The secondary metabolite bioinformatics portal: Computational tools to facilitate synthetic biology of secondary metabolite production

A review on the diversity of antimicrobial peptides and genome mining strategies for their prediction

Antibiotic resistance has become one of the most serious threats to human health in recent years. In response to the increasing microbial resistance to the antibiotics currently available, it is imperative to develop new antibiotics or explore new approaches to combat antibiotic resistance. Antimicrobial peptides (AMPs) have shown considerable promise in this regard, as the microbes develop low or no resistance against them. The discovery and development of AMPs still confront numerous obstacles such as finding a target, developing assays, and identifying hits and leads, which are time-consuming processes, making it difficult to reach the market. However, with the advent of genome mining, new antibiotics could be discovered efficiently using tools such as BAGEL, antiSMASH, RODEO, etc., providing hope for better treatment of diseases in the future. Computational methods used in genome mining automatically detect and annotate biosynthetic gene clusters in genomic data, making it a useful tool in natural product discovery. This review aims to shed light on the history, diversity, and mechanisms of action of AMPs and the data on new AMPs identified by traditional as well as genome mining strategies. It further substantiates the various phases of clinical trials for some AMPs, as well as an overview of genome mining databases and tools built expressly for AMP discovery. In light of the recent advancements, it is evident that targeted genome mining stands as a beacon of hope, offering immense potential to expedite the discovery of novel antimicrobials.

Accelerating enzyme discovery and engineering with high-throughput screening

Covering: up to August 2024Enzymes play an essential role in synthesizing value-added chemicals with high specificity and selectivity. Since enzymes utilize substrates derived from renewable resources, biocatalysis offers a pathway to an efficient bioeconomy with reduced environmental footprint. However, enzymes have evolved over millions of years to meet the needs of their host organisms, which often do not align with industrial requirements. As a result, enzymes frequently need to be tailored for specific industrial applications. Combining enzyme engineering with high-throughput screening has emerged as a key approach for developing novel biocatalysts, but several challenges are yet to be addressed. In this review, we explore emergent strategies and methods for isolating, creating, and characterizing enzymes optimized for bioproduction. We discuss fundamental approaches to discovering and generating enzyme variants and identifying those best suited for specific applications. Additionally, we cover techniques for creating libraries using automated systems and highlight innovative high-throughput screening methods that have been successfully employed to develop novel biocatalysts for natural product synthesis.

How Do Plant Growth-Promoting Bacteria Use Plant Hormones to Regulate Stress Reactions?

Phytohormones play a crucial role in regulating growth, productivity, and development while also aiding in the response to diverse environmental changes, encompassing both biotic and abiotic factors. Phytohormone levels in soil and plant tissues are influenced by specific soil bacteria, leading to direct effects on plant growth, development, and stress tolerance. Specific plant growth-promoting bacteria can either synthesize or degrade specific plant phytohormones. Moreover, a wide range of volatile organic compounds synthesized by plant growth-promoting bacteria have been found to influence the expression of phytohormones. Bacteria-plant interactions become more significant under conditions of abiotic stress such as saline soils, drought, and heavy metal pollution. Phytohormones function in a synergistic or antagonistic manner rather than in isolation. The study of plant growth-promoting bacteria involves a range of approaches, such as identifying singular substances or hormones, comparing mutant and non-mutant bacterial strains, screening for individual gene presence, and utilizing omics approaches for analysis. Each approach uncovers the concealed aspects concerning the effects of plant growth-promoting bacteria on plants. Publications that prioritize the comprehensive examination of the private aspects of PGPB and cultivated plant interactions are of utmost significance and crucial for advancing the practical application of microbial biofertilizers. This review explores the potential of PGPB-plant interactions in promoting sustainable agriculture. We summarize the interactions, focusing on the mechanisms through which plant growth-promoting bacteria have a beneficial effect on plant growth and development via phytohormones, with particular emphasis on detecting the synthesis of phytohormones by plant growth-promoting bacteria.

Structural, biochemical and bioinformatic analyses of nonribosomal peptide synthetase adenylation domains

Covering: 1997 to July 2023The adenylation reaction has been a subject of scientific intrigue since it was first recognized as essential to many biological processes, including the homeostasis and pathogenicity of some bacteria and the activation of amino acids for protein synthesis in mammals. Several foundational studies on adenylation (A) domains have facilitated an improved understanding of their molecular structures and biochemical properties, in particular work on nonribosomal peptide synthetases (NRPSs). In NRPS pathways, A domains activate their respective acyl substrates for incorporation into a growing peptidyl chain, and many nonribosomal peptides are bioactive. From a natural product drug discovery perspective, improving existing bioinformatics platforms to predict unique NRPS products more accurately from genomic data is desirable. Here, we summarize characterization efforts of A domains primarily from NRPS pathways from July 1997 up to July 2023, covering protein structure elucidation, in vitro assay development, and in silico tools for improved predictions.

Unraveling the metabolic potential of biocontrol fungi through omics data: a key to enhancing large-scaleapplication strategies

Biological control of pests and pathogens has attracted much attention due to its green, safe and effective characteristics. However, it faces the dilemma of insignificant effects in large-scale applications. Therefore, an in-depth exploration of the metabolic potential of biocontrol fungi based on big omics data is crucial for a comprehensive and systematic understanding of the specific modes of action operated by various biocontrol fungi. This article analyzes the preferences for extracellular carbon and nitrogen source degradation, secondary metabolites (nonribosomal peptides, polyketide synthases) and their product characteristics and the conversion relationship between extracellular primary metabolism and intracellular secondary metabolism for eight different filamentous fungi with characteristics appropriate for the biological control of bacterial pathogens and phytopathogenic nematodes. Further clarification is provided that Paecilomyces lilacinus, encoding a large number of hydrolase enzymes capable of degrading pathogen protection barrier, can be directly applied in the field as a predatory biocontrol fungus, whereas Trichoderma, as an antibiosis-active biocontrol control fungus, can form dominant strains on preferred substrates and produce a large number of secondary metabolites to achieve antibacterial effects. By clarifying the levels of biological control achievable by different biocontrol fungi, we provide a theoretical foundation for their application to cropping habitats.

