Bypassing the Identification: MS2Quant for Concentration Estimations of Chemicals Detected with Nontarget LC-HRMS from MS2 Data.

Nontarget analysis by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is now widely used to detect pollutants in the environment. Shifting away from targeted methods has led to detection of previously unseen chemicals, and assessing the risk posed by these newly detected chemicals is an important challenge. Assessing exposure and toxicity of chemicals detected with nontarget HRMS is highly dependent on the knowledge of the structure of the chemical. However, the majority of features detected in nontarget screening remain unidentified and therefore the risk assessment with conventional tools is hampered. Here, we developed MS2Quant, a machine learning model that enables prediction of concentration from fragmentation (MS2) spectra of detected, but unidentified chemicals. MS2Quant is an xgbTree algorithm-based regression model developed using ionization efficiency data for 1191 unique chemicals that spans 8 orders of magnitude. The ionization efficiency values are predicted from structural fingerprints that can be computed from the SMILES notation of the identified chemicals or from MS2 spectra of unidentified chemicals using SIRIUS+CSI:FingerID software. The root mean square errors of the training and test sets were 0.55 (3.5×) and 0.80 (6.3×) log-units, respectively. In comparison, ionization efficiency prediction approaches that depend on assigning an unequivocal structure typically yield errors from 2× to 6×. The MS2Quant quantification model was validated on a set of 39 environmental pollutants and resulted in a mean prediction error of 7.4×, a geometric mean of 4.5×, and a median of 4.0×. For comparison, a model based on PaDEL descriptors that depends on unequivocal structural assignment was developed using the same dataset. The latter approach yielded a comparable mean prediction error of 9.5×, a geometric mean of 5.6×, and a median of 5.2× on the validation set chemicals when the top structural assignment was used as input. This confirms that MS2Quant enables to extract exposure information for unidentified chemicals which, although detected, have thus far been disregarded due to lack of accurate tools for quantification. The MS2Quant model is available as an R-package in GitHub for improving discovery and monitoring of potentially hazardous environmental pollutants with nontarget screening.

Multireference Electron Correlation Methods: Journeys along Potential Energy Surfaces.

Multireference electron correlation methods describe static and dynamical electron correlation in a balanced way and, therefore, can yield accurate and predictive results even when single-reference methods or multiconfigurational self-consistent field theory fails. One of their most prominent applications in quantum chemistry is the exploration of potential energy surfaces. This includes the optimization of molecular geometries, such as equilibrium geometries and conical intersections and on-the-fly photodynamics simulations, both of which depend heavily on the ability of the method to properly explore the potential energy surface. Because such applications require nuclear gradients and derivative couplings, the availability of analytical nuclear gradients greatly enhances the scope of quantum chemical methods. This review focuses on the developments and advances made in the past two decades. A detailed account of the analytical nuclear gradient and derivative coupling theories is presented. Emphasis is given to the software infrastructure that allows one to make use of these methods. Notable applications of multireference electron correlation methods to chemistry, including geometry optimizations and on-the-fly dynamics, are summarized at the end followed by a discussion of future prospects.

MS2Tox Machine Learning Tool for Predicting the Ecotoxicity of Unidentified Chemicals in Water by Nontarget LC-HRMS.

To achieve water quality objectives of the zero pollution action plan in Europe, rapid methods are needed to identify the presence of toxic substances in complex water samples. However, only a small fraction of chemicals detected with nontarget high-resolution mass spectrometry can be identified, and fewer have ecotoxicological data available. We hypothesized that ecotoxicological data could be predicted for unknown molecular features in data-rich high-resolution mass spectrometry (HRMS) spectra, thereby circumventing time-consuming steps of molecular identification and rapidly flagging molecules of potentially high toxicity in complex samples. Here, we present MS2Tox, a machine learning method, to predict the toxicity of unidentified chemicals based on high-resolution accurate mass tandem mass spectra (MS2). The MS2Tox model for fish toxicity was trained and tested on 647 lethal concentration (LC50) values from the CompTox database and validated for 219 chemicals and 420 MS2 spectra from MassBank. The root mean square error (RMSE) of MS2Tox predictions was below 0.89 log-mM, while the experimental repeatability of LC50 values in CompTox was 0.44 log-mM. MS2Tox allowed accurate prediction of fish LC50 values for 22 chemicals detected in water samples, and empirical evidence suggested the right directionality for another 68 chemicals. Moreover, by incorporating structural information, e.g., the presence of carbonyl-benzene, amide moieties, or hydroxyl groups, MS2Tox outperforms baseline models that use only the exact mass or log KOW.

