استكشف المجموعة الواسعة من العناوين المتاحة.

A combination of small molecule chemistry, biosynthetic analysis, and genome mining has revealed the unexpected conservation of polycyclic tetramate macrolactam biosynthetic loci in diverse bacteria. Initially our chemical analysis of a Streptomyces strain associated with the southern pine beetle led to the discovery of frontalamides A and B, two previously undescribed members of this antibiotic family. Genome analyses and genetic manipulation of the producing organism led to the identification of the frontalamide biosynthetic gene cluster and several biosynthetic intermediates. The biosynthetic locus for the frontalamides' mixed polyketide/amino acid structure encodes a hybrid polyketide synthase nonribosomal peptide synthetase (PKS-NRPS), which resembles iterative enzymes known in fungi. No such mixed iterative PKS-NRPS enzymes have been characterized in bacteria. Genomemining efforts revealed strikingly conserved frontalamide-like biosynthetic clusters in the genomes of phylogenetically diverse bacteria ranging from proteobacteria to actinomycetes. Screens for environmental actinomycete isolates carrying frontalamide-like biosynthetic loci led to the isolation of a number of positive strains, the majority of which produced candidate frontalamide-like compounds under suitable growth conditions. These results establish the prevalence of frontalamide-like gene clusters in diverse bacterial types, with medicinally important Streptomyces species being particularly enriched.

Endophytic microorganisms which are ubiquitously present in plants may colonize intracellularly or intercellularly without causing any diseases. By living within the unique chemical environment of a host plant, they produce a vast array of compounds with a wide range of biological activities. Because of this, natural products of endophytic origin have been exploited for antimicrobial, antiviral, anticancer, and antioxidant properties. Also, they can be considered to function as an efficient microbial barrier to protect plants from various pathogens. In the present study, endophytic bacterium BmB 9 with antifungal and antibacterial activity isolated from the stem tissue of Bacopa monnieri was studied for the molecular and chemical basis of its activity. PCR-based genome mining for various biosynthetic gene clusters proved the presence of surfactin, iturin, and type I polyketide synthase (PKS) genes in the isolate. The LC–MS/MS based analysis of the extract further confirmed the production of surfactin derivatives (M + H⁺—1008.6602, 1022.6755), iturin (M + H⁺—1043.5697), and fengycin (M + H⁺—1491.8195, 1477.8055) by the selected bacterial isolate. The 16S rDNA sequence similarity based analysis identified the isolate BmB 9 as Bacillus sp. with 100 % identity to Bacillus sp. LCF1 (KP257289).

Polyketide–terpenoid hybrid compounds are one of the largest families of meroterpenoids, with great potential for drug development for resistant pathogens. Genome sequence analysis of secondary metabolite gene clusters of a phytopathogenic fungus, Bipolaris sorokiniana 11134, revealed a type I polyketide gene cluster, consisting of highly reducing polyketide synthase, non-reducing polyketide synthase, and adjacent prenyltransferase. MS- and UV-guided isolations led to the isolation of ten meroterpenoids, including two new compounds: 19-dehydroxyl-3-epi-arthripenoid A (1) and 12-keto-cochlioquinone A (2). The structures of 1–10 were elucidated by the analysis of NMR and high-resolution electrospray ionization mass spectroscopy data. Compounds 5–8 and 10 showed moderate activity against common Staphylococcus aureus and methicillin-resistant S. aureus, with minimum inhibitory concentration (MIC) values of 12.5–100 μg/mL. Compound 5 also exhibited activity against four clinical resistant S. aureus strains and synergistic antifungal activity against Candida albicans with MIC values of 12.5–25 μg/mL. The biosynthetic gene cluster of the isolated compounds and their putative biosynthetic pathway are also proposed.Key Points• Ten meroterpenoids were identified from B. sorokiniana, including two new compounds.• Cochlioquinone B (5) showed activity against MRSA and synergistic activity against C. albicans.• The biosynthetic gene cluster and biosynthetic pathway of meroterpenoids are proposed.• Genome mining provided a new direction to uncover the diversity of meroterpenoids.