Synteruptor: mining genomic islands for non-classical specialized metabolite gene clusters

Microbial specialized metabolite biosynthetic gene clusters (SMBGCs) are a formidable source of natural products of pharmaceutical interest. With the multiplication of genomic data available, very efficient bioinformatic tools for automatic SMBGC detection have been developed. Nevertheless, most of these tools identify SMBGCs based on sequence similarity with enzymes typically involved in specialised metabolism and thus may miss SMBGCs coding for undercharacterised enzymes. Here we present Synteruptor (https://bioi2.i2bc.paris-saclay.fr/synteruptor), a program that identifies genomic islands, known to be enriched in SMBGCs, in the genomes of closely related species. With this tool, we identified a SMBGC in the genome of Streptomyces ambofaciens ATCC23877, undetected by antiSMASH versions prior to antiSMASH 5, and experimentally demonstrated that it directs the biosynthesis of two metabolites, one of which was identified as sphydrofuran. Synteruptor is also a valuable resource for the delineation of individual SMBGCs within antiSMASH regions that may encompass multiple clusters, and for refining the boundaries of these SMBGCs.

Monaspin B, a Novel Cyclohexyl-furan from Cocultivation of Monascus purpureus and Aspergillus oryzae, Exhibits Potent Antileukemic Activity

Natural products are a rich resource for the discovery of innovative drugs. Microbial cocultivation enables discovery of novel natural products through tandem enzymatic catalysis between different fungi. In this study, Monascus purpureus, as a food fermentation strain capable of producing abundant natural products, was chosen as an example of a cocultivation pair strain. Cocultivation screening revealed that M. purpureus and Aspergillus oryzae led to the production of two novel cyclohexyl-furans, Monaspins A and B. Optimization of the cocultivation mode and media enhanced the production of Monaspins A and B to 1.2 and 0.8 mg/L, respectively. Monaspins A and B were structurally elucidated by HR-ESI-MS and NMR. Furthermore, Monaspin B displayed potent antiproliferative activity against the leukemic HL-60 cell line by inducing apoptosis, with a half-maximal inhibitory concentration (IC50) of 160 nM. Moreover, in a mouse leukemia model, Monaspin B exhibited a promising in vivo antileukemic effect by reducing white blood cell, lymphocyte, and neutrophil counts. Collectively, these results indicate that Monaspin B is a promising candidate agent for leukemia therapy.

Global characterization of biosynthetic gene clusters in non-model eukaryotes using domain architectures

The majority of pharmaceuticals are derived from natural products, bioactive compounds naturally synthesized by organisms to provide evolutionary advantages. Although the rich evolutionary history of eukaryotic algal species implicates a high potential for natural product-based drug discovery, it remains largely untouched. This study investigates 2762 putative biosynthetic gene clusters (BGCs) from 212 eukaryotic algal genomes. To analyze a vast set of structurally diverse BGCs, we employed comparative analysis based on the vectorization of biosynthetic domains, referred to as biosynthetic domain architecture (BDA). By characterizing core biosynthetic machineries through BDA, we identified key BDAs of modular BGCs in diverse eukaryotes and introduced 16 candidate modular BGCs with similar BDAs to previously validated BGCs. This study provides a global characterization of eukaryotic algal BGCs, offering an alternative to laborious manual curation for BGC prioritization.

The antiSMASH database version 4: additional genomes and BGCs, new sequence-based searches and more

Many microorganisms produce natural products that are frequently used in the development of medicines and crop protection agents. Genome mining has evolved into a prominent method to access this potential. antiSMASH is the most popular tool for this task. Here we present version 4 of the antiSMASH database, providing biosynthetic gene clusters detected by antiSMASH 7.1 in publicly available, dereplicated, high-quality microbial genomes via an interactive graphical user interface. In version 4, the database contains 231 534 high quality BGC regions from 592 archaeal, 35 726 bacterial and 236 fungal genomes and is available at https://antismash-db.secondarymetabolites.org/.

Bioprospecting of unexplored halophilic actinobacteria against human infectious pathogens

Human pathogenic diseases received much attention recently due to their uncontrolled spread of antimicrobial resistance (AMR) which causes several threads every year. Effective alternate antimicrobials are urgently required to combat those disease causing infectious microbes. Halophilic actinobacteria revealed huge potentials and unexplored cultivable/non-cultivable actinobacterial species producing enormous antimicrobials have been proved in several genomics approaches. Potential gene clusters, PKS and NRPKS from Nocardia, Salinospora, Rhodococcus, and Streptomyces have wide range coding genes of secondary metabolites. Biosynthetic pathways identification via various approaches like genome mining, In silico, OSMAC (one strain many compound) analysis provides better identification of knowing the active metabolites using several databases like AMP, APD and CRAMPR, etc. Genome constellations of actinobacteria particularly the prediction of BGCs (Biosynthetic Gene Clusters) to mine the bioactive molecules such as pigments, biosurfactants and few enzymes have been reported for antimicrobial activity. Saltpan, saltlake, lagoon and haloalkali environment exploring potential actinobacterial strains Micromonospora, Kocuria, Pseudonocardia, and Nocardiopsis revealed several acids and ester derivatives with antimicrobial potential. Marine sediments and marine macro organisms have been found as significant population holders of potential actinobacterial strains. Deadly infectious diseases (IDs) including tuberculosis, ventilator-associated pneumonia and Candidiasis, have been targeted by halo-actinobacterial metabolites with promising results. Methicillin resistant Staphylococus aureus and virus like Encephalitic alphaviruses were potentially targeted by halophilic actinobacterial metabolites by the compound Homoseongomycin from sponge associated antinobacterium. In this review, we discuss the potential antimicrobial properties of various biomolecules extracted from the unexplored halophilic actinobacterial strains specifically against human infectious pathogens along with prospective genomic constellations.

