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Molecular biology and integrated strategies for activating cryptic biosynthetic gene clusters toward next-generation antibiotic discovery.

Antimicrobial resistance (AMR) has been identified as one of the 21st century's severest global public health crises. AMR led to an estimated 4.95 million deaths in 2019 and will claim 10 million lives a year by 2050 in the absence of targeted interventions. During the same period, the number of novel antibiotics discovered has decreased drastically as many researchers are rediscovering known antibiotics, non-model microorganisms are poorly understood or difficult to culture and antibiotic research and development investment has declined drastically. However, high-throughput whole genome sequencing and the subsequent application of bioinformatics in bacterial and fungal genomes have shown that a numerous of cryptic or silent biosynthetic gene clusters (BGCs) remain latent at ambient laboratory conditions since their genes are transcriptionally inactive. Cryptic BGCs represent a vast source of unique secondary metabolites, many of which may yield novel antibacterial, antifungal, anti-cancer and other potentially valuable natural products. This review discusses the biological relevance of cryptic BGCs, the major limiting factors that restricts their activation and novel strategies that have been employed to activate them and exploit their potential to produce novel natural products. The review focuses on biological approaches including CRISPR-Cas mediation for the activation of cryptic BGCs, promoter engineering, pathway refactoring, and heterologous expression; biochemical strategies such as Osman, OsMAC, Precursor Feeding, Chemical Elicitation, Epigenetic Regulation and Co-cultivation and technology-based strategies such as Genome mining, Microfluidic Cultivation systems, High-Throughput Screening, Metabolomics, Molecular Networking and Artificial Intelligence and Machine Learning based prediction of BGCs and their metabolites. The use of multi-omics technologies combined with synthetic biology to achieve better discovery, characterization and large-scale production of novel natural products is also discussed herein. Finally, we will talk about the ecological significance and evolutionary advantage of cryptic BGCs' role in interactions between microorganisms, such as competition, communication, symbiosis and environmental adaptability, so as to provide a useful background for accelerating next-generation antibiotics.

CRISPR-Cas activation

Genetic background of neurological disorders with basal ganglia calcification.

BACKGROUND: Bilateral basal ganglia calcifications (BGCs), if severe, are known hallmarks for idiopathic BGC disease (IBGC), but if milder, are often considered radiological findings of unknown significance. In previous studies, only a minority of patients with BGC had monogenic forms of IBGC. METHODS: We studied consecutive patients from a tertiary neurology clinic with bilateral BGCs of variable severity, and their families. We analyzed known IBGC genes, and an extended panel of genes linked to monogenic stroke and metabolic conditions. Clinical, radiological, and genetic data were collected, including vascular risk factors, cerebrovascular events, imaging findings (total calcification score, white matter hyperintensities, ischemic/hemorrhagic lesions), and relevant family history. RESULTS: Twenty-four families with BGCs and neurological symptoms were analyzed. Disease-causing variants were identified in 14 families (58.3%). Eight patients had IBGC (variants in SLC20A2, PDGFB, MYORG), 4 had mitochondrial disease (MT-TL1), and 2 had monogenic vascular conditions (GAL, MAP3K6). Three variants were novel. BGC severity was highest in IBGC cases, while vascular and mitochondrial cases had milder calcifications. White matter hyperintensities were seen in 94.7% of cases and correlated highly with the total calcification score. Clinical vascular events had occurred in 41.7% cases. No monogenic cause was found in 10 patients, although many of these showed clinical or radiological features suggestive of monogenic disease. CONCLUSIONS: Bilateral BGCs can occur in many neurogenetic disorders apart from IBGCs, and a broader genetic search increases the diagnostic yield. Patients with BGCs frequently had clinical cerebrovascular events, which emphasizes the role of cerebrovascular pathology in BGCs.

Humans

Phyllosphere microbiomes in grassland plants harbor a vast reservoir of novel antimicrobial peptides and biosynthetic diversity.

