scholarly journals Out of the abyss: Genome and metagenome mining reveals unexpected environmental distribution of abyssomicins

2019 ◽  
Author(s):  
Alba Iglesias ◽  
Adriel Latorre-Pérez ◽  
James E. M. Stach ◽  
Manuel Porcar ◽  
Javier Pascual
Keyword(s):  
Genome Mining ◽  
Gene Clusters ◽  
Metagenomic Data ◽  
Model Organisms ◽  
Bacterial Genomes ◽  
Biosynthetic Gene Clusters ◽  
Environmental Distribution ◽  
Regulatory Systems ◽  
Terrestrial Habitats ◽  
Metagenome Mining

AbstractNatural products have traditionally been discovered through the screening of culturable microbial isolates from all sort of environments. The sequencing revolution allowed the identification of dozens of biosynthetic gene clusters (BGCs) within single bacterial genomes, either from cultured or uncultured strains. However, we are still far from fully exploiting the microbial reservoir, as most of the species are non-model organisms with complex regulatory systems and yet recalcitrant to be engineered. Today, genomic and metagenomic data produced by laboratories worldwide covering the most different natural and artificial environments on Earth, are an invaluable source of raw information from which natural product biosynthesis can be accessed. In the present work, we describe the environmental distribution and evolution of the abyssomicin BGC through the analysis of publicly available genomic and metagenomic data. Our results demonstrate that the selection of a pathway-specific enzyme to direct the genome mining is an excellent strategy that led to the identification of 74 new Diels-Alderase homologs and unveiled a surprising prevalence of the abyssomicin BGC within terrestrial habitats, mainly soil and plant-associated, where we have identified five complete and 12 partial new abyssomicin BGCs and 23 new potential abyssomicin BGCs. Our results strongly support the potential of genome and metagenome mining as a key preliminary tool to inform bioprospecting strategies aiming at the identification of new bioactive compounds such as -but not restricted to-abyssomicins.

scholarly journals Discovery and characterisation of an amidine-containing ribosomally-synthesised peptide that is widely distributed in nature

2020 ◽  
Author(s):  
Alicia H. Russell ◽  
Natalia M. Vior ◽  
Edward S. Hems ◽  
Rodney Lacret ◽  
Andrew W. Truman
Keyword(s):  
Natural Product ◽  
Genome Mining ◽  
Gene Clusters ◽  
Model Organisms ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Post Translational Modifications ◽  
Streptomyces Albus ◽  
Modified Peptides ◽  
Mining Tool

ABSTRACTRibosomally synthesised and post-translationally modified peptides (RiPPs) are a structurally diverse class of natural product with a range of bioactivities. Genome mining for RiPP biosynthetic gene clusters (BGCs) is often hampered by poor detection of the short precursor peptides that are ultimately modified into the final molecule. Here, we utilise a previously described genome mining tool, RiPPER, to identify novel RiPP precursor peptides near YcaO-domain proteins, enzymes that catalyse various RiPP post-translational modifications including heterocyclisation and thioamidation. Using this dataset, we identified a novel, diverse and highly conserved family of RiPP BGCs spanning over 230 species of Actinobacteria and Firmicutes. A representative BGC from Streptomyces albus J1074 was characterised, leading to the discovery of streptamidine, a novel-amidine containing RiPP. This highlights the breadth of unexplored natural products with structurally rare features, even in model organisms.

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 antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline

2019 ◽  
Vol 47 (W1) ◽  
pp. W81-W87 ◽  
Author(s):  
Kai Blin ◽  
Simon Shaw ◽  
Katharina Steinke ◽  
Rasmus Villebro ◽  
Nadine Ziemert ◽  
...  
Keyword(s):  
Secondary Metabolite ◽  
Polybrominated Diphenyl Ethers ◽  
Polyketide Synthase ◽  
Genome Mining ◽  
Gene Clusters ◽  
Fungal Genome ◽  
Bacterial Genomes ◽  
Biosynthetic Gene Clusters ◽  
Bacteria And Fungi ◽  
New Compounds