Recent advances in triterpenoid pathway elucidation and engineering

Triterpenoids are among the most assorted class of specialized metabolites found in all the taxa of living organisms. Triterpenoids are the leading active ingredients sourced from plant species and are utilized in pharmaceutical and cosmetic industries. The triterpenoid precursor 2,3-oxidosqualene, which is biosynthesized via the mevalonate (MVA) pathway is structurally diversified by the oxidosqualene cyclases (OSCs) and other scaffold-decorating enzymes such as cytochrome P450 monooxygenases (P450s), UDP-glycosyltransferases (UGTs) and acyltransferases (ATs). A majority of the bioactive triterpenoids are harvested from the native hosts using the traditional methods of extraction and occasionally semi-synthesized. These methods of supply are time-consuming and do not often align with sustainability goals. Recent advancements in metabolic engineering and synthetic biology have shown prospects for the green routes of triterpenoid pathway reconstruction in heterologous hosts such as Escherichia coli, Saccharomyces cerevisiae and Nicotiana benthamiana, which appear to be quite promising and might lead to the development of alternative source of triterpenoids. The present review describes the biotechnological strategies used to elucidate complex biosynthetic pathways and to understand their regulation and also discusses how the advances in triterpenoid pathway engineering might aid in the scale-up of triterpenoid production in engineered hosts.

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.

Advances in the adenylation domain: discovery of diverse non-ribosomal peptides

Non-ribosomal peptide synthetases are mega-enzyme assembly lines that synthesize many clinically useful compounds. As a gatekeeper, they have an adenylation (A)-domain that controls substrate specificity and plays an important role in product structural diversity. This review summarizes the natural distribution, catalytic mechanism, substrate prediction methods, and in vitro biochemical analysis of the A-domain. Taking genome mining of polyamino acid synthetases as an example, we introduce research on mining non-ribosomal peptides based on A-domains. We discuss how non-ribosomal peptide synthetases can be engineered based on the A-domain to obtain novel non-ribosomal peptides. This work provides guidance for screening non-ribosomal peptide-producing strains, offers a method to discover and identify A-domain functions, and will accelerate the engineering and genome mining of non-ribosomal peptide synthetases. KEY POINTS: • Introducing adenylation domain structure, substrate prediction, and biochemical analysis methods • Advances in mining homo polyamino acids based on adenylation domain analysis • Creating new non-ribosomal peptides by engineering adenylation domains.

antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures and visualisation

Microorganisms produce small bioactive compounds as part of their secondary or specialised metabolism. Often, such metabolites have antimicrobial, anticancer, antifungal, antiviral or other bio-activities and thus play an important role for applications in medicine and agriculture. In the past decade, genome mining has become a widely-used method to explore, access, and analyse the available biodiversity of these compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' (https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free to use web server and as a standalone tool under an OSI-approved open source licence. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in archaea, bacteria, and fungi. Here, we present the updated version 7 of antiSMASH. antiSMASH 7 increases the number of supported cluster types from 71 to 81, as well as containing improvements in the areas of chemical structure prediction, enzymatic assembly-line visualisation and gene cluster regulation.

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.

Peptidomics

Peptides are biopolymers, typically consisting of 2-50 amino acids. They are biologically produced by the cellular ribosomal machinery or by non-ribosomal enzymes and, sometimes, other dedicated ligases. Peptides are arranged as linear chains or cycles, and include post-translational modifications, unusual amino acids and stabilizing motifs. Their structure and molecular size render them a unique chemical space, between small molecules and larger proteins. Peptides have important physiological functions as intrinsic signalling molecules, such as neuropeptides and peptide hormones, for cellular or interspecies communication, as toxins to catch prey or as defence molecules to fend off enemies and microorganisms. Clinically, they are gaining popularity as biomarkers or innovative therapeutics; to date there are more than 60 peptide drugs approved and more than 150 in clinical development. The emerging field of peptidomics comprises the comprehensive qualitative and quantitative analysis of the suite of peptides in a biological sample (endogenously produced, or exogenously administered as drugs). Peptidomics employs techniques of genomics, modern proteomics, state-of-the-art analytical chemistry and innovative computational biology, with a specialized set of tools. The complex biological matrices and often low abundance of analytes typically examined in peptidomics experiments require optimized sample preparation and isolation, including in silico analysis. This Primer covers the combination of techniques and workflows needed for peptide discovery and characterization and provides an overview of various biological and clinical applications of peptidomics.

Natural and engineered cyclodipeptides: Biosynthesis, chemical diversity, and engineering strategies for diversification and high-yield bioproduction

Cyclodipeptides are diverse chemical scaffolds that show a broad range of bioactivities relevant for medicine, agriculture, chemical catalysis, and material sciences. Cyclodipeptides can be synthesized enzymatically through two unrelated enzyme families, non-ribosomal peptide synthetases (NRPS) and cyclodipeptide synthases (CDPSs). The chemical diversity of cyclodipeptides is derived from the two amino acid side chains and the modification of those side-chains by cyclodipeptide tailoring enzymes. While a large spectrum of chemical diversity is already known today, additional chemical space - and as such potential new bioactivities - could be accessed by exploring yet undiscovered NRPS and CDPS gene clusters as well as via engineering. Further, to exploit cyclodipeptides for applications, the low yield of natural biosynthesis needs to be overcome. In this review we summarize current knowledge on NRPS and CDPS-based cyclodipeptide biosynthesis, engineering approaches to further diversity the natural chemical diversity as well as strategies for high-yield production of cyclodipeptides, including a discussion of how advancements in synthetic biology and metabolic engineering can accelerate the translational potential of cyclodipeptides.

