Building the Environmental Chemical-Protein Interaction Network (eCPIN): An Exposome-Wide Strategy for Bioactive Chemical Contaminant Identification

Exploring the fate of 6PPD in zebrafish (Danio rerio): Understanding toxicokinetics, biotransformation mechanisms, and metabolomic profiling at environmentally relevant levels

In recent years, N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) has attracted significant attention in environmental science, yet its behavior in biological systems remains poorly understood. This study involved a 28-day zebrafish exposure experiment at three concentrations (2, 20, and 200 μg/L), to investigate its physiologically based toxicokinetic (PBTK) properties, the formation of biotransformation products, and the metabolic characteristics of liver tissue. The results indicated that the liver and intestines are key organs for 6PPD accumulation, with tissue-specific distribution patterns. The biotransformation of 6PPD in the liver involves various phase I and phase II metabolic reactions, including hydroxylation, N-dealkylation, and sulfation processes. Furthermore, Metabolomics analysis revealed substantial changes in both the diversity and abundance of liver metabolites with increasing 6PPD concentrations, particularly in key biological processes such as lipid metabolism, amino acid metabolism, and redox balance. Notably, significant disruptions in sphingolipid and glycerophospholipid pathways suggest 6PPD may impair membrane fluidity and stability, potentially leading to membrane damage and dysfunction. Overall, this study provides crucial insights into the biological behavior of 6PPD in zebrafish, contributing essential knowledge for its ecotoxicological evaluation.

Early life development and sex determination of brown trout affected by treated wastewater discharge

Artificial conditions limit the ability of laboratory studies to describe the complex effects of polluted environments on aquatic life. This study aimed to evaluate the impacts of treated wastewater discharge on the survival, growth, and sex ratio balance of the population of brown trout (Salmo trutta m. fario) in situ. Five floating incubators with 1000 eggs each were placed in the upstream reference and treated wastewater-affected sites in the Czech Republic for approximately three months. The hatched fish were grown in a natural environment for nearly one year. Water quality, including nutrients, temperature, pharmaceutical and personal care products, biological effects by bioassays and fish mortality, metabolic rate, and growth, were measured regularly. Up to 72 pharmaceutical and personal care products (7400-23000 ng/sampler) were detected in the passive samplers deployed downstream of the sewage treatment plant effluent. In vitro bioassays of the sampler extracts indicated elevated oestrogenic effects, transthyretin binding inhibition, and aryl hydrocarbon-mediated and androgenic potencies, showing endocrine-disrupting potential at the polluted site. The cumulated mortality of brown trout in the exposed group (9.67%) was significantly higher (p < 0.05) than in the control group (5.16%). In addition, the body size, growth, and metabolic rate of exposed fish were significantly lower (p < 0.05). The sex ratio of brown trout in the effluent-affected stretch was imbalanced, and sterile individuals were detected after several months of natural development in the stream. The observed effects of treated wastewater on the early developmental stages of aquatic wildlife could be connected to the development and readiness of adult individuals and, consequently, to the sustainability of freshwater ecosystems. Applying the hatching apparatus used in fishery practices, followed by comparing mortality, development, and sex with reference localities, seems to be a promising biomonitoring approach that can indicate hotspots for in-depth investigation and risk assessment.

Recent Advances in Nontargeted Screening of Chemical Hazards in Foodstuffs

The emergence of several chemical substances continues to enrich and facilitate the development of food science, but their irrational use also poses a threat to food safety and human health. Nontargeted screening (NTS) has become an important tool for rapid traceability and efficient identification of chemical hazards in food matrices. NTS in food analysis is highly integrated with sample pretreatment, instrumental analysis platforms, data acquisition and analysis, and toxicology. This article is a systemic review of current sample preparation, analytical platforms, and toxicity-guided NTS techniques and provides the latest advancements in workflows and innovative applications of the NTS process based on mass spectrometric techniques. High-throughput toxicity screening platforms play an important role in NTS of unknown chemical hazards of complex food matrices. Advanced machine learning and artificial intelligence are increasingly accessible fields that may effectively process large-scale screening data and advance food NTS research.

