Microbial natural product databases: moving forward in the multi-omics era

Production of marine-derived bioactive peptide molecules for industrial applications: A reverse engineering approach

This review examines a wide range of marine microbial-derived bioactive peptide molecules, emphasizing the significance of reverse engineering in their production. The discussion encompasses the advancements in Marine Natural Products (MNPs) bio-manufacturing through the integration of omics-driven microbial engineering and bioinformatics. The distinctive features of non-ribosomally synthesised peptides (NRPs), and ribosomally synthesised precursor peptides (RiPP) biosynthesis is elucidated and presented. Additionally, the article delves into the origins of common peptide modifications. It highlights various genome mining approaches for the targeted identification of Biosynthetic Gene Clusters (BGCs) and novel RiPP and NRPs-derived peptides. The review aims to demonstrate the advancements, prospects, and obstacles in engineering both RiPP and NRP biosynthetic pathways.

Overview and limitations of database in global traditional medicines: A narrative review

The study of traditional medicine has garnered significant interest, resulting in various research areas including chemical composition analysis, pharmacological research, clinical application, and quality control. The abundance of available data has made databases increasingly essential for researchers to manage the vast amount of information and explore new drugs. In this article we provide a comprehensive overview and summary of 182 databases that are relevant to traditional medicine research, including 73 databases for chemical component analysis, 70 for pharmacology research, and 39 for clinical application and quality control from published literature (2000-2023). The review categorizes the databases by functionality, offering detailed information on websites and capacities to facilitate easier access. Moreover, this article outlines the primary function of each database, supplemented by case studies to aid in database selection. A practical test was conducted on 68 frequently used databases using keywords and functionalities, resulting in the identification of highlighted databases. This review serves as a reference for traditional medicine researchers to choose appropriate databases and also provides insights and considerations for the function and content design of future databases.

Two new di-tert-butyl-type compounds from a saline-lake derived Streptomyces sp. XZB42

Two novel di-tert-butyl-type structures (1-2), and five known compounds (3-7) were isolated from the chemical investigations of a saline lake actinomycete, Streptomyces sp. XZB42. The structures of the new compounds were elucidated by extensive NMR spectroscopic analysis, HRESIMS data, GIAO (gauge-including atomic orbitals) NMR and specific optical rotation (SOR).

Marine Pharmacology in 2019-2021: Marine Compounds with Antibacterial, Antidiabetic, Antifungal, Anti-Inflammatory, Antiprotozoal, Antituberculosis and Antiviral Activities; Affecting the Immune and Nervous Systems, and Other Miscellaneous Mechanisms of Action

The current 2019-2021 marine pharmacology literature review provides a continuation of previous reviews covering the period 1998 to 2018. Preclinical marine pharmacology research during 2019-2021 was published by researchers in 42 countries and contributed novel mechanism-of-action pharmacology for 171 structurally characterized marine compounds. The peer-reviewed marine natural product pharmacology literature reported antibacterial, antifungal, antiprotozoal, antituberculosis, and antiviral mechanism-of-action studies for 49 compounds, 87 compounds with antidiabetic and anti-inflammatory activities that also affected the immune and nervous system, while another group of 51 compounds demonstrated novel miscellaneous mechanisms of action, which upon further investigation, may contribute to several pharmacological classes. Thus, in 2019-2021, a very active preclinical marine natural product pharmacology pipeline provided novel mechanisms of action as well as new lead chemistry for the clinical marine pharmaceutical pipeline targeting the therapy of several disease categories.

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.

Harnessing the potential: advances in cyanobacterial natural product research and biotechnology

Covering: 2000 to 2023Cyanobacteria produce a variety of bioactive natural products that can pose a threat to humans and animals as environmental toxins, but also have potential for or inspire pharmaceutical use. As oxygenic phototrophs, cyanobacteria furthermore hold great promise for sustainable biotechnology. Yet, the necessary tools for exploiting their biotechnological potential have so far been established only for a few model strains of cyanobacteria, while large untapped biosynthetic resources are hidden in slow-growing cyanobacterial genera that are difficult to access by genetic techniques. In recent years, several approaches have been developed to circumvent the bottlenecks in cyanobacterial natural product research. Here, we summarize current progress that has been made in unlocking or characterizing cryptic metabolic pathways using integrated omics techniques, orphan gene cluster activation, use of genetic approaches in original producers, heterologous expression and chemo-enzymatic techniques. We are mainly highlighting genomic mining concepts and strategies towards high-titer production of cyanobacterial natural products from the last 10 years and discuss the need for further research developments in this field.

Discovery of Streptomyces species CS-62, a novel producer of the Acinetobacter baumannii selective antibiotic factumycin

Narrow-spectrum antibiotics are of great interest given their ability to spare the microbiome and decrease widespread antibiotic resistance compared to broad-spectrum antibiotics. Herein, we screened an in-house library of Actinobacteria strains for selective activity against Acinetobacter baumannii and successfully identified Streptomyces sp. CS-62 as a producer of a natural product with this valuable activity. Analysis of the cultures via high-resolution mass spectrometry and tandem mass spectrometry, followed by comparison with molecules in the Natural Product Atlas and the Global Natural Products Social Molecular Networking platform, suggested a novel natural product. Genome mining analysis initially supported the production of a novel kirromycin derivative. Isolation and structure elucidation via mass spectrometry and Nuclear Magnetic Resonance (NMR) analyses revealed that the active natural product was the known natural product factumycin, exposing omissions and errors in the consulted databases. While public databases are generally very useful for avoiding rediscovery of known molecules, rediscovery remains a problem due to public databases either being incomplete or having errors that result in failed dereplication. Overall, the work describes the ongoing problem of dereplication and the continued need for public database curation.

