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解锁生物活性和代谢组学见解:热带水库中蓝细菌生物量的初步筛选。

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

机构信息

Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, SP, Brazil.

Department of Plant Biology, Rio de Janeiro State University, Rio de Janeiro, RJ, Brazil.

出版信息

Environ Toxicol Chem. 2024 Oct;43(10):2222-2231. doi: 10.1002/etc.5962. Epub 2024 Aug 7.

Abstract

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.

摘要

蓝藻有害藻华因其产生天然毒素的能力而在全球范围内对生态系统和人类健康构成威胁。蓝藻产生的众多代谢物所带来的潜在危险仍不清楚。只有少数几类蓝藻肽被广泛研究,目的是为其毒性提供大量证据,从而将其纳入风险管理和水质法规。关于几种蓝藻肽的暴露浓度、共同出现和毒性影响的信息在很大程度上仍未得到探索。我们使用基于液相色谱-质谱 (LC-MS) 的代谢组学方法和化学计量学工具(NP Analyst 和基于数据融合的发现)以及急性毒性试验,以创新的方式评估了从巴西东南部富营养化水库中采集的天然蓝藻生物量的光谱特征与生物活性之间的关联。通过代谢组学揭示了四类蓝藻肽:微囊藻毒素、微囊藻氨酸、鱼腥藻毒素和蓝藻肽。生物信息学工具显示,蓝藻肽类化合物的生物活性相关性评分很高(0.54),微囊藻毒素的评分也很高(0.54-0.58)。这些结果强调了全面评估与不同蓝藻肽相关的(生态)毒理学风险的紧迫性,同时考虑到它们暴露的潜在可能性。我们的研究还表明,将基于 LC-MS/MS 的代谢组学和化学计量学技术结合用于生态毒理学研究可以提供一种具有时间效率的策略,用于绘制具有潜在毒理学风险的化合物图谱。Environ Toxicol Chem 2024;43:2222-2231. © 2024 SETAC.

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