Microcystin-LR aerosol induces inflammatory responses in healthy human primary airway epithelium.

Harmful algal blooms plague bodies of freshwater globally. These blooms are often composed of outgrowths of cyanobacteria capable of producing the heptapeptide Microcystin-LR (MC-LR) which is a well-known hepatotoxin. Recently, MC-LR has been detected in aerosols generated from lake water. However, the risk for human health effects due to MC-LR inhalation exposure have not been extensively investigated. In this study, we exposed a fully differentiated 3D human airway epithelium derived from 14 healthy donors to MC-LR-containing aerosol once a day for 3 days. Concentrations of MC-LR ranged from 100 pM to 1 µM. Although there were little to no detrimental alterations in measures of the airway epithelial function (i.e. cell survival, tissue integrity, mucociliary clearance, or cilia beating frequency), a distinct shift in the transcriptional activity was found. Genes related to inflammation were found to be upregulated such as C-C motif chemokine 5 (CCL5; log2FC = 0.57, p = 0.03) and C-C chemokine receptor type 7 (CCR7; log2FC = 0.84, p = 0.03). Functionally, conditioned media from MC-LR exposed airway epithelium was also found to have significant chemo-attractive properties for primary human neutrophils. Additionally, increases were found in the concentration of secreted chemokine proteins in the conditioned media such as CCL1 (log2FC = 5.07, p = 0.0001) and CCL5 (log2FC = 1.02, p = 0.046). These results suggest that MC-LR exposure to the human airway epithelium is capable of inducing an inflammatory response that may potentiate acute or chronic disease.

Simulated Night-Shift Schedule Disrupts the Plasma Lipidome and Reveals Early Markers of Cardiovascular Disease Risk.

Introduction: The circadian system coordinates daily rhythms in lipid metabolism, storage and utilization. Disruptions of internal circadian rhythms due to altered sleep/wake schedules, such as in night-shift work, have been implicated in increased risk of cardiovascular disease and metabolic disorders. To determine the impact of a night-shift schedule on the human blood plasma lipidome, an in-laboratory simulated shift work study was conducted. Methods: Fourteen healthy young adults were assigned to 3 days of either a simulated day or night-shift schedule, followed by a 24-h constant routine protocol with fixed environmental conditions, hourly isocaloric snacks, and constant wakefulness to investigate endogenous circadian rhythms. Blood plasma samples collected at 3-h intervals were subjected to untargeted lipidomics analysis. Results: More than 400 lipids were identified and quantified across 21 subclasses. Focusing on lipids with low between-subject variation per shift condition, alterations in the circulating plasma lipidome revealed generally increased mean triglyceride levels and decreased mean phospholipid levels after night-shift relative to day-shift. The circadian rhythms of triglycerides containing odd chain fatty acids peaked earlier during constant routine after night-shift. Regardless of shift condition, triglycerides tended to either peak or be depleted at 16:30 h, with chain-specific differences associated with the direction of change. Discussion: The simulated night-shift schedule was associated with altered temporal patterns in the lipidome. This may be premorbid to the elevated cardiovascular risk that has been found epidemiologically in night-shift workers.

Risk assessment of predicted serum concentrations of bisphenol A in children and adults following treatment with dental composite restoratives, dental sealants, or orthodontic adhesives using physiologically based pharmacokinetic modeling.

Bisphenol A (BPA) is a chemical used to manufacture bisphenol A glycidyl methacrylate (BisGMA). BisGMA has been used for decades in dental composite restoratives, sealants, and adhesives. Based on published studies, exposure to low concentrations of BPA are possible from dental and orthodontic devices. The serum BPA concentrations arising from such devices and oral doses were predicted using a PBPK model in children and adult females based on 1) published extraction data for cured and uncured 3M ESPE Filtek Supreme Ultra Flowable, 3M ESPE Filtek Bulk Fill Restorative, and 3M ESPE Clinpro Sealant and 2) published 20% ethanol/water and water rinsate data following orthodontic application with 3M ESPE Transbond MIP Primer and 3M ESPE Transbond XT Adhesive. Predicted oral exposure to BPA arising from these dental and orthodontic devices is low (median <10 ng/treatment) and predicted serum BPA concentrations were also low (<10-4 nM). Even the maximum predicted exposure in this study (533.2 ng/treatment) yields a margin of exposure of 7.5 relative to the EFSA t-TDI (4 µg/kg-day) and is only 2.8% of the daily BPA exposure for the US population in a 58-kg woman (15,660 ng/day). Therefore, the exposure to BPA arising from the 3M ESPE dental and orthodontic devices evaluated in this study is negligible relative to daily BPA exposure in the general population and these potential BPA sources do not constitute a risk to patients.

Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples.

The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in part from our in silico chemical library engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multiattribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally derived libraries for building evidence for the presence of molecules in complex samples.

ISiCLE: A Quantum Chemistry Pipeline for Establishing in Silico Collision Cross Section Libraries.

High-throughput, comprehensive, and confident identifications of metabolites and other chemicals in biological and environmental samples will revolutionize our understanding of the role these chemically diverse molecules play in biological systems. Despite recent technological advances, metabolomics studies still result in the detection of a disproportionate number of features that cannot be confidently assigned to a chemical structure. This inadequacy is driven by the single most significant limitation in metabolomics, the reliance on reference libraries constructed by analysis of authentic reference materials with limited commercial availability. To this end, we have developed the in silico chemical library engine (ISiCLE), a high-performance computing-friendly cheminformatics workflow for generating libraries of chemical properties. In the instantiation described here, we predict probable three-dimensional molecular conformers (i.e., conformational isomers) using chemical identifiers as input, from which collision cross sections (CCS) are derived. The approach employs first-principles simulation, distinguished by the use of molecular dynamics, quantum chemistry, and ion mobility calculations, to generate structures and chemical property libraries, all without training data. Importantly, optimization of ISiCLE included a refactoring of the popular MOBCAL code for trajectory-based mobility calculations, improving its computational efficiency by over 2 orders of magnitude. Calculated CCS values were validated against 1983 experimentally measured CCS values and compared to previously reported CCS calculation approaches. Average calculated CCS error for the validation set is 3.2% using standard parameters, outperforming other density functional theory (DFT)-based methods and machine learning methods (e.g., MetCCS). An online database is introduced for sharing both calculated and experimental CCS values ( metabolomics.pnnl.gov ), initially including a CCS library with over 1 million entries. Finally, three successful applications of molecule characterization using calculated CCS are described, including providing evidence for the presence of an environmental degradation product, the separation of molecular isomers, and an initial characterization of complex blinded mixtures of exposure chemicals. This work represents a method to address the limitations of small molecule identification and offers an alternative to generating chemical identification libraries experimentally by analyzing authentic reference materials. All code is available at github.com/pnnl .

Comparative estrogenicity of endogenous, environmental and dietary estrogens in pregnant women II: Total estrogenicity calculations accounting for competitive protein and receptor binding and potency.

Evaluating the biological significance of human-relevant exposures to environmental estrogens involves assessing the individual and total estrogenicity of endogenous and exogenous estrogens found in serum, for example from biomonitoring studies. We developed a method for this assessment by integrating approaches for (i) measuring total hormone concentrations by mass spectrometry (Fleck et al., 2018), (ii) calculating hormone bioavailable concentrations in serum and, (iii) solving multiple equilibria between estrogenic ligands and receptors, and (iv) quantitatively describing key elements of estrogen potency. The approach was applied to endogenous (E1, E2, E3, E4), environmental (BPA), and dietary Genistein (GEN), Daidzein (DDZ) estrogens measured in the serum of thirty pregnant women. Fractional receptor occupancy (FRO) based estrogenicity was dominated by E1, E2 and E3 (ER-α, 94.4-99.2% (median: 97.3%), ER-ß, 82.7-97.7% (median: 92.8%), as was the total response (TR), which included ligand specific differences in recruitment of co-activator proteins (RCA). The median FRO for BPA was at least five orders of magnitude lower than E1, E2 and E3, and three orders of magnitude lower than the fetal derived E4 and GEN and DDZ. BPA contributed less than 1/1000th of the normal daily variability in total serum estrogenicity in this cohort of pregnant women.

