scholarly journals Genomic analysis of siderophore β-hydroxylases reveals divergent stereocontrol and expands the condensation domain family

2019 ◽  
Vol 116 (40) ◽  
pp. 19805-19814 ◽  
Author(s):  
Zachary L. Reitz ◽  
Clifford D. Hardy ◽  
Jaewon Suk ◽  
Jean Bouvet ◽  
Alison Butler
Keyword(s):  
Predictive Power ◽  
Genome Mining ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Biosynthetic Gene Cluster ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Peptide Synthetase ◽  
Condensation Domain

Genome mining of biosynthetic pathways streamlines discovery of secondary metabolites but can leave ambiguities in the predicted structures, which must be rectified experimentally. Through coupling the reactivity predicted by biosynthetic gene clusters with verified structures, the origin of the β-hydroxyaspartic acid diastereomers in siderophores is reported herein. Two functional subtypes of nonheme Fe(II)/α-ketoglutarate–dependent aspartyl β-hydroxylases are identified in siderophore biosynthetic gene clusters, which differ in genomic organization—existing either as fused domains (IβHAsp) at the carboxyl terminus of a nonribosomal peptide synthetase (NRPS) or as stand-alone enzymes (TβHAsp)—and each directs opposite stereoselectivity of Asp β-hydroxylation. The predictive power of this subtype delineation is confirmed by the stereochemical characterization of β-OHAsp residues in pyoverdine GB-1, delftibactin, histicorrugatin, and cupriachelin. The l-threo (2S, 3S) β-OHAsp residues of alterobactin arise from hydroxylation by the β-hydroxylase domain integrated into NRPS AltH, while l-erythro (2S, 3R) β-OHAsp in delftibactin arises from the stand-alone β-hydroxylase DelD. Cupriachelin contains both l-threo and l-erythro β-OHAsp, consistent with the presence of both types of β-hydroxylases in the biosynthetic gene cluster. A third subtype of nonheme Fe(II)/α-ketoglutarate–dependent enzymes (IβHHis) hydroxylates histidyl residues with l-threo stereospecificity. A previously undescribed, noncanonical member of the NRPS condensation domain superfamily is identified, named the interface domain, which is proposed to position the β-hydroxylase and the NRPS-bound amino acid prior to hydroxylation. Through mapping characterized β-OHAsp diastereomers to the phylogenetic tree of siderophore β-hydroxylases, methods to predict β-OHAsp stereochemistry in silico are realized.

scholarly journals Genome Mining and Characterization of Biosynthetic Gene Clusters in Two Cave Strains of Paenibacillus sp.

2021 ◽  
Vol 11 ◽  
Author(s):  
Jolanta Lebedeva ◽  
Gabriele Jukneviciute ◽  
Rimvydė Čepaitė ◽  
Vida Vickackaite ◽  
Raminta Pranckutė ◽  
...  
Keyword(s):  
Genome Mining ◽  
Gene Clusters ◽  
Phenotypic Characterization ◽  
Biosynthetic Pathways ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Paenibacillus Sp ◽  
Peptide Synthetase ◽  
Non Ribosomal Peptides

The genome sequencing and mining of microorganisms from unexplored and extreme environments has become important in the process of identifying novel biosynthetic pathways. In the present study, the biosynthetic potential of Paenibacillus sp. strains 23TSA30-6 and 28ISP30-2 was investigated. Both strains were isolated from the deep oligotrophic Krubera-Voronja Cave and were found to be highly active against both Gram-positive and Gram-negative bacteria. Genome mining revealed a high number of biosynthetic gene clusters in the cave strains: 21 for strain 23TSA30-6 and 19 for strain 28ISP30-2. Single clusters encoding the biosynthesis of phosphonate, terpene, and siderophore, as well as a single trans-AT polyketide synthase/non-ribosomal peptide synthetase, were identified in both genomes. The most numerous clusters were assigned to the biosynthetic pathways of non-ribosomal peptides and ribosomally synthesized and post-translationally modified peptides. Although four non-ribosomal peptide synthetase gene clusters were predicted to be involved in the biosynthesis of known compounds (fusaricidin, polymyxin B, colistin A, and tridecaptin) of the genus Paenibacillus, discrepancies in the structural organization of the clusters, as well as in the substrate specificity of some adenylation domains, were detected between the reference pathways and the clusters in our study. Among the clusters involved in the biosynthesis of ribosomally synthesized peptides, only one was predicted to be involved in the biosynthesis of a known compound: paenicidin B. Most biosynthetic gene clusters in the genomes of the cave strains showed a low similarity with the reference pathways and were predicted to represent novel biosynthetic pathways. In addition, the cave strains differed in their potential to encode the biosynthesis of a few unique, previously unknown compounds (class II lanthipeptides and three non-ribosomal peptides). The phenotypic characterization of proteinaceous and volatile compounds produced by strains 23TSA30-6 and 28ISP30-2 was also performed, and the results were compared with those of genome mining.

