global natural product social networking (GNPS) Dotaz Zobrazit nápovědu
Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.
- MeSH
- biologické přípravky chemie MeSH
- databáze faktografické MeSH
- hmotnostní spektrometrie * MeSH
- metabolomika metody MeSH
- software MeSH
- výpočetní biologie metody MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- Názvy látek
- biologické přípravky MeSH
Man-made shallow fishponds in the Czech Republic have been facing high eutrophication since the 1950s. Anthropogenic eutrophication and feeding of fish have strongly affected the physicochemical properties of water and its aquatic community composition, leading to harmful algal bloom formation. In our current study, we characterized the phytoplankton community across three eutrophic ponds to assess the phytoplankton dynamics during the vegetation season. We microscopically identified and quantified 29 cyanobacterial taxa comprising non-toxigenic and toxigenic species. Further, a detailed cyanopeptides (CNPs) profiling was performed using molecular networking analysis of liquid chromatography-tandem mass spectrometry (LC-MS/MS) data coupled with a dereplication strategy. This MS networking approach, coupled with dereplication, on the online global natural product social networking (GNPS) web platform led us to putatively identify forty CNPs: fourteen anabaenopeptins, ten microcystins, five cyanopeptolins, six microginins, two cyanobactins, a dipeptide radiosumin, a cyclooctapeptide planktocyclin, and epidolastatin 12. We applied the binary logistic regression to estimate the CNPs producers by correlating the GNPS data with the species abundance. The usage of the GNPS web platform proved a valuable approach for the rapid and simultaneous detection of a large number of peptides and rapid risk assessments for harmful blooms.
- Klíčová slova
- cyanobacteria, cyanopeptides, dereplication strategy, global natural product social networking (GNPS), harmful bloom, liquid chromatography-tandem mass spectrometry,
- MeSH
- bakteriální toxiny analýza toxicita MeSH
- hmotnostní spektrometrie s elektrosprejovou ionizací * MeSH
- hodnocení rizik MeSH
- metabolomika MeSH
- mikrobiologie vody MeSH
- mikrobiota MeSH
- monitorování životního prostředí * MeSH
- mořské toxiny analýza toxicita MeSH
- online sociální sítě * MeSH
- populační dynamika MeSH
- roční období MeSH
- rybníky mikrobiologie MeSH
- sinice klasifikace růst a vývoj metabolismus MeSH
- škodlivý vodní květ * MeSH
- tandemová hmotnostní spektrometrie * MeSH
- vysokoúčinná kapalinová chromatografie * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
- Názvy látek
- bakteriální toxiny MeSH
- mořské toxiny 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.
The rapid emergence of resistance in pathogenic bacteria together with a steep decline in economic incentives has rendered a new wave in the drug development by the pharmaceutical industry and researchers. Since cyanobacteria are recognized as wide producers of pharmaceutically important compounds, we investigated thirty-four cyanobacterial extracts prepared by solvents of different polarities for their antimicrobial potential. Almost all tested cyanobacterial strains exhibited some degree of antimicrobial bioactivity, with more general effect on fungal strains compared with bacteria. Surprisingly ~50% of cyanobacterial extracts exhibited specific activity against one or few bacterial indicator strains with Gram-positive bacteria being more affected. Extracts of two most promising strains were subjected to activity-guided fractionation and determination of the minimum inhibitory concentration (MIC) against selected bacterial and fungal isolates. Multiple fractions were responsible for their antimicrobial effect with MIC reaching low-micromolar concentrations and in some of them high level of specificity was recorded. Twenty-six bioactive fractions analyzed on LC-HRMS/MS and Global Natural Product Social Molecular Networking (GNPS) online workflow using dereplication resulted in identification of only forty-nine peptide spectrum matches (PSMs) with eleven unique metabolites spectrum matches (MSMs). Interestingly, only three fractions from Nostoc calcicola Lukešová 3/97 and four fractions from Desmonostoc sp. Cc2 showed the presence of unique MSMs suggesting the presence of unknown antimicrobial metabolites among majority of bioactive fractions from both the strains. Our results highlight potential for isolation and discovery of potential antimicrobial bioactive lead molecules from cyanobacterial extracts.
