RiPPMiner-Genome: A Web Resource for Automated Prediction of Crosslinked Chemical Structures of RiPPs by Genome Mining

2021 ◽  
pp. 166887 ◽  
Author(s):  
Priyesh Agrawal ◽  
Sana Amir ◽  
Deepak ◽  
Drishtee Barua ◽  
Debasisa Mohanty
Keyword(s):  
Genome Mining ◽  
Chemical Structures ◽  
Web Resource ◽  
Automated Prediction

scholarly journals Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters

2017 ◽  
Vol 20 (4) ◽  
pp. 1103-1113 ◽  
Author(s):  
Kai Blin ◽  
Hyun Uk Kim ◽  
Marnix H Medema ◽  
Tilmann Weber
Keyword(s):  
Natural Products ◽  
Small Molecules ◽  
Sequence Similarity ◽  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Rule Based ◽  
Chemical Structures ◽  
Annotation Quality

Abstract Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats such as rule-based BGC detection, sequence and annotation quality and cluster boundary prediction, which all have to be considered while planning for, performing and analyzing the results of genome mining studies.

scholarly journals Coordinated Biosynthesis of the Purine Nucleoside Antibiotics Aristeromycin and Coformycin in Actinomycetes

2018 ◽  
Vol 84 (22) ◽  
Author(s):  
Gudan Xu ◽  
Liyuan Kong ◽  
Rong Gong ◽  
Liudong Xu ◽  
Yaojie Gao ◽  
...  
Keyword(s):  
Biological Activities ◽  
Genome Mining ◽  
Combinatorial Biosynthesis ◽  
Purine Nucleoside ◽  
Enzymatic Reactions ◽  
Single Strain ◽  
Content Type ◽  
Precursor Pool ◽  
Irreversible Reaction ◽  
Chemical Structures

ABSTRACT Purine nucleoside antibiotic pairs, concomitantly produced by a single strain, are an important group of microbial natural products. Here, we report a target-directed genome mining approach to elucidate the biosynthesis of the purine nucleoside antibiotic pair aristeromycin (ARM) and coformycin (COF) in Micromonospora haikouensis DSM 45626 (a new producer for ARM and COF) and Streptomyces citricolor NBRC 13005 (a new COF producer). We also provide biochemical data that MacI and MacT function as unusual phosphorylases, catalyzing an irreversible reaction for the tailoring assembly of neplanocin A (NEP-A) and ARM. Moreover, we demonstrate that MacQ is shown to be an adenosine-specific deaminase, likely relieving the potential “excess adenosine” for producing cells. Finally, we report that MacR, an annotated IMP dehydrogenase, is actually an NADPH-dependent GMP reductase, which potentially plays a salvage role for the efficient supply of the precursor pool. Hence, these findings illustrate a fine-tuned pathway for the biosynthesis of ARM and also open the way for the rational search for purine antibiotic pairs. IMPORTANCE ARM and COF are well known for their prominent biological activities and unusual chemical structures; however, the logic of their biosynthesis has long been poorly understood. Actually, the new insights into the ARM and COF pathway will not only enrich the biochemical repertoire for interesting enzymatic reactions but may also lay a solid foundation for the combinatorial biosynthesis of this group of antibiotics via a target-directed genome mining strategy.

scholarly journals AcrFinder: genome mining anti-CRISPR operons in prokaryotes and their viruses

2020 ◽  
Vol 48 (W1) ◽  
pp. W358-W365 ◽  
Author(s):  
Haidong Yi ◽  
Le Huang ◽  
Bowen Yang ◽  
Javi Gomez ◽  
Han Zhang ◽  
...  
Keyword(s):  
Sequence Similarity ◽  
Genome Mining ◽  
Experimental Studies ◽  
Homology Search ◽  
Functional Domain ◽  
Web Interface ◽  
Web Resource ◽  
Guilt By Association ◽  
Leave One Out ◽  
User Friendly

