Bacterial secondary metabolites are rich sources of novel drug leads. The diversity of secondary metabolite biosynthetic gene clusters (BGCs) in genomesequenced bacteria, which will provide crucial information for the efficient discovery of novel natural products, has not been systematically investigated.Here, the distribution and genetic diversity of BGCs in 10 121 prokaryotic genomes (across 68 phyla) were obtained from their PRISM4 outputs using a custom python script. A total of 18 043 BGCs are detected from 5743 genomes with non-ribosomal peptide synthetases (25.4%) and polyketides (15.9%) as the dominant classes of BGCs. Bacterial strains harbouring the largest number of BGCs are revealed and BGC count in strains of some genera vary greatly, suggesting the necessity of individually evaluating the secondary metabolism potential. Additional analysis against 102 strains of discovered bacterial genera with abundant amounts of BGCs confirms that Kutzneria, Kibdelosporangium, Moorea, Saccharothrix, Cystobacter, Archangium, Actinosynnema, Kitasatospora, and Nocardia, may also be important sources of natural products and worthy of priority investigation. Comparative analysis of BGCs within these genera indicates the great diversity and novelty of the BGCs. This study presents an atlas of bacterial secondary metabolite BGCs that provides a lot of key information for the targeted discovery of novel natural products.

No abstract

Background Marine prokaryotes are a rich source of novel bioactive secondary metabolites for drug discovery. Recent genome mining studies have revealed their great potential to bio-synthesize novel secondary metabolites. However, the exact biosynthetic chemical space encoded by the marine prokaryotes has yet to be systematically evaluated. Results We first investigated the secondary metabolic potential of marine prokaryotes by analyzing the diversity and novelty of the biosynthetic gene clusters (BGCs) in 7541 prokaryotic genomes from cultivated and single cells, along with 26,363 newly assembled medium-to-high-quality genomes from marine environmental samples. To quantitatively evaluate the unexplored biosynthetic chemical space of marine prokaryotes, the clustering thresholds for constructing the biosynthetic gene cluster and molecular networks were optimized to reach a similar level of the chemical similarity between the gene cluster family (GCF)-encoded metabolites and molecular family (MF) scaffolds using the MIBiG database. The global genome mining analysis demonstrated that the predicted 70,011 BGCs were organized into 24,536 mostly new (99.5%) GCFs, while the reported marine prokaryotic natural products were only classified into 778 MFs at the optimized clustering thresholds. The number of MF scaffolds is only 3.2% of the number of GCF-encoded scaffolds, suggesting that at least 96.8% of the secondary metabolic potential in marine prokaryotes is untapped. The unexplored biosynthetic chemical space of marine prokaryotes was illustrated by the 88 potential novel antimicrobial peptides encoded by ribosomally synthesized and post-translationally modified peptide BGCs. Furthermore, a sea-water-derived Aquimarina strain was selected to illustrate the diverse biosynthetic chemical space through untargeted metabolomics and genomics approaches, which identified the potential biosynthetic pathways of a group of novel polyketides and two known compounds (didemnilactone B and macrolactin A 15-ketone). Conclusions The present bioinformatics and cheminformatics analyses highlight the promising potential to explore the biosynthetic chemical diversity of marine prokaryotes and provide valuable knowledge for the targeted discovery and biosynthesis of novel marine prokaryotic natural products.

Photorhabdus, the symbiotic bacteria of Heterorhabditis nematodes, has been reported to possess many non‐ribosomal peptide synthetase (NRPS) biosynthesis gene clusters (BGCs). To provide an in‐depth assessment of the non‐ribosomal peptide biosynthetic potential of Photorhabdus, we compared the distribution of BGCs in 81 Photorhabdus strains, confirming the predominant presence (44.80%) of NRPS BGCs in Photorhabdus. All 990 NRPS BGCs were clustered into 275 gene cluster families (GCFs) and only 13 GCFs could be annotated with known BGCs, suggesting their great diversity and novelty. These NRPS BGCs encoded 351 novel peptides containing more than four amino acids, and 173 of them showed high sequence similarity to known BGCs encoding bioactive peptides, implying the promising potential of Photorhabdus to produce valuable peptides. Sequence similarity networking of adenylation (A‐) domains suggested that the substrate specificity of A‐domains was not directly correlated with the sequence similarity. The molecular similarity network of predicted metabolite scaffolds of NRPS BGCs and reported peptides from Photorhabdus and a relevant database demonstrated that the non‐ribosomal peptide biosynthetic potential of Photorhabdus was largely untapped and revealed the core peptides deserving intensive studies. Our present study provides valuable information for the targeted discovery of novel non‐ribosomal peptides from Photorhabdus.

Kutzneria is a rare genus of Actinobacteria that harbors a variety of secondary metabolite gene clusters and produces several interesting types of bioactive secondary metabolites. Recent efforts have partially elucidated the biosynthetic pathways of some of these bioactive natural products, suggesting the diversity and specificity of secondary metabolism within this genus. Here, we summarized the chemical structures, biosynthetic pathways, and key metabolic enzymes of the secondary metabolites isolated from Kutzneria strains. In-depth comparative genomic analysis of all six available high-quality Kutzneria genomes revealed that the majority (77%) of the biosynthetic gene cluster families of Kutzneria were untapped and identified homologues of key metabolic enzymes in the putative gene clusters, including cytochrome P450s, halogenases, and flavin-dependent N-hydroxylases. The present study suggests that Kutzneria exhibits great potential to synthesize novel secondary metabolites, encodes a variety of valuable metabolic enzymes, and also provides valuable information for the targeted discovery and biosynthesis of novel natural products from Kutzneria.