Petroleum Hydrocarbon Catabolic Pathways as Targets for Metabolic Engineering Strategies for Enhanced Bioremediation of Crude-Oil-Contaminated Environments

Anthropogenic activities and industrial effluents are the major sources of petroleum hydrocarbon contamination in different environments. Microbe-based remediation techniques are known to be effective, inexpensive, and environmentally safe. In this review, the metabolic-target-specific pathway engineering processes used for improving the bioremediation of hydrocarbon-contaminated environments have been described. The microbiomes are characterised using environmental genomics approaches that can provide a means to determine the unique structural, functional, and metabolic pathways used by the microbial community for the degradation of contaminants. The bacterial metabolism of aromatic hydrocarbons has been explained via peripheral pathways by the catabolic actions of enzymes, such as dehydrogenases, hydrolases, oxygenases, and isomerases. We proposed that by using microbiome engineering techniques, specific pathways in an environment can be detected and manipulated as targets. Using the combination of metabolic engineering with synthetic biology, systemic biology, and evolutionary engineering approaches, highly efficient microbial strains may be utilised to facilitate the target-dependent bioprocessing and degradation of petroleum hydrocarbons. Moreover, the use of CRISPR-cas and genetic engineering methods for editing metabolic genes and modifying degradation pathways leads to the selection of recombinants that have improved degradation abilities. The idea of growing metabolically engineered microbial communities, which play a crucial role in breaking down a range of pollutants, has also been explained. However, the limitations of the in-situ implementation of genetically modified organisms pose a challenge that needs to be addressed in future research.

Strategizing the human microbiome for small molecules: Approaches and perspectives

Studies of the human microbiome are providing a deeper understanding of its significance to human health, and increasing evidence links the microbiota with several diseases. Nevertheless, the exact mechanisms involved in human-microbe interactions are mostly undefined. The genomic potential of the human microbiome to biosynthesize distinct molecules outmatches its known chemical space, and small-molecule discovery in this context remains in its infancy. The profiling of microbiome-derived small molecules and their contextualization through cause-effect mechanistic studies may provide a better understanding of host-microbe interactions, guide new therapeutic interventions, and modulate microbiome-based therapies. This review describes the advances, approaches, and allied challenges in mining new microbial scaffolds from the human microbiome using genomic, microbe cultivation, and chemical analytic platforms. In the future, the complete biological characterization of a single microbe-derived molecule that has a specific therapeutic application could resolve the current limitations of microbiota-modulating therapies.

Computational Approaches to Enzyme Inhibition by Marine Natural Products in the Search for New Drugs

The exploration of biologically relevant chemical space for the discovery of small bioactive molecules present in marine organisms has led not only to important advances in certain therapeutic areas, but also to a better understanding of many life processes. The still largely untapped reservoir of countless metabolites that play biological roles in marine invertebrates and microorganisms opens new avenues and poses new challenges for research. Computational technologies provide the means to (i) organize chemical and biological information in easily searchable and hyperlinked databases and knowledgebases; (ii) carry out cheminformatic analyses on natural products; (iii) mine microbial genomes for known and cryptic biosynthetic pathways; (iv) explore global networks that connect active compounds to their targets (often including enzymes); (v) solve structures of ligands, targets, and their respective complexes using X-ray crystallography and NMR techniques, thus enabling virtual screening and structure-based drug design; and (vi) build molecular models to simulate ligand binding and understand mechanisms of action in atomic detail. Marine natural products are viewed today not only as potential drugs, but also as an invaluable source of chemical inspiration for the development of novel chemotypes to be used in chemical biology and medicinal chemistry research.

Bioactive compounds as an alternative for the sugarcane industry: Towards an integrative approach

Here, a comprehensive review of sugarcane industrialization and its relationship with bioactive compounds (BCs) detected in various products and by-products generated during its processing is presented. Furthermore, it is discussed how these compounds have revealed important antioxidant, antineoplastic, antidiabetic, and antimicrobial activities. From this bibliographic research highlights the significance of two types of BCs of natural origin (phenolic compounds (PCs) and terpenoids) and a group of compounds synthesized during industrial transformation processes (Maillard reaction products (MRPs)). It was found that most of the studies about the BCs from sugarcane have been conducted by identifying, isolating, and analyzing ones or a few compounds at a specific period, this being a conventional approach. However, given the complexity of the synthesis processes of all these BCs and the biological activities they can manifest in a specific biological context, novel approaches are needed to address these analyses holistically. To overcome this challenge, integrating massive and multiscale methods, such as omics sciences, seems necessary to enrich these studies. This work is intended to contribute to the state of the art that could support future research about the exploration, characterization, or evaluation of different bioactive molecules from sugarcane and its derivatives.

In Silico Genomic Characterization of Bacillus velezensis Strain AAK_S6 for Secondary Metabolite and Biocontrol Potential

This study reports the draft genome sequence of Bacillus velezensis strain AAK_S6 as a valuable biocontrol agent with high genetic potential to harbor broad-spectrum secondary metabolite producing capacity. A genome data of 4,430,946 bp were generated with a GC content of 46.4% that comprised a total of 4861 genes including a total of 4757 coding sequences (CDS), 104 rRNAs, 85 tRNAs and 80 pseudo-genes. Based on the overall genome-based relatedness indices (OGRI), the strain AAK_S6 has been reassigned to its correct taxonomic position. The strain shared > 99% OrthoANI, > 98% ANIb, > 99% ANIm, > 0.9900 TETRA, > 93% dDDH and 0.08% GC content difference with model strains B. velezensis FZB42^T and B. velezensis NRRL B-41580^T thus delineating them as closely related species. The genome was mined for strain-specific secondary metabolites that revealed 20 gene clusters for the biosynthesis of several cyclic lipopeptides, saccharides, polyketides along with bacilysin. Thus, the comparative genome analysis of strain AAK_S6 with members of the genus Bacillus by phylogenomic approach revealed that the genomes were almost similar genetically and contained the core genome for B. velezensis. Genomic data strongly supported that the strain AAK_S6 represented an excellent potential candidate for the production of secondary metabolites that could serve as a basis for developing new biocontrol agents, plant growth promoters, and microbial fertilizers.

