The year 2020 in natural product bioinformatics: an overview of the latest tools and databases

Phylogenomic analysis uncovers an unexpected capacity for the biosynthesis of secondary metabolites in Pseudoalteromonas

Pseudoalteromonas is a genus of marine bacteria and a promising source of natural products with antibacterial, antifungal, and antifouling bioactivities. To accelerate the exploration of new compounds from this genus, we applied the gene-first approach to study 632 public Pseudoalteromonas genomes. We identified 3968 biosynthetic gene clusters (BGCs) involved in the biosynthesis of secondary metabolites and classified them into 995 gene cluster families (GCFs). Surprisingly, only 9 GCFs (0.9 %) included an experimentally identified reference biosynthetic gene cluster from the Minimum Information about a Biosynthetic Gene cluster database (MIBiG), suggesting a striking novelty of secondary metabolites in Pseudoalteromonas. Bioinformatic analysis of the biosynthetic diversity encoded in the identified BGCs uncovered six dominant species of this genus, P. citrea, P. flavipulchra, P. luteoviolacea, P. maricaloris, P. piscicida, and P. rubra, that encoded more than 17 BGCs on average. Moreover, each species exhibited a species-specific distribution of BGC. However, a deep analysis revealed two BGCs conserved across five of the six dominant species. These BGCS encoded an unknown lanthipeptide and the siderophore myxochelin B implying an essential role of antibiotics for Pseudoalteromonas. We chemically profiled 11 strains from the 6 dominant species and identified four new antibiotics, korormicins L-O (1-4), from P. citrea WJX-3. Our results highlight the unexplored biosynthetic potential for bioactive compounds in Pseudoalteromonas and provide an important guideline for targeting exploration.

Unraveling diabetes complexity through natural products, miRNAs modulation, and future paradigms in precision medicine and global health

BACKGROUND AND AIMS

The challenge posed by diabetes necessitates a paradigm shift from conventional diagnostic approaches focusing on glucose and lipid levels to the transformative realm of precision medicine. This approach, leveraging advancements in genomics and proteomics, acknowledges the individualistic genetic variations, dietary preferences, and environmental exposures in diabetes management. The study comprehensively analyzes the evolving diabetes landscape, emphasizing the pivotal role of genomics, proteomics, microRNAs (miRNAs), metabolomics, and bioinformatics.

RESULTS

Precision medicine revolutionizes diabetes research and treatment by diverging from traditional diagnostic methods, recognizing the heterogeneous nature of the condition. MiRNAs, crucial post-transcriptional gene regulators, emerge as promising therapeutic targets, influencing key facets such as insulin signaling and glucose homeostasis. Metabolomics, an integral component of omics sciences, contributes significantly to diabetes research, elucidating metabolic disruptions, and offering potential biomarkers for early diagnosis and personalized therapies. Bioinformatics unveils dynamic connections between natural substances, miRNAs, and cellular pathways, aiding in the exploration of the intricate molecular terrain in diabetes. The study underscores the imperative for experimental validation in natural product-based diabetes therapy, emphasizing the need for in vitro and in vivo studies leading to clinical trials for assessing effectiveness, safety, and tolerability in real-world applications. Global cooperation and ethical considerations play a pivotal role in addressing diabetes challenges worldwide, necessitating a multifaceted approach that integrates traditional knowledge, cultural competence, and environmental awareness.

CONCLUSIONS

The key components of diabetes treatment, including precision medicine, metabolomics, bioinformatics, and experimental validation, converge in future strategies, embodying a holistic paradigm for diabetes care anchored in cutting-edge research and global healthcare accessibility.

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

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

The structure of the monobactam-producing thioesterase domain of SulM forms a unique complex with the upstream carrier protein domain

Nonribosomal peptide synthetases (NRPSs) are responsible for the production of important biologically active peptides. The large, multidomain NRPSs operate through an assembly line strategy in which the growing peptide is tethered to carrier domains that deliver the intermediates to neighboring catalytic domains. While most NRPS domains catalyze standard chemistry of amino acid activation, peptide bond formation, and product release, some canonical NRPS catalytic domains promote unexpected chemistry. The paradigm monobactam antibiotic sulfazecin is produced through the activity of a terminal thioesterase domain of SulM, which catalyzes an unusual β-lactam-forming reaction in which the nitrogen of the C-terminal N-sulfo-2,3-diaminopropionate residue attacks its thioester tether to release the monobactam product. We have determined the structure of the thioesterase domain as both a free-standing domain and a didomain complex with the upstream holo peptidyl-carrier domain. The position of variant lid helices results in an active site pocket that is quite constrained, a feature that is likely necessary to orient the substrate properly for β-lactam formation. Modeling of a sulfazecin tripeptide into the active site identifies a plausible binding mode identifying potential interactions for the sulfamate and the peptide backbone with Arg2849 and Asn2819, respectively. The overall structure is similar to the β-lactone-forming thioesterase domain that is responsible for similar ring closure in the production of obafluorin. We further use these insights to enable bioinformatic analysis to identify additional, uncharacterized β-lactam-forming biosynthetic gene clusters by genome mining.

