MassIVE MSV000085840

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GNPS - Dataset Creation from GNPS Molcular Networking - c2034223333641b3a06a72b40d27b2e4

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Description

Man-made shallow fishponds in the Czech Republic have been facing a high eutrophication since 1950s. Anthropogenic eutrophication and feeding of fish have strongly affected the physico-chemical properties of water and its aquatic community composition leading to harmful algal bloom formation. In our current study, we have characterised the phytoplankton community across three hypertrophic ponds to assess the phytoplankton dynamics during the vegetation season. We microscopically identified and quantified 29 cyanobacterial taxa comprised of 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 dereplication strategy. This MS networking approach led us to putatively identify forty CNPs: fourteen anabaenopeptins, ten microcystins, five cyanopeptolins, six microginins, two cyanobactins, a dipeptide radiosumin, a cyclooctapeptide planktocyclin and epidolastatin12. The combination of molecular networking and dereplication on online global natural product social networking (GNPS) web platform has proved as a valuable approach for rapid and simultaneous detection of high number of peptides, and rapidly assessing the risk for harmful bloom. [doi:10.25345/C5MB3P] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: cyanobacteria ; cyanopeptides ; eutrophication ; harmful bloom

Contact

Principal Investigators:
(in alphabetical order) 		Kumar Saurav, Centrum Algatech, Institute of Microbiology, Czech Academy of Sciences, Czechia
Submitting User: sauravverma17

Publications

Kust A, ?eháková K, Vrba J, Maicher V, Mareš J, Hrouzek P, Chiriac MC, Benedová Z, Tesa?ová B, Saurav K.
Insight into Unprecedented Diversity of Cyanopeptides in Eutrophic Ponds Using an MS/MS Networking Approach.
Toxins (Basel). Epub 2020 Aug 31.

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GNPS content goes here (MSV000085840 [task=5dc59493fa39486eaba3445e29d3e542])
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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.