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Toxicity Testing of Effluent-Dominated Stream Using Predictive Molecular-Level Toxicity Signatures Based on High-Resolution Mass Spectrometry: A Case Study of the Lubbock Canyon Lake System
Environmental Science & Technology ( IF 11.4 ) Pub Date : 2021-02-18 , DOI: 10.1021/acs.est.0c05546
Naveen Kumar 1 , Haoqi Nina Zhao 2, 3 , Olushola Awoyemi 1 , Edward P. Kolodziej 2, 3, 4 , Jordan Crago 1
Affiliation  

Current aquatic toxicity assessments usually focus on targeted analyses coupled with toxicity testing to determine the impacts of complex mixtures on aquatic organisms. However, based on this approach alone, it is sometimes difficult to explain observed toxicity from the selected chemical analytes. Recent analytical advances such as high-resolution mass spectrometry (HRMS) can improve the characterizations of the chemical composition of complex mixtures, but the intensive labor required to produce confident identifications limits its utility in high-throughput screening. In the present study, we evaluated a rapid workflow to predict potential toxicity signatures of complex water samples based on high-throughput, tentative HRMS identifications derived from database matching, followed by identification of chemical–ligand interactions and pathway identification. We tested the workflow with water samples from the effluent-dominated Lubbock Canyon Lake System (LCLS). Results across all sites showed that predicted toxicity signatures had little variation when correcting for HRMS false-positive rates. The most common pathways across sites were gonadotropin-releasing hormone receptor and α-adrenergic receptor signaling. Alterations to the predicted pathways were successfully observed in larval zebrafish exposures to LCLS water samples. These results may allow researchers to better utilize rapid assessments of HRMS data for the assessment of adverse impacts on aquatic organisms.

中文翻译:

基于高分辨率质谱的预测分子水平毒性信号对污水主导流的毒性测试:以拉伯克峡谷湖系为例

当前的水生毒性评估通常集中于目标分析和毒性测试,以确定复杂混合物对水生生物的影响。但是,仅基于这种方法,有时很难解释从所选化学分析物中观察到的毒性。诸如高分辨率质谱(HRMS)之类的最新分析进展可以改善复杂混合物化学成分的表征,但是要产生可靠的鉴定结果需要大量的劳动,从而限制了其在高通量筛选中的应用。在本研究中,我们评估了一种快速的工作流程,以根据数据库匹配得出的高通量,暂定的HRMS识别来预测复杂水样品的潜在毒性特征,其次是化学配体相互作用的鉴定和途径鉴定。我们使用了以废水为主的拉伯克峡谷湖系统(LCLS)中的水样对工作流程进行了测试。所有站点的结果表明,校正HRMS假阳性率时,预测的毒性特征几乎没有变化。跨部位的最常见途径是促性腺激素释放激素受体和α-肾上腺素受体信号传导。在幼虫斑马鱼暴露于LCLS水样中成功观察到预测途径的改变。这些结果可以使研究人员更好地利用HRMS数据的快速评估来评估对水生生物的不利影响。所有站点的结果表明,校正HRMS假阳性率时,预测的毒性特征几乎没有变化。跨部位的最常见途径是促性腺激素释放激素受体和α-肾上腺素受体信号传导。在幼虫斑马鱼暴露于LCLS水样中成功观察到预测途径的改变。这些结果可以使研究人员更好地利用HRMS数据的快速评估来评估对水生生物的不利影响。所有站点的结果表明,校正HRMS假阳性率时,预测的毒性特征几乎没有变化。跨部位的最常见途径是促性腺激素释放激素受体和α-肾上腺素受体信号传导。在幼虫斑马鱼暴露于LCLS水样中成功观察到预测途径的改变。这些结果可以使研究人员更好地利用HRMS数据的快速评估来评估对水生生物的不利影响。
更新日期:2021-03-02
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