Expanded Natural Product Diversity Revealed by Analysis of Lanthipeptide-Like Gene Clusters in Actinobacteria

Lanthionine-containing peptides (lanthipeptides) are a rapidly growing family of polycyclic peptide natural products belonging to the large class of ribosomally synthesized and posttranslationally modified peptides (RiPPs). Lanthipeptides are widely distributed in taxonomically distant species, and their currently known biosynthetic systems and biological activities are diverse. Building on the recent natural product gene cluster family (GCF) project, we report here large-scale analysis of lanthipeptide-like biosynthetic gene clusters from Actinobacteria. Our analysis suggests that lanthipeptide biosynthetic pathways, and by extrapolation the natural products themselves, are much more diverse than currently appreciated and contain many different posttranslational modifications. Furthermore, lanthionine synthetases are much more diverse in sequence and domain topology than currently characterized systems, and they are used by the biosynthetic machineries for natural products other than lanthipeptides. The gene cluster families described here significantly expand the chemical diversity and biosynthetic repertoire of lanthionine-related natural products. Biosynthesis of these novel natural products likely involves unusual and unprecedented biochemistries, as illustrated by several examples discussed in this study. In addition, class IV lanthipeptide gene clusters are shown not to be silent, setting the stage to investigate their biological activities.     

链霉菌Streptomyces antibioticus NRRL 8167中Naphthgeranine A生物合成基因簇的分析鉴定

【背景】微生物来源的天然产物是小分子药物或药物先导物的重要来源。对链霉菌Streptomyces antibioticus NRRL 8167的基因组分析显示,其包含多个次级代谢产物的生物合成基因簇,具有产生多种新化合物的潜力。【目的】对链霉菌S. antibioticus NRRL 8167中次级代谢产物进行研究,以期发现结构新颖或生物活性独特的化合物,并对相应产物的生物合成基因簇和生物合成途径进行解析。【方法】利用HPLC图谱结合特征性紫外吸收和LC-MS方法,排除S. antibioticus NRRL 8167产生的已知化合物,确定具有特殊紫外吸收的化合物作为挖掘对象,然后利用正、反相硅胶柱色谱、高效液相色谱等技术对次级代谢产物进行分离纯化,分离化合物。利用质谱及核磁共振光谱技术对化合物结构进行解析和鉴定;提取链霉菌S. antibioticus NRRL 8167基因组DNA,利用PacBio测序平台进行基因组测序;利用生物信息学对基因组进行注释,并对合成该化合物的基因簇进行定位分析,推导其生物合成途径。【结果】确定这个化合物是NaphthgeranineA,属于聚酮类化合物。全基因组序列分析发现S.antibioticusNRRL8167基因组含有28个次级代谢产物生物合成基因簇,其中基因簇20可能负责Naphthgeranine A的生物合成,并对其生物合成途径进行了推导。【结论】基于紫外吸收光谱和质谱特征,从S. antibioticus NRRL 8167菌株的发酵提取物中分离鉴定了一个聚酮类化合物Naphthgeranine A。该菌株的全基因组测序为其生物合成基因簇的鉴定提供了前提,对Naphthgeranine A生物合成基因簇和生物合成途径的推测为进一步研究这个化合物的生物合成机制奠定了基础。     

A proteomic survey of nonribosomal peptide and polyketide biosynthesis in actinobacteria

Actinobacteria such as streptomycetes are renowned for their ability to produce bioactive natural products including nonribosomal peptides (NRPs) and polyketides (PKs). The advent of genome sequencing has revealed an even larger genetic repertoire for secondary metabolism with most of the small molecule products of these gene clusters still unknown. Here, we employed a "protein-first" method called PrISM (Proteomic Investigation of Secondary Metabolism) to screen 26 unsequenced actinomycetes using mass spectrometry-based proteomics for the targeted detection of expressed nonribosomal peptide synthetases or polyketide synthases. Improvements to the original PrISM screening approach (Nat. Biotechnol. 2009, 27, 951-956), for example, improved de novo peptide sequencing, have enabled the discovery of 10 NRPS/PKS gene clusters from 6 strains. Taking advantage of the concurrence of biosynthetic enzymes and the secondary metabolites they generate, two natural products were associated with their previously "orphan" gene clusters. This work has demonstrated the feasibility of a proteomics-based strategy for use in screening for NRP/PK production in actinomycetes (often >8 Mbp, high GC genomes) versus the bacilli (2-4 Mbp genomes) used previously.     