Evaluation of FXR Activity in Pollutants Identified in Sewage Sludge and Subsequent in Vitro and in Vivo Characterization of Metabolic Effects of Triphenyl Phosphate

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common liver disease worldwide, and increasing evidence suggests that exposure to environmental pollutants is associated with the increased incidence of MASLD. The farnesoid X receptor (FXR) plays an important role in the development of MASLD by regulating bile acids (BAs) and lipid metabolism. However, whether FXR-active pollutants are the environmental drivers of MASLD remains unclear.

OBJECTIVES

This study aimed to determine whether FXR-active pollutants exist in the environment and evaluate their ability to trigger MASLD development in mice.

METHODS

An FXR protein affinity pull-down assay and nontargeted mass spectrometry (MS) analysis were used to identify environmental FXR ligands in sewage sludge. A homogeneous time-resolved fluorescence coactivator recruitment assay and cell-based dual-luciferase reporter assay were used to determine the FXR activities of the identified pollutants. Targeted analysis of BAs, MS imaging, lipidomic analysis, 16S rRNA sequencing, and quantitative polymerase chain reaction were conducted to assess the ability of FXR-active pollutants to induce metabolic disorders of BAs and lipids and to contribute to MASLD development in C57BL/6N mice.

RESULTS

We identified 19 compounds in the sewage sludge that had FXR-antagonistic activity, and triphenyl phosphate (TPHP) was the FXR antagonist with the highest efficacy. Mice exposed to either 10 or 50 mg / kg TPHP for 30 d had higher levels of conjugated primary BAs in enterohepatic circulation, and the BA pool showed FXR antagonistic activities. The exposed mice also had greater lipogenesis (more Oil Red O staining and high triglyceride levels) in liver.

CONCLUSIONS

Nineteen FXR-antagonistic pollutants were identified in sewage sludge. FXR inhibition by the strongest antagonist TPHP may have a role in promoting MASLD development in mice by inducing a positive feedback loop between the FXR and BAs. https://doi.org/10.1289/EHP15435.

High-throughput protein target mapping enables accelerated bioactivity discovery for ToxCast and PFAS compounds

Chemical pollution is a global threat to human health, yet the toxicity mechanism of most contaminants remains unknown. Here, we applied an ultrahigh-throughput affinity-selection mass spectrometry (AS-MS) platform to systematically identify protein targets of prioritized chemical contaminants. After benchmarking the platform, we screened 50 human proteins against 481 prioritized chemicals, including 446 ToxCast chemicals and 35 per- and polyfluoroalkyl substances (PFAS). Among 24,050 interactions assessed, we discovered 35 novel interactions involving 14 proteins, with fatty acid-binding proteins (FABPs) emerging as the most ligandable protein family. Given this, we selected FABPs for further validation, which revealed a distinct PFAS binding pattern: legacy PFAS selectively bound to FABP1, whereas replacement compounds, PFECAs, unexpectedly interacted with all FABPs. X-ray crystallography further revealed that the ether group enhances molecular flexibility of alternative PFAS, to accommodate the binding pockets of FABPs. Our findings demonstrate that AS-MS is a robust platform for the discovery of novel protein targets beyond the scope of the ToxCast program and highlight the broader protein-binding spectrum of alternative PFAS as potential regrettable substitutes.