Recent advances in research for potential utilization of unexplored lichen metabolites

Several research studies have shown that lichens are productive organisms for the synthesis of a broad range of secondary metabolites. Lichens are a self-sustainable stable microbial ecosystem comprising an exhabitant fungal partner (mycobiont) and at least one or more photosynthetic partners (photobiont). The successful symbiosis is responsible for their persistence throughout time and allows all the partners (holobionts) to thrive in many extreme habitats, where without the synergistic relationship they would be rare or non-existent. The ability to survive in harsh conditions can be directly correlated with the production of some unique metabolites. Despite the potential applications, these unique metabolites have been underutilised by pharmaceutical and agrochemical industries due to their slow growth, low biomass availability and technical challenges involved in their artificial cultivation. However, recent development of biotechnological tools such as molecular phylogenetics, modern tissue culture techniques, metabolomics and molecular engineering are opening up a new opportunity to exploit these compounds within the lichen holobiome for industrial applications. This review also highlights the recent advances in culturing the symbionts and the computational and molecular genetics approaches of lichen gene regulation recognized for the enhanced production of target metabolites. The recent development of multi-omics novel biodiscovery strategies aided by synthetic biology in order to study the heterologous expressed lichen-derived biosynthetic gene clusters in a cultivatable host offers a promising means for a sustainable supply of specialized metabolites.

Process Technologies of Cyanobacteria

Although the handling and exploitation of cyanobacteria is associated with some challenges, these phototrophic bacteria offer great opportunities for innovative biotechnological processes. This chapter covers versatile aspects of working with cyanobacteria, starting with up-to-date in silico and in vitro screening methods for bioactive substances. Subsequently, common conservation techniques and vitality/viability estimation methods are compared and supplemented by own data regarding the non-invasive vitality evaluation via pulse amplitude modulated fluorometry. Moreover, novel findings about the influence the state of the pre-cultures have on main cultures are presented. The following sub-chapters deal with different photobioreactor-designs, with special regard to biofilm photobioreactors, as well as with heterotrophic and mixotrophic cultivation modes. The latter topic provides information from literature on successfully enhanced cyanobacterial production processes, augmented by own data.

Functional characterization of prokaryotic dark matter: the road so far and what lies ahead

Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the "microbial dark matter" (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.

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

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

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.

An Unprecedented Number of Cytochrome P450s Are Involved in Secondary Metabolism in Salinispora Species

Cytochrome P450 monooxygenases (CYPs/P450s) are heme thiolate proteins present in species across the biological kingdoms. By virtue of their broad substrate promiscuity and regio- and stereo-selectivity, these enzymes enhance or attribute diversity to secondary metabolites. Actinomycetes species are well-known producers of secondary metabolites, especially Salinispora species. Despite the importance of P450s, a comprehensive comparative analysis of P450s and their role in secondary metabolism in Salinispora species is not reported. We therefore analyzed P450s in 126 strains from three different species Salinispora arenicola, S. pacifica, and S. tropica. The study revealed the presence of 2643 P450s that can be grouped into 45 families and 103 subfamilies. CYP107 and CYP125 families are conserved, and CYP105 and CYP107 families are bloomed (a P450 family with many members) across Salinispora species. Analysis of P450s that are part of secondary metabolite biosynthetic gene clusters (smBGCs) revealed Salinispora species have an unprecedented number of P450s (1236 P450s-47%) part of smBGCs compared to other bacterial species belonging to the genera Streptomyces (23%) and Mycobacterium (11%), phyla Cyanobacteria (8%) and Firmicutes (18%) and the classes Alphaproteobacteria (2%) and Gammaproteobacteria (18%). A peculiar characteristic of up to six P450s in smBGCs was observed in Salinispora species. Future characterization Salinispora species P450s and their smBGCs have the potential for discovering novel secondary metabolites.

Functional characterization of key polyketide synthases by integrated metabolome and transcriptome analysis on curcuminoid biosynthesis in Curcuma wenyujin

Leaf and tuber extracts of Curcuma wenyujin contain a mixture of curcuminoids. However, the curcuminoid constituents and their molecular mechanisms are poorly understood, and the relevant curcumin synthases remain unclear. In this study, we comprehensively compared the metabolite profiles of the leaf and tuber tissues of C. wenyujin. A total of 11 curcuminoid metabolites were identified and exhibited differentially changed contents in the leaf and tuber tissues. An integrated analysis of metabolomic and transcriptomic data revealed the proposed biosynthesis pathway of curcuminoid. Two candidate type Ⅲ polyketide synthases (PKSs) were identified in the metabolically engineering yeasts, indicating that CwPKS1 and CwPKS2 maintained substrate and product specificities. Especially, CwPKS1 is the first type Ⅲ PKS identified to synthesize hydrogenated derivatives of curcuminoid, dihydrocurcumin and tetrehydrocurcumin. Interestingly, the substitution of the glycine at position 219 with aspartic acid (G219D mutant) resulted in the complete inactivation of CwPKS1. Our results provide the first comparative metabolome analysis of C. wenyujin and functionally identified type Ⅲ PKSs, giving valuable information for curcuminoids biosynthesis.

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.

