Unlocking Biological Activity and Metabolomics Insights: Primary Screening of Cyanobacterial Biomass from a Tropical Reservoir

• Published in: Environmental toxicology and chemistry Vol. 43; no. 10; pp. 2222 - 2231
• Main Authors: Médice, Rhuana Valdetário, Arruda, Renan Silva, Yoon, Jaewon, Borges, Ricardo Moreira, Noyma, Natália Pessoa, Lürling, Miquel, Crnkovic, Camila Manoel, Marinho, Marcelo Manzi, Pinto, Ernani
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01-10-2024
• Subjects: Acute toxicity; Algal blooms; Biocompatibility; Bioinformatics; Biological activity; Biomass; Chemometrics; Cyanobacteria; Data integration; Eutrophic environments; Eutrophication; Information management; Liquid chromatography; Mass spectrometry; Mass spectroscopy; Metabolites; Metabolomics; Microcystins; Reservoirs; Risk management; Spectral signatures; Toxicity; Toxicology; Toxins; Water quality; Metabolomics; Cyanopeptolins; Predictive toxicology; Bioinformatics; Algal toxins; Ecological risk assessment
• ISSN: 0730-7268; 1552-8618; 1552-8618
• DOI: 10.1002/etc.5962

Cyanobacterial harmful algal blooms can pose risks to ecosystems and human health worldwide due to their capacity to produce natural toxins. The potential dangers associated with numerous metabolites produced by cyanobacteria remain unknown. Only select classes of cyanopeptides have been extensively studied with the aim of yielding substantial evidence regarding their toxicity, resulting in their inclusion in risk management and water quality regulations. Information about exposure concentrations, co-occurrence, and toxic impacts of several cyanopeptides remains largely unexplored. We used liquid chromatography-mass spectrometry (LC-MS)-based metabolomic methods associated with chemometric tools (NP Analyst and Data Fusion-based Discovery), as well as an acute toxicity essay, in an innovative approach to evaluate the association of spectral signatures and biological activity from natural cyanobacterial biomass collected in a eutrophic reservoir in southeastern Brazil. Four classes of cyanopeptides were revealed through metabolomics: microcystins, microginins, aeruginosins, and cyanopeptolins. The bioinformatics tools showed high bioactivity correlation scores for compounds of the cyanopeptolin class (0.54), in addition to microcystins (0.54-0.58). These results emphasize the pressing need for a comprehensive evaluation of the (eco)toxicological risks associated with different cyanopeptides, considering their potential for exposure. Our study also demonstrated that the combined use of LC-MS/MS-based metabolomics and chemometric techniques for ecotoxicological research can offer a time-efficient strategy for mapping compounds with potential toxicological risk. Environ Toxicol Chem 2024;43:2222-2231. © 2024 SETAC.