Protein-Affinity Guided Nontargeted Analysis Reveals the Widespread FXR-Antagonistic Pollutants in Surface Water and Source Water Along the Yangtze River and Yellow River

Metabolism-disrupting chemicals (MDCs) have attracted widespread attention due to their contributions to the prevalence of metabolic diseases worldwide. The farnesoid X receptor (FXR) is a typical lipid-sensing nuclear receptor and plays a crucial role in the development of metabolic diseases. However, few studies have examined the FXR activities of environmental samples and the corresponding MDCs. In this study, we found FXR-antagonistic activities in 93.6% of source water, surface water, and wastewater samples (n = 78) collected from the Yangtze River and Yellow River. An FXR protein-affinity guided nontargeted analysis was performed and identified 79 potential FXR-active pollutants in samples from these two rivers. Nine of these pollutants exhibited strong FXR-antagonistic activities (IC50: 2.39-141.9 μM), and 6 pollutants, including triphenyl phosphate (TPHP), 4,4'-sulfonylbis[2-(2-propenyl) phenol (TGSA), tonalid (AHTN), dichlorophen, etoxazole (ETX), and loratadine, were identified to be FXR antagonists for the first time. The total concentrations of the nine FXR-antagonistic pollutants were relatively high in the middle and downstream reaches of the Yellow River and the downstream reaches of the Yangtze River, and two pollutants (TGSA and ETX) have not previously been found in aquatic environments. A risk prioritization analysis revealed that TPHP, TGSA, and AHTN are priority pollutants with the potential to affect the FXR. Appropriate management of these priority pollutants would reduce the health risks of metabolic disruptions associated with exposure to these MDCs.

Proteomics: An In-Depth Review on Recent Technical Advances and Their Applications in Biomedicine

Proteins hold pivotal importance since many diseases manifest changes in protein activity. Proteomics techniques provide a comprehensive exploration of protein structure, abundance, and function in biological samples, enabling the holistic characterization of overall changes in organisms. Nowadays, the breadth of emerging methodologies in proteomics is unprecedentedly vast, with constant optimization of technologies in sample processing, data collection, data analysis, and its scope of application is steadily transitioning from the bench to the clinic. Here, we offer an insightful review of the technical developments in proteomics and its applications in biomedicine over the past 5 years. We focus on its profound contributions in profiling disease spectra, discovering new biomarkers, identifying promising drug targets, deciphering alterations in protein conformation, and unearthing protein-protein interactions. Moreover, we summarize the cutting-edge technologies and potential breakthroughs in the proteomics pipeline and provide the principal challenges in proteomics. Based on these, we aspire to broaden the applicability of proteomics and inspire researchers to enhance our understanding of complex biological systems by utilizing such techniques.

Identifying Organic Chemicals with Acetylcholinesterase Inhibition in Nationwide Estuarine Waters by Machine Learning-Assisted Mass Spectrometric Screening

Neurotoxicity is frequently observed in the global aquatic environment, threatening aquatic ecosystems and human health. However, a very limited proportion of neurotoxic effects (∼1%) has been explained by known chemicals of concern. Here, we integrated machine learning, nontargeted analysis, and in vitro biotesting to identify neurotoxic drivers of acetylcholinesterase (AChE) inhibition in estuarine waters along the coast of China. Machine learning was used to predict AChE inhibitors in a large chemical space. The prediction output was profiled into a suspect screening list to guide high-resolution mass spectrometry (HRMS) screening of AChE inhibitors in estuarine water samples. Ultimately, 60 chemicals with diverse known and presently unknown structures were identified, explaining 82.1% of the observed AChE inhibition. Polyunsaturated fatty acids were unexpectedly found to be neurotoxic drivers, accounting for 80.5% of the overall effect. This proof-of-concept study demonstrates that machine learning-based toxicological prediction can achieve a virtual fractionation role to pinpoint HRMS features with the bioactivity potential. Our approach is expected to enable rapid and comprehensive screening of organic pollutants associated with various in vitro end points for large-scale monitoring of water quality.

