Computational Tools for Discovering and Engineering Natural Product Biosynthetic Pathways

Bioactivity-driven fungal metabologenomics identifies antiproliferative stemphone analogs and their biosynthetic gene cluster

INTRODUCTION

Fungi biosynthesize chemically diverse secondary metabolites with a wide range of biological activities. Natural product scientists have increasingly turned towards bioinformatics approaches, combining metabolomics and genomics to target secondary metabolites and their biosynthetic machinery. We recently applied an integrated metabologenomics workflow to 110 fungi and identified more than 230 high-confidence linkages between metabolites and their biosynthetic pathways.

OBJECTIVES

To prioritize the discovery of bioactive natural products and their biosynthetic pathways from these hundreds of high-confidence linkages, we developed a bioactivity-driven metabologenomics workflow combining quantitative chemical information, antiproliferative bioactivity data, and genome sequences.

METHODS

The 110 fungi from our metabologenomics study were tested against multiple cancer cell lines to identify which strains produced antiproliferative natural products. Three strains were selected for further study, fractionated using flash chromatography, and subjected to an additional round of bioactivity testing and mass spectral analysis. Data were overlaid using biochemometrics analysis to predict active constituents early in the fractionation process following which their biosynthetic pathways were identified using metabologenomics.

RESULTS

We isolated three new-to-nature stemphone analogs, 19-acetylstemphones G (1), B (2) and E (3), that demonstrated antiproliferative activity ranging from 3 to 5 µM against human melanoma (MDA-MB-435) and ovarian cancer (OVACR3) cells. We proposed a rational biosynthetic pathway for these compounds, highlighting the potential of using bioactivity as a filter for the analysis of integrated-Omics datasets.

CONCLUSIONS

This work demonstrates how the incorporation of biochemometrics as a third dimension into the metabologenomics workflow can identify bioactive metabolites and link them to their biosynthetic machinery.

High-Throughput Mining of Novel Compounds from Known Microbes: A Boost to Natural Product Screening

Advanced techniques can accelerate the pace of natural product discovery from microbes, which has been lagging behind the drug discovery era. Therefore, the present review article discusses the various interdisciplinary and cutting-edge techniques to present a concrete strategy that enables the high-throughput screening of novel natural compounds (NCs) from known microbes. Recent bioinformatics methods revealed that the microbial genome contains a huge untapped reservoir of silent biosynthetic gene clusters (BGC). This article describes several methods to identify the microbial strains with hidden mines of silent BGCs. Moreover, antiSMASH 5.0 is a free, accurate, and highly reliable bioinformatics tool discussed in detail to identify silent BGCs in the microbial genome. Further, the latest microbial culture technique, HiTES (high-throughput elicitor screening), has been detailed for the expression of silent BGCs using 500-1000 different growth conditions at a time. Following the expression of silent BGCs, the latest mass spectrometry methods are highlighted to identify the NCs. The recently emerged LAESI-IMS (laser ablation electrospray ionization-imaging mass spectrometry) technique, which enables the rapid identification of novel NCs directly from microtiter plates, is presented in detail. Finally, various trending 'dereplication' strategies are emphasized to increase the effectiveness of NC screening.

Integrating bacterial molecular genetics with chemical biology for renewed antibacterial drug discovery

The application of dyes to understanding the aetiology of infection inspired antimicrobial chemotherapy and the first wave of antibacterial drugs. The second wave of antibacterial drug discovery was driven by rapid discovery of natural products, now making up 69% of current antibacterial drugs. But now with the most prevalent natural products already discovered, ∼107 new soil-dwelling bacterial species must be screened to discover one new class of natural product. Therefore, instead of a third wave of antibacterial drug discovery, there is now a discovery bottleneck. Unlike natural products which are curated by billions of years of microbial antagonism, the vast synthetic chemical space still requires artificial curation through the therapeutics science of antibacterial drugs - a systematic understanding of how small molecules interact with bacterial physiology, effect desired phenotypes, and benefit the host. Bacterial molecular genetics can elucidate pathogen biology relevant to therapeutics development, but it can also be applied directly to understanding mechanisms and liabilities of new chemical agents with new mechanisms of action. Therefore, the next phase of antibacterial drug discovery could be enabled by integrating chemical expertise with systematic dissection of bacterial infection biology. Facing the ambitious endeavour to find new molecules from nature or new-to-nature which cure bacterial infections, the capabilities furnished by modern chemical biology and molecular genetics can be applied to prospecting for chemical modulators of new targets which circumvent prevalent resistance mechanisms.

Novel Biocatalysts from Specialized Metabolism

Enzymes are increasingly recognized as valuable (bio)catalysts that complement existing synthetic methods. However, the range of biotransformations used in the laboratory is limited. Here we give an overview on the biosynthesis-inspired discovery of novel biocatalysts that address various synthetic challenges. Prominent examples from this dynamic field highlight remarkable enzymes for protecting-group-free amide formation and modification, control of pericyclic reactions, stereoselective hetero- and polycyclizations, atroposelective aryl couplings, site-selective C-H activations, introduction of ring strain, and N-N bond formation. We also explore unusual functions of cytochrome P450 monooxygenases, radical SAM-dependent enzymes, flavoproteins, and enzymes recruited from primary metabolism, which offer opportunities for synthetic biology, enzyme engineering, directed evolution, and catalyst design.

