Genomic charting of ribosomally synthesized natural product chemical space facilitates targeted mining

Exploring Bioactive Fungal RiPPs: Advances, Challenges, and Future Prospects

Fungal ribosomally synthesized and post-translationally modified peptides (RiPPs) are a vital class of natural products known for their biological activities including anticancer, antitubulin, antinematode, and immunosuppressant properties. These bioactive fungal RiPPs play key roles in chemical ecology and have a significant therapeutic potential. Their structural diversity, which arises from intricate post-translational modifications of precursor peptides, is particularly remarkable. Despite their biological and ecological importance, the discovery of fungal RiPPs has been historically challenging and only a limited number have been identified. To date, known fungal RiPPs are primarily grouped into three groups: cycloamanides and borosins from basidiomycetes and dikaritins from ascomycetes. Recent advancements in bioinformatics have revealed the vast untapped potential of fungi to produce RiPPs, offering new opportunities for their discovery. This review highlights recent progress in fungal RiPP biosynthesis and genome-guided discovery strategies. We propose that combining the knowledge of fungal RiPP biosynthetic pathways with advanced gene-editing technologies and bioinformatic tools will significantly accelerate the discovery of novel bioactive fungal RiPPs.

GLYCOCINS: The sugar peppered antimicrobials

Glycosylated bacteriocins, known as glycocins, were first discovered in 2011. These bioactive peptides are produced by bacteria to gain survival advantages. They exhibit diverse types of glycans and demonstrate varied antimicrobial activity. Currently, there are 13 experimentally known glycocins, with over 250 identified in silico across different bacterial phyla. Notably, glycocins are recognized for their glycan-mediated antimicrobial activity, proving effective against drug-resistant and foodborne pathogens. Many glycocins contain rare S-linked glycans. Glycosyltransferases (GTs), responsible for transferring sugar to glycocins and involved in glycocin biosynthesis, often cluster together in the producer's genome. This clustering makes them valuable for custom glycoengineering with diverse substrate specificities. Heterologous expression of glycocins has paved the way for the establishment of microbial factories for glycopeptide and glycoconjugate production across various industries. In this review, we emphasize the primary roles of fully and partially characterized glycocins and their glycosylating enzymes. Additionally, we explore how specific glycan structures facilitate these functions in antibacterial activities. Furthermore, we discuss newer approaches and increasing efforts aimed at exploiting bacterial glycobiology for the development of food preservatives and as replacements or complements to traditional antibiotics, particularly in the face of antibiotic-resistant pathogenic bacteria.

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

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

Novel types of RiPP-modifying enzymes

Novel discoveries in natural product biosynthesis reveal hidden bioactive compounds and expand our knowledge in enzymology. Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a rapidly growing class of natural products featuring diverse non-canonical amino acids introduced by maturation enzymes as a class-defining characteristic. Underexplored RiPP sources, such as the human microbiome, the oceans, uncultured microorganisms, and plants are rich hunting grounds for novel enzymology. Unusual α- and β-amino acids, peptide cleavages, lipidations, diverse macrocyclizations, and other features expand the range of chemical groups that are installed in RiPPs by often promiscuous enzymes. This review highlights the search for novelty in RiPP enzymology in the past two years, with respect to the discovery of new biochemical modifications but also towards novel applications.

Exploring the roles of ribosomal peptides in prokaryote-phage interactions through deep learning-enabled metagenome mining

BACKGROUND

Microbial secondary metabolites play a crucial role in the intricate interactions within the natural environment. Among these metabolites, ribosomally synthesized and post-translationally modified peptides (RiPPs) are becoming a promising source of therapeutic agents due to their structural diversity and functional versatility. However, their biosynthetic capacity and ecological functions remain largely underexplored.

RESULTS

Here, we aim to explore the biosynthetic profile of RiPPs and their potential roles in the interactions between microbes and viruses in the ocean, which encompasses a vast diversity of unique biomes that are rich in interactions and remains chemically underexplored. We first developed TrRiPP to identify RiPPs from ocean metagenomes, a deep learning method that detects RiPP precursors in a hallmark gene-independent manner to overcome the limitations of classic methods in processing highly fragmented metagenomic data. Applying this method to metagenomes from the global ocean microbiome, we uncover a diverse array of previously uncharacterized putative RiPP families with great novelty and diversity. Through correlation analysis based on metatranscriptomic data, we observed a high prevalence of antiphage defense-related and phage-related protein families that were co-expressed with RiPP families. Based on this putative association between RiPPs and phage infection, we constructed an Ocean Virus Database (OVD) and established a RiPP-involving host-phage interaction network through host prediction and co-expression analysis, revealing complex connectivities linking RiPP-encoding prokaryotes, RiPP families, viral protein families, and phages. These findings highlight the potential of RiPP families involved in prokaryote-phage interactions and coevolution, providing insights into their ecological functions in the ocean microbiome.

CONCLUSIONS

This study provides a systematic investigation of the biosynthetic potential of RiPPs from the ocean microbiome at a global scale, shedding light on the essential insights into the ecological functions of RiPPs in prokaryote-phage interactions through the integration of deep learning approaches, metatranscriptomic data, and host-phage connectivity. This study serves as a valuable example of exploring the ecological functions of bacterial secondary metabolites, particularly their associations with unexplored microbial interactions. Video Abstract.

In Silico Screening of Bacteriocin Gene Clusters within a Set of Marine Bacillota Genomes

Due to their potential application as an alternative to antibiotics, bacteriocins, which are ribosomally synthesized antimicrobial peptides produced by bacteria, have received much attention in recent years. To identify bacteriocins within marine bacteria, most of the studies employed a culture-based method, which is more time-consuming than the in silico approach. For that, the aim of this study was to identify potential bacteriocin gene clusters and their potential producers in 51 marine Bacillota (formerly Firmicutes) genomes, using BAGEL4, a bacteriocin genome mining tool. As a result, we found out that a majority of selected Bacillota (60.78%) are potential bacteriocin producers, and we identified 77 bacteriocin gene clusters, most of which belong to class I bacteriocins known as RiPPs (ribosomally synthesized and post-translationally modified peptides). The identified putative bacteriocin gene clusters are an attractive target for further in vitro research, such as the production of bacteriocins using a heterologous expression system.

