The confluence of big data and evolutionary genome mining for the discovery of natural products

Discovery of a terpene synthase synthesizing a nearly non-flexible eunicellane reveals the basis of flexibility

Eunicellane diterpenoids, containing a typical 6,10-bicycle, are bioactive compounds widely present in marine corals, but rarely found in bacteria and plants. The intrinsic macrocycle exhibits innate structural flexibility resulting in dynamic conformational changes. However, the mechanisms controlling flexibility remain unknown. The discovery of a terpene synthase, MicA, that is responsible for the biosynthesis of a nearly non-flexible eunicellane skeleton, enable us to propose a feasible theory about the flexibility in eunicellane structures. Parallel studies of all eunicellane synthases in nature discovered to date, including 2Z-geranylgeranyl diphosphate incubations and density functional theory-based Boltzmann population computations, reveale that a trans-fused bicycle with a 2Z-configuration alkene restricts conformational flexibility resulting in a nearly non-flexible eunicellane skeleton. The catalytic route and the enzymatic mechanism of MicA are also elucidated by labeling experiments, density functional theory calculations, structural analysis of the artificial intelligence-based MicA model, and mutational studies.

Discovery of Prenyltransferase-Guided Hydroxyphenylacetic Acid Derivatives from Marine Fungus Penicillium sp. W21C371

Traditional isolation methods often lead to the rediscovery of known natural products. In contrast, genome mining strategies are considered effective for the continual discovery of new natural products. In this study, we discovered a unique prenyltransferase (PT) through genome mining, capable of catalyzing the transfer of a prenyl group to an aromatic nucleus to form C-C or C-O bonds. A pair of new hydroxyphenylacetic acid derivative enantiomers with prenyl units, (±)-peniprenydiol A (1), along with 16 known compounds (2-17), were isolated from a marine fungus, Penicillium sp. W21C371. The separation of 1 using chiral HPLC led to the isolation of the enantiomers 1a and 1b. Their structures were established on the basis of extensive spectroscopic analysis, including 1D, 2D NMR and HRESIMS. The absolute configurations of the new compounds were determined by a modified Mosher method. A plausible biosynthetic pathway for 1 was deduced, facilitated by PT catalysis. In the in vitro assay, 2 and 3 showed promising inhibitory activity against Escherichia coli β-glucuronidase (EcGUS), with IC50 values of 44.60 ± 0.84 μM and 21.60 ± 0.76 μM, respectively, compared to the positive control, D-saccharic acid 1,4-lactone hydrate (DSL). This study demonstrates the advantages of genome mining in the rational acquisition of new natural products.

Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products

Covering: 1995 to 2023Advances in bioanalytical methods, particularly mass spectrometry, have provided valuable molecular insights into the mechanisms of life. Non-targeted metabolomics aims to detect and (relatively) quantify all observable small molecules present in a biological system. By comparing small molecule abundances between different conditions or timepoints in a biological system, researchers can generate new hypotheses and begin to understand causes of observed phenotypes. Functional metabolomics aims to investigate the functional roles of metabolites at the scale of the metabolome. However, most functional metabolomics studies rely on indirect measurements and correlation analyses, which leads to ambiguity in the precise definition of functional metabolomics. In contrast, the field of natural products has a history of identifying the structures and bioactivities of primary and specialized metabolites. Here, we propose to expand and reframe functional metabolomics by integrating concepts from the fields of natural products and chemical biology. We highlight emerging functional metabolomics approaches that shift the focus from correlation to physical interactions, and we discuss how this allows researchers to uncover causal relationships between molecules and phenotypes.

