An intramolecular macrocyclase in plant ribosomal peptide biosynthesis.

The biosynthetic dogma of ribosomally synthesized and posttranslationally modified peptides (RiPP) involves enzymatic intermolecular modification of core peptide motifs in precursor peptides. The plant-specific BURP-domain protein family, named after their four founding members, includes autocatalytic peptide cyclases involved in the biosynthesis of side-chain-macrocyclic plant RiPPs. Here we show that AhyBURP, a representative of the founding Unknown Seed Protein-type BURP-domain subfamily, catalyzes intramolecular macrocyclizations of its core peptide during the sequential biosynthesis of monocyclic lyciumin I via glycine-tryptophan crosslinking and bicyclic legumenin via glutamine-tyrosine crosslinking. X-ray crystallography of AhyBURP reveals the BURP-domain fold with two type II copper centers derived from a conserved stapled-disulfide and His motif. We show the macrocyclization of lyciumin-C(sp3)-N-bond formation followed by legumenin-C(sp3)-O-bond formation requires dioxygen and radical involvement based on enzyme assays in anoxic conditions and isotopic labeling. Our study expands enzymatic intramolecular modifications beyond catalytic moiety and chromophore biogenesis to RiPP biosynthesis.

Plant peptides - redefining an area of ribosomally synthesized and post-translationally modified peptides.

Covering 1965 to February 2024Plants are prolific peptide chemists and are known to make thousands of different peptidic molecules. These peptides vary dramatically in their size, chemistry, and bioactivity. Despite their differences, all plant peptides to date are biosynthesized as ribosomally synthesized and post-translationally modified peptides (RiPPs). Decades of research in plant RiPP biosynthesis have extended the definition and scope of RiPPs from microbial sources, establishing paradigms and discovering new families of biosynthetic enzymes. The discovery and elucidation of plant peptide pathways is challenging due to repurposing and evolution of housekeeping genes as both precursor peptides and biosynthetic enzymes and due to the low rates of gene clustering in plants. In this review, we highlight the chemistry, biosynthesis, and function of the known RiPP classes from plants and recommend a nomenclature for the recent addition of BURP-domain-derived RiPPs termed burpitides. Burpitides are an emerging family of cyclic plant RiPPs characterized by macrocyclic crosslinks between tyrosine or tryptophan side chains and other amino acid side chains or their peptide backbone that are formed by copper-dependent BURP-domain-containing proteins termed burpitide cyclases. Finally, we review the discovery of plant RiPPs through bioactivity-guided, structure-guided, and gene-guided approaches.

Discovery and biosynthesis of cyclic plant peptides via autocatalytic cyclases.

Many bioactive plant cyclic peptides form side-chain-derived macrocycles. Lyciumins, cyclic plant peptides with tryptophan macrocyclizations, are ribosomal peptides (RiPPs) originating from repetitive core peptide motifs in precursor peptides with plant-specific BURP (BNM2, USP, RD22 and PG1beta) domains, but the biosynthetic mechanism for their formation has remained unknown. Here, we characterize precursor-peptide BURP domains as copper-dependent autocatalytic peptide cyclases and use a combination of tandem mass spectrometry-based metabolomics and plant genomics to systematically discover five BURP-domain-derived plant RiPP classes, with mono- and bicyclic structures formed via tryptophans and tyrosines, from botanical collections. As BURP-domain cyclases are scaffold-generating enzymes in plant specialized metabolism that are physically connected to their substrates in the same polypeptide, we introduce a bioinformatic method to mine plant genomes for precursor-peptide-encoding genes by detection of repetitive substrate domains and known core peptide features. Our study sets the stage for chemical, biosynthetic and biological exploration of plant RiPP natural products from BURP-domain cyclases.

Gene-Guided Discovery and Ribosomal Biosynthesis of Moroidin Peptides.

Moroidin is a bicyclic plant octapeptide with tryptophan side-chain cross-links, originally isolated as a pain-causing agent from the Australian stinging tree Dendrocnide moroides. Moroidin and its analog celogentin C, derived from Celosia argentea, are inhibitors of tubulin polymerization and, thus, lead structures for cancer therapy. However, low isolation yields from source plants and challenging organic synthesis hinder moroidin-based drug development. Here, we present biosynthesis as an alternative route to moroidin-type bicyclic peptides and report that they are ribosomally synthesized and posttranslationally modified peptides (RiPPs) derived from BURP-domain peptide cyclases in plants. By mining 793 plant transcriptomes for moroidin core peptide motifs within BURP-domain precursor peptides, we identified a moroidin cyclase in Japanese kerria, which catalyzes the installation of the tryptophan-indole-centered macrocyclic bonds of the moroidin bicyclic motif in the presence of cupric ions. Based on the kerria moroidin cyclase, we demonstrate the feasibility of producing diverse moroidins including celogentin C in transgenic tobacco plants and report specific cytotoxicity of celogentin C against a lung adenocarcinoma cancer cell line. Our study sets the stage for future biosynthetic development of moroidin-based therapeutics and highlights that mining plant transcriptomes can reveal bioactive cyclic peptides and their underlying cyclases from new source plants.

Uptake of Phytoplankton-Derived Carbon and Cobalamins by Novel Acidobacteria Genera in Microcystis Blooms Inferred from Metagenomic and Metatranscriptomic Evidence.

Interactions between bacteria and phytoplankton can influence primary production, community composition, and algal bloom development. However, these interactions are poorly described for many consortia, particularly for freshwater bloom-forming cyanobacteria. Here, we assessed the gene content and expression of two uncultivated Acidobacteria from Lake Erie Microcystis blooms. These organisms were targeted because they were previously identified as important catalase producers in Microcystis blooms, suggesting that they protect Microcystis from H2O2. Metatranscriptomics revealed that both Acidobacteria transcribed genes for uptake of organic compounds that are known cyanobacterial products and exudates, including lactate, glycolate, amino acids, peptides, and cobalamins. Expressed genes for amino acid metabolism and peptide transport and degradation suggest that use of amino acids and peptides by Acidobacteria may regenerate nitrogen for cyanobacteria and other organisms. The Acidobacteria genomes lacked genes for biosynthesis of cobalamins but expressed genes for its transport and remodeling. This indicates that the Acidobacteria obtained cobalamins externally, potentially from Microcystis, which has a complete gene repertoire for pseudocobalamin biosynthesis; expressed them in field samples; and produced pseudocobalamin in axenic culture. Both Acidobacteria were detected in Microcystis blooms worldwide. Together, the data support the hypotheses that uncultured and previously unidentified Acidobacteria taxa exchange metabolites with phytoplankton during harmful cyanobacterial blooms and influence nitrogen available to phytoplankton. Thus, novel Acidobacteria may play a role in cyanobacterial physiology and bloom development. IMPORTANCE Interactions between heterotrophic bacteria and phytoplankton influence competition and successions between phytoplankton taxa, thereby influencing ecosystem-wide processes such as carbon cycling and algal bloom development. The cyanobacterium Microcystis forms harmful blooms in freshwaters worldwide and grows in buoyant colonies that harbor other bacteria in their phycospheres. Bacteria in the phycosphere and in the surrounding community likely influence Microcystis physiology and ecology and thus the development of freshwater harmful cyanobacterial blooms. However, the impacts and mechanisms of interaction between bacteria and Microcystis are not fully understood. This study explores the mechanisms of interaction between Microcystis and uncultured members of its phycosphere in situ with population genome resolution to investigate the cooccurrence of Microcystis and freshwater Acidobacteria in blooms worldwide.

Gene-guided discovery and engineering of branched cyclic peptides in plants.

The plant kingdom contains vastly untapped natural product chemistry, which has been traditionally explored through the activity-guided approach. Here, we describe a gene-guided approach to discover and engineer a class of plant ribosomal peptides, the branched cyclic lyciumins. Initially isolated from the Chinese wolfberry Lycium barbarum, lyciumins are protease-inhibiting peptides featuring an N-terminal pyroglutamate and a macrocyclic bond between a tryptophan-indole nitrogen and a glycine α-carbon. We report the identification of a lyciumin precursor gene from L. barbarum, which encodes a BURP domain and repetitive lyciumin precursor peptide motifs. Genome mining enabled by this initial finding revealed rich lyciumin genotypes and chemotypes widespread in flowering plants. We establish a biosynthetic framework of lyciumins and demonstrate the feasibility of producing diverse natural and unnatural lyciumins in transgenic tobacco. With rapidly expanding plant genome resources, our approach will complement bioactivity-guided approaches to unlock and engineer hidden plant peptide chemistry for pharmaceutical and agrochemical applications.