Expanding our Understanding of Sequence-Function Relationships of Type II Polyketide Biosynthetic Gene Clusters: Bioinformatics-Guided Identification of Frankiamicin A from Frankia sp. EAN1pec

A large and rapidly increasing number of unstudied “orphan” natural product biosynthetic gene clusters are being uncovered in sequenced microbial genomes. An important goal of modern natural products research is to be able to accurately predict natural product structures and biosynthetic pathways from these gene cluster sequences. This requires both development of bioinformatic methods for global analysis of these gene clusters and experimental characterization of select products produced by gene clusters with divergent sequence characteristics. Here, we conduct global bioinformatic analysis of all available type II polyketide gene cluster sequences and identify a conserved set of gene clusters with unique ketosynthase α/β sequence characteristics in the genomes of Frankia species, a group of Actinobacteria with underexploited natural product biosynthetic potential. Through LC-MS profiling of extracts from several Frankia species grown under various conditions, we identified Frankia sp. EAN1pec as producing a compound with spectral characteristics consistent with the type II polyketide produced by this gene cluster. We isolated the compound, a pentangular polyketide which we named frankiamicin A, and elucidated its structure by NMR and labeled precursor feeding. We also propose biosynthetic and regulatory pathways for frankiamicin A based on comparative genomic analysis and literature precedent, and conduct bioactivity assays of the compound. Our findings provide new information linking this set of Frankia gene clusters with the compound they produce, and our approach has implications for accurate functional prediction of the many other type II polyketide clusters present in bacterial genomes.     

Phylum-wide comparative genomics unravel the diversity of secondary metabolism in Cyanobacteria

Background

Cyanobacteria are an ancient lineage of photosynthetic bacteria from which hundreds of natural products have been described, including many notorious toxins but also potent natural products of interest to the pharmaceutical and biotechnological industries. Many of these compounds are the products of non-ribosomal peptide synthetase (NRPS) or polyketide synthase (PKS) pathways. However, current understanding of the diversification of these pathways is largely based on the chemical structure of the bioactive compounds, while the evolutionary forces driving their remarkable chemical diversity are poorly understood.

Results

We carried out a phylum-wide investigation of genetic diversification of the cyanobacterial NRPS and PKS pathways for the production of bioactive compounds. 452 NRPS and PKS gene clusters were identified from 89 cyanobacterial genomes, revealing a clear burst in late-branching lineages. Our genomic analysis further grouped the clusters into 286 highly diversified cluster families (CF) of pathways. Some CFs appeared vertically inherited, while others presented a more complex evolutionary history. Only a few horizontal gene transfers were evidenced amongst strongly conserved CFs in the phylum, while several others have undergone drastic gene shuffling events, which could result in the observed diversification of the pathways.

Conclusions

Therefore, in addition to toxin production, several NRPS and PKS gene clusters are devoted to important cellular processes of these bacteria such as nitrogen fixation and iron uptake. The majority of the biosynthetic clusters identified here have unknown end products, highlighting the power of genome mining for the discovery of new natural products.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-977) contains supplementary material, which is available to authorized users.     

Microbial genomics for the improvement of natural product discovery

The quest for the discovery of novel natural products has entered a new chapter with the enormous wealth of genetic data that is now available. This information has been exploited by using whole-genome sequence mining to uncover cryptic pathways, or biosynthetic pathways for previously undetected metabolites. Alternatively, using known paradigms for secondary metabolite biosynthesis, genetic information has been 'fished out' of DNA libraries resulting in the discovery of new natural products and isolation of gene clusters for known metabolites. Novel natural products have been discovered by expressing genetic data from uncultured organisms or difficult-to-manipulate strains in heterologous hosts. Furthermore, improvements in heterologous expression have not only helped to identify gene clusters but have also made it easier to manipulate these genes in order to generate new compounds. Finally, and perhaps the most crucial aspect of the efficient and prosperous use of the abundance of genetic information, novel enzyme chemistry continues to be discovered, which has aided our understanding of how natural products are biosynthesized de novo, and enabled us to rework the current paradigms for natural product biosynthesis.     