Natural product biosynthetic potential reflects macroevolutionary diversification within a widely distributed bacterial taxon

IMPORTANCE

This is the most comprehensive study performed thus far on the biosynthetic potential within the Flavobacteriaceae family. Our findings reveal intertwined taxonomic and natural product biosynthesis diversification within the family. We posit that the carbohydrate, peptide, and secondary metabolism triad synergistically shaped the evolution of this keystone bacterial taxon, acting as major forces underpinning the broad host range and opportunistic-to-pathogenic behavior encompassed by species in the family. This study further breaks new ground for future research on select Flavobacteriaceae spp. as reservoirs of novel drug leads.

PhyloSophos: a high-throughput scientific name mapping algorithm augmented with explicit consideration of taxonomic science, and its application on natural product (NP) occurrence database processing

BACKGROUND

The standardization of biological data using unique identifiers is vital for seamless data integration, comprehensive interpretation, and reproducibility of research findings, contributing to advancements in bioinformatics and systems biology. Despite being widely accepted as a universal identifier, scientific names for biological species have inherent limitations, including lack of stability, uniqueness, and convertibility, hindering their effective use as identifiers in databases, particularly in natural product (NP) occurrence databases, posing a substantial obstacle to utilizing this valuable data for large-scale research applications.

RESULT

To address these challenges and facilitate high-throughput analysis of biological data involving scientific names, we developed PhyloSophos, a Python package that considers the properties of scientific names and taxonomic systems to accurately map name inputs to entries within a chosen reference database. We illustrate the importance of assessing multiple taxonomic databases and considering taxonomic syntax-based pre-processing using NP occurrence databases as an example, with the ultimate goal of integrating heterogeneous information into a single, unified dataset.

CONCLUSIONS

We anticipate PhyloSophos to significantly aid in the systematic processing of poorly digitized and curated biological data, such as biodiversity information and ethnopharmacological resources, enabling full-scale bioinformatics analysis using these valuable data resources.

EMNPD: a comprehensive endophytic microorganism natural products database for prompt the discovery of new bioactive substances

The discovery and utilization of natural products derived from endophytic microorganisms have garnered significant attention in pharmaceutical research. While remarkable progress has been made in this field each year, the absence of dedicated open-access databases for endophytic microorganism natural products research is evident. To address the increasing demand for mining and sharing of data resources related to endophytic microorganism natural products, this study introduces EMNPD, a comprehensive endophytic microorganism natural products database comprising manually curated data. Currently, EMNPD offers 6632 natural products from 1017 endophytic microorganisms, targeting 1286 entities (including 94 proteins, 282 cell lines, and 910 species) with 91 diverse bioactivities. It encompasses the physico-chemical properties of natural products, ADMET information, quantitative activity data with their potency, natural products contents with diverse fermentation conditions, systematic taxonomy, and links to various well-established databases. EMNPD aims to function as an open-access knowledge repository for the study of endophytic microorganisms and their natural products, thereby facilitating drug discovery research and exploration of bioactive substances. The database can be accessed at http://emnpd.idrblab.cn/ without the need for registration, enabling researchers to freely download the data. EMNPD is expected to become a valuable resource in the field of endophytic microorganism natural products and contribute to future drug development endeavors.

A Data Deposition Platform for Sharing Nuclear Magnetic Resonance Data

Nuclear magnetic resonance (NMR) data are rarely deposited in open databases, leading to loss of critical scientific knowledge. Existing data reporting methods (images, tables, lists of values) contain less information than raw data and are poorly standardized. Together, these issues limit FAIR (findable, accessible, interoperable, reusable) access to these data, which in turn creates barriers for compound dereplication and the development of new data-driven discovery tools. Existing NMR databases either are not designed for natural products data or employ complex deposition interfaces that disincentivize deposition. Journals, including the Journal of Natural Products (JNP), are now requiring data submission as part of the publication process, creating the need for a streamlined, user-friendly mechanism to deposit and distribute NMR data.

Modeling control and transduction of electrochemical gradients in acid-stressed bacteria

Transmembrane electrochemical gradients drive solute uptake and constitute a substantial fraction of the cellular energy pool in bacteria. These gradients act not only as "homeostatic contributors," but also play a dynamic and keystone role in several bacterial functions, including sensing, stress response, and metabolism. At the system level, multiple gradients interact with ion transporters and bacterial behavior in a complex, rapid, and emergent manner; consequently, experiments alone cannot untangle their interdependencies. Electrochemical gradient modeling provides a general framework to understand these interactions and their underlying mechanisms. We quantify the generation, maintenance, and interactions of electrical, proton, and potassium potential gradients under lactic acid-stress and lactic acid fermentation. Further, we elucidate a gradient-mediated mechanism for intracellular pH sensing and stress response. We demonstrate that this gradient model can yield insights on the energetic limitations of membrane transport, and can predict bacterial behavior across changing environments.