Crystalline-Sponge-Based Structural Analysis of Crude Natural Product Extracts.

Characterization of complex natural product mixtures to the absolute structural level of their components often requires significant amounts of starting materials and lengthy purification process, followed by arduous structure elucidation efforts. The crystalline sponge (CS) method has demonstrated utility in the absolute structure elucidation of isolated organic compounds at miniscule quantities compared to conventional methods. In this work, we developed a new CS-based workflow that greatly expedites the in-depth structural analysis of crude natural product extracts. Using a crude extract of the red alga Laurencia pacifica, we showed that CS affinity screening prior to compound isolation enables prioritization of analytes present in the extract, and we subsequently resolved the molecular structures of six sesquiterpenes with stereochemical clarity from around 10 mg crude extract. This study demonstrates a new chemotyping workflow that can greatly accelerate natural product discovery from complex samples.

A Red Algal Bourbonane Sesquiterpene Synthase Defined by Microgram-Scale NMR-Coupled Crystalline Sponge X-ray Diffraction Analysis.

Sesquiterpene scaffolds are the core backbones of many medicinally and industrially important natural products. A plethora of sesquiterpene synthases, widely present in bacteria, fungi, and plants, catalyze the formation of these intricate structures often with multiple stereocenters starting from linear farnesyl diphosphate substrates. Recent advances in next-generation sequencing and metabolomics technologies have greatly facilitated gene discovery for sesquiterpene synthases. However, a major bottleneck limits biochemical characterization of recombinant sesquiterpene synthases: the absolute structural elucidation of the derived sesquiterpene products. Here, we report the identification and biochemical characterization of LphTPS-A, a sesquiterpene synthase from the red macroalga Laurencia pacifica. Using the combination of transcriptomics, sesquiterpene synthase expression in yeast, and microgram-scale nuclear magnetic resonance-coupled crystalline sponge X-ray diffraction analysis, we resolved the absolute stereochemistry of prespatane, the major sesquiterpene product of LphTPS-A, and thereby functionally define LphTPS-A as the first bourbonane-producing sesquiterpene synthase and the first biochemically characterized sesquiterpene synthase from red algae. Our study showcases a workflow integrating multiomics approaches, synthetic biology, and the crystalline sponge method, which is generally applicable for uncovering new terpene chemistry and biochemistry from source-limited living organisms.

Direct cloning and refactoring of a silent lipopeptide biosynthetic gene cluster yields the antibiotic taromycin A.

Recent developments in next-generation sequencing technologies have brought recognition of microbial genomes as a rich resource for novel natural product discovery. However, owing to the scarcity of efficient procedures to connect genes to molecules, only a small fraction of secondary metabolomes have been investigated to date. Transformation-associated recombination (TAR) cloning takes advantage of the natural in vivo homologous recombination of Saccharomyces cerevisiae to directly capture large genomic loci. Here we report a TAR-based genetic platform that allows us to directly clone, refactor, and heterologously express a silent biosynthetic pathway to yield a new antibiotic. With this method, which involves regulatory gene remodeling, we successfully expressed a 67-kb nonribosomal peptide synthetase biosynthetic gene cluster from the marine actinomycete Saccharomonospora sp. CNQ-490 and produced the dichlorinated lipopeptide antibiotic taromycin A in the model expression host Streptomyces coelicolor. The taromycin gene cluster (tar) is highly similar to the clinically approved antibiotic daptomycin from Streptomyces roseosporus, but has notable structural differences in three amino acid residues and the lipid side chain. With the activation of the tar gene cluster and production of taromycin A, this study highlights a unique "plug-and-play" approach to efficiently gaining access to orphan pathways that may open avenues for novel natural product discoveries and drug development.

