Large-scale, enzyme-based xenobiotic identification for exposomics

Liu, Ken; Lee, Choon; Singer, Grant; Woodworth, Michael H.; Ziegler, Thomas R.; Kraft, Colleen S.; Miller, Gary W.; Li, Shuzhao; Go, Young‐Mi; Morgan, Edward M.; Jones, Dean P.

doi:10.21203/rs.3.rs-77801/v1

Cited by 4 publications

(7 citation statements)

References 29 publications

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“…Although current efforts are focused on generating spectral libraries of unknown metabolites, these methods have not been extended to GC-HRMS. (29,32) The limited annotation of environmental chemicals associated with PSC underscores a major challenge in gaining biological insight using untargeted GC-HRMS and the need for improved annotation tools for exposome research. This chemical, terbucarb, is a carbamate pesticide, a class of insecticide widely used in household, agricultural, and industrial applications.…”

Section: Discussionmentioning

confidence: 99%

High‐Resolution Exposomics and Metabolomics Reveals Specific Associations in Cholestatic Liver Diseases

et al. 2021

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Progress in development of prognostic and therapeutic options for the rare cholestatic liver diseases, primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC), is hampered by limited knowledge of their pathogeneses. In particular, the potential role of hepatotoxic and/or metabolism‐altering environmental chemicals in the pathogenesis of these diseases remains relatively unstudied. Moreover, the extent to which metabolic pathways are altered due to ongoing cholestasis and subsequent liver damage or possibly influenced by hepatotoxic chemicals is poorly understood. In this study, we applied a comprehensive exposomics‐metabolomics approach to uncover potential pathogenic contributors to PSC and PBC. We used untargeted high‐resolution mass spectrometry to characterize a wide range of exogenous chemicals and endogenous metabolites in plasma and tested them for association with disease. Exposome‐wide association studies (EWAS) identified environmental chemicals, including pesticides, additives and persistent pollutants, that were associated with PSC and/or PBC, suggesting potential roles for these compounds in disease pathogenesis. Metabolome‐wide association studies (MWAS) found disease‐associated alterations to amino acid, eicosanoid, lipid, co‐factor, nucleotide, mitochondrial and microbial metabolic pathways, many of which were shared between PSC and PBC. Notably, this analysis implicates a potential role of the 5‐lipoxygenase pathway in the pathogenesis of these diseases. Finally, EWAS × MWAS network analysis uncovered linkages between environmental agents and disrupted metabolic pathways that provide insight into potential mechanisms for PSC and PBC. Conclusion: This study establishes combined exposomics‐metabolomics as a generalizable approach to identify potentially pathogenic environmental agents and enumerate metabolic alterations that may impact PSC and PBC, providing a foundation for diagnostic and therapeutic strategies.

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Section: Discussionmentioning

confidence: 99%

High‐Resolution Exposomics and Metabolomics Reveals Specific Associations in Cholestatic Liver Diseases

et al. 2021

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“…Furthermore, we observed dihydroxybupropion in mice following oral gavage of bupropion (Fig. 4A), and in a plasma sample from a patient with documented bupropion use in which we had previously identified hydroxybupropion and hydrobupropion (Liu et al, 2021). The retention times and ion fragmentation spectra for dihydroxybupropion detected in the patient matched that of the CYP2B6 generated dihydroxybupropion (Fig.…”

Section: Resultsmentioning

confidence: 60%

“…We have previously shown that S9 enzymes can be used to provide a high-throughput approach to generate Phase I and II metabolites to identify xenobiotic exposures in humans (Liu et al, 2021). The P450 cell lines provide a complementary workflow for simultaneous generation of Phase I, CYP-dependent, metabolites of xenobiotics, and subsequent identification of active enzyme-substrate pairs.…”

Section: Discussionmentioning

confidence: 99%

“…We recently used human liver S9 fractions to develop an in vitro high-throughput biotransformation platform coupled with HRMS, showing that generated xenobiotic metabolites can be used as reference mixtures to identify xenobiotic exposures in human blood and urine (Liu et al, 2021). However, one disadvantage of using S9 fractions for biotransformation is that not all xenobiotic metabolizing enzymes are equally expressed.…”

Section: Introductionmentioning

confidence: 99%

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High-throughput Production of Diverse Xenobiotic Metabolites with P450-transduced Huh7 Hepatoma Cell Lines