Cytochromes P450 Associated with the Biosyntheses of Ribosomally Synthesized and Post-translationally Modified Peptides

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a class of exponentially increased natural products with characteristic chemical structures, topologies, and biosynthetic mechanisms as well as exceptional bioactivities including antibacteria, antitumors, and antiviruses. The biosynthesis of RiPP proceeds via a ribosomally assembled precursor peptide that undergoes varied post-translational modifications to generate a mature peptide. Cytochrome P450 (CYP or P450) monooxygenases are a superfamily of heme-containing enzymes that span a wide range of secondary metabolite biosynthetic pathways due to their broad substrate scopes and excellent catalytic versatility. In contrast to the enormous quantities of RiPPs and P450s, the P450 associated RiPP biosynthesis is comparatively limited, with most of their functions and timings remaining mysterious. Herein, this Review aims to provide an overview on the striking roles of P450s in RiPP biosyntheses uncovered to date and to illustrate their remarkable functions, mechanisms, as well as remaining challenges. This will shed light on novel P450 discovery and characterizations in RiPP biosyntheses.

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

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

Genome Mining and Discovery of Imiditides, a Family of RiPPs with a Class-Defining Aspartimide Modification

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a large and diverse class of natural products of ribosomal origin. In the past decade, various sophisticated machine-learning-based software packages have been established to discover novel RiPPs that do not resemble the known families. Here, we show that tailoring enzymes that cluster with various RiPP families can serve as effective bioinformatic seeds, providing a complementary approach for novel RiPP discovery. Leveraging the fact that O-methyltransferases homologous to protein isoaspartyl methyltransferases (PIMTs) are associated with lasso peptide, graspetide, and lanthipeptide biosynthetic gene clusters (BGCs), we utilized a C-terminal motif unique to RiPP-associated O-methyltransferases as the search query to discover a novel family of RiPPs, the imiditides. Our genome-mining algorithm reveals a total of 670 imiditide BGCs, distributed across Gram-positive bacterial genomes. In addition, we demonstrate the heterologous production of the founding member of the imiditide family, mNmaAM, encoded in the genome of Nonomuraea maritima. In contrast to other RiPP-associated PIMTs that recognize constrained peptides as substrates, the PIMT homologue in the mNmaAM BGC, NmaM, methylates a specific Asp residue on the linear precursor peptide, NmaA. The methyl ester is then turned into an aspartimide spontaneously. Substrate specificity is achieved by extensive charge-charge interactions between the precursor NmaA and the modifying enzyme NmaM suggested by both experiments and an AlphaFold model prediction. Our study shows that PIMT-mediated aspartimide formation is an emerging backbone modification strategy in the biosynthesis of multiple RiPP families.

Structure of lasso peptide epimerase MslH reveals metal-dependent acid/base catalytic mechanism

The lasso peptide MS-271 is a ribosomally synthesized and post-translationally modified peptide (RiPP) consisting of 21 amino acids with D-tryptophan at the C-terminus, and is derived from the precursor peptide MslA. MslH, encoded in the MS-271 biosynthetic gene cluster (msl), catalyzes the epimerization at the Cα center of the MslA C-terminal Trp21, leading to epi-MslA. The detailed catalytic process, including the catalytic site and cofactors, has remained enigmatic. Herein, based on X-ray crystallographic studies in association with MslA core peptide analogues, we show that MslH is a metallo-dependent peptide epimerase with a calcineurin-like fold. The crystal structure analysis, followed by site-directed mutagenesis, docking simulation, and ICP-MS studies demonstrate that MslH employs acid/base chemistry to facilitate the reversible epimerization of the C-terminal Trp21 of MslA, by utilizing two pairs of His/Asp catalytic residues that are electrostatically tethered to a six-coordination motif with a Ca(II) ion via water molecules.

Metabolome-guided genome mining of RiPP natural products

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

Discovery and Characterization of a Myxobacterial Lanthipeptide with Unique Biosynthetic Features and Anti-inflammatory Activity

The genomes of myxobacteria harbor a variety of biosynthetic gene clusters encoding numerous secondary metabolites, including ribosomally synthesized and post-translationally modified peptides (RiPPs) with diverse chemical structures and biological activities. However, the biosynthetic potential of RiPPs from myxobacteria remains barely explored. Herein, we report a novel myxobacteria lanthipeptide myxococin identified from Myxococcus fulvus. Myxococins represent the first example of lanthipeptides, of which the characteristic multiple thioether rings are installed by employing a Class II lanthipeptide synthetase MfuM and a Class I lanthipeptide cyclase MfuC in a cascaded way. Unprecedentedly, we biochemically characterized the first M61 family aminopeptidase MfuP involved in RiPP biosynthesis, demonstrating that MfuP showed the activity of an endopeptidase activity. MfuP is leader-independent but strictly selective for the multibridge structure of myxococin A and responsible for unwrapping two rings via amide bond hydrolysis, yielding myxococin B. Furthermore, the X-ray crystal structure of MfuP and structural analysis, including active-site mutations, are reported. Finally, myxococins are evaluated to exhibit anti-inflammatory activity in lipopolysaccharide-induced macrophages without detectable cytotoxicity.

HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

On the evolution of natural product biosynthesis

Natural products are the raw material for drug discovery programmes. Bioactive natural products are used extensively in medicine and agriculture and have found utility as antibiotics, immunosuppressives, anti-cancer drugs and anthelminthics. Remarkably, the natural role and what mechanisms drive evolution of these molecules is relatively poorly understood. The exponential increase in genome and chemical data in recent years, coupled with technical advances in bioinformatics and genetics have enabled progress to be made in understanding the evolution of biosynthetic gene clusters and the products of their enzymatic machinery. Here we discuss the diversity of natural products, incorporating the mechanisms that govern evolution of metabolic pathways and how this can be applied to biosynthetic gene clusters. We build on the nomenclature of natural products in terms of primary, integrated, secondary and specialised metabolism and place this within an ecology-evolutionary-developmental biology framework. This eco-evo-devo framework we believe will help to clarify the nature and use of the term specialised metabolites in the future.

Deciphering the Biosynthesis of Novel Class I Lanthipeptides from Marine Pseudoalteromonas Reveals a Dehydratase PsfB with Dethiolation Activity

Lanthipeptides are a representative class of RiPPs that possess characteristic lanthionine and/or methyllanthionine thioether cross-links. The biosynthetic potentials of marine-derived lanthipeptides remain largely unexplored. In this study, we characterized three novel lanthipeptides pseudorosin A-C by heterologous expression of a class I lanthipeptide biosynthetic gene cluster from marine Pseudoalteromonas flavipulchra S16. Interestingly, pseudorosin C contains a large loop spanning 18 amino acid residues, which is rare in lanthipeptides. Unexpectedly, the dehydratase PsfB could catalyze the dethiolation of specific Cys residues in all three core peptides, thereby generating dehydroalanines in the absence of LanC cyclase. To the best of our knowledge, we identified the first member of the LanB dehydratase family to perform glutamylation and subsequent elimination on Cys thiol groups, which likely represents a new bypass for class I lanthipeptide biosynthesis. Furthermore, we employed mutagenesis to determine the important motif of the core peptide for dethiolation activity. Moreover, sequence analysis revealed that PsfB exhibited a distinct phylogenetic distance from the characterized LanBs from Gram-positive bacteria. Our findings, therefore, pave the way for further genome mining of lanthipeptides, novel post-translational modification enzymes from marine Gram-negative bacteria, and bioengineering applications.

Genome Mining and Discovery of Imiditides, a Novel Family of RiPPs with a Class-defining Aspartimide Modification

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a fascinating class of natural products of ribosomal origins. In the past decade, various sophisticated machine learning-based software packages have been established to discover novel RiPPs that do not resemble the known families. Instead, we argue that tailoring enzymes that cluster with various RiPP families can serve as effective bioinformatic seeds for novel RiPP discovery. Leveraging that O -methyltransferases homologous to protein isoaspartyl methyltransferases (PIMTs) are associated with lasso peptide, graspetide, and lanthipeptide biosynthetic gene clusters (BGCs), we utilized the C-terminal motif unique to RiPP-associated O -methyltransferases as the search query to discover a novel family of RiPPs, imiditides. Our genome-mining algorithm reveals a total of 670 imiditide BGCs, widely distributed in Gram-positive bacterial genomes. In addition, we demonstrate the heterologous production of the founding member of the imiditide family, mNmaA M , encoded in the genome of Nonomuraea maritima . In contrast to other RiPP associated PIMTs that recognize constrained peptides as substrates, the PIMT homolog in mNmaA M BGC, NmaM, methylates a specific Asp residue on the linear precursor peptide, NmaA. The methyl ester is then turned into an aspartimide spontaneously. The aspartimide moiety formed is unusually stable, leading to the accumulation of the aspartimidylated product in vivo . The substrate specificity is achieved by extensive charge-charge interactions between the precursor NmaA and the modifying enzyme NmaM suggested by both experimental validations as well as an AlphaFold model prediction. Our study suggests that PIMT-mediated aspartimide formation is an underappreciated backbone modification strategy in RiPP biosynthesis, compared to the well-studied backbone rigidification chemistries, such as thiazol(in)e and oxazol(in)e formations. Additionally, our findings suggest that aspartimide formation in Gram-positive bacterial proteomes are not limited to spontaneous protein aging and degradation.

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Recent Advances in Discovery, Bioengineering, and Bioactivity-Evaluation of Ribosomally Synthesized and Post-translationally Modified Peptides

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are of increasing interest in natural products as well as drug discovery. This empowers not only the unique chemical structures and topologies in natural products but also the excellent bioactivities such as antibacteria, antifungi, antiviruses, and so on. Advances in genomics, bioinformatics, and chemical analytics have promoted the exponential increase of RiPPs as well as the evaluation of biological activities thereof. Furthermore, benefiting from their relatively simple and conserved biosynthetic logic, RiPPs are prone to be engineered to obtain diverse analogues that exhibit distinct physiological activities and are difficult to synthesize. This Review aims to systematically address the variety of biological activities and/or the mode of mechanisms of novel RiPPs discovered in the past decade, albeit the characteristics of selective structures and biosynthetic mechanisms are briefly covered as well. Almost one-half of the cases are involved in anti-Gram-positive bacteria. Meanwhile, an increasing number of RiPPs related to anti-Gram-negative bacteria, antitumor, antivirus, etc., are also discussed in detail. Last but not least, we sum up some disciplines of the RiPPs' biological activities to guide genome mining as well as drug discovery and optimization in the future.

Advances in mining and expressing microbial biosynthetic gene clusters

Natural products (NPs) especially the secondary metabolites originated from microbes exhibit great importance in biomedical, industrial and agricultural applications. However, mining biosynthetic gene clusters (BGCs) to produce novel NPs has been hindered owing that a large population of environmental microbes are unculturable. In the past decade, strategies to explore BGCs directly from (meta)genomes have been established along with the fast development of high-throughput sequencing technologies and the powerful bioinformatics data-processing tools, which greatly expedited the exploitations of novel BGCs from unculturable microbes including the extremophilic microbes. In this review, we firstly summarized the popular bioinformatics tools and databases available to mine novel BGCs from (meta)genomes based on either pure cultures or pristine environmental samples. Noticeably, approaches rooted from machine learning and deep learning with focuses on the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs) were dramatically increased in recent years. Moreover, synthetic biology techniques to express the novel BGCs in culturable native microbes or heterologous hosts were introduced. This working pipeline including the discovery and biosynthesis of novel NPs will greatly advance the exploitations of the abundant but unexplored microbial BGCs.

