尼日利亚和南非鱼塘中蓝藻毒素的比较分析

Odo J. Bassey, J. Gumbo, M. Mujuru, Adeeyo Adeyemi, F. Dondofema
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引用次数: 0

摘要

几十年来,水产养殖业取得了长足的发展,为国家经济做出了巨大贡献。然而,蓝藻水华的威胁威胁着养鱼业的可持续性。考虑到食物和水中的蓝藻毒素可能带来的危害,本研究采用了尼日利亚和南非商业鱼类之间的比较研究设计,以调查鱼塘水中的蓝藻毒素。研究人员选取了尼日利亚卡拉巴尔市和南非 Duthuni- 的六个商业鱼塘,这些鱼塘所处的气候带各不相同。在不同季节(夏季、冬季、旱季和雨季)间隔采集鱼塘水样,以捕捉气候引起的变化。液相色谱-质谱法(LCMS)与代谢物数据库相结合,用于鉴定水样中的有毒氰代谢物。分子网络方法与全球天然产品社会分子网络(GNPS)数据库和 CANOPUS 注释相结合,实现了对氰基代谢物的推定鉴定。由此形成的分子网络揭示了代表相关分子家族的可辨认群集,有助于识别已知的氰毒素和不熟悉的类似物。此外,分子网络还显示,尽管地点、当地气候因素和采样地点不同,但不同鱼塘的水样具有相同的特定代谢物,包括乙磺酸、嗜铬肽 A、胆酸、苯丙氨酸、戊胺、磷胆碱(PC)和磺酸。尼日利亚的鱼塘显示,在旱季、雨季和夏季,水中都存在多种蓝藻毒素。在尼日利亚的所有采样点(N1、N2 和 N3)都发现了黄曲霉毒素。南非 Duthuni 的采样点(P1、P2 和 P3)发现了微囊藻毒素和微囊藻毒素。在所选的夏季,所有鱼塘都普遍出现了氨肽酶、芹菜毒素、黄曲霉毒素、微藻毒素和海葵毒素。总之,以 GNPS 为指导的非目标代谢组分析在识别鱼塘中有毒和无毒代谢物方面证明非常有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Analysis of Cyanotoxins in Fishponds in Nigeria and South Africa
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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