Mining genomes to illuminate the specialized chemistry of life

Small Molecule in situ Resin Capture - A Compound First Approach to Natural Product Discovery

Microbial natural products remain an important resource for drug discovery. Yet, commonly employed discovery techniques are plagued by the rediscovery of known compounds, the relatively few microbes that can be cultured, and laboratory growth conditions that do not elicit biosynthetic gene expression among myriad other challenges. Here we introduce a culture independent approach to natural product discovery that we call the Small Molecule In situ Resin Capture (SMIRC) technique. SMIRC exploits in situ environmental conditions to elicit compound production and represents a new approach to access poorly explored chemical space by capturing natural products directly from the environments in which they are produced. In contrast to traditional methods, this compound-first approach can capture structurally complex small molecules across all domains of life in a single deployment while relying on Nature to provide the complex and poorly understood environmental cues needed to elicit biosynthetic gene expression. We illustrate the effectiveness of SMIRC in marine habitats with the discovery of numerous new compounds and demonstrate that sufficient compound yields can be obtained for NMR-based structure assignment. Two new compound classes are reported including one novel carbon skeleton that possesses a functional group not previously observed among natural products and a second that possesses potent biological activity. We introduce expanded deployments, in situ cultivation, and metagenomics as methods to facilitate compound discovery, enhance yields, and link compounds to producing organisms. This compound first approach can provide unprecedented access to new natural product chemotypes with broad implications for drug discovery.

Accessing hidden microbial biosynthetic potential from underexplored sources for novel drug discovery

Microbial natural products and their structural analogues have widely used as pharmaceutical agents, especially for infectious diseases and cancer. Despite this success, new structural classes with innovative chemistry and modes of action are urgently needed to be developed to combat the growing antimicrobial resistance and other public health problems. The advances in next-generation sequencing technologies and powerful computational tools open up new opportunities to explore microbial biosynthetic potential from underexplored sources, with millions of secondary metabolites awaiting discovery. The review highlights challenges associated with discovery of new chemical entities, rich reservoirs provided by untapped taxa, ecological niches or host microbiomes, emerging synthetic biotechnologies to unearth the hidden microbial biosynthetic potential for novel drug discovery at scale and speed.

Data-Driven Elucidation of Flavor Chemistry

Flavor molecules are commonly used in the food industry to enhance product quality and consumer experiences but are associated with potential human health risks, highlighting the need for safer alternatives. To address these health-associated challenges and promote reasonable application, several databases for flavor molecules have been constructed. However, no existing studies have comprehensively summarized these data resources according to quality, focused fields, and potential gaps. Here, we systematically summarized 25 flavor molecule databases published within the last 20 years and revealed that data inaccessibility, untimely updates, and nonstandard flavor descriptions are the main limitations of current studies. We examined the development of computational approaches (e.g., machine learning and molecular simulation) for the identification of novel flavor molecules and discussed their major challenges regarding throughput, model interpretability, and the lack of gold-standard data sets for equitable model evaluation. Additionally, we discussed future strategies for the mining and designing of novel flavor molecules based on multi-omics and artificial intelligence to provide a new foundation for flavor science research.

Uncovering the Cryptic Gene Cluster ahb for 3-amino-4-hydroxybenzoate Derived Ahbamycins, by Searching SARP Regulator Encoding Genes in the Streptomyces argillaceus Genome

Genome mining using standard bioinformatics tools has allowed for the uncovering of hidden biosynthesis gene clusters for specialized metabolites in Streptomyces genomes. In this work, we have used an alternative approach consisting in seeking "Streptomyces Antibiotic Regulatory Proteins" (SARP) encoding genes and analyzing their surrounding DNA region to unearth cryptic gene clusters that cannot be identified using standard bioinformatics tools. This strategy has allowed the unveiling of the new ahb cluster in Streptomyces argillaceus, which had not been retrieved before using antiSMASH. The ahb cluster is highly preserved in other Streptomyces strains, which suggests a role for their encoding compounds in specific environmental conditions. By combining overexpression of three regulatory genes and generation of different mutants, we were able to activate the ahb cluster, and to identify and chemically characterize the encoded compounds that we have named ahbamycins (AHBs). These constitute a new family of metabolites derived from 3-amino-4-hydroxybenzoate (3,4-AHBA) known for having antibiotic and antitumor activity. Additionally, by overexpressing three genes of the cluster (ahbH, ahbI, and ahbL2) for the synthesis and activation of 3,4-AHBA, a new hybrid compound, AHB18, was identified which had been produced from a metabolic crosstalk between the AHB and the argimycin P pathways. The identification of this new BGC opens the possibility to generate new compounds by combinatorial biosynthesis.

Homo medicus: The transition to meat eating increased pathogen pressure and the use of pharmacological plants in Homo

The human lineage transitioned to a more carnivorous niche 2.6 mya and evolved a large body size and slower life history, which likely increased zoonotic pathogen pressure. Evidence for this increase includes increased zoonotic infections in modern hunter-gatherers and bushmeat hunters, exceptionally low stomach pH compared to other primates, and divergence in immune-related genes. These all point to change, and probably intensification, in the infectious disease environment of Homo compared to earlier hominins and other apes. At the same time, the brain, an organ in which immune responses are constrained, began to triple in size. We propose that the combination of increased zoonotic pathogen pressure and the challenges of defending a large brain and body from pathogens in a long-lived mammal, selected for intensification of the plant-based self-medication strategies already in place in apes and other primates. In support, there is evidence of medicinal plant use by hominins in the middle Paleolithic, and all cultures today have sophisticated, plant-based medical systems, add spices to food, and regularly consume psychoactive plant substances that are harmful to helminths and other pathogens. We propose that the computational challenges of discovering effective plant-based treatments, the consequent ability to consume more energy-rich animal foods, and the reduced reliance on energetically-costly immune responses helped select for increased cognitive abilities and unique exchange relationships in Homo. In the story of human evolution, which has long emphasized hunting skills, medical skills had an equal role to play.