Small investments with big returns: environmental genomic bioprospecting of microbial life

Microorganisms and their natural products are major drivers of ecological processes and industrial applications. Microbial bioprospecting has been critical for the advancement in various fields such as pharmaceuticals, sustainable industries, food security and bioremediation. Next generation sequencing has been paramount in the exploration of diverse environmental microbiomes. It presents a culture-independent approach to investigating hitherto uncultured taxa, resulting in the creation of massive sequence databases, which are available in the public domain. Genome mining searches available (meta)genomic data for target biosynthetic genes, and combined with the large-scale public data, this in-silico bioprospecting method presents an efficient and extensive way to uncover microbial bioproducts. Bioinformatic tools have progressed to a stage where we can recover genomes from the environment; these metagenome-assembled genomes present a way to understand the metabolic capacity of microorganisms in a physiological and ecological context. Environmental sampling been extensive across various ecological settings, including microbiomes with unique physicochemical properties that could influence the discovery of novel functions and metabolic pathways. Although in-silico methods cannot completely substitute in-vitro studies, the contextual information it provides is invaluable for understanding the ecological and taxonomic distribution of microbial genotypes and to form effective strategies for future microbial bioprospecting efforts.

In silico genome mining of potential novel biosynthetic gene clusters for drug discovery from Burkholderia bacteria

As an emerging resource, Gram-negative Burkholderia bacteria were able to produce a wide range of bioactive secondary metabolites with potential therapeutic and biotechnological applications. Genome mining has emerged as an influential platform for screening and pinpointing natural product diversity with the increasing number of Burkholderia genome sequences. Here, for genome mining of potential biosynthetic gene clusters (BGCs) and prioritizing prolific producing Burkholderia strains, we investigated the relationship between species evolution and distribution of main BGC groups using computational analysis of complete genome sequences of 248 Burkholderia species publicly available. We uncovered significantly differential distribution patterns of BGCs in the Burkholderia phyla, even among strains that are genetically very similar. We found various types of BGCs in Burkholderia, including some representative and most common BGCs for biosynthesis of encrypted or known terpenes, non-ribosomal peptides (NRPs) and some hybrid BGCs for cryptic products. We also observed that Burkholderia contain a lot of unspecified BGCs, representing high potentials to produce novel compounds. Analysis of BGCs for RiPPs (Ribosomally synthesized and posttranslationally modified peptides) and a texobactin-like BGC as examples showed wide classification and diversity of RiPP BGCs in Burkholderia at species level and metabolite predication. In conclusion, as the biggest investigation in silico by far on BGCs of the particular genus Burkholderia, our data implied a great diversity of natural products in Burkholderia and BGC distributions closely related to phylogenetic variation, and suggested different or concurrent strategies used to identify new drug molecules from these microorganisms will be important for the selection of potential BGCs and prolific producing strains for drug discovery.

Cyanobacterial Genome Sequencing, Annotation, and Bioinformatics

Cyanobacteria are collectively a globally important monophyletic phylum of bacteria. They have attracted a lot of attention, not only because they are rich sources of natural bioactive products, including toxic substances, but also because they play an important role in global nitrogen and carbon cycles, and are capable of maintaining versatile environmental niche adaptations. A vast number of cyanobacterial genomes have become available due to fast development of sequencing technologies, but effort is still needed to comprehensively understand the molecular basis of their diversity. Here, we introduce a basic pipeline for the cyanobacterial genome sequencing project that can be employed to complete the whole cyanobacterial genome. The pipeline includes DNA extraction from the cyanobacterial culture of interest, hybrid genome sequencing, and genome assembly and annotation. At the end of the chapter, we briefly introduce genome mining tools and one successful genome mining example from our laboratory. This chapter provides general guidance regarding the sequencing project and thus includes several references for alternative methods and tools so that the reader can easily modify the pipeline according to the needs of the laboratory.

An Overview of Bioprocesses Employing Specifically Selected Microbial Catalysts for γ-Aminobutyric Acid Production

Gamma-aminobutyric acid (GABA) is an important chemical compound in the human brain. GABA acts as an inhibitory neurotransmitter by inducing hyperpolarization of cellular membranes. Usually, this pharmaceutically important compound is synthesized using a chemical process, but in this short overview we have only analysed microbial processes, which have been studied for the biosynthesis of this commercially important compound. The content of this article includes the following summarised information: the search for biological processes showed a number of lactic acid bacteria and certain species of fungi, which could be effectively used for the production of GABA. Strains found to possess GABA-producing pathways include Lactobacillus brevis CRL 1942, L. plantarum FNCC 260, Streptococcus salivarius subsp. thermophilus Y2, Bifidobacterium strains, Monascus spp., and Rhizopus spp. Each of these strains required specific growth conditions. However, several factors were common among these strains, such as the use of two main supplements in their fermentation medium—monosodium glutamate and pyridoxal phosphate—and maintaining an acidic pH. Optimization studies of GABA production were comprised of altering the media constituents, modifying growth conditions, types of cultivation system, and genetic manipulation. Some strains increased the production of GABA under anaerobic conditions. Genetic manipulation focused on silencing some genes or overexpression of gadB and gadC. The conclusion, based on the review of information available in published research, is that the targeted manipulation of selected microorganisms, as well as the culture conditions for an optimised bioprocess, should be adopted for an increased production of GABA to meet its increasing demand for food and pharmaceutical applications.

Evaluating the Distribution of Bacterial Natural Product Biosynthetic Genes across Lake Huron Sediment

Environmental microorganisms continue to serve as a major source of bioactive natural products (NPs) and as an inspiration for many other scaffolds in the toolbox of modern medicine. Nearly all microbial NP-inspired therapies can be traced to field expeditions to collect samples from the environment. Despite the importance of these expeditions in the search for new drugs, few studies have attempted to document the extent to which NPs or their corresponding production genes are distributed within a given environment. To gain insights into this, the geographic occurrence of NP ketosynthase (KS) and adenylation (A) domains was documented across 53 and 58 surface sediment samples, respectively, covering 59,590 square kilometers of Lake Huron. Overall, no discernible NP geographic distribution patterns were observed for 90,528 NP classes of nonribosomal peptides and polyketides detected in the survey. While each sampling location harbored a similar number of A domain operational biosynthetic units (OBUs), a limited overlap of OBU type was observed, suggesting that at the sequencing depth used in this study, no single location served as a NP "hotspot". These data support the hypothesis that there is ample variation in NP occurrence between sampling sites and suggest that extensive sample collection efforts are required to fully capture the functional chemical diversity of sediment microbial communities on a regional scale.