Outside the Safe Operating Space of the Planetary Boundary for Novel Entities.

We submit that the safe operating space of the planetary boundary of novel entities is exceeded since annual production and releases are increasing at a pace that outstrips the global capacity for assessment and monitoring. The novel entities boundary in the planetary boundaries framework refers to entities that are novel in a geological sense and that could have large-scale impacts that threaten the integrity of Earth system processes. We review the scientific literature relevant to quantifying the boundary for novel entities and highlight plastic pollution as a particular aspect of high concern. An impact pathway from production of novel entities to impacts on Earth system processes is presented. We define and apply three criteria for assessment of the suitability of control variables for the boundary: feasibility, relevance, and comprehensiveness. We propose several complementary control variables to capture the complexity of this boundary, while acknowledging major data limitations. We conclude that humanity is currently operating outside the planetary boundary based on the weight-of-evidence for several of these control variables. The increasing rate of production and releases of larger volumes and higher numbers of novel entities with diverse risk potentials exceed societies' ability to conduct safety related assessments and monitoring. We recommend taking urgent action to reduce the harm associated with exceeding the boundary by reducing the production and releases of novel entities, noting that even so, the persistence of many novel entities and/or their associated effects will continue to pose a threat.

Steady-State Mass Balance Model for Predicting Particle-Gas Concentration Ratios of PBDEs.

Assuming equilibrium partitioning between the gas and particle phases has been shown to overestimate the fraction of low-volatility chemicals in the particle phase. Here, we present a new steady-state mass balance model that includes separate compartments for fine and coarse aerosols and the gas phase and study its sensitivity to the input parameters. We apply the new model to investigate deviations from equilibrium partitioning by exploring model scenarios for seven generic aerosol scenarios representing different environments and different distributions of emissions as the gas phase, fine aerosol, and coarse aerosol. With 100% of emissions as the particle phase, the particle-gas concentration ratio in our model is similar to the equilibrium model, while differences are up to a factor of 106 with 100% of emissions as the gas phase. The particle-gas concentration ratios also depend on the particle size distributions and aerosol loadings in the different environmental scenarios. The new mass balance model can predict the particle-gas concentration ratio with more fidelity to measurements than equilibrium models. However, further laboratory-based evaluations and calibrations of the standard sampling techniques, field investigations with preferably size-resolved measurements of aerosol particle composition, together with the appropriate process modeling for low-volatility chemicals are warranted.

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.

Weathering Plastics as a Planetary Boundary Threat: Exposure, Fate, and Hazards.

We described in 2017 how weathering plastic litter in the marine environment fulfils two of three criteria to impose a planetary boundary threat related to "chemical pollution and the release of novel entities": (1) planetary-scale exposure, which (2) is not readily reversible. Whether marine plastics meet the third criterion, (3) eliciting a disruptive impact on vital earth system processes, was uncertain. Since then, several important discoveries have been made to motivate a re-evaluation. A key issue is if weathering macroplastics, microplastics, nanoplastics, and their leachates have an inherently higher potential to elicit adverse effects than natural particles of the same size. We summarize novel findings related to weathering plastic in the context of the planetary boundary threat criteria that demonstrate (1) increasing exposure, (2) fate processes leading to poorly reversible pollution, and (3) (eco)toxicological hazards and their thresholds. We provide evidence that the third criterion could be fulfilled for weathering plastics in sensitive environments and therefore conclude that weathering plastics pose a planetary boundary threat. We suggest future research priorities to better understand (eco)toxicological hazards modulated by increasing exposure and continuous weathering processes, to better parametrize the planetary boundary threshold for plastic pollution.