Discovery of fungal onoceroid triterpenoids through domainless enzyme-targeted global genome mining

Genomics-guided methodologies have revolutionized the discovery of natural products. However, a major challenge in the field of genome mining is determining how to selectively extract biosynthetic gene clusters (BGCs) for untapped natural products from numerous available genome sequences. In this study, we developed a fungal genome mining tool that extracts BGCs encoding enzymes that lack a detectable protein domain (i.e., domainless enzymes) and are not recognized as biosynthetic proteins by existing bioinformatic tools. We searched for BGCs encoding a homologue of Pyr4-family terpene cyclases, which are representative examples of apparently domainless enzymes, in approximately 2000 fungal genomes and discovered several BGCs with unique features. The subsequent characterization of selected BGCs led to the discovery of fungal onoceroid triterpenoids and unprecedented onoceroid synthases. Furthermore, in addition to the onoceroids, a previously unreported sesquiterpene hydroquinone, of which the biosynthesis involves a Pyr4-family terpene cyclase, was obtained. Our genome mining tool has broad applicability in fungal genome mining and can serve as a beneficial platform for accessing diverse, unexploited natural products.

Cheminformatics-Guided Cell-Free Exploration of Peptide Natural Products

There have been significant advances in the flexibility and power of in vitro cell-free translation systems. The increasing ability to incorporate noncanonical amino acids and complement translation with recombinant enzymes has enabled cell-free production of peptide-based natural products (NPs) and NP-like molecules. We anticipate that many more such compounds and analogs might be accessed in this way. To assess the peptide NP space that is directly accessible to current cell-free technologies, we developed a peptide parsing algorithm that breaks down peptide NPs into building blocks based on ribosomal translation logic. Using the resultant data set, we broadly analyze the biophysical properties of these privileged compounds and perform a retrobiosynthetic analysis to predict which peptide NPs could be directly synthesized in augmented cell-free translation reactions. We then tested these predictions by preparing a library of highly modified peptide NPs. Two macrocyclases, PatG and PCY1, were used to effect the head-to-tail macrocyclization of candidate NPs. This retrobiosynthetic analysis identified a collection of high-priority building blocks that are enriched throughout peptide NPs, yet they had not previously been tested in cell-free translation. To expand the cell-free toolbox into this space, we established, optimized, and characterized the flexizyme-enabled ribosomal incorporation of piperazic acids. Overall, these results demonstrate the feasibility of cell-free translation for peptide NP total synthesis while expanding the limits of the technology. This work provides a novel computational tool for exploration of peptide NP chemical space, that could be expanded in the future to allow design of ribosomal biosynthetic pathways for NPs and NP-like molecules.

Global genome mining-driven discovery of an unusual biosynthetic logic for fungal polyketide-terpenoid hybrids

Genome mining has facilitated the efficient discovery of untapped natural products. We performed global genome mining in fungi and discovered a series of biosynthetic gene clusters (BGCs) that appeared to afford polyketide-terpenoid hybrids via a distinct biosynthetic mechanism from those adopted by known pathways. Characterization of one of the BGCs revealed that it yields the drimane-phthalide hybrid 1. During the biosynthesis of 1, the farnesyl group is unusually introduced by the dimethylallyltryptophan synthase-type prenyltransferase MfmD and is then cyclized by the Pyr4-family terpene cyclase MfmH. The replacement of MfmH with its homologue OcdTC gave another hybrid molecule with a monocyclic terpenoid moiety. Moreover, PsetPT, an MfmD homologue, was found to perform dimethylallylation and was then engineered to install a geranyl group. Our study unraveled an unusual biosynthetic mechanism for fungal phthalide-terpenoid hybrids and provided insights into how their structural diversification could be achieved.

DNMT3L inhibits hepatocellular carcinoma progression through DNA methylation of CDO1: insights from big data to basic research

BACKGROUND

DNMT3L is a crucial DNA methylation regulatory factor, yet its function and mechanism in hepatocellular carcinoma (HCC) remain poorly understood. Bioinformatics-based big data analysis has increasingly gained significance in cancer research. Therefore, this study aims to elucidate the role of DNMT3L in HCC by integrating big data analysis with experimental validation.

