Advances in mass spectrometry-based omics analysis of trace organics in water

What is the role of nitrate/nitrite in trace organic contaminants degradation and transformation during UV-based advanced oxidation processes?

The effectiveness of UV-based advanced oxidation processes (UV-AOPs) in degrading trace organic contaminants (TrOCs) can be significantly influenced by the ubiquitous presence of nitrate (NO3-) and nitrite (NO2-) in water and wastewater. Indeed, NO3-/NO2- can play multiple roles of NO3-/NO2- in UV-AOPs, leading to complexities and conflicting results observed in existing research. They can inhibit the degradation of TrOCs by scavenging reactive species and/or competitively absorbing UV light. Conversely, they can also enhance the elimination of TrOCs by generating additional •OH and reactive nitrogen species (RNS). Furthermore, the presence of NO3-/NO2- during UV-AOP treatment can affect the transformation pathways of TrOCs, potentially resulting in the nitration/nitrosation of TrOCs. The resulting nitro(so)-products are generally more toxic than the parent TrOCs and may become precursors of nitrogenous disinfection byproducts (N-DBPs) upon chlorination. Particularly, since the impact of NO3-/NO2- in UV-AOPs is largely due to the generation of RNS from NO3-/NO2- including NO•, NO2•, and peroxynitrite (ONOO-/ONOOH), this review covers the generation, properties, and detection methods of these RNS. From kinetic, mechanistic, and toxicologic perspectives, future research needs are proposed to advance the understanding of how NO3-/NO2- can be exploited to improve the performance of UV-AOPs treating TrOCs. This critical review provides a comprehensive framework outlining the multifaceted impact of NO3-/NO2- in UV-AOPs, contributing insights for basic research and practical applications of UV-AOPs containing NO3-/NO2-.

Nontarget Analysis and Comprehensive Characterization of Iodinated Polyfluoroalkyl Acids in Wastewater and River Water by LC-HRMS with Cascade Precursor-Ion Exclusions and Algorithmic Approach

Poly- and perfluoroalkyl acids (PFAAs) are a large family of widespread contaminants of worldwide concern and well-known as "forever chemicals". Direct emission of PFAAs from the fluorochemical industry is a crucial source of PFAA pollutants in the environment. This study implemented nontarget analysis and comprehensive characterization for a category of new PFAA contaminants, i.e., iodinated PFAAs (IPFAAs), in fluorochemical industry wastewater and relevant contaminated river water by liquid chromatography-high-resolution mass spectrometry with a cascade precursor ion exclusion (PIE) strategy and in-house developed data extraction and processing algorithms. A total of 26 IPFAAs (including 2 isomers of an IPFAA) were found and identified with tentative molecular structures. Semiquantification of the IPFAAs was implemented, and the total concentrations of IPFAAs were 0.16-285.52 and 0.15-0.17 μg/L in wastewater and river water, respectively. The high concentrations in association with the predicted ecotoxicities and environmental behaviors demonstrate that these IPFAAs are worthy of more concern and further in-depth research. The cascade PIE strategy along with the data extraction and processing algorithms can be extended to nontarget analysis for other pollutants beyond IPFAAs. The nontarget identification and characterization outcomes provide new understanding on the environmental occurrence and pollution status of IPFAAs from a comprehensive perspective.

Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features

Unknown features in untargeted metabolomics and non-targeted analysis (NTA) are identified using fragment ions from MS/MS spectra to predict the structures of the unknown compounds. The precursor ion selected for fragmentation is commonly performed using data dependent acquisition (DDA) strategies or following statistical analysis using targeted MS/MS approaches. However, the selected precursor ions from DDA only cover a biased subset of the peaks or features found in full scan data. In addition, different statistical analysis can select different precursor ions for MS/MS analysis, which make the post-hoc validation of ions selected following a secondary analysis impossible for precursor ions selected by the original statistical method. Here we propose an automated, exhaustive, statistical model-free workflow: paired mass distance-dependent analysis (PMDDA), for reproducible untargeted mass spectrometry MS2 fragment ion collection of unknown compounds found in MS1 full scan. Our workflow first removes redundant peaks from MS1 data and then exports a list of precursor ions for pseudo-targeted MS/MS analysis on independent peaks. This workflow provides comprehensive coverage of MS2 collection on unknown compounds found in full scan analysis using a “one peak for one compound” workflow without a priori redundant peak information. We compared pseudo-spectra formation and the number of MS2 spectra linked to MS1 data using the PMDDA workflow to that obtained using CAMERA and RAMclustR algorithms. More annotated compounds, molecular networks, and unique MS/MS spectra were found using PMDDA compared with CAMERA and RAMClustR. In addition, PMDDA can generate a preferred ion list for iterative DDA to enhance coverage of compounds when instruments support such functions. Finally, compounds with signals in both positive and negative modes can be identified by the PMDDA workflow, to further reduce redundancies. The whole workflow is fully reproducible as a docker image xcmsrocker with both the original data and the data processing template.

Biosensing based on upconversion nanoparticles for food quality and safety applications

Food safety and quality regulations inevitably call for sensitive and accurate analytical methods to detect harmful contaminants in food and to ensure safe food for the consumer. Both novel and well-established biorecognition elements, together with different transduction schemes, enable the simple and rapid analysis of various food contaminants. Upconversion nanoparticles (UCNPs) are inorganic nanocrystals that convert near-infrared light into shorter wavelength emission. This unique photophysical feature, along with narrow emission bandwidths and large anti-Stokes shift, render UCNPs excellent optical labels for biosensing because they can be detected without optical background interferences from the sample matrix. In this review, we show how this exciting technique has evolved into biosensing platforms for food quality and safety monitoring and highlight recent applications in the field.

Nontargeted identification and predicted toxicity of new byproducts generated from UV treatment of water containing micropollutant 2-mercaptobenzothiazole

Comprehensive identification of byproducts including intermediate transformation products (TPs) of micropollutants in source water is challenging and paramount for assessment of drinking water quality and treatment technologies. Here, we have developed a nontargeted analysis strategy coupled with computational toxicity assessment to identify indistinguishable TPs including isomers with large differences in toxicity. The new strategy was applied to study the UV treatment of water containing micropollutant 2-mercaptobenzothiazole (2-MBT), and it enabled successful identification of a total of 22 organic TPs. Particularly, the structures of nine new TPs were identified for the first time; in addition, three isomers (P2, P3, and P4) were distinguished from the toxic contaminant 2-hydroxybenzothiazole (2-OH-BT). Computational assessments indicate that estrogenic activity of the three isomers (P2-P4) is higher than that of 2-OH-BT. Mass balance study shows that the 22 organic products accounted for 70% of the 2-MBT degraded, while 30% may degrade to inorganic products. Most TPs are resistant to UV photolysis. Computational toxicity assessment predicted the TPs to increase inhibition of human thyroperoxidase activity although they have lower aquatic toxicity compared to original 2-MBT. This study emphasizes the importance of monitoring the 2-MBT photodegradation products and the overall toxicity of finished water whose production included a UV light-based treatment process.