The evolution of genome mining in microbes - a review

Identification by Synthesis: Imidacins, Urocanate-Derived Alkaloids from the Myxobacterium Stigmatella aurantiaca

Innovative discovery approaches such as genome-mining and metabolomics-inspired methods have reshaped the natural product research field, complementing traditional bioactivity-based screens and allowing hitherto unseen compounds to be uncovered from previously investigated producers. In line with these trends, we report here imidacins, a novel class of secondary metabolites specific to the myxobacterial genus Stigmatella. A combination of secondary metabolome analysis, genome-mining techniques, spectroscopic analysis, and finally total synthesis was used to allow structure elucidation. Imidacins are urocanate-derived aliphatic acids with an adjacent cyclopropane moiety, structural features unprecedented in natural products to date.

Dual-Mechanism Peptide SR25 has Broad Antimicrobial Activity and Potential Application for Healing Bacteria-infected Diabetic Wounds

The rise of antibiotic resistance poses a significant public health crisis, particularly due to limited antimicrobial options for the treatment of infections with Gram-negative pathogens. Here, an antimicrobial peptide (AMP) SR25 is characterized, which effectively kills both Gram-negative and Gram-positive bacteria through a unique dual-targeting mechanism without detectable resistance. Meanwhile, an SR25-functionalized hydrogel is developed for the efficient treatment of infected diabetic wounds. SR25 is obtained through genome mining from an uncultured bovine enteric actinomycete named Nonomuraea Jilinensis sp. nov. Investigations reveal that SR25 has two independent cellular targets, disrupting bacterial membrane integrity and restraining the activity of succinate:quinone oxidoreductase (SQR). In a diabetic mice wound infection model, the SR25-incorporated hydrogel exhibits high efficacy against mixed infections of Escherichia coli (E. coli) and methicillin-resistant Staphylococcus aureus (MRSA), accelerating wound healing. Overall, these findings demonstrate the therapeutic potential of SR25 and highlight the value of mining drugs with multiple mechanisms from uncultured animal commensals for combating challenging bacterial pathogens.

Analysis of Co-localized Biosynthetic Gene Clusters Identifies a Membrane-Permeabilizing Natural Product

Combination therapy is an effective strategy to combat antibiotic resistance. Multiple synergistic antimicrobial combinations are produced by enzymes encoded in biosynthetic gene clusters (BGCs) that co-localize on the bacterial genome. This phenomenon led to the hypothesis that mining co-localized BGCs will reveal new synergistic combinations of natural products. Here, we bioinformatically identified 38 pairs of co-localized BGCs, which we predict to produce natural products that are related to known compounds, including polycyclic tetramate macrolactams (PoTeMs). We further showed that ikarugamycin, a PoTeM, increases the membrane permeability of Acinetobacter baumannii and Staphylococcus aureus, which suggests that ikarugamycin might be an adjuvant that facilitates the entry of other natural products. Our work outlines a promising avenue to discover synergistic combinations of natural products by mining bacterial genomes.

Bacterial polyynes uncovered: a journey through their bioactive properties, biosynthetic mechanisms, and sustainable production strategies

Covering: up to 2023Conjugated polyynes are natural compounds characterized by alternating single and triple carbon-carbon bonds, endowing them with distinct physicochemical traits and a range of biological activities. While traditionally sourced mainly from plants, recent investigations have revealed many compounds originating from bacterial strains. This review synthesizes current research on bacterial-derived conjugated polyynes, delving into their biosynthetic routes, underscoring the variety in their molecular structures, and examining their potential applications in biotechnology. Additionally, we outline future directions for metabolic and protein engineering to establish more robust and stable platforms for their production.

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.

A systematic comparison of natural product potential, with an emphasis on RiPPs, by mining of bacteria of three large ecosystems

The implementation of several global microbiome studies has yielded extensive insights into the biosynthetic potential of natural microbial communities. However, studies on the distribution of several classes of ribosomally synthesized and post-translationally modified peptides (RiPPs), non-ribosomal peptides (NRPs) and polyketides (PKs) in different large microbial ecosystems have been very limited. Here, we collected a large set of metagenome-assembled bacterial genomes from marine, freshwater and terrestrial ecosystems to investigate the biosynthetic potential of these bacteria. We demonstrate the utility of public dataset collections for revealing the different secondary metabolite biosynthetic potentials among these different living environments. We show that there is a higher occurrence of RiPPs in terrestrial systems, while in marine systems, we found relatively more terpene-, NRP-, and PK encoding gene clusters. Among the many new biosynthetic gene clusters (BGCs) identified, we analyzed various Nif-11-like and nitrile hydratase leader peptide (NHLP) containing gene clusters that would merit further study, including promising products, such as mersacidin-, LAP- and proteusin analogs. This research highlights the significance of public datasets in elucidating the biosynthetic potential of microbes in different living environments and underscores the wide bioengineering opportunities within the RiPP family.

Unearthing naturally-occurring cyclic antibacterial peptides and their structural optimization strategies

Natural products with antibacterial activity are highly desired globally to combat against multidrug-resistant (MDR) bacteria. Antibacterial peptide (ABP), especially cyclic ABP (CABP), is one of the abundant classes. Most of them were isolated from microbes, demonstrating excellent bactericidal effects. With the improved proteolytic stability, CABPs are normally considered to have better druggability than linear peptides. However, most clinically-used CABP-based antibiotics, such as colistin, also face the challenges of drug resistance soon after they reached the market, urgently requiring the development of next-generation succedaneums. We present here a detail review on the novel naturally-occurring CABPs discovered in the past decade and some of them are under clinical trials, exhibiting anticipated application potential. According to their chemical structures, they were broadly classified into five groups, including (i) lactam/lactone-based CABPs, (ii) cyclic lipopeptides, (iii) glycopeptides, (iv) cyclic sulfur-rich peptides and (v) multiple-modified CABPs. Their chemical structures, antibacterial spectrums and proposed mechanisms are discussed. Moreover, engineered analogs of these novel CABPs are also summarized to preliminarily analyze their structure-activity relationship. This review aims to provide a global perspective on research and development of novel CABPs to highlight the effectiveness of derivatives design in identifying promising antibacterial agents. Further research efforts in this area are believed to play important roles in fighting against the multidrug-resistance crisis.