The insect microbiome is a vast source of bioactive small molecules

Covering: September 1964 to June 2023Bacteria and fungi living in symbiosis with insects have been studied over the last sixty years and found to be important sources of bioactive natural products. Not only classic producers of secondary metabolites such as Streptomyces and other members of the phylum Actinobacteria but also numerous bacteria from the phyla Proteobacteria and Firmicutes and an impressive array of fungi (usually pathogenic) serve as the source of a structurally diverse number of small molecules with important biological activities including antimicrobial, cytotoxic, antiparasitic and specific enzyme inhibitors. The insect niche is often the exclusive provider of microbes producing unique types of biologically active compounds such as gerumycins, pederin, dinactin, and formicamycins. However, numerous insects still have not been described taxonomically, and in most cases, the study of their microbiota is completely unexplored. In this review, we present a comprehensive survey of 553 natural products produced by microorganisms isolated from insects by collating and classifying all the data according to the type of compound (rather than the insect or microbial source). The analysis of the correlations among the metadata related to insects, microbial partners, and their produced compounds provides valuable insights into the intricate dynamics between insects and their symbionts as well as the impact of their metabolites on these relationships. Herein, we focus on the chemical structure, biosynthesis, and biological activities of the most relevant compounds.

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.

Natural product discovery in soil actinomycetes: unlocking their potential within an ecological context

Natural products (NPs) produced by bacteria, particularly soil actinomycetes, often possess diverse bioactivities and play a crucial role in human health, agriculture, and biotechnology. Soil actinomycete genomes contain a vast number of predicted biosynthetic gene clusters (BGCs) yet to be exploited. Understanding the factors governing NP production in an ecological context and activating cryptic and silent BGCs in soil actinomycetes will provide researchers with a wealth of molecules with potential novel applications. Here, we highlight recent advances in NP discovery strategies employing ecology-inspired approaches and discuss the importance of understanding the environmental signals responsible for activation of NP production, particularly in a soil microbial community context, as well as the challenges that remain.

The structure of the monobactam-producing thioesterase domain of SulM forms a unique complex with the upstream carrier protein domain

Nonribosomal peptide synthetases (NRPSs) are responsible for the production of important biologically active peptides. The large, multidomain NRPSs operate through an assembly line strategy in which the growing peptide is tethered to carrier domains that deliver the intermediates to neighboring catalytic domains. While most NRPS domains catalyze standard chemistry of amino acid activation, peptide bond formation and product release, some canonical NRPS catalytic domains promote unexpected chemistry. The paradigm monobactam antibiotic sulfazecin is produced through the activity of a terminal thioesterase domain that catalyzes an unusual β-lactam forming reaction in which the nitrogen of the C-terminal N-sulfo-2,3-diaminopropionate residue attacks its thioester tether to release the β-lactam product. We have determined the structure of the thioesterase domain as both a free-standing domain and a didomain complex with the upstream holo peptidyl-carrier domain. The structure illustrates a constrained active site that orients the substrate properly for β-lactam formation. In this regard, the structure is similar to the β-lactone forming thioesterase domain responsible for the production of obafluorin. Analysis of the structure identifies features that are responsible for this four-membered ring closure and enable bioinformatic analysis to identify additional, uncharacterized β-lactam-forming biosynthetic gene clusters by genome mining.

Medicinal plants meet modern biodiversity science

Plants have been an essential source of human medicine for millennia. In this review, we argue that a holistic, interdisciplinary approach to the study of medicinal plants that combines methods and insights from three key disciplines - evolutionary ecology, molecular biology/biochemistry, and ethnopharmacology - is poised to facilitate new breakthroughs in science, including pharmacological discoveries and rapid advancements in human health and well-being. Such interdisciplinary research leverages data and methods spanning space, time, and species associated with medicinal plant species evolution, ecology, genomics, and metabolomic trait diversity, all of which build heavily on traditional Indigenous knowledge. Such an interdisciplinary approach contrasts sharply with most well-funded and successful medicinal plant research during the last half-century, which, despite notable advancements, has greatly oversimplified the dynamic relationships between plants and humans, kept hidden the larger human narratives about these relationships, and overlooked potentially important research and discoveries into life-saving medicines. We suggest that medicinal plants and people should be viewed as partners whose relationship involves a complicated and poorly explored set of (socio-)ecological interactions including not only domestication but also commensalisms and mutualisms. In short, medicinal plant species are not just chemical factories for extraction and exploitation. Rather, they may be symbiotic partners that have shaped modern societies, improved human health, and extended human lifespans.

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.

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.