Bioinformatics toolbox for exploring target mutation-induced drug resistance

Drug resistance is increasingly among the main issues affecting human health and threatening agriculture and food security. In particular, developing approaches to overcome target mutation-induced drug resistance has long been an essential part of biological research. During the past decade, many bioinformatics tools have been developed to explore this type of drug resistance, and they have become popular for elucidating drug resistance mechanisms in a low cost, fast and effective way. However, these resources are scattered and underutilized, and their strengths and limitations have not been systematically analyzed and compared. Here, we systematically surveyed 59 freely available bioinformatics tools for exploring target mutation-induced drug resistance. We analyzed and summarized these resources based on their functionality, data volume, data source, operating principle, performance, etc. And we concisely discussed the strengths, limitations and application examples of these tools. Specifically, we tested some predictive tools and offered some thoughts from the clinician's perspective. Hopefully, this work will provide a useful toolbox for researchers working in the biomedical, pesticide, bioinformatics and pharmaceutical engineering fields, and a good platform for non-specialists to quickly understand drug resistance prediction.

Terpene biosynthesis in marine sponge animals

Sea sponges are the largest marine source of small-molecule natural products described to date. Sponge-derived molecules, such as the chemotherapeutic eribulin, the calcium-channel blocker manoalide, and antimalarial compound kalihinol A, are renowned for their impressive medicinal, chemical, and biological properties. Sponges contain microbiomes that control the production of many natural products isolated from these marine invertebrates. In fact, all genomic studies to date investigating the metabolic origins of sponge-derived small molecules concluded that microbes-not the sponge animal host-are the biosynthetic producers. However, early cell-sorting studies suggested the sponge animal host may play a role particularly in the production of terpenoid molecules. To investigate the genetic underpinnings of sponge terpenoid biosynthesis, we sequenced the metagenome and transcriptome of an isonitrile sesquiterpenoid-containing sponge of the order Bubarida. Using bioinformatic searches and biochemical validation, we identified a group of type I terpene synthases (TSs) from this sponge and multiple other species, the first of this enzyme class characterized from the sponge holobiome. The Bubarida TS-associated contigs consist of intron-containing genes homologous to sponge genes and feature GC percentage and coverage consistent with other eukaryotic sequences. We identified and characterized TS homologs from five different sponge species isolated from geographically distant locations, thereby suggesting a broad distribution amongst sponges. This work sheds light on the role of sponges in secondary metabolite production and speaks to the possibility that other sponge-specific molecules originate from the animal host.

Current status of secondary metabolite pathways linked to their related biosynthetic gene clusters in Aspergillus section Nigri

Covering: up to the end of 2021Aspergilli are biosynthetically 'talented' micro-organisms and therefore the natural products community has continually been interested in the wealth of biosynthetic gene clusters (BGCs) encoding numerous secondary metabolites related to these fungi. With the rapid increase in sequenced fungal genomes combined with the continuous development of bioinformatics tools such as antiSMASH, linking new structures to unknown BGCs has become much easier when taking retro-biosynthetic considerations into account. On the other hand, in most cases it is not as straightforward to prove proposed biosynthetic pathways due to the lack of implemented genetic tools in a given fungal species. As a result, very few secondary metabolite biosynthetic pathways have been characterized even amongst some of the most well studied Aspergillus spp., section Nigri (black aspergilli). This review will cover all known biosynthetic compound families and their structural diversity known from black aspergilli. We have logically divided this into sub-sections describing major biosynthetic classes (polyketides, non-ribosomal peptides, terpenoids, meroterpenoids and hybrid biosynthesis). Importantly, we will focus the review on metabolites which have been firmly linked to their corresponding BGCs.

Genome Mining and Heterologous Expression Guided the Discovery of Antimicrobial Naphthocyclinones from Streptomyces eurocidicus CGMCC 4.1086

A type II polyketide synthase biosynthetic gene cluster (nap) was identified in Streptomyces eurocidicus CGMCC 4.1086 via genome mining. The heterologous expression of the cryptic nap gene cluster in Streptomyces albus J1074 generated dimerized aromatic polyketide naphthocyclinones (1-3), whose structures were determined via extensive analysis using nuclear magnetic resonance and high-resolution electrospray ionization mass spectroscopy. The biological pathway of naphthocyclinone synthesis was revealed via in vivo gene deletion, in vitro biochemical reactions, and comparative genomics. Remarkably, 3 played a crucial role in inhibiting Phytophthora capsici and Phytophthora sojae, with EC₅₀ values of 6.1 and 20.2 μg/mL, respectively. Furthermore, 3 exhibited a potent protective effect against P. capsici and P. sojae in greenhouse tests.

Biosynthesis of Lyngbyastatins 1 and 3, Cytotoxic Depsipeptides from an Okeania sp. Marine Cyanobacterium

Lyngbyastatins (Lbns) 1 (1) and 3 (2) belong to a group of cyclic depsipeptides that inhibit cancer cell proliferation. These compounds have been isolated from different marine cyanobacterial collections, while further development of these compounds relies on their lengthy total synthesis. Biosynthetic studies of these compounds can provide viable strategies to access these compounds and develop new analogs. In this study, we report the identification and characterization of one Lbn biosynthetic gene cluster (BGC) from the marine cyanobacterium Okeania sp. VPG18-21. We initially identified 1 and 2 in the organic extract by mass spectrometry and performed the targeted isolation of these compounds, which feature a (2S,3R)-3-amino-2-methylpentanoic acid (MAP) and a (2S,3R)-3-amino-2-methylhexanoic acid (Amha) moiety, respectively. Parallel metagenomic sequencing of VPG18-21 led to the identification of a putative Lbn BGC that encodes six megaenzymes (LbnA-F), including one polyketide synthase (PKS, LbnE), four nonribosomal peptide synthetases (NRPSs, LbnB-D and -F), and one PKS-NRPS hybrid (LbnA). Bioinformatic analysis of these enzymes suggested that the BGC produces 1 and 2. Furthermore, our biochemical studies of three recombinant adenylation domains uncovered their substrate specificities, supporting the identity of the BGC. Finally, we identified near-complete Lbn-like BGCs in the genomes of two other marine cyanobacteria.

Complete Genome Sequence Analysis of Kribbella sp. CA-293567 and Identification of the Kribbellichelins A & B and Sandramycin Biosynthetic Gene Clusters

Minor genera actinomycetes are considered a promising source of new secondary metabolites. The strain Kribbella sp. CA-293567 produces sandramycin and kribbellichelins A & B In this work, we describe the complete genome sequencing of this strain and the in silico identification of biosynthetic gene clusters (BGCs), focusing on the pathways encoding sandramycin and kribbellichelins A-B. We also present a comparative analysis of the biosynthetic potential of 38 publicly available genomes from Kribbella strains.