scholarly journals Genomic Assemblies of Members of Burkholderia and Related Genera as a Resource for Natural Product Discovery

2020 ◽  
Vol 9 (42) ◽  
Author(s):  
Alex J. Mullins ◽  
Cerith Jones ◽  
Matthew J. Bull ◽  
Gordon Webster ◽  
Julian Parkhill ◽  
...  
Keyword(s):  
Natural Product ◽  
Genome Mining ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Natural Product Discovery

ABSTRACT The genomes of 450 members of Burkholderiaceae, isolated from clinical and environmental sources, were sequenced and assembled as a resource for genome mining. Genomic analysis of the collection has enabled the identification of multiple metabolites and their biosynthetic gene clusters, including the antibiotics gladiolin, icosalide A, enacyloxin, and cepacin A.

scholarly journals Recent advances in the genome mining of Aspergillus secondary metabolites (covering 2012–2018)

MedChemComm ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 840-866 ◽  
Author(s):  
Jillian Romsdahl ◽  
Clay C. C. Wang
Keyword(s):  
Aspergillus Terreus ◽  
Genome Mining ◽  
Gene Clusters ◽  
Genetic Identification ◽  
Biosynthetic Pathways ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
The Past ◽  
Made In

This review covers advances made in genome mining SMs produced by Aspergillus nidulans, Aspergillus fumigatus, Aspergillus niger, and Aspergillus terreus in the past six years (2012–2018). Genetic identification and molecular characterization of SM biosynthetic gene clusters, along with proposed biosynthetic pathways, is discussed in depth.

scholarly journals Activation and Identification of a Griseusin Cluster in Streptomyces sp. CA-256286 by Employing Transcriptional Regulators and Multi-Omics Methods

Molecules ◽  
2021 ◽  
Vol 26 (21) ◽  
pp. 6580
Author(s):  
Charlotte Beck ◽  
Tetiana Gren ◽  
Francisco Javier Ortiz-López ◽  
Tue Sparholt Jørgensen ◽  
Daniel Carretero-Molina ◽  
...  
Keyword(s):  
Biosynthetic Pathway ◽  
Genome Mining ◽  
Gene Clusters ◽  
Transcriptional Regulators ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Heterologous Host ◽  
Streptomyces Sp ◽  
Identification And Characterization

Streptomyces are well-known producers of a range of different secondary metabolites, including antibiotics and other bioactive compounds. Recently, it has been demonstrated that “silent” biosynthetic gene clusters (BGCs) can be activated by heterologously expressing transcriptional regulators from other BGCs. Here, we have activated a silent BGC in Streptomyces sp. CA-256286 by overexpression of a set of SARP family transcriptional regulators. The structure of the produced compound was elucidated by NMR and found to be an N-acetyl cysteine adduct of the pyranonaphtoquinone polyketide 3′-O-α-d-forosaminyl-(+)-griseusin A. Employing a combination of multi-omics and metabolic engineering techniques, we identified the responsible BGC. These methods include genome mining, proteomics and transcriptomics analyses, in combination with CRISPR induced gene inactivations and expression of the BGC in a heterologous host strain. This work demonstrates an easy-to-implement workflow of how silent BGCs can be activated, followed by the identification and characterization of the produced compound, the responsible BGC, and hints of its biosynthetic pathway.

scholarly journals MIBiG 2.0: a repository for biosynthetic gene clusters of known function

2019 ◽  
Author(s):  
Satria A Kautsar ◽  
Kai Blin ◽  
Simon Shaw ◽  
Jorge C Navarro-Muñoz ◽  
Barbara R Terlouw ◽  
...  
Keyword(s):  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene Cluster ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Data Schema ◽  
Cluster Data ◽  
Structure Databases ◽  
And Storage