Machine Learning-Enabled Genome Mining and Bioactivity Prediction of Natural Products

Natural products (NPs) produced by microorganisms and plants are a major source of drugs, herbicides, and fungicides. Thanks to recent advances in DNA sequencing, bioinformatics, and genome mining tools, a vast amount of data on NP biosynthesis has been generated over the years, which has been increasingly exploited to develop machine learning (ML) tools for NP discovery. In this review, we discuss the latest advances in developing and applying ML tools for exploring the potential NPs that can be encoded by genomic language and predicting the types of bioactivities of NPs. We also examine the technical challenges associated with the development and application of ML tools for NP research.

Biomimetic engineering of nonribosomal peptide synthesis

Nonribosomal peptides (NRPs) have gained attention due to their diverse biological activities and potential applications in medicine and agriculture. The natural diversity of NRPs is a result of evolutionary processes that have occurred over millions of years. Recent studies have shed light on the mechanisms by which nonribosomal peptide synthetases (NRPSs) evolve, including gene duplication, recombination, and horizontal transfer. Mimicking natural evolution could be a useful strategy for engineering NRPSs to produce novel compounds with desired properties. Furthermore, the emergence of antibiotic-resistant bacteria has highlighted the urgent need for new drugs, and NRPs represent a promising avenue for drug discovery. This review discusses the engineering potential of NRPSs in light of their evolutionary history.

Flux balance analysis-based metabolic modeling of microbial secondary metabolism: Current status and outlook

In microorganisms, different from primary metabolism for cellular growth, secondary metabolism is for ecological interactions and stress responses and an important source of natural products widely used in various areas such as pharmaceutics and food additives. With advancements of sequencing technologies and bioinformatics tools, a large number of biosynthetic gene clusters of secondary metabolites have been discovered from microbial genomes. However, due to challenges from the difficulty of genome-scale pathway reconstruction and the limitation of conventional flux balance analysis (FBA) on secondary metabolism, the quantitative modeling of secondary metabolism is poorly established, in contrast to that of primary metabolism. This review first discusses current efforts on the reconstruction of secondary metabolic pathways in genome-scale metabolic models (GSMMs), as well as related FBA-based modeling techniques. Additionally, potential extensions of FBA are suggested to improve the prediction accuracy of secondary metabolite production. As this review posits, biosynthetic pathway reconstruction for various secondary metabolites will become automated and a modeling framework capturing secondary metabolism onset will enhance the predictive power. Expectedly, an improved FBA-based modeling workflow will facilitate quantitative study of secondary metabolism and in silico design of engineering strategies for natural product production.

The Cytotoxic Properties of Extreme Fungi's Bioactive Components-An Updated Metabolic and Omics Overview

Fungi are the most diverse living organisms on planet Earth, where their ubiquitous presence in various ecosystems offers vast potential for the research and discovery of new, naturally occurring medicinal products. Concerning human health, cancer remains one of the leading causes of mortality. While extensive research is being conducted on treatments and their efficacy in various stages of cancer, finding cytotoxic drugs that target tumor cells with no/less toxicity toward normal tissue is a significant challenge. In addition, traditional cancer treatments continue to suffer from chemical resistance. Fortunately, the cytotoxic properties of several natural products derived from various microorganisms, including fungi, are now well-established. The current review aims to extract and consolidate the findings of various scientific studies that identified fungi-derived bioactive metabolites with antitumor (anticancer) properties. The antitumor secondary metabolites identified from extremophilic and extremotolerant fungi are grouped according to their biological activity and type. It became evident that the significance of these compounds, with their medicinal properties and their potential application in cancer treatment, is tremendous. Furthermore, the utilization of omics tools, analysis, and genome mining technology to identify the novel metabolites for targeted treatments is discussed. Through this review, we tried to accentuate the invaluable importance of fungi grown in extreme environments and the necessity of innovative research in discovering naturally occurring bioactive compounds for the development of novel cancer treatments.

Synthase-selected sorting approach identifies a beta-lactone synthase in a nudibranch symbiotic bacterium

BACKGROUND

Nudibranchs comprise a group of > 6000 marine soft-bodied mollusk species known to use secondary metabolites (natural products) for chemical defense. The full diversity of these metabolites and whether symbiotic microbes are responsible for their synthesis remains unexplored. Another issue in searching for undiscovered natural products is that computational analysis of genomes of uncultured microbes can result in detection of novel biosynthetic gene clusters; however, their in vivo functionality is not guaranteed which limits further exploration of their pharmaceutical or industrial potential. To overcome these challenges, we used a fluorescent pantetheine probe, which produces a fluorescent CoA-analog employed in biosynthesis of secondary metabolites, to label and capture bacterial symbionts actively producing these compounds in the mantle of the nudibranch Doriopsilla fulva.

