New voyages to explore the natural product galaxy

Microbial secondary metabolites: advancements to accelerate discovery towards application

Microbial secondary metabolites not only have key roles in microbial processes and relationships but are also valued in various sectors of today's economy, especially in human health and agriculture. The advent of genome sequencing has revealed a previously untapped reservoir of biosynthetic capacity for secondary metabolites indicating that there are new biochemistries, roles and applications of these molecules to be discovered. New predictive tools for biosynthetic gene clusters (BGCs) and their associated pathways have provided insights into this new diversity. Advanced molecular and synthetic biology tools and workflows including cell-based and cell-free expression facilitate the study of previously uncharacterized BGCs, accelerating the discovery of new metabolites and broadening our understanding of biosynthetic enzymology and the regulation of BGCs. These are complemented by new developments in metabolite detection and identification technologies, all of which are important for unlocking new chemistries that are encoded by BGCs. This renaissance of secondary metabolite research and development is catalysing toolbox development to power the bioeconomy.

Profiling expression strategies for a type III polyketide synthase in a lysate-based, cell-free system

Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli. Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli often results in a myriad of unpredictable issues with regard to protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as a valuable expression platform as a testbed for rapid prototyping expression parameters. Here, we use a type III polyketide synthase from Streptomyces griseus, RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We applied a library of constructs with different combinations of promoters and rppA coding sequences to investigate the synergies between promoter and codon usage. Subsequently, we assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. More importantly, the choice of coding sequences and promoters impact protein expression synergistically, which should be considered for future efforts to use CFE for high-yield protein expression. The promoter strategy when applied to RppA was not completely correlated with that observed with GFP, indicating that different promoter strategies should be applied for different proteins. In vivo experiments suggest that there is correlation, but not complete alignment between expressing in cell free and in vivo. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs, which advances CFE as a tool for natural product research.

Naming of new natural products: Standard, pitfalls and tips-and-tricks

Naming a newly discovered natural product (NP) is a pleasant but difficult exercise. In most cases, the NP name will be given with reference to the species of origin, be it a plant, a marine organism, a mammalian or microbial species. For a long time, the use of biologically-based trivial names has been recommended to identify the parental linkage between the product and the originating genus or species. But the recommendation is not always followed and a multiplicity of trivial names have been attributed to NP, based on locations (country, region, city), foods, music, animals, forenames, etc. Tips-and-tricks associated with the naming of NP are underlined here. Usually, NP are differentiated across a homogeneous chemical series with a letter (from the Latin or Greek alphabet), followed or not with a number. In other cases, the change of a single letter distinguishes a series of NP. Common pitfalls associated with the naming of NP are enumerated, including the complexity of names, use of synonyms, duplicated names, confusing names and inappropriate terminology. The difficulties regularly encountered with the naming of NP are discussed. Four essential recommendations are recalled: (i) a thorough analysis of the existing products to avoid duplicated names and confusion, (ii) the use of a biologically-based trivial name to retrace the origin of the product, (iii) the strict adherence to the codes of chemical nomenclature, and (iv) the preference for simple names to facilitate transmission. Naming a new NP is a rewarding task, which shall be performed with all due skill, care and diligence.

TCMPG: an integrative database for traditional Chinese medicine plant genomes

Because of their great therapeutic and economic value, medicinal plants have attracted increasing scientific attention. With the rapid development of high-throughput sequencing technology, the genomes of many medicinal plants have been sequenced. Storing and analyzing the increasing volume of genomic data has become an urgent task. To solve this challenge, we have proposed the Traditional Chinese Medicine Plant Genome database (TCMPG, http://cbcb.cdutcm.edu.cn/TCMPG/), an integrative database for storing the scattered genomes of medicinal plants. TCMPG currently includes 160 medicinal plants, 195 corresponding genomes, and 255 herbal medicines. Detailed information on plant species, genomes, and herbal medicines is also integrated into TCMPG. Popular genomic analysis tools are embedded in TCMPG to facilitate the systematic analysis of medicinal plants. These include BLAST for identifying orthologs from different plants, SSR Finder for identifying simple sequence repeats, JBrowse for browsing genomes, Synteny Viewer for displaying syntenic blocks between two genomes, and HmmSearch for identifying protein domains. TCMPG will be continuously updated by integrating new data and tools for comparative and functional genomic analysis.