Biological Demands and Toxicity of Isoprenoid Precursors in Bacillus Subtilis Through Cell-Permeant Analogs of Isopentenyl Pyrophosphate and Dimethylallyl Pyrophosphate

Bacterial isoprenoids are necessary for many biological processes, including maintaining membrane integrity, facilitating intercellular communication, and preventing oxidative damage. All bacterial isoprenoids are biosynthesized from two five carbon structural isomers, isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP), which are cell impermeant. Herein, we demonstrate exogenous delivery of IPP and DMAPP into Bacillus subtilis by utilizing a self-immolative ester (SIE)-caging approach. We initially evaluated native B. subtilis esterase activity, which revealed a preference for short straight chain esters. We then examined the viability of the SIE-caging approach in B. subtilis and demonstrate that the released caging groups are well tolerated and the released IPP and DMAPP are bioavailable, such that isoprenoid biosynthesis can be rescued in the presence of pathway inhibitors. We further show that IPP and DMAPP are both toxic and inhibit growth of B. subtilis at the same concentration. Lastly, we establish the optimal ratio of IPP to DMAPP (5 : 1) for B. subtilis growth and find that, surprisingly, DMAPP alone is insufficient to rescue isoprenoid biosynthesis under high concentrations of fosmidomycin. These findings showcase the potential of the SIE-caging approach in B. subtilis and promise to both aid in novel isoprenoid discovery and to inform metabolic engineering efforts in bacteria.

BGCFlow: systematic pangenome workflow for the analysis of biosynthetic gene clusters across large genomic datasets

Genome mining is revolutionizing natural products discovery efforts. The rapid increase in available genomes demands comprehensive computational platforms to effectively extract biosynthetic knowledge encoded across bacterial pangenomes. Here, we present BGCFlow, a novel systematic workflow integrating analytics for large-scale genome mining of bacterial pangenomes. BGCFlow incorporates several genome analytics and mining tools grouped into five common stages of analysis such as: (i) data selection, (ii) functional annotation, (iii) phylogenetic analysis, (iv) genome mining, and (v) comparative analysis. Furthermore, BGCFlow provides easy configuration of different projects, parallel distribution, scheduled job monitoring, an interactive database to visualize tables, exploratory Jupyter Notebooks, and customized reports. Here, we demonstrate the application of BGCFlow by investigating the phylogenetic distribution of various biosynthetic gene clusters detected across 42 genomes of the Saccharopolyspora genus, known to produce industrially important secondary/specialized metabolites. The BGCFlow-guided analysis predicted more accurate dereplication of BGCs and guided the targeted comparative analysis of selected RiPPs. The scalable, interoperable, adaptable, re-entrant, and reproducible nature of the BGCFlow will provide an effective novel way to extract the biosynthetic knowledge from the ever-growing genomic datasets of biotechnologically relevant bacterial species.

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.

Cinnamosyn, a Cinnamoylated Synthetic-Bioinformatic Natural Product with Cytotoxic Activity

Most biosynthetic gene clusters (BGCs) are functionally inaccessible by using fermentation methods. Bioinformatic-coupled total synthesis provides an alternative approach for accessing BGC-encoded bioactivities. To date, synthetic bioinformatic natural product (synBNP) methods have focused on lipopeptides containing simple lipids. Here we increase the bioinformatic and synthetic complexity of the synBNP approach by targeting BGCs that encode N-cinnamoyl lipids. This led to our synthesis of cinnamosyn, a 10-mer N-cinnamoyl-containing peptide that is cytotoxic to human cells.

Multi-omic analysis tools for microbial metabolites prediction

How to resolve the metabolic dark matter of microorganisms has long been a challenging problem in discovering active molecules. Diverse omics tools have been developed to guide the discovery and characterization of various microbial metabolites, which make it gradually possible to predict the overall metabolites for individual strains. The combinations of multi-omic analysis tools effectively compensates for the shortcomings of current studies that focus only on single omics or a broad class of metabolites. In this review, we systematically update, categorize and sort out different analysis tools for microbial metabolites prediction in the last five years to appeal for the multi-omic combination on the understanding of the metabolic nature of microbes. First, we provide the general survey on different updated prediction databases, webservers, or software that based on genomics, transcriptomics, proteomics, and metabolomics, respectively. Then, we discuss the essentiality on the integration of multi-omics data to predict metabolites of different microbial strains and communities, as well as stressing the combination of other techniques, such as systems biology methods and data-driven algorithms. Finally, we identify key challenges and trends in developing multi-omic analysis tools for more comprehensive prediction on diverse microbial metabolites that contribute to human health and disease treatment.

