Pharmaceutical footprint in the river ecosystem: Suspect screening approach with high resolution mass spectrometry.

Modern high-resolution mass spectrometry (HRMS) enables full-spectrum trace level analysis of emerging environmental organic contaminants. This raises the opportunity for post-acquisition suspect screening when no reference standards are a priori available. When setting up a conventional screening identification train based on successively different identification criteria including mass error and isotope fit, the false negative rate typically accumulates upon advancing through the decision tree. The challenge is thus to elaborate a well-balanced screening, in which the different criteria are equally stringent, leading to a controllable number of false negatives. Presented is a novel suspect screening approach using liquid-chromatography Orbitrap HRMS. Based on a multivariate statistical model, the screening takes into account the accurate mass error of the mono isotopic ion and up to three isotopes, isotope ratios, and a peak/noise filter. As such, for the first time, controlling the overall false negative rate of the screening algorithm to a desired level (5% in this study) is achieved. Simultaneously, a well-balanced identification decision is guaranteed taking the different identification criteria as a whole in a holistic statistical approach. Taking into account 1, 2, and 3 isotopes decreases the false positive rate from 22, 2.8 to <0.3%, but the cost of increasing the median limits of identification from 200, 2000 to 2062 ng L(-1), respectively, should also be considered. As proof of concept, 7 biologically treated wastewaters were screened toward 77 suspect pharmaceuticals resulting in the indicative identification of 25 suspects. Subsequently obtained reference standards allowed confirmation for 19 out of these 25 pharmaceutical contaminants.

Suspect Screening of Pharmaceuticals and Related Bioactive Compounds, Their Metabolites and Their Transformation Products in the Aquatic Environment, Biota and Humans Using LC-HR-MS Techniques

Suspect screening of glycoalkaloids in plant extracts using neutral loss – High resolution mass spectrometry

Suspect screening and targeted analyses: Two complementary approaches to characterize human exposure to pesticides

Suspect screening of natural toxins in surface and drinking water by high performance liquid chromatography and high-resolution mass spectrometry

This study demonstrates that regulatory databases combined with the latest advances in high resolution mass spectrometry (HRMS) can be efficiently used to prioritize and identify new, potentially hazardous pollutants being discharged into the aquatic environment. Of the approximately 23000 chemicals registered in the database of the National Swedish Product Register, 160 potential organic micropollutants were prioritized through quantitative knowledge of market availability, quantity used, extent of use on the market, and predicted compartment-specific environmental exposure during usage. Advanced liquid chromatography (LC)-HRMS-based suspect screening strategies were used to search for the selected compounds in 24 h composite samples collected from the effluent of three major wastewater treatment plants (WWTPs) in Sweden. In total, 36 tentative identifications were successfully achieved, mostly for substances not previously considered by environmental scientists. Of these substances, 23 were further confirmed with reference standards, showing the efficiency of combining a systematic prioritization strategy based on a regulatory database and a suspect-screening approach. These findings show that close collaboration between scientists and regulatory authorities is a promising way forward for enhancing identification rates of emerging pollutants and expanding knowledge on the occurrence of potentially hazardous substances in the environment.

The number of new psychoactive substances (NPS) is constantly increasing. However, although the number might be large, most NPS have a low prevalence of use, so keeping screening libraries updated with the relevant analytical targets becomes a challenge. One way to ensure sufficient screening coverage is to use shared high resolution-mass spectrometry (HR-MS) databases, such as HighResNPS.com: a free, online, spreadsheet-format, crowd-sourced HR-MS database for NPS screening. The aims of this study were (i) to present the database to the scientific community and (ii) to verify that the HighResNPS database can be utilized in suspect screening workflows for LC-HR-MS instruments and software from four different instrument vendors. A sample was spiked with 10 NPS, and participating laboratories then analyzed the sample with their respective HR-MS vendor platforms and the HighResNPS database. The HighResNPS data were obtained via a spreadsheet converted to fit the import specifications of the different vendor platforms. Suspect screening was performed using LC-HR-MS vendor platforms from Thermo Fisher, Waters, Bruker and Agilent. All 10 NPS were identified in at least three workflows used for the four different vendor platforms. Multiple users have submitted data to HighResNPS for the same NPS, which resulted in multiple true-positive identifications for these NPS. Suspect screening with LC-HR-MS can be based on diagnostic fragment ions reported by users of different vendor platforms and can support NPS identification in biological samples and/or seizure analyses when no reference standard is available in-house. The present work clearly demonstrates that HighResNPS data is compatible with instruments and screening software from at least four different vendor platforms. The database can thus serve as a useful add-on in LC-HR-MS screening workflows.