Applications of machine learning in microbial natural product drug discovery

INTRODUCTION

Natural products (NPs) are a desirable source of new therapeutics due to their structural diversity and evolutionarily optimized bioactivities. NPs and their derivatives account for roughly 70% of approved pharmaceuticals. However, the rate at which novel NPs are discovered has decreased. To accelerate the microbial NP discovery process, machine learning (ML) is being applied to numerous areas of NP discovery and development.

AREAS COVERED

This review explores the utility of ML at various phases of the microbial NP drug discovery pipeline, discussing concrete examples throughout each major phase: genome mining, dereplication, and biological target prediction. Moreover, the authors discuss how ML approaches can be applied to semi-synthetic approaches to drug discovery.

EXPERT OPINION

Despite the important role that microbial NPs play in the development of novel drugs, their discovery has declined due to challenges associated with the conventional discovery process. ML is positioned to overcome these limitations given its ability to model complex datasets and generalize to novel chemical and sequence space. Unsurprisingly, ML comes with its own limitations that must be considered for its successful implementation. The authors stress the importance of continuing to build high quality and open access NP datasets to further increase the utility of ML in NP discovery.

Global analysis of the biosynthetic chemical space of marine prokaryotes

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. Video Abstract.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.

Santalane-type sesquiterpenoids and isobenzofuranones from cultures of Paraconiothyrium sporulosum YK-03

Three undescribed santalane-type sesquiterpenoids (parasantalenoic acids A-C) and two undescribed epimeric isobenzofuranones (paraphthalides A and B) were isolated from cultures of the marine mud-associated fungus Paraconiothyrium sporulosum YK-03. Their structures were elucidated by analysis of the extensive spectroscopic and crystal X-ray diffraction data, combined with ECD calculations and comparison. Santalane-type sesquiterpenoids have been firstly found in the Paraconiothyrium species. Parasantalenoic acids A-C represent three rare polyhydroxylated santalane-type sesquiterpenoid carboxylic acids, and parasantalenoic acid A represents the first example of 2-chlorinated santalane-type sesquiterpenoid. A plausible biosynthetic pathway for parasantalenoic acids A-C was proposed. Additionally, the anti-neuroinflammatory activities of parasantalenoic acids A-C were investigated by evaluating their inhibitory effects on nitric oxide (NO) production in lipopolysaccharide (LPS)-stimulated BV-2 microglia cells. Among them, parasantalenoic acid C showed significant anti-neuroinflammatory activity with an inhibition of 86.45 ± 2.45% at 10 μM.

Modern Trends in Natural Antibiotic Discovery

Natural scaffolds remain an important basis for drug development. Therefore, approaches to natural bioactive compound discovery attract significant attention. In this account, we summarize modern and emerging trends in the screening and identification of natural antibiotics. The methods are divided into three large groups: approaches based on microbiology, chemistry, and molecular biology. The scientific potential of the methods is illustrated with the most prominent and recent results.

SynBioTools: a one-stop facility for searching and selecting synthetic biology tools

BACKGROUND

The rapid development of synthetic biology relies heavily on the use of databases and computational tools, which are also developing rapidly. While many tool registries have been created to facilitate tool retrieval, sharing, and reuse, no relatively comprehensive tool registry or catalog addresses all aspects of synthetic biology.

RESULTS

We constructed SynBioTools, a comprehensive collection of synthetic biology databases, computational tools, and experimental methods, as a one-stop facility for searching and selecting synthetic biology tools. SynBioTools includes databases, computational tools, and methods extracted from reviews via SCIentific Table Extraction, a scientific table-extraction tool that we built. Approximately 57% of the resources that we located and included in SynBioTools are not mentioned in bio.tools, the dominant tool registry. To improve users' understanding of the tools and to enable them to make better choices, the tools are grouped into nine modules (each with subdivisions) based on their potential biosynthetic applications. Detailed comparisons of similar tools in every classification are included. The URLs, descriptions, source references, and the number of citations of the tools are also integrated into the system.

CONCLUSIONS

SynBioTools is freely available at https://synbiotools.lifesynther.com/ . It provides end-users and developers with a useful resource of categorized synthetic biology databases, tools, and methods to facilitate tool retrieval and selection.

An untargeted exometabolomics approach to characterize dissolved organic matter in groundwater of the Samail Ophiolite

The process of serpentinization supports life on Earth and gives rise to the habitability of other worlds in our Solar System. While numerous studies have provided clues to the survival strategies of microbial communities in serpentinizing environments on the modern Earth, characterizing microbial activity in such environments remains challenging due to low biomass and extreme conditions. Here, we used an untargeted metabolomics approach to characterize dissolved organic matter in groundwater in the Samail Ophiolite, the largest and best characterized example of actively serpentinizing uplifted ocean crust and mantle. We found that dissolved organic matter composition is strongly correlated with both fluid type and microbial community composition, and that the fluids that were most influenced by serpentinization contained the greatest number of unique compounds, none of which could be identified using the current metabolite databases. Using metabolomics in conjunction with metagenomic data, we detected numerous products and intermediates of microbial metabolic processes and identified potential biosignatures of microbial activity, including pigments, porphyrins, quinones, fatty acids, and metabolites involved in methanogenesis. Metabolomics techniques like the ones used in this study may be used to further our understanding of life in serpentinizing environments, and aid in the identification of biosignatures that can be used to search for life in serpentinizing systems on other worlds.