All that is silver is not toxic: silver ion and particle kinetics reveals the role of silver ion aging and dosimetry on the toxicity of silver nanoparticles.

BACKGROUND: When suspended in cell culture medium, nano-objects composed of soluble metals such as silver can dissolve resulting in ion formation, altered particle properties (e.g. mass, morphology, etc.), and modulated cellular dose. Cultured cells are exposed not just to nanoparticles but to a complex, dynamic mixture of altered nanoparticles, unbound ions, and ion-ligand complexes. Here, three different cell types (RAW 264.7 macrophages and bone marrow derived macrophages from wild-type C57BL/6 J mice and Scavenger Receptor A deficient (SR-A(-/-)) mice) were exposed to 20 and 110 nm silver nanoparticles, and RAW 264.7 cells were exposed to freshly mixed silver ions, aged silver ions (ions incubated in cell culture medium), and ions formed from nanoparticle dissolution. The In Vitro Sedimentation, Diffusion, Dissolution, and Dosimetry Model (ISD3) was used to predict dose metrics for each exposure scenario. RESULTS: Silver nanoparticles, freshly mixed ions, and ions from nanoparticle dissolution were toxic, while aged ions were not toxic. Macrophages from SR-A(-/-) mice did not take up 20 nm silver nanoparticles as well as wild-types but demonstrated no differences in silver levels after exposure to 110 nm nanoparticles. Dose response modeling with ISD3 predicted dose metrics suggest that amount of ions in cells and area under the curve (AUC) of ion amount in cells are the most predictive of cell viability after nanoparticle and combined nanoparticle/dissolution-formed-ions exposures, respectively. CONCLUSIONS: Results of this study suggest that the unbound silver cation is the ultimate toxicant, and ions formed extracellularly drive toxicity after exposure to nanoparticles. Applying computational modeling (ISD3) to better understand dose metrics for soluble nanoparticles allows for better interpretation of in vitro hazard assessments.

An automated framework for NMR chemical shift calculations of small organic molecules.

When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typically depended upon to build libraries experimentally. Considering complex biological samples, such as blood and soil, the entirety of NMR spectra required for all possible compounds would be infeasible to ascertain due to limitations of available standards and experimental processing time. As an alternative, we introduce the in silico Chemical Library Engine (ISiCLE) NMR chemical shift module to accurately and automatically calculate NMR chemical shifts of small organic molecules through use of quantum chemical calculations. ISiCLE performs density functional theory (DFT)-based calculations for predicting chemical properties-specifically NMR chemical shifts in this manuscript-via the open source, high-performance computational chemistry software, NWChem. ISiCLE calculates the NMR chemical shifts of sets of molecules using any available combination of DFT method, solvent, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Calculated NMR chemical shifts are provided to the user for each molecule, along with comparisons with respect to a number of metrics commonly used in the literature. Here, we demonstrate ISiCLE using a set of 312 molecules, ranging in size up to 90 carbon atoms. For each, calculation of NMR chemical shifts have been performed with 8 different levels of DFT theory, and with solvation effects using the implicit solvent Conductor-like Screening Model. The DFT method dependence of the calculated chemical shifts have been systematically investigated through benchmarking and subsequently compared to experimental data available in the literature. Furthermore, ISiCLE has been applied to a set of 80 methylcyclohexane conformers, combined via Boltzmann weighting and compared to experimental values. We demonstrate that our protocol shows promise in the automation of chemical shift calculations and, ultimately, the expansion of chemical shift libraries.

Comparative estrogenicity of endogenous, environmental and dietary estrogens in pregnant women I: Serum levels, variability and the basis for urinary biomonitoring of serum estrogenicity.