Biosynthesis of polybrominated aromatic organic compounds by marine bacteria.

Polybrominated diphenyl ethers (PBDEs) and polybrominated bipyrroles are natural products that bioaccumulate in the marine food chain. PBDEs have attracted widespread attention because of their persistence in the environment and potential toxicity to humans. However, the natural origins of PBDE biosynthesis are not known. Here we report marine bacteria as producers of PBDEs and establish a genetic and molecular foundation for their production that unifies paradigms for the elaboration of bromophenols and bromopyrroles abundant in marine biota. We provide biochemical evidence of marine brominases revealing decarboxylative-halogenation enzymology previously unknown among halogenating enzymes. Biosynthetic motifs discovered in our study were used to mine sequence databases to discover unrealized marine bacterial producers of organobromine compounds.

Glycogenomics as a mass spectrometry-guided genome-mining method for microbial glycosylated molecules.

Glycosyl groups are an essential mediator of molecular interactions in cells and on cellular surfaces. There are very few methods that directly relate sugar-containing molecules to their biosynthetic machineries. Here, we introduce glycogenomics as an experiment-guided genome-mining approach for fast characterization of glycosylated natural products (GNPs) and their biosynthetic pathways from genome-sequenced microbes by targeting glycosyl groups in microbial metabolomes. Microbial GNPs consist of aglycone and glycosyl structure groups in which the sugar unit(s) are often critical for the GNP's bioactivity, e.g., by promoting binding to a target biomolecule. GNPs are a structurally diverse class of molecules with important pharmaceutical and agrochemical applications. Herein, O- and N-glycosyl groups are characterized in their sugar monomers by tandem mass spectrometry (MS) and matched to corresponding glycosylation genes in secondary metabolic pathways by a MS-glycogenetic code. The associated aglycone biosynthetic genes of the GNP genotype then classify the natural product to further guide structure elucidation. We highlight the glycogenomic strategy by the characterization of several bioactive glycosylated molecules and their gene clusters, including the anticancer agent cinerubin B from Streptomyces sp. SPB74 and an antibiotic, arenimycin B, from Salinispora arenicola CNB-527.

MS/MS networking guided analysis of molecule and gene cluster families.

The ability to correlate the production of specialized metabolites to the genetic capacity of the organism that produces such molecules has become an invaluable tool in aiding the discovery of biotechnologically applicable molecules. Here, we accomplish this task by matching molecular families with gene cluster families, making these correlations to 60 microbes at one time instead of connecting one molecule to one organism at a time, such as how it is traditionally done. We can correlate these families through the use of nanospray desorption electrospray ionization MS/MS, an ambient pressure MS technique, in conjunction with MS/MS networking and peptidogenomics. We matched the molecular families of peptide natural products produced by 42 bacilli and 18 pseudomonads through the generation of amino acid sequence tags from MS/MS data of specific clusters found in the MS/MS network. These sequence tags were then linked to biosynthetic gene clusters in publicly accessible genomes, providing us with the ability to link particular molecules with the genes that produced them. As an example of its use, this approach was applied to two unsequenced Pseudoalteromonas species, leading to the discovery of the gene cluster for a molecular family, the bromoalterochromides, in the previously sequenced strain P. piscicida JCM 20779(T). The approach itself is not limited to 60 related strains, because spectral networking can be readily adopted to look at molecular family-gene cluster families of hundreds or more diverse organisms in one single MS/MS network.

Mass spectral molecular networking of living microbial colonies.