NPASS database update 2023: quantitative natural product activity and species source database for biomedical research

Quantitative activity and species source data of natural products (NPs) are important for drug discovery, medicinal plant research, and microbial investigations. Activity values of NPs against specific targets are useful for discovering targeted therapeutic agents and investigating the mechanism of medicinal plants. Composition/concentration values of NPs in individual species facilitate the assessments and investigations of the therapeutic quality of herbs and phenotypes of microbes. Here, we describe an update of the NPASS natural product activity and species source database previously featured in NAR. This update includes: (i) new data of ∼95 000 records of the composition/concentration values of ∼1 490 NPs/NP clusters in ∼390 species, (ii) extended data of activity values of ∼43 200 NPs against ∼7 700 targets (∼40% and ∼32% increase, respectively), (iii) extended data of ∼31 600 species sources of ∼94 400 NPs (∼26% and ∼32% increase, respectively), (iv) new species types of ∼440 co-cultured microbes and ∼420 engineered microbes, (v) new data of ∼66 600 NPs without experimental activity values but with estimated activity profiles from the established chemical similarity tool Chemical Checker, (vi) new data of the computed drug-likeness properties and the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties for all NPs. NPASS update version is freely accessible at http://bidd.group/NPASS.

Solanimycin: Biosynthesis and Distribution of a New Antifungal Antibiotic Regulated by Two Quorum-Sensing Systems

The increasing emergence of drug-resistant fungal infections has necessitated a search for new compounds capable of combating fungal pathogens of plants, animals, and humans. Microorganisms represent the main source of antibiotics with applicability in agriculture and in the clinic, but many aspects of their metabolic potential remain to be explored. This report describes the discovery and characterization of a new antifungal compound, solanimycin, produced by a hybrid polyketide/nonribosomal peptide (PKS/NRPS) system in Dickeya solani, the enterobacterial pathogen of potato. Solanimycin was active against a broad range of plant-pathogenic fungi of global economic concern and the human pathogen Candida albicans. The genomic cluster responsible for solanimycin production was defined and analyzed to identify the corresponding biosynthetic proteins, which include four multimodular PKS/NRPS proteins and several tailoring enzymes. Antifungal production in D. solani was enhanced in response to experimental conditions found in infected potato tubers and high-density fungal cultures. Solanimycin biosynthesis was cell density dependent in D. solani and was controlled by both the ExpIR acyl-homoserine lactone and Vfm quorum-sensing systems of the bacterial phytopathogen. The expression of the solanimycin cluster was also regulated at the post-transcriptional level, with the regulator RsmA playing a major role. The solanimycin biosynthetic cluster was conserved across phylogenetically distant bacterial genera, and multiple pieces of evidence support that the corresponding gene clusters were acquired by horizontal gene transfer. Given its potent broad-range antifungal properties, this study suggests that solanimycin and related molecules may have potential utility for agricultural and clinical exploitation. IMPORTANCE Fungal infections represent a major clinical, agricultural, and food security threat worldwide, which is accentuated due to the difficult treatment of these infections. Microorganisms represent a prolific source of antibiotics, and current data support that this enormous biosynthetic potential has been scarcely explored. To improve the performance in the discovery of novel antimicrobials, there is a need to diversify the isolation niches for new antibiotic-producing microorganisms as well as to scrutinize novel phylogenetic positions. With the identification of the antifungal antibiotic solanimycin in a broad diversity of phytopathogenic Dickeya spp., we provide further support for the potential of plant-associated bacteria for the biosynthesis of novel antimicrobials. The complex regulatory networks involved in solanimycin production reflect the high metabolic cost of bacterial secondary metabolism. This metabolic regulatory control makes many antibiotics cryptic under standard laboratory conditions, and mimicking environmental conditions, as shown here, is a strategy to activate cryptic antibiotic clusters.

Navigating and expanding the roadmap of natural product genome mining tools

Natural products are structurally highly diverse and exhibit a wide array of biological activities. As a result, they serve as an important source of new drug leads. Traditionally, natural products have been discovered by bioactivity-guided fractionation. The advent of genome sequencing technology has resulted in the introduction of an alternative approach towards novel natural product scaffolds: Genome mining. Genome mining is an in-silico natural product discovery strategy in which sequenced genomes are analyzed for the potential of the associated organism to produce natural products. Seemingly universal biosynthetic principles have been deciphered for most natural product classes that are used to detect natural product biosynthetic gene clusters using pathway-encoded conserved key enzymes, domains, or motifs as bait. Several generations of highly sophisticated tools have been developed for the biosynthetic rule-based identification of natural product gene clusters. Apart from these hard-coded algorithms, multiple tools that use machine learning-based approaches have been designed to complement the existing genome mining tool set and focus on natural product gene clusters that lack genes with conserved signature sequences. In this perspective, we take a closer look at state-of-the-art genome mining tools that are based on either hard-coded rules or machine learning algorithms, with an emphasis on the confidence of their predictions and potential to identify non-canonical natural product biosynthetic gene clusters. We highlight the genome mining pipelines' current strengths and limitations by contrasting their advantages and disadvantages. Moreover, we introduce two indirect biosynthetic gene cluster identification strategies that complement current workflows. The combination of all genome mining approaches will pave the way towards a more comprehensive understanding of the full biosynthetic repertoire encoded in microbial genome sequences.

Mining and characterization of the PKS-NRPS hybrid for epicoccamide A: a mannosylated tetramate derivative from Epicoccum sp. CPCC 400996

BACKGROUND

Genomic analysis indicated that the genomes of ascomycetes might carry dozens of biosynthetic gene clusters (BGCs), yet many clusters have remained enigmatic. The ascomycete genus Epicoccum, belonging to the family Didymellaceae, is ubiquitous that colonizes different types of substrates and is associated with phyllosphere or decaying vegetation. Species of this genus are prolific producers of bioactive substances. The epicoccamides, as biosynthetically distinct mannosylated tetramate, were first isolated in 2003 from Epicoccum sp. In this study, using a combination of genome mining, chemical identification, genetic deletion, and bioinformatic analysis, we identified the required BGC epi responsible for epicoccamide A biosynthesis in Epicoccum sp. CPCC 400996.

