Harmonized Quality Assurance/Quality Control Provisions for Nontargeted Measurement of Urinary Pesticide Biomarkers in the HBM4EU Multisite SPECIMEn Study.

A set of quality assurance/quality control (QA/QC) criteria for nontargeted measurement of pesticide exposure markers in a large-scale study of human urine has been proposed and applied across five laboratories within the HBM4EU project. Quality control material, including reference standards and fortified pooled urine samples (QC urine) were prepared in a centralized way and distributed across participants to monitor analytical performance and consistency of the liquid chromatography coupled to high-resolution mass spectrometry data generated with a harmonized workflow. Signal intensities, mass accuracy, and retention times of selected QA/QC markers covering a broad range of physicochemical properties were monitored across QC solvent standards, QC urine samples, study urine samples, and procedural blanks, setting acceptance thresholds for repeatability and accuracy. Overall, results showed high repeatability of the collected data. The RSDs of the signal intensities were typically below 20-30% in QC and study samples, with good stability of the chromatographic separation (retention time drift within 2-4 s intrabatch and 5 s interbatch) and excellent mass accuracy (average error < 2 ppm). The use of the proposed criteria allowed for the identification of handling errors, instrumental issues, and potential batch effects. This is the first elaboration of harmonized QA/QC criteria applied across multiple laboratories to assess the quality of data generated by nontargeted analysis of human samples.

Cytochrome P450 expression, induction and activity in human induced pluripotent stem cell-derived intestinal organoids and comparison with primary human intestinal epithelial cells and Caco-2 cells.

Human intestinal organoids (HIOs) are a promising in vitro model consisting of different intestinal cell types with a 3D microarchitecture resembling native tissue. In the current study, we aimed to assess the expression of the most common intestinal CYP enzymes in a human induced pluripotent stem cell (hiPSC)-derived HIO model, and the suitability of that model to study chemical-induced changes in CYP expression and activity. We compared this model with the commonly used human colonic adenocarcinoma cell line Caco-2 and with a human primary intestinal epithelial cell (IEC)-based model, closely resembling in vivo tissue. We optimized an existing protocol to differentiate hiPSCs into HIOs and demonstrated that obtained HIOs contain a polarized epithelium with tight junctions consisting of enterocytes, goblet cells, enteroendocrine cells and Paneth cells. We extensively characterized the gene expression of CYPs and activity of CYP3A4/5, indicating relatively high gene expression levels of the most important intestinal CYP enzymes in HIOs compared to the other models. Furthermore, we showed that CYP1A1 and CYP1B1 were induced by ß-naphtoflavone in all three models, whereas CYP3A4 was induced by phenobarbital and rifampicin in HIOs, in the IEC-based model (although not statistically significant), but not in Caco-2 cells. Interestingly, CYP2B6 expression was not induced in any of the models by the well-known liver CYP2B6 inducer phenobarbital. In conclusion, our study indicates that hiPSC-based HIOs are a useful in vitro intestinal model to study biotransformation of chemicals in the intestine.

Comparison of Compound Identification Tools Using Data Dependent and Data Independent High-Resolution Mass Spectrometry Spectra.

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.

Assessment of exposure to pesticide mixtures in five European countries by a harmonized urinary suspect screening approach.

Humans are exposed to a mixture of pesticides through diet as well as through the environment. We conducted a suspect-screening based study to describe the probability of (concomitant) exposure to a set of pesticide profiles in five European countries (Latvia, Hungary, Czech Republic, Spain and the Netherlands). We explored whether living in an agricultural area (compared to living in a peri-urban area), being a a child (compared to being an adult), and the season in which the urine sample was collected had an impact on the probability of detection of pesticides (-metabolites). In total 2088 urine samples were collected from 1050 participants (525 parent-child pairs) and analyzed through harmonized suspect screening by five different laboratories. Fourty pesticide biomarkers (either pesticide metabolites or the parent pesticides as such) relating to 29 pesticides were identified at high levels of confidence in samples across all study sites. Most frequently detected were biomarkers related to the parent pesticides acetamiprid and chlorpropham. Other biomarkers with high detection rates in at least four countries related to the parent pesticides boscalid, fludioxonil, pirimiphos-methyl, pyrimethanil, clothianidin, fluazifop and propamocarb. In 84% of the samples at least two different pesticides were detected. The median number of detected pesticides in the urine samples was 3, and the maximum was 13 pesticides detected in a single sample. The most frequently co-occurring substances were acetamiprid with chlorpropham (in 62 urine samples), and acetamiprid with tebuconazole (30 samples). Some variation in the probability of detection of pesticides (-metabolites) was observed with living in an agricultural area or season of urine sampling, though no consistent patterns were observed. We did observe differences in the probability of detection of a pesticide (metabolite) among children compared to adults, suggesting a different exposure and/or elimination patterns between adults and children. This survey demonstrates the feasibility of conducting a harmonized pan-European sample collection, combined with suspect screening to provide insight in the presence of exposure to pesticide mixtures in the European population, including agricultural areas. Future improvements could come from improved (harmonized) quantification of pesticide levels.

Aflatoxin B1 Metabolism of Reared Alphitobius diaperinus in Different Life-Stages.