Abstract Secondary metabolites produced by bacteria and fungi are an important source of antimicrobials and other bioactive compounds. In recent years, genome mining has seen broad applications in identifying and characterizing new compounds as well as in metabolic engineering. Since 2011, the ‘antibiotics and secondary metabolite analysis shell—antiSMASH’ (https://antismash.secondarymetabolites.org) has assisted researchers in this, both as a web server and a standalone tool. It has established itself as the most widely used tool for identifying and analysing biosynthetic gene clusters (BGCs) in bacterial and fungal genome sequences. Here, we present an entirely redesigned and extended version 5 of antiSMASH. antiSMASH 5 adds detection rules for clusters encoding the biosynthesis of acyl-amino acids, β-lactones, fungal RiPPs, RaS-RiPPs, polybrominated diphenyl ethers, C-nucleosides, PPY-like ketones and lipolanthines. For type II polyketide synthase-encoding gene clusters, antiSMASH 5 now offers more detailed predictions. The HTML output visualization has been redesigned to improve the navigation and visual representation of annotations. We have again improved the runtime of analysis steps, making it possible to deliver comprehensive annotations for bacterial genomes within a few minutes. A new output file in the standard JavaScript object notation (JSON) format is aimed at downstream tools that process antiSMASH results programmatically.

Expanding the Natural Products Heterologous Expression Repertoire in the Model Cyanobacterium Anabaena sp. Strain PCC 7120: Production of Pendolmycin and Teleocidin B-4

2019 ◽  
Author(s):  
Patrick Videau ◽  
Kaitlyn Wells ◽  
Arun Singh ◽  
Jessie Eiting ◽  
Philip Proteau ◽  
...  
Keyword(s):  
Natural Products ◽  
Genome Mining ◽  
Gene Clusters ◽  
Combinatorial Biosynthesis ◽  
Test Case ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Cyanobacterium Anabaena ◽  
Anabaena Sp ◽  
Pcc 7120

Cyanobacteria are prolific producers of natural products and genome mining has shown that many orphan biosynthetic gene clusters can be found in sequenced cyanobacterial genomes. New tools and methodologies are required to investigate these biosynthetic gene clusters and here we present the use of <i>Anabaena </i>sp. strain PCC 7120 as a host for combinatorial biosynthesis of natural products using the indolactam natural products (lyngbyatoxin A, pendolmycin, and teleocidin B-4) as a test case. We were able to successfully produce all three compounds using codon optimized genes from Actinobacteria. We also introduce a new plasmid backbone based on the native <i>Anabaena</i>7120 plasmid pCC7120ζ and show that production of teleocidin B-4 can be accomplished using a two-plasmid system, which can be introduced by co-conjugation.

scholarly journals Identification of a New Antimicrobial, Desertomycin H, Utilizing a Modified Crowded Plate Technique

Marine Drugs ◽  
2021 ◽  
Vol 19 (8) ◽  
pp. 424
Author(s):  
Osama G. Mohamed ◽  
Sadaf Dorandish ◽  
Rebecca Lindow ◽  
Megan Steltz ◽  
Ifrah Shoukat ◽  
...  
Keyword(s):  
Antibiotic Production ◽  
Gene Clusters ◽  
Multidrug Resistant ◽  
Microbial Interactions ◽  
Mass Spectrometry Data ◽  
Metagenomic Data ◽  
Resistant Bacteria ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Plate Technique

The antibiotic-resistant bacteria-associated infections are a major global healthcare threat. New classes of antimicrobial compounds are urgently needed as the frequency of infections caused by multidrug-resistant microbes continues to rise. Recent metagenomic data have demonstrated that there is still biosynthetic potential encoded in but transcriptionally silent in cultivatable bacterial genomes. However, the culture conditions required to identify and express silent biosynthetic gene clusters that yield natural products with antimicrobial activity are largely unknown. Here, we describe a new antibiotic discovery scheme, dubbed the modified crowded plate technique (mCPT), that utilizes complex microbial interactions to elicit antimicrobial production from otherwise silent biosynthetic gene clusters. Using the mCPT as part of the antibiotic crowdsourcing educational program Tiny Earth®, we isolated over 1400 antibiotic-producing microbes, including 62, showing activity against multidrug-resistant pathogens. The natural product extracts generated from six microbial isolates showed potent activity against vancomycin-intermediate resistant Staphylococcus aureus. We utilized a targeted approach that coupled mass spectrometry data with bioactivity, yielding a new macrolactone class of metabolite, desertomycin H. In this study, we successfully demonstrate a concept that significantly increased our ability to quickly and efficiently identify microbes capable of the silent antibiotic production.