RESULTS

We recovered the genome of Candidatus Doriopsillibacter californiensis from the Ca. Tethybacterales order, an uncultured lineage of sponge symbionts not found in nudibranchs previously. It forms part of the core skin microbiome of D. fulva and is nearly absent in its internal organs. We showed that crude extracts of D. fulva contained secondary metabolites that were consistent with the presence of a beta-lactone encoded in Ca. D. californiensis genome. Beta-lactones represent an underexplored group of secondary metabolites with pharmaceutical potential that have not been reported in nudibranchs previously.

CONCLUSIONS

Altogether, this study shows how probe-based, targeted sorting approaches can capture bacterial symbionts producing secondary metabolites in vivo. Video Abstract.

Draft genome sequence of potato crop bacterial isolates and nanoparticles-intervention for the induction of secondary metabolites biosynthesis

Introduction

Insights about the effects of gold nanoparticles (AuNPs) on the biosynthetic manipulation of unknown microbe secondary metabolites could be a promising technique for prospective research on nano-biotechnology.

Aim

In this research, we aimed to isolate a fresh, non-domesticated unknown bacterium strain from a common scab of potato crop located in Saudi Arabia and study the metabolic profile.

Methodology

This was achieved through genomic DNA (gDNA) sequencing using Oxford Nanopore Technology. The genomic data were subjected to several bioinformatics tools, including canu-1.9 software, Prokka, DFAST, Geneious Prime, and AntiSMASH. We exposed the culture of the bacterial isolate with different concentrations of AuNPs and investigated the effects of AuNPs on secondary metabolites biosynthesis using several analytical techniques. Furthermore, Tandem-mass spectrometric (MS/MS) technique was optimized for the characterization of several significant sub-classes.

Results

The genomic draft sequence assembly, alignment, and annotation have verified the bacterial isolate as Priestia megaterium. This bacterium has secondary metabolites related to different biosynthetic gene clusters. AuNPs intervention showed an increase in the production of compounds with the molecular weights of 254 and 270 Da in a direct-dependent manner with the increase of the AuNPs concentrations.

Conclusion

The increase in the yields of compound 1 and 2 concomitantly with the increase in the concentration of the added AuNPs provide evidences about the effects of nanoparticles on the biosynthesis of the secondary metabolites. It contributes to the discovery of genes involved in different biosynthetic gene clusters (BGCs) and prediction of the structures of the natural products.

Endophytic fungi mediates production of bioactive secondary metabolites via modulation of genes involved in key metabolic pathways and their contribution in different biotechnological sector

Endophytic fungi stimulate the production of an enormous number of bioactive metabolites in medicinal plants and affect the different steps of biosynthetic pathways of these secondary metabolites. Endophytic fungi possess a number of biosynthetic gene clusters that possess genes for various enzymes, transcription factors, etc., in their genome responsible for the production of secondary metabolites. Additionally, endophytic fungi also modulate the expression of various genes responsible for the synthesis of key enzymes involved in metabolic pathways of such as HMGR, DXR, etc. involved in the production of a large number of phenolic compounds as well as regulate the expression of genes involved in the production of alkaloids and terpenoids in different plants. This review aims to provide a comprehensive overview of gene expression related to endophytes and their impact on metabolic pathways. Additionally, this review will emphasize the studies done to isolate these secondary metabolites from endophytic fungi in large quantities and assess their bioactivity. Due to ease in synthesis of secondary metabolites and their huge application in the medical industry, these bioactive metabolites are now being extracted from strains of these endophytic fungi commercially. Apart from their application in the pharmaceutical industry, most of these metabolites extracted from endophytic fungi also possess plant growth-promoting ability, bioremediation potential, novel bio control agents, sources of anti-oxidants, etc. The review will comprehensively shed a light on the biotechnological application of these fungal metabolites at the industrial level.

Macrocyclization and Backbone Rearrangement During RiPP Biosynthesis by a SAM-Dependent Domain-of-Unknown-Function 692

The domain of unknown function 692 (DUF692) is an emerging family of post-translational modification enzymes involved in the biosynthesis of ribosomally synthesized and post-translationally modified peptide (RiPP) natural products. Members of this family are multinuclear iron-containing enzymes, and only two members have been functionally characterized to date: MbnB and TglH. Here, we used bioinformatics to select another member of the DUF692 family, ChrH, that is encoded in the genomes of the Chryseobacterium genus along with a partner protein ChrI. We structurally characterized the ChrH reaction product and show that the enzyme complex catalyzes an unprecedented chemical transformation that results in the formation of a macrocycle, an imidazolidinedione heterocycle, two thioaminals, and a thiomethyl group. Based on isotopic labeling studies, we propose a mechanism for the four-electron oxidation and methylation of the substrate peptide. This work identifies the first SAM-dependent reaction catalyzed by a DUF692 enzyme complex, further expanding the repertoire of remarkable reactions catalyzed by these enzymes. Based on the three currently characterized DUF692 family members, we suggest the family be called multinuclear non-heme iron dependent oxidative enzymes (MNIOs).