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.

Synthetic Biology Advanced Natural Product Discovery

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a limited number of natural products have been discovered, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels under conventional laboratory conditions. With the rapid development of synthetic biology, advanced genome mining and engineering strategies have been reported and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions.

Developing fungal heterologous expression platforms to explore and improve the production of natural products from fungal biodiversity

Natural products from fungi represent an important source of biologically active metabolites notably for therapeutic agent development. Genome sequencing revealed that the number of biosynthetic gene clusters (BGCs) in fungi is much larger than expected. Unfortunately, most of them are silent or barely expressed under laboratory culture conditions. Moreover, many fungi in nature are uncultivable or cannot be genetically manipulated, restricting the extraction and identification of bioactive metabolites from these species. Rapid exploration of the tremendous number of cryptic fungal BGCs necessitates the development of heterologous expression platforms, which will facilitate the efficient production of natural products in fungal cell factories. Host selection, BGC assembly methods, promoters used for heterologous gene expression, metabolic engineering strategies and compartmentalization of biosynthetic pathways are key aspects for consideration to develop such a microbial platform. In the present review, we summarize current progress on the above challenges to promote research effort in the relevant fields.

Defining the Expression, Production, and Signaling Roles of Specialized Metabolites during Bacillus subtilis Differentiation

Bacterial specialized (or secondary) metabolites are structurally diverse molecules that mediate intra- and interspecies interactions by altering growth and cellular physiology and differentiation. Bacillus subtilis, a Gram-positive model bacterium commonly used to study biofilm formation and sporulation, has the capacity to produce more than 10 specialized metabolites. Some of these B. subtilis specialized metabolites have been investigated for their role in facilitating cellular differentiation, but only rarely has the behavior of multiple metabolites been simultaneously investigated. In this study, we explored the interconnectivity of differentiation (biofilm and sporulation) and specialized metabolites in B. subtilis. Specifically, we interrogated how development influences specialized metabolites and vice versa. Using the sporulation-inducing medium DSM, we found that the majority of the specialized metabolites examined are expressed and produced during biofilm formation and sporulation. Additionally, we found that six of these metabolites (surfactin, ComX, bacillibactin, bacilysin, subtilosin A, and plipastatin) are necessary signaling molecules for proper progression of B. subtilis differentiation. This study further supports the growing body of work demonstrating that specialized metabolites have essential physiological functions as cell-cell communication signals in bacteria. IMPORTANCE Bacterially produced specialized metabolites are frequently studied for their potential use as antibiotics and antifungals. However, a growing body of work has suggested that the antagonistic potential of specialized metabolites is not their only function. Here, using Bacillus subtilis as our model bacterium, we demonstrated that developmental processes such as biofilm formation and sporulation are tightly linked to specialized metabolite gene expression and production. Additionally, under our differentiation-inducing conditions, six out of the nine specialized metabolites investigated behave as intraspecific signals that impact B. subtilis physiology and influence biofilm formation and sporulation. Our work supports the viewpoint that specialized metabolites have a clear role as cell-cell signaling molecules within differentiated populations of bacteria.

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.

antiSMASH 6.0: improving cluster detection and comparison capabilities

Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products. Since 2011, the "antibiotics and secondary metabolite analysis shell—antiSMASH" (https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free-to-use web server and as a standalone tool under an OSI-approved open-source license. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi. Here, we present the updated version 6 of antiSMASH. antiSMASH 6 increases the number of supported cluster types from 58 to 71, displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, allows for the integration of results from other prediction tools, and more effectively detects tailoring enzymes in RiPP clusters.

Spectrum of deep learning algorithms in drug discovery

Deep learning (DL) algorithms are a subset of machine learning algorithms with the aim of modeling complex mapping between a set of elements and their classes. In parallel to the advance in revealing the molecular bases of diseases, a notable innovation has been undertaken to apply DL in data/libraries management, reaction optimizations, differentiating uncertainties, molecule constructions, creating metrics from qualitative results, and prediction of structures or interactions. From source identification to lead discovery and medicinal chemistry of the drug candidate, drug delivery, and modification, the challenges can be subjected to artificial intelligence algorithms to aid in the generation and interpretation of data. Discovery and design approach, both demand automation, large data management and data fusion by the advance in high-throughput mode. The application of DL can accelerate the exploration of drug mechanisms, finding novel indications for existing drugs (drug repositioning), drug development, and preclinical and clinical studies. The impact of DL in the workflow of drug discovery, design, and their complementary tools are highlighted in this review. Additionally, the type of DL algorithms used for this purpose, and their pros and cons along with the dominant directions of future research are presented.

Streptomyces: host for refactoring of diverse bioactive secondary metabolites

Microbial secondary metabolites are intensively explored due to their demands in pharmaceutical, agricultural and food industries. Streptomyces are one of the largest sources of secondary metabolites having diverse applications. In particular, the abundance of secondary metabolites encoding biosynthetic gene clusters and presence of wobble position in Streptomyces strains make it potential candidate as a native or heterologous host for secondary metabolite production including several cryptic gene clusters expression. Here, we have discussed the developments in Streptomyces strains genome mining, its exploration as a suitable host and application of synthetic biology for refactoring genetic systems for developing chassis for enhanced as well as novel secondary metabolites with reduced genome and cleaned background.