Sorptive Capacities of Nonpolymeric Plant Lipids for Hydrophobic Chemicals Determined by Passive Dosing.

Vegetation plays an important role in the partitioning, transport, and fate of semivolatile hydrophobic organic chemicals (HOCs) in the environment. Leaf/air partition ratios ( Kleaf/air) of HOCs are highly variable for different plant species. The differences cannot be fully explained by the fraction of lipids in the leaves or the thickness of the cuticle. Our goal was to elucidate the importance of nonpolymeric lipids in determining Kleaf/air. To do this, we extracted organic matter from 7 plant species using solvents that do not extract the polymeric lipids cutin and cutan, to yield extractable organic matter (EOM). We used passive dosing to determine the partition ratios of selected HOCs between the EOM of the leaves and our reference lipid, olive oil ( KEOM/olive oil). In addition, we measured analogous partition ratios for three lipid standards. Proton nuclear magnetic resonance (NMR) spectroscopy was used to characterize the composition of lipids. Differences in KEOM/olive oil of two polychlorinated biphenyls and four chlorinated benzenes were below a factor of 2 in the plant species studied, indicating that the reported differences in Kleaf/air are not caused by differences in the sorptive capacities of nonpolymeric lipids or that our EOM is not representative of all nonpolymeric leaf lipids.

Effects of Leachates from UV-Weathered Microplastic in Cell-Based Bioassays.

Standard ecotoxicological testing of microplastic does not provide insight into the influence that environmental weathering by, e.g., UV light has on related effects. In this study, we leached chemicals from plastic into artificial seawater during simulated UV-induced weathering. We tested largely additive-free preproduction polyethylene, polyethylene terephthalate, polypropylene, and polystyrene and two types of plastic obtained from electronic equipment as positive controls. Leachates were concentrated by solid-phase extraction and dosed into cell-based bioassays that cover (i) cytotoxicity; (ii) activation of metabolic enzymes via binding to the arylhydrocarbon receptor (AhR) and the peroxisome proliferator-activated receptor (PPARγ); (iii) specific, receptor-mediated effects (estrogenicity, ERα); and (iv) adaptive response to oxidative stress (AREc32). LC-HRMS analysis was used to identify possible chain-scission products of polymer degradation, which were then tested in AREc32 and PPARγ. Explicit activation of all assays by the positive controls provided proof-of-concept of the experimental setup to demonstrate effects of chemicals liberated during weathering. All plastic leachates activated the oxidative stress response, in most cases with increased induction by UV-treated samples compared to dark controls. For PPARγ, polyethylene-specific effects were partially explained by the detected dicarboxylic acids. Since the preproduction plastic showed low effects often in the range of the blanks future studies should investigate implications of weathering on end consumer products containing additives.

Deriving in Vivo Bioconcentration Factors of a Mixture of Fragrance Ingredients Using a Single Dietary Exposure and Internal Benchmarking.

Chemicals in mixtures that are hydrophobic with Log KOW > 4 are potentially bioaccumulative. Here, we evaluate an abbreviated and benchmarked in vivo BCF measurement methodology by exposing rainbow trout to a mixture of eight test chemicals found in fragrance substances and three benchmark chemicals (musk xylene (MX), hexachlorobenzene (HCB) and PCB52) via a single contaminated feeding event followed by a 28-day depuration period. Concentrations of HCB and PCB52 in fish did not decline significantly (their apparent depuration rate constants, kT, were close to zero), whereas kT for MX was 0.022 d-1. The test chemicals were eliminated much more rapidly than the benchmark chemicals ( kT > 0.117 d-1). The bioconcentration factors (BCFA) for the test chemicals were in the range of 273 L kg-1 (8-cyclohexadecen-1-one (globanone)) to 1183 L kg-1 (α-pinene); the benchmarked BCFs (BCFG) calculated relative to HCB ranged from 238 L kg-1 (globanone) to 1147 L kg-1 (α-pinene). BCFG were not significantly different from BCFA but had smaller standard errors. BCFs derived here agreed well with values previously measured using the OECD 305 test protocol. We conclude that it will be feasible to derive BCFs of chemicals in mixtures using a single dietary exposure and chemical benchmarking.