The presence of carcinogenic aflatoxins in food and feed is a major issue. In prior studies, aflatoxin B1 (AfB1) and known primary metabolites were absent from Lesser Mealworm (LMW, Alphitobius diaperinus) reared on contaminated diets. LMW is a promising alternative protein source. The objectives of this stu\dy were to determine whether LMW can be reared on AfB1-contaminated feed in each life-stage, and to gather more insight into potential metabolites formed. Results suggested no adverse effects in terms of survival/growth when three stages of LMW (larvae, pre-pupae, beetles) were exposed to feed containing AfB1 concentrations of 200 and 600 µg/kg for 48 h. Insect and frass samples were analyzed by LC-MS/MS and high-resolution MS to, respectively, quantify concentrations of AfB1 and its major metabolites, and determine secondary metabolites. No AfB1 or major metabolites were quantified in the insect samples. Mass balance calculations showed that up to 40% of spiked AfB1 could be recovered in the frass, in the form of AfB1, aflatoxicol and AfM1. HRMS results suggested the presence of additional metabolites in the frass, but, due to lack of commercially available reference standards for these compounds, exact identification and quantification was not possible. More research is needed to verify the absence of toxicity.

Systematic assessment of acquisition and data-processing parameters in the suspect screening of veterinary drugs in archive matrices using LC-HRMS.

Monitoring strategies for veterinary drugs in products of animal origin are shifting towards a more risk-based approach. Such strategies not only target a limited number of predefined .substances but also facilitate detection of unexpected substances. By combining the use of archive matrices such as feather meal with suspect-screening methods, early detection of new hazards in the food and feed industry can be achieved. Effective application of such strategies is hampered by complex data interpretation and therefore, targeted data analysis is commonly applied. In this study, the performance of a suspect-screening data processing workflow using a suspect list or the online spectral database mzCloudTM was explored to facilitate detection of veterinary drugs in archive matrices. Data evaluation parameters specifically investigated for application of a suspect list were mass tolerance and the addition or omission of retention times. Application of a mass tolerance of 1.5 ppm leads to an increase in the number of false positives, as does omission of retention times in the suspect list. Different acquisition modes yielding different qualities of MS2 data were studied and proved to be a critical factor, where data-dependent acquisition is preferred when matching to the mzCloudTM database. Using this approach, it is possible to search for compounds on a dedicated suspect list based on the exact mass and retention times and, at the same time, detect unexpected compounds without a priori information. A pilot study was conducted and fourteen different antibiotics were detected (and confirmed by MS/MS). Three of these antibiotics were not included in the suspect list. The optimised suspect-screening method proved to be fit for the purpose of finding veterinary drugs in feather meal, which are not in the scope of the current monitoring methods and therefore, it gives added value in the perspective of a risk-based monitoring.

Pesticides in doormat and floor dust from homes close to treated fields: Spatio-temporal variance and determinants of occurrence and concentrations.

Indoor dust has been postulated as an important matrix for residential pesticide exposure. However, there is a lack of information on presence, concentrations and determinants of multiple pesticides in dust in residential homes close to treated fields. Our objective was to characterize the spatial and temporal variance of pesticides in house dust, study the use of doormats and floors as proxies for pesticides in indoor dust and identify determinants of occurrence and concentrations. Homes within 250 m from selected bulb fields were invited to participate. Homes within 20 km from these fields but not having agricultural fields within 500 m were selected as controls. House dust was vacuumed in all homes from floors (VFD) and from newly placed clean doormats (DDM). Sampling was done during two periods, when pesticides are used and not-used. For determination of 46 prioritized pesticides, a multi-residue extraction method was used. Most statistical analyses are focused on the 12 and 14 pesticides that were detected in >40% of DDM and VFD samples, respectively. Mixed models were used to evaluate relationships between possible determinants and pesticides occurrence and concentrations in DDM and VFD. 17 pesticides were detected in more than 50% of the homes in both matrixes. Concentrations differed by about a factor five between use and non-use periods among homes within 250 m of fields and between these homes and controls. For 7 pesticides there was a moderate to strong correlation (Spearman rho 0.30-0.75) between concentrations in DDM and VFD. Distance to agricultural fields and air concentrations were among the most relevant predictors for occurrence and levels of a given pesticide in DDM. Concentrations in dust are overall higher during application periods and closer to fields (<250 m) than further away. The omnipresence of pesticides in dust lead to residents being exposed all year round.

A large scale multi-laboratory suspect screening of pesticide metabolites in human biomonitoring: From tentative annotations to verified occurrences.

Within the Human Biomonitoring for Europe initiative (HBM4EU), a study to determine new biomarkers of exposure to pesticides and to assess exposure patterns was conducted. Human urine samples (N = 2,088) were collected from five European regions in two different seasons. The objective of the study was to identify pesticides and their metabolites in collected urine samples with a harmonized suspect screening approach based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) applied in five laboratories. A combined data processing workflow included comprehensive data reduction, correction of mass error and retention time (RT) drifts, isotopic pattern analysis, adduct and elemental composition annotation, finalized by a mining of the elemental compositions for possible annotations of pesticide metabolites. The obtained tentative annotations (n = 498) were used for acquiring representative data-dependent tandem mass spectra (MS2) and verified by spectral comparison to reference spectra generated from commercially available reference standards or produced through human liver S9 in vitro incubation experiments. 14 parent pesticides and 71 metabolites (including 16 glucuronide and 11 sulfate conjugates) were detected. Collectively these related to 46 unique pesticides. For the remaining tentative annotations either (i) no data-dependent MS2 spectra could be acquired, (ii) the spectral purity was too low for sufficient matching, or (iii) RTs indicated a wrong annotation, leaving potential for more pesticides and/or their metabolites being confirmed in further studies. Thus, the reported results are reflecting only a part of the possible pesticide exposure.