Competitive Biotransformation Among Phenolic Xenobiotic Mixtures: Underestimated Risks for Toxicity Assessment

Toxicity evolution of triclosan during environmental transformation and human metabolism: Misgivings in the post-pandemic era

In the context of pandemic viruses and pathogenic bacteria, triclosan (TCS), as a typical antibacterial agent, is widely used around the world. However, the health risks from TCS increase with exposure, and it is widespread in environmental and human samples. Notably, environmental transformation and human metabolism could induce potentially undesirable risks to humans, rather than simple decontamination or detoxification. This review summarizes the environmental and human exposure to TCS covering from 2004 to 2023. Particularly, health impacts from the environmental and metabolic transformation of TCS are emphasized. Environmental transformations aimed at decontamination are recognized to form carcinogenic products such as dioxins, and ultraviolet light and excessive active chlorine can promote the formation of these dioxin congeners, potentially threatening environmental and human health. Although TCS can be rapidly metabolized for detoxification, these processes can induce the formation of lipophilic ether metabolic analogs via cytochrome P450 catalysis, causing possible adverse cross-talk reactions in human metabolic disorders. Accordingly, TCS may be more harmful in environmental transformation and human metabolism. In particular, TCS can stimulate the transmission of antibiotic resistance even at trace levels, threatening public health. Considering these accruing epidemiological and toxicological studies indicating the multiple adverse health outcomes of TCS, we call on environmental toxicologists to pay more attention to the toxicity evolution of TCS during environmental transformation and human metabolism.

In Vitro and In Vivo Biotransformation Profiling of 6PPD-Quinone toward Their Detection in Human Urine

The antioxidant N-(1,3-Dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) and its oxidized quinone product 6PPD-quinone (6PPD-Q) in rubber have attracted attention due to the ecological risk that they pose. Both 6PPD and 6PPD-Q have been detected in various environments that humans cohabit. However, to date, a clear understanding of the biotransformation of 6PPD-Q and a potential biomarker for exposure in humans are lacking. To address this issue, this study presents a comprehensive analysis of the extensive biotransformation of 6PPD-Q across species, encompassing both in vitro and in vivo models. We have tentatively identified 17 biotransformation metabolites in vitro, 15 in mice in vivo, and confirmed the presence of two metabolites in human urine samples. Interestingly, different biotransformation patterns were observed across species. Through semiquantitative analysis based on peak areas, we found that almost all 6PPD-Q underwent biotransformation within 24 h of exposure in mice, primarily via hydroxylation and subsequent glucuronidation. This suggests a rapid metabolic processing of 6PPD-Q in mammals, underscoring the importance of identifying effective biomarkers for exposure. Notably, monohydroxy 6PPD-Q and 6PPD-Q-O-glucuronide were consistently the most predominant metabolites across our studies, highlighting monohydroxy 6PPD-Q as a potential key biomarker for epidemiological research. These findings represent the first comprehensive data set on 6PPD-Q biotransformation in mammalian systems, offering insights into the metabolic pathways involved and possible exposure biomarkers.

Application of the Key Characteristics of Carcinogens to Bisphenol A

The ten key characteristics (KCs) of carcinogens are based on characteristics of known human carcinogens and encompass many types of endpoints. We propose that an objective review of the large amount of cancer mechanistic evidence for the chemical bisphenol A (BPA) can be achieved through use of these KCs. A search on metabolic and mechanistic data relevant to the carcinogenicity of BPA was conducted and web-based software tools were used to screen and organize the results. We applied the KCs to systematically identify, organize, and summarize mechanistic information for BPA, and to bring relevant carcinogenic mechanisms into focus. For some KCs with very large data sets, we utilized reviews focused on specific endpoints. Over 3000 studies for BPA from various data streams (exposed humans, animals, in vitro and cell-free systems) were identified. Mechanistic data relevant to each of the ten KCs were identified, with receptor-mediated effects, epigenetic alterations, oxidative stress, and cell proliferation being especially data rich. Reactive and bioactive metabolites are also associated with a number of KCs. This review demonstrates how the KCs can be applied to evaluate mechanistic data, especially for data-rich chemicals. While individual entities may have different approaches for the incorporation of mechanistic data in cancer hazard identification, the KCs provide a practical framework for conducting an objective examination of the available mechanistic data without a priori assumptions on mode of action. This analysis of the mechanistic data available for BPA suggests multiple and inter-connected mechanisms through which this chemical can act.