Analysis of the stereoselective fate and toxicity of penflufen in the water-sediment system for risk reduction

Chiral succinate dehydrogenase inhibitor (SDHI) fungicides are widely used in agricultural production, but there is insufficient research on their environmental risk in water-sediment ecosystems. Here, the stereoselective fate and toxic effects of the chiral SDHI fungicide, penflufen, in the water-sediment system were investigated. The results showed that S-penflufen is more persistent in water, sediment, and zebrafish. Additionally, the sorption coefficient (Koc) in sediment and uptake rate constant (Ku) in zebrafish of S-penflufen were higher than those of R-penflufen. The acute toxicity of S-penflufen to zebrafish, Daphnia magna and Chironomus kiiensis were 32-, 6.1-, and 8.9-fold higher than those of R-penflufen. The AlphaFold2 and molecular docking results showed that S-penflufen had stronger binding capability with SDH in the three water-sediment organisms than R-penflufen. Therefore, S-penflufen induced stronger sub-chronic toxic effects on zebrafish than R-penflufen, even at 0.05 mg/L. The results of multi-omics analysis showed that S-penflufen affected the tricarboxylic acid cycle in zebrafish and induced antioxidant, detoxification, and immune system responses, ultimately affecting zebrafish metabolic processes and cellular function. The overall results indicate that S-penflufen has a higher risk in water-sediment systems. Moreover, combining multi-omics and AlphaFold2 techniques facilitates the elucidation of the molecular mechanism of the stereoselective toxic effects of chiral pesticides.

Multi-omics integration analysis: Tools and applications in environmental toxicology

Nowadays, traditional single-omics study is not enough to explain the causality between molecular alterations and toxicity endpoints for environmental pollutants. With the development of high-throughput sequencing technology and high-resolution mass spectrometry technology, the integrative analysis of multi-omics has become an efficient strategy to understand holistic biological mechanisms and to uncover the regulation network in specific biological processes. This review summarized sample preparation methods, integration analysis tools and the application of multi-omics integration analyses in environmental toxicology field. Currently, omics methods have been widely applied being as the sensitivity of early biological response, especially for low-dose and long-term exposure to environmental pollutants. Integrative omics can reveal the overall changes of genes, proteins, and/or metabolites in the cells, tissues or organisms, which provide new insights into revealing the overall toxicity effects, screening the toxic targets, and exploring the underlying molecular mechanism of pollutants.

Quality evaluation parameter and classification model for effluents of wastewater treatment plant based on machine learning

With the growing consensus of emerging pollutants and biological toxicity risks in wastewater treatment plant (WWTP) effluents, traditional water quality management based on general chemical parameters no longer meets the new challenges. Here, a first-hand dataset containing 9 conventional parameters, 22 mental and inorganic ions, 25 biotoxicity parameters, and 54 emerging pollutants from effluents of 176 municipal WWTPs across China were measured. Four clustering algorithms and five classification algorithms were applied to 65 well-performing models to determine a novel evaluation parameter system. A total of 14 parameters were selected by semi-supervised machine learning, including TN, TP, NH4+-N, NO2--N, Se, SO42-, Caenorhabditis elegans body width, 72 hpf zebrafish embryo hatching rate, tetracycline, acetaminophen, gemfibrozil (Lopid), PFBA, PFHxA, and HFPO-DA. These parameters were then used to construct a Healthy Effluent Quality Index model (HEQi). The application efficiency of HEQi was compared with other common methods such as the Water Quality Index (WQI), Fuzzy Synthesized Evaluation (FSE), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in classifying 176 effluents. Results implicated that under the new evaluation criteria, the major task in North and Northeast China remains to reduce the conventional parameters, especially NO2--N. However, it is necessary to strengthen the removal of biotoxicity and emerging pollutants in parts of Central and Eastern China. This study offers new methodological tools and scientific insights for improving water quality assessment and safe discharge of wastewater.