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.

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.

A remarkable transformation catalyzed by a domain-of-unknown-function 692 during the biosynthesis of a new RiPP natural product

The domain of unknown function 692 (DUF692) is an emerging family of posttranslational modification enzymes involved in the biosynthesis of ribosomally-synthesized and posttranslationally modified peptide (RiPP) natural products. Members of this family are multinuclear iron-containing enzymes and only two members have been functionally characterized to date: MbnB and TglH. Here, we used bioinformatics to select another member of the DUF692 family, ChrH, that is ubiquitously encoded in the genomes of the Chryseobacterium genus along with a partner protein ChrI. We structurally characterized the ChrH reaction product and show that the enzyme catalyzes an unprecedented chemical transformation that results in the formation of a macrocycle, an imidazolidinedione heterocycle, two thioaminals, and a thiomethylation. Based on isotopic labeling studies, we propose a mechanism for the four-electron oxidation and methylation of the substrate peptide. This work identifies the first SAM-dependent DUF692 enzyme, further expanding the repertoire of remarkable reactions catalyzed by these enzymes.

Biomanufacturing by In Vitro Biotransformation (ivBT) Using Purified Cascade Multi-enzymes

In vitro biotransformation (ivBT) refers to the use of an artificial biological reaction system that employs purified enzymes for the one-pot conversion of low-cost materials into biocommodities such as ethanol, organic acids, and amino acids. Unshackled from cell growth and metabolism, ivBT exhibits distinct advantages compared with metabolic engineering, including but not limited to high engineering flexibility, ease of operation, fast reaction rate, high product yields, and good scalability. These characteristics position ivBT as a promising next-generation biomanufacturing platform. Nevertheless, challenges persist in the enhancement of bulk enzyme preparation methods, the acquisition of enzymes with superior catalytic properties, and the development of sophisticated approaches for pathway design and system optimization. In alignment with the workflow of ivBT development, this chapter presents a systematic introduction to pathway design, enzyme mining and engineering, system construction, and system optimization. The chapter also proffers perspectives on ivBT development.

Biosynthetic novelty index reveals the metabolic potential of rare actinobacteria isolated from highly oligotrophic sediments

Calculations predict that testing of 5 000-10 000 molecules and >1 billion US dollars (£0.8 billion, £1=$1.2) are required for one single drug to come to the market. A solution to this problem is to establish more efficient protocols that reduce the high rate of re-isolation and continuous rediscovery of natural products during early stages of the drug development process. The study of 'rare actinobacteria' has emerged as a possible approach for increasing the discovery rate of drug leads from natural sources. Here, we define a simple genomic metric, defined as biosynthetic novelty index (BiNI), that can be used to rapidly rank strains according to the novelty of the subset of encoding biosynthetic clusters. By comparing a subset of high-quality genomes from strains of different taxonomic and ecological backgrounds, we used the BiNI score to support the notion that rare actinobacteria encode more biosynthetic gene cluster (BGC) novelty. In addition, we present the isolation and genomic characterization, focused on specialized metabolites and phenotypic screening, of two isolates belonging to genera Lentzea and Actinokineospora from a highly oligotrophic environment. Our results show that both strains harbour a unique subset of BGCs compared to other members of the genera Lentzea and Actinokineospora. These BGCs are responsible for potent antimicrobial and cytotoxic bioactivity. The experimental data and analysis presented in this study contribute to the knowledge of genome mining analysis in rare actinobacteria and, most importantly, can serve to direct sampling efforts to accelerate early stages of the drug discovery pipeline.

Identification of PKS Gene Clusters from Metagenomic Libraries Using a Next-Generation Sequencing Approach

Microbial secondary metabolites have been an important source of bioactive compounds with diverse applications from medicine to agriculture, noticeably those encoded by polyketide synthase (PKS) clusters due to their astounding chemical diversity. While most discovered compounds originate from culturable microorganisms, yet-to-be cultured microbes represent a reservoir of previously inaccessible compounds. The advent and development of metagenomics have allowed not only the characterization of these microorganisms but also their metabolic potential, making viable the prospection of environmental PKS for natural product discovery.Study of environmental PKSs often relies on the construction of metagenomic libraries and their mining, with clones containing PKS clusters identified via amplification of conserved domains and then screened for an activity of interest. Compounds produced by clones exhibiting the desired bioactivity can be isolated and characterized. However, these approaches can be less sensitive and biased against more divergent clusters, in addition to precluding the use of bioinformatics for cluster characterization prior to expression. While direct shotgun sequencing of metagenomes has identified and profiled a great number of PKSs from different environments and yet-to-be cultured microorganisms, it does not lend itself well to heterologous expression, the cruxes of natural product discovery.Here, we describe a strategy for sequencing entire metagenomic libraries while maintaining correspondence between sequence and clone, allowing the full characterization and annotation of all clusters present in a library using bioinformatic tools and then seamlessly passing clones of interest for activity screening through heterologous expression. Once a library is sequenced, the methods herein can be adapted for the mining of any biosynthetic gene cluster of interest within a metagenomic library.