Machine learning-assisted structure annotation of natural products based on MS and NMR data

Covering: up to March 2023Machine learning (ML) has emerged as a popular tool for analyzing the structures of natural products (NPs). This review presents a summary of the recent advancements in ML-assisted mass spectrometry (MS) and nuclear magnetic resonance (NMR) data analysis to establish the chemical structures of NPs. First, ML-based MS/MS analyses that rely on library matching are discussed, which involves the utilization of ML algorithms to calculate similarity, predict the MS/MS fragments, and form molecular fingerprint. Then, ML assisted MS/MS structural annotation without library matching is reviewed. Furthermore, the cases of ML algorithms in assisting structural studies of NPs based on NMR are discussed from four perspectives: NMR prediction, functional group identification, structural categorization and quantum chemical calculation. Finally, the review concludes with a discussion of the challenges and the trends associated with the structural establishment of NPs based on ML algorithms.

Marine indole alkaloid diversity and bioactivity. What do we know and what are we missing?

Covering: marine indole alkaloids (n = 2048) and their reported bioactivities up to the end of 2021Despite increasing numbers of marine natural products (MNPs) reported each year, most have only been examined for cytotoxic, antibacterial, and/or antifungal biological activities with the majority found to be inactive in these assays. In this context, why are natural products continuing to be examined in assays they are unlikely to show significant activity in, and what targets might be more useful for expanding knowledge of their biologically relevant chemical space? We have undertaken a meta-analysis of the biological activities for 2048 marine indole alkaloids (MIAs), a diverse sub-class of MNPs reported up to the end of 2021, and this has highlighted that the bioactivity potentials for up to 86% of published MIAs remains underexplored and/or undefined. Although most published MIAs are not cytotoxic or antimicrobial, there is a continued focus on using these assays to evaluate new structurally related analogues. Using cheminformatics analyses, the chemical diversity of the 2048 MIAs were clustered using fragment based fingerprints and their reported bioactivity potency towards specific disease targets was assessed for structure activity trends. These analyses showed that there are groups of MIAs that possess potent and diverse activities and that many analogues, previously tested only in cellular toxicity assays, could be better exploited to generate structure activity relationships associated with leads to treat emerging diseases. A collection of indole drug and drug-lead structures from non-natural sources were also incorporated into the dataset providing complementary bioactivity profiles that were further used to predict underexplored areas of potential new activity and to better direct future testing of MIAs. Our findings clearly suggest the biological evaluation of MIAs continues to be conducted on a narrow range of bioassays and disease targets, and that shifting the focus to non-toxic disease targets should provide expanded knowledge of biologically relevant chemical space aimed at maximising the potential of MIAs for drug discovery.

Present and future outlooks on environmental DNA-based methods for antibiotic discovery

Novel antibiotics are in constant demand to combat a global increase in antibiotic-resistant infections. Bacterial natural products have been a long-standing source of antibiotic compounds, and metagenomic mining of environmental DNA (eDNA) has increasingly provided new antibiotic leads. The metagenomic small-molecule discovery pipeline can be divided into three main steps: surveying eDNA, retrieving a sequence of interest, and accessing the encoded natural product. Improvements in sequencing technology, bioinformatic algorithms, and methods for converting biosynthetic gene clusters into small molecules are steadily increasing our ability to discover metagenomically encoded antibiotics. We predict that, over the next decade, ongoing technological improvements will dramatically increase the rate at which antibiotics are discovered from metagenomes.

Structural advances toward understanding the catalytic activity and conformational dynamics of modular nonribosomal peptide synthetases

Covering: up to fall 2022.Nonribosomal peptide synthetases (NRPSs) are a family of modular, multidomain enzymes that catalyze the biosynthesis of important peptide natural products, including antibiotics, siderophores, and molecules with other biological activity. The NRPS architecture involves an assembly line strategy that tethers amino acid building blocks and the growing peptides to integrated carrier protein domains that migrate between different catalytic domains for peptide bond formation and other chemical modifications. Examination of the structures of individual domains and larger multidomain proteins has identified conserved conformational states within a single module that are adopted by NRPS modules to carry out a coordinated biosynthetic strategy that is shared by diverse systems. In contrast, interactions between modules are much more dynamic and do not yet suggest conserved conformational states between modules. Here we describe the structures of NRPS protein domains and modules and discuss the implications for future natural product discovery.

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.

Combinatorial biosynthesis: playing chess with the metabolism

Secondary metabolites are a group of natural products that produced by bacteria, fungi and plants. Many applications of these compounds from medicine to industry have been discovered. However, some changes in their structure and biosynthesis mechanism are necessary for their properties to be more suitable and also for their production to be profitable. The main and most useful method to achieve this goal is combinatorial biosynthesis. This technique uses the multi-unit essence of the secondary metabolites biosynthetic enzymes to make changes in their order, structure and also the organism that produces them.