Abstract Anti-CRISPR (Acr) proteins encoded by (pro)phages/(pro)viruses have a great potential to enable a more controllable genome editing. However, genome mining new Acr proteins is challenging due to the lack of a conserved functional domain and the low sequence similarity among experimentally characterized Acr proteins. We introduce here AcrFinder, a web server (http://bcb.unl.edu/AcrFinder) that combines three well-accepted ideas used by previous experimental studies to pre-screen genomic data for Acr candidates. These ideas include homology search, guilt-by-association (GBA), and CRISPR-Cas self-targeting spacers. Compared to existing bioinformatics tools, AcrFinder has the following unique functions: (i) it is the first online server specifically mining genomes for Acr-Aca operons; (ii) it provides a most comprehensive Acr and Aca (Acr-associated regulator) database (populated by GBA-based Acr and Aca datasets); (iii) it combines homology-based, GBA-based, and self-targeting approaches in one software package; and (iv) it provides a user-friendly web interface to take both nucleotide and protein sequence files as inputs, and output a result page with graphic representation of the genomic contexts of Acr-Aca operons. The leave-one-out cross-validation on experimentally characterized Acr-Aca operons showed that AcrFinder had a 100% recall. AcrFinder will be a valuable web resource to help experimental microbiologists discover new Anti-CRISPRs.

scholarly journals Bioactive Secondary Metabolites from Octocoral-Associated Microbes—New Chances for Blue Growth

Marine Drugs ◽  
2018 ◽  
Vol 16 (12) ◽  
pp. 485 ◽  
Author(s):  
Inês Raimundo ◽  
Sandra Silva ◽  
Rodrigo Costa ◽  
Tina Keller-Costa
Keyword(s):  
Natural Products ◽  
Genome Mining ◽  
Gene Clusters ◽  
Chemical Diversity ◽  
Chemical Structures ◽  
Novel Drugs ◽  
Blue Growth ◽  
Microbial Symbionts ◽  
Bacteria And Fungi ◽  
Near Future

Octocorals (Cnidaria, Anthozoa Octocorallia) are magnificent repositories of natural products with fascinating and unusual chemical structures and bioactivities of interest to medicine and biotechnology. However, mechanistic understanding of the contribution of microbial symbionts to the chemical diversity of octocorals is yet to be achieved. This review inventories the natural products so-far described for octocoral-derived bacteria and fungi, uncovering a true chemical arsenal of terpenes, steroids, alkaloids, and polyketides with antibacterial, antifungal, antiviral, antifouling, anticancer, anti-inflammatory, and antimalarial activities of enormous potential for blue growth. Genome mining of 15 bacterial associates (spanning 12 genera) cultivated from Eunicella spp. resulted in the identification of 440 putative and classifiable secondary metabolite biosynthetic gene clusters (BGCs), encompassing varied terpene-, polyketide-, bacteriocin-, and nonribosomal peptide-synthase BGCs. This points towards a widespread yet uncharted capacity of octocoral-associated bacteria to synthetize a broad range of natural products. However, to extend our knowledge and foster the near-future laboratory production of bioactive compounds from (cultivatable and currently uncultivatable) octocoral symbionts, optimal blending between targeted metagenomics, DNA recombinant technologies, improved symbiont cultivation, functional genomics, and analytical chemistry are required. Such a multidisciplinary undertaking is key to achieving a sustainable response to the urgent industrial demand for novel drugs and enzyme varieties.

scholarly journals Mining and Biosynthesis of Bioactive Lanthipeptides From Microorganisms

2021 ◽  
Vol 9 ◽  
Author(s):  
Caiyun Li ◽  
Khorshed Alam ◽  
Yiming Zhao ◽  
Jinfang Hao ◽  
Qing Yang ◽  
...  
Keyword(s):  
New Technologies ◽  
Genome Mining ◽  
Multidrug Resistant ◽  
Health Issues ◽  
Antimicrobial Drugs ◽  
Drug Candidates ◽  
Chemical Structures ◽  
Modified Peptides ◽  
Biosynthetic Engineering ◽  
High Diversity

Antimicrobial resistance is one of the most serious public health issues in the worldwide and only a few new antimicrobial drugs have been discovered in recent decades. To overcome the ever-increasing emergence of multidrug-resistant (MDR) pathogens, discovery of new natural products (NPs) against MDR pathogens with new technologies is in great demands. Lanthipeptides which are ribosomally synthesized and post-translationally modified peptides (RiPPs) display high diversity in their chemical structures and mechanisms of action. Genome mining and biosynthetic engineering have also yielded new lanthipeptides, which are a valuable source of drug candidates. In this review we cover the recent advances in the field of microbial derived lanthipeptide discovery and development.