Stability and Biotransformation of 6:2 Fluorotelomer Sulfonic Acid, Sulfonamide Amine Oxide, and Sulfonamide Alkylbetaine in Aerobic Sludge

The 6:2 fluorotelomer sulfonamide (6:2 FTSAm)-based compounds signify a prominent group of per- and polyfluoroalkyl substances (PFAS) widely used in contemporary aqueous film-forming foam (AFFF) formulations. Despite their widespread presence, the biotransformation behavior of these compounds in wastewater treatment plants remains uncertain. This study investigated the biotransformation of 6:2 FTSAm-based amine oxide (6:2 FTNO), alkylbetaine (6:2 FTAB), and 6:2 fluorotelomer sulfonic acid (6:2 FTSA) in aerobic sludge over a 100-day incubation period. The biotransformation of 6:2 fluorotelomer sulfonamide alkylamine (6:2 FTAA), a primary intermediate product of 6:2 FTNO, was indirectly assessed. Their stability was ranked based on the estimated half-lives (t1/2): 6:2 FTAB (no obvious products were detected) ≫ 6:2 FTSA (t1/2 ≈28.8 days) > 6:2 FTAA (t1/2 ≈11.5 days) > 6:2 FTNO (t1/2 ≈1.2 days). Seven transformation products of 6:2 FTSA and 15 products of 6:2 FTNO were identified through nontarget and suspect screening using high-resolution mass spectrometry. The transformation pathways of 6:2 FTNO and 6:2 FTSA in aerobic sludge were proposed. Interestingly, 6:2 FTSAm was hardly hydrolyzed to 6:2 FTSA and further biotransformed to perfluoroalkyl carboxylic acids (PFCAs). Furthermore, the novel pathways for the generation of perfluoroheptanoic acid (PFHpA) from 6:2 FTSA were revealed.

Co-exposure health risk of benzo[a]pyrene with aromatic VOCs: Monoaromatic hydrocarbons inhibit the glucuronidation of benzo[a]pyrene

Occupational workers and residents near petrochemical industry facilities are exposed to multiple contaminants on a daily basis. However, little is known about the co-exposure effects of different pollutants based on biotransformation. The study examined benzo[a]pyrene (BaP), a representative polycyclic aromatic hydrocarbon related to the petrochemical industry, to investigate changes in toxicity and co-exposure mechanism associated with different monoaromatic hydrocarbons (MAHs). A central composite design method was used to simulate site co-exposure scenarios to reveal biotransformation of BaP when co-exposed with benzene, toluene, chlorobenzene, or nitrobenzene in microsome systems. BaP metabolism depended on MAH concentration, and association of MAH with microsome concentration/incubation time. Particularly, MAH co-exposure negatively affected BaP glucuronidation, an important phase Ⅱ detoxification process. BaP metabolite intensities decreased to 43%-80% for OH-BaP-G, and 32%-71% for diOH-BaP-G in co-exposure system with MAHs, compared with control group. Furthermore, glucuronidation was affected by competitive and time-dependent inhibition. Co-exposure significantly decreased gene expression of UGT 1A10 and BCRP/ABCG2 in HepG2 cells, which are involved in BaP detoxification through metabolism and transmembrane transportation. Therefore, human co-exposure to multiple contaminants may deteriorate toxic effects of these chemicals by disturbing metabolic pathways. This study provides a reference for assessing toxic effects and co-exposure risks of pollutants.

Characterization of different contaminants and current knowledge for defining chemical mixtures in human milk: A review

Hundreds of xenobiotics, with very diverse origins, have been detected in human milk, including contaminants of emerging concern, personal care products and other current-use substances reflecting lifestyle. The routes of exposure to these chemicals include dermal absorption, ingestion and inhalation. Specific families of chemicals are dominant among human milk monitoring studies (e.g., organochlorine pesticides, bisphenol A, dioxins), even though other understudied families may be equally toxicologically relevant (e.g., food-processing chemicals, current-use plasticizers and flame retardants, mycotoxins). Importantly, the lack of reliable human milk monitoring data for some individual chemicals and, especially, for complex mixtures, is a major factor hindering risk assessment. Non-targeted screening can be used as an effective tool to identify unknown contaminants of concern in human milk. This approach, in combination with novel methods to conduct risk assessments on the chemical mixtures detected in human milk, will assist in elucidating exposures that may have adverse effects on the development of breastfeeding infants.