Tapping Into Actinobacterial Genomes for Natural Product Discovery

The presence of secondary metabolite biosynthetic gene clusters (BGCs) makes actinobacteria well-known producers of diverse metabolites. These ubiquitous microbes are extensively exploited for their ability to synthesize diverse secondary metabolites. The extent of their ability to synthesize various molecules is yet to be evaluated. Current advancements in genome sequencing, metabolomics, and bioinformatics have provided a plethora of information about the mechanism of synthesis of these bioactive molecules. Accessing the biosynthetic gene cluster responsible for the production of metabolites has always been a challenging assignment. The genomic approach developments have opened a new gateway for examining and manipulating novel antibiotic gene clusters. These advancements have now developed a better understanding of actinobacterial physiology and their genetic regulation for the prolific production of natural products. These new approaches provide a unique opportunity to discover novel bioactive compounds that might replenish antibiotics’ exhausted stock and counter the microbes’ resistance crisis.

Cytosine Base Editor-Mediated Multiplex Genome Editing to Accelerate Discovery of Novel Antibiotics in Bacillus subtilis and Paenibacillus polymyxa

Genome-based identification of new antibiotics is emerging as an alternative to traditional methods. However, uncovering hidden antibiotics under the background of known antibiotics remains a challenge. To over this problem using a quick and effective genetic approach, we developed a multiplex genome editing system using a cytosine base editor (CBE). The CBE system achieved simultaneous double, triple, quadruple, and quintuple gene editing with efficiencies of 100, 100, 83, and 75%, respectively, as well as the 100% editing efficiency of single targets in Bacillus subtilis. Whole-genome sequencing of the edited strains showed that they had an average of 8.5 off-target single-nucleotide variants at gRNA-independent positions. The CBE system was used to simultaneously knockout five known antibiotic biosynthetic gene clusters to leave only an uncharacterized polyketide biosynthetic gene cluster in Paenibacillus polymyxa E681. The polyketide showed antimicrobial activities against gram-positive bacteria, but not gram-negative bacteria and fungi. Therefore, our findings suggested that the CBE system might serve as a powerful tool for multiplex genome editing and greatly accelerating the unraveling of hidden antibiotics in Bacillus and Paenibacillus species.

CRISPR-Cas9-Based Discovery of the Verrucosidin Biosynthesis Gene Cluster in Penicillium polonicum

Penicillium polonicum, commonly found on food matrices, is a mycotoxigenic species able to produce a neurotoxin called verrucosidin. This methylated α-pyrone polyketide inhibits oxidative phosphorylation in mitochondria and thereby causes neurological diseases. Despite the importance of verrucosidin as a toxin, its biosynthetic genes have not been characterized yet. By similarity analysis with the polyketide synthase (PKS) genes for the α-pyrones aurovertin (AurA) and citreoviridin (CtvA), 16 PKS genes for putative α-pyrones were identified in the P. polonicum genome. A single PKS gene, verA, was found to be transcribed under verrucosidin-producing growth conditions. The annotated functions of the genes neighboring verA correspond to those required for verrucosidin biosynthesis. To prove the involvement of verA in verrucosidin biosynthesis, the clustered regularly interspaced short palindrome repeats (CRISPR) technology was applied to P. polonicum. In vitro reconstituted CRISPR-Cas9 was used to induce targeted gene deletions in P. polonicum. This approach allowed identifying and characterizing the verrucosidin biosynthetic gene cluster. VerA deletion mutants were no longer able to produce verrucosidin, whereas they were displaying morphological characteristics comparable with the wild-type strain. The available CRISPR-Cas9 technology allows characterizing the biosynthetic potential of P. polonicum as a valuable source of novel compounds.

Comparative Genomics Analysis of Keratin-Degrading Chryseobacterium Species Reveals Their Keratinolytic Potential for Secondary Metabolite Production

A promising keratin-degrading strain from the genus Chryseobacterium (Chryseobacterium sp. KMC2) was investigated using comparative genomic tools against three publicly available reference genomes to reveal the keratinolytic potential for biosynthesis of valuable secondary metabolites. Genomic features and metabolic potential of four species were compared, showing genomic differences but similar functional categories. Eleven different secondary metabolite gene clusters of interest were mined from the four genomes successfully, including five common ones shared across all genomes. Among the common metabolites, we identified gene clusters involved in biosynthesis of flexirubin-type pigment, microviridin, and siderophore, showing remarkable conservation across the four genomes. Unique secondary metabolite gene clusters were also discovered, for example, ladderane from Chryseobacterium sp. KMC2. Additionally, this study provides a more comprehensive understanding of the potential metabolic pathways of keratin utilization in Chryseobacterium sp. KMC2, with the involvement of amino acid metabolism, TCA cycle, glycolysis/gluconeogenesis, propanoate metabolism, and sulfate reduction. This work uncovers the biosynthesis of secondary metabolite gene clusters from four keratinolytic Chryseobacterium species and shades lights on the keratinolytic potential of Chryseobacterium sp. KMC2 from a genome-mining perspective, can provide alternatives to valorize keratinous materials into high-value bioactive natural products.

Salicylic Acid Biosynthesis and Metabolism: A Divergent Pathway for Plants and Bacteria

Salicylic acid (SA) is an active secondary metabolite that occurs in bacteria, fungi, and plants. SA and its derivatives (collectively called salicylates) are synthesized from chorismate (derived from shikimate pathway). SA is considered an important phytohormone that regulates various aspects of plant growth, environmental stress, and defense responses against pathogens. Besides plants, a large number of bacterial species, such as Pseudomonas, Bacillus, Azospirillum, Salmonella, Achromobacter, Vibrio, Yersinia, and Mycobacteria, have been reported to synthesize salicylates through the NRPS/PKS biosynthetic gene clusters. This bacterial salicylate production is often linked to the biosynthesis of small ferric-ion-chelating molecules, salicyl-derived siderophores (known as catecholate) under iron-limited conditions. Although bacteria possess entirely different biosynthetic pathways from plants, they share one common biosynthetic enzyme, isochorismate synthase, which converts chorismate to isochorismate, a common precursor for synthesizing SA. Additionally, SA in plants and bacteria can undergo several modifications to carry out their specific functions. In this review, we will systematically focus on the plant and bacterial salicylate biosynthesis and its metabolism.