In Silico Screening-Level Prioritization of 8468 Chemicals Produced in OECD Countries to Identify Potential Planetary Boundary Threats.

Legislation such as the Stockholm Convention and REACH aim to identify and regulate the production and use of chemicals that qualify as persistent organic pollutants (POPs) and very persistent and very bioaccumulative (vPvB) chemicals, respectively. Recently, a series of studies on planetary boundary threats proposed seven chemical hazard profiles that are distinct from the POP and vPvB profiles. We previously defined two exposure-based hazard profiles; airborne persistent contaminants (APCs) and waterborne persistent contaminants (WPCs) that correspond to two profiles of chemicals that are planetary boundary threats. Here, we extend our method to screen a database of chemicals consisting of 8648 substances produced within the OECD countries. We propose a new scoring scheme to disentangle the POP, vPvB, APC and WPC profiles by focusing on the spatial range of exposure potential, discuss the relationship between high exposure hazard and elemental composition of chemicals, and identify chemicals with high exposure hazard potential.

On cross-conditional and fluctuation correlations in competitive RNA networks.

MOTIVATION: In competitive endogenous RNA (ceRNA) networks, different mRNAs targeted by the same miRNA can 'cross-talk' by absorbing miRNAs and relieving repression on the other mRNAs. This creates correlations in mRNA expression even without direct interaction. Most previous theoretical study of cross-talk has focused on correlations in stochastic fluctuations of mRNAs around their steady state values. However, the experimentally known examples of cross-talk do not involve single-cell fluctuations, but rather bulk tissue-level changes between conditions, such as due to differentiation or disease. In our study, we quantify for the first time both fluctuational and cross-conditional cross-talk in chemical kinetic models of miRNA-mRNA interaction networks. We study the parameter regions under which these different types of cross-talk arise, and how they are affected by network structure. RESULTS: We find that while a network may support both fluctuational and cross-conditional cross-talk, the parameter regimes under which each type of cross-talk tends to emerge are rather different. Consistent with previous studies, fluctuational cross-talk occurs when miRNA and mRNA expression levels are 'balanced', whereas cross-conditional cross-talk tends to emerge when average miRNA levels are high and average mRNA levels are low. Conversely, cross-conditional miRNA cross-talk-a little-discussed phenomenon-is greatest when miRNA levels are low and mRNA levels are high. We show that the parameter ranges where cross-talk is maximized can, to some degree, be predicted based on network structure. Indeed, we find that the dominant effect of network structure on correlations happens through the effect of network structure on the overall balance between miRNA and mRNA expression. However, it is not the only effect, as we find that the density of connections between miRNAs and mRNAs in larger networks increases cross-talk without altering the expression balance. CONCLUSION: Our results deepen the theoretical understanding of cross-talk in ceRNA networks, and have implications for the experimental identification of ceRNA cross-talk phenomena. AVAILABILITY AND IMPLEMENTATION: Simulation software available upon request. CONTACT: tperkins@ohri.ca.

Quantifying Short-Chain Chlorinated Paraffin Congener Groups.