Detecting differential and correlated protein expression in label-free shotgun proteomics

Recent studies have revealed a relationship between protein abundance and sampling statistics, such as sequence coverage, peptide count, and spectral count, in label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics. The use of sampling statistics offers a promising method of measuring relative protein abundance and detecting differentially expressed or coexpressed proteins. We performed a systematic analysis of various approaches to quantifying differential protein expression in eukaryotic Saccharomyces cerevisiae and prokaryotic Rhodopseudomonas palustris label-free LC-MS/MS data. First, we showed that, among three sampling statistics, the spectral count has the highest technical reproducibility, followed by the less-reproducible peptide count and relatively nonreproducible sequence coverage. Second, we used spectral count statistics to measure differential protein expression in pairwise experiments using five statistical tests: Fisher's exact test, G-test, AC test, t-test, and LPE test. Given the S. cerevisiae data set with spiked proteins as a benchmark and the false positive rate as a metric, our evaluation suggested that the Fisher's exact test, G-test, and AC test can be used when the number of replications is limited (one or two), whereas the t-test is useful with three or more replicates available. Third, we generalized the G-test to increase the sensitivity of detecting differential protein expression under multiple experimental conditions. Out of 1622 identified R. palustris proteins in the LC-MS/MS experiment, the generalized G-test detected 1119 differentially expressed proteins under six growth conditions. Finally, we studied correlated expression of these 1119 proteins by analyzing pairwise expression correlations and by delineating protein clusters according to expression patterns. Through pairwise expression correlation analysis, we demonstrated that proteins co-located in the same operon were much more strongly coexpressed than those from different operons. Combining cluster analysis with existing protein functional annotations, we identified six protein clusters with known biological significance. In summary, the proposed generalized G-test using spectral count sampling statistics is a viable methodology for robust quantification of relative protein abundance and for sensitive detection of biologically significant differential protein expression under multiple experimental conditions in label-free shotgun proteomics.     

Identification of a poly-cyclopropylglycine–containing peptide via bioinformatic mapping of radical S-adenosylmethionine enzymes

Peptide-derived natural products are a large class of bioactive molecules that often contain chemically challenging modifications. In the biosynthesis of ribosomally synthesized and posttranslationally modified peptides (RiPPs), radical-SAM (rSAM) enzymes have been shown to catalyze the formation of ether, thioether, and carbon-carbon bonds on the precursor peptide. The installation of these bonds typically establishes the skeleton of the mature RiPP. To facilitate the search for unexplored rSAM-dependent RiPPs for the community, we employed a bioinformatic strategy to screen a subfamily of peptide-modifying rSAM enzymes which are known to bind up to three [4Fe-4S] clusters. A sequence similarity network was used to partition related families of rSAM enzymes into >250 clusters. Using representative sequences, genome neighborhood diagrams were generated using the Genome Neighborhood Tool. Manual inspection of bacterial genomes yielded numerous putative rSAM-dependent RiPP pathways with unique features. From this analysis, we identified and experimentally characterized the rSAM enzyme, TvgB, from the tvg gene cluster from Halomonas anticariensis. In the tvg gene cluster, the precursor peptide, TvgA, is comprised of a repeating TVGG motif. Structural characterization of the TvgB product revealed the repeated formation of cyclopropylglycine, where a new bond is formed between the γ-carbons on the precursor valine. This novel RiPP modification broadens the functional potential of rSAM enzymes and validates the proposed bioinformatic approach as a practical broad search tool for the discovery of new RiPP topologies.     

Genome mining for natural product biosynthetic gene clusters in the Subsection V cyanobacteria

Background

Cyanobacteria are well known for the production of a range of secondary metabolites. Whilst recent genome sequencing projects has led to an increase in the number of publically available cyanobacterial genomes, the secondary metabolite potential of many of these organisms remains elusive. Our study focused on the 11 publically available Subsection V cyanobacterial genomes, together with the draft genomes of Westiella intricata UH strain HT-29-1 and Hapalosiphon welwitschii UH strain IC-52-3, for their genetic potential to produce secondary metabolites. The Subsection V cyanobacterial genomes analysed in this study are reported to produce a diverse range of natural products, including the hapalindole-family of compounds, microcystin, hapalosin, mycosporine-like amino acids and hydrocarbons.