Biosynthesis of fungal terpenoids

Covering: up to August 2023Terpenoids, which are widely distributed in animals, plants, and microorganisms, are a large group of natural products with diverse structures and various biological activities. They have made great contributions to human health as therapeutic agents, such as the anti-cancer drug paclitaxel and anti-malarial agent artemisinin. Accordingly, the biosynthesis of this important class of natural products has been extensively studied, which generally involves two major steps: hydrocarbon skeleton construction by terpenoid cyclases and skeleton modification by tailoring enzymes. Additionally, fungi (Ascomycota and Basidiomycota) serve as an important source for the discovery of terpenoids. With the rapid development of sequencing technology and bioinformatics approaches, genome mining has emerged as one of the most effective strategies to discover novel terpenoids from fungi. To date, numerous terpenoid cyclases, including typical class I and class II terpenoid cyclases as well as emerging UbiA-type terpenoid cyclases, have been identified, together with a variety of tailoring enzymes, including cytochrome P450 enzymes, flavin-dependent monooxygenases, and acyltransferases. In this review, our aim is to comprehensively present all fungal terpenoid cyclases identified up to August 2023, with a focus on newly discovered terpenoid cyclases, especially the emerging UbiA-type terpenoid cyclases, and their related tailoring enzymes from 2015 to August 2023.

Natural products from the human microbiome: an emergent frontier in organic synthesis and drug discovery

Often referred to as the "second genome", the human microbiome is at the epicenter of complex inter-habitat biochemical networks like the "gut-brain axis", which has emerged as a significant determinant of cognition, overall health and well-being, as well as resistance to antibiotics and susceptibility to diseases. As part of a broader understanding of the nexus between the human microbiome, diseases and microbial interactions, whether encoded secondary metabolites (natural products) play crucial signalling roles has been the subject of intense scrutiny in the recent past. A major focus of these activities involves harvesting the genomic potential of the human microbiome via bioinformatics guided genome mining and culturomics. Through these efforts, an impressive number of structurally intriguing antibiotics, with enhanced chemical diversity vis-à-vis conventional antibiotics have been isolated from human commensal bacteria, thereby generating considerable interest in their total synthesis and expanding their therapeutic space for drug discovery. These developments augur well for the discovery of new drugs and antibiotics, particularly in the context of challenges posed by mycobacterial resistance and emerging new diseases. The current landscape of various synthetic campaigns and drug discovery initiatives on antibacterial natural products from the human microbiome is captured in this review with an intent to stimulate further activities in this interdisciplinary arena among the new generation.

Strategies, Achievements, and Potential Challenges of Plant and Microbial Chassis in the Biosynthesis of Plant Secondary Metabolites

Diverse secondary metabolites in plants, with their rich biological activities, have long been important sources for human medicine, food additives, pesticides, etc. However, the large-scale cultivation of host plants consumes land resources and is susceptible to pest and disease problems. Additionally, the multi-step and demanding nature of chemical synthesis adds to production costs, limiting their widespread application. In vitro cultivation and the metabolic engineering of plants have significantly enhanced the synthesis of secondary metabolites with successful industrial production cases. As synthetic biology advances, more research is focusing on heterologous synthesis using microorganisms. This review provides a comprehensive comparison between these two chassis, evaluating their performance in the synthesis of various types of secondary metabolites from the perspectives of yield and strategies. It also discusses the challenges they face and offers insights into future efforts and directions.

Searching for new plastic-degrading enzymes from the plastisphere of alpine soils using a metagenomic mining approach

Plastic materials, including microplastics, accumulate in all types of ecosystems, even in remote and cold environments such as the European Alps. This pollution poses a risk for the environment and humans and needs to be addressed. Using shotgun DNA metagenomics of soils collected in the eastern Swiss Alps at about 3,000 m a.s.l., we identified genes and their proteins that potentially can degrade plastics. We screened the metagenomes of the plastisphere and the bulk soil with a differential abundance analysis, conducted similarity-based screening with specific databases dedicated to putative plastic-degrading genes, and selected those genes with a high probability of signal peptides for extracellular export and a high confidence for functional domains. This procedure resulted in a final list of nine candidate genes. The lengths of the predicted proteins were between 425 and 845 amino acids, and the predicted genera producing these proteins belonged mainly to Caballeronia and Bradyrhizobium. We applied functional validation, using heterologous expression followed by enzymatic assays of the supernatant. Five of the nine proteins tested showed significantly increased activities when we used an esterase assay, and one of these five proteins from candidate genes, a hydrolase-type esterase, clearly had the highest activity, by more than double. We performed the fluorescence assays for plastic degradation of the plastic types BI-OPL and ecovio® only with proteins from the five candidate genes that were positively active in the esterase assay, but like the negative controls, these did not show any significantly increased activity. In contrast, the activity of the positive control, which contained a PLA-degrading gene insert known from the literature, was more than 20 times higher than that of the negative controls. These findings suggest that in silico screening followed by functional validation is suitable for finding new plastic-degrading enzymes. Although we only found one new esterase enzyme, our approach has the potential to be applied to any type of soil and to plastics in various ecosystems to search rapidly and efficiently for new plastic-degrading enzymes.