Comparative genomics with evolutionary lineage in Streptomyces bacteria reveals high biosynthetic potentials

Genome mining in silico approaches allow scientists to proficiently evaluate the genomic potency of secondary bioactive chemical producers and find new bioactive compounds in different bacteria. Streptomyces is one of the most ubiquitous bacterial genera in the environments, and well-known as prolific producers of diverse and valuable natural products (NPs) with significant biological activities. Mining and prioritizing of NP biosynthetic gene clusters (BGCs) would be the most important stage in the identification of novel compounds. Comparative genomics and genetic similarity network analysis of 62 Streptomyces public reference genomes demonstrated that individuals of these species exhibit a huge number of distinct NP BGCs, the most of which are cryptic and unconnected to any reported NPs with high phylogenetic variation among individuals. It was assumed that substantial heterogeneity across the varieties of species of Streptomyces drives outstanding biosynthetic and metabolic potential, making them plausible candidates for the identification of novel molecules.

A scalable platform to discover antimicrobials of ribosomal origin

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a promising source of new antimicrobials in the face of rising antibiotic resistance. Here, we report a scalable platform that combines high-throughput bioinformatics with automated biosynthetic gene cluster refactoring for rapid evaluation of uncharacterized gene clusters. As a proof of concept, 96 RiPP gene clusters that originate from diverse bacterial phyla involving 383 biosynthetic genes are refactored in a high-throughput manner using a biological foundry with a success rate of 86%. Heterologous expression of all successfully refactored gene clusters in Escherichia coli enables the discovery of 30 compounds covering six RiPP classes: lanthipeptides, lasso peptides, graspetides, glycocins, linear azol(in)e-containing peptides, and thioamitides. A subset of the discovered lanthipeptides exhibit antibiotic activity, with one class II lanthipeptide showing low µM activity against Klebsiella pneumoniae, an ESKAPE pathogen. Overall, this work provides a robust platform for rapidly discovering RiPPs.

Streptomyces can be an excellent plant growth manager

Streptomyces, the most abundant and arguably the most important genus of actinomycetes, is an important source of biologically active compounds such as antibiotics, and extracellular hydrolytic enzymes. Since Streptomyces can have a beneficial symbiotic relationship with plants they can contribute to nutrition, health and fitness of the latter. This review article summarizes recent research contributions on the ability of Streptomyces to promote plant growth and improve plant tolerance to biotic and abiotic stress responses, as well as on the consequences, on plant health, of the enrichment of rhizospheric soils in Streptomyces species. This review summarizes the most recent reports of the contribution of Streptomyces to plant growth, health and fitness and suggests future research directions to promote the use of these bacteria for the development of a cleaner agriculture.

A brief guide to machine learning for antibiotic discovery

Rising antibiotic resistance and an alarmingly lean antibiotic pipeline require the adoption of novel approaches to rapidly discover new structural and functional classes of antibiotics. Excitingly, algorithmic approaches to antibiotic discovery are sufficiently advanced to meaningfully influence the antibiotic discovery process. Indeed, once trained on high-quality datasets, contemporary machine-learning and deep-learning models can be used to perform predictions for new antibiotics across vast chemical spaces, orders of magnitude more rapidly than compounds can be screened in the laboratory. This increases the probability of discovering new antibiotics with desirable properties. In this short review, we briefly describe the utility of contemporary machine-learning and deep-learning approaches to guide the discovery of new small-molecule antibiotics and unidentified natural products. We then propose a call to action for more open sharing of high-quality screening datasets to accelerate the rate at which forthcoming antibiotic-prediction models can be trained. Together, we aim to introduce antibiotic discoverers to a sample of recent applications of contemporary algorithmic methods to facilitate the wider adoption of these powerful computational approaches.

Exploring Newer Biosynthetic Gene Clusters in Marine Microbial Prospecting

Marine microbes genetically evolved to survive varying salinity, temperature, pH, and other stress factors by producing different bioactive metabolites. These microbial secondary metabolites (SMs) are novel, have high potential, and could be used as lead molecule. Genome sequencing of microbes revealed that they have the capability to produce numerous novel bioactive metabolites than observed under standard in vitro culture conditions. Microbial genome has specific regions responsible for SM assembly, termed biosynthetic gene clusters (BGCs), possessing all the necessary genes to encode different enzymes required to generate SM. In order to augment the microbial chemo diversity and to activate these gene clusters, various tools and techniques are developed. Metagenomics with functional gene expression studies aids in classifying novel peptides and enzymes and also in understanding the biosynthetic pathways. Genome shuffling is a high-throughput screening approach to improve the development of SMs by incorporating genomic recombination. Transcriptionally silent or lower level BGCs can be triggered by artificially knocking promoter of target BGC. Additionally, bioinformatic tools like antiSMASH, ClustScan, NAPDOS, and ClusterFinder are effective in identifying BGCs of existing class for annotation in genomes. This review summarizes the significance of BGCs and the different approaches for detecting and elucidating BGCs from marine microbes.