The structure of MadC from Clostridium maddingley reveals new insights into class I lanthipeptide cyclases

The rapid emergence of microbial multi-resistance against antibiotics has led to intense search for alternatives. One of these alternatives are ribosomally synthesized and post-translationally modified peptides (RiPPs), especially lantibiotics. They are active in a low nanomolar range and their high stability is due to the presence of characteristic (methyl-) lanthionine rings, which makes them promising candidates as bacteriocides. However, innate resistance against lantibiotics exists in nature, emphasizing the need for artificial or tailor-made lantibiotics. Obviously, such an approach requires an in-depth mechanistic understanding of the modification enzymes, which catalyze the formation of (methyl-)lanthionine rings. Here, we determined the structure of a class I cyclase (MadC), involved in the modification of maddinglicin (MadA) via X-ray crystallography at a resolution of 1.7 Å, revealing new insights about the structural composition of the catalytical site. These structural features and substrate binding were analyzed by mutational analyses of the leader peptide as well as of the cyclase, shedding light into the mode of action of MadC.

Genomic diversity and metabolic potential of marine Pseudomonadaceae

Recent changes in the taxonomy of the Pseudomonadaceae family have led to the delineation of three new genera (Atopomonas, Halopseudomonas and Stutzerimonas). However, the genus Pseudomonas remains the most densely populated and displays a broad genetic diversity. Pseudomonas are able to produce a wide variety of secondary metabolites which drives important ecological functions and have a great impact in sustaining their lifestyles. While soilborne Pseudomonas are constantly examined, we currently lack studies aiming to explore the genetic diversity and metabolic potential of marine Pseudomonas spp. In this study, 23 Pseudomonas strains were co-isolated with Vibrio strains from three marine microalgal cultures and rpoD-based phylogeny allowed their assignment to the Pseudomonas oleovorans group (Pseudomonas chengduensis, Pseudomonas toyotomiensis and one new species). We combined whole genome sequencing on three selected strains with an inventory of marine Pseudomonas genomes to assess their phylogenetic assignations and explore their metabolic potential. Our results revealed that most strains are incorrectly assigned at the species level and half of them do not belong to the genus Pseudomonas but instead to the genera Halopseudomonas or Stutzerimonas. We highlight the presence of 26 new species (Halopseudomonas (n = 5), Stutzerimonas (n = 7) and Pseudomonas (n = 14)) and describe one new species, Pseudomonas chaetocerotis sp. nov. (type strain 536^T = LMG 31766^T = DSM 111343^T). We used genome mining to identify numerous BGCs coding for the production of diverse known metabolites (i.e., osmoprotectants, photoprotectants, quorum sensing molecules, siderophores, cyclic lipopeptides) but also unknown metabolites (e.g., ARE, hybrid ARE-DAR, siderophores, orphan NRPS gene clusters) awaiting chemical characterization. Finally, this study underlines that marine environments host a huge diversity of Pseudomonadaceae that can drive the discovery of new secondary metabolites.

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.

Mechanism of Action of Ribosomally Synthesized and Post-Translationally Modified Peptides

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a natural product class that has undergone significant expansion due to the rapid growth in genome sequencing data and recognition that they are made by biosynthetic pathways that share many characteristic features. Their mode of actions cover a wide range of biological processes and include binding to membranes, receptors, enzymes, lipids, RNA, and metals as well as use as cofactors and signaling molecules. This review covers the currently known modes of action (MOA) of RiPPs. In turn, the mechanisms by which these molecules interact with their natural targets provide a rich set of molecular paradigms that can be used for the design or evolution of new or improved activities given the relative ease of engineering RiPPs. In this review, coverage is limited to RiPPs originating from bacteria.

Functional expression of diverse post-translational peptide-modifying enzymes in Escherichia coli under uniform expression and purification conditions

RiPPs (ribosomally-synthesized and post-translationally modified peptides) are a class of pharmaceutically-relevant natural products expressed as precursor peptides before being enzymatically processed into their final functional forms. Bioinformatic methods have illuminated hundreds of thousands of RiPP enzymes in sequence databases and the number of characterized chemical modifications is growing rapidly; however, it remains difficult to functionally express them in a heterologous host. One challenge is peptide stability, which we addressed by designing a RiPP stabilization tag (RST) based on a small ubiquitin-like modifier (SUMO) domain that can be fused to the N- or C-terminus of the precursor peptide and proteolytically removed after modification. This is demonstrated to stabilize expression of eight RiPPs representative of diverse phyla. Further, using Escherichia coli for heterologous expression, we identify a common set of media and growth conditions where 24 modifying enzymes, representative of diverse chemistries, are functional. The high success rate and broad applicability of this system facilitates: (i) RiPP discovery through high-throughput “mining” and (ii) artificial combination of enzymes from different pathways to create a desired peptide.

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

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

Biological Dark Matter Exploration using Data Mining for the Discovery of Antimicrobial Natural Products

The discovery of novel antimicrobials has significantly slowed down over the last three decades. At the same time, humans rely increasingly on antimicrobials because of the progressive antimicrobial resistance in medical practices, human communities, and the environment. Data mining is currently considered a promising option in the discovery of new antibiotics. Some of the advantages of data mining are the ability to predict chemical structures from sequence data, anticipation of the presence of novel metabolites, the understanding of gene evolution, and the corroboration of data from multiple omics technologies. This review analyzes the state-of-the-art for data mining in the fields of bacteria, fungi, and plant genomic data, as well as metabologenomics. It also summarizes some of the most recent research accomplishments in the field, all pinpointing to innovation through uncovering and implementing the next generation of antimicrobials.