Marine natural products

Covering: January to December 2021This review covers the literature published in 2021 for marine natural products (MNPs), with 736 citations (724 for the period January to December 2021) referring to compounds isolated from marine microorganisms and phytoplankton, green, brown and red algae, sponges, cnidarians, bryozoans, molluscs, tunicates, echinoderms, mangroves and other intertidal plants and microorganisms. The emphasis is on new compounds (1425 in 416 papers for 2021), together with the relevant biological activities, source organisms and country of origin. Pertinent reviews, biosynthetic studies, first syntheses, and syntheses that led to the revision of structures or stereochemistries, have been included. An analysis of the number of authors, their affiliations, domestic and international collection locations, focus of MNP studies, citation metrics and journal choices is discussed.

Streptomyces cell-free systems for natural product discovery and engineering

Streptomyces bacteria are a major microbial source of natural products, which are encoded within so-called biosynthetic gene clusters (BGCs). This highlight discusses the emergence of native Streptomyces cell-free systems as a new tool to accelerate the study of the fundamental chemistry and biology of natural product biosynthesis from these bacteria. Cell-free systems provide a prototyping platform to study plug-and-play reactions in microscale reactions. So far, Streptomyces cell-free systems have been used to rapidly characterise gene expression regulation, access secondary metabolite biosynthetic enzymes, and catalyse cell-free transcription, translation, and biosynthesis of example natural products. With further progress, we anticipate the development of more complex systems to complement existing experimental tools for the discovery and engineering of natural product biosynthesis from Streptomyces and related high G + C (%) bacteria.

Engineering the biosynthesis of fungal nonribosomal peptides

Covering: 2011 up to the end of 2021.Fungal nonribosomal peptides (NRPs) and the related polyketide-nonribosomal peptide hybrid products (PK-NRPs) are a prolific source of bioactive compounds, some of which have been developed into essential drugs. The synthesis of these complex natural products (NPs) utilizes nonribosomal peptide synthetases (NRPSs), multidomain megaenzymes that assemble specific peptide products by sequential condensation of amino acids and amino acid-like substances, independent of the ribosome. NRPSs, collaborating polyketide synthase modules, and their associated tailoring enzymes involved in product maturation represent promising targets for NP structure diversification and the generation of small molecule unnatural products (uNPs) with improved or novel bioactivities. Indeed, reprogramming of NRPSs and recruiting of novel tailoring enzymes is the strategy by which nature evolves NRP products. The recent years have witnessed a rapid development in the discovery and identification of novel NRPs and PK-NRPs, and significant advances have also been made towards the engineering of fungal NRP assembly lines to generate uNP peptides. However, the intrinsic complexities of fungal NRP and PK-NRP biosynthesis, and the large size of the NRPSs still present formidable conceptual and technical challenges for the rational and efficient reprogramming of these pathways. This review examines key examples for the successful (and for some less-successful) re-engineering of fungal NRPS assembly lines to inform future efforts towards generating novel, biologically active peptides and PK-NRPs.

Functional modulation of chemical mediators in microbial communities

Interactions between microorganisms are often mediated by specialized metabolites. Although the structures and biosynthesis of these compounds may have been elucidated, microbes exist within complex microbiomes and chemical signals can thus also be subject to community-dependent modifications. Increasingly powerful chemical and biological tools allow to shed light on this poorly understood aspect of chemical ecology. We provide an overview of loss-of-function and gain-of-function chemical mediator (CM) modifications within microbial multipartner relationships. Although loss-of-function modifications are abundant in the literature, few gain-of-function modifications have been described despite their important role in microbial interactions. Research in this field holds great potential for our understanding of microbial interactions and may also provide novel tools for targeted interference with microbial signaling.

Structure Elucidation of Antibiotics

To date, there are hundreds of characterized natural products with antibacterial activity against pathogenic bacteria, and several have become bonafide antibiotic drugs. The development of antibacterial natural products into antibiotic drugs, both in the past and in the future, hinges upon an accurate description of the exact chemical structure of the compound. Bolstered by some form of mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy is the primary technique for elucidating the chemical structure of organic molecules including natural products. By combining various one-dimensional (1D) and two-dimensional (2D) experiments, the connectivity between atoms is established and a complete "picture" of the molecule is thereby revealed.

Discovering New Natural Products Using Metabolomics-Based Approaches

The incessant search for new natural molecules with biological activities has forced researchers in the field of chemistry of natural products to seek different approaches for their prospection studies. In particular, researchers around the world are turning to approaches in metabolomics to avoid high rates of re-isolation of certain compounds, something recurrent in this branch of science. Thanks to the development of new technologies in the analytical instrumentation of spectroscopic and spectrometric techniques, as well as the advance in the computational processing modes of the results, metabolomics has been gaining more and more space in studies that involve the prospection of natural products. Thus, this chapter summarizes the precepts and good practices in the metabolomics of microbial natural products using mass spectrometry and nuclear magnetic resonance spectroscopy, and also summarizes several examples where this approach has been applied in the discovery of bioactive molecules.