RESULTS

The unconventional biosynthetic gene cluster epi was obtained from an endophyte Epicoccum sp. CPCC 400996 through AntiSMASH-based genome mining. The cluster epi includes six putative open reading frames (epiA-epiF) altogether, in which the epiA encodes a tetramate-forming polyketide synthase and nonribosomal peptide synthetases (PKS-NRPS hybrid). Sequence alignments and bioinformatic analysis to other metabolic pathways of fungal tetramates, we proposed that the gene cluster epi could be involved in generating epicoccamides. Genetic knockout of epiA completely abolished the biosynthesis of epicoccamide A (1), thereby establishing the correlation between the BGC epi and biosynthesis of epicoccamide A. Bioinformatic adenylation domain signature analysis of EpiA and other fungal PKS-NRPSs (NRPs) indicated that the EpiA is L-alanine incorporating tetramates megasynthase. Furthermore, based on the molecular structures of epicoccamide A and deduced gene functions of the cluster epi, a hypothetic metabolic pathway for biosynthesizing compound 1 was proposed. The corresponding tetramates releasing during epicoccamide A biosynthesis was catalyzed through Dieckmann-type cyclization, in which the reductive (R) domain residing in terminal module of EpiA accomplished the conversion. These results unveiled the underlying mechanism of epicoccamides biosynthesis and these findings might provide opportunities for derivatization of epicoccamides or generation of new chemical entities.

CONCLUSION

Genome mining and genetic inactivation experiments unveiled a previously uncharacterized PKS - NRPS hybrid-based BGC epi responsible for the generation of epicoccamide A (1) in endophyte Epicoccum sp. CPCC 400996. In addition, based on the gene cluster data, a hypothetical biosynthetic pathway of epicoccamide A was proposed.

Bioinspired Total Synthesis of Pyritide A2 through Pyridine Ring Synthesis

Pyritides belong to the ribosomally synthesized and post-translationally modified peptide class of natural products that were recently genome-predicted and are structurally defined by unique pyridine-containing macrocycles. Inspired by their biosynthesis, proceeding through peptide modification and cycloaddition to form the heterocyclic core, we report the chemical synthesis of pyritide A2 involving pyridine ring synthesis from an amino acid precursor through aza-Diels-Alder reaction. This strategy permitted the preparation of the decorated pyridine core with an appended amino acid residue in two steps from a commercially available arginine derivative and secured pyritide A2 in ten steps. Moreover, the synthetic logic enables efficient preparation of different pyridine subunits associated with pyritides, allowing rapid and convergent access to this new class of natural products and analogues thereof.

Inventa: A computational tool to discover structural novelty in natural extracts libraries

Collections of natural extracts hold potential for the discovery of novel natural products with original modes of action. The prioritization of extracts from collections remains challenging due to the lack of a workflow that combines multiple-source information to facilitate the data interpretation. Results from different analytical techniques and literature reports need to be organized, processed, and interpreted to enable optimal decision-making for extracts prioritization. Here, we introduce Inventa, a computational tool that highlights the structural novelty potential within extracts, considering untargeted mass spectrometry data, spectral annotation, and literature reports. Based on this information, Inventa calculates multiple scores that inform their structural potential. Thus, Inventa has the potential to accelerate new natural products discovery. Inventa was applied to a set of plants from the Celastraceae family as a proof of concept. The Pristimera indica (Willd.) A.C.Sm roots extract was highlighted as a promising source of potentially novel compounds. Its phytochemical investigation resulted in the isolation and de novo characterization of thirteen new dihydro-β-agarofuran sesquiterpenes, five of them presenting a new 9-oxodihydro-β-agarofuran base scaffold.

A roadmap to understanding diversity and function of coral reef-associated fungi

Tropical coral reefs are hotspots of marine productivity, owing to the association of reef-building corals with endosymbiotic algae and metabolically diverse bacterial communities. However, the functional importance of fungi, well-known for their contribution to shaping terrestrial ecosystems and global nutrient cycles, remains underexplored on coral reefs. We here conceptualize how fungal functional traits may have facilitated the spread, diversification, and ecological adaptation of marine fungi on coral reefs. We propose that functions of reef-associated fungi may be diverse and go beyond their hitherto described roles of pathogens and bioeroders, including but not limited to reef-scale biogeochemical cycles and the structuring of coral-associated and environmental microbiomes via chemical mediation. Recent technological and conceptual advances will allow the elucidation of the physiological, ecological, and chemical contributions of understudied marine fungi to coral holobiont and reef ecosystem functioning and health and may help provide an outlook for reef management actions.

Ulleungdolin, a Polyketide-Peptide Hybrid Bearing a 2,4-Di-O-methyl-β-d-antiarose from Streptomyces sp. 13F051 Co-cultured with Leohumicola minima 15S071

A new secondary metabolite, ulleungdolin (1), was isolated from the co-culture of an actinomycete, Streptomyces sp. 13F051, and a fungus, Leohumicola minima 15S071. Based on the NMR, UV, and MS data, it was deduced that the planar structure of 1 comprised an isoindolinone (IsoID) with an octanoic acid, a tripeptide, and a sugar. The tripeptide has the unprecedented amino acids norcoronamic acid, 3-hydroxy-glutamine, and 4-hydroxy-phenylglycine and is linked by a C-N bond with IsoID. The absolute configurations were determined by chemical derivatization, extensive spectroscopic methods, and electronic circular dichroism calculations and supported by bioinformatic analyses. Bioactivity evaluation studies indicated that 1 had an antimigration effect on MDA-MB-231 breast cancer cells.

Genome mining of Fusarium reveals structural and functional diversity of pectin lyases: a bioinformatics approach

Pectin lyase (PNL) is an important enzyme of the pectinases group which degrades pectin polymer to 4,5-unsaturated oligogalacturonides by a unique β-elimination mechanism and is used in several industries. The existence of multigene families of pectin lyases has been investigated by mining microbial genomes. In the present study, 52 pectin lyase genes were predicted from sequenced six species of Fusarium, namely F. fujikuroi, F. graminearum, F. proliferatum, F. oxysporum, F. verticillioides and F. virguliforme. These sequences were in silico characterized for several physico-chemical, structural and functional attributes. The translated PNL proteins showed variability with 344-1142 amino acid residues, 35.44-127.41 kDa molecular weight, and pI ranging from 4.63 to 9.28. The aliphatic index ranged from 75.33 to 84.75. Multiple sequence alignment analysis showed several conserved amino acid residues and five distinct groups marked as I, II, III, IV, and V were observed in the phylogenetic tree. The Three-dimensional Structure of five of these PNLs, each representing a distinct group of phylogenetic trees was predicted using I-TASSER Server and validated. The pectin lyase proteins of Fusarium species revealed close similarity with pectin lyase of Aspergillus niger PelA(1IDJ) and PelB(1QCX). Diversity in the structural motifs was observed among Fusarium species with 2 β-sheets, 1 β-hairpin, 7-12 β bulges, 18-25 strands, 6 -11 helices, 1 helix-helix interaction, 32-49 β turns, 2-6 γ turns and 2- 3 disulfide bonds. The unique Pec_lyase domain was uniformly observed among all PNL proteins confirming its identity. The genome-wide mining of Fusarium species was attempted to provide the diversity of PNL genes, which could be explored for diverse applications after performing cloning and expression studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03333-w.

