scholarly journals SYN-View: A Phylogeny-Based Synteny Exploration Tool for the Identification of Gene Clusters Linked to Antibiotic Resistance

Molecules ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 144
Author(s):  
Jason Stahlecker ◽  
Erik Mingyar ◽  
Nadine Ziemert ◽  
Mehmet Direnç Mungan
Keyword(s):  
Natural Products ◽  
Pathogenic Bacteria ◽  
Target Genes ◽  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene Clusters ◽  
Antibiotic Resistant ◽  
The Arts ◽  
Exploration Tool

The development of new antibacterial drugs has become one of the most important tasks of the century in order to overcome the posing threat of drug resistance in pathogenic bacteria. Many antibiotics originate from natural products produced by various microorganisms. Over the last decades, bioinformatical approaches have facilitated the discovery and characterization of these small compounds using genome mining methodologies. A key part of this process is the identification of the most promising biosynthetic gene clusters (BGCs), which encode novel natural products. In 2017, the Antibiotic Resistant Target Seeker (ARTS) was developed in order to enable an automated target-directed genome mining approach. ARTS identifies possible resistant target genes within antibiotic gene clusters, in order to detect promising BGCs encoding antibiotics with novel modes of action. Although ARTS can predict promising targets based on multiple criteria, it provides little information about the cluster structures of possible resistant genes. Here, we present SYN-view. Based on a phylogenetic approach, SYN-view allows for easy comparison of gene clusters of interest and distinguishing genes with regular housekeeping functions from genes functioning as antibiotic resistant targets. Our aim is to implement our proposed method into the ARTS web-server, further improving the target-directed genome mining strategy of the ARTS pipeline.

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 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 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 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 A Multi-Omics Characterization of the Natural Product Potential of Tropical Filamentous Marine Cyanobacteria

Marine Drugs ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 20
Author(s):  
Tiago Leão ◽  
Mingxun Wang ◽  
Nathan Moss ◽  
Ricardo da Silva ◽  
Jon Sanders ◽  
...  
Keyword(s):  
Natural Products ◽  
Natural Product ◽  
Genome Mining ◽  
Gene Clusters ◽  
Microbial Interactions ◽  
Marine Cyanobacteria ◽  
Pharmaceutical Drugs ◽  
Genes Encoding ◽  
Microbial Natural Products

Microbial natural products are important for the understanding of microbial interactions, chemical defense and communication, and have also served as an inspirational source for numerous pharmaceutical drugs. Tropical marine cyanobacteria have been highlighted as a great source of new natural products, however, few reports have appeared wherein a multi-omics approach has been used to study their natural products potential (i.e., reports are often focused on an individual natural product and its biosynthesis). This study focuses on describing the natural product genetic potential as well as the expressed natural product molecules in benthic tropical cyanobacteria. We collected from several sites around the world and sequenced the genomes of 24 tropical filamentous marine cyanobacteria. The informatics program antiSMASH was used to annotate the major classes of gene clusters. BiG-SCAPE phylum-wide analysis revealed the most promising strains for natural product discovery among these cyanobacteria. LCMS/MS-based metabolomics highlighted the most abundant molecules and molecular classes among 10 of these marine cyanobacterial samples. We observed that despite many genes encoding for peptidic natural products, peptides were not as abundant as lipids and lipopeptides in the chemical extracts. Our results highlight a number of highly interesting biosynthetic gene clusters for genome mining among these cyanobacterial samples.

scholarly journals A widespread family of bacterial gene clusters produces ClpP inhibitors

2021 ◽  
Author(s):  
Gerry Wright ◽  
Elizabeth Culp ◽  
David Sychantha ◽  
Christian Hobson ◽  
Andrew Pawlowski ◽  
...  
Keyword(s):  
Pathogenic Bacteria ◽  
Genome Mining ◽  
Antibiotic Resistance Genes ◽  
Gene Clusters ◽  
Biosynthetic Gene Clusters ◽  
Bacterial Gene ◽  
Clinical Potential ◽  
Novel Scaffold

Abstract Intracellular proteolytic complexes play an essential role in modeling the proteome in both bacteria and eukaryotes. ClpP is the protease subunit of one such highly conserved proteolytic complex that, despite its potential, remains unexploited as a drug target. Here we describe a target-directed genome mining strategy to identify ClpP targeting compounds from the bacterial order Actinomycetales. By searching for biosynthetic gene clusters that contain duplicated copies of ClpP as putative antibiotic resistance genes, we identify a family of ClpP-associated clusters that are widespread across phyla, including environmental and pathogenic bacteria. While numerous bacterial pyrrolizidine alkaloids produced by these gene clusters are known, their connection to ClpP has never been made. We show that these previously characterized molecules do not affect ClpP function but are shunt metabolites derived from the genuine product of these gene clusters, a reactive covalent ClpP inhibitor. Focusing on one such cryptic gene cluster from Streptomyces cattleya DSM 46488, we use heterologous expression to purify the relevant ClpP inhibitor, which we name clipibicyclene. We show in vitro and in vivo that clipibicyclene is a potent covalent inhibitor of ClpP and that cluster-associated ClpPs provide resistance. ClpP inhibition results in antibacterial activity against actinobacteria, including Mycobacterium smegmatis, and inhibition of virulence factor production by Staphylococcus aureus. Finally, we solve the crystal structure of clipibicyclene-modified Escherichia coli ClpP. Clipibicyclene’s discovery deconvolutes the actual function of a family of natural products widespread in nature. It provides a novel scaffold for therapeutic ClpP inhibitor development, making these findings significant from the perspective of their discovery and their clinical potential.

