Nejvíce citovaný článek - PubMed ID 26284661
Minimum Information about a Biosynthetic Gene cluster
Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.
Cyanobacteria require iron for growth and often inhabit iron-limited habitats, yet only a few siderophores are known to be produced by them. We report that cyanobacterial genomes frequently encode polyketide synthase (PKS)/nonribosomal peptide synthetase (NRPS) biosynthetic pathways for synthesis of lipopeptides featuring β-hydroxyaspartate (β-OH-Asp), a residue known to be involved in iron chelation. Iron starvation triggered the synthesis of β-OH-Asp lipopeptides in the cyanobacteria Rivularia sp. strain PCC 7116, Leptolyngbya sp. strain NIES-3755, and Rubidibacter lacunae strain KORDI 51-2. The induced compounds were confirmed to bind iron by mass spectrometry (MS) and were capable of Fe3+ to Fe2+ photoreduction, accompanied by their cleavage, when exposed to sunlight. The siderophore from Rivularia, named cyanochelin A, was structurally characterized by MS and nuclear magnetic resonance (NMR) and found to contain a hydrophobic tail bound to phenolate and oxazole moieties followed by five amino acids, including two modified aspartate residues for iron chelation. Phylogenomic analysis revealed 26 additional cyanochelin-like gene clusters across a broad range of cyanobacterial lineages. Our data suggest that cyanochelins and related compounds are widespread β-OH-Asp-featuring cyanobacterial siderophores produced by phylogenetically distant species upon iron starvation. Production of photolabile siderophores by phototrophic cyanobacteria raises questions about whether the compounds facilitate iron monopolization by the producer or, rather, provide Fe2+ for the whole microbial community via photoreduction. IMPORTANCE All living organisms depend on iron as an essential cofactor for indispensable enzymes. However, the sources of bioavailable iron are often limited. To face this problem, microorganisms synthesize low-molecular-weight metabolites capable of iron scavenging, i.e., the siderophores. Although cyanobacteria inhabit the majority of the Earth's ecosystems, their repertoire of known siderophores is remarkably poor. Their genomes are known to harbor a rich variety of gene clusters with unknown function. Here, we report the awakening of a widely distributed class of silent gene clusters by iron starvation to yield cyanochelins, β-hydroxy aspartate lipopeptides involved in iron acquisition. Our results expand the limited arsenal of known cyanobacterial siderophores and propose products with ecological function for a number of previously orphan gene clusters.
- Klíčová slova
- cyanobacteria, iron acquisition, lipopeptides, secondary metabolism, siderophores,
- MeSH
- bakteriální proteiny genetika metabolismus MeSH
- biosyntetické dráhy MeSH
- fylogeneze MeSH
- lipopeptidy metabolismus MeSH
- multigenová rodina * MeSH
- peptidsynthasy genetika metabolismus MeSH
- polyketidsynthasy genetika metabolismus MeSH
- siderofory biosyntéza MeSH
- sinice klasifikace enzymologie genetika metabolismus MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- bakteriální proteiny MeSH
- lipopeptidy MeSH
- non-ribosomal peptide synthase MeSH Prohlížeč
- peptidsynthasy MeSH
- polyketidsynthasy MeSH
- siderofory MeSH
Streptomyces are among the most promising genera in terms of production ability to biosynthesize a variety of bioactive secondary metabolites with pharmaceutical interest. Coinciding with the increase in genomic sequencing of these bacteria, mining of their genomes for biosynthetic gene clusters (BGCs) has become a routine component of natural product discovery. Herein, we describe the isolation and characterization of a Streptomyces tendae VITAKN with quorum sensing inhibitory (QSI) activity that was isolated from southern coastal part of India. The nearly complete genome consists of 8,621,231bp with a GC content of 72.2%. Sequence similarity networks of the BGCs detected from this strain against the Minimum Information about a Biosynthetic Gene Cluster (MIBiG) database and 3365 BGCs predicted by antiSMASH analysis of publicly available complete Streptomyces genomes were generated through the BiG-SCAPE-CORASON platform to evaluate its biosynthetic novelty. Crude extract analysis using high-performance liquid chromatography connected to high resolution tandem mass spectrometry (HPLC-HRMS/MS) and dereplication through the Global Natural Product Social Molecular Networking (GNPS) online workflow resulted in the identification of cyclic dipeptides (2, 5-diketopiperazines, DKPs) in the extract, which are known to possess QSI activity. Our results highlight the potential of genome mining coupled with LC-HRMS/MS and in silico tools (GNPS) as a valid approach for the discovery of novel QSI lead compounds. This study also provides the biosynthetic diversity of BGCs and an assessment of the predicted chemical space yet to be discovered.
Natural products represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs, anticancer therapies, and immunomodulatory agents. These molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms, although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers reduced false positive rates in BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing machine-learning tools. We supplemented this with random forest classifiers that accurately predicted BGC product classes and potential chemical activity. Application of DeepBGC to bacterial genomes uncovered previously undetectable putative BGCs that may code for natural products with novel biologic activities. The improved accuracy and classification ability of DeepBGC represents a major addition to in-silico BGC identification.
Oceanic harmful algal blooms of Pseudo-nitzschia diatoms produce the potent mammalian neurotoxin domoic acid (DA). Despite decades of research, the molecular basis for its biosynthesis is not known. By using growth conditions known to induce DA production in Pseudo-nitzschia multiseries, we implemented transcriptome sequencing in order to identify DA biosynthesis genes that colocalize in a genomic four-gene cluster. We biochemically investigated the recombinant DA biosynthetic enzymes and linked their mechanisms to the construction of DA's diagnostic pyrrolidine skeleton, establishing a model for DA biosynthesis. Knowledge of the genetic basis for toxin production provides an orthogonal approach to bloom monitoring and enables study of environmental factors that drive oceanic DA production.
- MeSH
- eutrofizace * MeSH
- kyselina kainová analogy a deriváty chemie metabolismus MeSH
- multigenová rodina MeSH
- neurotoxiny biosyntéza genetika MeSH
- rekombinantní proteiny genetika metabolismus MeSH
- rozsivky genetika metabolismus MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Názvy látek
- domoic acid MeSH Prohlížeč
- kyselina kainová MeSH
- neurotoxiny MeSH
- rekombinantní proteiny MeSH
This review aims at comparing some historical data with the current situation in the study of biogenesis of natural compounds, antibiotics in the first place. Biogenesis of tetracyclines and cycloheximide and related compounds serves as example. Examples of molecular biological and bioinformatics methods used in the study of antibiotic biogenesis are described both in terms of its historical aspects and the current knowledge.
- MeSH
- antibakteriální látky biosyntéza metabolismus MeSH
- dějiny 20. století MeSH
- dějiny 21. století MeSH
- metabolické sítě a dráhy genetika MeSH
- objevování léků dějiny MeSH
- výpočetní biologie MeSH
- Check Tag
- dějiny 20. století MeSH
- dějiny 21. století MeSH
- Publikační typ
- časopisecké články MeSH
- historické články MeSH
- přehledy MeSH
- Názvy látek
- antibakteriální látky MeSH