INTRODUCTION: The phyllosphere microorganisms colonizing plant surface harbor capacities to synthesize diverse specialized metabolites that mediate communication and interactions with environment and host. However, most known metabolites are derived from a few culturable microorganisms, and the genomic diversity and biosynthetic potential of the vast majority of bacteria associated with plants remain largely unexplored. OBJECTIVES: Here, we aim to explore the genome architecture, biosynthetic ability, and host specific adaptability of grassland ecosystems, uncovering new perspectives on grassland phyllosphere microbial resources. METHODS: We employed ultra-deep metagenomic sequencing, functional analysis, host-associated characterization, and bioactivity assays to explore the phyllosphere microbiome across 221 grassland plant samples representing 45 families. This approach revealed host preference in biosynthetic gene clusters (BGCs) and validated the antimicrobial efficacy of phyllosphere-derived antimicrobial peptides (AMPs). RESULTS: Grassland plant phyllosphere microbiomes encode diverse BGCs. We identified 885,396 potential AMPs from over 68 million non-redundant gene sequences. Then, we reconstructed hundreds of near-complete genomes from phyllosphere metagenomes, and 32.61 % of reconstructed genomes were identified as unclassified genomes, primarily within Pseudomonadota, Actinomycetota, Bacillota and Bacteroidota phyla. Of the near-complete genomes, 91.97 % of the BGCs and 99.76 % of the identified AMPs were previously uncharacterized. Host phylogenetic analysis revealed functional divergence. Poaceae-associated Pseudomonas genomes contain an average of 28 BGCs, significantly higher than those in Asteraceae-associated genomes (mean = 14.76, P = 0.033). Similarly, Poaceae-associated Pantoea genomes carried an average of 9 BGCs, exhibiting significant enrichment compared to genomes from Asteraceae (mean = 7.13, P = 6.1e-05), Lamiaceae (mean = 7, P = 0.015), Ranunculaceae (mean = 8.22, P = 0.0053), and Rosaceae (mean = 7.75, P = 0.00069). ParaFit analyses further confirmed that host phylogeny significantly structures microbial functional repertoires, with intra-family hosts sharing more KEGG pathways than inter-family hosts. These results suggest that host evolutionary relationships are associated with metabolic specialization in phyllosphere microbiomes. All 13 AMPs synthesized via solid-phase peptide synthesis demonstrated antimicrobial activity, inhibiting the growth of at least one tested bacterial strain. CONCLUSION: This study demonstrates the promise of grassland plant phyllosphere microbiome as a rich source for novel antimicrobial agents.

Antimicrobial Peptides

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

Biosynthetic potential of the culturable foliar fungi associated with field-grown lettuce.

Fungal endophytes and epiphytes associated with plant leaves can play important ecological roles through the production of specialized metabolites encoded by biosynthetic gene clusters (BGCs). However, their functional capacity, especially in crops like lettuce (Lactuca sativa L.), remains poorly understood. We sequenced the genomes of nine fungal isolates, representing Fusarium sp., Fulvia sp., Alternaria alternata, and Alternaria postmessia, from leaves of lettuce grown under field conditions in Arizona, USA. We used antibiotics and secondary metabolite analysis shell (antiSMASH) and the database for automated carbohydrate-active enzyme annotation (dbCAN3), to predict BGCs and carbohydrate-active enzymes (CAZymes) for each strain, and then compared them to conspecific strains from other environments and substrates. Foliar lettuce-associated fungi featured 39-95 BGCs per genome, with substantial overlap between isolates occurring in association with lettuce leaves vs. from other substrates. Species identity was a significant determinant of BGC count, while host type, isolation source, and lifestyle were not. Several BGCs, including those for alternariol and 1,3,6,8-Tetrahydroxynaphthalene (T4HN), showed 100% similarity to characterized minimum information about a biosynthetic gene cluster (MIBiG) clusters based on antiSMASH predictions. Although analysis by biosynthetic gene similarity clustering and prospecting engine (BiG-SCAPE) identified gene cluster families (GCFs) across the dataset, these reference-matching clusters were not always grouped, reflecting methodological differences in how the tools assess similarity. Comparative CAZyme analysis in a focal species (Fulvia sp.) revealed higher gene counts in a foliar lettuce-derived isolate than in tomato (Solanum lycopersicum)-associated strains, challenging assumptions about host chemical complexity. These results highlight the importance of phylogenetic context in shaping fungal functional potential and suggest that selection on microbial traits in edible leafy crops may be more subtle and species-specific than previously assumed. KEY POINTS: • Lettuce-associated fungi feature diverse biosynthetic potential • Phylogeny predicts fungal BGC content more strongly than ecological lifestyle • Findings support genome-informed microbiome strategies for leafy crops.

Lactuca

Benchmarking methods for measuring biosynthetic gene cluster similarity and determination of gene cluster families.