Biomineralized Nuclear Receptor Protein-Selection Mass Spectrometry for the Discovery of Drugs and Toxics

Protein-selection mass spectrometry is cost-effective for the discovery of drugs and toxics. Nuclear receptors (NRs) are major targets for pharmaceuticals and endocrine-disrupting chemicals and are, thus, widely used as "bait" proteins. However, their application is limited due to the tendency to lose protein activity during cold storage. To address this problem, we introduced a novel biomineralization-based approach to preserve activity in NRs, exemplified by human retinoic acid receptor alpha (hRARα), a target for cancer and leucocythemia therapy. Since information on the coordination chemistry of metal ion and NR protein complexes is almost unavailable, we applied peptide mapping analysis for the first time for the rational design of his-hRARα-Co phosphate nanobiomaterial with high bioactivity. This nanobiomaterial successfully captured hRARα bioactive chemicals from a Chinese herb and environmental water and discovered an unsaturated fatty acid, (±)-(9Z,11E)-13-hydroxy-9,11-octadecadienoic acid ((±)13-HODE), which exhibited strong hRARα antagonistic activity.

DNA Adductomics: A Narrative Review of Its Development, Applications, and Future

DNA adductomics is the global study of all DNA adducts and was first proposed in 2006 by the Matsuda group. Its development has been greatly credited to the advances in mass spectrometric techniques, particularly tandem and multiple-stage mass spectrometry. In fact, liquid chromatography-mass spectrometry (LC-MS)-based methods are virtually the sole technique with practicality for DNA adductomic studies to date. At present, DNA adductomics is primarily used as a tool to search for DNA adducts, known and unknown, providing evidence for exposure to exogenous genotoxins and/or for the molecular mechanisms of their genotoxicity. Some DNA adducts discovered in this way have the potential to predict cancer risks and/or to be associated with adverse health outcomes. DNA adductomics has been successfully used to identify and determine exogenous carcinogens that may contribute to the etiology of certain cancers, including bacterial genotoxins and an N-nitrosamine. Also using the DNA adductomic approach, multiple DNA adducts have been observed to show age dependence and may serve as aging biomarkers. These achievements highlight the capability and power of DNA adductomics in the studies of medicine, biological science, and environmental science. Nonetheless, DNA adductomics is still in its infancy, and great advances are expected in the future.

Identification and Prioritization of Organic Pollutants in Human Milk from the Yangtze River Delta, China

Pollutants in human milk are critical for evaluating maternal internal exposure and infant external exposure. However, most studies have focused on a limited range of pollutants. Here, 15 pooled samples (prepared from 467 individual samples) of human milk from three areas of the Yangtze River Delta (YRD) in China were analyzed by gas chromatography quadrupole time-of-flight mass spectrometry. In total, 171 compounds of nine types were preliminarily identified. Among these, 16 compounds, including 2,5-di-tert-butylhydroquinone and 2-tert-butyl-1,4-benzoquinone, were detected in human milk for the first time. Partial least-squares discriminant analysis identified ten area-specific pollutants, including 2-naphthylamine, 9-fluorenone, 2-isopropylthianthrone, and benzo[a]pyrene, among pooled human milk samples from Shanghai (n = 3), Jiangsu Province (n = 6), and Zhejiang Province (n = 6). Risk index (RI) values were calculated and indicated that legacy polycyclic aromatic hydrocarbons (PAHs) contributed only 20% of the total RIs for the identified PAHs and derivatives, indicating that more attention should be paid to PAHs with various functional groups. Nine priority pollutants in human milk from the YRD were identified. The most important were 4-tert-amylphenol, caffeine, and 2,6-di-tert-butyl-p-benzoquinone, which are associated with apoptosis, oxidative stress, and other health hazards. The results improve our ability to assess the health risks posed by pollutants in human milk.