Lee

Liu

Singer

et al. 2022

Preprint

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Precision medicine requires methods to assess drug metabolism and distribution, including the identification of known and undocumented drug and chemical exposures as well as their metabolites. Recent work demonstrated high-throughput generation of xenobiotic metabolites with human liver S-9 fractions and detection in human plasma and urine. Here, we developed a panel of lentivirally transduced human hepatoma cell lines (Huh7) that stably express individual cytochrome P450 (P450) enzymes and generate P450-specific xenobiotic metabolites. We verified protein expression by immunoblotting and demonstrated that the cell lines generate P450-specific metabolites from probe substrates. To increase analytical throughput, we used a pooling strategy where 36 chemicals were grouped into 12 unique mixtures, each mixture containing 6 randomly selected compounds, and each compound being present in two separate mixtures. Each mixture of compounds was incubated with 8 different P450 cell lines with cell extracts analyzed at 0 and 2 h. Extracts were analyzed using liquid chromatography-high resolution mass spectrometry. Cell lines selectively metabolized test substrates, with pazopanib metabolized by CYP3A4 and CYP2C8 cells, bupropion by CYP2B6, and β-naphthoflavone by CYP1A2 for example, showing substrate-enzyme specificity. Predicted metabolites from the remaining 33 compounds as well as many unidentified m/z features were detected. We also show that a specific metabolite generated by CYP2B6 cells, but not detected in the S9 system, was identified in human samples. Our data show that incubating these cell lines with chemical mixtures accelerated characterization of xenobiotic chemical space, while simultaneously allowing for the contributions of specific P450 enzymes to be identified.

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“…HRMS analyses follow established protocols using dual liquid chromatography-ultrahigh-resolution mass spectrometry (LC-MS) for metabolomics and gas chromatography-ultrahigh-resolution mass spectrometry (GC-MS) for exposomics with data extraction supporting both targeted and untargeted analyses [28,29]. Capabilities can identify a very broad spectrum of endogenous metabolites, food and microbiome metabolites, and environmental chemical exposures [28,29].…”

Section: Biological Specimen Collection For Crp and Multi-omics Studiesmentioning

confidence: 99%

PISTACHIo (PreemptIon of diSrupTive behAvior in CHIldren): real-time monitoring of sleep and behavior of children 3–7 years old receiving parent–child interaction therapy augment with artificial intelligence — the study protocol, pilot study

Saliba

Drapeau

Skime

et al. 2023

Pilot Feasibility Stud

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Background Emotional behavior problems (EBP) are the most common and persistent mental health issues in early childhood. Early intervention programs are crucial in helping children with EBP. Parent–child interaction therapy (PCIT) is an evidence-based therapy designed to address personal difficulties of parent–child dyads as well as reduce externalizing behaviors. In clinical practice, parents consistently struggle to provide accurate characterizations of EBP symptoms (number, timing of tantrums, precipitating events) even from the week before in their young children. The main aim of the study is to evaluate feasibility of the use of smartwatches in children aged 3–7 years with EBP. Methods This randomized double-blind controlled study aims to recruit a total of 100 participants, consisting of 50 children aged 3–7 years with an EBP measure rated above the clinically significant range (T-score ≥ 60) (Eyberg Child Behavior Inventory-ECBI; Eyberg & Pincus, 1999) and their parents who are at least 18 years old. Participants are randomly assigned to the artificial intelligence-PCIT group (AI-PCIT) or the PCIT-sham biometric group. Outcome parameters include weekly ECBI and Pediatric Sleep Questionnaire (PSQ) as well as Child Behavior Checklist (CBCL) obtained weeks 1, 6, and 12 of the study. Two smartphone applications (Garmin connect and mEMA) and a wearable Garmin smartwatch are used collect the data to monitor step count, sleep, heart rate, and activity intensity. In the AI-PCIT group, the mEMA application will allow for the ecological momentary assessment (EMA) and will send behavioral alerts to the parent. Discussion Real-time predictive technologies to engage patients rely on daily commitment on behalf of the participant and recurrent frequent smartphone notifications. Ecological momentary assessment (EMA) provides a way to digitally phenotype in-the-moment behavior and functioning of the parent–child dyad. One of the study’s goals is to determine if AI-PCIT outcomes are superior in comparison with standard PCIT. Overall, we believe that the PISTACHIo study will also be able to determine tolerability of smartwatches in children aged 3–7 with EBP and could participate in a fundamental shift from the traditional way of assessing and treating EBP to a more individualized treatment plan based on real-time information about the child’s behavior. Trial registration The ongoing clinical trial study protocol conforms to the international Consolidated Standards of Reporting Trials (CONSORT) guidelines and is registered in clinicaltrials.gov (ID: NCT05077722), an international clinical trial registry.

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Large-scale, enzyme-based xenobiotic identification for exposomics

Cited by 4 publications

References 29 publications

High‐Resolution Exposomics and Metabolomics Reveals Specific Associations in Cholestatic Liver Diseases

High‐Resolution Exposomics and Metabolomics Reveals Specific Associations in Cholestatic Liver Diseases

High-throughput Production of Diverse Xenobiotic Metabolites with P450-transduced Huh7 Hepatoma Cell Lines

PISTACHIo (PreemptIon of diSrupTive behAvior in CHIldren): real-time monitoring of sleep and behavior of children 3–7 years old receiving parent–child interaction therapy augment with artificial intelligence — the study protocol, pilot study

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