The animal gut microbiome is a complex system of diverse, predominantly anaerobic microbiota with secondary metabolite potential. These metabolites likely play roles in shaping microbial community membership and influencing animal host health. As such, novel secondary metabolites from gut microbes hold significant biotechnological and therapeutic interest. Despite their potential, gut microbes are largely untapped for secondary metabolites, with gut fungi and obligate anaerobes being particularly under-explored. To advance understanding of these metabolites, culture-based and (meta)genome-based approaches are essential. Culture-based approaches enable isolation, cultivation, and direct study of gut microbes, and (meta)genome-based approaches utilize in silico tools to mine biosynthetic gene clusters (BGCs) from microbes that have not yet been successfully cultured. In this mini-review, we highlight recent innovations in this area, including anaerobic biofoundries like ExFAB, the NSF BioFoundry for Extreme & Exceptional Fungi, Archaea, and Bacteria. These facilities enable high-throughput workflows to study oxygen-sensitive microbes and biosynthetic machinery. Such recent advances promise to improve our understanding of the gut microbiome and its secondary metabolism.

Fungi are prolific producers of natural products, compounds which have had a large societal impact as pharmaceuticals, mycotoxins, and agrochemicals. Despite the availability of over 1,000 fungal genomes and several decades of compound discovery efforts from fungi, the biosynthetic gene clusters (BGCs) encoded by these genomes and the associated chemical space have yet to be analyzed systematically. Here, we provide detailed annotation and analyses of fungal biosynthetic and chemical space to enable genome mining and discovery of fungal natural products. Using 1,037 genomes from species across the fungal kingdom (e.g., Ascomycota, Basidiomycota, and non-Dikarya taxa), 36,399 predicted BGCs were organized into a network of 12,067 gene cluster families (GCFs). Anchoring these GCFs with reference BGCs enabled automated annotation of 2,026 BGCs with predicted metabolite scaffolds. We performed parallel analyses of the chemical repertoire of fungi, organizing 15,213 fungal compounds into 2,945 molecular families (MFs). The taxonomic landscape of fungal GCFs is largely species specific, though select families such as the equisetin GCF are present across vast phylogenetic distances with parallel diversifications in the GCF and MF. We compare these fungal datasets with a set of 5,453 bacterial genomes and their BGCs and 9,382 bacterial compounds, revealing dramatic differences between bacterial and fungal biosynthetic logic and chemical space. These genomics and cheminformatics analyses reveal the large extent to which fungal and bacterial sources represent distinct compound reservoirs. With a >10-fold increase in the number of interpreted strains and annotated BGCs, this work better regularizes the biosynthetic potential of fungi for rational compound discovery.

Nonribosomal peptides and polyketides are a diverse group of natural products with complex chemical structures and enormous pharmaceutical potential. They are synthesized on modular nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) enzyme complexes by a conserved thiotemplate mechanism. Here, we report the widespread occurrence of NRPS and PKS genetic machinery across the three domains of life with the discovery of 3,339 gene clusters from 991 organisms, by examining a total of 2,699 genomes. These gene clusters display extraordinarily diverse organizations, and a total of 1,147 hybrid NRPS/PKS clusters were found. Surprisingly, 10% of bacterial gene clusters lacked modular organization, and instead catalytic domains were mostly encoded as separate proteins. The finding of common occurrence of nonmodular NRPS differs substantially from the current classification. Sequence analysis indicates that the evolution of NRPS machineries was driven by a combination of common descent and horizontal gene transfer. We identified related siderophore NRPS gene clusters that encoded modular and nonmodular NRPS enzymes organized in a gradient. A higher frequency of the NRPS and PKS gene clusters was detected from bacteria compared with archaea or eukarya. They commonly occurred in the phyla of Proteobacteria, Actinobacteria, Firmicutes, and Cyanobacteria in bacteria and the phylum of Ascomycota in fungi. The majority of these NRPS and PKS gene clusters have unknown end products highlighting the power of genome mining in identifying novel genetic machinery for the biosynthesis of secondary metabolites.

Background Lanthipeptides belong to the ribosomally synthesized and post-translationally modified peptide group of natural products and have a variety of biological activities ranging from antibiotics to antinociceptives. These peptides are cyclized through thioether crosslinks and can bear other secondary post-translational modifications. While lanthipeptide biosynthetic gene clusters can be identified by the presence of genes encoding characteristic enzymes involved in the post-translational modification process, locating the precursor peptides encoded within these clusters is challenging due to their short length and high sequence variability, which limits the high-throughput exploration of lanthipeptide biosynthesis. To address this challenge, we enhanced the predictive capabilities of Rapid ORF Description & Evaluation Online (RODEO) to identify members of all four known classes of lanthipeptides. Results Using RODEO, we mined over 100,000 bacterial and archaeal genomes in the RefSeq database. We identified nearly 8500 lanthipeptide precursor peptides. These precursor peptides were identified in a broad range of bacterial phyla as well as the Euryarchaeota phylum of archaea. Bacteroidetes were found to encode a large number of these biosynthetic gene clusters, despite making up a relatively small portion of the genomes in this dataset. A number of these precursor peptides are similar to those of previously characterized lanthipeptides, but even more were not, including potential antibiotics. One such new antimicrobial lanthipeptide was purified and characterized. Additionally, examination of the biosynthetic gene clusters revealed that enzymes installing secondary post-translational modifications are more widespread than initially thought. Conclusion Lanthipeptide biosynthetic gene clusters are more widely distributed and the precursor peptides encoded within these clusters are more diverse than previously appreciated, demonstrating that the lanthipeptide sequence-function space remains largely underexplored.