Integrating the governing chemistry with the genomics and phenotypes of microbial colonies has been a "holy grail" in microbiology. This work describes a highly sensitive, broadly applicable, and cost-effective approach that allows metabolic profiling of live microbial colonies directly from a Petri dish without any sample preparation. Nanospray desorption electrospray ionization mass spectrometry (MS), combined with alignment of MS data and molecular networking, enabled monitoring of metabolite production from live microbial colonies from diverse bacterial genera, including Bacillus subtilis, Streptomyces coelicolor, Mycobacterium smegmatis, and Pseudomonas aeruginosa. This work demonstrates that, by using these tools to visualize small molecular changes within bacterial interactions, insights can be gained into bacterial developmental processes as a result of the improved organization of MS/MS data. To validate this experimental platform, metabolic profiling was performed on Pseudomonas sp. SH-C52, which protects sugar beet plants from infections by specific soil-borne fungi [R. Mendes et al. (2011) Science 332:1097-1100]. The antifungal effect of strain SH-C52 was attributed to thanamycin, a predicted lipopeptide encoded by a nonribosomal peptide synthetase gene cluster. Our technology, in combination with our recently developed peptidogenomics strategy, enabled the detection and partial characterization of thanamycin and showed that it is a monochlorinated lipopeptide that belongs to the syringomycin family of antifungal agents. In conclusion, the platform presented here provides a significant advancement in our ability to understand the spatiotemporal dynamics of metabolite production in live microbial colonies and communities.

NRPquest: Coupling Mass Spectrometry and Genome Mining for Nonribosomal Peptide Discovery.

Nonribosomal peptides (NRPs) such as vancomycin and daptomycin are among the most effective antibiotics. While NRPs are biomedically important, the computational techniques for sequencing these peptides are still in their infancy. The recent emergence of mass spectrometry techniques for NRP analysis (capable of sequencing an NRP from small amounts of nonpurified material) revealed an enormous diversity of NRPs. However, as many NRPs have nonlinear structure (e.g., cyclic or branched-cyclic peptides), the standard de novo sequencing tools (developed for linear peptides) are not applicable to NRP analysis. Here, we introduce the first NRP identification algorithm, NRPquest, that performs mutation-tolerant and modification-tolerant searches of spectral data sets against a database of putative NRPs. In contrast to previous studies aimed at NRP discovery (that usually report very few NRPs), NRPquest revealed nearly a hundred NRPs (including unknown variants of previously known peptides) in a single study. This result indicates that NRPquest can potentially make MS-based NRP identification as robust as the identification of linear peptides in traditional proteomics.

Discovering type I cis-AT polyketides through computational mass spectrometry and genome mining with Seq2PKS.

Type 1 polyketides are a major class of natural products used as antiviral, antibiotic, antifungal, antiparasitic, immunosuppressive, and antitumor drugs. Analysis of public microbial genomes leads to the discovery of over sixty thousand type 1 polyketide gene clusters. However, the molecular products of only about a hundred of these clusters are characterized, leaving most metabolites unknown. Characterizing polyketides relies on bioactivity-guided purification, which is expensive and time-consuming. To address this, we present Seq2PKS, a machine learning algorithm that predicts chemical structures derived from Type 1 polyketide synthases. Seq2PKS predicts numerous putative structures for each gene cluster to enhance accuracy. The correct structure is identified using a variable mass spectral database search. Benchmarks show that Seq2PKS outperforms existing methods. Applying Seq2PKS to Actinobacteria datasets, we discover biosynthetic gene clusters for monazomycin, oasomycin A, and 2-aminobenzamide-actiphenol.

Biosynthetic multitasking facilitates thalassospiramide structural diversity in marine bacteria.

Thalassospiramides A and B are immunosuppressant cyclic lipopeptides first reported from the marine α-proteobacterium Thalassospira sp. CNJ-328. We describe here the discovery and characterization of an extended family of 14 new analogues from four Tistrella and Thalassospira isolates. These potent calpain 1 protease inhibitors belong to six structure classes in which the length and composition of the acylpeptide side chain varies extensively. Genomic sequence analysis of the thalassospiramide-producing microbes revealed related, genus-specific biosynthetic loci encoding hybrid nonribosomal peptide synthetase/polyketide synthases consistent with thalassospiramide assembly. The bioinformatics analysis of the gene clusters suggests that structural diversity, which ranges from the 803.4 Da thalassospiramide C to the 1291.7 Da thalassospiramide F, results from a complex sequence of reactions involving amino acid substrate channeling and enzymatic multimodule skipping and iteration. Preliminary biochemical analysis of the N-terminal nonribosomal peptide synthetase module from the Thalassospira TtcA megasynthase supports a biosynthetic model in which in cis amino acid activation competes with in trans activation to increase the range of amino acid substrates incorporated at the N terminus.

