数据非依赖采集的砷脂质谱分析法及海产品中砷脂新形态发现

Exposure to arsenic compounds is a major public health problem that affects hundreds of millions of people worldwide. However, knowledge concerning identity and toxicity of one major and emerging class of arsenic compounds, arsenolipids (lipid-soluble arsenic compounds), is limited compared to that of the water-soluble arsenic compounds. This is due to the difficulties associated with isolation and characterization of these arsenicals. Therefore, the primary objective of this study is to develop a new analytical method that can fast screen and identify the arsenolipids in the crude extracts of seafood with high sensitivity. To achieve this goal, we will first build up a typical arsenic-containing fragment library on the basis of the results of high-resolution mass spectrometry analysis on available arsenic standards. Secondly, wavelet analysis, hierarchical clustering, peak shape similarity calculation will be utilized stepwise to establish a computation-based strategy for finding the precursor ions of some specific fragments generated in data-independent acquisition (DIA) on mass spectrometry. Finally, the analytical method of high-pressure liquid chromatography accompanied by electrospray ionization DIA tandem mass spectrometry, the fragment library, and the DIA data processing strategy will be coupled to conduct the speciation analysis of arsenolipids in seafood and to characterize the new arsenolipids. Upon finding a new arsenolipid, the analytical method developed here and cell models will be used to assess the cytotoxicity and genotoxicity of this arsenical and its metabolites. The development of this new method will empower researchers to efficiently detect and identify arsenolipids and gain an insightful understanding of the toxicity of the new arsenolipids. The result of this study will also contribute to the evidence-based policy surrounding the consumption of seafood.

脂溶性砷化合物，即砷脂，是一类重要的潜在新型污染物。因含量低、基体复杂、前处理和结构鉴定困难，许多砷脂形态和毒性尚不明确。为此，本项目拟运用数据非依赖采集(DIA)寻找前体离子的新策略，通过高分辨质谱建立砷脂特征碎片离子库，进一步联合使用高效液相色谱偶联电喷雾电离串联质谱法和DIA计算，确定复杂基体中低含量砷脂新形态及其分子结构。在此基础上构建细胞模型，利用所开发的砷脂质谱分析法研究新形态及其代谢物的细胞和基因毒性。项目以不同砷脂的碎片离子和前体离子的分布特征及配对机制为主要关键科学问题，以建立一种快速、简便、灵敏的砷脂检测分析法和质谱数据处理新方法为基础，发现海产品中的砷脂新形态和检测砷脂新形态在细胞模型中的代谢产物。预期在海产品中砷脂新形态的发现及其毒理机制研究方面取得创新性成果，对砷的环境暴露研究和食品安全评估具有十分重要的意义。

砷脂大量存在于海产品中，且部分形态被证实具有高细胞毒性和神经毒性。因含量低、基体复杂和同系物多，许多砷脂形态的鉴定十分困难。本项目的目标在于建立一种高灵敏高通量的砷脂分析新方法，发现海产品中的砷脂新形态及其代谢产物。首先，项目组建立了最佳的色谱质谱联用分析条件，探索了砷脂的质谱碎裂规律；其次利用小波相关和层次聚类，建立了从数据非依赖采集（DIA）数据中挖掘特征性碎片离子的前体离子的计算模型。将两者结合，构建了一个高效的未知砷脂形态的鉴定方法，并应用于海产品和电子烟中砷的新形态发现和其转化产物的研究中。重要结果如下: （1）寻找到了对砷脂形态分离较好的反相色谱条件，发现了已知砷脂在质谱上的碎裂规律和特征碎片。基于查找特征碎片的前体离子的计算策略开发了分析程序，实现了“采用DIA进行前体离子扫描”。该方法能节省样品分析时间，提高对低浓度分析物的检测灵敏度。利用该方法，成功从海产品中发现并鉴定了23种砷脂，并首次鉴定出10种新的砷脂，其中包括4种从未被报道过的砷脂大类。（2）对常见海鲜做了市场调查，进行了各种海鲜中砷脂的形态分析和半定量分析。共检测到3种砷烃、5种砷脂肪酸、氧化三甲基胂和硫代三甲基胂酸。大多数砷脂形态在带鱼和黄花鱼中含量最高。微波熟成仅可降低砷脂肪酸AsFA362和AsFA390的含量，而对其它砷脂形态无影响。（3）在电子烟烟油和烟雾中共检出6种砷形态，包括砷酸、亚砷酸、单甲基胂酸和3种未被报道过的新砷形态。气溶胶冷凝液中亚砷酸的浓度显著高于电子烟油。气溶胶中无机砷的浓度约为3.4 mg/m3。人体可能因吸食电子烟带来的砷暴露而增加的肺癌发病率高达1.5×10-4。本项目在发现海产品中砷脂新形态和明确电子烟危害方面取得了多项具有创新性和系统性的研究成果，为未知砷形态的毒理学研究提供了研究基础，对砷的环境暴露研究和食品安全评估具有十分重要的意义。