Biomonitoring of human exposure to estrogens most frequently focuses on environmental and dietary estrogens, and infrequently includes measures of exposure to potent endogenous estrogens present in serum. Pregnancy is a developmentally sensitive period during which "added" serum estrogenicity exceeding normal intra-individual daily variability may be of particular relevance. We made repeated measurements of serum concentrations of estrone (E1), estradiol (E2), estriol (E3), estetrol (E4), daidzein (DDZ), genistein (GEN) and bisphenol A (BPA) in thirty pregnant women using ultra-performance liquid chromatography coupled with tandem mass spectrometry detection (UPLC-MS/MS) and electrospray ionization (ESI). Serum E1, E2, and E3 concentrations varied significantly (coefficients of variation 9-10%) with broad ranges across the cohort: 1.61-85.1 nM, 9.09-69.7 nM, and 1.5-36.3 nM respectively. BPA (undetected, estimated from total exposure), DDZ and GEN concentrations were 1-5 orders of magnitude lower. The 24-h urinary elimination profiles of endogenous estrogens were each strongly correlated with their corresponding serum concentrations (Pearson's Correlation Coefficients of 0.83 (E1), 0.84 (E2) and 0.94 (E3)). A multivariate regression analysis produced equations for estimating serum concentrations of E1, E2, E3, E4, GEN and DDZ from urinary elimination rates and gestation period, an important step towards non-invasive biomonitoring for assessment of "added" estrogenicity during pregnancy.

ISD3: a particokinetic model for predicting the combined effects of particle sedimentation, diffusion and dissolution on cellular dosimetry for in vitro systems.

BACKGROUND: The development of particokinetic models describing the delivery of insoluble or poorly soluble nanoparticles to cells in liquid cell culture systems has improved the basis for dose-response analysis, hazard ranking from high-throughput systems, and now allows for translation of exposures across in vitro and in vivo test systems. Complimentary particokinetic models that address processes controlling delivery of both particles and released ions to cells, and the influence of particle size changes from dissolution on particle delivery for cell-culture systems would help advance our understanding of the role of particles and ion dosimetry on cellular toxicology. We developed ISD3, an extension of our previously published model for insoluble particles, by deriving a specific formulation of the Population Balance Equation for soluble particles. RESULTS: ISD3 describes the time, concentration and particle size dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. We applied the model to calculate the particle and ion dosimetry of nanosilver and silver ions in vitro after calibration of two empirical models, one for particle dissolution and one for ion uptake. Total media ion concentration, particle concentration and total cell-associated silver time-courses were well described by the model, across 2 concentrations of 20 and 110 nm particles. ISD3 was calibrated to dissolution data for 20 nm particles as a function of serum protein concentration, but successfully described the media and cell dosimetry time-course for both particles at all concentrations and time points. We also report the finding that protein content in media affects the initial rate of dissolution and the resulting near-steady state ion concentration in solution for the systems we have studied. CONCLUSIONS: By combining experiments and modeling, we were able to quantify the influence of proteins on silver particle solubility, determine the relative amounts of silver ions and particles in exposed cells, and demonstrate the influence of particle size changes resulting from dissolution on particle delivery to cells in culture. ISD3 is modular and can be adapted to new applications by replacing descriptions of dissolution, sedimentation and boundary conditions with those appropriate for particles other than silver.

Implications of Bioremediation of Polycyclic Aromatic Hydrocarbon-Contaminated Soils for Human Health and Cancer Risk.

Bioremediation uses soil microorganisms to degrade polycyclic aromatic hydrocarbons (PAHs) into less toxic compounds and can be performed in situ, without the need for expensive infrastructure or amendments. This review provides insights into the cancer risks associated with PAH-contaminated soils and places bioremediation outcomes in a context relevant to human health. We evaluated which bioremediation strategies were most effective for degrading PAHs and estimated the cancer risks associated with PAH-contaminated soils. Cancer risk was statistically reduced in 89% of treated soils following bioremediation, with a mean degradation of 44% across the B2 group PAHs. However, all 180 treated soils had postbioremediation cancer risk values that exceeded the U.S. Environmental Protection Agency (USEPA) health-based acceptable risk level (by at least a factor of 2), with 32% of treated soils exceeding recommended levels by greater than 2 orders of magnitude. Composting treatments were most effective at biodegrading PAHs in soils (70% average reduction compared with 28-53% for the other treatment types), which was likely due to the combined influence of the rich source of nutrients and microflora introduced with organic compost amendments. Ultimately, bioremediation strategies, in the studies reviewed, were unable to successfully remove carcinogenic PAHs from contaminated soils to concentrations below the target cancer risk levels recommended by the USEPA.