scholarly journals On the Risks of Phylogeny-Based Strain Prioritization for Drug Discovery: Streptomyces lunaelactis as a Case Study

Biomolecules ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1027 ◽  
Author(s):  
Loïc Martinet ◽  
Aymeric Naômé ◽  
Dominique Baiwir ◽  
Edwin De Pauw ◽  
Gabriel Mazzucchelli ◽  
...  
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Reference Strain ◽  
Pattern Analysis ◽  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Representative Strain

Strain prioritization for drug discovery aims at excluding redundant strains of a collection in order to limit the repetitive identification of the same molecules. In this work, we wanted to estimate what can be unexploited in terms of the amount, diversity, and novelty of compounds if the search is focused on only one single representative strain of a species, taking Streptomyces lunaelactis as a model. For this purpose, we selected 18 S. lunaelactis strains taxonomically clustered with the archetype strain S. lunaelactis MM109T. Genome mining of all S. lunaelactis isolated from the same cave revealed that 54% of the 42 biosynthetic gene clusters (BGCs) are strain specific, and five BGCs are not present in the reference strain MM109T. In addition, even when a BGC is conserved in all strains such as the bag/fev cluster involved in bagremycin and ferroverdin production, the compounds produced highly differ between the strains and previously unreported compounds are not produced by the archetype MM109T. Moreover, metabolomic pattern analysis uncovered important profile heterogeneity, confirming that identical BGC predisposition between two strains does not automatically imply chemical uniformity. In conclusion, trying to avoid strain redundancy based on phylogeny and genome mining information alone can compromise the discovery of new natural products and might prevent the exploitation of the best naturally engineered producers of specific molecules.

scholarly journals Synthetic Biology Advanced Natural Product Discovery

Metabolites ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 785
Author(s):  
Junyang Wang ◽  
Jens Nielsen ◽  
Zihe Liu
Keyword(s):  
Natural Products ◽  
Synthetic Biology ◽  
Natural Product ◽  
Rapid Development ◽  
Genome Mining ◽  
Gene Clusters ◽  
Future Research ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Natural Product Discovery

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a limited number of natural products have been discovered, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels under conventional laboratory conditions. With the rapid development of synthetic biology, advanced genome mining and engineering strategies have been reported and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions.

scholarly journals Identification of a Tambjamine Gene Cluster in Streptomyces Reveals Convergent Evolution of the Biosynthetic Pathway

2020 ◽  
Author(s):  
Neil L Grenade ◽  
Dragos S. Chiriac ◽  
Graeme W. Howe ◽  
Avena Ross
Keyword(s):  
Natural Products ◽  
De Novo ◽  
Sequence Similarity ◽  
Genome Mining ◽  
Gene Clusters ◽  
Primary Metabolism ◽  
Biosynthetic Gene Clusters ◽  
Microbial Genomes ◽  
Sequence Similarity Networks ◽  
Related Compounds

Bacterial natural products are an immensely valuable source of therapeutics. As modern DNA sequencing efforts provide increasing numbers of microbial genomes, it is clear that the molecules produced by most natural product biosynthetic gene clusters (BGCs) remain unknown. Genome mining makes use of bioinformatic techniques to elucidate the natural products produced by these “orphan” BGCs. Here, we report the use of sequence similarity networks (SSNs) and genome neighborhood networks (GNNs) to identify an orphan BGC that is responsible for the production of the antitumor tambjamine BE-18591 in Streptomyces albus NRRL B-2362. Although BE-18591 is a close structural analogue of tambjamine YP1 produced by Pseudoalteromonas tunicata, the biosynthetic routes to produce these molecules differ significantly. Notably, the C12-alkylamine tail that is appended onto the bipyrrole core of tambjamine YP1 is derived from fatty acids siphoned from the primary metabolism of the pseudoalteromonad, whilst the S. albus NRRL B-2362 BGC encodes a dedicated system for the de novo biosynthesis of the alkylamine portion of tambjamine BE-18591. These remarkably different biosynthetic strategies represent a striking example of convergent BGC evolution, with selective pressure for the production of tambjamines seemingly leading to the emergence of separate biosynthetic pathways in pseudoalteromonads and streptomycetes that ultimately produce closely related compounds

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