Identification of Hydrocarbon Sulfonates as Previously Overlooked Transthyretin Ligands in the Environment

Incidences of thyroid disease, which has long been hypothesized to be partially caused by exposure to thyroid hormone disrupting chemicals (TDCs), have rapidly increased in recent years. However, known TDCs can only explain a small portion (∼1%) of in vitro human transthyretin (hTTR) binding activities in environmental samples, indicating the existence of unknown hTTR ligands. In this study, we aimed to identify the major environmental hTTR ligands by employing protein Affinity Purification with Nontargeted Analysis (APNA). hTTR binding activities were detected in all 11 indoor dust and 9 out of 10 sewage sludge samples by the FITC-T4 displacement assay. By using APNA, 31 putative hTTR ligands were detected including perfluorooctanesulfonate (PFOS). Two of the most abundant ligands were identified as hydrocarbon surfactants (e.g., dodecyl benzenesulfonate). Moreover, another abundant ligand was surprisingly identified as a disulfonate fluorescent brightener, 4,4'-bis(2-sulfostyryl)biphenyl sodium (CBS). CBS was validated as a nM-affinity hTTR ligand with an IC50 of 345 nM. In total, hydrocarbon surfactants and fluorescent brighteners explain 1.92-17.0 and 5.74-54.3% of hTTR binding activities in dust and sludge samples, respectively, whereas PFOS only contributed <0.0001%. Our study revealed for the first time that hydrocarbon sulfonates are previously overlooked hTTR ligands in the environment.

Identification of new endocrine disruptive transthyretin ligands in polluted waters using pull-down assay coupled to non-target mass spectrometry

Surface and treated wastewater are contaminated with highly complex mixtures of micropollutants, which may cause numerous adverse effects, often mediated by endocrine disruption. However, there is limited knowledge regarding some important modes of action, such as interference with thyroid hormone (TH) regulation, and the compounds driving these effects. This study describes an effective approach for the identification of compounds with the potential to bind to transthyretin (TTR; protein distributing TH to target tissues), based on their specific separation in a pull-down assay followed by non-target analysis (NTA). The method was optimized with known TTR ligands and applied to complex water samples. The specific separation of TTR ligands provided a substantial reduction of chromatographic features from the original samples. The applied NTA workflow resulted in the identification of 34 structures. Twelve compounds with available standards were quantified in the original extracts and their TH-displacement potency was confirmed. Eleven compounds were discovered as TTR binders for the first time and linear alkylbenzene sulfonates (LAS) were highlighted as contaminants of concern. Pull-down assay combined with NTA proved to be a well-functioning approach for the identification of unknown bioactive compounds in complex mixtures with great application potential across various biological targets and environmental compartments.

Ligand Modification-Free Methods for the Profiling of Protein-Environmental Chemical Interactions

Adverse health outcomes caused by environmental chemicals are often initiated via their interactions with proteins. Essentially, one environmental chemical may interact with a number of proteins and/or a protein may interact with a multitude of environmental chemicals, forming an intricate interaction network. Omics-wide protein-environmental chemical interaction profiling (PECI) is of prominent importance for comprehensive understanding of these interaction networks, including the toxicity mechanisms of action (MoA), and for providing systematic chemical safety assessment. However, such information remains unknown for most environmental chemicals, partly due to their vast chemical diversity. In recent years, with the continuous efforts afforded, especially in mass spectrometry (MS) based omics technologies, several ligand modification-free methods have been developed, and new attention for systematic PECI profiling was gained. In this Review, we provide a comprehensive overview on these methodologies for the identification of ligand-protein interactions, including affinity interaction-based methods of affinity-driven purification, covalent modification profiling, and activity-based protein profiling (ABPP) in a competitive mode, physicochemical property changes assessment methods of ligand-directed nuclear magnetic resonance (ligand-directed NMR), MS integrated with equilibrium dialysis for the discovery of allostery systematically (MIDAS), thermal proteome profiling (TPP), limited proteolysis-coupled mass spectrometry (LiP-MS), stability of proteins from rates of oxidation (SPROX), and several intracellular downstream response characterization methods. We expect that the applications of these ligand modification-free technologies will drive a considerable increase in the number of PECI identified, facilitate unveiling the toxicological mechanisms, and ultimately contribute to systematic health risk assessment of environmental chemicals.

