In Silico supported nontarget analysis of contaminants of emerging concern: Increasing confidence in unknown identification in wastewater and surface waters
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Abstract
Nontarget analysis using liquid chromatography–high resolution mass spectrometry (LC–HRMS) is a valuable approach in characterizing for contaminants of emerging concern (CECs) in the environment. In this study, wastewater and surface water samples from three locations in Manila, Philippines were analyzed for CECs using a nontarget analysis approach with an LC-Orbitrap. A previously optimized semiautomated workflow was used for data processing with Compound Discoverer. A total of 157 compounds were identified, with 21 confirmed with reference standards, 83 confirmed with evidence from a mass spectral library (mzCloud), and 53 tentatively identified using in silico fragmentation (MetFrag). These compounds include pharmaceuticals such as antibiotics, antifungal, and antihypertensive compounds, human metabolites, natural products, pesticides, and industrial chemicals. Compounds confirmed with reference standards include antibiotics ciprofloxacin, clarithromycin, acetyl-sulfamethoxazole, and trimethoprim (2 to 19 ng/L), and antifungal compounds carbendazim and climbazole (3–47 ng/L). The pesticides diethyltoluamide (DEET) and diuron were also detected (37 ng/L). The utility of a preliminary multivariable linear regression quality structure-retention relationship (QSRR) model based on quantum chemical molecular descriptors is demonstrated. This study demonstrates the importance of using tools and software that are helpful for annotating HRMS data and reporting detections according to a standardized classification system. The detection of several CECs in wastewater and surface water samples show the importance of performing nontarget analysis in determining occurrence of CECs in the environment.
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We acknowledge support from the National Science Foundation PIRE-HEARD award number 1545756 and USAID PEER subaward number 2000009924. S.S. thanks the National Science Foundation (Award #1904825) for support of this research, and the Donors of the American Chemical Society Petroleum Research Fund (PRF-58954-UNI5). We also thank Shyrill Mae Mariano from the Marine Science Institute in the University of the Philippines − Diliman who helped with the sample collection and Rebecca Dickman from University at Buffalo for her help on technical work.
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Angeles, L. F., Halwatura, L. M., Antle, J. P., Simpson, S., Jaraula, C. M., & Aga, D. S. (2021). In Silico supported nontarget analysis of contaminants of emerging concern: Increasing confidence in unknown identification in wastewater and surface waters. ACS ES&T Water, 1(8), 1765–1775.