Biosynthetic pathways of triterpenoids and strategies to improve their Biosynthetic Efficiency

"Triterpenoids" can be considered natural products derived from the cyclization of squalene, yielding 3-deoxytriterpenes (hydrocarbons) or 3-hydroxytriterpenes. Triterpenoids are metabolites of these two classes of triterpenes, produced by the functionalization of their carbon skeleton. They can be categorized into different groups based on their structural formula/design. Triterpenoids are an important group of compounds that are widely used in the fields of pharmacology, food, and industrial biotechnology. However, inadequate synthetic methods and insufficient knowledge of the biosynthesis of triterpenoids, such as their structure, enzymatic activity, and the methods used to produce pure and active triterpenoids, are key problems that limit the production of these active metabolites. Here, we summarize the derivatives, pharmaceutical properties, and biosynthetic pathways of triterpenoids and review the enzymes involved in their biosynthetic pathway. Furthermore, we concluded the screening methods, identified the genes involved in the pathways, and highlighted the appropriate strategies used to enhance their biosynthetic production to facilitate the commercial process of triterpenoids through the synthetic biology method.

Investigating Fungal Biosynthetic Pathways Using Pichia pastoris as a Heterologous Host

Fungal natural products have extensive biological activities, and thus have been largely commercialized in the pharmaceutical, agricultural, and food industries. Recently, heterologous expression has become an irreplaceable technique to functionalize fungal biosynthetic gene clusters and synthesize fungal natural products in various chassis organisms. This chapter describes the general method of using Pichia pastoris as a chassis host to investigate fungal biosynthetic pathways.

Comprehensive Guide to Extracting and Expressing Fungal Secondary Metabolites with Aspergillus fumigatus as a Case Study

Fungal secondary metabolites (SMs) have captured the interest of natural products researchers in academia and industry for decades. In recent years, the high rediscovery rate of previously characterized metabolites is making it increasingly difficult to uncover novel compounds. Additionally, the vast majority of fungal SMs reside in genetically intractable fungi or are silent under normal laboratory conditions in genetically tractable fungi. The fungal natural products community has broadly overcome these barriers by altering the physical growth conditions of the fungus and heterologous/homologous expression of biosynthetic gene cluster regulators or proteins. The protocols described here summarize vital methodologies needed when researching SM production in fungi. We also summarize the growth conditions, genetic backgrounds, and extraction protocols for every published SM in Aspergillus fumigatus, enabling readers to easily replicate the production of previously characterized SMs. Readers will also be equipped with the tools for developing their own strategy for expressing and extracting SMs from their given fungus or a suitable heterologous model system. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Making glycerol stocks from spore suspensions Alternate Protocol 1: Creating glycerol stocks from non-sporulating filamentous fungi Basic Protocol 2: Activating spore-suspension glycerol stocks Basic Protocol 3: Extracting secondary metabolites from Aspergillus spp grown on solid medium Alternate Protocol 2: Extracting secondary metabolites from Aspergillus spp using ethyl acetate Alternate Protocol 3: High-volume metabolite extraction using ethyl acetate Alternate Protocol 4: Extracting secondary metabolites from Aspergillus spp in liquid medium Support Protocol: Creating an overlay culture Basic Protocol 4: Extracting DNA from filamentous fungi Basic Protocol 5: Creating a DNA construct with double-joint PCR Alternate Protocol 5: Creating a DNA construct with yeast recombineering Basic Protocol 6: Transformation of Aspergillus spp Basic Protocol 7: Co-culturing fungi and bacteria for extraction of secondary metabolites.

Genome mining for drug discovery: progress at the front end

Microbial genome mining for drug discovery and development has been accelerating in recent years, driven by technical advancements in genome sequencing, bioinformatics, metabolomics/metabologenomics, and synthetic biology. Microbial genome mining is a multistep process that starts with the sequencing of microbes that encode multiple secondary metabolites and identifying new and novel secondary metabolite biosynthetic gene clusters (BGCs) to pursue. The initial steps in the process are critical for the overall success, and they encompass the most innovative new technologies to revitalize natural product discovery. As microbial genome mining has matured in recent years, unvalidated conjectures about what microbes to pursue, how to identify legitimate secondary metabolite BGCs, and how to sequence DNA to satisfactory levels of completion have been identified. The solutions to correct the misconceptions around these topics are beginning to be implemented.

Halocins, natural antimicrobials of Archaea: Exotic or special or both?