scholarly journals Comparative Investigation into Formycin A and Pyrazofurin A Biosynthesis Reveals Branch Pathways for the Construction of C-Nucleoside Scaffolds

2019 ◽  
Vol 86 (2) ◽  
Author(s):  
Meng Zhang ◽  
Peichao Zhang ◽  
Gudan Xu ◽  
Wenting Zhou ◽  
Yaojie Gao ◽  
...  
Keyword(s):  
Biological Activities ◽  
Genome Mining ◽  
Gene Clusters ◽  
Combinatorial Biosynthesis ◽  
Glycosidic Bond ◽  
Enzymatic Reactions ◽  
Nucleoside Antibiotics ◽  
Enzymatic Mechanism ◽  
Chemical Structures ◽  
The Way

ABSTRACT Formycin A (FOR-A) and pyrazofurin A (PRF-A) are purine-related C-nucleoside antibiotics in which ribose and a pyrazole-derived base are linked by a C-glycosidic bond. However, the logic underlying the biosynthesis of these molecules has remained largely unexplored. Here, we report the discovery of the pathways for FOR-A and PRF-A biosynthesis from diverse actinobacteria and propose that their biosynthesis is likely initiated by a lysine N6-monooxygenase. Moreover, we show that forT and prfT (involved in FOR-A and PRF-A biosynthesis, respectively) mutants are correspondingly capable of accumulating the unexpected pyrazole-related intermediates 4-amino-3,5-dicarboxypyrazole and 3,5-dicarboxy-4-oxo-4,5-dihydropyrazole. We also decipher the enzymatic mechanism of ForT/PrfT for C-glycosidic bond formation in FOR-A/PRF-A biosynthesis. To our knowledge, ForT/PrfT represents an example of β-RFA-P (β-ribofuranosyl-aminobenzene 5ʹ-phosphate) synthase-like enzymes governing C-nucleoside scaffold construction in natural product biosynthesis. These data establish a foundation for combinatorial biosynthesis of related purine nucleoside antibiotics and also open the way for target-directed genome mining of PRF-A/FOR-A-related antibiotics. IMPORTANCE FOR-A and PRF-A are C-nucleoside antibiotics known for their unusual chemical structures and remarkable biological activities. Deciphering the enzymatic mechanism for the construction of a C-nucleoside scaffold during FOR-A/PRF-A biosynthesis will not only expand the biochemical repertoire for novel enzymatic reactions but also permit target-oriented genome mining of FOR-A/PRF-A-related C-nucleoside antibiotics. Moreover, the availability of FOR-A/PRF-A biosynthetic gene clusters will pave the way for the rational generation of designer FOR-A/PRF-A derivatives with enhanced/selective bioactivity via synthetic biology strategies.

scholarly journals Comparative investigation into formycin A and pyrazofurin A biosynthesis reveals branch pathways for the construction of C-nucleoside scaffolds

2019 ◽  
Author(s):  
Meng Zhang ◽  
Peichao Zhang ◽  
Gudan Xu ◽  
Wenting Zhou ◽  
Yaojie Gao ◽  
...  
Keyword(s):  
Biological Activities ◽  
Bond Formation ◽  
Genome Mining ◽  
Comparative Investigation ◽  
Combinatorial Biosynthesis ◽  
Glycosidic Bond ◽  
Enzymatic Reactions ◽  
Natural Product Biosynthesis ◽  
Nucleoside Antibiotics ◽  
Chemical Structures

ABSTRACTFormycin A (FOR-A) and pyrazofurin A (PRF-A) are purine-related C-nucleoside antibiotics, in which ribose and a pyrazole-derived base are linked by a C-glycosidic bond, however, the logic underlying the biosynthesis of these molecules has remained largely unexplored. Here, we report the discovery of the pathways for FOR-A and PRF-A biosynthesis from diverse actinobacteria, and demonstrate that their biosynthesis is initiated by a lysine N6-monooxygenase. Moreover, we show that the forT and prfE (individually related to FOR-A and PRF-A biosynthesis) mutants are correspondingly capable of accumulating the unexpected pyrazole-related intermediates, compound 11 and 9a. We also decipher the enzymatic basis of ForT/PrfE for the C-glycosidic bond formation in FOR-A/PRF-A biosynthesis. To our knowledge, ForT/PrfE represents the first example of β-RFA-P (β-ribofuranosyl-aminobenzene 5’-phosphate) synthase-like enzymes governing C-nucleoside scaffold construction in natural product biosynthesis. These data establish a foundation for combinatorial biosynthesis of related purine nucleoside antibiotics, and also open the way for target-directed genome mining of PRF-A/FOR-A related antibiotics.IMPORTANCEFormycin A (FOR-A) and pyrazofurin A (PRF-A) are well known for their unusual chemical structures and remarkable biological activities. Actually, deciphering FOR-A/PRF-A biosynthesis will not only expand biochemical repertoire for novel enzymatic reactions, but also permit the target-oriented genome mining of FOR-A/PRF-A related C-nucleoside antibiotics.

A machine learning-based method for prediction of macrocyclization patterns of polyketides and non-ribosomal peptides

2020 ◽  
Author(s):  
Priyesh Agrawal ◽  
Debasisa Mohanty
Keyword(s):  
Machine Learning ◽  
Polyketide Synthase ◽  
Genome Mining ◽  
Gene Clusters ◽  
Supplementary Information ◽  
Prediction Algorithm ◽  
Chemical Structures ◽  
Large Numbers ◽  
A Genome ◽  
Major Bottleneck

Abstract Motivation Even though genome mining tools have successfully identified large numbers of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) biosynthetic gene clusters (BGCs) in bacterial genomes, currently no tool can predict the chemical structure of the secondary metabolites biosynthesized by these BGCs. Lack of algorithms for predicting complex macrocyclization patterns of linear PK/NRP biosynthetic intermediates has been the major bottleneck in deciphering the final bioactive chemical structures of PKs/NRPs by genome mining. Results Using a large dataset of known chemical structures of macrocyclized PKs/NRPs, we have developed a machine learning (ML) algorithm for distinguishing the correct macrocyclization pattern of PKs/NRPs from the library of all theoretically possible cyclization patterns. Benchmarking of this ML classifier on completely independent datasets has revealed ROC–AUC and PR–AUC values of 0.82 and 0.81, respectively. This cyclization prediction algorithm has been used to develop SBSPKSv3, a genome mining tool for completely automated prediction of macrocyclized structures of NRPs/PKs. SBSPKSv3 has been extensively benchmarked on a dataset of over 100 BGCs with known PKs/NRPs products. Availability and implementation The macrocyclization prediction pipeline and all the datasets used in this study are freely available at http://www.nii.ac.in/sbspks3.html. Supplementary information Supplementary data are available at Bioinformatics online.

Chemical structure of diamond-like carbon thin films

1990 ◽  
Vol 48 (4) ◽  
pp. 710-711
Author(s):  
N.-H. Cho ◽  
K.M. Krishnan ◽  
D.B. Bogy
Keyword(s):  
Electrical Resistivity ◽  
Chemical Structure ◽  
Diamond Like Carbon ◽  
Chemical Structures ◽  
Sputtering Power ◽  
Data Aquisition ◽  
Equilibrium Phases ◽  
Electron Energy Loss ◽  
Power Densities ◽  
Preparation Techniques

Diamond-like carbon (DLC) films have attracted much attention due to their useful properties and applications. These properties are quite variable depending on film preparation techniques and conditions, DLC is a metastable state formed from highly non-equilibrium phases during the condensation of ionized particles. The nature of the films is therefore strongly dependent on their particular chemical structures. In this study, electron energy loss spectroscopy (EELS) was used to investigate how the chemical bonding configurations of DLC films vary as a function of sputtering power densities. The electrical resistivity of the films was determined, and related to their chemical structure.DLC films with a thickness of about 300Å were prepared at 0.1, 1.1, 2.1, and 10.0 watts/cm2, respectively, on NaCl substrates by d.c. magnetron sputtering. EEL spectra were obtained from diamond, graphite, and the films using a JEOL 200 CX electron microscope operating at 200 kV. A Gatan parallel EEL spectrometer and a Kevex data aquisition system were used to analyze the energy distribution of transmitted electrons. The electrical resistivity of the films was measured by the four point probe method.

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