Abstract Fueled by the explosion of (meta)genomic data, genome mining of specialized metabolites has become a major technology for drug discovery and studying microbiome ecology. In these efforts, computational tools like antiSMASH have played a central role through the analysis of Biosynthetic Gene Clusters (BGCs). Thousands of candidate BGCs from microbial genomes have been identified and stored in public databases. Interpreting the function and novelty of these predicted BGCs requires comparison with a well-documented set of BGCs of known function. The MIBiG (Minimum Information about a Biosynthetic Gene Cluster) Data Standard and Repository was established in 2015 to enable curation and storage of known BGCs. Here, we present MIBiG 2.0, which encompasses major updates to the schema, the data, and the online repository itself. Over the past five years, 851 new BGCs have been added. Additionally, we performed extensive manual data curation of all entries to improve the annotation quality of our repository. We also redesigned the data schema to ensure the compliance of future annotations. Finally, we improved the user experience by adding new features such as query searches and a statistics page, and enabled direct link-outs to chemical structure databases. The repository is accessible online at https://mibig.secondarymetabolites.org/.

scholarly journals PlantiSMASH: automated identification, annotation and expression analysis of plant biosynthetic gene clusters

2016 ◽  
Author(s):  
Satria A. Kautsar ◽  
Hernando G. Suarez Duran ◽  
Kai Blin ◽  
Anne Osbourn ◽  
Marnix H. Medema
Keyword(s):  
Genome Mining ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Plant Genome ◽  
Gene Clustering ◽  
Comparative Genomic ◽  
Biosynthetic Gene ◽  
Automated Identification ◽  
Biosynthetic Gene Clusters ◽  
Rich Diversity

ABSTRACTPlant specialized metabolites are chemically highly diverse, play key roles in host-microbe interactions, have important nutritional value in crops and are frequently applied as medicines. It has recently become clear that plant biosynthetic pathway-encoding genes are sometimes densely clustered in specific genomic loci: biosynthetic gene clusters (BGCs). Here, we introduce plantiSMASH, a versatile online analysis platform that automates the identification of candidate plant BGCs. Moreover, it allows integration of transcriptomic data to prioritize candidate BGCs based on the coexpression patterns of predicted biosynthetic enzyme-coding genes, and facilitates comparative genomic analysis to study the evolutionary conservation of each cluster. Applied on 48 high-quality plant genomes, plantiSMASH identifies a rich diversity of candidate plant BGCs. These results will guide further experimental exploration of the nature and dynamics of gene clustering in plant metabolism. Moreover, spurred by the continuing decrease in costs of plant genome sequencing, they will allow genome mining technologies to be applied to plant natural product discovery.The plantiSMASH web server, precalculated results and source code are freely available from http://plantismash.secondarymetabolites.org.

scholarly journals Recapitulation of the evolution of biosynthetic gene clusters reveals hidden chemical diversity on bacterial genomes

2015 ◽  
Author(s):  
Pablo Cruz-Morales ◽  
Christian E. Martínez-Guerrero ◽  
Marco A. Morales-Escalante ◽  
Luis Yáñez-Guerra ◽  
Johannes Florian Kopp ◽  
...  
Keyword(s):  
Natural Products ◽  
Chemical Space ◽  
Streptomyces Coelicolor ◽  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene Cluster ◽  
Chemical Diversity ◽  
Biosynthetic Gene ◽  
Bacterial Genomes ◽  
Biosynthetic Gene Clusters

AbstractNatural products have provided humans with antibiotics for millennia. However, a decline in the pace of chemical discovery exerts pressure on human health as antibiotic resistance spreads. The empirical nature of current genome mining approaches used for natural products research limits the chemical space that is explored. By integration of evolutionary concepts related to emergence of metabolism, we have gained fundamental insights that are translated into an alternative genome mining approach, termed EvoMining. As the founding assumption of EvoMining is the evolution of enzymes, we solved two milestone problems revealing unprecedented conversions. First, we report the biosynthetic gene cluster of the ‘orphan’ metabolite leupeptin in Streptomyces roseus. Second, we discover an enzyme involved in formation of an arsenic-carbon bond in Streptomyces coelicolor and Streptomyces lividans. This work provides evidence that bacterial chemical repertoire is underexploited, as well as an approach to accelerate the discovery of novel antibiotics from bacterial genomes.