HSQC-based small molecule accurate recognition technology discovery of diverse cytotoxic sesquiterpenoids from Elephantopus tomentosus L. and structural revision of molephantins A and B

Elephantopus tomentosus L. is a perennial herb taxonomically belonging to the family Asteraceae, which has been used as a folk medicine for the treatment of hepatobiliary diseases. Sesquiterpenoids from this plant have broad biological activities, including anti-tumor, anti-inflammatory, and antibacterial effects. In this study, fifteen structurally diverse sesquiterpenoids comprised 11 germacrane-type and 4 eudesmane-type sesquiterpenoids were prioritized to isolated from Elephantopus tomentosus L. based on the HSQC-based Small Molecule Accurate Recognition Technology (SMART) strategy. Among them, ten sesquiterpenoids were previously unreported, and their structures were elucidated by spectroscopic data, computational methods, single-crystal X-ray diffraction crystallographic data or electronic circular dichroism calculations. In addition, the structures of two known sesquiterpenoids, molephantin A and B, which were reported to possess E-geometry for the Δ¹⁽¹⁰⁾ double bond, were revised by reanalyzing their spectroscopic and X-ray crystallographic data. Some sesquiterpenoids exhibited significant cytotoxic activities against Hep3B and HepG2 cell lines.

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.

Metabolomics and Genomics Enable the Discovery of a New Class of Nonribosomal Peptidic Metallophores from a Marine Micromonospora

Although microbial genomes harbor an abundance of biosynthetic gene clusters, there remain substantial technological gaps that impair the direct correlation of newly discovered gene clusters and their corresponding secondary metabolite products. As an example of one approach designed to minimize or bridge such gaps, we employed hierarchical clustering analysis and principal component analysis (hcapca, whose sole input is MS data) to prioritize 109 marine Micromonospora strains and ultimately identify novel strain WMMB482 as a candidate for in-depth "metabologenomics" analysis following its prioritization. Highlighting the power of current MS-based technologies, not only did hcapca enable the discovery of one new, nonribosomal peptide bearing an incredible diversity of unique functional groups, but metabolomics for WMMB482 unveiled 16 additional congeners via the application of Global Natural Product Social molecular networking (GNPS), herein named ecteinamines A-Q (1-17). The ecteinamines possess an unprecedented skeleton housing a host of uncommon functionalities including a menaquinone pathway-derived 2-naphthoate moiety, 4-methyloxazoline, the first example of a naturally occurring Ψ[CH2NH] "reduced amide", a methylsulfinyl moiety, and a d-cysteinyl residue that appears to derive from a unique noncanonical epimerase domain. Extensive in silico analysis of the ecteinamine (ect) biosynthetic gene cluster and stable isotope-feeding experiments helped illuminate the novel enzymology driving ecteinamine assembly as well the role of cluster collaborations or "duets" in producing such structurally complex agents. Finally, ecteinamines were found to bind nickel, cobalt, zinc, and copper, suggesting a possible biological role as broad-spectrum metallophores.

Computer Science Technology in Natural Products Research: A Review of Its Applications and Implications

Computational approaches to drug development are rapidly growing in popularity and have been used to produce significant results. Recent developments in information science have expanded databases and chemical informatics knowledge relating to natural products. Natural products have long been well-studied, and a large number of unique structures and remarkable active substances have been reported. Analyzing accumulated natural product knowledge using emerging computational science techniques is expected to yield more new discoveries. In this article, we discuss the current state of natural product research using machine learning. The basic concepts and frameworks of machine learning are summarized. Natural product research that utilizes machine learning is described in terms of the exploration of active compounds, automatic compound design, and application to spectral data. In addition, efforts to develop drugs for intractable diseases will be addressed. Lastly, we discuss key considerations for applying machine learning in this field. This paper aims to promote progress in natural product research by presenting the current state of computational science and chemoinformatics approaches in terms of its applications, strengths, limitations, and implications for the field.

The Natural Product Domain Seeker version 2 (NaPDoS2) webtool relates ketosynthase phylogeny to biosynthetic function

The Natural Product Domain Seeker (NaPDoS) webtool detects and classifies ketosynthase (KS) and condensation domains from genomic, metagenomic, and amplicon sequence data. Unlike other tools, a phylogeny-based classification scheme is used to make broader predictions about the polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) genes in which these domains are found. NaPDoS is particularly useful for the analysis of incomplete biosynthetic genes or gene clusters, as are often observed in poorly assembled genomes and metagenomes, or when loci are not clustered, as in eukaryotic genomes. To help support the growing interest in sequence-based analyses of natural product biosynthetic diversity, here we introduce version 2 of the webtool, NaPDoS2, available at http://napdos.ucsd.edu/napdos2. This update includes the addition of 1417 KS sequences, representing a major expansion of the taxonomic and functional diversity represented in the webtool database. The phylogeny-based KS classification scheme now recognizes 41 class and subclass assignments, including new type II PKS subclasses. Workflow modifications accelerate run times, allowing larger datasets to be analyzed. In addition, default parameters were established using statistical validation tests to maximize KS detection and classification accuracy while minimizing false positives. We further demonstrate the applications of NaPDoS2 to assess PKS biosynthetic potential using genomic, metagenomic, and PCR amplicon datasets. These examples illustrate how NaPDoS2 can be used to predict biosynthetic potential and detect genes involved in the biosynthesis of specific structure classes or new biosynthetic mechanisms.