Marine Bacterial Ribosomal Peptides: Recent Genomics- and Synthetic Biology-Based Discoveries and Biosynthetic Studies

Marine biodiversity is represented by an exceptional and ample array of intriguing natural product chemistries. Due to their extensive post-translational modifications, ribosomal peptides—also known as ribosomally synthesized and post-translationally modified peptides (RiPPs)—exemplify a widely diverse class of natural products, endowing a broad range of pharmaceutically and biotechnologically relevant properties for therapeutic or industrial applications. Most RiPPs are of bacterial origin, yet their marine derivatives have been quite rarely investigated. Given the rapid advancement engaged in a more powerful genomics approach, more biosynthetic gene clusters and pathways for these ribosomal peptides continue to be increasingly characterized. Moreover, the genome-mining approach in integration with synthetic biology techniques has markedly led to a revolution of RiPP natural product discovery. Therefore, this present short review article focuses on the recent discovery of RiPPs from marine bacteria based on genome mining and synthetic biology approaches during the past decade. Their biosynthetic studies are discussed herein, particularly the organization of targeted biosynthetic gene clusters linked to the encoded RiPPs with potential bioactivities.

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.

Single cell mutant selection for metabolic engineering of actinomycetes

Actinomycetes are important producers of pharmaceuticals and industrial enzymes. However, wild type strains require laborious development prior to industrial usage. Here we present a generally applicable reporter-guided metabolic engineering tool based on random mutagenesis, selective pressure, and single-cell sorting. We developed fluorescence-activated cell sorting (FACS) methodology capable of reproducibly identifying high-performing individual cells from a mutant population directly from liquid cultures. Actinomycetes are an important source of catabolic enzymes, where product yields determine industrial viability. We demonstrate 5-fold yield improvement with an industrial cholesterol oxidase ChoD producer Streptomyces lavendulae to 20.4 U g^-1 in three rounds. Strain development is traditionally followed by production medium optimization, which is a time-consuming multi-parameter problem that may require hard to source ingredients. Ultra-high throughput screening allowed us to circumvent medium optimization and we identified high ChoD yield production strains directly from mutant libraries grown under preset culture conditions. Genome-mining based drug discovery is a promising source of bioactive compounds, which is complicated by the observation that target metabolic pathways may be silent under laboratory conditions. We demonstrate our technology for drug discovery by activating a silent mutaxanthene metabolic pathway in Amycolatopsis. We apply the method for industrial strain development and increase mutaxanthene yields 9-fold to 99 mg l^-1 in a second round of mutant selection. In summary, the ability to screen tens of millions of mutants in a single cell format offers broad applicability for metabolic engineering of actinomycetes for activation of silent metabolic pathways and to increase yields of proteins and natural products.

Biosynthetic potential of the global ocean microbiome

Natural microbial communities are phylogenetically and metabolically diverse. In addition to underexplored organismal groups¹, this diversity encompasses a rich discovery potential for ecologically and biotechnologically relevant enzymes and biochemical compounds^2,3. However, studying this diversity to identify genomic pathways for the synthesis of such compounds⁴ and assigning them to their respective hosts remains challenging. The biosynthetic potential of microorganisms in the open ocean remains largely uncharted owing to limitations in the analysis of genome-resolved data at the global scale. Here we investigated the diversity and novelty of biosynthetic gene clusters in the ocean by integrating around 10,000 microbial genomes from cultivated and single cells with more than 25,000 newly reconstructed draft genomes from more than 1,000 seawater samples. These efforts revealed approximately 40,000 putative mostly new biosynthetic gene clusters, several of which were found in previously unsuspected phylogenetic groups. Among these groups, we identified a lineage rich in biosynthetic gene clusters (‘Candidatus Eudoremicrobiaceae’) that belongs to an uncultivated bacterial phylum and includes some of the most biosynthetically diverse microorganisms in this environment. From these, we characterized the phospeptin and pythonamide pathways, revealing cases of unusual bioactive compound structure and enzymology, respectively. Together, this research demonstrates how microbiomics-driven strategies can enable the investigation of previously undescribed enzymes and natural products in underexplored microbial groups and environments.

Global ocean microbiome survey reveals the bacterial family ‘Candidatus Eudoremicrobiaceae’, which includes some of the most biosynthetically diverse microorganisms in the ocean environment.

Towards a Better Understanding of Toxin Biosynthesis in Seaweeds

Harmful algal blooms (HABs) represent both ecological and public health hazards in the marine environment. Indeed, some algae can produce metabolites that have negative effects on marine ecosystems and mammals. Kainoid derivatives such as kainic acid (KA) and domoic acid (DA) are considered some of the most toxic metabolites of marine origin biosynthesized by a limited number of micro- and macroalgae. While recent works have provided the first insights into the biosynthetic route of KA in red algae and DA in diatoms, the DA biosynthetic pathway has remained uncharacterized for red algae. In a recent work, the research groups of Chekan and Moore have not only elucidated the biosynthetic pathway of DA in the red alga Chondria armata but also shed light on its complex evolution among marine species. We discuss here the importance of pursuing active research in this area to gain insights into secondary biosynthetic pathways in marine organisms for diagnostic and metabolic engineering perspectives.

Allopeptimicins: unique antibacterial metabolites generated by hybrid PKS-NRPS, with original self-defense mechanism in Actinoallomurus

In the search for structurally novel metabolites with antibacterial activity, innovative approaches must be implemented to increase the probability of discovering novel chemistry from microbial sources. Here we report on the application of metabolomic tools to the genus Actinoallomurus, a poorly explored member of the Actinobacteria. From examining extracts derived from 88 isolates belonging to this genus, we identified a family of cyclodepsipeptides acylated with a C20 polyketide chain, which we named allopeptimicins. These molecules possess unusual structural features, including several double bonds in the amino-polyketide chain and four non-proteinogenic amino acids in the octapeptide. Remarkably, allopeptimicins are produced as a complex of active and inactive congeners, the latter carrying a sulfate group on the polyketide amine. This modification is also a mechanism of self-protection in the producer strain. The structural uniqueness of allopeptimicins is reflected in a biosynthetic gene cluster showing a mosaic structure, with dedicated gene cassettes devoted to formation of specialized precursors and modular assembly lines related to those from different pathways.