A Timeline of Biosynthetic Gene Cluster Discovery in Aspergillus fumigatus: From Characterization to Future Perspectives

In 1999, the first biosynthetic gene cluster (BGC), synthesizing the virulence factor DHN melanin, was characterized in Aspergillus fumigatus. Since then, 19 additional BGCs have been linked to specific secondary metabolites (SMs) in this species. Here, we provide a comprehensive timeline of A. fumigatus BGC discovery and find that initial advances centered around the commonly expressed SMs where chemical structure informed rationale identification of the producing BGC (e.g., gliotoxin, fumigaclavine, fumitremorgin, pseurotin A, helvolic acid, fumiquinazoline). Further advances followed the transcriptional profiling of a ΔlaeA mutant, which aided in the identification of endocrocin, fumagillin, hexadehydroastechrome, trypacidin, and fumisoquin BGCs. These SMs and their precursors are the commonly produced metabolites in most A. fumigatus studies. Characterization of other BGC/SM pairs required additional efforts, such as induction treatments, including co-culture with bacteria (fumicycline/neosartoricin, fumigermin) or growth under copper starvation (fumivaline, fumicicolin). Finally, four BGC/SM pairs were discovered via overexpression technologies, including the use of heterologous hosts (fumicycline/neosartoricin, fumihopaside, sphingofungin, and sartorypyrone). Initial analysis of the two most studied A. fumigatus isolates, Af293 and A1160, suggested that both harbored ca. 34-36 BGCs. However, an examination of 264 available genomes of A. fumigatus shows up to 20 additional BGCs, with some strains showing considerable variations in BGC number and composition. These new BGCs present a new frontier in the future of secondary metabolism characterization in this important species.

Microplastics and nanoplastics: Source, behavior, remediation, and multi-level environmental impact

Plastics introduced into the natural environment persist, degrade, and fragment into smaller particles due to various environmental factors. Microplastics (MPs) (ranging from 1 μm to 5 mm) and nanoplastics (NPs) (less than 1 μm) have emerged as pollutants posing a significant threat to all life forms on Earth. Easily ingested by living organisms, they lead to ongoing bioaccumulation and biomagnification. This review summarizes existing studies on the sources of MPs and NPs in various environments, highlighting their widespread presence in air, water, and soil. It primarily focuses on the sources, fate, degradation, fragmentation, transport, and ecotoxicity of MPs and NPs. The aim is to elucidate their harmful effects on marine organisms, soil biota, plants, mammals, and humans, thereby enhancing the understanding of the complex impacts of plastic particles on the environment. Additionally, this review highlights remediation technologies and global legislative and institutional measures for managing waste associated with MPs and NPs. It also shows that effectively combating plastic pollution requires the synergization of diverse management, monitoring strategies, and regulatory measures into a comprehensive policy framework.

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

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

N-Cα Bond Cleavage Catalyzed by a Multinuclear Iron Oxygenase from a Divergent Methanobactin-like RiPP Gene Cluster

DUF692 multinuclear iron oxygenases (MNIOs) are an emerging family of tailoring enzymes involved in the biosynthesis of ribosomally synthesized and post-translationally modified peptides (RiPPs). Three members, MbnB, TglH, and ChrH, have been characterized to date and shown to catalyze unusual and complex transformations. Using a co-occurrence-based bioinformatic search strategy, we recently generated a sequence similarity network of MNIO-RiPP operons that encode one or more MNIOs adjacent to a transporter. The network revealed >1000 unique gene clusters, evidence of an unexplored biosynthetic landscape. Herein, we assess an MNIO-RiPP cluster from this network that is encoded in Proteobacteria and Actinobacteria. The cluster, which we have termed mov (for methanobactin-like operon in Vibrio), encodes a 23-residue precursor peptide, two MNIOs, a RiPP recognition element, and a transporter. Using both in vivo and in vitro methods, we show that one MNIO, homologous to MbnB, installs an oxazolone-thioamide at a Thr-Cys dyad in the precursor. Subsequently, the second MNIO catalyzes N-Cα bond cleavage of the penultimate Asn to generate a C-terminally amidated peptide. This transformation expands the reaction scope of the enzyme family, marks the first example of an MNIO-catalyzed modification that does not involve Cys, and sets the stage for future exploration of other MNIO-RiPPs.

Empowering Site-Specific Bioconjugations In Vitro and In Vivo: Advances in Sortase Engineering and Sortase-Mediated Ligation

Sortase-mediated ligation (SML) has emerged as a powerful and versatile methodology for site-specific protein conjugation, functionalization/labeling, immobilization, and design of biohybrid molecules and systems. However, the broader application of SML faces several challenges, such as limited activity and stability, dependence on calcium ions, and reversible reactions caused by nucleophilic side-products. Over the past decade, protein engineering campaigns and particularly directed evolution, have been extensively employed to overcome sortase limitations, thereby expanding the potential application of SML in multiple directions, including therapeutics, biorthogonal chemistry, biomaterials, and biosensors. This review provides an overview of achieved advancements in sortase engineering and highlights recent progress in utilizing SML in combination with other state-of-the-art chemical and biological methodologies. The aim is to encourage scientists to employ sortases in their conjugation experiments.

OSMAC Strategy: A promising way to explore microbial cyclic peptides

Microbial secondary metabolites are pivotal for the development of novel drugs. However, conventional culture techniques, have left a vast array of unexpressed biosynthetic gene clusters (BGCs) in microorganisms, hindering the discovery of metabolites with distinct structural features and diverse biological functions. To address this limitation, several innovative strategies have been emerged. The "One Strain Many Compounds" (OSMAC) strategy, which involves altering microbial culture conditions, has proven to be particularly effective in mining numerous novel secondary metabolites for the past few years. Among these, microbial cyclic peptides stand out. These peptides often comprise rare amino acids, unique chemical structures, and remarkable biological function. With the advancement of the OSMAC strategy, a plethora of new cyclic peptides have been identified from diverse microbial genera. This work reviews the progress in mining novel compounds using the OSMAC strategy and the applications of this strategy in discovering 284 microbial cyclic peptides from 63 endophytic strains, aiming to offer insights for the further explorations into novel active cyclic peptides.