Designing Microbial Cell Factories for the Production of Chemicals

The sustainable production of chemicals from renewable, nonedible biomass has emerged as an essential alternative to address pressing environmental issues arising from our heavy dependence on fossil resources. Microbial cell factories are engineered microorganisms harboring biosynthetic pathways streamlined to produce chemicals of interests from renewable carbon sources. The biosynthetic pathways for the production of chemicals can be defined into three categories with reference to the microbial host selected for engineering: native-existing pathways, nonnative-existing pathways, and nonnative-created pathways. Recent trends in leveraging native-existing pathways, discovering nonnative-existing pathways, and designing de novo pathways (as nonnative-created pathways) are discussed in this Perspective. We highlight key approaches and successful case studies that exemplify these concepts. Once these pathways are designed and constructed in the microbial cell factory, systems metabolic engineering strategies can be used to improve the performance of the strain to meet industrial production standards. In the second part of the Perspective, current trends in design tools and strategies for systems metabolic engineering are discussed with an eye toward the future. Finally, we survey current and future challenges that need to be addressed to advance microbial cell factories for the sustainable production of chemicals.

Native metabolomics identifies the rivulariapeptolide family of protease inhibitors

The identity and biological activity of most metabolites still remain unknown. A bottleneck in the exploration of metabolite structures and pharmaceutical activities is the compound purification needed for bioactivity assignments and downstream structure elucidation. To enable bioactivity-focused compound identification from complex mixtures, we develop a scalable native metabolomics approach that integrates non-targeted liquid chromatography tandem mass spectrometry and detection of protein binding via native mass spectrometry. A native metabolomics screen for protease inhibitors from an environmental cyanobacteria community reveals 30 chymotrypsin-binding cyclodepsipeptides. Guided by the native metabolomics results, we select and purify five of these compounds for full structure elucidation via tandem mass spectrometry, chemical derivatization, and nuclear magnetic resonance spectroscopy as well as evaluation of their biological activities. These results identify rivulariapeptolides as a family of serine protease inhibitors with nanomolar potency, highlighting native metabolomics as a promising approach for drug discovery, chemical ecology, and chemical biology studies.

Bioactivity-guided isolation of specialized metabolites is an iterative process. Here, the authors demonstrate a native metabolomics approach that allows for fast screening of complex metabolite extracts against a protein of interest and simultaneous structure annotation.

Exploring fungal RiPPs from the perspective of chemical ecology

Since the initial detection, in 2007, of fungal ribosomally synthesised and post-translationally modified peptides (RiPPs), this group of natural products has undergone rapid expansion, with four separate classes now recognised: amatoxins/phallotoxins, borosins, dikaritins, and epichloëcyclins. Largely due to their historically anthropocentric employment in medicine and agriculture, novel fungal proteins and peptides are seldom investigated in relation to the fungus itself. Therefore, although the benefits these compounds confer to humans are often realised, their evolutionary advantage to the fungus, the reason for their continued production, is often obscure or ignored. This review sets out to summarise current knowledge on how these small peptide-derived products influence their producing species and surrounding biotic environment.

Discovery of New Secondary Metabolites from Marine Bacteria Hahella Based on an Omics Strategy

Hahella is one characteristic genus under the Hahellaceae family and shows a good potential for synthesizing new natural products. In this study, we examined the distribution of the secondary metabolite biosynthetic gene cluster (SMBGC) under Hahella with anti-SMASH. The results derived from five genomes released 70 SMBGCs. On average, each strain contains 12 gene clusters, and the most abundant ones (45.7%) are from the family of non-ribosomal peptide synthetase (NRPS) and non-ribosomal peptide synthetase hybrid with polyketide synthase (NRPS/PKS), indicating a great potential to find bioactive compounds. The comparison of SMBGC between H. chejuensis and other species showed that H. chejuensis contained two times more gene clusters than H. ganghwensis. One strain, designed as NBU794, was isolated from the mangrove soil of Dongzhai Port in Haikou (China) by iChip. The 16S rRNA gene of NBU794 exhibited 99% identity to H. chejuensis KCTC 2396 and clustered with the H. chejuensis clade on the phylogenetic trees. Genome mining on strain NBU794 released 17 SMBGCs and two groups of bioactive compounds, which are chejuenolide A-C and nine prodiginines derivatives. The prodiginines derivatives include the well-known lead compound prodigiosin and two new compounds, 2-methyl-3-pentyl-4-O-methyl-prodiginine and 2-methyl-3-octyl-prodiginine, which were identified through fragmentation analysis based on LC-MS/MS. The anti-microbial activity assay showed prodigiosin and 2-methyl-3-heptyl-prodiginine exhibited the best performance in inhibiting Escherichia coli, Salmonella paratyphi B, MASA Staphylococcus aureus, Bacillus subtilis, and Candida albicans. Moreover, the yield of prodigiosin in H. chejuensis NBU794 was also evaluated, which could reach 1.40 g/L under the non-optimized condition and increase to 5.83 g/L in the modified ISP4 medium with macroporous adsorption beads added, indicating that NBU794 is a promising source of prodigiosin.

Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family

Natural products produced by plants are one of the most investigated natural sources, which substantially contributed to the development of the natural products field. Even though these compounds are widely explored, the literature still lacks comprehensive investigations aiming to explore the evolution of secondary metabolites produced by plants, especially if classical methodologies are employed. The development of sensitive hyphenated techniques and computational tools for data processing has enabled the study of large datasets, being valuable assets for chemosystematic studies. Here, we describe a strategy for chemotaxonomic investigations using the Malpighiaceae botanical family as a model. Our workflow was based on MS/MS untargeted metabolomics, spectral searches, and recently described in silico classification tools, which were mapped into the latest molecular phylogeny accepted for this family. The metabolomic analysis revealed that different ionization modes and extraction protocols significantly impacted the chemical profiles, influencing the chemotaxonomic results. Spectral searches within public databases revealed several clades or genera-specific molecular families, being potential chemical markers for these taxa, while the in silico classification tools were able to expand the Malpighiaceae chemical space. The classes putatively annotated were used for ancestral character reconstructions, which recovered several classes of metabolites as homoplasies (i.e., non-exclusive) or synapomorphies (i.e., exclusive) for all sampled clades and genera. Our workflow combines several approaches to perform a comprehensive evolutionary chemical study. We expect it to be used on further chemotaxonomic investigations to expand chemical knowledge and reveal biological insights for compounds classes in different biological groups.

New Glycosylated Polyene Macrolides: Refining the Ore from Genome Mining

Glycosylated polyene macrolides include effective antifungal agents, such as pimaricin, nystatin, candicidin, and amphotericin B. For the treatment of systemic mycoses, amphotericin B has been described as a gold-standard antibiotic because of its potent activity against a broad spectrum of fungal pathogens, which do not readily become resistant. However, amphotericin B has severe toxic side effects, and the development of safer alternatives remains an important objective. One approach towards obtaining such compounds is to discover new related natural products. Advances in next-generation sequencing have delivered a wealth of microbial genome sequences containing polyene biosynthetic gene clusters. These typically encode a modular polyketide synthase that catalyzes the assembly of the aglycone core, a cytochrome P450 that oxidizes a methyl branch to a carboxyl group, and additional enzymes for synthesis and attachment of a single mycosamine sugar residue. In some cases, further P450s catalyze epoxide formation or hydroxylation within the macrolactone. Bioinformatic analyses have identified over 250 of these clusters. Some are predicted to encode potentially valuable new polyenes that have not been uncovered by traditional screening methods. Recent experimental studies have characterized polyenes with new polyketide backbones, previously unknown late oxygenations, and additional sugar residues that increase water-solubility and reduce hemolytic activity. Here we review these studies and assess how this new knowledge can help to prioritize silent polyene clusters for further investigation. This approach should improve the chances of discovering better antifungal antibiotics.

Engineered Chimeras Unveil Swappable Modular Features of Fatty Acid and Polyketide Synthase Acyl Carrier Proteins

The strategic redesign of microbial biosynthetic pathways is a compelling route to access molecules of diverse structure and function in a potentially environmentally sustainable fashion. The promise of this approach hinges on an improved understanding of acyl carrier proteins (ACPs), which serve as central hubs in biosynthetic pathways. These small, flexible proteins mediate the transport of molecular building blocks and intermediates to enzymatic partners that extend and tailor the growing natural products. Past combinatorial biosynthesis efforts have failed due to incompatible ACP-enzyme pairings. Herein, we report the design of chimeric ACPs with features of the actinorhodin polyketide synthase ACP (ACT) and of the Escherichia coli fatty acid synthase (FAS) ACP (AcpP). We evaluate the ability of the chimeric ACPs to interact with the E. coli FAS ketosynthase FabF, which represents an interaction essential to building the carbon backbone of the synthase molecular output. Given that AcpP interacts with FabF but ACT does not, we sought to exchange modular features of ACT with AcpP to confer functionality with FabF. The interactions of chimeric ACPs with FabF were interrogated using sedimentation velocity experiments, surface plasmon resonance analyses, mechanism-based cross-linking assays, and molecular dynamics simulations. Results suggest that the residues guiding AcpP-FabF compatibility and ACT-FabF incompatibility may reside in the loop I, α-helix II region. These findings can inform the development of strategic secondary element swaps that expand the enzyme compatibility of ACPs across systems and therefore represent a critical step toward the strategic engineering of "un-natural" natural products.