MOTIVATION: Natural products are often produced by a set of biosynthetic enzymes that are encoded by genes clustered together in the producer's genome, referred to as a biosynthetic gene cluster (BGC). The ability to compare and cluster BGCs is essential for several applications, including predicting which bacteria will make a known product and assessing the potential diversity of natural products produced by a set of bacteria. There are multiple methods for comparing and clustering BGCs based on their similarity, but there has been a lack of investigation into how strongly BGC similarity relates to product structural similarity and how these methods perform relative to each other. RESULTS: Using publicly available databases, we developed a benchmark dataset to assess how well different BGC similarity metrics correlate with the structural similarity of their products and how well these methods cluster BGCs. We found that all methods showed moderate correlation between BGC and structural similarity, with correlations improving for more similar BGCs and varying significantly by BGC biosynthetic class. Analysis of outliers revealed some outliers were due to mistakes or omissions in public datasets, while others represented deviation between BGC similarity and product structural similarity. All methods generally performed better on clustering metrics, with BiG-SCAPE performing the best after errors in the public datasets had been corrected. AVAILABILITY AND IMPLEMENTATION: Scripts and data required to reproduce the results are available at https://github.com/aswalker-lab/BGC-clustering-benchmark and processed similarity, clusters, and scaffolds are also available at https://huggingface.co/datasets/allie-walker/BGC-clustering-benchmark. Code is also available at Zenodo: 10.5281/zenodo.17373546.

Multigene Family

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

A novel biocontrol Pseudomonas species with broad-spectrum antagonistic activity against phytopathogens.

Bacterial and fungal diseases cause significant losses in horticultural crops, and biocontrol using beneficial microorganisms offers a sustainable alternative to chemical pesticides. In this study, a novel Pseudomonas strain D3 was isolated from Actinidiae rhizosphere. D3 exhibited strong antibacterial activity in LB medium but showed no activity against fungi or oomycetes. However, when cultured in KIDO medium, it demonstrated potent antifungal activity. Phylogenetic analysis based on 16S rRNA gene showed that D3 was most closely related to Pseudomonas mosselii CIP_105259T, while whole-genome sequencing revealed ANI values below 95% with eight known P. mosselii strains. Digital DNA-DNA hybridization (dDDH) further confirmed its genomic distinctiveness, with the highest dDDH value (58.2%) against the type strain P. mosselii DSM 17497T, well below the 70% species delineation threshold, supporting D3 as a novel Pseudomonas species. Functional validation via targeted gene knockout revealed a dichotomy in the antagonistic mechanisms of D3. Knockout of individual biosynthetic gene clusters (BGCs) only partially reduced antibacterial activity against Pseudomonas syringae pv. actinidiae, indicating that multiple BGCs contribute to this activity in a partially redundant manner. In contrast, disruption of a specific lipopeptide synthase cluster completely abolished antifungal activity against Valsa mali. LC-MS/MS analysis confirmed that this lipopeptide was produced exclusively in KIDO medium, consistent with the observed medium-dependent antifungal activity. Detached leaf and twig assays showed that D3 provides strong preventive biocontrol against both pathogens. Collectively, strain D3 employs a dual biocontrol mechanism, combining antibacterial activity mediated by multiple BGCs with lipopeptide-dependent antifungal activity, positioning it as a promising agent for sustainable disease management in horticultural crops.

Pseudomonas

Multichassis Expression of Cyanobacterial and Other Bacterial Biosynthetic Gene Clusters.

Heterologous expression of biosynthetic gene clusters (BGCs) is a powerful strategy for natural product (NP) discovery, yet achieving consistent expression across microbial hosts remains challenging. Here, we developed cross-phyla vector systems enabling the expression of BGCs from cyanobacteria and other bacterial origins in Gram-negative Escherichia coli, Gram-positive Bacillus subtilis, and two model cyanobacterial strains including unicellular Synechocystis PCC 6803 and filamentous Anabaena sp. PCC 7120. Following validation using constitutive and inducible expression of the enhanced yellow fluorescent protein (eYFP), we applied these vectors to express the shinorine and violacein BGCs in all four hosts. Promoter tuning, substrate feeding, BGC refactoring, and inducible control enhanced NP production and mitigated host toxicity. Notably, we demonstrated that B. subtilis can serve as a chassis for cyanobacterial NP BGC expression. Our results provide versatile expression platforms for probing BGC function and accelerating natural product discovery from diverse cyanobacterial and other bacterial lineages.

Multigene Family

Nerpa 2: probabilistic linking of biosynthetic gene clusters to nonribosomal peptides.