METHODS

Dozens of HCC datasets were collected to analyze the expression of DNMT3L and its relationship with prognostic indicators, and were used for molecular regulatory relationship evaluation. The effects of DNMT3L on the malignant phenotypes of hepatoma cells were confirmed in vitro and in vivo. The regulatory mechanisms of DNMT3L were explored through MSP, western blot, and dual-luciferase assays.

RESULTS

DNMT3L was found to be downregulated in HCC tissues and associated with better prognosis. Overexpression of DNMT3L inhibits cell proliferation and metastasis. Additionally, CDO1 was identified as a target gene of DNMT3L and also exhibits anti-cancer effects. DNMT3L upregulates CDO1 expression by competitively inhibiting DNMT3A-mediated methylation of CDO1 promoter.

CONCLUSIONS

Our study revealed the role and epi-transcriptomic regulatory mechanism of DNMT3L in HCC, and underscored the essential role and applicability of big data analysis in elucidating complex biological processes.

Exploring the biosynthetic gene clusters in Brevibacterium: a comparative genomic analysis of diversity and distribution

Exploring Brevibacterium strains from various ecosystems may lead to the discovery of new antibiotic-producing strains. Brevibacterium sp. H-BE7, a strain isolated from marine sediments from Northern Patagonia, Chile, had its genome sequenced to study the biosynthetic potential to produce novel natural products within the Brevibacterium genus. The genome sequences of 98 Brevibacterium strains, including strain H-BE7, were selected for a genomic analysis. A phylogenomic cladogram was generated, which divided the Brevibacterium strains into four major clades. A total of 25 strains are potentially unique new species according to Average Nucleotide Identity (ANIb) values. These strains were isolated from various environments, emphasizing the importance of exploring diverse ecosystems to discover the full diversity of Brevibacterium. Pangenome analysis of Brevibacterium strains revealed that only 2.5% of gene clusters are included within the core genome, and most gene clusters occur either as singletons or as cloud genes present in less than ten strains. Brevibacterium strains from various phylogenomic clades exhibit diverse BGCs. Specific groups of BGCs show clade-specific distribution patterns, such as siderophore BGCs and carotenoid-related BGCs. A group of clade IV-A Brevibacterium strains possess a clade-specific Polyketide synthase (PKS) BGCs that connects with phenazine-related BGCs. Within the PKS BGC, five genes, including the biosynthetic PKS gene, participate in the mevalonate pathway and exhibit similarities with the phenazine A BGC. However, additional core biosynthetic phenazine genes were exclusively discovered in nine Brevibacterium strains, primarily isolated from cheese. Evaluating the antibacterial activity of strain H-BE7, it exhibited antimicrobial activity against Salmonella enterica and Listeria monocytogenes. Chemical dereplication identified bioactive compounds, such as 1-methoxyphenazine in the crude extracts of strain H-BE7, which could be responsible of the observed antibacterial activity. While strain H-BE7 lacks the core phenazine biosynthetic genes, it produces 1-methoxyphenazine, indicating the presence of an unknown biosynthetic pathway for this compound. This suggests the existence of alternative biosynthetic pathways or promiscuous enzymes within H-BE7's genome.

Identification of the lipodepsipeptide selethramide encoded in a giant nonribosomal peptide synthetase from a Burkholderia bacterium

Bacterial natural products have found many important industrial applications. Yet traditional discovery pipelines often prioritize individual natural product families despite the presence of multiple natural product biosynthetic gene clusters in each bacterial genome. Systematic characterization of talented strains is a means to expand the known natural product space. Here, we report genomics, epigenomics, and metabolomics studies of Burkholderia sp. FERM BP-3421, a soil isolate and known producer of antitumor spliceostatins. Its genome is composed of two chromosomes and two plasmids encoding at least 29 natural product families. Metabolomics studies showed that FERM BP-3421 also produces antifungal aminopyrrolnitrin and approved anticancer romidepsin. From the orphan metabolome features, we connected a lipopeptide of 1,928 Da to an 18-module nonribosomal peptide synthetase encoded as a single gene in chromosome 1. Isolation and structure elucidation led to the identification of selethramide which contains a repeating pattern of serine and leucine and is cyclized at the side chain oxygen of the one threonine residue at position 13. A (R)-3-hydroxybutyric acid moiety decorates the N-terminal serine. Initial attempts to obtain deletion mutants to probe the role of selethramide failed. After acquiring epigenome (methylome) data for FERM BP-3421, we employed a mimicry by methylation strategy that improved DNA transfer efficiency. Mutants defective in selethramide biosynthesis showed reduced surfactant activity and impaired swarming motility that could be chemically complemented with selethramide. This work unveils a lipopeptide that promotes surface motility, establishes improved DNA transfer efficiency, and sets the stage for continued natural product identification from a prolific strain.

Accessing hidden microbial biosynthetic potential from underexplored sources for novel drug discovery

Microbial natural products and their structural analogues have widely used as pharmaceutical agents, especially for infectious diseases and cancer. Despite this success, new structural classes with innovative chemistry and modes of action are urgently needed to be developed to combat the growing antimicrobial resistance and other public health problems. The advances in next-generation sequencing technologies and powerful computational tools open up new opportunities to explore microbial biosynthetic potential from underexplored sources, with millions of secondary metabolites awaiting discovery. The review highlights challenges associated with discovery of new chemical entities, rich reservoirs provided by untapped taxa, ecological niches or host microbiomes, emerging synthetic biotechnologies to unearth the hidden microbial biosynthetic potential for novel drug discovery at scale and speed.

On the evolution of natural product biosynthesis

Natural products are the raw material for drug discovery programmes. Bioactive natural products are used extensively in medicine and agriculture and have found utility as antibiotics, immunosuppressives, anti-cancer drugs and anthelminthics. Remarkably, the natural role and what mechanisms drive evolution of these molecules is relatively poorly understood. The exponential increase in genome and chemical data in recent years, coupled with technical advances in bioinformatics and genetics have enabled progress to be made in understanding the evolution of biosynthetic gene clusters and the products of their enzymatic machinery. Here we discuss the diversity of natural products, incorporating the mechanisms that govern evolution of metabolic pathways and how this can be applied to biosynthetic gene clusters. We build on the nomenclature of natural products in terms of primary, integrated, secondary and specialised metabolism and place this within an ecology-evolutionary-developmental biology framework. This eco-evo-devo framework we believe will help to clarify the nature and use of the term specialised metabolites in the future.

Biogeographic patterns of biosynthetic potential and specialized metabolites in marine sediments

While the field of microbial biogeography has largely focused on the contributions of abiotic factors to community patterns, the potential influence of biotic interactions in structuring microbial communities, such as those mediated by the production of specialized metabolites, remains largely unknown. Here, we examined the relationship between microbial community structure and specialized metabolism at local spatial scales in marine sediment samples collected from the Long-Term Ecological Research (LTER) site in Moorea, French Polynesia. By employing a multi-omic approach to characterize the taxonomic, functional, and specialized metabolite composition within sediment communities, we find that biogeographic patterns were driven by local scale processes (e.g., biotic interactions) and largely independent of dispersal limitation. Specifically, we observed high variation in biosynthetic potential (based on Bray-Curtis dissimilarity) between samples, even within 1 m² plots, that reflected uncharacterized chemical space associated with site-specific metabolomes. Ultimately, connecting biosynthetic potential to community metabolomes facilitated the in situ detection of natural products and revealed new insights into the complex metabolic dynamics associated with sediment microbial communities. Our study demonstrates the potential to integrate biosynthetic genes and metabolite production into assessments of microbial community dynamics.

