Molecular-networking-based characterization of cytotoxic metabolites produced by the cyanobacterium Nostoc edaphicum...

Cyanobacteria of the genus Nostoc, known for their large genomes and rich repertoire of biosynthetic gene clusters, represent a prolific source of structurally diverse secondary metabolites with diverse biological activities, including cytotoxic effects. However, the identification of bioactive compounds is often hindered by low metabolite abundance and difficulties in isolating sufficient quantities for individual testing. In this study, we investigated the cytotoxic potential of chromatographic fractions obtained from Nostoc edaphicum CCNP1411 using a combination of bioassay-guided fractionation and LC-MS/MS-based feature-based molecular networking (FBMN). Cytotoxic activity was evaluated using the MTT assay across a panel of epithelial and neuronal cancer cell lines, as well as normal human dermal fibroblasts. The most active fractions, eluted with 80-90% MeOH, exhibited broad cytotoxic effects across all tested cancer cell lines. Molecular networking analysis revealed that these fractions were dominated by lipid derivatives, including lysophospholipids, monoacylglycerols, and free fatty acids, whereas previously described peptide metabolites were distributed across all fractions and were unlikely to be the main agents responsible for the observed activity. Targeted testing of selected commercially available lipid compounds confirmed their cytotoxic effects, with lysophospholipids showing the highest potency in selected cell lines. However, dose-response analysis indicated that most compounds exhibited limited potency at lower concentrations, as reflected by relatively high IC₅₀ values. Overall, our results demonstrate that lipid constituents, previously overlooked as bioactive metabolites produced by N. edaphicum CCNP1411, contribute significantly to the cytotoxic activity of the tested fractions. The application of molecular networking enabled the prioritization of bioactive metabolites and highlights its utility in linking chemical composition with biological effects in complex cyanobacterial extracts.