Results

A putative gene cluster for the cyclic depsipeptide hapalosin, known to reverse P-glycoprotein multiple drug resistance, was identified within three Subsection V cyanobacterial genomes, including the producing cyanobacterium H. welwitschii UH strain IC-52-3. A number of orphan NRPS/PKS gene clusters and ribosomally-synthesised and post translationally-modified peptide gene clusters (including cyanobactin, microviridin and bacteriocin gene clusters) were identified. Furthermore, gene clusters encoding the biosynthesis of mycosporine-like amino acids, scytonemin, hydrocarbons and terpenes were also identified and compared.

Conclusions

Genome mining has revealed the diversity, abundance and complex nature of the secondary metabolite potential of the Subsection V cyanobacteria. This bioinformatic study has identified novel biosynthetic enzymes which have not been associated with gene clusters of known classes of natural products, suggesting that these cyanobacteria potentially produce structurally novel secondary metabolites.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1855-z) contains supplementary material, which is available to authorized users.     

Synthetic biology and metabolic engineering of actinomycetes for natural product discovery

Actinomycetes are one of the most valuable sources of natural products with industrial and medicinal importance. After more than half a century of exploitation, it has become increasingly challenging to find novel natural products with useful properties as the same known compounds are often repeatedly re-discovered when using traditional approaches. Modern genome mining approaches have led to the discovery of new biosynthetic gene clusters, thus indicating that actinomycetes still harbor a huge unexploited potential to produce novel natural products. In recent years, innovative synthetic biology and metabolic engineering tools have greatly accelerated the discovery of new natural products and the engineering of actinomycetes. In the first part of this review, we outline the successful application of metabolic engineering to optimize natural product production, focusing on the use of multi-omics data, genome-scale metabolic models, rational approaches to balance precursor pools, and the engineering of regulatory genes and regulatory elements. In the second part, we summarize the recent advances of synthetic biology for actinomycetal metabolic engineering including cluster assembly, cloning and expression, CRISPR/Cas9 technologies, and chassis strain development for natural product overproduction and discovery. Finally, we describe new advances in reprogramming biosynthetic pathways through polyketide synthase and non-ribosomal peptide synthetase engineering. These new developments are expected to revitalize discovery and development of new natural products with medicinal and other industrial applications.     

Motif-Independent Prediction of a Secondary Metabolism Gene Cluster Using Comparative Genomics: Application to Sequenced Genomes of Aspergillus and Ten Other Filamentous Fungal Species

Despite their biological importance, a significant number of genes for secondary metabolite biosynthesis (SMB) remain undetected due largely to the fact that they are highly diverse and are not expressed under a variety of cultivation conditions. Several software tools including SMURF and antiSMASH have been developed to predict fungal SMB gene clusters by finding core genes encoding polyketide synthase, nonribosomal peptide synthetase and dimethylallyltryptophan synthase as well as several others typically present in the cluster. In this work, we have devised a novel comparative genomics method to identify SMB gene clusters that is independent of motif information of the known SMB genes. The method detects SMB gene clusters by searching for a similar order of genes and their presence in nonsyntenic blocks. With this method, we were able to identify many known SMB gene clusters with the core genes in the genomic sequences of 10 filamentous fungi. Furthermore, we have also detected SMB gene clusters without core genes, including the kojic acid biosynthesis gene cluster of Aspergillus oryzae. By varying the detection parameters of the method, a significant difference in the sequence characteristics was detected between the genes residing inside the clusters and those outside the clusters.     

Identification, isolation, and analysis of a gene cluster involved in iron acquisition by Pseudomonas mendocina ymp

Microbial acquisition of iron from natural sources in aerobic environments is a little-studied process that may lead to mineral instability and trace metal mobilization. Pseudomonas mendocina ymp was isolated from the Yucca Mountain Site for long-term nuclear waste storage. Its ability to solubilize a variety of Fe-containing minerals under aerobic conditions has been previously investigated but its molecular and genetic potential remained uncharacterized. Here, we have shown that the organism produces a hydroxamate and not a catecholate-based siderophore that is synthesized via non-ribosomal peptide synthetases. Gene clustering patterns observed in other Pseudomonads suggested that hybridizing multiple probes to the same library could allow for the identification of one or more clusters of syntenic siderophore-associated genes. Using this approach, two independent clusters were identified. An unfinished draft genome sequence of P. mendocina ymp indicated that these mapped to two independent contigs. The sequenced clusters were investigated informatically and shown to contain respectively a potentially complete set of genes responsible for siderophore biosynthesis, uptake, and regulation, and an incomplete set of genes with low individual homology to siderophore-associated genes. A mutation in the cluster’s pvdA homolog (pmhA) resulted in a siderophore-null phenotype, which could be reversed by complementation. The organism likely produces one siderophore with possibly different isoforms and a peptide backbone structure containing seven residues (predicted sequence: Acyl-Asp-Dab-Ser-fOHOrn-Ser-fOHorn). A similar approach could be applied for discovery of Fe− and siderophore-associated genes in unsequenced or poorly annotated organisms.     