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

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

Natural and engineered precision antibiotics in the context of resistance

Antibiotics are essential weapons in our fight against infectious disease, yet the consequences of broad-spectrum antibiotic use on microbiome stability and pathogen resistance are prompting investigations into more selective alternatives. Echoing the advent of precision medicine in oncology, precision antibiotics with focused activities are emerging as a means of addressing infections without damaging microbiomes or incentivizing resistance. Historically, antibiotic design principles have been gleaned from Nature, and reinvestigation of overlooked antibacterials is now providing scaffolds and targets for the design of pathogen-specific drugs. In this perspective, we summarize the biosynthetic and antibacterial mechanisms used to access these activities, and discuss how such strategies may be co-opted through engineering approaches to afford precision antibiotics.

Diverse Protein Architectures and α-N-Methylation Patterns Define Split Borosin RiPP Biosynthetic Gene Clusters

Borosins are ribosomally synthesized and post-translationally modified peptides (RiPPs) with α-N-methylations installed on the peptide backbone that impart unique properties like proteolytic stability to these natural products. The borosin RiPP family was initially reported only in fungi until our recent discovery and characterization of a Type IV split borosin system in the metal-respiring bacterium Shewanella oneidensis. Here, we used hidden Markov models and sequence similarity networks to identify over 1600 putative pathways that show split borosin biosynthetic gene clusters are widespread in bacteria. Noteworthy differences in precursor and α-N-methyltransferase open reading frame sizes, architectures, and core peptide properties allow further subdivision of the borosin family into six additional discrete structural types, of which five have been validated in this study.

Strategies to access biosynthetic novelty in bacterial genomes for drug discovery

Bacteria provide a rich source of natural products with potential therapeutic applications, such as novel antibiotic classes or anticancer drugs. Bioactivity-guided screening of bacterial extracts and characterization of biosynthetic pathways for drug discovery is now complemented by the availability of large (meta)genomic collections, placing researchers into the postgenomic, big-data era. The progress in next-generation sequencing and the rise of powerful computational tools provide unprecedented insights into unexplored taxa, ecological niches and 'biosynthetic dark matter', revealing diverse and chemically distinct natural products in previously unstudied bacteria. In this Review, we discuss such sources of new chemical entities and the implications for drug discovery with a particular focus on the strategies that have emerged in recent years to identify and access novelty.

Creating optimized peptide libraries for AMP discovery via PepSAVI-MS

Antimicrobial peptides (AMPs) are host defense peptides with a range of functions/activities/modes of action that are ubiquitously expressed across all forms of life. Continued discovery of novel AMPs presents exciting opportunities to address evolving resistance to existing treatments in multiple fields, including agricultural pathogens/pests as well as antimicrobial and chemotherapeutics for human health. However, typical discovery methods including bioassay-guided fractionation and genome mining generally lack the capacity for robust AMP discovery in non-model/unsequenced organisms. PepSAVI-MS (Statistically guided bioactive peptides prioritized via mass spectrometry) was developed as an AMP discovery approach that addresses some of the limitations associated with these standard methods. PepSAVI-MS is a multi-pronged pipeline that includes peptide library creation, bioactivity screening, LC-MS analysis, and statistical modeling for putative AMP identification. The original implementation of PepSAVI-MS outlined strategies for the fractionation of plant extracts with strong cation exchange chromatography (SCX). Herein, we elaborate on recent improvements to peptide library creation through the use of orthogonal fractionation methods, specifically crude SCX chromatography and reversed-phase liquid chromatography (RPLC). This optimization of the "peptide library creation" step has demonstrated improvements for processing and AMP identifications via PepSAVI-MS.

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.

Nerpa: A Tool for Discovering Biosynthetic Gene Clusters of Bacterial Nonribosomal Peptides

Microbial natural products are a major source of bioactive compounds for drug discovery. Among these molecules, nonribosomal peptides (NRPs) represent a diverse class of natural products that include antibiotics, immunosuppressants, and anticancer agents. Recent breakthroughs in natural product discovery have revealed the chemical structure of several thousand NRPs. However, biosynthetic gene clusters (BGCs) encoding them are known only for a few hundred compounds. Here, we developed Nerpa, a computational method for the high-throughput discovery of novel BGCs responsible for producing known NRPs. After searching 13,399 representative bacterial genomes from the RefSeq repository against 8368 known NRPs, Nerpa linked 117 BGCs to their products. We further experimentally validated the predicted BGC of ngercheumicin from Photobacterium galatheae via mass spectrometry. Nerpa supports searching new genomes against thousands of known NRP structures, and novel molecular structures against tens of thousands of bacterial genomes. The availability of these tools can enhance our understanding of NRP synthesis and the function of their biosynthetic enzymes.

