Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS.

Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.

Improving predictions of compound amenability for liquid chromatography-mass spectrometry to enhance non-targeted analysis.

Mass-spectrometry-based non-targeted analysis (NTA), in which mass spectrometric signals are assigned chemical identities based on a systematic collation of evidence, is a growing area of interest for toxicological risk assessment. Successful NTA results in better identification of potentially hazardous pollutants within the environment, facilitating the development of targeted analytical strategies to best characterize risks to human and ecological health. A supporting component of the NTA process involves assessing whether suspected chemicals are amenable to the mass spectrometric method, which is necessary in order to assign an observed signal to the chemical structure. Prior work from this group involved the development of a random forest model for predicting the amenability of 5517 unique chemical structures to liquid chromatography-mass spectrometry (LC-MS). This work improves the interpretability of the group's prior model of the same endpoint, as well as integrating 1348 more data points across negative and positive ionization modes. We enhance interpretability by feature engineering, a machine learning practice that reduces the input dimensionality while attempting to preserve performance statistics. We emphasize the importance of interpretable machine learning models within the context of building confidence in NTA identification. The novel data were curated by the labeling of compounds as amenable or unamenable by expert curators, resulting in an enhanced set of chemical compounds to expand the applicability domain of the prior model. The balanced accuracy benchmark of the newly developed model is comparable to performance previously reported (mean CV BA is 0.84 vs. 0.82 in positive mode, and 0.85 vs. 0.82 in negative mode), while on a novel external set, derived from this work's data, the Matthews correlation coefficients (MCC) for the novel models are 0.66 and 0.68 for positive and negative mode, respectively. Our group's prior published models scored MCC of 0.55 and 0.54 on the same external sets. This demonstrates appreciable improvement over the chemical space captured by the expanded dataset. This work forms part of our ongoing efforts to develop models with higher interpretability and higher performance to support NTA efforts.

Homologue Composition of Technical Chlorinated Paraffins Used in Several Countries over the Last 50 Years─SCCPs Are Still Out There.

Chlorinated paraffins (CPs) are widely produced chemicals, with certain CP subgroups facing global restrictions due to their environmental dispersion, persistence, bioaccumulation, and toxicity. To evaluate the effectiveness of these international restrictions, we assessed the homologue group contribution and the mass fraction of short-chain CPs (SCCPs: C10-C13), medium-chain CPs (MCCPs: C14-C17), and long-chain CPs (LCCPs: ≥C18) in 36 technical CP mixtures used worldwide over the last 50 years. Using low-resolution mass spectrometry (LC-ESI-MS/MS), we quantified 74 CP homologue groups (C10Cl4-C20Cl10). Additionally, high-resolution mass spectrometry (LC-ESI-QTOF-MS) screening was employed to identify unresolved CP contents, covering 375 CP homologue groups (C6Cl4-C30Cl30). Overall, 1 sample was mainly composed of

Efficient workflow for suspect screening analysis to characterize novel and legacy per- and polyfluoroalkyl substances (PFAS) in biosolids.

Land application of treated sewage sludge (also known as biosolids) is considered a sustainable route of disposal because it reduces waste loading into landfills while improving soil health. However, this waste management practice can introduce contaminants from biosolids, such as per- and polyfluoroalkyl substances (PFAS), into the environment. PFAS have been observed to be taken up by plants, accumulate in humans and animals, and have been linked to various negative health effects. There is limited information on the nature and amounts of PFAS introduced from biosolids that have undergone different treatment processes. Therefore, this study developed analytical techniques to improve the characterization of PFAS in complex biosolid samples. Different clean-up techniques were evaluated and applied to waste-activated sludge (WAS) and lime-stabilized primary solids (PS) prior to targeted analysis and suspect screening of biosolid samples. Using liquid chromatography with high-resolution mass spectrometry, a workflow was developed to achieve parallel quantitative targeted analysis and qualitative suspect screening. This study found that concentrations of individual PFAS (27 targeted analytes) can range from 0.6 to 84.6 ng/g in WAS (average total PFAS = 241.4 ng/g) and from 1.6 to 33.8 ng/g in PS (average total PFAS = 72.1 ng/g). The suspect screening workflow identified seven additional PFAS in the biosolid samples, five of which have not been previously reported in environmental samples. Some of the newly identified compounds are a short-chain polyfluorinated carboxylate (a PFOS replacement), a diphosphate ester (a PFOA precursor), a possible transformation product of carboxylate PFAS, and an imidohydrazide which contains a sulfonate and benzene ring.

Combining Headspace Solid-Phase Microextraction with Internal Benchmarking to Determine the Elimination Kinetics of Hydrophobic UVCBs.