MOTIVATION: Nonribosomal peptides (NRPs) are bioactive microbial metabolites with high pharmaceutical potential. Although genome mining enables large-scale detection of biosynthetic gene clusters (BGCs) predicted to encode NRPs, reliably linking these clusters to their chemical products remains challenging due to the flexible and heterogeneous organization of NRP assembly pathways. RESULTS: We present Nerpa 2, a probabilistic framework for accurate and scalable linking of NRP BGCs to candidate chemical structures. The method represents assembly lines as hidden Markov models (HMMs) that capture uncertainty and alternative biosynthetic routes. On curated datasets of experimentally validated BGC-product pairs, our tool outperforms existing methods in linking accuracy and pathway reconstruction. When applied to large genome mining datasets, Nerpa 2 efficiently identifies BGCs likely associated with known compounds and highlights potential producers of novel chemistry. AVAILABILITY AND IMPLEMENTATION: Nerpa 2 is freely available at https://github.com/gurevichlab/nerpa.

Multigene Family

Fine-grained structural classification of biosynthetic gene cluster-encoded products.

MOTIVATION: Biosynthetic gene clusters (BGCs) are responsible the biosynthesis of many natural products, including a multitude of effective therapeutics and their precursors. Advances in genomic data collection as well as computational techniques have made it possible to identify BGCs at scale. However, accurately determining the types of BGC-encoded products from genomic content remains elusive. RESULTS: Here, we introduce BGC annotation tool (BGCat), a machine learning method for fine-grained structural classification of BGC-encoded products, leveraging the NPClassifier natural product nomenclature. Our method leverages a pre-trained protein language model for creating meaningful gene representations and a deep neural network for class label prediction. We show the method outperforms state-of-the-art approaches in coarse-grained product classification and is effective for detailed classification. We implement a clustering-based augmentation strategy for BGC-product relationships, addressing a crucial gap in the available datasets. We then introduce the concept of product class profiles of gene cluster families (GCFs), associating each GCF with a probabilistic distribution of product types and offering a new perspective on GCF functions. Lastly, we use BGCat to provide new product class labels for over 100k BGCs in antiSMASH DB that presently have minimal information about their products. AVAILABILITY AND IMPLEMENTATION: The source code and trained model weights are freely available at https://github.com/HassounLab/BGCat.

Multigene Family

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

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

Genome-Guided Discovery of Antimalarial 4-Amino-2,4-Pentadienoate-Containing Cyclolipodepsipeptides.

4-Amino-2,4-pentadienoate-containing cyclolipodepsipeptides (APD-CLDs) represent a structurally distinctive family of natural products known for their selective activity against hypoxic cancer cells. To explore the structural diversity of APD-CLDs, we have identified and prioritized cryptic APD-CLD biosynthetic gene clusters (BGCs) for compound discovery. Using a combination of genetic and chemical methods, we successfully activated three dormant BGCs, leading to the discovery of 12 new APD-CLDs. These newly discovered metabolites significantly expanded the diversity of the APD-CLD family, with chloromalamides and arabimalamides representing the first halogenated and glycosylated members, respectively. Unexpectedly, chloromalamides and arabimalamides exhibited potent antiplasmodial activity, with IC50 values in the 25-161 nM range against drug-sensitive and multidrug-resistant Plasmodium falciparum strains. Phenotypic studies revealed arabimalamide B halted parasite development during the asexual blood stage life cycle, resulting in enlarged digestive vacuoles, dispersed hemozoin, and ultimately reduced reinvasion efficiency. These phenotypes are reminiscent of the effect of chloroquine and other 4-aminoquinoline drugs, suggesting that arabimalamides may disrupt the parasite's heme detoxification mechanism. Biosynthetic studies identified key scaffold-forming and modifying enzymes, including a rare membrane glycosyltransferase in arabimalamide biosynthesis. Together, these findings unveil APD-CLDs as new antimalarial lead scaffolds and set the stage for structural diversification and optimization.

Antimalarials

Deciphering the Function and Structure of PA1216 as an S-Adenosyl-l-Methionine Binding Protein Using Differential Scanning Fluorimetry and Circular Dichroism.

Microbes produce bioactive secondary metabolites as toxins, pigments, or virulence factors. These specialized compounds are produced by nonribosomal peptide synthetases (NRPS), polyketide synthases (PKS), or hybrid NRPS/PKS pathways. The genes encoding NRPS and PKS reside in biosynthetic gene clusters (BGCs), some of which have no identified metabolite associated with them. Characterization of these orphan BGCs could provide insights into potential bioactive compounds that have yet to be discovered. Here, we characterize PA1216, a putative methyltransferase embedded within an NRPS BGC in Pseudomonas aeruginosa strain PAO1. We cloned, expressed, and purified PA1216, and developed an optimized differential scanning fluorimetry assay to measure its thermal stability, demonstrating concentration-dependent stabilization in the presence of established methyltransferase cofactors and inhibitors. We then adapted this assay for high-throughput screening of potential PA1216 substrates, identifying destabilizing compounds, including glycyl-glycine dipeptides, amino esters with aromatic or basic side chains, and N-Boc-protected amino acids. In contrast, sodium salts of organic acids stabilized PA1216. Lastly, we employed AlphaFold to construct a predictive model, revealing that PA1216 contains a Rossmann-like fold and a glycine-rich loop, typical of class I methyltransferases, and we corroborated these secondary structural elements using circular dichroism spectroscopy. Overall, these studies illuminate PA1216 function and establish a platform for characterizing cryptic gene clusters within secondary metabolic pathways.