Identification of Novel Rotihibin Analogues in Streptomyces scabies, Including Discovery of Its Biosynthetic Gene Cluster

Streptomyces scabies is a phytopathogen associated with common scab disease. This is mainly attributed to its ability to produce the phytotoxin thaxtomin A, the biosynthesis of which is triggered by cellobiose. During a survey of other metabolites released in the presence of cellobiose, we discovered additional compounds in the thaxtomin-containing extract from Streptomyces scabies. Structural analysis by mass spectrometry (MS) and nuclear magnetic resonance (NMR) revealed that these compounds are amino acid sequence variants of the TOR (target of rapamycin) kinase (TORK) pathway-inhibitory lipopeptide rotihibin A, and the main compounds were named rotihibins C and D. In contrast to thaxtomin, the production of rotihibins C and D was also elicited in the presence of glucose, indicating different regulation of their biosynthesis. Through a combination of shotgun and targeted proteomics, the putative rotihibin biosynthetic gene cluster rth was identified in the publicly available genome of S. scabies 87-22. This cluster spans 33 kbp and encodes 2 different nonribosomal peptide synthetases (NRPSs) and 12 additional enzymes. Homologous rth biosynthetic gene clusters were found in other publicly available and complete actinomycete genomes. Rotihibins C and D display herbicidal activity against Lemna minor and Arabidopsis thaliana at low concentrations, shown by monitoring the effects on growth and the maximal photochemistry efficiency of photosystem II. IMPORTANCE Rotihibins A and B are plant growth inhibitors acting on the TORK pathway. We report the isolation and characterization of new sequence analogues of rotihibin from Streptomyces scabies, a major cause of common scab in potato and other tuber and root vegetables. By combining proteomics data with genomic analysis, we found a cryptic biosynthetic gene cluster coding for enzyme machinery capable of rotihibin production. This work may lead to the biotechnological production of variants of this lipopeptide to investigate the exact mechanism by which it can target the plant TORK pathway in Arabidopsis thaliana. In addition, bioinformatics revealed the existence of other variants in plant-associated Streptomyces strains, both pathogenic and nonpathogenic species, raising new questions about the actual function of this lipopeptide. The discovery of a module in the nonribosomal peptide synthetase (NRPS) that incorporates the unusual citrulline residue may improve the prediction of peptides encoded by cryptic NRPS gene clusters.

Heterologous characterization of mechercharmycin A biosynthesis reveals alternative insights into post-translational modifications for RiPPs

Mechercharmycin A (MCM-A) is a marine natural product belonging to a family of polyazole cyclopeptides with remarkable bioactivities and unique structures. Identification, heterologous expression, and genetic characterizations of the MCM biosynthetic gene cluster in Bacillus subtilis revealed that it is a ribosomally synthesized and post-translationally modified peptide (RiPP) possessing complex with distinctive modifications. Based on this heterologous expression system, two MCM analogs with comparable antitumor activity are generated by engineering the biosynthetic pathway. Combinatorial co-production of a precursor peptide with different modifying enzymes in Escherichia coli identifies a different timing of modifications, showing that a tRNA^Glu-dependent highly regioselective dehydration is the first modification step, followed by polyazole formation through heterocyclization and dehydrogenation in an N- to C-terminal direction. Therefore, a rational biosynthetic pathway of MCMs is proposed, which unveils a subfamily of azol(in)e-containing RiPPs and sets the stage for further investigations of the enzymatic mechanism and synthetic biology.

Discovery of the Class I Antimicrobial Lasso Peptide Arcumycin

Lasso peptides are a structurally diverse superfamily of conformationally constrained peptide natural products, of which a subset exhibits broad antimicrobial activity. Although advances in bioinformatics have increased our knowledge of strains harboring the biosynthetic machinery for lasso peptide production, relating peptide sequence to bioactivity remains a continuous challenge. To this end, genome mining investigation of Actinobacteria-produced antimicrobial lasso peptides was performed to correlate predicted structure with antibiotic activity. Bioinformatic evaluation revealed eight putative novel class I lasso peptide sequences. Fermentation of one of these hits, Streptomyces NRRL F-5639, resulted in the production of a novel class I lasso peptide, arcumycin. Arcumycin exhibited antibiotic activity against Gram-positive bacteria including Bacillus subtilis (4 μg/mL), Staphylococcus aureus (8 μg/mL), and Micrococcus luteus (8 μg/mL). Arcumycin treatment of B. subtilis liaI-β-gal promoter fusion reporter strain resulted in upregulation of the liaRS system by the promoter liaI, indicating arcumycin interferes with lipid II biosynthesis. Cumulatively, the results illustrate the relationship between phylogenetically related lasso peptides and their bioactivity as validated through the isolation, structural determination, and evaluation of bioactivity of the novel class I antimicrobial lasso peptide arcumycin.

Mining and unearthing hidden biosynthetic potential

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

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

A User Guide for the Identification of New RiPP Biosynthetic Gene Clusters Using a RiPPER-Based Workflow

In recent years, genome mining has become a powerful strategy for the discovery of new specialized metabolites from microorganisms. However, the discovery of new groups of ribosomally synthesized and post-translationally modified peptides (RiPPs) by employing the currently available genome mining tools has proven challenging due to their inherent biases towards previously known RiPP families. In this chapter we provide detailed guidelines on using RiPPER, a recently developed RiPP-oriented genome mining tool conceived for the exploration of genomic database diversity in a flexible manner, thus allowing the discovery of truly new RiPP chemistry. In addition, using TfuA proteins of Alphaproteobacteria as an example, we present a complete workflow which integrates the functionalities of RiPPER with existing bioinformatic tools into a complete genome mining strategy. This includes some key updates to RiPPER (updated to version 1.1), which substantially simplify implementing this workflow.

Peptide backbone modifications in lanthipeptides

Lanthipeptides are a class of ribosomally synthesized and posttranslationally modified peptide (RiPP) natural products characterized by the presence of lanthionine and methyllanthionine. During the maturation of select lanthipeptides, five different alterations have been observed to the chemical structure of the peptide backbone. First, dehydratases generate dehydroalanine and dehydrobutyrine from Ser or Thr residues, respectively. A second example of introduction of unsaturation is the oxidative decarboxylation of C-terminal Cys residues catalyzed by the decarboxylase LanD. Both modifications result in loss of chirality at the α-carbon of the amino acid residues. Attack of a cysteine thiol onto a dehydrated amino acid results in thioether crosslink formation with either inversion or retention of the l-stereochemical configuration at the α-carbon of former Ser and Thr residues. A fourth modification of the protein backbone is the hydrogenation of dehydroamino acids to afford d-amino acids catalyzed by NAD(P)H-dependent reductases. A fifth modification is the conversion of Asp to isoAsp. Herein, the methods used to produce and characterize the lanthipeptide bicereucin will be described in detail along with a brief overview of other lanthipeptides.

