules with therapeutic potential. This systematic review and meta-analysis synthesize current literature to evaluate the strategies used in microbial natural product discovery, highlighting both ecological and technological approaches that maximize chemical diversity. By integrating cultivation-based, genomic, and bioinformatic methodologies, researchers can systematically exploit microbial resources, reduce redundancy, and accelerate the identification of novel compounds. The findings underscore the immense untapped potential within microbial communities and provide a roadmap for future biodiscovery initiatives aimed at combating multidrug-resistant pathogens and advancing therapeutic development.

The urgent need for new antimicrobials arises from antimicrobial resistance. Actinobacteria, especially Streptomyces genus, are responsible for production of numerous clinical antibiotics and anticancer agents. Genome mining reveals the biosynthetic gene clusters (BGCs) related to secondary metabolites and the genetic potential of a strain to produce natural products. However, this potential may not be expressed under laboratory conditions. In the present study, the Antarctic bacterium was taxonomically affiliated as Streptomyces albidoflavus ANT_B131 (CBMAI 1855). The crude extracts showed antimicrobial activity against both fungi, Gram-positive and Gram-negative bacteria and antiproliferative activity against five human tumor cell lines. Whole-genome sequencing reveals a genome size of 6.96Mb, and the genome mining identified 24 BGCs, representing 13.3% of the genome. The use of three culture media and three extraction methods reveals the expression and recovery of 20.8% of the BGCs. The natural products identified included compounds, such as surugamide A, surugamide D, desferrioxamine B + Al, desferrioxamine E, and ectoine. This study reveals the potential of S. albidoflavus ANT_B131 as a natural product producer. Yet, the diversity of culture media and extraction methods could enhance the BGCs expression and recovery of natural products, and could be a strategy to intensify the BGC expression of natural products.