Interactions between biofilms and PFASs in aquatic ecosystems: Literature exploration

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) have been detected in most aquatic environments worldwide and are referred to as "forever chemicals" because of their extreme chemical and thermal stability. Biofilms, as basic aquatic bioresources, can colonize various substratum surfaces. Biofilms in the aquatic environment have to interact with the ubiquitous PFASs and have significant implications for both their behavior and destiny, which are still poorly understood. Here, we have a preliminary literature exploration of the interaction between PFASs and biofilms in the various aquatic environments and expect to provide some thoughts on further study. In this review, the biosorption properties of biofilms on PFASs and possible mechanisms are presented. The complex impact of PFASs on biofilm systems was further discussed in terms of the composition and electrical charges of extracellular polymeric substances, intracellular microbial communities, and overall contaminant purification functions. Correspondingly, the effects of biofilms on the redistribution of PFASs in the aqueous environment were analyzed. Finally, we propose that biofilm after adsorption of PFASs is a unique ecological niche that not only reflects the contamination level of PFASs in the aquatic environment but also offers a possible "microbial pool" for PFASs biodegradation. We outline existing knowledge gaps and potential future efforts for investigating how PFASs interact with biofilms in aquatic ecosystems.

Nontargeted Analysis Reveals a Broad Range of Bioactive Pollutants in Drinking Water by Estrogen Receptor Affinity-Mass Spectrometry

Exposure to environmental endocrine-disrupting chemicals (EDCs) can cause extensive health issues. However, specific EDCs remain elusive. This work aimed at performing nontargeted identification of estrogen receptor α (ERα)-active compounds using an ERα protein affinity assay combined with high-resolution mass spectrometry in the source and drinking water sampled from major rivers in China. Fifty-one potential ERα-active compounds across 13 categories were identified. For the first time, diisodecyl phenyl phosphate was found to have antiestrogenic activity, and three chemicals (galaxolidone, bensulfuron methyl, and UV234) were plausible ERα ligands. Among the 51 identified compounds, 12 were detected in the aquatic environment for the first time, and the concentration of N-phenyl-2-naphthylamine, a widely used antioxidant in rubber products, was up to 1469 and 1190 ng/L in source and drinking water, respectively. This study demonstrated the widespread presence of known and unknown ERα estrogenic and antiestrogenic pollutants in the major rivers that serve as key sources of drinking water in China and the low removal efficiency of these chemicals in drinking water treatment plants.

Exploring Single-Cell Exposomics by Mass Spectrometry

Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.

Disclosing Environmental Ligands of L-FABP and PPARγ: Should We Re-evaluate the Chemical Safety of Hydrocarbon Surfactants?

Chemical contaminants can cause adverse effects by binding to the liver-fatty acid binding protein (L-FABP) and peroxisome proliferator-activated nuclear receptor γ (PPARγ), which are vital in lipid metabolism. However, the presence of numerous compounds in the environment has hindered the identification of their ligands, and thus only a small portion have been discovered to date. In this study, protein Affinity Purification with Nontargeted Analysis (APNA) was employed to identify the ligands of L-FABP and PPARγ in indoor dust and sewage sludge. A total of 83 nonredundant features were pulled-out by His-tagged L-FABP as putative ligands, among which 13 were assigned as fatty acids and hydrocarbon surfactants. In contrast, only six features were isolated when His-tagged PPARγ LBD was used as the protein bait. The binding of hydrocarbon surfactants to L-FABP and PPARγ was confirmed using both recombinant proteins and reporter cells. These hydrocarbon surfactants, along with >50 homologues and isomers, were detected in dust and sludge at high concentrations. Fatty acids and hydrocarbon surfactants explained the majority of L-FABP (57.7 ± 32.9%) and PPARγ (66.0 ± 27.1%) activities in the sludge. This study revealed hydrocarbon surfactants as the predominant synthetic ligands of L-FABP and PPARγ, highlighting the importance of re-evaluating their chemical safety.