A Putative Effector LtCSEP1 from Lasiodiplodia theobromae Inhibits BAX-Triggered Cell Death and Suppresses Immunity Responses in Nicotiana benthamiana

Lasiodiplodia theobromae is a causal agent of grapevine trunk disease, and it poses a significant threat to the grape industry worldwide. Fungal effectors play an essential role in the interaction between plants and pathogens. However, few studies have been conducted to understand the functions of individual effectors in L. theobromae. In this study, we identified and characterized a candidate secreted effector protein, LtCSEP1, in L. theobromae. Gene expression analysis suggested that transcription of LtCSEP1 in L. theobromae was induced at the early infection stages in the grapevine. Yeast secretion assay revealed that LtCSEP1 contains a functional signal peptide. Transient expression of LtCSEP1 in Nicotiana benthamiana suppresses BAX-trigged cell death and significantly inhibits the flg22-induced PTI-associated gene expression. Furthermore, the ectopic expression of LtCSEP1 in N. benthamiana enhanced disease susceptibility to L. theobromae by downregulating the defense-related genes. These results demonstrated that LtCSEP1 is a potential effector of L. theobromae, which contributes to suppressing the plant’s defenses.

Ancient plant-like terpene biosynthesis in corals

Octocorals are major contributors of terpenoid chemical diversity in the ocean. Natural products from other sessile marine animals are primarily biosynthesized by symbiotic microbes rather than by the host. Here, we challenge this long-standing paradigm by describing a monophyletic lineage of animal-encoded terpene cyclases (TCs) ubiquitous in octocorals. We characterized 15 TC enzymes from nine genera, several of which produce precursors of iconic coral-specific terpenoids, such as pseudopterosin, lophotoxin and eleutherobin. X-ray crystallography revealed that coral TCs share conserved active site residues and structural features with bacterial TCs. The identification of coral TCs enabled the targeted identification of the enzyme that constructs the coral-exclusive capnellane scaffold. Several TC genes are colocalized with genes that encode enzymes known to modify terpenes. This work presents an example of biosynthetic capacity in the kingdom Animalia that rivals the chemical complexity generated by plants, unlocking the biotechnological potential of octocorals for biomedical applications.

Secondary Metabolite Transcriptomic Pipeline (SeMa-Trap), an expression-based exploration tool for increased secondary metabolite production in bacteria

For decades, natural products have been used as a primary resource in drug discovery pipelines to find new antibiotics, which are mainly produced as secondary metabolites by bacteria. The biosynthesis of these compounds is encoded in co-localized genes termed biosynthetic gene clusters (BGCs). However, BGCs are often not expressed under laboratory conditions. Several genetic manipulation strategies have been developed in order to activate or overexpress silent BGCs. Significant increases in production levels of secondary metabolites were indeed achieved by modifying the expression of genes encoding regulators and transporters, as well as genes involved in resistance or precursor biosynthesis. However, the abundance of genes encoding such functions within bacterial genomes requires prioritization of the most promising ones for genetic manipulation strategies. Here, we introduce the ‘Secondary Metabolite Transcriptomic Pipeline’ (SeMa-Trap), a user-friendly web-server, available at https://sema-trap.ziemertlab.com. SeMa-Trap facilitates RNA-Seq based transcriptome analyses, finds co-expression patterns between certain genes and BGCs of interest, and helps optimize the design of comparative transcriptomic analyses. Finally, SeMa-Trap provides interactive result pages for each BGC, allowing the easy exploration and comparison of expression patterns. In summary, SeMa-Trap allows a straightforward prioritization of genes that could be targeted via genetic engineering approaches to (over)express BGCs of interest.

Widely Distributed Bifunctional Bacterial Cytochrome P450 Enzymes Catalyze both Intramolecular C-C Bond Formation in cyclo-l-Tyr-l-Tyr and Its Coupling with Nucleobases

Tailoring enzymes are important modification biocatalysts in natural product biosynthesis. We report herein six orthologous two‐gene clusters for mycocyclosin and guatyromycine biosynthesis. Expression of the cyclodipeptide synthase genes gymA₁–gymA₆ in Escherichia coli resulted in the formation of cyclo‐l‐Tyr‐l‐Tyr as the major product. Reconstruction of the biosynthetic pathways in Streptomyces albus and biochemical investigation proved that the cytochrome P450 enzymes GymB₁–GymB₆ act as both intramolecular oxidases and intermolecular nucleobase transferases. They catalyze not only the oxidative C−C coupling within cyclo‐l‐Tyr‐l‐Tyr, leading to mycocyclosin, but also its connection with guanine and hypoxanthine, and are thus responsible for the formation of tyrosine‐containing guatyromycines, instead of the reported tryptophan‐nucleobase adducts. Phylogenetic data suggest the presence of at least 47 GymB orthologues, indicating the occurrence of a widely distributed enzyme class.

Biosynthesis of Xylariolide D in Penicillium crustosum Implies a Chain Branching Reaction Catalyzed by a Highly Reducing Polyketide Synthase

Fungi are important sources for the discovery of natural products. During the last decades, technological progress and the increasing number of sequenced genomes facilitated the exploration of new secondary metabolites. Among those, polyketides represent a structurally diverse group with manifold biological activities. In this study, we successfully used genome mining and genetic manipulation for functional proof of a polyketide biosynthetic gene cluster from the filamentous fungus Penicillium crustosum. Gene activation in the native host and heterologous expression in Aspergillus nidulans led to the identification of the xil cluster, being responsible for the formation of the 6-methyl-2-pyrone derivative xylariolide D. Feeding with ¹³C-labeled precursors supported the hypothesis of chain branching during the backbone formation catalyzed by a highly reducing fungal polyketide synthase. A cytochrome P450-catalyzed hydroxylation converts the PKS product to the final metabolite. This proved that just two enzymes are required for the biosynthesis of xylariolide D.