Artificial intelligence in microbial natural product drug discovery: current and emerging role

Covering: up to the end of 2022Microorganisms are exceptional sources of a wide array of unique natural products and play a significant role in drug discovery. During the golden era, several life-saving antibiotics and anticancer agents were isolated from microbes; moreover, they are still widely used. However, difficulties in the isolation methods and repeated discoveries of the same molecules have caused a setback in the past. Artificial intelligence (AI) has had a profound impact on various research fields, and its application allows the effective performance of data analyses and predictions. With the advances in omics, it is possible to obtain a wealth of information for the identification, isolation, and target prediction of secondary metabolites. In this review, we discuss drug discovery based on natural products from microorganisms with the help of AI and machine learning.

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.

A Candidate Gene Cluster for the Bioactive Natural Product Gyrophoric Acid in Lichen-Forming Fungi

Natural products of lichen-forming fungi are structurally diverse and have a variety of medicinal properties. Despite this, they have limited implementation in industry mostly because the corresponding genes are unknown for most of their natural products. Here, we implement a long-read sequencing and bioinformatic approach to identify the putative biosynthetic gene cluster of the bioactive natural product gyrophoric acid (GA). Using 15 high-quality genomes representing nine GA-producing species of the lichen-forming fungal genus Umbilicaria, we identify the most likely GA cluster and investigate the cluster gene organization and composition across the nine species. Our results show that GA clusters are promiscuous within Umbilicaria, and only three genes are conserved across species, including the polyketide synthase (PKS) gene. In addition, our results suggest that the same cluster codes for different, but structurally similar compounds, namely, GA, umbilicaric-, and hiascic acid, bringing new evidence that lichen metabolite diversity is also generated through regulatory mechanisms at the molecular level. Ours is the first study to identify the most likely GA cluster and, thus, provides essential information to open new avenues for biotechnological approaches to producing and modifying GA and similar lichen-derived compounds. GA PKS is the first tridepside PKS to be identified.

IMPORTANCE The implementation of natural products in the pharmaceutical industry relies on the possibility of modifying the natural product (NP) pathway to optimize yields and pharmacological effects. Characterization of genes and pathways underlying natural product biosynthesis is a major bottleneck for exploiting the medicinal properties of the natural products. Genome mining is a promising and relatively cost- and time-effective approach to utilize unexplored NP resources for drug discovery. In this study, we identify the most likely gene cluster for the lichen-forming fungal depside gyrophoric acid in nine Umbilicaria species. This compound shows cytotoxic and antiproliferative properties against several cancer cell lines and is also a broad-spectrum antimicrobial agent. This information paves the way for generating GA analogs with modified properties by selective activation/deactivation of genes.

Genomic and Chemical Decryption of the Bacteroidetes Phylum for Its Potential to Biosynthesize Natural Products

With progress in genome sequencing and data sharing, 1,000s of bacterial genomes are publicly available. Genome mining-using bioinformatics tools in terms of biosynthetic gene cluster (BGC) identification, analysis, and rating-has become a key technology to explore the capabilities for natural product (NP) biosynthesis. Comprehensively, analyzing the genetic potential of the phylum Bacteroidetes revealed Chitinophaga as the most talented genus in terms of BGC abundance and diversity. Guided by the computational predictions, we conducted a metabolomics and bioactivity driven NP discovery program on 25 Chitinophaga strains. High numbers of strain-specific metabolite buckets confirmed the upfront predicted biosynthetic potential and revealed a tremendous uncharted chemical space. Mining this data set, we isolated the new iron chelating nonribosomally synthesized cyclic tetradeca- and pentadecalipodepsipeptide antibiotics chitinopeptins with activity against Candida, produced by C. eiseniae DSM 22224 and C. flava KCTC 62435, respectively. IMPORTANCE The development of pipelines for anti-infectives to be applied in plant, animal, and human health management are dried up. However, the resistance development against compounds in use calls for new lead structures. To fill this gap and to enhance the probability of success for the discovery of new bioactive natural products, microbial taxa currently underinvestigated must be mined. This study investigates the potential within the bacterial phylum Bacteroidetes. A combination of omics-technologies revealed taxonomical hot spots for specialized metabolites. Genome- and metabolome-based analyses showed that the phylum covers a new chemical space compared with classic natural product producers. Members of the Bacteroidetes may thus present a promising bioresource for future screening and isolation campaigns.

Investigation of the Molecular Landscape of Bacterial Aromatic Polyketides by Global Analysis of Type II Polyketide Synthases

Aromatic polyketides biosynthesized by microorganisms are a prominent class of natural products widely used in clinical treatments. Although genome mining approaches have accelerated the discovery of these molecules, the molecular diversity, abundance, and distribution of bacterial aromatic polyketides at a global scale remain elusive. Here, we provide a global atlas of bacterial aromatic polyketides based on large-scale analysis of type II polyketide synthases. We first established the chain length factor protein as a marker that can predict both chemical class and molecular uniqueness of the biosynthetic product, and analyzed the abundance, taxonomic distribution, estimated structural diversity, and the total number of aromatic polyketides in bacteria. We further show the identification of oryzanaphthopyrans with an unprecedented angular naphthopyran scaffold from a rare actinobacterium by genome mining guided by the global atlas. These results serve as a compass for exploiting the entire type II polyketide synthase-derived aromatic polyketides in bacteria.