Natural product drug discovery in the artificial intelligence era

Natural products (NPs) are primarily recognized as privileged structures to interact with protein drug targets. Their unique characteristics and structural diversity continue to marvel scientists for developing NP-inspired medicines, even though the pharmaceutical industry has largely given up. High-performance computer hardware, extensive storage, accessible software and affordable online education have democratized the use of artificial intelligence (AI) in many sectors and research areas. The last decades have introduced natural language processing and machine learning algorithms, two subfields of AI, to tackle NP drug discovery challenges and open up opportunities. In this article, we review and discuss the rational applications of AI approaches developed to assist in discovering bioactive NPs and capturing the molecular "patterns" of these privileged structures for combinatorial design or target selectivity.

Heterologous Expression of Fungal Biosynthetic Pathways in Aspergillus nidulans Using Episomal Vectors

Filamentous fungi produce a wide diversity of secondary metabolites, whose biosynthesis is encoded in biosynthetic gene clusters (BGCs). As novel BGCs are often found in fungal species that are genetically intractable or difficult to cultivate, heterologous expression is increasingly being used for compound discovery. In addition, heterologous expression is a useful strategy to elucidate the function of the genes within a BGC and shed light on their enzymatic mechanisms. Here, we describe a method for BGC elucidation using multi-marker AMA1-based pYFAC vectors for episomal expression in the fungal host Aspergillus nidulans. The pYFAC vectors have the advantage of high transformation efficiency and support high compound production. In addition, different pathway intermediates can be easily evaluated by testing different vector combinations. This protocol encompasses different AMA1-based strategies for BGC expression such as cloning of a BGC native sequence, promoter exchange or transcription factor overexpression. We also describe procedures for A. nidulans protoplasting, transformation, and small-scale culture analysis of strains containing AMA1 vectors.

Actinobacteria From Desert: Diversity and Biotechnological Applications

Deserts, as an unexplored extreme ecosystem, are known to harbor diverse actinobacteria with biotechnological potential. Both multidrug-resistant (MDR) pathogens and environmental issues have sharply raised the emerging demand for functional actinobacteria. From 2000 to 2021, 129 new species have been continuously reported from 35 deserts worldwide. The two largest numbers are of the members of the genera Streptomyces and Geodermatophilus, followed by other functional extremophilic strains such as alkaliphiles, halotolerant species, thermophiles, and psychrotolerant species. Improved isolation strategies for the recovery of culturable and unculturable desert actinobacteria are crucial for the exploration of their diversity and offer a better understanding of their survival mechanisms under extreme environmental stresses. The main bioprospecting processes involve isolation of target actinobacteria on selective media and incubation and selection of representatives from isolation plates for further investigations. Bioactive compounds obtained from desert actinobacteria are being continuously explored for their biotechnological potential, especially in medicine. To date, there are more than 50 novel compounds discovered from these gifted actinobacteria with potential antimicrobial activities, including anti-MDR pathogens and anti-inflammatory, antivirus, antifungal, antiallergic, antibacterial, antitumor, and cytotoxic activities. A range of plant growth-promoting abilities of the desert actinobacteria inspired great interest in their agricultural potential. In addition, several degradative, oxidative, and other functional enzymes from desert strains can be applied in the industry and the environment. This review aims to provide a comprehensive overview of desert environments as a remarkable source of diverse actinobacteria while such rich diversity offers an underexplored resource for biotechnological exploitations.

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

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

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

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

Biosynthesis, evolution and ecology of microbial terpenoids

Covering: through June 2021Terpenoids are the largest class of natural products recognised to date. While mostly known to humans as bioactive plant metabolites and part of essential oils, structurally diverse terpenoids are increasingly reported to be produced by microorganisms. For many of the compounds biological functions are yet unknown, but during the past years significant insights have been obtained for the role of terpenoids in microbial chemical ecology. Their functions include stress alleviation, maintenance of cell membrane integrity, photoprotection, attraction or repulsion of organisms, host growth promotion and defense. In this review we discuss the current knowledge of the biosynthesis and evolution of microbial terpenoids, and their ecological and biological roles in aquatic and terrestrial environments. Perspectives on their biotechnological applications, knowledge gaps and questions for future studies are discussed.

Host and microbiota metabolic signals in aging and longevity

Aging is an inevitable biochemical process that adversely affects personal health and poses ever-increasing challenges to society. Recent research has revealed the crucial role of metabolism in regulating aging and longevity. During diverse metabolic processes, the host organism and their symbiotic partners-the microbiota-produce thousands of chemical products (metabolites). Emerging studies have uncovered specific metabolites that act as signaling molecules to actively regulate longevity. Here we review the latest progress in understanding the molecular mechanisms by which metabolites from the host and/or microbiota promote longevity. We also highlight state-of-the-art technologies for discovering, profiling and imaging aging- and longevity-regulating metabolites and for deciphering the molecular basis of their actions. The broad application of these technologies in aging research, together with future advances, will foster the systematic discovery of aging- and longevity-regulating metabolites and their signaling pathways. These metabolite signals should provide promising targets for developing new interventions to promote longevity and healthy aging.