Bioactivity-guided genome mining reveals the lomaiviticin biosynthetic gene cluster in Salinispora tropica.

The use of genome sequences has become routine in guiding the discovery and identification of microbial natural products and their biosynthetic pathways. In silico prediction of molecular features, such as metabolic building blocks, physico-chemical properties or biological functions, from orphan gene clusters has opened up the characterization of many new chemo- and genotypes in genome mining approaches. Here, we guided our genome mining of two predicted enediyne pathways in Salinispora tropica CNB-440 by a DNA interference bioassay to isolate DNA-targeting enediyne polyketides. An organic extract of S. tropica showed DNA-interference activity that surprisingly was not abolished in genetic mutants of the targeted enediyne pathways, ST_pks1 and spo. Instead we showed that the product of the orphan type II polyketide synthase pathway, ST_pks2, is solely responsible for the DNA-interfering activity of the parent strain. Subsequent comparative metabolic profiling revealed the lomaiviticins, glycosylated diazofluorene polyketides, as the ST_pks2 products. This study marks the first report of the 59 open reading frame lomaiviticin gene cluster (lom) and supports the biochemical logic of their dimeric construction through a pathway related to the kinamycin monomer.

A mass spectrometry-guided genome mining approach for natural product peptidogenomics.

Peptide natural products show broad biological properties and are commonly produced by orthogonal ribosomal and nonribosomal pathways in prokaryotes and eukaryotes. To harvest this large and diverse resource of bioactive molecules, we introduce here natural product peptidogenomics (NPP), a new MS-guided genome-mining method that connects the chemotypes of peptide natural products to their biosynthetic gene clusters by iteratively matching de novo tandem MS (MS(n)) structures to genomics-based structures following biosynthetic logic. In this study, we show that NPP enabled the rapid characterization of over ten chemically diverse ribosomal and nonribosomal peptide natural products of previously unidentified composition from Streptomycete bacteria as a proof of concept to begin automating the genome-mining process. We show the identification of lantipeptides, lasso peptides, linardins, formylated peptides and lipopeptides, many of which are from well-characterized model Streptomycetes, highlighting the power of NPP in the discovery of new peptide natural products from even intensely studied organisms.

Jujube Fruit Metabolomic Profiles Reveal Cultivar Differences and Function as Cultivar Fingerprints.

Jujube is a nutritious fruit, and is high in vitamin C, fiber, phenolics, flavonoids, nucleotides, and organic acids. It is both an important food and a source of traditional medicine. Metabolomics can reveal metabolic differences between Ziziphus jujuba fruits from different jujube cultivars and growth sites. In the fall of 2022, mature fresh fruit of eleven cultivars from replicated trials at three sites in New Mexico-Leyendecker, Los Lunas, and Alcalde-were sampled from September to October for an untargeted metabolomics study. The 11 cultivars were Alcalde 1, Dongzao, Jinsi (JS), Jinkuiwang (JKW), Jixin, Kongfucui (KFC), Lang, Li, Maya, Shanxi Li, and Zaocuiwang (ZCW). Based on the LC-MS/MS analysis, there were 1315 compounds detected with amino acids and derivatives (20.15%) and flavonoids (15.44%) as dominant categories. The results reveal that the cultivar was the dominant factor in metabolite profiles, while the location was secondary. A pairwise comparison of cultivar metabolomes revealed that two pairs had fewer differential metabolites (i.e., Li/Shanxi Li and JS/JKW) than all the other pairs, highlighting that pairwise metabolic comparison can be applied for cultivar fingerprinting. Differential metabolite analysis also showed that half of drying cultivars have up-regulated lipid metabolites compared to fresh or multi-purpose fruit cultivars and that specialized metabolites vary significantly between cultivars from 35.3% (Dongzao/ZCW) to 56.7% (Jixin/KFC). An exemplary analyte matching sedative cyclopeptide alkaloid sanjoinine A was only detected in the Jinsi and Jinkuiwang cultivars. Overall, our metabolic analysis of the jujube cultivar's mature fruits provides the largest resource of jujube fruit metabolomes to date and will inform cultivar selection for nutritional and medicinal research and for fruit metabolic breeding.

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.