Accurate quantification of short-chain chlorinated paraffins (SCCPs) poses an exceptional challenge to analytical chemists. SCCPs are complex mixtures of chlorinated alkanes with variable chain length and chlorination level; congeners with a fixed chain length (n) and number of chlorines (m) are referred to as a "congener group" CnClm. Recently, we resolved individual CnClm by mathematically deconvolving soft ionization high-resolution mass spectra of SCCP mixtures. Here we extend the method to quantifying CnClm by introducing CnClm specific response factors (RFs) that are calculated from 17 SCCP chain-length standards with a single carbon chain length and variable chlorination level. The signal pattern of each standard is measured on APCI-QTOF-MS. RFs of each CnClm are obtained by pairwise optimization of the normal distribution's fit to the signal patterns of the 17 chain-length standards. The method was verified by quantifying SCCP technical mixtures and spiked environmental samples with accuracies of 82-123% and 76-109%, respectively. The absolute differences between calculated and manufacturer-reported chlorination degrees were -0.9 to 1.0%Cl for SCCP mixtures of 49-71%Cl. The quantification method has been replicated with ECNI magnetic sector MS and ECNI-Q-Orbitrap-MS. CnClm concentrations determined with the three instruments were highly correlated (R2 > 0.90) with each other.

Deconvolution of Soft Ionization Mass Spectra of Chlorinated Paraffins To Resolve Congener Groups.

We describe and illustrate a three-step data-processing approach that enables individual congener groups of chlorinated paraffins (CPs) to be resolved in mass spectra obtained from either of two soft ionization methods: electron capture negative ionization mass spectrometry (ECNI-MS) or atmospheric pressure chemical ionization mass spectrometry (APCI-MS). In the first step, general fragmentation pathways of CPs are deduced from analysis of mass spectra of individual CP congeners. In the second step, all possible fragment ions in the general fragmentation pathways of CPs with 10 to 20 carbon atoms are enumerated and compared to mass spectra of CP mixture standards, and a deconvolution algorithm is applied to identify fragment ions that are actually observed. In the third step, isotope permutations of the observed fragment ions are calculated and used to identify isobaric overlaps, so that mass intensities of individual CP congener groups can be deconvolved from the unresolved isobaric ion signal intensities in mass spectra. For a specific instrument, the three steps only need to be done once to enable deconvolution of CPs in unknown samples. This approach enables congener group-level resolution of CP mixtures in environmental samples, and it opens up the possibility for quantification of congener groups.

Fast quantification of chlorinated paraffins in environmental samples by direct injection high-resolution mass spectrometry with pattern deconvolution.

Chlorinated paraffins (CPs) are high production volume chemicals, but data about their environmental fate are scarce. CP mixtures composed of thousands of isomers represent a major challenge for quantification at low levels in environmental samples. Here, we present a novel analytical method for analysis of short-chain, medium-chain, and long-chain CPs in a single injection, that also yields information about congener group pattern. Our detection method is based on direct injection into an atmospheric pressure chemical ionization source operated in negative ion mode under chlorine-enhanced conditions, followed by quadrupole time-of-flight high-resolution mass spectrometry (APCI-qTOF-HRMS) operated in full-scan mode. A mathematical algorithm is applied to deconvolute the CP patterns in the analyzed samples into a linear combination of patterns of technical CP mixtures and to quantify CPs using technical mixtures as external calibration standards. For CP mixtures with known composition, the new method provided concentrations that were within a factor of 1.2 of the target value. Accuracies for CPs spiked to sediment and fish extracts were between 91% and 123%. Concentrations determined in unspiked field samples were within a factor of 5 for short-chain CPs and a factor of 16 for medium-chain CPs of results obtained with an independent method based on gas chromatography/electron capture negative ionization high-resolution mass spectrometry (GC/ECNI-HRMS). The presented APCI-qTOF-HRMS pattern deconvolution method is an interesting alternative for CP analysis in environmental samples. It is particularly sensitive for medium- and long-chain CPs and has the advantage of being extremely fast (instrumental analysis time, less than 1 min).

Organic Carbon/Water and Dissolved Organic Carbon/Water Partitioning of Cyclic Volatile Methylsiloxanes: Measurements and Polyparameter Linear Free Energy Relationships.