Updated Trends on the Biodiscovery of New Marine Natural Products from Invertebrates

From 1990–2019, a total of 15,442 New Marine Natural Products from Invertebrates (NMNPIs) were reported. The 2010s saw the most prolific decade of biodiscovery, with 5630 NMNPIs recorded. The phyla that contributed most biomolecules were the Porifera (sponges) (47.2%, 2659 NMNPIs) and the Cnidaria (35.3%, 1989 NMNPIs). The prevalence of these two phyla as the main sources of NMNPIs became more pronounced in the 2010s. The tropical areas of the Pacific Ocean yielded more NMNPIs, most likely due to the remarkable biodiversity of coral reefs. The Indo-Burma biodiversity hotspot (BH) was the most relevant area for the biodiscovery of NMNPIs in the 2010s, accounting for nearly one-third (1819 NMNPIs) of the total and surpassing the top BH from the 1990s and the 2000s (the Sea of Japan and the Caribbean Islands, respectively). The Chinese exclusive economic zone (EEZ) alone contributed nearly one-quarter (24.7%) of all NMNPIs recorded during the 2010s, displacing Japan’s leading role from the 1990s and the 2000s. With the biodiscovery of these biomolecules steadily decreasing since 2012, it is uncertain whether this decline has been caused by lower bioprospecting efforts or the potential exhaustion of chemodiversity from traditional marine invertebrate sources.

Biosynthesis of Fungal Natural Products Involving Two Separate Pathway Crosstalk

Fungal natural products (NPs) usually possess complicated structures, exhibit satisfactory bioactivities, and are an outstanding source of drug leads, such as the cholesterol-lowering drug lovastatin and the immunosuppressive drug mycophenolic acid. The fungal NPs biosynthetic genes are always arranged within one single biosynthetic gene cluster (BGC). However, a rare but fascinating phenomenon that a crosstalk between two separate BGCs is indispensable to some fungal dimeric NPs biosynthesis has attracted increasing attention. The hybridization of two separate BGCs not only increases the structural complexity and chemical diversity of fungal NPs, but also expands the scope of bioactivities. More importantly, the underlying mechanism for this hybridization process is poorly understood and needs further exploration, especially the determination of BGCs for each building block construction and the identification of enzyme(s) catalyzing the two biosynthetic precursors coupling processes such as Diels–Alder cycloaddition and Michael addition. In this review, we summarized the fungal NPs produced by functional crosstalk of two discrete BGCs, and highlighted their biosynthetic processes, which might shed new light on genome mining for fungal NPs with unprecedented frameworks, and provide valuable insights into the investigation of mysterious biosynthetic mechanisms of fungal dimeric NPs which are constructed by collaboration of two separate BGCs.

Unveiling the genomic potential of Pseudomonas type strains for discovering new natural products

Microbes host a huge variety of biosynthetic gene clusters that produce an immeasurable array of secondary metabolites with many different biological activities such as antimicrobial, anticarcinogenic and antiviral. Despite the complex task of isolating and characterizing novel natural products, microbial genomic strategies can be useful for carrying out these types of studies. However, although genomic-based research on secondary metabolism is on the increase, there is still a lack of reports focusing specifically on the genus Pseudomonas. In this work, we aimed (i) to unveil the main biosynthetic systems related to secondary metabolism in Pseudomonas type strains, (ii) to study the evolutionary processes that drive the diversification of their coding regions and (iii) to select Pseudomonas strains showing promising results in the search for useful natural products. We performed a comparative genomic study on 194 Pseudomonas species, paying special attention to the evolution and distribution of different classes of biosynthetic gene clusters and the coding features of antimicrobial peptides. Using EvoMining, a bioinformatic approach for studying evolutionary processes related to secondary metabolism, we sought to decipher the protein expansion of enzymes related to the lipid metabolism, which may have evolved toward the biosynthesis of novel secondary metabolites in Pseudomonas. The types of metabolites encoded in Pseudomonas type strains were predominantly non-ribosomal peptide synthetases, bacteriocins, N-acetylglutaminylglutamine amides and ß-lactones. Also, the evolution of genes related to secondary metabolites was found to coincide with Pseudomonas species diversification. Interestingly, only a few Pseudomonas species encode polyketide synthases, which are related to the lipid metabolism broadly distributed among bacteria. Thus, our EvoMining-based search may help to discover new types of secondary metabolite gene clusters in which lipid-related enzymes are involved. This work provides information about uncharacterized metabolites produced by Pseudomonas type strains, whose gene clusters have evolved in a species-specific way. Our results provide novel insight into the secondary metabolism of Pseudomonas and will serve as a basis for the prioritization of the isolated strains. This article contains data hosted by Microreact.

