Insight into Unprecedented Diversity of Cyanopeptides in Eutrophic Ponds Using an MS/MS Networking Approach

Toxins

Maria-Cecilia Chiriac¹  Klára Řeháková¹  Jaroslav Vrba¹  Blanka Tesařová²  Zdeňka Benedová²  Andreja Kust³  Kumar Saurav³  Jan Mareš³  Pavel Hrouzek³  Vincent Maicher⁴ 

[1] Biology Centre of the Czech Academy of Sciences, Institute of Hydrobiology, 37005 České Budějovice, Czech Republic;ENKI, o.p.s. Třeboň, Dukelská 145, 37901 Třeboň, Czech Republic;Laboratory of Algal Biotechnology-Centre Algatech, Institute of Microbiology of the Czech Academy of Sciences, 37901 Třeboň, Czech Republic;Nicholas School of the Environment, Duke University, Durham, NC 27710, USA;

关键词: cyanobacteria;    cyanopeptides;    harmful bloom;    liquid chromatography-tandem mass spectrometry;    global natural product social networking (GNPS);    dereplication strategy;   

DOI  :  10.3390/toxins12090561

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown