Nontargeted Discovery of Novel Contaminants in the Great Lakes Region: A Comparison of Fish Fillets and Fish Consumers

Unraveling the Exposure Spectrum of PFAS in Fluorochemical Occupational Workers: Structural Diversity, Temporal Trends, and Risk Prioritization

Despite extensive poly/perfluoroalkyl substance (PFAS) discovery studies in various samples, the exposure spectrum in fluorochemical occupational workers remains largely unexplored. Here, serum samples from 28 workers at a fluorochemical facility were analyzed using nontarget techniques, identifying 64 PFAS classes, including 15 novel ones such as pentafluorosulfur ether-substituted perfluoroalkyl sulfonic acids, hydrogen-substituted perfluoroalkylamines, and perfluoroalkylsulfonyl protocatechualdehyde esters. Temporal trend analyses (2008-2018) revealed stable levels for most PFAS but an increase in perfluorobutanoic acid (PFBA) and perfluorohexanesulfonic acid (PFHxS), suggesting industrial shifts from long-chain PFAS to short-chain homologues in China since the early 2010s. Commonly reported structurally modified PFAS (e.g., hydrogen/carbonyl/chlorine substitution, ether insertion, and unsaturation) were likely historical byproducts of legacy PFAS production rather than intentionally manufactured alternatives. A Toxicological Priority Index-based risk assessment, integrating mobility, persistence, and bioaccumulation indices, identified perfluoroalkylamines, di(perfluoroakyl sulfonyl)imides, structurally modified perfluoroalkyl sulfonic acids/carboxylic acids, and perfluoroalkylsulfonamidoacetic acids as high-risk PFAS chemicals. Overall, structurally modified PFAS exhibited higher mobility but lower persistence and bioaccumulation than legacy PFAS, except for chlorinated variants, which showed increased bioaccumulation potential. This study highlights critical gaps in the spectrum of historically emitted PFAS and emphasizes the need for large-scale monitoring and extensive risk assessments to manage emerging PFAS.

Utilization of Negative Chemical Ionization to Expand Nontargeted Screening of Halogenated Organics in Great Lakes Top Predator Fish

Nontargeted screening (NTS) of halogenated contaminants in biota is part of the routine monitoring of the Great Lakes ecosystem. NTS can give insight into new chemicals with possible persistent, bioaccumulative, and toxic (PBT) properties and help quantify known PBT's degradation and transformation products. The most common ionization technique for NTS is electron impact ionization (EI) due to the consistent and easily standardized fragmentation patterns. This research uses electron capture negative ionization (ECNI) as a complementary technique to broaden the range of halogenated contaminants detected in the Great Lakes. ECNI has higher sensitivity and selectivity to halogenated compounds compared to EI. GC × GC-HR-ToF MS with a multimode ion source (MMS) offers consecutive runs in EI and ECNI modes using the same chromatographic setup, facilitating retention time alignment. The exact mass measurements help in identifying compounds found only in ECNI. A total of 85 novel halogenated features were detected, 78% of which were detected only in ECNI. Only 9% of the features were detected in both modes, indicating that ECNI is a necessary complementary technique for NTS of halogenated features.

Chemical exposure in females of childbearing age associated with sex hormones: Evidence from an untargeted exposomic approach

Exposure to organic chemicals can cause reproductive hormones disturbance in women. However, there is very limited evidence regarding real-world chemical exposures in reproductive-aged women and their joint effects on sex hormone levels. Here, we applied non-targeted screening workflow based on High-Performance Liquid Chromatography-High-Resolution Mass Spectrometry to investigate the serum chemical exposome of 156 women of childbearing age from Jinan, China. A total of 185 exogenous chemicals from 19 categories were identified in at least 80% of serum samples with confidence levels 1-3, 84 of which have never been reported in humans, and 9 of those showed active effects on multiple biological targets in ToxCast program. A combination of grouped weighted quantile sum regression (GWQS), weighted quantile sum regression (WQS), quantile g calculation (q g-comp), and Bayesian kernel machine regression (BKMR) models indicated significant associations of chemical mixture exposure with progesterone (P4), testosterone (T), and luteinizing hormone (LH)/follicle-stimulating hormone (FSH) ratios, and 7, 4, and 8 priority contributors were identified, respectively, such as fipronil sulfone for P4, dicyclohexyl phthalate for T, and 3-hydroxybenzyl alcohol for LH/FSH. Three chemicals closely related to androgen synthesis and metabolism were proposed. Restricted cubic spline curves showed that 10 of the 28 priority compound-hormone pairs displayed significant non-monotonic exposure-response relationships. This study provides more information on the chemical exposome in Chinese women of childbearing age and has important implications for understanding the effect of chemical co-exposure on sex hormone homeostasis in women.

Exploring Prenatal Exposure to Halogenated Compounds and Its Relationship with Birth Outcomes Using Nontarget Analysis

Halogenated organic compounds (HOCs) are a class of contaminants showing high toxicity, low biodegradability, and high bioaccumulation potential, especially chlorinated and brominated HOCs (Cl/Br-HOCs). Knowledge gaps exist on whether novel Cl/Br-HOCs could penetrate the placental barrier and cause adverse birth outcomes. Herein, 326 cord blood samples were collected in a hospital in Jinan, Shandong Province from February 2017 to January 2022, and 44 Cl/Br-HOCs were identified with communicating confidence level above 4 based on a nontarget approach, covering veterinary drugs, pesticides, and their transformation products, pharmaceutical and personal care products, disinfection byproducts, and so on. To our knowledge, the presence of closantel, bromoxynil, 4-hydroxy-2,5,6-trichloroisophthalonitrile, 2,6-dibromo-4-nitrophenol, and related components in cord blood samples was reported for the first time. Both multiple linear regression (MLR) and Bayesian kernel machine regression (BKMR) models were applied to evaluate the relationships of newborn birth outcomes (birth weight, length, and ponderal index) with individual Cl/Br-HOC and Cl/Br-HOCs mixture exposure, respectively. A significantly negative association was observed between pentachlorophenol exposure and newborn birth length, but the significance vanished after the false discovery rate correction. The BKMR analysis showed that Cl/Br-HOCs mixture exposure was significantly associated with reduced newborn birth length, indicating higher risks of fetal growth restriction. Our findings offer an overview of Cl/Br-HOCs exposome during the early life stage and enhance the understanding of its exposure risks.

Closing the Organofluorine Mass Balance in Marine Mammals Using Suspect Screening and Machine Learning-Based Quantification

High-resolution mass spectrometry (HRMS)-based suspect and nontarget screening has identified a growing number of novel per- and polyfluoroalkyl substances (PFASs) in the environment. However, without analytical standards, the fraction of overall PFAS exposure accounted for by these suspects remains ambiguous. Fortunately, recent developments in ionization efficiency (IE) prediction using machine learning offer the possibility to quantify suspects lacking analytical standards. In the present work, a gradient boosted tree-based model for predicting log IE in negative mode was trained and then validated using 33 PFAS standards. The root-mean-square errors were 0.79 (for the entire test set) and 0.29 (for the 7 PFASs in the test set) log IE units. Thereafter, the model was applied to samples of liver from pilot whales (n = 5; East Greenland) and white beaked dolphins (n = 5, West Greenland; n = 3, Sweden) which contained a significant fraction (up to 70%) of unidentified organofluorine and 35 unquantified suspect PFASs (confidence level 2-4). IE-based quantification reduced the fraction of unidentified extractable organofluorine to 0-27%, demonstrating the utility of the method for closing the fluorine mass balance in the absence of analytical standards.

Comparison of high-resolution mass spectrometry acquisition methods for the simultaneous quantification and identification of per- and polyfluoroalkyl substances (PFAS)

Simultaneous identification and quantification of per- and polyfluoroalkyl substances (PFAS) were evaluated for three quadrupole time-of-flight mass spectrometry (QTOF) acquisition methods. The acquisition methods investigated were MS-Only, all ion fragmentation (All-Ions), and automated tandem mass spectrometry (Auto-MS/MS). Target analytes were the 25 PFAS of US EPA Method 533 and the acquisition methods were evaluated by analyte response, limit of quantification (LOQ), accuracy, precision, and target-suspect screening identification limit (IL). PFAS LOQs were consistent across acquisition methods, with individual PFAS LOQs within an order of magnitude. The mean and range for MS-Only, All-Ions, and Auto-MS/MS are 1.3 (0.34-5.1), 2.1 (0.49-5.1), and 1.5 (0.20-5.1) pg on column. For fast data processing and tentative identification with lower confidence, MS-Only is recommended; however, this can lead to false-positives. Where high-confidence identification, structural characterisation, and quantification are desired, Auto-MS/MS is recommended; however, cycle time should be considered where many compounds are anticipated to be present. For comprehensive screening workflows and sample archiving, All-Ions is recommended, facilitating both quantification and retrospective analysis. This study validated HRMS acquisition approaches for quantification (based upon precursor data) and exploration of identification workflows for a range of PFAS compounds.

A targeted and non-targeted discovery screening approach for poly-and per-fluoroalkyl substances in model environmental biota samples

A comprehensive analytical approach for targeted and non-targeted discovery screening of per- and polyfluoroalkyl substances (PFAS) was developed and applied to model complex environmental biotic samples. Samples were extracted by formic acid-acetonitrile solution and cleaned up and fractionated by SPE (WAX). Target PFAS quantification was performed by ultra-high performance liquid chromatography interfaced with a triple quadrupole mass spectrometer (UPLC-QqQ-MS/MS). Non-targeted analysis (NTA) PFAS screening was performed with UPLC coupled with a quadrupole-Exactive orbitrap high resolution mass spectrometer (UPLC-Q-Exactive-HRMS). An iterative exclusion (IE) approach was applied to data acquisition for NTA suspect screening to increase the potential for unknown PFAS discovery with MS/MS. A complex workflow in Compound Discoverer was set up to automate data processing of the PFAS suspects search. New mass lists and MS/MS databases, which included a large number of PFAS, were set up and introduced into the search for high-throughput structure identification using HRMS techniques. The integrated targeted-NTA method successfully analyzed for legacy and alternative PFAS in model environmental biota samples, namely polar bear liver and bird egg samples. Targeted analysis provided unequivocal identification of well known/established PFAS (mainly perfluoroalkyl acids) with quantification at very low levels. The NTA suspect screening was able to determine a broader range of PFAS. The data analysis method offered high-confidence annotations for PFAS despite lacking available authentic standards. Overall, the analytical coverage of PFAS was greater and elucidated other PFAS present in these model apex predators.

Combining large-scale investigation and quantum chemical calculation of pharmaceuticals: Spatiotemporal patterns of occurrence and structural insights into removal

This study investigated the spatiotemporal distribution of 17 pharmaceuticals in wastewater treatment plants (WWTPs) from 17 provinces across China, and explored structural insights into their removal in full-scale wastewater treatment processes by quantum chemistry. Briefly, 10 pharmaceuticals were detected in above 85 % of samples, of which ibuprofen and sulfamethoxazole dominated with concentrations up to the μg/L level. Seasonally, concentrations of psychoactive drugs (PDs) were 1.3-2.6 times higher in summer than in other seasons. Spatially, higher average concentrations were detected in northern WWTPs, and regions with similar economic levels exhibited similar contamination patterns. Pharmaceutical removal in WWTPs ranged from 41.4 % (carbamazepine) to 87.2 % (sulfamethizole), with the secondary treatment segment, especially aerobic treatment units, maintaining an important position. Molecular structural mechanisms behind these removal performances were further revealed. Firstly, we demonstrated a significant association of pharmaceutical overall removal with electrophilicity index (ωcubic) as well as the lowest unoccupied molecular orbital energy (ELUMO). Highly electrophilic pharmaceuticals may persist in WWTPs and their sensitivity to electron exchange reactions accounted for the discrepant removal. In terms of treatment segments, pharmaceuticals with reaction sites masked in molecular structure, such as ibuprofen and venlafaxine, showed a propensity for tertiary treatment suitability. Furthermore, enzymes of aerobic units exhibited excellent docking affinity to pharmaceutical molecules with an average affinity of -7.2 kcal/mol, and hydrogen-bond interactions played an important factor in promoting biodegradation. Our results emphasize the necessity of assessing pharmaceutical contamination on a larger spatiotemporal scale. Moreover, the structural insights into removal phenomena offer scientific molecular-level justification for the design and optimization of pharmaceutical treatment technologies in WWTPs.

IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets

Poor chemical annotation of high-resolution mass spectrometry data limits applications of untargeted metabolomics datasets. Our new software, the Integrated Data Science Laboratory for Metabolomics and Exposomics─Composite Spectra Analysis (IDSL.CSA) R package, generates composite mass spectra libraries from MS1-only data, enabling the chemical annotation of high-resolution mass spectrometry coupled with liquid chromatography peaks regardless of the availability of MS2 fragmentation spectra. We demonstrate comparable annotation rates for commonly detected endogenous metabolites in human blood samples using IDSL.CSA libraries versus MS/MS libraries in validation tests. IDSL.CSA can create and search composite spectra libraries from any untargeted metabolomics dataset generated using high-resolution mass spectrometry coupled to liquid or gas chromatography instruments. The cross-applicability of these libraries across independent studies may provide access to new biological insights that may be missed due to the lack of MS2 fragmentation data. The IDSL.CSA package is available in the R-CRAN repository at https://cran.r-project.org/package=IDSL.CSA. Detailed documentation and tutorials are provided at https://github.com/idslme/IDSL.CSA.

IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets

Poor chemical annotation of high-resolution mass spectrometry data limit applications of untargeted metabolomics datasets. Our new software, the Integrated Data Science Laboratory for Metabolomics and Exposomics - Composite Spectra Analysis (IDSL.CSA) R package, generates composite mass spectra libraries from MS1-only data, enabling the chemical annotation of LC/HRMS peaks regardless of the availability of MS2 fragmentation spectra. We demonstrate comparable annotation rates for commonly detected endogenous metabolites in human blood samples using IDSL.CSA libraries versus MS/MS libraries in validation tests. IDSL.CSA can create and search composite spectra libraries from any untargeted metabolomics dataset generated using high-resolution mass spectrometry coupled to liquid or gas chromatography instruments. The cross-applicability of these libraries across independent studies may provide access to new biological insights that may be missed due to the lack of MS2 fragmentation data. The IDSL.CSA package is available in the R CRAN repository at https://cran.r-project.org/package=IDSL.CSA . Detailed documentation and tutorials are provided at https://github.com/idslme/IDSL.CSA .

For Table of Contents Only

Suspect Screening and Nontargeted Analysis of Per- and Polyfluoroalkyl Substances in a Lake Ontario Food Web

Per- and polyfluoroalkyl substances (PFAS) are globally distributed in the natural environment, and their persistent and bioaccumulative potential illicit public concern. The production of certain PFAS has been halted or controlled by regulation due to their adverse effect on the health of humans and wildlife. However, new PFAS are continuously developed as alternatives to legacy PFAS. Additionally, many precursors are unknown, and their metabolites have not been assessed. To better understand the PFAS profiles in the Lake Ontario (LO) aquatic food web, a quadrupole time-of-flight mass spectrometer (QToF) coupled to ultrahigh-performance liquid chromatography (UPLC) was used to generate high-resolution mass spectra (HRMS) from sample extracts. The HRMS data files were analyzed using an isotopic profile deconvoluted chromatogram (IPDC) algorithm to isolate PFAS profiles in aquatic organisms. Fourteen legacy PFAAs (C5-C14) and 15 known precursors were detected in the LO food web. In addition, over 400 unknown PFAS features that appear to biomagnify in the LO food web were found. Profundal benthic organisms, deepwater sculpin(Myoxocephalus thompsonii), and Mysis were found to have more known precursors than other species in the food web, suggesting that there is a large reservoir of fluorinated substances in the benthic zone.

Enhancing spectral quality in complex environmental matrices: Supporting suspect and non-target screening in zebra mussels with ion mobility

Identification of bioaccumulating contaminants of emerging concern (CECs) via suspect and non-target screening remains a challenging task. In this study, ion mobility separation with high-resolution mass spectrometry (IM-HRMS) was used to investigate the effects of drift time (DT) alignment on spectrum quality and peak annotation for screening of CECs in complex sample matrices using data independent acquisition (DIA). Data treatment approaches (Binary Sample Comparison) and prioritisation strategies (Halogen Match, co-occurrence of features in biota and the water phase) were explored in a case study on zebra mussel (Dreissena polymorpha) in Lake Mälaren, Sweden's largest drinking water reservoir. DT alignment evidently improved the fragment spectrum quality by increasing the similarity score to reference spectra from on average (±standard deviation) 0.33 ± 0.31 to 0.64 ± 0.30 points, thus positively influencing structure elucidation efforts. Thirty-two features were tentatively identified at confidence level 3 or higher using MetFrag coupled with the new PubChemLite database, which included predicted collision cross-section values from CCSbase. The implementation of predicted mobility data was found to support compound annotation. This study illustrates a quantitative assessment of the benefits of IM-HRMS on spectral quality, which will enhance the performance of future screening studies of CECs in complex environmental matrices.

IDSL.UFA Assigns High-Confidence Molecular Formula Annotations for Untargeted LC/HRMS Data Sets in Metabolomics and Exposomics

Untargeted liquid chromatography/high-resolution mass spectrometry (LC/HRMS) assays in metabolomics and exposomics aim to characterize the small molecule chemical space in a biospecimen. To gain maximum biological insights from these data sets, LC/HRMS peaks should be annotated with chemical and functional information including molecular formula, structure, chemical class, and metabolic pathways. Among these, molecular formulas may be assigned to LC/HRMS peaks through matching theoretical and observed isotopic profiles (MS1) of the underlying ionized compound. For this, we have developed the Integrated Data Science Laboratory for Metabolomics and Exposomics-United Formula Annotation (IDSL.UFA) R package. In the untargeted metabolomics validation tests, IDSL.UFA assigned 54.31-85.51% molecular formula for true positive annotations as the top hit and 90.58-100% within the top five hits. Molecular formula annotations were also supported by tandem mass spectrometry data. We have implemented new strategies to (1) generate formula sources and their theoretical isotopic profiles, (2) optimize the formula hits ranking for the individual and aligned peak lists, and (3) scale IDSL.UFA-based workflows for studies with larger sample sizes. Annotating the raw data for a publicly available pregnancy metabolome study using IDSL.UFA highlighted hundreds of new pregnancy-related compounds and also suggested the presence of chlorinated perfluorotriether alcohols (Cl-PFTrEAs) in human specimens. IDSL.UFA is useful for human metabolomics and exposomics studies where we need to minimize the loss of biological insights in untargeted LC/HRMS data sets. The IDSL.UFA package is available in the R CRAN repository https://cran.r-project.org/package=IDSL.UFA. Detailed documentation and tutorials are also provided at www.ufa.idsl.me.

Simplifying Nontargeted Analysis of PFAS in Complex Food Matrixes

Background

Per- and polyfluoroalkyl substances (PFAS) are a class of toxic environmental contaminants that are characterized by their high chemical stability and enormous structural diversity.

Objective

The limited availability of PFAS reference standards is the main motivation for developing nontargeted analytical methods. Current concepts are complex and rely on multiple filtering steps (e.g., assumption of homologous series, detection of mass defects, generic fragments, and spectra obtained from web-based sources).

Method

High-resolution mass spectrometry (HRMS)–based chromatograms of fish liver extracts were deconvoluted. Based on the ion abundance between the monoisotopic and the first isotopic peak, the number of carbons (C) was estimated for each extracted feature. A mass over carbon (m/C) and mass defect over carbon (md/C) ratio was calculated.

Results

PFAS-related peaks are strongly discriminated from matrix peaks when plotting m/C versus md/C. This enables nontarget detection of PFAS present at low µg/kg concentration in complex food matrixes.

Conclusions

The proposed concept is highly selective by revealing a relatively small number of high-probability PFAS candidates (features). The small number of surviving candidates permits the MS/MS-based confirmation of each feature. This strategy led to the finding of one PFAS not present in the reference standard solution, as well as the detection of an unexpected set of PFAS adducts.

Highlights

The proposed concept of mass over carbon versus mass defect over carbon is suited for the nontarget detection of low amounts of PFAS in complex matrixes. It should be capable of detecting any PFAS (F/H ratio should be >1:1) regardless of the ionization mode.

IDSL.IPA Characterizes the Organic Chemical Space in Untargeted LC/HRMS Data Sets

Generating comprehensive and high-fidelity metabolomics data matrices from LC/HRMS data remains to be extremely challenging for population-scale large studies (n > 200). Here, we present a new data processing pipeline, the Intrinsic Peak Analysis (IDSL.IPA) R package (https://ipa.idsl.me), to generate such data matrices specifically for organic compounds. The IDSL.IPA pipeline incorporates (1) identifying potential ¹²C and ¹³C ion pairs in individual mass spectra; (2) detecting and characterizing chromatographic peaks using a new sensitive and versatile approach to perform mass correction, peak smoothing, baseline development for local noise measurement, and peak quality determination; (3) correcting retention time and cross-referencing peaks from multiple samples by a dynamic retention index marker approach; (4) annotating peaks using a reference database of m/z and retention time; and (5) accelerating data processing using a parallel computation of the peak detection and alignment steps for larger studies. This pipeline has been successfully evaluated for studies ranging from 200 to 1600 samples. By specifically isolating high quality and reliable signals pertaining to carbon-containing compounds in untargeted LC/HRMS data sets from larger studies, IDSL.IPA opens new opportunities for discovering new biological insights in the population-scale metabolomics and exposomics projects. The package is available in the R CRAN repository at https://cran.r-project.org/package=IDSL.IPA.

Widening the Lens on PFASs: Direct Human Exposure to Perfluoroalkyl Acid Precursors (pre-PFAAs)

Determining health risks associated with per-/polyfluoroalkyl substances (PFASs) is a highly complex problem requiring massive efforts for scientists, risk assessors, and regulators. Among the most poorly understood pressing questions is the relative importance of pre-PFAAs, which are PFASs that degrade to highly persistent perfluoroalkyl acids. How many of the vast number of existing pre-PFAAs are relevant for direct human exposure, and what are the predominant exposure pathways? What evidence of direct exposure to pre-PFAAs is provided by human biomonitoring studies? How important are pre-PFAAs and their biotransformation products for human health risk assessment? This article outlines recent progress and recommendations toward widening the lens on human PFAS exposure to include the pre-PFAA subclass.

Comparison of untargeted and targeted perfluoroalkyl acids measured in adolescent girls

Quantitative biomonitoring (e.g., targeted analysis) has served as the gold standard for environmental exposure biomonitoring for several decades. Recent advancements to broaden exposomic research brought new semi-quantitative untargeted assays that capture a wide range of endogenous metabolites and exogenous exposures in a single assay for discovery, though usually at the expense of absolute quantitation. The high-resolution mass spectrometers (HRMS) typically used in untargeted workflows are sensitive and robust, but there do not yet exist comprehensive comparisons between environmental chemicals at population exposure levels measured using targeted and untargeted assays. Using liquid chromatography (LC)-HRMS, we measured per- and polyfluoroalkyl substances (PFAS) including perfluorohexane sulfonate (PFHxS), n-perfluorooctanoic acid (PFOA), n-perfluorooctanesulfonic acid (PFOS), and perfluorononanoic acid (PFNA) in plasma of 180 girls from New York City, and compared them to previously obtained targeted measures using correlation and rank order methods. We showed high agreement between the methods with Spearman Rhos ranging from 0.69 to 0.92 and weighted Kappa's from 0.62 to 0.82 for tertiles among the PFAS. This finding demonstrates that semi-quantitative data from untargeted assays designed for exposomics can be reliably used to estimate environmental exposures occurring in the general population, providing an economic alternative to targeted assays. We also describe an approach that can be used to compare relative quantitation measurements from an untargeted assay to traditional targeted measures to establish fit-for-purpose usability and validation. These results suggest that environmental exposure measures from untargeted assays can serve as reliable inputs into statistical analysis for discovery and for determining their resultant biological impacts. Future efforts to develop new statistical approaches for standardization and merging with targeted measures-toward harmonization-will further enhance the utility of untargeted assays in environmental epidemiology.

Recent advances in mass spectrometry analytical techniques for per- and polyfluoroalkyl substances (PFAS)

The ubiquitous presence of per- and polyfluoroalkyl substances (PFAS) in various environments has led to increasing concern, and these chemicals have been confirmed as global contaminants. Following the chemical regulatory restrictions imposed, PFAS alternatives that are presumed to be less toxic have been manufactured to replace the traditional ones in the market. However, owing to the original release and alternative usage, continuous accumulation of PFAS has been reported in environmental and human samples, with uncertain consequences for ecosystem and human health. It is crucial to promote and improve existing analytical techniques to facilitate the detection of trace amounts of PFAS in diverse environmental matrices. This review summarizes analytical methods that have been applied to and advanced for targeted detection and suspect screening of PFAS, which mainly include (i) sampling and sample preparation methods for various environment matrices and organisms, and quality assurance/quality control during the analysis process, and (ii) quantitative methods for targeted analysis and automated suspect screening strategies for non-targeted PFAS analysis, together with their applications, advantages, shortcomings, and need for new method development.

Bioaccumulation and metabolic response of PFAS mixtures in wild-caught freshwater turtles (Emydura macquariimacquarii) using omics-based ecosurveillance techniques

PFAS mixtures in the environment are common and identifying PFAS constituents, bioaccumulation, and biological impacts of mixtures remains a challenge. Here, an omics-based ecosurveillance approach was taken to investigate the impacts of PFAS pollution in freshwater turtles (Emydura macquariimacquarii). Four turtles were collected from an impacted waterway downstream from an industrial source of PFAS contamination in Queensland, Australia and analysed for 49 different PFAS. One turtle was collected from a suitable control site. PFAS concentrations were quantified in turtle serum using an established targeted methodology. The serum PFAS concentration was ten-fold greater at the impacted site (Σ49 PFAS 1933 ± 481 ng/mL) relative to the control sample (Σ49 PFAS 140 ng/mL). Perfluorooctane sulfonate (PFOS; 889 ± 56 ng/mL) was 235 times higher in turtle serum than in the water that they were collected from (ΣPFAS 32.0 μg/L). Perfluorobutane sulfonamide (FBSA; 403 ± 83 ng/mL) and perfluorohexane sulfonamide (FHxSA; 550 ± 330 ng/mL) were also reported at substantial concentrations in the serum of impacted turtles. Biochemical profiles were analysed using a mixture of liquid chromatography triple quadrupole (QqQ) and quadrupole time-of-flight (QToF) mass spectrometry methodologies. These profiles demonstrated a positive correlation in the impacted turtles exposed to elevated PFAS with an enhanced purine metabolism, glycerophosphocholines and an innate immune response, which suggest an inflammation response, metabolic preservation and re-routing of central carbon metabolites. Conversely, lipid transport and binding activity were negatively correlated. Using these preliminary data, we were able to demonstrate the negative metabolic impact from PFAS mixtures on turtle metabolic health. With further research on a larger turtle cohort, omics-based data will contribute towards linking adverse outcome pathways for turtle populations exposed to PFAS mixtures. Moreover, expanding the use of ecosurveillance tools will inform mechanistic toxicological data for risk assessment and regulatory applications.

The Eco-Exposome Concept: Supporting an Integrated Assessment of Mixtures of Environmental Chemicals

Organisms are exposed to ever-changing complex mixtures of chemicals over the course of their lifetime. The need to more comprehensively describe this exposure and relate it to adverse health effects has led to formulation of the exposome concept in human toxicology. Whether this concept has utility in the context of environmental hazard and risk assessment has not been discussed in detail. In this Critical Perspective, we propose-by analogy to the human exposome-to define the eco-exposome as the totality of the internal exposure (anthropogenic and natural chemicals, their biotransformation products or adducts, and endogenous signaling molecules that may be sensitive to an anthropogenic chemical exposure) over the lifetime of an ecologically relevant organism. We describe how targeted and nontargeted chemical analyses and bioassays can be employed to characterize this exposure and discuss how the adverse outcome pathway concept could be used to link this exposure to adverse effects. Available methods, their limitations, and/or requirement for improvements for practical application of the eco-exposome concept are discussed. Even though analysis of the eco-exposome can be resource-intensive and challenging, new approaches and technologies make this assessment increasingly feasible. Furthermore, an improved understanding of mechanistic relationships between external chemical exposure(s), internal chemical exposure(s), and biological effects could result in the development of proxies, that is, relatively simple chemical and biological measurements that could be used to complement internal exposure assessment or infer the internal exposure when it is difficult to measure. Environ Toxicol Chem 2022;41:30-45. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.