Association of preconception mixtures of phenol and phthalate metabolites with birthweight among subfertile couples

Although parental preconception exposure to some phenols and phthalates have been associated with reduced birthweight, few studies have examined these chemicals as complex mixtures.

Gut microbial metabolite p-cresol alters biotransformation of bisphenol A: Enzyme competition or gene induction?

Recent studies on pharmaceuticals have revealed the direct and indirect mechanisms that link human gut microbiome to xenobiotic biotransformation. Though environmental contaminants compose a vital portion of xenobiotics and share overlapping biotransformation pathways with gut microbial metabolites, the possible interplay between gut microbiome and biotransformation of environmental contaminants remains obscure. This study utilized bisphenol A (BPA) and p-cresol as model compounds to explore whether gut microbial metabolites could affect environmental phenol metabolism on both in vitro and in vivo models. We have observed some distinct biotransformation behavior, where in vivo mouse examination using 171 & 1972 μg/kg bw p-cresol injection exhibited enhancing effect on BPA metabolism, but p-cresol was found as a strong inhibitor from 10/5 μM in a non-competitive pattern for BPA biotransformation in in vitro models of liver S9 fractions and HepG2 cell line, respectively. A further investigation revealed that the expression of biotransformation enzyme genes including Ugt1a1, Ugt2b1, or Sult1a1 of p-cresol treated mice were dynamically induced. In silico docking approach was also utilized to explore the non-competitive inhibition mechanism by estimating the binding affinity of key enzyme SULT 1A1. Overall, our results provided a novel insight into the biotransformation interaction between gut microbiome and environmental contaminants.

Carcinogenic Risk of 2,6-Di-tert-Butylphenol and Its Quinone Metabolite 2,6-DTBQ Through Their Interruption of RARβ: In Vivo, In Vitro, and In Silico Investigations

Thousands of contaminants are used worldwide and eventually released into the environment, presenting a challenge of health risk assessment. The identification of key toxic pathways and characterization of interactions with target biomacromolecules are essential for health risk assessments. The adverse outcome pathway (AOP) incorporates toxic mechanisms into health risk assessment by emphasizing the relationship among molecular initiating events (MIEs), key events (KEs), and adverse outcome (AO). Herein, we attempted the use of AOP to decipher the toxic effects of 2,6-di-tert-butylphenol (2,6-DTBP) and its para-quinone metabolite 2,6-di-tert-butyl-1,4-benzoquinone (2,6-DTBQ) based on integrated transcriptomics, molecular modeling, and cell-based assays. Through transcriptomics and quantitative real-time PCR validation, we identified retinoic acid receptor β (RARβ) as the key target biomacromolecule. The epigenetic analysis and molecular modeling revealed RARβ interference as one MIE, including DNA methylation and conformational changes. In vitro assays extended subsequent KEs, including altered protein expression of p-Erk1/2 and COX-2, and promoted cancer cell H4IIE proliferation and metastasis. These toxic effects altogether led to carcinogenic risk as the AO of 2,6-DTBP and 2,6-DTBQ, in line with chemical carcinogenesis identified from transcriptome profiling. Overall, our simplified AOP network of 2,6-DTBP and 2,6-DTBQ facilitates relevant health risk assessment.

RTP: One Effective Platform to Probe Reactive Compound Transformation Products and Its Applications for a Reactive Plasticizer BADGE

Reactive compounds, such as covalent toxicants/drugs, have their ubiquitous occurrences and are known to react with protein or DNA in human beings, but their reactions with endogenous metabolites are rarely understood. Currently, a viable platform is demanded for discovering their reaction products since their efficacy/toxicity may be altered after the reaction. We aim to develop a platform for identifying unknown abiotic or biotransformation products for these reactive compounds. Based on stable isotope-labeling (SIL) metabolomics, we have developed a novel and robust analytical platform, reactive compound transformation profiler (RTP), which can automatically analyze preannotated high-resolution mass spectrometry (LC-HRMS) data sets and uncover probable transformation products. Generally, RTP consists of four complementary steps: (1) selecting peak pairs of light and heavy-labeled products, (2) defining the "core structure mass" for possible reaction search, (3) constructing an endogenous metabolite reaction database, and (4) developing algorithms to propose the potential transformation products by searching against the database with a single-/multiple-site reaction. Its performance was validated using the reactive plasticizer bisphenol A diglycidyl ether (BADGE) in several sample matrices. This platform enabled the identification of novel transformation products while also demonstrating its capacity to filter out the false-positive signals and provide product annotation. The RTP is freely accessible at https://github.com/FangLabNTU/Reactive-Compound-Transformation-Profiler-RTP-.

