Laboratory for Food Safety, ANSES, Université Paris-Est, F-94701 Maisons-Alfort, France.
Agreenium, the French Agricultural, Veterinary and Forestry Institute, 75116 Paris, France.
Toxins (Basel). 2018 Sep 14;10(9):375. doi: 10.3390/toxins10090375.
When considering the geographical expansion of marine toxins, the emergence of new toxins and the associated risk for human health, there is urgent need for versatile and efficient analytical methods that are able to detect a range, as wide as possible, of known or emerging toxins. Current detection methods for marine toxins rely on a priori defined target lists of toxins and are generally inappropriate for the detection and identification of emerging compounds. The authors describe the implementation of a recent approach for the non-targeted analysis of marine toxins in shellfish with a focus on a comprehensive workflow for the acquisition and treatment of the data generated after liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) analysis. First, the study was carried out in targeted mode to assess the performance of the method for known toxins with an extended range of polarities, including lipophilic toxins (okadaic acid, dinophysistoxins, azaspiracids, pectenotoxins, yessotoxins, cyclic imines, brevetoxins) and domoic acid. The targeted method, assessed for 14 toxins, shows good performance both in mussel and oyster extracts. The non-target potential of the method was then challenged via suspects and without a priori screening by blind analyzing mussel and oyster samples spiked with marine toxins. The data processing was optimized and successfully identified the toxins that were spiked in the blind samples.
当考虑海洋毒素的地理扩张、新毒素的出现以及对人类健康的相关风险时,迫切需要多功能且高效的分析方法,这些方法能够尽可能广泛地检测已知或新兴的毒素。目前用于海洋毒素检测的方法依赖于预先定义的毒素目标清单,通常不适合检测和识别新兴化合物。作者描述了最近一种用于贝类中海洋毒素非靶向分析的方法的实施情况,重点介绍了在液相色谱-高分辨率质谱(LC-HRMS)分析后获取和处理数据的综合工作流程。首先,该研究以目标模式进行,以评估该方法对具有扩展极性范围的已知毒素的性能,包括亲脂性毒素(麻痹性贝类毒素、鳍藻毒素、短裸甲藻毒素、扇贝毒素、膝沟藻毒素、环状亚胺、蛤蚌毒素)和软骨藻酸。针对 14 种毒素评估的靶向方法在贻贝和牡蛎提取物中均表现出良好的性能。然后通过可疑物和无先验筛选的方式,通过盲法分析添加海洋毒素的贻贝和牡蛎样本来挑战该方法的非靶向潜力。对数据处理进行了优化,并成功鉴定出在盲样中添加的毒素。