Global Genome Mining Reveals the Distribution of Diverse Thioamidated RiPP Biosynthesis Gene Clusters

Thioamidated ribosomally synthesized and post-translationally modified peptides (RiPPs) are recently characterized natural products with wide range of potent bioactivities, such as antibiotic, antiproliferative, and cytotoxic activities. These peptides are distinguished by the presence of thioamide bonds in the peptide backbone catalyzed by the YcaO-TfuA protein pair with its genes adjacent to each other. Genome mining has facilitated an in silico approach to identify biosynthesis gene clusters (BGCs) responsible for thioamidated RiPP production. In this work, publicly available genomic data was used to detect and illustrate the diversity of putative BGCs encoding for thioamidated RiPPs. AntiSMASH and RiPPER analysis identified 613 unique TfuA-related gene cluster families (GCFs) and 797 precursor peptide families, even on phyla where the presence of these clusters have not been previously described. Several additional biosynthesis genes are colocalized with the detected BGCs, suggesting an array of possible chemical modifications. This study shows that thioamidated RiPPs occupy a widely unexplored chemical landscape.

Leveraging orthogonal mass spectrometry based strategies for comprehensive sequencing and characterization of ribosomal antimicrobial peptide natural products

Covering: Up to July 2020Ribosomal antimicrobial peptide (AMP) natural products, also known as ribosomally synthesized and post-translationally modified peptides (RiPPs) or host defense peptides, demonstrate potent bioactivities and impressive complexity that complicate molecular and biological characterization. Tandem mass spectrometry (MS) has rapidly accelerated bioactive peptide sequencing efforts, yet standard workflows insufficiently address intrinsic AMP diversity. Herein, orthogonal approaches to accelerate comprehensive and accurate molecular characterization without the need for prior isolation are reviewed. Chemical derivatization, proteolysis (enzymatic and chemical cleavage), multistage MS fragmentation, and separation (liquid chromatography and ion mobility) strategies can provide complementary amino acid composition and post-translational modification data to constrain sequence solutions. Examination of two complex case studies, gomesin and styelin D, highlights the practical implementation of the proposed approaches. Finally, we emphasize the importance of heterogeneous AMP peptidoforms that confer varying biological function, an area that warrants significant further development.

New developments in RiPP discovery, enzymology and engineering

Covering: up to June 2020Ribosomally-synthesized and post-translationally modified peptides (RiPPs) are a large group of natural products. A community-driven review in 2013 described the emerging commonalities in the biosynthesis of RiPPs and the opportunities they offered for bioengineering and genome mining. Since then, the field has seen tremendous advances in understanding of the mechanisms by which nature assembles these compounds, in engineering their biosynthetic machinery for a wide range of applications, and in the discovery of entirely new RiPP families using bioinformatic tools developed specifically for this compound class. The First International Conference on RiPPs was held in 2019, and the meeting participants assembled the current review describing new developments since 2013. The review discusses the new classes of RiPPs that have been discovered, the advances in our understanding of the installation of both primary and secondary post-translational modifications, and the mechanisms by which the enzymes recognize the leader peptides in their substrates. In addition, genome mining tools used for RiPP discovery are discussed as well as various strategies for RiPP engineering. An outlook section presents directions for future research.

Omics-based strategies to discover novel classes of RiPP natural products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) form a highly diverse class of natural products, with various biotechnologically and clinically relevant activities. A recent increase in discoveries of novel RiPP classes suggests that currently known RiPPs constitute just the tip of the iceberg. Genome mining has been a driving force behind these discoveries, but remains challenging due to a lack of universal genetic markers for RiPP detection. In this review, we discuss how various genome mining methodologies contribute towards the discovery of novel RiPP classes. Some methods prioritize novel biosynthetic gene clusters (BGCs) based on shared modifications between RiPP classes. Other methods identify RiPP precursors using machine-learning classifiers. The integration of such methods as well as integration with other types of omics data in more comprehensive pipelines could help these tools reach their potential, and keep pushing the boundaries of the chemical diversity of this important class of molecules.

Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences

Novel antibiotics are urgently needed to address the looming global crisis of antibiotic resistance. Historically, the primary source of clinically used antibiotics has been microbial secondary metabolism. Microbial genome sequencing has revealed a plethora of uncharacterized natural antibiotics that remain to be discovered. However, the isolation of these molecules is hindered by the challenge of linking sequence information to the chemical structures of the encoded molecules. Here, we present PRISM 4, a comprehensive platform for prediction of the chemical structures of genomically encoded antibiotics, including all classes of bacterial antibiotics currently in clinical use. The accuracy of chemical structure prediction enables the development of machine-learning methods to predict the likely biological activity of encoded molecules. We apply PRISM 4 to chart secondary metabolite biosynthesis in a collection of over 10,000 bacterial genomes from both cultured isolates and metagenomic datasets, revealing thousands of encoded antibiotics. PRISM 4 is freely available as an interactive web application at http://prism.adapsyn.com.

Large-scale sequencing efforts have uncovered a large number of secondary metabolic pathways, but the chemicals they synthesise remain unknown. Here the authors present PRISM 4, which predicts the chemical structures encoded by microbial genome sequences, including all classes of bacterial antibiotics in clinical use.