Suspect screening boosts bioaccessibility assays of phenolic compounds in food commodities: A proof of concept

This study investigated the degradation of strobilurin fungicide kresoxim-methyl (KM) in three typical agricultural soils from China by aerobic and anaerobic degradation experiments, focusing on degradation kinetics of KM, identification of transformation products (TPs), and prediction of toxicity end points via in silico approaches. KM showed a pronounced biphasic degradation in different soils and could rapidly degrade, with DT50 of <3 days. Four TPs were identified by high-resolution mass spectrometry (HRMS), and three of them have never been reported before. Possible degradation pathways of KM in soil were proposed, including hydrolysis, oxidation, and reduction, and the main mechanism involved in the biodegradation of KM was the hydrolysis of methyl ester regardless of aerobic or anaerobic conditions. The results of toxicity evaluation indicated that some TPs are more toxic than KM and may have a developmental toxicity and mutagenicity, and further risk assessment should be carried out.

Active pharmaceutical ingredients (APIs) have raised considerable concern over the past decade due to their widespread detection in water resources and their potential to affect ecosystem health. This triggered many attempts to prioritize the large number of known APIs to target monitoring efforts and testing of fate and effects. However, so far, a comprehensive approach to screen for their presence in surface waters has been missing. Here, we explore a combination of an automated suspect screening approach based on liquid chromatography coupled to high-resolution mass spectrometry and a model-based prioritization using consumption data, readily predictable fate properties and a generic mass balance model for activated sludge treatment to comprehensively detect APIs with relevant exposure in wastewater treatment plant effluents. The procedure afforded the detection of 27 APIs that had not been covered in our previous target method, which included 119 parent APIs. The newly detected APIs included seven compounds with a high potential for bioaccumulation and persistence, and also three compounds that were suspected to stem from point sources rather than from consumption as medicines. Analytical suspect screening proved to be more selective than model-based prioritization, making it the method of choice for focusing analytical method development or fate and effect testing on those APIs most relevant to the aquatic environment. However, we found that state-of-the-practice exposure modeling used to predict potential high-exposure substances can be a useful complement to point toward oversights and known or suspected detection gaps in the analytical method, most of which were related to insufficient ionization.

Liquid chromatography combined with high-resolution mass spectrometry (LC-HRMS) is a frequently applied technique for suspect screening (SS) and non-target screening (NTS) in metabolomics and environmental toxicology. However, correctly identifying compounds based on SS or NTS approaches remains challenging, especially when using data-independent acquisition (DIA). This study assessed the performance of four HRMS-spectra identification tools to annotate in-house generated data-dependent acquisition (DDA) and DIA HRMS spectra of 32 pesticides, veterinary drugs, and their metabolites. The identification tools were challenged with a diversity of compounds, including isomeric compounds. The identification power was evaluated in solvent standards and spiked feed extract. In DDA spectra, the mass spectral library mzCloud provided the highest success rate, with 84% and 88% of the compounds correctly identified in the top three in solvent standard and spiked feed extract, respectively. The in silico tools MSfinder, CFM-ID, and Chemdistiller also performed well in DDA data, with identification success rates above 75% for both solvent standard and spiked feed extract. MSfinder provided the highest identification success rates using DIA spectra with 72% and 75% (solvent standard and spiked feed extract, respectively), and CFM-ID performed almost similarly in solvent standard and slightly less in spiked feed extract (72% and 63%). The identification success rates for Chemdistiller (66% and 38%) and mzCloud (66% and 31%) were lower, especially in spiked feed extract. The difference in success rates between DDA and DIA is most likely caused by the higher complexity of the DIA spectra, making direct spectral matching more complex. However, this study demonstrates that DIA spectra can be used for compound annotation in certain software tools, although the success rate is lower than for DDA spectra.

Comprehensive micropollutant characterization of wastewater during Covid-19 crisis in 2020: Suspect screening and environmental risk prioritization strategy

Oxidative processes - insights in reaction mechanisms gained by high resolution and isotope ratio mass spectrometry

Suspect screening of halogenated carboxylic acids in drinking water using ion exchange chromatography – high resolution (Orbitrap) mass spectrometry (IC-HRMS)

Suspect screening analysis of the occurrence and removal of micropollutants by GC-QTOF MS during wastewater treatment processes.