Circular Dichroism

South African Myxococcota: an untapped resource for microbial ecolo gy and biotechnology.

An extraordinary multicellular life cycle, ecological versatility, and prolific production of bioactive secondary metabolites characterise the phylum Myxococcota. While research has predominantly focused on Myxococcota in Asia, Europe, and North America, their potential occurrence in Sub-Saharan Africa remains largely unexplored. To date, only one study has isolated Myxococcota in South Africa, with additional findings limited to incidental detection through metagenomic studies. Considering South Africa's ecological diversity, its biomes may represent promising but under-examined environments for systematic bioprospecting aimed at discovering novel Myxococcota with ecological or biotechnological potential. The recent reclassification of Myxococcota from the former Deltaproteobacteria has provided a more coherent taxonomic framework to guide future ecological and systematic studies. This review presents an overview of the taxonomic revision and explores the potential occurrence of Myxococcota in South African biomes. It covers the challenges associated with conventional culture-based isolation methods and highlights potential genome- and metagenome-based approaches, including the use of metagenome-assembled genomes (MAGs) to identify cryptic biosynthetic gene clusters (BGCs), while acknowledging current limitations. Considering the increasing resistance to chemical fungicides in South African agriculture, this review further explores the potential of Myxococcota-derived secondary metabolites as candidate bioprotective alternatives. By identifying current research gaps, it aims to support future efforts towards systematic bioprospecting to investigate the ecological and biotechnological potential of Myxococcota in South Africa. KEY POINTS: • South African biomes may harbour novel Myxococcota with biosynthetic potential. • Genome mining could reveal cryptic biosynthetic gene clusters (BGCs). • Myxococcota metabolites may help control resistant fungal phytopathogens.

South Africa

Comparative Genomics of Paenibacillus Secondary Metabolism: Unveiling the Putative Biosynthetic Gene Cluster for Paenialvins in Paenibacillus Alvei Strain 32.

In this study, we used comparative genomics and culture-based methods to investigate Biosynthetic Gene Clusters (BGCs) responsible for the production of antimicrobial peptides. Paenibacillus alvei strain 32 was isolated from a cystic fibrosis sputum. Its genome was sequenced using Illumina, showing a size of 6,584,590 bp with 239 contigs assembled in 26 scaffolds, an average coverage of 243X, and 6,832 coding sequences. ANI analysis and in silico DNA-DNA hybridization showed its affiliation inside Paenibacillus alvei, with a clear separation from other related strains, leading us to propose a distinct species-level genomic clade (genomospecies) within this group. AntiSMASH analysis predicted 22 putative BGCs in the genome of strain 32. Its culture supernatant exhibited inhibitory activity against Gram-positive pathogens, including methicillin-resistant Staphylococcus aureus (MRSA), Bacillus cereus, and Enterococcus faecalis. By comparing in silico BGC predictions with activities described in the literature, we propose that strain 32 harbours a specific 110-kb cluster (cluster 6.2) with five non-ribosomal peptide synthetase (NRPS) genes. These synthetases are predicted to direct the assembly of a 16-amino acid backbone that correlates with the structure of paenialvins, which are known anti-MRSA molecules. This study describes the putative biosynthetic pathway of the paenialvins and explains structural variations, bringing useful data on Paenibacillus secondary metabolism for future antibiotic development.

Paenibacillus alvei

Natural product discovery in soil actinomycetes: unlocking their potential within an ecological context.

Natural products (NPs) produced by bacteria, particularly soil actinomycetes, often possess diverse bioactivities and play a crucial role in human health, agriculture, and biotechnology. Soil actinomycete genomes contain a vast number of predicted biosynthetic gene clusters (BGCs) yet to be exploited. Understanding the factors governing NP production in an ecological context and activating cryptic and silent BGCs in soil actinomycetes will provide researchers with a wealth of molecules with potential novel applications. Here, we highlight recent advances in NP discovery strategies employing ecology-inspired approaches and discuss the importance of understanding the environmental signals responsible for activation of NP production, particularly in a soil microbial community context, as well as the challenges that remain.

Soil Microbiology