Endophytic fungi as a potential source of anti-cancer drug

Endophytes are considered one of the major sources of bioactive compounds used in different aspects of health care including cancer treatment. When colonized, they either synthesize these bioactive compounds as a part of their secondary metabolite production or augment the host plant machinery in synthesising such bioactive compounds. Hence, the study of endophytes has drawn the attention of the scientific community in the last few decades. Among the endophytes, endophytic fungi constitute a major portion of endophytic microbiota. This review deals with a plethora of anti-cancer compounds derived from endophytic fungi, highlighting alkaloids, lignans, terpenes, polyketides, polyphenols, quinones, xanthenes, tetralones, peptides, and spirobisnaphthalenes. Further, this review emphasizes modern methodologies, particularly omics-based techniques, asymmetric dihydroxylation, and biotic elicitors, showcasing the dynamic and evolving landscape of research in this field and describing the potential of endophytic fungi as a source of anticancer drugs in the future.

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/.

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

IMPORTANCE

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

Microplastics in mangroves with special reference to Asia: Occurrence, distribution, bioaccumulation and remediation options

Microplastics (MPs) are a new and lesser-known pollutant that has intrigued the interest of scientists all over the world in recent decades. MP (<5mm in size) can enter marine environments such as mangrove forests in a variety of ways, interfering with the health of the environment and organisms. Mangroves are now getting increasingly exposed to microplastic contamination due to their proximity to human activities and their position as critical transitional zones between land and sea. The present study reviews the status of MPs contamination specifically in mangrove ecosystems situated in Asia. Different sources and characteristics of MPs, subsequent deposition of MPs in mangrove water and sediments, bioaccumulation in different organisms are discussed in this context. MP concentrations in sediments and organisms were higher in mangrove forests exposed to fishing, coastal tourism, urban, and industrial wastewater than in pristine areas. The distribution of MPs varies from organism to organism in mangrove ecosystems, and is significantly influenced by their morphometric characteristics, feeding habits, dwelling environment etc. Mangrove plants can accumulate microplastics in their roots, stem and leaves through absorption, adsorption and entrapment helping in reducing abundance of microplastic in the surrounding environment. Several bacterial and fungal species are reported from these mangrove ecosystems, which are capable of degrading MPs. The bioremediation potential of mangrove plants offers an innovative and sustainable approach to mitigate microplastic pollution. Diverse mechanisms of MP biodegradation by mangrove dwelling organisms are discussed in this context. Biotechnological applications can be utilized to explore the genetic potential of the floral and faunal species found in the Asian mangroves. Detailed studies are required to monitor, control, and evaluate MP pollution in sediments and various organisms in mangrove ecosystems in Asia as well as in other parts of the world.

Mining natural products for advanced biofuels and sustainable bioproducts

Recently, there has been growing interest in the sustainable production of biofuels and bioproducts derived from renewable sources. Natural products, the largest and more structurally diverse group of metabolites, hold significant promise as sources for such bio-based products. However, there are two primary challenges in harnessing natural products' potential: precise mining of biosynthetic gene clusters (BGCs) that can be used as scaffolds or bioparts and their functional expression for biofuel and bioproduct manufacture. In this review, we explore recent advances in the development of bioinformatic tools for BGC mining and the manipulation of various hosts for natural product-based biofuels and bioproducts manufacture. Moreover, we discuss potential strategies for expanding the chemical diversity of biofuels and bioproducts and enhancing their overall yield.

Biochemical and Structural Characterization of OvoATh2: A Mononuclear Nonheme Iron Enzyme from Hydrogenimonas thermophila for Ovothiol Biosynthesis

Ovothiol A and ergothioneine are thiol-histidine derivatives with sulfur substitutions at the δ-carbon or ε-carbon of the l-histidine imidazole ring, respectively. Both ovothiol A and ergothioneine have protective effects on many aging-related diseases, and the sulfur substitution plays a key role in determining their chemical and biological properties, while factors governing sulfur incorporation regioselectivities in ovothiol and ergothioneine biosynthesis in the corresponding enzymes (OvoA, Egt1, or EgtB) are not yet known. In this study, we have successfully obtained the first OvoA crystal structure, which provides critical information to explain their C-S bond formation regioselectivity. Furthermore, OvoATh2 exhibits several additional activities: (1) ergothioneine sulfoxide synthase activity akin to Egt1 in ergothioneine biosynthesis; (2) cysteine dioxygenase activity using l-cysteine and l-histidine analogues as substrates; (3) cysteine dioxygenase activity upon mutation of an active site tyrosine residue (Y406). The structural insights and diverse chemistries demonstrated by OvoATh2 pave the way for future comprehensive structure-function correlation studies.

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.

Joint deep autoencoder and subgraph augmentation for inferring microbial responses to drugs

Exploring microbial stress responses to drugs is crucial for the advancement of new therapeutic methods. While current artificial intelligence methodologies have expedited our understanding of potential microbial responses to drugs, the models are constrained by the imprecise representation of microbes and drugs. To this end, we combine deep autoencoder and subgraph augmentation technology for the first time to propose a model called JDASA-MRD, which can identify the potential indistinguishable responses of microbes to drugs. In the JDASA-MRD model, we begin by feeding the established similarity matrices of microbe and drug into the deep autoencoder, enabling to extract robust initial features of both microbes and drugs. Subsequently, we employ the MinHash and HyperLogLog algorithms to account intersections and cardinality data between microbe and drug subgraphs, thus deeply extracting the multi-hop neighborhood information of nodes. Finally, by integrating the initial node features with subgraph topological information, we leverage graph neural network technology to predict the microbes' responses to drugs, offering a more effective solution to the 'over-smoothing' challenge. Comparative analyses on multiple public datasets confirm that the JDASA-MRD model's performance surpasses that of current state-of-the-art models. This research aims to offer a more profound insight into the adaptability of microbes to drugs and to furnish pivotal guidance for drug treatment strategies. Our data and code are publicly available at: https://github.com/ZZCrazy00/JDASA-MRD.