scholarly journals Targeted Genome Mining—From Compound Discovery to Biosynthetic Pathway Elucidation

2020 ◽  
Vol 8 (12) ◽  
pp. 2034
Author(s):  
Nils Gummerlich ◽  
Yuriy Rebets ◽  
Constanze Paulus ◽  
Josef Zapp ◽  
Andriy Luzhetskyy
Keyword(s):  
Natural Products ◽  
Polyketide Synthase ◽  
Genomic Library ◽  
Mutational Analysis ◽  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene Cluster ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Feeding Experiments

Natural products are an important source of novel investigational compounds in drug discovery. Especially in the field of antibiotics, Actinobacteria have been proven to be a reliable source for lead structures. The discovery of these natural products with activity- and structure-guided screenings has been impeded by the constant rediscovery of previously identified compounds. Additionally, a large discrepancy between produced natural products and biosynthetic potential in Actinobacteria, including representatives of the order Pseudonocardiales, has been revealed using genome sequencing. To turn this genomic potential into novel natural products, we used an approach including the in-silico pre-selection of unique biosynthetic gene clusters followed by their systematic heterologous expression. As a proof of concept, fifteen Saccharothrixespanaensis genomic library clones covering predicted biosynthetic gene clusters were chosen for expression in two heterologous hosts, Streptomyceslividans and Streptomycesalbus. As a result, two novel natural products, an unusual angucyclinone pentangumycin and a new type II polyketide synthase shunt product SEK90, were identified. After purification and structure elucidation, the biosynthetic pathways leading to the formation of pentangumycin and SEK90 were deduced using mutational analysis of the biosynthetic gene cluster and feeding experiments with 13C-labelled precursors.

scholarly journals Identification and Verification of the Prodigiosin Biosynthetic Gene Cluster (BGC) in Pseudoalteromonas rubra S4059

2021 ◽  
Author(s):  
Xiyan Wang ◽  
Thomas Isbrandt ◽  
Emil Ørsted Christensen ◽  
Jette Melchiorsen ◽  
Thomas Ostenfeld Larsen ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Heterologous Expression ◽  
Gene Cluster ◽  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene Cluster ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Pseudoalteromonas Rubra

Pigmented Pseudoalteromonas strains are renowned for their production of secondary metabolites, and genome mining has revealed a high number of biosynthetic gene clusters (BGCs) for which the chemistry is unknown. Identification of those BGCs is a prerequisite for linking products to gene clusters and for further exploitation through heterologous expression.

scholarly journals Identification and Characterization of Biosynthetic Gene Clusters from Halophilic Marine Fungus Eurotium rubrum

2020 ◽  
Author(s):  
Obul Reddy Bandapali ◽  
Frederik Teilfeldt Hansen ◽  
Alisha Parveen ◽  
Pradeep Phule ◽  
Emmagouni Sharath Kumar Goud ◽  
...  
Keyword(s):  
Polyketide Synthase ◽  
Gene Clusters ◽  
Marine Fungus ◽  
Type I ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Peptide Synthetase ◽  
Future Drug ◽  
Identification And Characterization

Eurotium rubrum is a halophilic marine ascomycete, which can bear the hypersalinities of the Red Sea and proliferate, while most living entities cannot bear this condition. Recently, a 26.2 Mb assembled genome of this fungus had become available. Marine fungi are fascinating organisms capable of harboring several biosynthetic gene clusters (BGCs), which enables them to produce several natural compounds with antibiotic and anticancerous properties. Understanding the BGCs are critically important for the development of biotechnological applications and the discovery of future drugs. There is no knowledge available on the BGCs of this halophilic marine ascomycete. Herein, we set out to explore and characterize BGCs and the corresponding genes from E. rubrum using bioinformatic methods. We deciphered 36 BGCs in the genome of E. rubrum. These 36 BGCs can be grouped into four non-ribosomal peptide synthetase (NRPS) clusters, eight NRPS-like (NRPSL) BGCs, eight type I polyketide synthase (T1PKS), 11 terpene BGCs including one β-lactone cluster, four hybrid BGCs, and two siderophore BGCs. This study is an example of marine genomics application into potential future drug-like compound discovery.

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