The sorption of cyclic volatile methyl siloxanes (cVMS) to organic matter has a strong influence on their fate in the aquatic environment. We report new measurements of the partition ratios between freshwater sediment organic carbon and water (KOC) and between Aldrich humic acid dissolved organic carbon and water (KDOC) for three cVMS, and for three polychlorinated biphenyls (PCBs) that were used as reference chemicals. Our measurements were made using a purge-and-trap method that employs benchmark chemicals to calibrate mass transfer at the air/water interface in a fugacity-based multimedia model. The measured log KOC of octamethylcyclotetrasiloxane (D4), decamethylcyclopentasiloxane (D5), and dodecamethylcyclohexasiloxane (D6) were 5.06, 6.12, and 7.07, and log KDOC were 5.05, 6.13, and 6.79. To our knowledge, our measurements for KOC of D6 and KDOC of D4 and D6 are the first reported. Polyparameter linear free energy relationships (PP-LFERs) derived from training sets of empirical data that did not include cVMS generally did not predict our measured partition ratios of cVMS accurately (root-mean-squared-error (RMSE) for logKOC 0.76 and for logKDOC 0.73). We constructed new PP-LFERs that accurately describe partition ratios for the cVMS as well as for other chemicals by including our new measurements in the existing training sets (logKOC RMSEcVMS: 0.09, logKDOC RMSEcVMS: 0.12). The PP-LFERs we have developed here should be further evaluated and perhaps recalibrated when experimental data for other siloxanes become available.

Kinetics and Mechanism of the Oxidation of Cyclic Methylsiloxanes by Hydroxyl Radical in the Gas Phase: An Experimental and Theoretical Study.

The ubiquitous presence of cyclic volatile methylsiloxanes (cVMS) in the global atmosphere has recently raised environmental concern. In order to assess the persistence and long-range transport potential of cVMS, their second-order rate constants (k) for reactions with hydroxyl radical ((•)OH) in the gas phase are needed. We experimentally and theoretically investigated the kinetics and mechanism of (•)OH oxidation of a series of cVMS, hexamethylcyclotrisiloxane (D3), octamethycyclotetrasiloxane (D4), and decamethycyclopentasiloxane (D5). Experimentally, we measured k values for D3, D4, and D5 with (•)OH in a gas-phase reaction chamber. The Arrhenius activation energies for these reactions in the temperature range from 313 to 353 K were small (-2.92 to 0.79 kcal·mol(-1)), indicating a weak temperature dependence. We also calculated the thermodynamic and kinetic behaviors for reactions at the M06-2X/6-311++G**//M06-2X/6-31+G** level of theory over a wider temperature range of 238-358 K that encompasses temperatures in the troposphere. The calculated Arrhenius activation energies range from -2.71 to -1.64 kcal·mol(-1), also exhibiting weak temperature dependence. The measured k values were approximately an order of magnitude higher than the theoretical values but have the same trend with increasing size of the siloxane ring. The calculated energy barriers for H-atom abstraction at different positions were similar, which provides theoretical support for extrapolating k for other cyclic siloxanes from the number of abstractable hydrogens.

Using chemical benchmarking to determine the persistence of chemicals in a Swedish lake.

It is challenging to measure the persistence of chemicals under field conditions. In this work, two approaches for measuring persistence in the field were compared: the chemical mass balance approach, and a novel chemical benchmarking approach. Ten pharmaceuticals, an X-ray contrast agent, and an artificial sweetener were studied in a Swedish lake. Acesulfame K was selected as a benchmark to quantify persistence using the chemical benchmarking approach. The 95% confidence intervals of the half-life for transformation in the lake system ranged from 780-5700 days for carbamazepine to <1-2 days for ketoprofen. The persistence estimates obtained using the benchmarking approach agreed well with those from the mass balance approach (1-21% difference), indicating that chemical benchmarking can be a valid and useful method to measure the persistence of chemicals under field conditions. Compared to the mass balance approach, the benchmarking approach partially or completely eliminates the need to quantify mass flow of chemicals, so it is particularly advantageous when the quantification of mass flow of chemicals is difficult. Furthermore, the benchmarking approach allows for ready comparison and ranking of the persistence of different chemicals.