An antibiotic produced by Pseudomonas fluorescens CFBP2392 with antifungal activity against Rhizoctonia solani

Pseudomonas fluorescens CFBP2392 has been recognized as a potential biocontrol agent due to its ability to suppress damping-off and root rot disease. This isolate has antibacterial activity in vitro as many other strains from the Pseudomonas fluorescens complex. In this work, the antibacterial and antifungal activity of the strain were explored. Dual culture assays evidenced the antifungal activity of the strain against different phytopathogens: Alternaria sp., Pythium ultimun, Fusarium oxysporum, and Rhizoctonia solani. Purification of an antifungal fraction was performed by preparative HPLC from the chemical extraction of growth media. The fraction showed altered R. solani growth and ultrastructure. Transmission electron microscopy revealed the purified compound induced hypertrophied mitochondria, membranous vesicles, and a higher number of vacuoles in R. salani cytoplasm. In addition, co-cultivation of P. fluorescens CFBP2392 with R. solani resulted in an enlarged and deformed cell wall. To gain genomic insights on this inhibition, the complete genome of P. fluorescens CFBP2392 was obtained with Oxford Nanopore technology. Different biosynthetic gene clusters (BGCs) involved in specialized metabolites production including a lokisin-like and a koreenceine-like cluster were identified. In accordance with the putative BGCs identified, sequence phylogeny analysis of the MacB transporter in the lokisin-like cluster further supports the similarity with other transporters from the amphisin family. Our results give insights into the cellular effects of the purified microbial metabolite in R. solani ultrastructure and provide a genomic background to further explore the specialized metabolite potential.

Functional Crosstalk between Discrete Indole Terpenoid Gene Clusters in Tolypocladium album

Indole terpenoids make up a large group of secondary metabolites that display an enticing array of bioactivities. While indole diterpene (IDT) and rarely indole sesquiterpene (IST) pathways have been found individually in filamentous fungi, here we show that both cluster types are encoded within the genome of Tolypocladium album. Through heterologous reconstruction, we demonstrate the SES cluster encodes for IST biosynthesis and can tailor IDT substrates produced by the TER cluster.

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

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

Pseudomonassin, a New Bioactive Ribosomally Synthesised and Post-Translationally Modified Peptide from Pseudomonas sp. SST3

Genome mining and metabolomics have become valuable tools in natural products research to evaluate and identify potential new chemistry from bacteria. In the search for new compounds from the deep-sea organism, Pseudomonas sp. SST3, from the South Shetland Trough, Antarctica, a co-cultivation with a second deep-sea Pseudomonas zhaodongensis SST2, was undertaken to isolate pseudomonassin, a ribosomally synthesised and post-translationally modified peptide (RiPP) that belongs to a class of RiPP called lasso peptides. Pseudomonassin was identified using a genome-mining approach and isolated by means of mass spectrometric guided isolation. Extensive metabolomics analysis of the co-cultivation of Pseudomonas sp. SST3 and P. zhaodongensis SST2, Pseudomonas sp. SST3 and Escherichia coli, and P. zhaodongensis SST2 and E. coli were performed using principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA), which revealed potential new metabolites in the outlier regions of the co-cultivation, with other metabolites identified previously from other species of Pseudomonas. The sequence of pseudomonassin was completely deduced using high collision dissociation tandem mass spectrometry (HCD-MS/MS). Preliminary studies on its activity against the pathogenic P. aeruginosa and its biofilm formation have been assessed and produced a minimum inhibitory concentration (MIC) of 63 μg/mL and 28 μg/mL, respectively.

A critical review of machine-learning for "multi-omics" marine metabolite datasets

During the last decade, genomic, transcriptomic, proteomic, metabolomic, and other omics datasets have been generated for a wide range of marine organisms, and even more are still on the way. Marine organisms possess unique and diverse biosynthetic pathways contributing to the synthesis of novel secondary metabolites with significant bioactivities. As marine organisms have a greater tendency to adapt to stressed environmental conditions, the chance to identify novel bioactive metabolites with potential biotechnological application is very high. This review presents a comprehensive overview of the available "-omics" and "multi-omics" approaches employed for characterizing marine metabolites along with novel data integration tools. The need for the development of machine-learning algorithms for "multi-omics" approaches is briefly discussed. In addition, the challenges involved in the analysis of "multi-omics" data and recommendations for conducting "multi-omics" study were discussed.

gutSMASH predicts specialized primary metabolic pathways from the human gut microbiota

The gut microbiota produce hundreds of small molecules, many of which modulate host physiology. Although efforts have been made to identify biosynthetic genes for secondary metabolites, the chemical output of the gut microbiome consists predominantly of primary metabolites. Here we introduce the gutSMASH algorithm for identification of primary metabolic gene clusters, and we used it to systematically profile gut microbiome metabolism, identifying 19,890 gene clusters in 4,240 high-quality microbial genomes. We found marked differences in pathway distribution among phyla, reflecting distinct strategies for energy capture. These data explain taxonomic differences in short-chain fatty acid production and suggest a characteristic metabolic niche for each taxon. Analysis of 1,135 individuals from a Dutch population-based cohort shows that the level of microbiome-derived metabolites in plasma and feces is almost completely uncorrelated with the metagenomic abundance of corresponding metabolic genes, indicating a crucial role for pathway-specific gene regulation and metabolite flux. This work is a starting point for understanding differences in how bacterial taxa contribute to the chemistry of the microbiome.