Compendium of specialized metabolite biosynthetic diversity encoded in bacterial genomes

Bacterial specialized metabolites are a proven source of antibiotics and cancer therapies, but whether we have sampled all the secondary metabolite chemical diversity of cultivated bacteria is not known. We analysed ~170,000 bacterial genomes and ~47,000 metagenome assembled genomes (MAGs) using a modified BiG-SLiCE and the new clust-o-matic algorithm. We estimate that only 3% of the natural products potentially encoded in bacterial genomes have been experimentally characterized. We show that the variation in secondary metabolite biosynthetic diversity drops significantly at the genus level, identifying it as an appropriate taxonomic rank for comparison. Equal comparison of genera based on relative evolutionary distance revealed that Streptomyces bacteria encode the largest biosynthetic diversity by far, with Amycolatopsis, Kutzneria and Micromonospora also encoding substantial diversity. Finally, we find that several less-well-studied taxa, such as Weeksellaceae (Bacteroidota), Myxococcaceae (Myxococcota), Pleurocapsa and Nostocaceae (Cyanobacteria), have potential to produce highly diverse sets of secondary metabolites that warrant further investigation.

Signaling repurposable drug combinations against COVID-19 by developing the heterogeneous deep herb-graph method

BACKGROUND

Coronavirus disease 2019 (COVID-19) has spurred a boom in uncovering repurposable existing drugs. Drug repurposing is a strategy for identifying new uses for approved or investigational drugs that are outside the scope of the original medical indication.

MOTIVATION

Current works of drug repurposing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are mostly limited to only focusing on chemical medicines, analysis of single drug targeting single SARS-CoV-2 protein, one-size-fits-all strategy using the same treatment (same drug) for different infected stages of SARS-CoV-2. To dilute these issues, we initially set the research focusing on herbal medicines. We then proposed a heterogeneous graph embedding method to signaled candidate repurposing herbs for each SARS-CoV-2 protein, and employed the variational graph convolutional network approach to recommend the precision herb combinations as the potential candidate treatments against the specific infected stage.

METHOD

We initially employed the virtual screening method to construct the 'Herb-Compound' and 'Compound-Protein' docking graph based on 480 herbal medicines, 12,735 associated chemical compounds and 24 SARS-CoV-2 proteins. Sequentially, the 'Herb-Compound-Protein' heterogeneous network was constructed by means of the metapath-based embedding approach. We then proposed the heterogeneous-information-network-based graph embedding method to generate the candidate ranking lists of herbs that target structural, nonstructural and accessory SARS-CoV-2 proteins, individually. To obtain precision synthetic effective treatments forvarious COVID-19 infected stages, we employed the variational graph convolutional network method to generate candidate herb combinations as the recommended therapeutic therapies.

RESULTS

There were 24 ranking lists, each containing top-10 herbs, targeting 24 SARS-CoV-2 proteins correspondingly, and 20 herb combinations were generated as the candidate-specific treatment to target the four infected stages. The code and supplementary materials are freely available at https://github.com/fanyang-AI/TCM-COVID19.

Comprehensive Genomic Analysis of Marine Strain Streptomyces sp. 891, an Excellent Producer of Chrysomycin A with Therapeutic Potential

Chrysomycin A is one of the most promising therapeutic candidates for treating infections caused by multidrug-resistant Gram-positive bacteria. By hybridizing next-step generation (Illumina) and third-generation (PacBio) sequencing technologies, a high-quality chromosome-level genome together with a plasmid was firstly assembled for chrysomycin A-producing marine strain 891. Phylogenetic analysis of the 16S rRNA gene and genome sequences revealed that this strain unambiguously belonged to the genus Streptomyces, and its genomic features and functional genes were comprehensively analyzed and annotated. AntiSMASH analysis of this strain unveiled one key biosynthetic gene cluster, T2PKS, responsible for the biosynthesis of chrysomycin, the biosynthesis pathway of which was putatively proposed. These findings definitely shed light on further investigation for construction of a robust industrial strain with high-yield chrysomycin A production using genetic engineering techniques and combinatorial biology approaches.

Marine Demospongiae: A Challenging Treasure of Bioactive Compounds

In the last decades, it has been demonstrated that marine organisms are a substantial source of bioactive compounds with possible biotechnological applications. Marine sponges, in particular those belonging to the class of Demospongiae, have been considered among the most interesting invertebrates for their biotechnological potential. In this review, particular attention is devoted to natural compounds/extracts isolated from Demospongiae and their associated microorganisms with important biological activities for pharmacological applications such as antiviral, anticancer, antifouling, antimicrobial, antiplasmodial, antifungal and antioxidant. The data here presented show that this class of sponges is an exciting source of compounds, which are worth developing into new drugs, such as avarol, a hydroquinone isolated from the marine sponge Disidea avara, which is used as an antitumor, antimicrobial and antiviral drug.

Harnessing ortho-Quinone Methides in Natural Product Biosynthesis and Biocatalysis

The implementation of ortho-quinone methide (o-QM) intermediates in complex molecule assembly represents a remarkably efficient strategy designed by Nature and utilized by synthetic chemists. o-QMs have been taken advantage of in biomimetic syntheses for decades, yet relatively few examples of o-QM-generating enzymes in natural product biosynthetic pathways have been reported. The biosynthetic enzymes that have been discovered thus far exhibit tremendous potential for biocatalytic applications, enabling the selective production of desirable compounds that are otherwise intractable or inherently difficult to achieve by traditional synthetic methods. Characterization of this biosynthetic machinery has the potential to shine a light on new enzymes capable of similar chemistry on diverse substrates, thus expanding our knowledge of Nature's catalytic repertoire. The presently known o-QM-generating enzymes include flavin-dependent oxidases, hetero-Diels-Alderases, S-adenosyl-l-methionine-dependent pericyclases, and α-ketoglutarate-dependent nonheme iron enzymes. In this review, we discuss their diverse enzymatic mechanisms and potential as biocatalysts in constructing natural product molecules such as cannabinoids.