Drug-Exposome Interactions: The Next Frontier in Precision Medicine

Drug-drug interactions are a known concern during medical treatment. However, in addition to therapeutic drugs, humans are exposed to thousands of environment- and food-related chemicals on a daily basis. The exposome (i.e.,the total measure of environmental factors on the human body) is an emerging concept in the field of environmental health. Many chemicals have the potential to interact with drugs and subsequently influence health outcomes. To date, this concept has not been systematicallyinvestigated. Nevertheless, adverse effects have been observed betweenenvironmental, dietary, and microbiome-derived xenobiotics and a number of drugs, including chemotherapeutics. Recent technological advances in mass spectrometry-based metabolomics and the establishment of omic-scale exposure assessment will enable a broader and systemic investigation of these interactions. As a complement to pharmacogenomics and pharmacometabolomics, research ondrug-exposome interactions holds immense potential to elevate precision medicineto an unprecedented level.

Computational Biotransformation Profile of Emerging Phenolic Pollutants by Cytochromes P450: Phenol-Coupling Mechanism

Phenols are ubiquitous environmental pollutants, whose biotransformation involving phenol coupling catalyzed by cytochromes P450 may produce more lipophilic and toxic metabolites. Density functional theory (DFT) computations were performed to explore the debated phenol-coupling mechanisms, taking triclosan as a model substrate. We find that a diradical pathway facilitated by compound I and protonated compound II of P450 is favored vs alternative radical addition or electron-transfer mechanisms. The identified diradical coupling resembles a "two-state reactivity" from compound I characterized by significantly high rebound barriers of the phenoxy radicals, which can be formulated into three equations for calculating the ratio [coupling]/[hydroxylation]. A higher barrier for rebound than for H-abstraction in high-spin triclosan can facilitate the phenoxy radical dissociation and thus enable phenol coupling, while H-abstraction/radical rebound causing phenol hydroxylation via minor rebound barriers mostly occurs via the low-spin state. Therefore, oxidation of triclosan by P450 fits the first equation with a ratio [coupling]/[hydroxylation] of 1:4, consistent with experimental data indicating different extents of triclosan coupling (6-40%). The high rebound barrier of phenoxy radicals, as a key for the mechanistic identification of phenol coupling vs hydroxylation, originates from their weak electron donor ability due to spin aromatic delocalization. We envision that the revealed mechanism can be extended to the cross-coupling reactions between different phenolic pollutants, and the coupling reactions of several other aromatic pollutants, to infer unknown metabolites.

Summation of disinfection by-product CHO cell relative toxicity indices: sampling bias, uncertainty, and a path forward

The cyto- and genotoxic potencies of disinfection by-products (DBPs) have been evaluated in published literature by measuring the response of exposed Chinese hamster ovary cells. In recent publications, DBP concentrations divided by their individual toxicity indices are summed to predict the relative toxicity of a water sample. We hypothesized that the omission or inclusion of certain DBPs over others is equivalent to statistical sampling bias and may result in biased conclusions. To test this hypothesis, we removed or added actual or simulated DBP measurements to that of published studies which evaluated granular activated carbon as a treatment to reduce the relative toxicity of the effluent. In several examples, it was possible to overturn the conclusions (i.e., activated carbon is detrimental or beneficial in reducing toxicity) by preferentially including specific DBPs. In one example, removing measured haloacetaldehydes caused the predicted cytotoxicity of a treated sample to decrease by up to 47%, reversing the initial conclusion that activated carbon increased the toxicity of the water. We also discuss measurements of statistical error, which are rarely included in publications related to predicted toxicity, but strongly influence the outcomes. Finally, we discuss future research needs in the light of these and other concerns.