The Pangenome of Gram-Negative Environmental Bacteria Hides a Promising Biotechnological Potential

Secondary metabolites (SMs) from environmental bacteria offer viable solutions for various health and environmental challenges. Researchers are employing advanced bioinformatic tools to investigate less-explored microorganisms and unearth novel bioactive compounds. In this research area, our understanding of SMs from environmental Gram-negative bacteria lags behind that of its Gram-positive counterparts. In this regard, Pedobacter spp. have recently gained attention, not only for their role as plant growth promoters but also for their potential in producing antimicrobials. This study focuses on the genomic analysis of Pedobacter spp. to unveil the diversity of the SMs encoded in their genomes. Among the 41 genomes analyzed, a total of 233 biosynthetic gene clusters (BGCs) were identified, revealing the potential for the production of diverse SMs, including RiPPs (27%), terpenes (22%), hybrid SMs (17%), PKs (12%), NRPs (9%) and siderophores (6%). Overall, BGC distribution did not correlate with phylogenetic lineage and most of the BGCs showed no significant hits in the MIBiG database, emphasizing the uniqueness of the compounds that Pedobacter spp. can produce. Of all the species examined, P. cryoconitis and P. lusitanus stood out for having the highest number and diversity of BGCs. Focusing on their applicability and ecological functions, we investigated in greater detail the BGCs responsible for siderophore and terpenoid production in these species and their relatives. Our findings suggest that P. cryoconitis and P. lusitanus have the potential to produce novel mixtures of siderophores, involving bifunctional IucAC/AcD NIS synthetases, as well as carotenoids and squalene. This study highlights the biotechnological potential of Pedobacter spp. in medicine, agriculture and other industries, emphasizing the need for a continued exploration of its SMs and their applications.

Genome analysis of a halophilic Virgibacillus halodenitrificans ASH15 revealed salt adaptation, plant growth promotion, and isoprenoid biosynthetic machinery

Globally, due to widespread dispersion, intraspecific diversity, and crucial ecological components of halophilic ecosystems, halophilic bacteria is considered one of the key models for ecological, adaptative, and biotechnological applications research in saline environments. With this aim, the present study was to enlighten the plant growth-promoting features and investigate the systematic genome of a halophilic bacteria, Virgibacillus halodenitrificans ASH15, through single-molecule real-time (SMRT) sequencing technology. Results showed that strain ASH15 could survive in high salinity up to 25% (w/v) NaCl concentration and express plant growth-promoting traits such as nitrogen fixation, plant growth hormones, and hydrolytic enzymes, which sustain salt stress. The results of pot experiment revealed that strain ASH15 significantly enhanced sugarcane plant growth (root shoot length and weight) under salt stress conditions. Moreover, the sequencing analysis of the strain ASH15 genome exhibited that this strain contained a circular chromosome of 3,832,903 bp with an average G+C content of 37.54%: 3721 predicted protein-coding sequences (CDSs), 24 rRNA genes, and 62 tRNA genes. Genome analysis revealed that the genes related to the synthesis and transport of compatible solutes (glycine, betaine, ectoine, hydroxyectoine, and glutamate) confirm salt stress as well as heavy metal resistance. Furthermore, functional annotation showed that the strain ASH15 encodes genes for root colonization, biofilm formation, phytohormone IAA production, nitrogen fixation, phosphate metabolism, and siderophore production, which are beneficial for plant growth promotion. Strain ASH15 also has a gene resistance to antibiotics and pathogens. In addition, analysis also revealed that the genome strain ASH15 has insertion sequences and CRISPRs, which suggest its ability to acquire new genes through horizontal gene transfer and acquire immunity to the attack of viruses. This work provides knowledge of the mechanism through which V. halodenitrificans ASH15 tolerates salt stress. Deep genome analysis, identified MVA pathway involved in biosynthesis of isoprenoids, more precisely "Squalene." Squalene has various applications, such as an antioxidant, anti-cancer agent, anti-aging agent, hemopreventive agent, anti-bacterial agent, adjuvant for vaccines and drug carriers, and detoxifier. Our findings indicated that strain ASH15 has enormous potential in industries such as in agriculture, pharmaceuticals, cosmetics, and food.

Non-Native Site-Selective Enzyme Catalysis

The ability to site-selectively modify equivalent functional groups in a molecule has the potential to streamline syntheses and increase product yields by lowering step counts. Enzymes catalyze site-selective transformations throughout primary and secondary metabolism, but leveraging this capability for non-native substrates and reactions requires a detailed understanding of the potential and limitations of enzyme catalysis and how these bounds can be extended by protein engineering. In this review, we discuss representative examples of site-selective enzyme catalysis involving functional group manipulation and C-H bond functionalization. We include illustrative examples of native catalysis, but our focus is on cases involving non-native substrates and reactions often using engineered enzymes. We then discuss the use of these enzymes for chemoenzymatic transformations and target-oriented synthesis and conclude with a survey of tools and techniques that could expand the scope of non-native site-selective enzyme catalysis.