High-Throughput Cultivation for the Selective Isolation of Acidobacteria From Termite Nests

Microbial communities in the immediate environment of socialized invertebrates can help to suppress pathogens, in part by synthesizing bioactive natural products. Here we characterized the core microbiomes of three termite species (genus Coptotermes) and their nest material to gain more insight into the diversity of termite-associated bacteria. Sampling a healthy termite colony over time implicated a consolidated and highly stable microbiome, pointing toward the fact that beneficial bacterial phyla play a major role in termite fitness. In contrast, there was a significant shift in the composition of the core microbiome in one nest during a fungal infection, affecting the abundance of well-characterized Streptomyces species (phylum Actinobacteria) as well as less-studied bacterial phyla such as Acidobacteria. High-throughput cultivation in microplates was implemented to isolate and identify these less-studied bacterial phylogenetic group. Amplicon sequencing confirmed that our method maintained the bacterial diversity of the environmental samples, enabling the isolation of novel Acidobacteriaceae and expanding the list of cultivated species to include two strains that may define new species within the genera Terracidiphilus and Acidobacterium.

Advances in antibiotic drug discovery: reducing the barriers for antibiotic development

Antibiotic drug discovery has been an essential field of research since the early 1900s, but the threat from infectious bacteria has only increased over the decades because of the emergence of widespread multidrug resistance. In this review, we discuss the recent advances in natural product, computational and medicinal chemistry that have reinvigorated the field of antibiotic drug discovery while giving perspective on how easily, both in cost and in expertise, these methods can be implemented by other researchers with the goal of increasing the number of scientists contributing to this public health crisis.

An Amphipathic Alpha-Helix Guides Maturation of the Ribosomally-Synthesized Lipolanthines

The recently discovered strongly anti-Gram-positive lipolanthines represent a new group of lipidated, ribosomally synthesized and post-translationally modified peptides (RiPPs). They are bicyclic octapeptides with a central quaternary carbon atom (avionin), which is installed through the cooperative action of the class-III lanthipeptide synthetase MicKC and the cysteine decarboxylase MicD. Genome mining efforts indicate a widespread distribution and unprecedented biosynthetic diversity of lipolanthine gene clusters, combining elements of RiPPs, polyketide and non-ribosomal peptide biosynthesis. Utilizing NMR spectroscopy, we show that a (θxx)θxxθxxθ (θ=L, I, V, M or T) motif, which is conserved in the leader peptides of all class-III and -IV lanthipeptides, forms an amphipathic α-helix in MicA that destines the peptide substrate for enzymatic processing. Our results provide general rules of substrate recruitment and enzymatic regulation during lipolanthine maturation. These insights will facilitate future efforts to rationally design new lanthipeptide scaffolds with antibacterial potency.

Challenges and advances in genome mining of ribosomally synthesized and post-translationally modified peptides (RiPPs)

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a class of cyclic or linear peptidic natural products with remarkable structural and functional diversity. Recent advances in genomics and synthetic biology, are facilitating us to discover a large number of new ribosomal natural products, including lanthipeptides, lasso peptides, sactipeptides, thiopeptides, microviridins, cyanobactins, linear thiazole/oxazole-containing peptides and so on. In this review, we summarize bioinformatic strategies that have been developed to identify and prioritize biosynthetic gene clusters (BGCs) encoding RiPPs, and the genome mining-guided discovery of novel RiPPs. We also prospectively provide a vision of what genomics-guided discovery of RiPPs may look like in the future, especially the discovery of RiPPs from dominant but uncultivated microbes, which will be promoted by the combinational use of synthetic biology and metagenome mining strategies.

A Cell-Free Platform Based on Nisin Biosynthesis for Discovering Novel Lanthipeptides and Guiding their Overproduction In Vivo

Lanthipeptides have extensive therapeutic and industrial applications. However, because many are bactericidal, traditional in vivo platforms are limited in their capacity to discover and mass produce novel lanthipeptides as bacterial organisms are often critical components in these systems. Herein, the development of a cell-free protein synthesis (CFPS) platform that enables rapid genome mining, screening, and guided overproduction of lanthipeptides in vivo is described. For proof-of-concept studies, a type I lanthipeptide, nisin, is selected. Four novel lanthipeptides with antibacterial activity are identified among all nisin analogs in the National Center for Biotechnology Information (NCBI) database in a single day. Further, the CFPS platform is coupled with a screening assay for anti-gram-negative bacteria growth, resulting in the identification of a potent nisin mutant, M5. The titers of nisin and the nisin analog are found to be improved with CFPS platform guidance. Owing to the similarities in biosynthesis, the CFPS platform is broadly applicable to other lanthipeptides, thereby providing a universal method for lanthipeptide discovery and overproduction.

Structure Prediction and Synthesis of Pyridine-Based Macrocyclic Peptide Natural Products

The structural and functional characterization of natural products is vastly outpaced by the bioinformatic identification of biosynthetic gene clusters (BGCs) that encode such molecules. Uniting our knowledge of bioinformatics and enzymology to predict and synthetically access natural products is an effective platform for investigating cryptic/silent BGCs. We report the identification, biosynthesis, and total synthesis of a minimalistic class of ribosomally synthesized and post-translationally modified peptides (RiPPs) with the responsible BGCs encoding a subset of enzymes known from thiopeptide biosynthesis. On the basis of the BGC content, these RiPPs were predicted to undergo enzymatic dehydration of serine followed by [4+2]-cycloaddition to produce a trisubstituted, pyridine-based macrocycle. These RiPPs, termed "pyritides", thus contain the same six-membered, nitrogenous heterocycle that defines the thiopeptide RiPP class but lack the ubiquitous thiazole/thiazoline heterocycles, suggesting that thiopeptides should be reclassified as a more elaborate subclass of the pyritides. One pyritide product was obtained using an 11-step synthesis, and the structure verified by an orthogonal chemoenzymatic route using the precursor peptide and cognate pyridine synthase. This work exemplifies complementary bioinformatics, enzymology, and synthesis to characterize a minimalistic yet structurally intriguing scaffold that, unlike most thiopeptides, lacks growth-suppressive activity toward Gram-positive bacteria.