Engineering microbial cells to efficiently synthesize high-value-added natural products has received increasing attention in recent years. In this review, we describe the pipeline to build chassis cells for natural product production. First, we discuss recently developed genome mining strategies for identifying and designing biosynthetic modules and compare the characteristics of different host microbes. Then, we summarize state-of-the-art systems metabolic engineering tools for reconstructing and fine-tuning biosynthetic pathways and transport mechanisms. Finally, we discuss the future prospects of building next-generation chassis cells for the production of natural products. This review provides theoretical guidance for the rational design and construction of microbial strains to produce natural products. Recent advances in omics, in silico modeling analysis and design, and DNA assembly provide big data and various tools to identify, design, and assemble the synthesis modules of natural products.Besides classical strains, various other microorganisms can be used as chassis cells for natural products due to developments in systems biology and synthetic biology.Metabolic engineering based on genetic circuits and novel genome editing tools can optimize the complex pathway of natural products.Biosensor-based high-throughput screening helps to identify transporters for natural products and facilitate their secretion.

The link between gut microbiome and brain is being slowly acknowledged due to the speculated role of resident gut microbial community in altering the functions of gut-brain axis (GBA). Recently, a number of microbial metabolites (referred to as neuro-active metabolites) produced through tryptophan metabolism have been suggested to influence the GBA. In view of this, the current study focuses on microbial tryptophan metabolism pathways which produce neuro-active metabolites. An analysis was performed on bacterial genomes as well as publicly available gut microbiome data. The results provide a comprehensive catalog of the analyzed pathways across bacteria. The analysis indicates an enrichment of tryptophan metabolism pathways in five gut-associated phyla, namely, Actinobacteria, Firmicutes, Bacteroidetes, Proteobacteria, and Fusobacteria. Further, five genera, namely, , , , , and have been predicted to be enriched in terms of number of the analyzed tryptophan metabolism pathways, suggesting a higher potential of these bacterial groups to metabolize tryptophan in gut. Analysis of available microbiome data corresponding to gut samples from patients of neurological diseases and healthy individuals suggests probable association of different sets of tryptophan metabolizing bacterial pathways with the etiology of different diseases. The insights obtained from the present study are expected to provide directions toward designing of microbiome based diagnostic and therapeutic approaches for neurological diseases/disorders.

Background Genome mining tools have enabled us to predict biosynthetic gene clusters that might encode compounds with valuable functions for industrial and medical applications. With the continuously increasing number of genomes sequenced, we are confronted with an overwhelming number of predicted clusters. In order to guide the effective prioritization of biosynthetic gene clusters towards finding the most promising compounds, knowledge about diversity, phylogenetic relationships and distribution patterns of biosynthetic gene clusters is necessary. Results Here, we provide a comprehensive analysis of the model actinobacterial genus Amycolatopsis and its potential for the production of secondary metabolites. A phylogenetic characterization, together with a pan-genome analysis showed that within this highly diverse genus, four major lineages could be distinguished which differed in their potential to produce secondary metabolites. Furthermore, we were able to distinguish gene cluster families whose distribution correlated with phylogeny, indicating that vertical gene transfer plays a major role in the evolution of secondary metabolite gene clusters. Still, the vast majority of the diverse biosynthetic gene clusters were derived from clusters unique to the genus, and also unique in comparison to a database of known compounds. Our study on the locations of biosynthetic gene clusters in the genomes of Amycolatopsis ’ strains showed that clusters acquired by horizontal gene transfer tend to be incorporated into non-conserved regions of the genome thereby allowing us to distinguish core and hypervariable regions in Amycolatopsis genomes. Conclusions Using a comparative genomics approach, it was possible to determine the potential of the genus Amycolatopsis to produce a huge diversity of secondary metabolites. Furthermore, the analysis demonstrates that horizontal and vertical gene transfer play an important role in the acquisition and maintenance of valuable secondary metabolites. Our results cast light on the interconnections between secondary metabolite gene clusters and provide a way to prioritize biosynthetic pathways in the search and discovery of novel compounds.