Abstract
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.
Highlights
Cyanobacteria are important primary producers in the food chain with high nutritional value [1]and tend to proliferate, forming dense blooms, scums, and floating mats under favorable environmental conditions [2,3]
The most frequently reported cyanotoxins can be classified as cyclic oligopeptides (i.e., microcystins (MCs) and nodularins (NODs)) or alkaloids based on their chemical structures, and as hepatotoxins, neurotoxins, and dermatotoxins based on their mechanism of toxic action in vertebrates [6,7]
The metabolic composition was determined by leveraging the global natural product social networking (GNPS) online workflow in silico tools and molecular networking to obtain a complete CNP profile of cyanobacterial proliferation of the studied ponds
Summary
Cyanobacteria are important primary producers in the food chain with high nutritional value [1]. Further introduction of an in-silico annotation tool (such as Dereplicator+) at the GNPS online workflow has revolutionized the detection of known/unknown natural products by comparing experimental MS/MS spectra against chemical structure databases. These tools enable the analyses and curation of hundreds to thousands of obtained. MS/MS data from analytes within the extract, which is almost impossible to analyze manually [26] Recent application of these tools in the field of annotating metabolites from cyanobacterial bloom has led to the discovery of various novel compounds as well as unknown analogs [27,28,29,30]. The metabolic composition was determined by leveraging the GNPS online workflow in silico tools and molecular networking to obtain a complete CNP profile of cyanobacterial proliferation of the studied ponds
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