New trends in synthetic drugs and natural products targeting 20S proteasomes in cancers

Cancer is a global health challenge that remains to be a field of extensive research aiming to find new anticancer therapeutics. The 20S proteasome complex is one of the targets of anticancerdrugs, as it is correlated with several cancer types. Herein, we aim to discuss the 20S proteasome subunits and investigatethe currently studied proteasome inhibitors targeting the catalytically active proteasome subunits. In this review, we summarize the proteindegradation mechanism of the 20S proteasome complex and compareit with the 26S proteasome complex. Afterwards, the localization of the 20S proteasome is summarized as well as its use as a diagnosticandprognostic marker. The FDA-approved proteasome inhibitors (PIs) under clinical trials are summarized and their current limited use in solid tumors is also reviewed in addition to the expression of theβ5 subunit in differentcell lines. The review discusses in-silico analysis of the active subunit of the 20S proteasome complex. For development of new proteasome inhibitor drugs, the natural products inhibiting the 20S proteasome are summarized, as well as novel methodologies and challenges for the natural product discovery and current information about the biosynthetic gene clusters encoding them. We herein briefly summarize some resistancemechanismsto the proteasomeinhibitors. Additionally, we focus on the three main classes of proteasome inhibitors: 1] boronic acid, 2] beta-lactone and 3] epoxide inhibitor classes, as well as other PI classes, and their IC₅₀ values and their structure-activity relationship (SAR). Lastly,we summarize several future prospects of developing new proteasome inhibitors towards the treatment of tumors, especially solid tumors.

Genomics-Guided Efficient Identification of 2,5-Diketopiperazine Derivatives from Actinobacteria

Secondary metabolites derived from microorganism constitute an important part of natural products. Mining of the microbial genomes revealed a large number of uncharacterized biosynthetic gene clusters, indicating their greater potential to synthetize specialized or secondary metabolites (SMs) than identified by classic fermentation and isolation approaches. Various bioinformatics tools have been developed to analyze and identify such gene clusters, thus accelerating significantly the mining process. Heterologous expression of an individual biosynthetic gene cluster has been proven as an efficient way to activate the genes and identify the encoded metabolites that cannot be detected under normal laboratory cultivation conditions. Herein, we describe a concept of genomics-guided approach by performing genome mining and heterologous expression to uncover novel CDPS-derived DKPs and functionally characterize novel tailoring enzymes embedded in the biosynthetic pathways. Recent works focused on the identification of the nucleobase-related and dimeric DKPs are also presented.

Specialized Metabolism of Gordonia Genus: An Integrated Survey on Chemodiversity Combined with a Comparative Genomics-Based Analysis

Members of the phylum Actinomycetota (formerly Actinobacteria) have historically been the most prolific providers of small bioactive molecules. Although the genus Streptomyces is the best-known member for this issue, other genera, such as Gordonia, have shown interesting potential in their specialized metabolism. Thus, we combined herein the result of a comprehensive literature survey on metabolites derived from Gordonia strains with a comparative genomic analysis to examine the potential of the specialized metabolism of the genus Gordonia. Thirty Gordonia-derived compounds of different classes were gathered (i.e., alkaloids, amides, phenylpropanoids, and terpenoids), exhibiting antimicrobial and cytotoxic activities, and several were also isolated from Streptomyces (e.g., actinomycin, nocardamin, diolmycin A1). With the genome data, we estimated an open pan-genome of 57,901 genes, most of them being part of the cloud genome. Regarding the BGCs content, 531 clusters were found, including Terpenes, RiPP-like, and NRPS clusters as the most frequent clusters. Our findings demonstrated that Gordonia is a poorly studied genus in terms of its specialized metabolism production and potential applications. Nevertheless, given their BGCs content, Gordonia spp. are a valuable biological resource that could expand the chemical spectrum of the phylum Actinomycetota, involving novel BGCs for inspiring innovative outlines for synthetic biology and further use in biotechnological initiatives. Therefore, further studies and more efforts should be made to explore different environments and evaluate other bioactivities.