Integrating perspectives in actinomycete research: an ActinoBase review of 2020-21

Last year ActinoBase, a Wiki-style initiative supported by the UK Microbiology Society, published a review highlighting the research of particular interest to the actinomycete community. Here, we present the second ActinoBase review showcasing selected reports published in 2020 and early 2021, integrating perspectives in the actinomycete field. Actinomycetes are well-known for their unsurpassed ability to produce specialised metabolites, of which many are used as therapeutic agents with antibacterial, antifungal, or immunosuppressive activities. Much research is carried out to understand the purpose of these metabolites in the environment, either within communities or in host interactions. Moreover, many efforts have been placed in developing computational tools to handle big data, simplify experimental design, and find new biosynthetic gene cluster prioritisation strategies. Alongside, synthetic biology has provided advances in tools to elucidate the biosynthesis of these metabolites. Additionally, there are still mysteries to be uncovered in understanding the fundamentals of filamentous actinomycetes' developmental cycle and regulation of their metabolism. This review focuses on research using integrative methodologies and approaches to understand the bigger picture of actinomycete biology, covering four research areas: i) technology and methodology; ii) specialised metabolites; iii) development and regulation; and iv) ecology and host interactions.

Comparative Genomics Reveals a Remarkable Biosynthetic Potential of the Streptomyces Phylogenetic Lineage Associated with Rugose-Ornamented Spores

The genus Streptomyces is one of the richest sources of secondary metabolite biosynthetic gene clusters (BGCs). Sequencing of a large number of genomes has provided evidence that this well-known bacterial genus still harbors a large number of cryptic BGCs, and their metabolites are yet to be discovered. When taking a gene-first approach for new natural product discovery, BGC prioritization would be the most crucial step for the discovery of novel chemotypes. We hypothesized that strains with a greater number of BGCs would also contain a greater number of silent unique BGCs due to the presence of complex regulatory systems. Based on this hypothesis, we employed a comparative genomics approach to identify a specific Streptomyces phylogenetic lineage with the highest and yet-uncharacterized biosynthetic potential. A comparison of BGC abundance and genome size across 158 phylogenetically diverse Streptomyces type strains identified that members of the phylogenetic group characterized by the formation of rugose-ornamented spores possess the greatest number of BGCs (average, 50 BGCs) and also the largest genomes (average, 11.5 Mb). The study of genetic and biosynthetic diversities using comparative genomics of 11 sequenced genomes and a genetic similarity network analysis of BGCs suggested that members of this group carry a large number of unique BGCs, the majority of which are cryptic and not associated with any known natural product. We believe that members of this Streptomyces phylogenetic group possess a remarkable biosynthetic potential and thus would be a good target for a metabolite characterization study that could lead to the discovery of novel chemotypes.

IMPORTANCE It is now well recognized that members of the genus Streptomyces still harbor a large number of cryptic BGCs in their genomes, which are mostly silent under laboratory culture conditions. Activation of transcriptionally silent BGCs is technically challenging and thus forms a bottleneck when taking a gene-first approach for the discovery of new natural products. Thus, it is important to focus activation efforts on strains with BGCs that have the potential to produce novel metabolites. The clade-level analysis of biosynthetic diversity could provide insights into the relationship between phylogenetic lineage and biosynthetic diversity. By exploring BGC abundance in relation to Streptomyces phylogeny, we identified a specific monophyletic lineage associated with the highest BGC abundance. Then, using a combined analysis of comparative genomics and a genetic network, we demonstrated that members of this lineage are genetically and biosynthetically diverse, contain a large number of cryptic BGCs with novel genotypes, and thus would be a good target for metabolite characterization studies.

Anti-Zika candidates from a marine fungus with a remarkable biosynthetic repertoire

The study of natural products provides exciting opportunities for the discovery of novel biologically active molecules and biosynthetic pathways. Recently, Yuan and colleagues described 30 cyclic depsipeptides that are biosynthesized by proteins encoded by three distinct gene clusters in the marine fungus, Beauveria felina. Genetic and biochemical studies confirmed the involvement of nonribosomal peptide synthetases in the production of multiple compounds, some of which inhibit Zika virus replication.

Metabolomics as a Tool to Study Underused Soy Parts: In Search of Bioactive Compounds

The valorization of agri-food by-products is essential from both economic and sustainability perspectives. The large quantity of such materials causes problems for the environment; however, they can also generate new valuable ingredients and products which promote beneficial effects on human health. It is estimated that soybean production, the major oilseed crop worldwide, will leave about 597 million metric tons of branches, leaves, pods, and roots on the ground post-harvesting in 2020/21. An alternative for the use of soy-related by-products arises from the several bioactive compounds found in this plant. Metabolomics studies have already identified isoflavonoids, saponins, and organic and fatty acids, among other metabolites, in all soy organs. The present review aims to show the application of metabolomics for identifying high-added-value compounds in underused parts of the soy plant, listing the main bioactive metabolites identified up to now, as well as the factors affecting their production.

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

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