Haloarchaea are adapted to survive under extreme saline conditions by accumulating osmolytes and salts to counteract the high osmotic pressure in their habitats. As a consequence, their proteins have evolved to remain active, or even most active, at very high ionic strength. Halocins are proteinaceous antimicrobial substances that are ribosomally-synthesized by haloarchaea and they provide the producers an advantage in the competition for nutrients and ecological niches. These antimicrobials are stable at high temperature, elevated salt concentrations, and alkaline pH conditions. These properties have endowed them with great potential in diverse biotechnological applications, which involve extreme processing conditions (such as high salt concentrations, high pressure, or high temperatures). They kill target cells by inhibition of Na⁺/H⁺ antiporter in the membrane or modification/disruption of the cell membrane leading to cell lysis. In general, the taxonomy of haloarchaea and their typical phenotypic and genotypic characteristics are well studied; however, information regarding their halocins, especially aspects related to genetics, biosynthetic pathways, mechanism of action, and structure-function relationship is very limited. A few studies have demonstrated the potential applications of halocins in the preservation of salted food products and brine-cured hides in leather industries, protecting the myocardium from ischemia and reperfusion injury, as well as from life-threatening diseases such as cardiac arrest and cancers. In recent years, genome mining has been an essential tool to decipher the genetic basis of halocin biosynthesis. Nevertheless, this is likely the tip of the iceberg as genome analyses have revealed many putative halocins in databases waiting for further investigation. Identification and characterization of this source of halocins may lead to antimicrobials for future therapeutics and/or food preservation. Hence, the present review analyzes different aspects of halocins such as biosynthesis, mechanism of action against target cells, and potential biotechnological applications.

Characterization of promoters in archaeal genomes based on DNA structural parameters

The transcription machinery of archaea can be roughly classified as a simplified version of eukaryotic organisms. The basal transcription factor machinery binds to the TATA box found around 28 nucleotides upstream of the transcription start site; however, some transcription units lack a clear TATA box and still have TBP/TFB binding over them. This apparent absence of conserved sequences could be a consequence of sequence divergence associated with the upstream region, operon, and gene organization. Furthermore, earlier studies have found that a structural analysis gains more information compared with a simple sequence inspection. In this work, we evaluated and coded 3630 archaeal promoter sequences of three organisms, Haloferax volcanii, Thermococcus kodakarensis, and Sulfolobus solfataricus into DNA duplex stability, enthalpy, curvature, and bendability parameters. We also split our dataset into conserved TATA and degenerated TATA promoters to identify differences among these two classes of promoters. The structural analysis reveals variations in archaeal promoter architecture, that is, a distinctive signal is observed in the TFB, TBP, and TFE binding sites independently of these being TATA-conserved or TATA-degenerated. In addition, the promoter encountering method was validated with upstream regions of 13 other archaea, suggesting that there might be promoter sequences among them. Therefore, we suggest a novel method for locating promoters within the genome of archaea based on DNA energetic/structural features.

Gene Cluster Analysis of Marine Bacteria Seeking for Natural Anticancer Products

Background: In the past decade, metabolites of marine microorganisms have been increasingly used for their various biological activities. An intense effort has been dedicated to assessing the therapeutic efficacy of the marine natural products and metabolites obtained from marine bacteria in cancer therapy. Fast and reliable analytical bacterial genome sequencing provides specialized bioinformatic tools to identify potential gene clusters in bacteria for obtaining secondary metabolites. Objectives: This study aimed to analyze the genome sequences of marine bacteria to recognize bioactive compounds with anti-cancer properties. Methods: Marine bacteria with the genomic sequences registered in the National Center for Biotechnology Information (NCBI) genome database were used in this study. The genome was analyzed for proteins, tRNAs, and rRNAs from GenBank entries by Feature Extract 1.2L Server. The Anti-SMASH webserver was used for the analysis of unique marine bacterial metabolites of the marine bacterial genome, available from the NCBI database. Results: A number of marine bacterial species, including Salinispora arenicola, Salinispora tropica, Crocosphaera watsonii, and Blastopirellula marina encoded metabolites belonging to the polyketide and nonribosomal peptide (NRP) families, showing anti-cancer properties. Among the marine species described, S. tropica and S. arenicola are richer in the genes encoding polyketide and NRP with potential antitumor activities. Conclusions: Marine bacteria are an excellent and exceptional source of anti-cancer compounds. In silico genome analysis of marine bacteria provided an opportunity to evaluate gene clusters for known natural products. Like this chemical engineering approaches for pharmaceutical application are useful in clinical evaluation of cancer treatment.

Discovery and mining of enzymes from the human gut microbiome

Advances in technological and bioinformatics approaches have led to the generation of a plethora of human gut metagenomic datasets. Metabolomics has also provided substantial data regarding the small metabolites produced and modified by the microbiota. Comparatively, the microbial enzymes mediating the transformation of metabolites have not been intensively investigated. Here, we discuss the recent efforts and technologies used for discovering and mining enzymes from the human gut microbiota. The wealth of knowledge on metabolites, reactions, genome sequences, and structures of proteins, may drive the development of strategies for enzyme mining. Ongoing efforts to annotate gut microbiota enzymes will explain catalytic mechanisms that may guide the clinical applications of the gut microbiome for diagnostic and therapeutic purposes.