Substances classified as unknown or variable composition, complex reaction products or biological origin (UVCB) present a challenge for environmental hazard and risk assessment. Here, we present a novel approach for whole-substance bioconcentration testing applied to cedarwood oil-an essential oil composed of volatile, hydrophobic organic chemicals. The method yields whole-body elimination rate constants for a mixture of constituents. Our approach combines in vivo dietary fish exposure with internal benchmarking and headspace solid-phase microextraction (HS-SPME) equilibrium sampling followed by suspect-screening analysis. We quantified depuration rate constants of 13 individual cedarwood oil constituents based on relative peak areas using gas chromatography (GC) coupled with Orbitrap-mass spectrometry (MS) and GC triple-quadrupole (QqQ)-MS. For seven constituents with available analytical standards, we compared the rate constants to the results obtained from solvent extraction, clean-up, and targeted GC-MS analysis. The HS-SPME sampling approach allowed for automated sample extraction and analyte enrichment while minimizing evaporative losses of the volatile target analytes and reducing matrix interferences from low-volatility organics. The suspect-screening analysis enabled the quantification of constituents without available analytical standards, while the internal benchmarking significantly reduced variability from differences in delivered dose and analytical variability between the samples.

Predicting compound amenability with liquid chromatography-mass spectrometry to improve non-targeted analysis.

With the increasing availability of high-resolution mass spectrometers, suspect screening and non-targeted analysis are becoming popular compound identification tools for environmental researchers. Samples of interest often contain a large (unknown) number of chemicals spanning the detectable mass range of the instrument. In an effort to separate these chemicals prior to injection into the mass spectrometer, a chromatography method is often utilized. There are numerous types of gas and liquid chromatographs that can be coupled to commercially available mass spectrometers. Depending on the type of instrument used for analysis, the researcher is likely to observe a different subset of compounds based on the amenability of those chemicals to the selected experimental techniques and equipment. It would be advantageous if this subset of chemicals could be predicted prior to conducting the experiment, in order to minimize potential false-positive and false-negative identifications. In this work, we utilize experimental datasets to predict the amenability of chemical compounds to detection with liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS). The assembled dataset totals 5517 unique chemicals either explicitly detected or not detected with LC-ESI-MS. The resulting detected/not-detected matrix has been modeled using specific molecular descriptors to predict which chemicals are amenable to LC-ESI-MS, and to which form(s) of ionization. Random forest models, including a measure of the applicability domain of the model for both positive and negative modes of the electrospray ionization source, were successfully developed. The outcome of this work will help to inform future suspect screening and non-targeted analyses of chemicals by better defining the potential LC-ESI-MS detectable chemical landscape of interest.

Identifying xenobiotic metabolites with in silico prediction tools and LCMS suspect screening analysis.

Understanding the metabolic fate of a xenobiotic substance can help inform its potential health risks and allow for the identification of signature metabolites associated with exposure. The need to characterize metabolites of poorly studied or novel substances has shifted exposure studies towards non-targeted analysis (NTA), which often aims to profile many compounds within a sample using high-resolution liquid-chromatography mass-spectrometry (LCMS). Here we evaluate the suitability of suspect screening analysis (SSA) liquid-chromatography mass-spectrometry to inform xenobiotic chemical metabolism. Given a lack of knowledge of true metabolites for most chemicals, predictive tools were used to generate potential metabolites as suspect screening lists to guide the identification of selected xenobiotic substances and their associated metabolites. Thirty-three substances were selected to represent a diverse array of pharmaceutical, agrochemical, and industrial chemicals from Environmental Protection Agency's ToxCast chemical library. The compounds were incubated in a metabolically-active in vitro assay using primary hepatocytes and the resulting supernatant and lysate fractions were analyzed with high-resolution LCMS. Metabolites were simulated for each compound structure using software and then combined to serve as the suspect screening list. The exact masses of the predicted metabolites were then used to select LCMS features for fragmentation via tandem mass spectrometry (MS/MS). Of the starting chemicals, 12 were measured in at least one sample in either positive or negative ion mode and a subset of these were used to develop the analysis workflow. We implemented a screening level workflow for background subtraction and the incorporation of time-varying kinetics into the identification of likely metabolites. We used haloperidol as a case study to perform an in-depth analysis, which resulted in identifying five known metabolites and five molecular features that represent potential novel metabolites, two of which were assigned discrete structures based on in silico predictions. This workflow was applied to five additional test chemicals, and 15 molecular features were selected as either reported metabolites, predicted metabolites, or potential metabolites without a structural assignment. This study demonstrates that in some-but not all-cases, suspect screening analysis methods provide a means to rapidly identify and characterize metabolites of xenobiotic chemicals.

Identification, occurrence, concentration and composition profile of fiproles in municipal wastewater treatment plants.

Although fipronil and several of its transformation products are ubiquitous in aquatic environments, limited information is available on the structural identities, detection frequencies, concentrations and composition profiles of fiproles (fipronil and its known and unknown transformation products) in municipal wastewater treatment plants (WWTPs). In this study, a suspect screening analysis was applied to identify and characterize fipronil transformation products in 16 municipal WWTPs from three cities in China. In addition to fipronil and its four transformation products (fipronil amide, fipronil sulfide, fipronil sulfone and desulfinyl fipronil), fipronil chloramine and fipronil sulfone chloramine were detected for the first time in municipal wastewater. Moreover, the cumulative concentrations of six transformation products were 0.236 ng/L and 3.44 ng/L in wastewater influents and effluents, and accounted for one-third (in influents) to half (in effluents) of fiproles. Of those transformation products, two chlorinated byproducts (fipronil chloramine and fipronil sulfone chloramine) were major transformation products in both municipal wastewater influents and effluents. Notably, the log Kow and bioconcentration factor (evaluated by EPI Suite software) of fipronil chloramine (log Kow = 6.64, and BCF = 11,200 L/kg wet-wt) and fipronil sulfone chloramine (log Kow = 4.42, and BCF = 382.9 L/kg wet-wt) were greater than that of their parent compound. Considering the persistence, bioaccumulation potential and toxicity, the high detection rates of fipronil chloramine and fipronil sulfone chloramine in urban aquatic systems need to be specifically considered in future ecological risk assessments.

Non-targeted analysis (NTA) and suspect screening analysis (SSA): a review of examining the chemical exposome.

Non-targeted analysis (NTA) and suspect screening analysis (SSA) are powerful techniques that rely on high-resolution mass spectrometry (HRMS) and computational tools to detect and identify unknown or suspected chemicals in the exposome. Fully understanding the chemical exposome requires characterization of both environmental media and human specimens. As such, we conducted a review to examine the use of different NTA and SSA methods in various exposure media and human samples, including the results and chemicals detected. The literature review was conducted by searching literature databases, such as PubMed and Web of Science, for keywords, such as "non-targeted analysis", "suspect screening analysis" and the exposure media. Sources of human exposure to environmental chemicals discussed in this review include water, air, soil/sediment, dust, and food and consumer products. The use of NTA for exposure discovery in human biospecimen is also reviewed. The chemical space that has been captured using NTA varies by media analyzed and analytical platform. In each media the chemicals that were frequently detected using NTA were: per- and polyfluoroalkyl substances (PFAS) and pharmaceuticals in water, pesticides and polyaromatic hydrocarbons (PAHs) in soil and sediment, volatile and semi-volatile organic compounds in air, flame retardants in dust, plasticizers in consumer products, and plasticizers, pesticides, and halogenated compounds in human samples. Some studies reviewed herein used both liquid chromatography (LC) and gas chromatography (GC) HRMS to increase the detected chemical space (16%); however, the majority (51%) only used LC-HRMS and fewer used GC-HRMS (32%). Finally, we identify knowledge and technology gaps that must be overcome to fully assess potential chemical exposures using NTA. Understanding the chemical space is essential to identifying and prioritizing gaps in our understanding of exposure sources and prior exposures. IMPACT STATEMENT: This review examines the results and chemicals detected by analyzing exposure media and human samples using high-resolution mass spectrometry based non-targeted analysis (NTA) and suspect screening analysis (SSA).

Enhanced database creation with in silico workflows for suspect screening of unknown tebuconazole transformation products in environmental samples by UHPLC-HRMS.

The search and identification of organic contaminants in agricultural watersheds has become a crucial effort to better characterize watershed contamination by pesticides. The past decade has brought a more holistic view of watershed contamination via the deployment of powerful analytical strategies such as non-target and suspect screening analysis that can search more contaminants and their transformation products. However, suspect screening analysis remains broadly confined to known molecules, primarily due to the lack of analytical standards and suspect databases for unknowns such as pesticide transformation products. Here we developed a novel workflow by cross-comparing the results of various in silico prediction tools against literature data to create an enhanced database for suspect screening of pesticide transformation products. This workflow was applied on tebuconazole, used here as a model pesticide, and resulted in a suspect screening database counting 291 transformation products. The chromatographic retention times and tandem mass spectra were predicted for each of these compounds using 6 models based on multilinear regression and more complex machine-learning algorithms. This comprehensive approach to the investigation and identification of tebuconazole transformation products was retrospectively applied on environmental samples and found 6 transformation products identified for the first time in river water samples.

Comparison of extraction and clean-up methods for comprehensive screening of organic micropollutants in fish using gas chromatography coupled to high-resolution mass spectrometry.

Monitoring the vast number of micropollutants in the environment by using comprehensive chemical screening is a major analytical challenge. The aim of this study was to evaluate a comprehensive analysis method for screening purposes of fish muscle samples by comparing sample preparation methods for a broad range of mid-to non-polar contaminants. Five extraction and three clean-up methods were evaluated for the analysis of 60 compounds with a log Kow range between 0.8 and 8.3 in fish. Both fresh and freeze-dried muscle tissue and extraction sodium sulphate blanks were included to assess recoveries and matrix effects. The performance of the different methods was evaluated using both comprehensive target and nontarget analysis using high resolution mass spectrometry (HRMS). The results showed that open-column and ultrasonication extractions (recoveries mostly between 20 and 160 %) resulted in higher recoveries than accelerated solvent extraction (ASE) (recoveries mostly between 20 and 80 %) and bead mixer homogenization extractions (recoveries between 0 and 50 % for the whole Kow range). Multilayer silica was the clean-up method resulting in the lowest matrix effects and highest recoveries, however some compounds (mostly pesticides) were denatured under the acidic conditions used. The convenient and time efficient ultrasonication extraction followed by deactivated silica clean-up proved to be promising for both target and nontarget approaches. The large difference in recoveries and number of detected peaks using target and nontarget approaches between fresh and freeze-dried fish seen for all methods calls for careful consideration, and further studies are needed to improve performance for screening of mid-to non-polar compounds in freeze-dried fish.

Suspect screening analysis in house dust from Belgium using high resolution mass spectrometry; prioritization list and newly identified chemicals.

In recent years, several changes have been made to the composition of various products which are used indoors. Plenty of new chemical additives have been incorporated to materials to comply with current legislation and safety rules. Consequently, the emission profiles of contaminants detected indoors may change over time, requiring continuous monitoring. In this study, dust samples were collected from 25 homes located in the Flemish region of Belgium during different seasons (winter and summer). Our aim was the development of a suspect screening workflow for the identification of new chemicals which might have been applied to indoor goods, released into the indoor environment, and accumulated in dust. An in-house suspect list was curated including selected groups of compounds, namely "phthalates", "phosphates", "terephthalates", "citrates", "trimellitates", (di-, tri-, tetra-) "carboxylic acids", "adipates", "azelates", "sebacates", (di-)"benzoates", and "succinates". 63 chemicals were prioritized based on their level of identification and detection frequency in samples. Seasonal comparison was tested, indicating that higher temperatures of summer might facilitate the release of few chemicals from the products into the indoor environment. Seven chemicals, to the best of our knowledge not previously reported, were selected out of the 63 listed and identified for structure confirmation using high-resolution mass spectrometry. Tributyl trimellitate (TBTM), bis (3,5,5-trimethylhexyl) phosphate (Bis-3,5,5-TMHPh), iso-octyl 2-phenoxy ethyl terephthalate (IOPhET), dimethyl azelate (DMA), dimethyl sebacate (DMS), dipropylene glycol dibenzoate (DiPGDB) and 3,5-di-tert-butyl-4-hydroxybenzaldehyde (BHT-CHO) were detected at frequencies ranging from 8 to 52% in winter and 4-56% in summer dust.

Identification of chemicals of emerging concern in urine of Flemish adolescents using a new suspect screening workflow for LC-QTOF-MS.

An essential step in human biomonitoring or molecular epidemiology programs is to estimate human exposure to environmental chemicals. Despite significant progress in the capabilities of analytical methods, the number of pollutants and their metabolites keeps increasing continuously. Some of these relatively unknown chemicals of emerging concern (CECs) may pose significant health risks to humans and biota, but remain virtually undetected in traditional HBM-studies. Non-target and suspect screening techniques based on high-resolution mass spectrometry (HRMS) perform the detection and identification of compounds without any a priori compound selection or chemical information and provide a more holistic overview of human exposure. In this study, 50 urine samples (25 female and 25 male) from a larger cohort of the Flemish Environment and Health Study (FLEHS IV, 2016-2020) have been submitted to suspect screening analysis, with the aim of detecting and identifying new CECs. For this purpose, an analytical method has been developed, optimised and evaluated in terms of analytical performance. Satisfactory results were obtained in terms of reproducibility, sensitivity and quality control. Data-mining was performed through the combination of two different workflows. The use of two complementary workflows enhanced the number of identified compounds. As a result, 45 CECs have been identified with a level of confidence ranged between 3 and 1. Most of the identified compounds were metabolisation products, many of which were currently not included in the targeted measurements of FLEHS IV. The identified chemicals and metabolites could be used as candidate biomarkers of exposure in future studies. Overall, the newly developed suspect screening workflow of this pilot study provided complementary and promising results for future HBM-programs.

Comprehensive chemical characterization of indoor dust by target, suspect screening and nontarget analysis using LC-HRMS and GC-HRMS.

Since humans spend more than 90% of their time in indoor environments, indoor exposure can be an important non-dietary pathway to hazardous organic contaminants. It is thus important to characterize the chemical composition of indoor dust to assess the total contaminant exposure and estimate human health risks. The aim of this investigation was to perform a comprehensive chemical characterization of indoor dust. First, the robustness of an adopted extraction method using ultrasonication was evaluated for 85 target compounds. Thereafter, a workflow combining target analysis, suspect screening analysis (SSA) and nontarget analysis (NTA) was applied to dust samples from different indoor environments. Chemical analysis was performed using both gas chromatography and liquid chromatography coupled with high resolution mass spectrometry. Although suppressing matrix effects were prominent, target analysis enabled the quantification of organophosphate/brominated flame retardants (OPFRs/BFRs), liquid crystal monomers (LCMs), toluene diisocyanate, bisphenols, pesticides and tributyl citrate. The SSA confirmed the presence of OPFRs but also enabled the detection of polyethylene glycols (PEGs) and phthalates/parabens. The combination of hierarchical cluster analysis and scaled mass defect plots in the NTA workflow confirmed the presence of the above mentioned compounds, as well as detect other contaminants such as tetrabromobisphenol A, triclocarban, diclofenac and 3,5,6-trichloro-2-pyridinol, which were further confirmed using pure standards.

Pharmaceuticals and other contaminants in waters and sediments from Augusta Bay (southern Italy).

The contamination by pharmaceuticals products (PPs) in the marine environment is particularly relevant where wastewater treatment of urban areas on land is lacking. However, the number of studies focused on description of sources and fate of PP molecules in the marine environment remains still limited. In this study, the occurrence of 46 PPs was investigated in the marine and coastal-marine system (waters and sediments) of Augusta Bay (central Mediterranean Sea). This area is highly affected by industrial pollution and urban discharges (without wastewater treatment) and thus represents a 'natural laboratory' for exploring dynamics of multi-mixture contaminants in the marine environment. The study area is also part of the sub-region 'Central Mediterranean Sea' of the Marine Strategy Framework Directive and therefore offers an important reference site for exploring the distribution modes of PPs in the central Mediterranean Sea. In this work, samples of seawater, sediment, untreated wastewater, and marine receiving water were analysed using mass spectrometry with a target analysis for PPs and a suspect screening analysis for the presence of other contaminants. PPs concentration ranges were: 2426-67,155 ng/L for untreated wastewaters, 550-27,889 ng/L for marine receiving waters and 12-281 ng/L for seawaters. The highest concentrations were measured for the antibiotics, anti-inflammatories, cardiovascular and antihypertensive therapeutic classes. Likewise, sediments collected from untreated wastewater sewers resulted more contaminated. Ionic, non-ionic surfactants and personal care products were the most abundant compounds found in waters and sediments by suspect screening analysis. The risk associated with PPs contamination for aquatic organisms was relatively high in samples of marine receiving waters of the bay (with a risk quotient value up to 33,599). The levels of PPs in seawater and sediment compartments were generally not hazardous (RQ < 0.01), except for estrone with a calculated RQ = 2775.

A new opening for the tricky untargeted investigation of natural and modified short peptides.

Short peptides are of extreme interest in clinical and food research fields, nevertheless they still represent a crucial analytical issue. The main aim of this paper was the development of an analytical platform for a considerable advancement in short peptides identification. For the first time, short sequences presenting both natural and post-translationally modified amino acids were comprehensively studied thanks to the generation of specific databases. Short peptide databases had a dual purpose. First, they were employed as inclusion lists for a suspect screening mass-spectrometric analysis, overcoming the limits of data dependent acquisition mode and allowing the fragmentation of such low-abundance substances. Moreover, the databases were implemented in Compound Discoverer 3.0, a software dedicated to the analysis of short molecules, for the creation of a data processing workflow specifically dedicated to short peptide tentative identification. For this purpose, a detailed study of short peptide fragmentation pathways was carried out for the first time. The proposed method was applied to the study of short peptide sequences in enriched urine samples and led to the tentative identification more than 200 short natural and modified short peptides, the highest number ever reported.