A Comprehensive Self-Resistance Gene Database for Natural-Product Discovery with an Application to Marine Bacterial Genome Mining

In the world of microorganisms, the biosynthesis of natural products in secondary metabolism and the self-resistance of the host always occur together and complement each other. Identifying resistance genes from biosynthetic gene clusters (BGCs) helps us understand the self-defense mechanism and predict the biological activity of natural products synthesized by microorganisms. However, a comprehensive database of resistance genes is still lacking, which hinders natural product annotation studies in large-scale genome mining. In this study, we compiled a resistance gene database (RGDB) by scanning the four available databases: CARD, MIBiG, NCBIAMR, and UniProt. Every resistance gene in the database was annotated with resistance mechanisms and possibly involved chemical compounds, using manual annotation and transformation from the resource databases. The RGDB was applied to analyze resistance genes in 7432 BGCs in 1390 genomes from a marine microbiome project. Our calculation showed that the RGDB successfully identified resistance genes for more than half of the BGCs, suggesting that the database helps prioritize BGCs that produce biologically active natural products.

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.

Metabolome-guided genome mining of RiPP natural products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a chemically diverse class of metabolites. Many RiPPs show potent biological activities that make them attractive starting points for drug development. A promising approach for the discovery of new classes of RiPPs is genome mining. However, the accuracy of genome mining is hampered by the lack of signature genes shared across different RiPP classes. One way to reduce false-positive predictions is by complementing genomic information with metabolomics data. In recent years, several new approaches addressing such integrative genomics and metabolomics analyses have been developed. In this review, we provide a detailed discussion of RiPP-compatible software tools that integrate paired genomics and metabolomics data. We highlight current challenges in data integration and identify opportunities for further developments targeting new classes of bioactive RiPPs.

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.

Fungal BGCs for Production of Secondary Metabolites: Main Types, Central Roles in Strain Improvement, and Regulation According to the Piano Principle

Filamentous fungi are one of the most important producers of secondary metabolites. Some of them can have a toxic effect on the human body, leading to diseases. On the other hand, they are widely used as pharmaceutically significant drugs, such as antibiotics, statins, and immunosuppressants. A single fungus species in response to various signals can produce 100 or more secondary metabolites. Such signaling is possible due to the coordinated regulation of several dozen biosynthetic gene clusters (BGCs), which are mosaically localized in different regions of fungal chromosomes. Their regulation includes several levels, from pathway-specific regulators, whose genes are localized inside BGCs, to global regulators of the cell (taking into account changes in pH, carbon consumption, etc.) and global regulators of secondary metabolism (affecting epigenetic changes driven by velvet family proteins, LaeA, etc.). In addition, various low-molecular-weight substances can have a mediating effect on such regulatory processes. This review is devoted to a critical analysis of the available data on the "turning on" and "off" of the biosynthesis of secondary metabolites in response to signals in filamentous fungi. To describe the ongoing processes, the model of "piano regulation" is proposed, whereby pressing a certain key (signal) leads to the extraction of a certain sound from the "musical instrument of the fungus cell", which is expressed in the production of a specific secondary metabolite.

Bacterial synthetic biology: tools for novel drug discovery

INTRODUCTION

Bacterial synthetic biology has provided powerful tools to revolutionize the drug discovery process. These tools can be harnessed to generate bacterial novel pharmaceutical compounds with enhanced bioactivity and selectivity or to create genetically modified microorganisms as living drugs.

AREAS COVERED

This review provides a current overview of the state-of-the-art in bacterial synthetic biology tools for novel drug discovery. The authors discuss the application of these tools including bioinformatic tools, CRISPR tools, engineered bacterial transcriptional regulators, and synthetic biosensors for novel drug discovery. Additionally, the authors present the recent progress on reprogramming bacteriophages as living drugs to fight against antibiotic-resistant pathogens.

EXPERT OPINION

The field of using bacterial synthetic biology tools for drug discovery is rapidly advancing. However, challenges remain in developing reliable and robust methods to engineer bacteria. Further advancements in synthetic biology hold promise to speed up drug discovery, facilitating the development of novel therapeutics against various diseases.

Metagenomic Analyses Reveal the Influence of Depth Layers on Marine Biodiversity on Tropical and Subtropical Regions

The emergence of open ocean global-scale studies provided important information about the genomics of oceanic microbial communities. Metagenomic analyses shed light on the structure of marine habitats, unraveling the biodiversity of different water masses. Many biological and environmental factors can contribute to marine organism composition, such as depth. However, much remains unknown about microbial communities' taxonomic and functional features in different water layer depths. Here, we performed a metagenomic analysis of 76 publicly available samples from the Tara Ocean Project, distributed in 8 collection stations located in tropical or subtropical regions, and sampled from three layers of depth (surface water layer-SRF, deep chlorophyll maximum layer-DCM, and mesopelagic zone-MES). The SRF and DCM depth layers are similar in abundance and diversity, while the MES layer presents greater diversity than the other layers. Diversity clustering analysis shows differences regarding the taxonomic content of samples. At the domain level, bacteria prevail in most samples, and the MES layer presents the highest proportion of archaea among all samples. Taken together, our results indicate that the depth layer influences microbial sample composition and diversity.

Deep self-supervised learning for biosynthetic gene cluster detection and product classification

Natural products are chemical compounds that form the basis of many therapeutics used in the pharmaceutical industry. In microbes, natural products are synthesized by groups of colocalized genes called biosynthetic gene clusters (BGCs). With advances in high-throughput sequencing, there has been an increase of complete microbial isolate genomes and metagenomes, from which a vast number of BGCs are undiscovered. Here, we introduce a self-supervised learning approach designed to identify and characterize BGCs from such data. To do this, we represent BGCs as chains of functional protein domains and train a masked language model on these domains. We assess the ability of our approach to detect BGCs and characterize BGC properties in bacterial genomes. We also demonstrate that our model can learn meaningful representations of BGCs and their constituent domains, detect BGCs in microbial genomes, and predict BGC product classes. These results highlight self-supervised neural networks as a promising framework for improving BGC prediction and classification.

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.