一种适用于链霉菌异源合成基因簇同框缺失的高效方法

【背景】对抗生素生物合成途径的阐明有助于提高目标化合物的产量并开发具有更高活性的新化合物。基因的同框缺失是天然产物生物合成研究的常规手段,通过分析突变菌株积累的中间产物,可以帮助推导天然产物的合成途径及相关基因的功能。天然产物生物合成基因簇的大小一般在20 kb以上,对每个基因进行同框缺失耗时耗力,因此,优化链霉菌来源的基因同框缺失的方法有重要的意义。【目的】基于PCR-targeting重新设计了一套在链霉菌柯斯文库质粒上进行基因同框缺失的方法,实现链霉菌基因在大肠杆菌中快速、高效的基因同框缺失的技术体系。【方法】使用氨苄青霉素抗性基因bla作为PCR-targeting DNA片段的筛选标记,同时使用体外的Pac I酶切和酶连系统代替体内的Flp/FRT系统来介导同框缺失的构建。【结果】利用这种方法,在6 d内完成了米多霉素生物合成基因簇中14个基因的同框缺失。【结论】此方法与传统的PCR-targeting方法相比,构建同框缺失载体的效率明显提高;Pac I识别序列在链霉菌基因组上的稀有性使得此方法在构建抗生素生物合成基因簇必需基因的同框缺失载体上具有普适性。     

Protein database and quantitative analysis considerations when integrating genetics and proteomics to compare mouse strains

Decades of genetics research comparing mouse strains has identified many regions of the genome associated with quantitative traits. Microarrays have been used to identify which genes in those regions are differentially expressed and are therefore potentially causal; however, genetic variants that affect probe hybridization lead to many false conclusions. Here we used spectral counting to compare brain striata between two mouse strains. Using strain-specific protein databases, we concluded that proteomics was more robust to sequence differences than microarrays; however, some proteins were still significantly affected. To generate strain-specific databases, we used a complete database that contained all of the putative genetic isoforms for each protein. While the increased proteome coverage in the databases led to a 6.8% gain in peptide assignments compared to a nonredundant database, it also necessitated the development of a strategy for grouping similar proteins due to a large number of shared peptides. Of the 4563 identified proteins (2.1% FDR), there were 1807 quantifiable proteins/groups that exceeded minimum count cutoffs. With four pooled biological replicates per strain, we used quantile normalization, ComBat (a package that adjusts for batch effects), and edgeR (a package for differential expression analysis of count data) to identify 101 differentially expressed proteins/groups, 84 of which had a coding region within one of the genomic regions of interest identified by the Portland Alcohol Research Center.     

Genome mining for ribosomally synthesized natural products

In recent years, the number of known peptide natural products that are synthesized via the ribosomal pathway has rapidly grown. Taking advantage of sequence homology among genes encoding precursor peptides or biosynthetic proteins, in silico mining of genomes combined with molecular biology approaches has guided the discovery of a large number of new ribosomal natural products, including lantipeptides, cyanobactins, linear thiazole/oxazole-containing peptides, microviridins, lasso peptides, amatoxins, cyclotides, and conopeptides. In this review, we describe the strategies used for the identification of these ribosomally synthesized and posttranslationally modified peptides (RiPPs) and the structures of newly identified compounds. The increasing number of chemical entities and their remarkable structural and functional diversity may lead to novel pharmaceutical applications.     

Coelichelin, a new peptide siderophore encoded by the Streptomyces coelicolor genome: structure prediction from the sequence of its non-ribosomal peptide synthetase

A gene cluster for the non-ribosomal synthesis of a peptide of unknown structure has been identified in the partial genome sequence of Streptomyces coelicolor. Using molecular and computational analyses, the total structure of a tripeptide siderophore synthesized by the non-ribosomal peptide synthetase within the cluster has been deduced from the translated sequence of its encoding gene. This represents a novel method for the structural assignment of natural products from genome sequence data.