Microbiome composition modulates secondary metabolism in a multispecies bacterial community

Bacterial secondary metabolites are a major source of antibiotics and other bioactive compounds. In microbial communities, these molecules can mediate interspecies interactions and responses to environmental change. Despite the importance of secondary metabolites in human health and microbial ecology, little is known about their roles and regulation in the context of multispecies communities. In a simplified model of the rhizosphere composed of Bacillus cereus, Flavobacterium johnsoniae, and Pseudomonas koreensis, we show that the dynamics of secondary metabolism depend on community species composition and interspecies interactions. Comparative metatranscriptomics and metametabolomics reveal that the abundance of transcripts of biosynthetic gene clusters (BGCs) and metabolomic molecular features differ between monocultures or dual cultures and a tripartite community. In both two- and three-member cocultures, P. koreensis modified expression of BGCs for zwittermicin, petrobactin, and other secondary metabolites in B. cereus and F. johnsoniae, whereas the BGC transcriptional response to the community in P. koreensis itself was minimal. Pairwise and tripartite cocultures with P. koreensis displayed unique molecular features that appear to be derivatives of lokisin, suggesting metabolic handoffs between species. Deleting the BGC for koreenceine, another P. koreensis metabolite, altered transcript and metabolite profiles across the community, including substantial up-regulation of the petrobactin and bacillibactin BGCs in B. cereus, suggesting that koreenceine represses siderophore production. Results from this model community show that bacterial BGC expression and chemical output depend on the identity and biosynthetic capacity of coculture partners, suggesting community composition and microbiome interactions may shape the regulation of secondary metabolism in nature.

Integrated Metabolomic-Genomic Workflows Accelerate Microbial Natural Product Discovery

The pairing of analytical chemistry with genomic techniques represents a new wave in natural product chemistry. With an increase in the availability of sequencing and assembly of microbial genomes, interrogation into the biosynthetic capability of producers with valuable secondary metabolites is possible. However, without the development of robust, accessible, and medium to high throughput tools, the bottleneck in pairing metabolic potential and compound isolation will continue. Several innovative approaches have proven useful in the nascent stages of microbial genome-informed drug discovery. Here, we consider a number of these approaches which have led to prioritization of strain targets and have mitigated rediscovery rates. Likewise, we discuss integration of principles of comparative evolutionary studies and retrobiosynthetic predictions to better understand biosynthetic mechanistic details and link genome sequence to structure. Lastly, we discuss advances in engineering, chemistry, and molecular networking and other computational approaches that are accelerating progress in the field of omic-informed natural product drug discovery. Together, these strategies enhance the synergy between cutting edge omics, chemical characterization, and computational technologies that pitch the discovery of natural products with pharmaceutical and other potential applications to the crest of the wave where progress is ripe for rapid advances.

Targeted Large-Scale Genome Mining and Candidate Prioritization for Natural Product Discovery

Large-scale genome-mining analyses have identified an enormous number of cryptic biosynthetic gene clusters (BGCs) as a great source of novel bioactive natural products. Given the sheer number of natural product (NP) candidates, effective strategies and computational methods are keys to choosing appropriate BGCs for further NP characterization and production. This review discusses genomics-based approaches for prioritizing candidate BGCs extracted from large-scale genomic data, by highlighting studies that have successfully produced compounds with high chemical novelty, novel biosynthesis pathway, and potent bioactivities. We group these studies based on their BGC-prioritization logics: detecting presence of resistance genes, use of phylogenomics analysis as a guide, and targeting for specific chemical structures. We also briefly comment on the different bioinformatics tools used in the field and examine practical considerations when employing a large-scale genome mining study.