Metagenomic Sequencing of Multiple Soil Horizons and Sites in Close Vicinity Revealed Novel Secondary Metabolite Diversity

Discovery of novel antibiotics is crucial for combating rapidly spreading antimicrobial resistance and new infectious diseases. Most of the clinically used antibiotics are natural products—secondary metabolites produced by soil microbes that can be cultured in the lab. Rediscovery of these secondary metabolites during discovery expeditions costs both time and resources. Metagenomics approaches can overcome this challenge by capturing both culturable and unculturable hidden microbial diversity. To be effective, such an approach should address questions like the following. Which sequencing method is better at capturing the microbial diversity and biosynthesis potential? What part of the soil should be sampled? Can patterns and correlations from such big-data explorations guide future novel natural product discovery surveys? Here, we address these questions by a paired amplicon and shotgun metagenomic sequencing survey of samples from soil horizons of multiple forest sites very close to each other. Metagenome mining identified numerous novel biosynthetic gene clusters (BGCs) and enzymatic domain sequences. Hybrid assembly of both long reads and short reads improved the metagenomic assembly and resulted in better BGC annotations. A higher percentage of novel domains was recovered from shotgun metagenome data sets than from amplicon data sets. Overall, in addition to revealing the biosynthetic potential of soil microbes, our results suggest the importance of sampling not only different soils but also their horizons to capture microbial and biosynthetic diversity and highlight the merits of metagenome sequencing methods.

IMPORTANCE This study helped uncover the biosynthesis potential of forest soils via exploration of shotgun metagenome and amplicon sequencing methods and showed that both methods are needed to expose the full microbial diversity in soil. Based on our metagenome mining results, we suggest revising the historical strategy of sampling soils from far-flung places, as we found a significant number of novel and diverse BGCs and domains even in different soils that are very close to each other. Furthermore, sampling of different soil horizons can reveal the additional diversity that often remains hidden and is mainly caused by differences in environmental key parameters such as soil pH and nutrient content. This paired metagenomic survey identified diversity patterns and correlations, a step toward developing a rational approach for future natural product discovery surveys.

Antibiotic Production and Antibiotic Resistance: The Two Sides of AbrB1/B2, a Two-Component System of Streptomyces coelicolor

Antibiotic resistance currently presents one of the biggest threats to humans. The development and implementation of strategies against the spread of superbugs is a priority for public health. In addition to raising social awareness, approaches such as the discovery of new antibiotic molecules and the elucidation of resistance mechanisms are common measures. Accordingly, the two-component system (TCS) of Streptomyces coelicolor AbrB1/B2, offer amenable ways to study both antibiotic production and resistance. Global transcriptomic comparisons between the wild-type strain S. coelicolor M145 and the mutant ΔabrB, using RNA-Seq, showed that the AbrB1/B2 TCS is implicated in the regulation of different biological processes associated with stress responses, primary and secondary metabolism, and development and differentiation. The ΔabrB mutant showed the up-regulation of antibiotic biosynthetic gene clusters and the down-regulation of the vancomycin resistance gene cluster, according to the phenotypic observations of increased antibiotic production of actinorhodin and undecylprodigiosin, and greater susceptibility to vancomycin. The role of AbrB1/B2 in vancomycin resistance has also been shown by an in silico analysis, which strongly indicates that AbrB1/B2 is a homolog of VraR/S from Staphylococcus aureus and LiaR/S from Enterococcus faecium/Enterococcus faecalis, both of which are implied in vancomycin resistance in these pathogenic organisms that present a serious threat to public health. The results obtained are interesting from a biotechnological perspective since, on one hand, this TCS is a negative regulator of antibiotic production and its high degree of conservation throughout Streptomyces spp. makes it a valuable tool for improving antibiotic production and the discovery of cryptic metabolites with antibiotic action. On the other hand, AbrB1/B2 contributes to vancomycin resistance and is a homolog of VraR/S and LiaR/S, important regulators in clinically relevant antibiotic-resistant bacteria. Therefore, the study of AbrB1/B2 could provide new insight into the mechanism of this type of resistance.

IMG-ABC v.5.0: an update to the IMG/Atlas of Biosynthetic Gene Clusters Knowledgebase

Microbial secondary metabolism is a reservoir of bioactive compounds of immense biotechnological and biomedical potential. The biosynthetic machinery responsible for the production of these secondary metabolites (SMs) (also called natural products) is often encoded by collocated groups of genes called biosynthetic gene clusters (BGCs). High-throughput genome sequencing of both isolates and metagenomic samples combined with the development of specialized computational workflows is enabling systematic identification of BGCs and the discovery of novel SMs. In order to advance exploration of microbial secondary metabolism and its diversity, we developed the largest publicly available database of predicted BGCs combined with experimentally verified BGCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc-public). Here we describe the first major content update of the IMG-ABC knowledgebase, since its initial release in 2015, refreshing the BGC prediction pipeline with the latest version of antiSMASH (v5) as well as presenting the data in the context of underlying environmental metadata sourced from GOLD (https://gold.jgi.doe.gov/). This update has greatly improved the quality and expanded the types of predicted BGCs compared to the previous version.