scholarly journals A global co-expression network approach for connecting genes to specialized metabolic pathways in plants

2016 ◽  
Author(s):  
Jennifer H. Wisecaver ◽  
Alexander T. Borowsky ◽  
Vered Tzin ◽  
Georg Jander ◽  
Daniel J. Kliebenstein ◽  
...  
Keyword(s):  
Genetic Basis ◽  
Meta Analysis ◽  
Null Distribution ◽  
Gene Clusters ◽  
Cytochrome P450s ◽  
Model Organisms ◽  
Biosynthetic Gene Clusters ◽  
Terpene Synthases ◽  
Specialized Metabolites ◽  
Data Source

AbstractPlants produce a tremendous diversity of specialized metabolites (SMs) to interact with and manage their environment. A major challenge hindering efforts to tap this seemingly boundless source of pharmacopeia is the identification of SM pathways and their constituent genes. Given the well-established observation that the genes comprising a SM pathway are co-regulated in response to specific environmental conditions, we hypothesized that genes from a given SM pathway would form tight associations (modules) with each other in gene co-expression networks, facilitating their identification. To evaluate this hypothesis, we used 10 global co-expression datasets—each a meta-analysis of hundreds to thousands of expression experiments—across eight plant model organisms to identify hundreds of modules of co-expressed genes for each species. In support of our hypothesis, 15.3-52.6% of modules contained two or more known SM biosynthetic genes (e.g., cytochrome P450s, terpene synthases, and chalcone synthases), and module genes were enriched in SM functions (e.g., glucoside and flavonoid biosynthesis). Moreover, modules recovered many experimentally validated SM pathways in these plants, including all six known to form biosynthetic gene clusters (BGCs). In contrast, genes predicted based on physical proximity on a chromosome to form plant BGCs were no more co-expressed than the null distribution for neighboring genes. These results not only suggest that most predicted plant BGCs do not represent genuine SM pathways but also argue that BGCs are unlikely to be a hallmark of plant specialized metabolism. We submit that global gene co-expression is a rich, but largely untapped, data source for discovering the genetic basis and architecture of plant natural products, which can be applied even without knowledge of the genome sequence.

scholarly journals Discovery of Cyanobacterial Natural Products Containing Fatty Acid Residues

2020 ◽  
Author(s):  
Sandra A. C. Figueiredo ◽  
Marco Preto ◽  
Gabriela Moreira ◽  
Teresa P. Martins ◽  
Kathleen Abt ◽  
...  
Keyword(s):  
Natural Products ◽  
Fatty Acid ◽  
Isotope Labeling ◽  
Gene Clusters ◽  
New Drugs ◽  
Beta Oxidation ◽  
Bacterial Genomes ◽  
Biosynthetic Gene Clusters ◽  
Apparent Lack ◽  
Massive Sequencing

Natural products have an important role in several human activities, most notably as sources of new drugs. In recent years, massive sequencing and annotation of bacterial genomes has revealed an unexpectedly large number of secondary metabolite biosynthetic gene clusters whose products are yet to be discovered. For example, cyanobacterial genomes contain a large number of gene clusters that likely incorporate fatty acid-derived moieties, but for most cases we lack the knowledge and tools to effectively predict or detect the encoded natural products. Here, we exploit the apparent lack of a functional beta-oxidation pathway in cyanobacteria to achieve efficient stable-isotope labeling of their fatty acid-derived lipidome. We show that supplementation of cyanobacterial cultures with deuterated fatty acids can be used to easily detect natural product signatures in individual strains. The utility of this strategy is demonstrated in two cultured cyanobacteria by uncovering analogues of the multidrug-resistance reverting hapalosin, and novel, cytotoxic, lactylate-nocuolin A hybrids – the nocuolactylates.