Bioprospecting the microbiome of Red Sea Atlantis II brine pool for peptidases and biosynthetic genes with promising antibacterial activity

Background

The search for novel antimicrobial agents is crucial as antibiotic-resistant pathogens continue to emerge, rendering the available antibiotics no longer effective. Likewise, new anti-cancer drugs are needed to combat the emergence of multi-drug resistant tumors. Marine environments are wealthy sources for natural products. Additionally, extreme marine environments are interesting niches to search for bioactive natural compounds. In the current study, a fosmid library of metagenomic DNA isolated from Atlantis II Deep Lower Convective Layer (ATII LCL), was functionally screened for antibacterial activity as well as anticancer effects.

Results

Two clones exhibited antibacterial effects against the marine Bacillus Cc6 strain, namely clones 102-5A and 88-1G and they were further tested against eleven other challenging strains, including six safe relatives of ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter  spp.), a safe relative to Mycobacterium tuberculosis and four resistant clinical isolates. Clone 88-1G resulted in clear zones of inhibition against eight bacterial strains, while clone 102-5A resulted in zones of inhibition against five bacterial strains. The whole cell lysates of clone 88-1G showed 15% inhibition of Mtb ClpP protease -Mycobacterium tuberculosis drug target-, while whole cell lysates of clone 102-5A showed 19% inhibition of Mtb ClpP protease. Whole cell lysates from the selected clones exhibited anticancer effects against MCF-7 breast cancer cells (cell viability at 50% v/v was 46.2% ± 9.9 for 88-1G clone and 38% ± 7 for 102-5A clone), U2OS osteosarcoma cells (cell viability at 50% v/v was 64.6% ± 12.3 for 88-1G clone and 28.3% ± 1.7 for 102-5A clone) and 1BR hTERT human fibroblast cells (cell viability at 50% v/v was 74.4% ± 5.6 for 88-1G clone and 57.6% ± 8.9 for 102-5A clone). Sequencing of 102-5A and 88-1G clones, and further annotation detected putative proteases and putative biosynthetic genes in clones 102-5A and 88-1G, respectively.

Conclusions

The ATII LCL metagenome hosts putative peptidases and biosynthetic genes that confer antibiotic and anti-cancer effects. The tested clones exhibited promising antibacterial activities against safe relative strains to ESKAPE pathogens and Mycobacterium tuberculosis. Thus, searching the microbial dark matter of extreme environments is a promising approach to identify new molecules with pharmaceutical potential use.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01835-z.

Compendium of specialized metabolite biosynthetic diversity encoded in bacterial genomes

Bacterial specialized metabolites are a proven source of antibiotics and cancer therapies, but whether we have sampled all the secondary metabolite chemical diversity of cultivated bacteria is not known. We analysed ~170,000 bacterial genomes and ~47,000 metagenome assembled genomes (MAGs) using a modified BiG-SLiCE and the new clust-o-matic algorithm. We estimate that only 3% of the natural products potentially encoded in bacterial genomes have been experimentally characterized. We show that the variation in secondary metabolite biosynthetic diversity drops significantly at the genus level, identifying it as an appropriate taxonomic rank for comparison. Equal comparison of genera based on relative evolutionary distance revealed that Streptomyces bacteria encode the largest biosynthetic diversity by far, with Amycolatopsis, Kutzneria and Micromonospora also encoding substantial diversity. Finally, we find that several less-well-studied taxa, such as Weeksellaceae (Bacteroidota), Myxococcaceae (Myxococcota), Pleurocapsa and Nostocaceae (Cyanobacteria), have potential to produce highly diverse sets of secondary metabolites that warrant further investigation.