Transgenerational inheritance of neurobehavioral and physiological deficits from developmental exposure to benzo[a]pyrene in zebrafish.

Benzo[a]pyrene (B[a]P) is a well-known genotoxic polycylic aromatic compound whose toxicity is dependent on signaling via the aryl hydrocarbon receptor (AHR). It is unclear to what extent detrimental effects of B[a]P exposures might impact future generations and whether transgenerational effects might be AHR-dependent. This study examined the effects of developmental B[a]P exposure on 3 generations of zebrafish. Zebrafish embryos were exposed from 6 to 120h post fertilization (hpf) to 5 and 10µM B[a]P and raised in chemical-free water until adulthood (F0). Two generations were raised from F0 fish to evaluate transgenerational inheritance. Morphological, physiological and neurobehavioral parameters were measured at two life stages. Juveniles of the F0 and F2 exhibited hyper locomotor activity, decreased heartbeat and mitochondrial function. B[a]P exposure during development resulted in decreased global DNA methylation levels and generally reduced expression of DNA methyltransferases in wild type zebrafish, with the latter effect largely reversed in an AHR2-null background. Adults from the F0 B[a]P exposed lineage displayed social anxiety-like behavior. Adults in the F2 transgeneration manifested gender-specific increased body mass index (BMI), increased oxygen consumption and hyper-avoidance behavior. Exposure to benzo[a]pyrene during development resulted in transgenerational inheritance of neurobehavioral and physiological deficiencies. Indirect evidence suggested the potential for an AHR2-dependent epigenetic route.

PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association.

MOTIVATION: Drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS-MS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS at multiple electric fields and compute their associated collisional cross sections (CCS), we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of data that can then be used to create a reference library of experimental CCS values for use in high throughput omics analyses. RESULTS: We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were within error of those calculated using commercially available instrument vendor software. AVAILABILITY AND IMPLEMENTATION: PIXiE is an open-source tool, freely available on Github. The documentation, source code of the software, and a GUI can be found at https://github.com/PNNL-Comp-Mass-Spec/PIXiE and the source code of the backend workflow library used by PIXiE can be found at https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library . CONTACT: erin.baker@pnnl.gov or thomas.metz@pnnl.gov. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrating ion mobility spectrometry into mass spectrometry-based exposome measurements: what can it add and how far can it go?

Measuring the exposome remains a challenge due to the range and number of anthropogenic molecules that are encountered in our daily lives, as well as the complex systemic responses to these exposures. One option for improving the coverage, dynamic range and throughput of measurements is to incorporate ion mobility spectrometry (IMS) into current MS-based analytical methods. The implementation of IMS in exposomics studies will lead to more frequent observations of previously undetected chemicals and metabolites. LC-IMS-MS will provide increased overall measurement dynamic range, resulting in detections of lower abundance molecules. Alternatively, the throughput of IMS-MS alone will provide the opportunity to analyze many thousands of longitudinal samples over lifetimes of exposure, capturing evidence of transitory accumulations of chemicals or metabolites. The volume of data corresponding to these new chemical observations will almost certainly outpace the generation of reference data to enable their confident identification. In this perspective, we briefly review the state-of-the-art in measuring the exposome, and discuss the potential use for IMS-MS and the physico-chemical property of collisional cross section in both exposure assessment and molecular identification.

Urine and serum biomonitoring of exposure to environmental estrogens II: Soy isoflavones and zearalenone in pregnant women.

UNLABELLED: Urine and serum biomonitoring was used to measure internal exposure to selected dietary estrogens in a cohort of 30 pregnant women. Exposure was measured over a period comprising one-half day in the field (6 h) and one day in a clinic (24 h). Biomonitoring of the dietary phytoestrogens genistein (GEN), daidzein (DDZ) and equol (EQ), as well as the mycoestrogen, zearalenone (ZEN) and its congeners, was conducted using UPLC-MS/MS. Biomonitoring revealed evidence of internal exposure to naturally occurring dietary estrogens during pregnancy. Urinary concentrations of total GEN, DDZ and EQ were similar to levels reported for general adult U.S. POPULATION: Measurable concentrations of total (parent and metabolites) GEN, DDZ and EQ were present in 240, 207 and 2 of 270 serum samples, respectively. Six out of 30 subjects had measurable concentrations of unconjugated GEN and/or DDZ in serum between 0.6 and 7.1 nM. Urine to serum total isoflavone ratios for GEN, DDZ and EQ were 13, 47, and 180, respectively. ZEN and its reductive metabolite, α-zearalenol (α-ZEL), were present in pregnant women (11 out of 30 subjects) as conjugates at levels near the limit of quantification. The average total urinary concentration was 0.10 µg/L for ZEN and 0.11 µg/L for α-ZEL.

Urine and serum biomonitoring of exposure to environmental estrogens I: Bisphenol A in pregnant women.

Despite its very low oral bioavailability and rapid elimination, multiple reports of unexpectedly high bisphenol A (BPA) concentrations in the serum of pregnant mothers or cord blood have raised questions about BPA exposures during pregnancy. Thirty healthy pregnant women recruited to the study were evaluated for total BPA exposure over a 30-h period comprising one-half day in the field and one day in a clinical setting. BPA and its metabolites were measured in serum and total BPA was measured in matching urine samples. The mean total exposure was similar to the 50(th) percentile of exposure for U.S. women and pregnant women in a large North American cohort. Twenty volunteers had total daily exposures equal to or exceeding the U.S. mean, and six volunteers had exposures exceeding the 75th percentile. Women working as cashiers did not have higher total BPA exposure. BPA was detected in some serum samples (0.25-0.51 ng/ml), but showed no relationship to total BPA in corresponding urine samples, no relationship to total BPA exposure, and had unconjugated BPA fractions of 60-80%, consistent with established criteria for sample contamination. We conclude that typical exposures of North American pregnant women produce internal exposures to BPA in the picomolar range.

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework.

Driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the "systems approaches" used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more meaningful integration of exposure assessment and hazard identification. Together, the two frameworks form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making.

Passive samplers accurately predict PAH levels in resident crayfish.

Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10 years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4 ± 1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests that it could be easily adapted to predict contamination in other shellfish of concern.

SPE-IMS-MS: An automated platform for sub-sixty second surveillance of endogenous metabolites and xenobiotics in biofluids.

Characterization of endogenous metabolites and xenobiotics is essential to deconvoluting the genetic and environmental causes of disease. However, surveillance of chemical exposure and disease-related changes in large cohorts requires an analytical platform that offers rapid measurement, high sensitivity, efficient separation, broad dynamic range, and application to an expansive chemical space. Here, we present a novel platform for small molecule analyses that addresses these requirements by combining solid-phase extraction with ion mobility spectrometry and mass spectrometry (SPE-IMS-MS). This platform is capable of performing both targeted and global measurements of endogenous metabolites and xenobiotics in human biofluids with high reproducibility (CV 6 3%), sensitivity (LODs in the pM range in biofluids) and throughput (10-s sample-to-sample duty cycle). We report application of this platform to the analysis of human urine from patients with and without type 1 diabetes, where we observed statistically significant variations in the concentration of disaccharides and previously unreported chemical isomers. This SPE-IMS-MS platform overcomes many of the current challenges of large-scale metabolomic and exposomic analyses and offers a viable option for population and patient cohort screening in an effort to gain insights into disease processes and human environmental chemical exposure.