scholarly journals Uncovering the unexplored diversity of thioamidated ribosomal peptides in Actinobacteria using the RiPPER genome mining tool

2018 ◽  
Author(s):  
Javier Santos-Aberturas ◽  
Govind Chandra ◽  
Luca Frattaruolo ◽  
Rodney Lacret ◽  
Thu H. Pham ◽  
...  
Keyword(s):  
Genome Mining ◽  
Gene Clusters ◽  
Chemical Diversity ◽  
Bioactive Molecules ◽  
Post Translational Modification ◽  
Biosynthetic Gene Clusters ◽  
New Family ◽  
The Family ◽  
Modified Peptides ◽  
Mining Tool

ABSTRACTThe rational discovery of new specialized metabolites by genome mining represents a very promising strategy in the quest for new bioactive molecules. Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a major class of natural product that derive from genetically encoded precursor peptides. However, RiPP gene clusters are particularly refractory to reliable bioinformatic predictions due to the absence of a common biosynthetic feature across all pathways. Here, we describe RiPPER, a new tool for the family-independent identification of RiPP precursor peptides and apply this methodology to search for novel thioamidated RiPPs in Actinobacteria. Until now, thioamidation was believed to be a rare post-translational modification, which is catalyzed by a pair of proteins (YcaO and TfuA) in Archaea. In Actinobacteria, the thioviridamide-like molecules are a family of cytotoxic RiPPs that feature multiple thioamides, and it has been proposed that a YcaO-TfuA pair of proteins also catalyzes their formation. Potential biosynthetic gene clusters encoding YcaO and TfuA protein pairs are common in Actinobacteria but the chemical diversity generated by these pathways is almost completely unexplored. A RiPPER analysis reveals a highly diverse landscape of precursor peptides encoded in previously undescribed gene clusters that are predicted to make thioamidated RiPPs. To illustrate this strategy, we describe the first rational discovery of a new family of thioamidated natural products, the thiovarsolins from Streptomyces varsoviensis.

scholarly journals Discovery of Unusual Cyanobacterial Tryptophan-containing Anabaenopeptins by MS/MS Based Molecular Networking

2020 ◽  
Author(s):  
Subhasish Saha ◽  
Germana Esposito ◽  
Petra Urajova ◽  
Jan Mareš ◽  
Daniela Ewe ◽  
...  
Keyword(s):  
Multidisciplinary Approach ◽  
Spectroscopic Analysis ◽  
Chemical Space ◽  
Genome Mining ◽  
Gc Content ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Hela Cell Lines ◽  
Bioactive Secondary Metabolites

Heterocytous cyanobacteria are among the most prolific source of bioactive secondary metabolites, including anabaenopeptins (APTs). A terrestrial filamentous Brasilonema sp. CT11 collected in Costa Rica bamboo forest, as black mat was studied using a multidisciplinary approach: genome mining and HPLC-HRMS/MS coupled with bionformatic analyses. Herein, we report the nearly complete genome consisting 8.79 Mbp with a GC content of 42.4%. Moreover, we report on three novel tryptophane-containing APTs; anabaenopeptin 788 (1), anabaenopeptin 802 (2) and anabaenopeptin 816 (3). Further, the structure of two homologues, i.e., anabaenopeptin 802 (2a) and anabaenopeptin 802 (2b) was determined by spectroscopic analysis (NMR and MS). Both compounds were shown to exert weak to moderate antiproliferative activity against HeLa cell lines. This study also provides the unique and diverse potential of biosynthetic gene clusters and an assessment of the predicted chemical space yet to be discovered from this genus.

scholarly journals IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites

mBio ◽  
2015 ◽  
Vol 6 (4) ◽  
Author(s):  
Michalis Hadjithomas ◽  
I-Min Amy Chen ◽  
Ken Chu ◽  
Anna Ratner ◽  
Krishna Palaniappan ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Secondary Metabolism ◽  
Genomic Data ◽  
Gene Clusters ◽  
Metagenomic Data ◽  
Integrated Analysis ◽  
Analysis Tool ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Analysis Tools

ABSTRACTIn the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time inAlphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules.IMPORTANCEIMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

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