MGF6mARice: prediction of DNA N6-methyladenine sites in rice by exploiting molecular graph feature and residual block

DNA N6-methyladenine (6mA) is produced by the N6 position of the adenine being methylated, which occurs at the molecular level, and is involved in numerous vital biological processes in the rice genome. Given the shortcomings of biological experiments, researchers have developed many computational methods to predict 6mA sites and achieved good performance. However, the existing methods do not consider the occurrence mechanism of 6mA to extract features from the molecular structure. In this paper, a novel deep learning method is proposed by devising DNA molecular graph feature and residual block structure for 6mA sites prediction in rice, named MGF6mARice. Firstly, the DNA sequence is changed into a simplified molecular input line entry system (SMILES) format, which reflects chemical molecular structure. Secondly, for the molecular structure data, we construct the DNA molecular graph feature based on the principle of graph convolutional network. Then, the residual block is designed to extract higher level, distinguishable features from molecular graph features. Finally, the prediction module is used to obtain the result of whether it is a 6mA site. By means of 10-fold cross-validation, MGF6mARice outperforms the state-of-the-art approaches. Multiple experiments have shown that the molecular graph feature and residual block can promote the performance of MGF6mARice in 6mA prediction. To the best of our knowledge, it is the first time to derive a feature of DNA sequence by considering the chemical molecular structure. We hope that MGF6mARice will be helpful for researchers to analyze 6mA sites in rice.

Unlocking plant metabolic diversity: A (pan)-genomic view

Plants produce a remarkable diversity of structurally and functionally diverse natural chemicals that serve as adaptive compounds throughout their life cycles. However, unlocking this metabolic diversity is significantly impeded by the size, complexity, and abundant repetitive elements of typical plant genomes. As genome sequencing becomes routine, we anticipate that links between metabolic diversity and genetic variation will be strengthened. In addition, an ever-increasing number of plant genomes have revealed that biosynthetic gene clusters are not only a hallmark of microbes and fungi; gene clusters for various classes of compounds have also been found in plants, and many are associated with important agronomic traits. We present recent examples of plant metabolic diversification that have been discovered through the exploration and exploitation of various genomic and pan-genomic data. We also draw attention to the fundamental genomic and pan-genomic basis of plant chemodiversity and discuss challenges and future perspectives for investigating metabolic diversity in the coming pan-genomics era.

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.

The Studies in Constructing Yeast Cell Factories for the Production of Fatty Acid Alkyl Esters

Fatty acid alkyl esters have broad applications in biofuels, lubricant formulas, paints, coatings, and cosmetics. Traditionally, these esters are mostly produced through unsustainable and energy-intensive processes. In contrast, microbial production of esters from renewable and sustainable feedstocks may provide a promising alternative and has attracted widespread attention in recent years. At present, yeasts are used as ideal hosts for producing such esters, due to their availability for high-density fermentation, resistance to phage infection, and tolerance against toxic inhibitors. Here, we summarize recent development on the biosynthesis of alkyl esters, including fatty acid ethyl esters (FAEEs), fatty acid short-branched chain alkyl esters (FASBEs), and wax esters (WEs) by various yeast cell factories. We focus mainly on the enzyme engineering strategies of critical wax ester synthases, and the pathway engineering strategies employed for the biosynthesis of various ester products. The bottlenecks that limit productivity and their potential solutions are also discussed in this review.

Strategies for Improving Small-Molecule Biosensors in Bacteria

In recent years, small-molecule biosensors have become increasingly important in synthetic biology and biochemistry, with numerous new applications continuing to be developed throughout the field. For many biosensors, however, their utility is hindered by poor functionality. Here, we review the known types of mechanisms of biosensors within bacterial cells, and the types of approaches for optimizing different biosensor functional parameters. Discussed approaches for improving biosensor functionality include methods of directly engineering biosensor genes, considerations for choosing genetic reporters, approaches for tuning gene expression, and strategies for incorporating additional genetic modules.

Electrochemistry for the Chemoselective Modification of Peptides and Proteins

Although electrochemical strategies for small-molecule synthesis are flourishing, this technology has yet to be fully exploited for the mild and chemoselective modification of peptides and proteins. With the growing number of diverse peptide natural products being identified and the emergence of modified proteins as therapeutic and diagnostic agents, methods for electrochemical modification stand as alluring prospects for harnessing the reactivity of polypeptides to build molecular complexity. As a mild and inherently tunable reaction platform, electrochemistry is arguably well-suited to overcome the chemo- and regioselectivity issues which limit existing bioconjugation strategies. This Perspective will showcase recently developed electrochemical approaches to peptide and protein modification. The article also highlights the wealth of untapped opportunities for the production of homogeneously modified biomolecules, with an eye toward realizing the enormous potential of electrochemistry for chemoselective bioconjugation chemistry.

Antimicrobial resistance: progress and challenges in antibiotic discovery and anti-infective therapy

The alarming rise in the emergence of antimicrobial resistance in human, animal and plant pathogens is challenging global health and food production. Traditional strategies used for antibiotic discovery persistently result in the re-isolation of known compounds, calling for the need to develop more rational strategies to identify new antibiotics. Additionally, anti-infective therapy approaches targeting bacterial signalling pathways related to virulence is emerging as an alternative to the use of antibiotics. In this perspective article, we critically analyse approaches aimed at revitalizing the identification of new antibiotics and to advance antivirulence therapies. The development of high-throughput in vivo, in vitro and in silico platforms, together with the progress in chemical synthesis, analytical chemistry and structural biology, are reviving a research area that is of tremendous relevance for global health.

In vivo, in vitro and in silico: an open space for the development of microbe-based applications of synthetic biology

Living systems are studied using three complementary approaches: living cells, cell-free systems and computer-mediated modelling. Progresses in understanding, allowing researchers to create novel chassis and industrial processes rest on a cycle that combines in vivo, in vitro and in silico studies. This design-build-test-learn iteration loop cycle between experiments and analyses combines together physiology, genetics, biochemistry and bioinformatics in a way that keeps going forward. Because computer-aided approaches are not directly constrained by the material nature of the entities of interest, we illustrate here how this virtuous cycle allows researchers to explore chemistry which is foreign to that present in extant life, from whole chassis to novel metabolic cycles. Particular emphasis is placed on the importance of evolution.

Elucidation of the Streptoazine Biosynthetic Pathway in Streptomyces aurantiacus Reveals the Presence of a Promiscuous Prenyltransferase/Cyclase

Heterologous expression of a three-gene cluster from Streptomyces aurantiacus coding for a cyclodipeptide synthase, a prenyltransferase, and a methyltransferase led to the elucidation of the biosynthetic steps of streptoazine C (2). In vivo biotransformation experiments proved the high flexibility of the prenyltransferase SasB toward tryptophan-containing cyclodipeptides for regular C-3-prenylation. Furthermore, their corresponding dehydrogenated derivatives prepared by using cyclodipeptide oxidases were also used for prenylation. This study provides an enzyme with high substrate promiscuity from a less explored group of prenyltransferases for potential use to generate prenylated derivatives.