Recent advances in the chemo-biological characterization of decalin natural products and unraveling of the workings of Diels-Alderases

The Diels-Alder (DA) reaction refers to a [4 + 2] cycloaddition reaction that falls under the category of pericyclic reactions. It is a reaction that allows regio- and stereo-selective construction of two carbon-carbon bonds simultaneously in a concerted manner to generate a six-membered ring structure through a six-electron cyclic transition state. The DA reaction is one of the most widely applied reactions in organic synthesis, yet its role in biological systems has been debated intensely over the last four decades. A survey of secondary metabolites produced by microorganisms suggests strongly that many of the compounds possess features that are likely formed through DA reactions, and most of them are considered to be catalyzed by enzymes that are commonly referred to as Diels-Alderases (DAases). In recent years, especially over the past 10 years or so, we have seen an accumulation of a substantial body of work that substantiates the argument that DAases indeed exist and play a critical role in the biosynthesis of complex metabolites. This review will cover the DAases involved in the biosynthesis of decalin moieties, which are found in many of the medicinally important natural products, especially those produced by fungi. In particular, we will focus on a subset of secondary metabolites referred to as pyrrolidine-2-one-bearing decalin compounds and discuss the decalin ring stereochemistry and the biological activities of those compounds. We will also look into the genes and enzymes that drive the biosynthetic construction of those complex natural products, and highlight the recent progress made on the structural and mechanistic understanding of DAases, especially regarding how those enzymes exert stereochemical control over the [4 + 2] cycloaddition reactions they catalyze.

Nutrient Availability Shifts the Biosynthetic Potential of Soil-Derived Microbial Communities

Secondary metabolites produced by microorganisms are the main source of antimicrobials and other pharmaceutical drugs. Soil microbes have been the primary discovery source for these secondary metabolites, often producing complex organic compounds with specific biological activities. Research suggests that secondary metabolism broadly shapes microbial ecological interactions, but little is known about the factors that shape the abundance, distribution, and diversity of biosynthetic gene clusters in the context of microbial communities. In this study, we investigate the role of nutrient availability on the abundance of biosynthetic gene clusters in soil-derived microbial consortia. Soil microbial consortia enriched in high sugar medium (150 mg/L of glucose and 200 mg/L of trehalose) had more biosynthetic gene clusters and higher inhibitory activity than those enriched in low sugar medium (15 mg/L of glucose + 20 mg/L of trehalose). Our results demonstrate that experimental microbial communities are a promising tool to study the ecology of specialized metabolites.

From solo to duet, intersections of natural product assembly with self-resistance

Covering: up to 2021Self-resistance mechanisms adopted by natural product producers have long been recognized and studied as a standalone system separated from the assembly machinery. However, as more examples of self-resistance have been characterized in detail, it has been revealed that self-resistance could associate with the assembly machinery to fulfill the task of biosynthesis. This review summarizes different self-resistance mechanisms showing a common feature: intersection with natural product assembly. Furthermore, their possible evolutionary origin and synthetic biology applications are discussed.

Vertical Inheritance Facilitates Interspecies Diversification in Biosynthetic Gene Clusters and Specialized Metabolites

While specialized metabolites are thought to mediate ecological interactions, the evolutionary processes driving chemical diversification, particularly among closely related lineages, remain poorly understood. Here, we examine the evolutionary dynamics governing the distribution of natural product biosynthetic gene clusters (BGCs) among 118 strains representing all nine currently named species of the marine actinobacterial genus Salinispora. While much attention has been given to the role of horizontal gene transfer (HGT) in structuring BGC distributions, we find that vertical descent facilitates interspecies BGC diversification over evolutionary timescales. Moreover, we identified a distinct phylogenetic signal among Salinispora species at both the BGC and metabolite level, indicating that specialized metabolism represents a conserved phylogenetic trait. Using a combination of genomic analyses and liquid chromatography–high-resolution tandem mass spectrometry (LC-MS/MS) targeting nine experimentally characterized BGCs and their small molecule products, we identified gene gain/loss events, constrained interspecies recombination, and other evolutionary processes associated with vertical inheritance as major contributors to BGC diversification. These evolutionary dynamics had direct consequences for the compounds produced, as exemplified by species-level differences in salinosporamide production. Together, our results support the concept that specialized metabolites, and their cognate BGCs, can represent phylogenetically conserved functional traits with chemical diversification proceeding in species-specific patterns over evolutionary time frames.