Over the decades, the aquaculture sector has witnessed substantial growth, contributing significantly to the nation’s economy. However, the menace of CyanoHABs threatens the sustainability of fish farming. Considering the possible hazards linked to cyanotoxins in food and water, a comparative study design between commercial fish in Nigeria and South Africa was employed to investigate cyanotoxins in the water from fishponds. Six commercial fishponds in Calabar Municipality—Nigeria and Duthuni—South Africa with varying climatic zones were selected. Water samples from the ponds were collected at intervals during different seasons (summer, winter, dry, and wet seasons) to capture climate-induced variation. Liquid chromatography–mass spectrometry (LCMS) in combination with the metabolites database was used for the identification of toxic cyanometabolites in water samples. The molecular networking approach, coupled with the Global Natural Products Social Molecular Networking (GNPS) database and CANOPUS annotation, enabled the putative identification of cyanometabolites. The resulting molecular network unveiled discernible clusters representing related molecule families, aiding in the identification of both known cyanotoxins and unfamiliar analogues. Furthermore, the molecular network revealed that water samples from different fishponds shared specific metabolites, including ethanesulfonic acid, pheophorbide A, cholic acid, phenylalanine, amyl amine, phosphocholine (PC), and sulfonic acid, despite variations in location, local climatic factors, and sampling sites. The fishponds in Nigeria showed the presence of multiple cyanotoxin classes in the dry, wet, and summer seasons in the water. Aflatoxin was identified in all sampling sites in Nigeria (N1, N2, and N3). The Duthuni, South Africa, sampling sites (P1, P2, and P3) exhibited the presence of microginins and microcystins. All the fishponds displayed a widespread occurrence of anabaenopeptins, aplysiatoxins, aflatoxin, microcolins, and marabmids during the selected summer. In conclusion, the untargeted metabolome analysis, guided by GNPS, proved highly effective in identifying both toxic and non-toxic metabolites in fishponds.
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