Evolutionary Genome Mining for the Discovery and Engineering of Natural Product Biosynthesis

Genome mining has become an invaluable tool in natural products research to quickly identify and characterize the biosynthetic pathways that assemble secondary or specialized metabolites. Recently, evolutionary principles have been incorporated into genome mining strategies in an effort to better assess and prioritize novelty and understand their chemical diversification for engineering purposes. Here, we provide an introduction to the principles underlying evolutionary genome mining, including bioinformatic strategies and natural product biosynthetic databases. We introduce workflows for traditional genome mining, focusing on the popular pipeline antiSMASH, and methods to predict enzyme substrate specificity from genomic information. We then provide an in-depth discussion of evolutionary genome mining workflows, including EvoMining, CORASON, ARTS, and others, as adopted by our group for the discovery and prioritization of natural products biosynthetic gene clusters and their products.

Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities

Covering: 2010 to 2021Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.

Advancements in capturing and mining mass spectrometry data are transforming natural products research

Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.

Marine natural products targeting the eukaryotic cell membrane

The cell membrane, with high fluidity and alternative curvatures, maintains the robust integrity to distinguish inner and outer space of cells or organelles. Lipids are the main components of the cell membrane, but their functions are largely unknown. Even the visualization of lipids is not straightforward since modification of lipids often hampers its correct physical properties. Many natural products target cell membranes, some of which are used as pharmaceuticals and/or research tools. They show specific recognition on lipids, and thus exhibit desired pharmacological effects and unique biological phenotypes. This review is a catalog of marine natural products that target eukaryotic cell membranes. Chemical structures, biological activities, and molecular mechanisms are summarized. I hope that this review will be helpful for readers to notice the potential of marine natural products in the exploration of the function of lipids and the druggability of eukaryotic cell membranes.

Activation of Cryptic Antibiotic Biosynthetic Gene Clusters Guided by RNA-seq Data from Both Streptomyces ansochromogenes and ΔwblA

With the increase of drug resistance caused by the improper use and abuse of antibiotics, human beings are facing a global health crisis. Sequencing of Streptomyces genomes revealed the presence of an important reservoir of secondary metabolic gene clusters for previously unsuspected products with potentially valuable bioactivity. It has therefore become necessary to activate these cryptic pathways through various strategies. Here, we used RNA-seq data to perform a comparative transcriptome analysis of Streptomyces ansochromogenes (wild-type, WT) and its global regulatory gene disruption mutant ΔwblA, in which some differentially expressed genes are associated with the abolished nikkomycin biosynthesis and activated tylosin analogue compounds (TACs) production, and also with the oviedomycin production that is induced by the genetic manipulation of two differentially expressed genes (san7324 and san7324L) encoding RsbR. These results provide a significant clue for the discovery of new drug candidates and the activation of cryptic biosynthetic gene clusters.

Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop

We report the major conclusions of the online open-access workshop "Computational Applications in Secondary Metabolite Discovery (CAiSMD)" that took place from 08 to 10 March 2021. Invited speakers from academia and industry and about 200 registered participants from five continents (Africa, Asia, Europe, South America, and North America) took part in the workshop. The workshop highlighted the potential applications of computational methodologies in the search for secondary metabolites (SMs) or natural products (NPs) as potential drugs and drug leads. During 3 days, the participants of this online workshop received an overview of modern computer-based approaches for exploring NP discovery in the "omics" age. The invited experts gave keynote lectures, trained participants in hands-on sessions, and held round table discussions. This was followed by oral presentations with much interaction between the speakers and the audience. Selected applicants (early-career scientists) were offered the opportunity to give oral presentations (15 min) and present posters in the form of flash presentations (5 min) upon submission of an abstract. The final program available on the workshop website ( https://caismd.indiayouth.info/ ) comprised of 4 keynote lectures (KLs), 12 oral presentations (OPs), 2 round table discussions (RTDs), and 5 hands-on sessions (HSs). This meeting report also references internet resources for computational biology in the area of secondary metabolites that are of use outside of the workshop areas and will constitute a long-term valuable source for the community. The workshop concluded with an online survey form to be completed by speakers and participants for the goal of improving any subsequent editions.

Burkholderia in the genomic era: from taxonomy to the discovery of new antimicrobial secondary metabolites

Species of Burkholderia are highly versatile being found not only abundantly in soil, but also as plants and animals' commensals or pathogens. Their complex multireplicon genomes harbour an impressive number of polyketide synthase (PKS) and nonribosomal peptide-synthetase (NRPS) genes coding for the production of antimicrobial secondary metabolites (SMs), which have been successfully deciphered by genome-guided tools. Moreover, genome metrics supported the split of this genus into Burkholderia sensu stricto (s.s.) and five new other genera. Here, we show that the successful antimicrobial SMs producers belong to Burkholderia s.s. Additionally, we reviewed the occurrence, bioactivities, modes of action, structural, and biosynthetic information of thirty-eight Burkholderia antimicrobial SMs shedding light on their diversity, complexity, and uniqueness as well as the importance of genome-guided strategies to facilitate their discovery. Several Burkholderia NRPS and PKS display unusual features, which are reflected in their structural diversity, important bioactivities, and varied modes of action. Up to now, it is possible to observe a general tendency of Burkholderia SMs being more active against fungi. Although the modes of action and biosynthetic gene clusters of many SMs remain unknown, we highlight the potential of Burkholderia SMs as alternatives to fight against new diseases and antibiotic resistance.