Mining and unearthing hidden biosynthetic potential

Genetically encoded small molecules (secondary metabolites) play eminent roles in ecological interactions, as pathogenicity factors and as drug leads. Yet, these chemical mediators often evade detection, and the discovery of novel entities is hampered by low production and high rediscovery rates. These limitations may be addressed by genome mining for biosynthetic gene clusters, thereby unveiling cryptic metabolic potential. The development of sophisticated data mining methods and genetic and analytical tools has enabled the discovery of an impressive array of previously overlooked natural products. This review shows the newest developments in the field, highlighting compound discovery from unconventional sources and microbiomes.

Natural products are an important source of bioactive compounds and have versatile applications in different fields, but their discovery is challenging. Here, the authors review the recent developments in genome mining for discovery of natural products, focusing on compounds from unconventional microorganisms and microbiomes.

Bioproduction process of natural products and biopharmaceuticals: Biotechnological aspects

Decades of research have been put in place for developing sustainable routes of bioproduction of high commercial value natural products (NPs) on the global market. In the last few years alone, we have witnessed significant advances in the biotechnological production of NPs. The development of new methodologies has resulted in a better understanding of the metabolic flux within the organisms, which have driven manipulations to improve production of the target product. This was further realised due to the recent advances in the omics technologies such as genomics, transcriptomics, proteomics, metabolomics and secretomics, as well as systems and synthetic biology. Additionally, the combined application of novel engineering strategies has made possible avenues for enhancing the yield of these products in an efficient and economical way. Invention of high-throughput technologies such as next generation sequencing (NGS) and toolkits for genome editing Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated 9 (CRISPR/Cas9) have been the game changers and provided unprecedented opportunities to generate rationally designed synthetic circuits which can produce complex molecules. This review covers recent advances in the engineering of various hosts for the production of bioactive NPs and biopharmaceuticals. It also highlights general approaches and strategies to improve their biosynthesis with higher yields in a perspective of plants and microbes (bacteria, yeast and filamentous fungi). Although there are numerous reviews covering this topic on a selected species at a time, our approach herein is to give a comprehensive understanding about state-of-art technologies in different platforms of organisms.

The Design-Build-Test-Learn cycle for metabolic engineering of Streptomycetes

Streptomycetes are producers of a wide range of specialized metabolites of great medicinal and industrial importance, such as antibiotics, antifungals, or pesticides. Having been the drivers of the golden age of antibiotics in the 1950s and 1960s, technological advancements over the last two decades have revealed that very little of their biosynthetic potential has been exploited so far. Given the great need for new antibiotics due to the emerging antimicrobial resistance crisis, as well as the urgent need for sustainable biobased production of complex molecules, there is a great renewed interest in exploring and engineering the biosynthetic potential of streptomycetes. Here, we describe the Design-Build-Test-Learn (DBTL) cycle for metabolic engineering experiments in streptomycetes and how it can be used for the discovery and production of novel specialized metabolites.

Ethnobotany and the Role of Plant Natural Products in Antibiotic Drug Discovery

The crisis of antibiotic resistance necessitates creative and innovative approaches, from chemical identification and analysis to the assessment of bioactivity. Plant natural products (NPs) represent a promising source of antibacterial lead compounds that could help fill the drug discovery pipeline in response to the growing antibiotic resistance crisis. The major strength of plant NPs lies in their rich and unique chemodiversity, their worldwide distribution and ease of access, their various antibacterial modes of action, and the proven clinical effectiveness of plant extracts from which they are isolated. While many studies have tried to summarize NPs with antibacterial activities, a comprehensive review with rigorous selection criteria has never been performed. In this work, the literature from 2012 to 2019 was systematically reviewed to highlight plant-derived compounds with antibacterial activity by focusing on their growth inhibitory activity. A total of 459 compounds are included in this Review, of which 50.8% are phenolic derivatives, 26.6% are terpenoids, 5.7% are alkaloids, and 17% are classified as other metabolites. A selection of 183 compounds is further discussed regarding their antibacterial activity, biosynthesis, structure-activity relationship, mechanism of action, and potential as antibiotics. Emerging trends in the field of antibacterial drug discovery from plants are also discussed. This Review brings to the forefront key findings on the antibacterial potential of plant NPs for consideration in future antibiotic discovery and development efforts.

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.

Strategies for Discovering New Antibiotics from Bacteria in the Post-Genomic Era

New antibiotics are urgently required in clinical treatment and agriculture with the development of antimicrobial resistance. However, products discovered by repeating previous strategies are either not antibiotics or already known antibiotics. There is a growing demand for efficient strategies to discover new antibiotics. With the continuous improvement of gene sequencing technology and genomic data, some mining strategies have emerged. These strategies are expected to alleviate the current dilemma of antibiotics. In this review, we discuss the recent advances in discovery of bacterial antibiotics from the following aspects: activation of silent gene clusters, genome mining and metagenome mining. In the future, we envision the discovery of natural antibiotic will be accelerated by the combination of these strategies.