Effective approaches to discover new microbial metabolites in a large strain library

Natural products have provided many molecules to treat and prevent illnesses in humans, animals and plants. While only a small fraction of the existing microbial diversity has been explored for bioactive metabolites, tens of thousands of molecules have been reported in the literature over the past 80 years. Thus, the main challenge in microbial metabolite screening is to avoid the re-discovery of known metabolites in a cost-effective manner. In this perspective, we report and discuss different approaches used in our laboratory over the past few years, ranging from bioactivity-based screening to looking for metabolic rarity in different datasets to deeply investigating a single Streptomyces strain. Our results show that it is possible to find novel chemistry through a limited screening effort, provided that appropriate selection criteria are in place.

Biosynthesis and Heterologous Expression of Cacaoidin, the First Member of the Lanthidin Family of RiPPs

Cacaoidin is produced by the strain Streptomyces cacaoi CA-170360 and represents the first member of the new lanthidin (class V lanthipeptides) RiPP family. In this work, we describe the complete identification, cloning and heterologous expression of the cacaoidin biosynthetic gene cluster, which shows unique RiPP genes whose functions were not predicted by any bioinformatic tool. We also describe that the cacaoidin pathway is restricted to strains of the subspecies Streptomyces cacaoi subsp. cacaoi found in public genome databases, where we have also identified the presence of other putative class V lanthipeptide pathways. This is the first report on the heterologous production of a class V lanthipeptide.

Synergizing the potential of bacterial genomics and metabolomics to find novel antibiotics

Antibiotic development based on natural products has faced a long lasting decline since the 1970s, while both the speed and the extent of antimicrobial resistance (AMR) development have been severely underestimated. The discovery of antimicrobial natural products of bacterial and fungal origin featuring new chemistry and previously unknown mode of actions is increasingly challenged by rediscovery issues. Natural products that are abundantly produced by the corresponding wild type organisms often featuring strong UV signals have been extensively characterized, especially the ones produced by extensively screened microbial genera such as streptomycetes. Purely synthetic chemistry approaches aiming to replace the declining supply from natural products as starting materials to develop novel antibiotics largely failed to provide significant numbers of antibiotic drug leads. To cope with this fundamental issue, microbial natural products science is being transformed from a 'grind-and-find' study to an integrated approach based on bacterial genomics and metabolomics. Novel technologies in instrumental analytics are increasingly employed to lower detection limits and expand the space of detectable substance classes, while broadening the scope of accessible and potentially bioactive natural products. Furthermore, the almost exponential increase in publicly available bacterial genome data has shown that the biosynthetic potential of the investigated strains by far exceeds the amount of detected metabolites. This can be judged by the discrepancy between the number of biosynthetic gene clusters (BGC) encoded in the genome of each microbial strain and the number of secondary metabolites actually detected, even when considering the increased sensitivity provided by novel analytical instrumentation. In silico annotation tools for biosynthetic gene cluster classification and analysis allow fast prioritization in BGC-to-compound workflows, which is highly important to be able to process the enormous underlying data volumes. BGC prioritization is currently accompanied by novel molecular biology-based approaches to access the so-called orphan BGCs not yet correlated with a secondary metabolite. Integration of metabolomics, in silico genomics and molecular biology approaches into the mainstream of natural product research will critically influence future success and impact the natural product field in pharmaceutical, nutritional and agrochemical applications and especially in anti-infective research.

Recent Advances in Silent Gene Cluster Activation in Streptomyces

Natural products (NPs) are critical sources of drug molecules for decades. About two-thirds of natural antibiotics are produced by Streptomyces. Streptomyces have a large number of secondary metabolite biosynthetic gene clusters (SM-BGCs) that may encode NPs. However, most of these BGCs are silent under standard laboratory conditions. Hence, activation of these silent BGCs is essential to current natural products discovery research. In this review, we described the commonly used strategies for silent BGC activation in Streptomyces from two aspects. One focused on the strategies applied in heterologous host, including methods to clone and reconstruct BGCs along with advances in chassis engineering; the other focused on methods applied in native host which includes engineering of promoters, regulatory factors, and ribosomes. With the metabolic network being elucidated more comprehensively and methods optimized more high-thoroughly, the discovery of NPs will be greatly accelerated.

Comparative Metabologenomics Analysis of Polar Actinomycetes

Biosynthetic and chemical datasets are the two major pillars for microbial drug discovery in the omics era. Despite the advancement of analysis tools and platforms for multi-strain metabolomics and genomics, linking these information sources remains a considerable bottleneck in strain prioritisation and natural product discovery. In this study, molecular networking of the 100 metabolite extracts derived from applying the OSMAC approach to 25 Polar bacterial strains, showed growth media specificity and potential chemical novelty was suggested. Moreover, the metabolite extracts were screened for antibacterial activity and promising selective bioactivity against drug-persistent pathogens such as Klebsiella pneumoniae and Acinetobacter baumannii was observed. Genome sequencing data were combined with metabolomics experiments in the recently developed computational approach, NPLinker, which was used to link BGC and molecular features to prioritise strains for further investigation based on biosynthetic and chemical information. Herein, we putatively identified the known metabolites ectoine and chrloramphenicol which, through NPLinker, were linked to their associated BGCs. The metabologenomics approach followed in this study can potentially be applied to any large microbial datasets for accelerating the discovery of new (bioactive) specialised metabolites.