Identification of urinary biomarkers of exposure to di-(2-propylheptyl) phthalate using high-resolution mass spectrometry and two data-screening approaches

Dose-response technique combined with stable isotope tracing for drug metabolite profiling by using high-resolution mass spectrometry

Background: Mass spectrometry metabolomics-based data-processing approaches have been developed for drug metabolite profiling. However, existing approaches cannot be used to comprehensively identify drug metabolites with high efficacy. Methods: Herein, we propose a two-stage data-processing approach for effective and comprehensive drug metabolite identification. The approach combines dose-response experiments with stable isotope tracing (SIT). Rosiglitazone (ROS), commonly used to treat type 2 diabetes, was employed as a model drug. Results: In the first stage of data processing, 1,071 features exhibited a dose-response relationship among 22,597 features investigated. In the second stage, these 1,071 features were screened for isotope pairs, and 200 features with isotope pairs were identified. In time-course experiments, a large proportion of the identified features (69.5%: 137 out of 200 features) were confirmed to be possible ROS metabolites. We compared the validated features identified using our approach with those identified using a previously reported approach [the mass defect filter (MDF) combined with SIT] and discovered that most of the validated features (37 out of 42) identified using the MDF-SIT combination were also successfully identified using our approach. Of the 143 validated features identified by both approaches, 74 had a proposed structure of an ROS-structure-related metabolite; the other 34 features that contained a specific fragment of ROS metabolites were considered possible ROS metabolites. Interestingly, numerous ROS-structure-related metabolites were identified in this study, most of which were novel. Conclusion: The results reveal that the proposed approach can effectively and comprehensively identify ROS metabolites.

Identification of Xenobiotic Biotransformation Products Using Mass Spectrometry-Based Metabolomics Integrated with a Structural Elucidation Strategy by Assembling Fragment Signatures

The identification of xenobiotic biotransformation products is crucial for delineating toxicity and carcinogenicity that might be caused by xenobiotic exposures and for establishing monitoring systems for public health. However, the lack of available reference standards and spectral data leads to the generation of multiple candidate structures during identification and reduces the confidence in identification. Here, a UHPLC-HRMS-based metabolomics strategy integrated with a metabolite structure elucidation approach, namely, FragAssembler, was proposed to reduce the number of false-positive structure candidates. biotransformation product candidates were filtered by mass defect filtering (MDF) and multiple-group comparison. FragAssembler assembled fragment signatures from the MS/MS spectra and generated the modified moieties corresponding to the identified biotransformation products. The feasibility of this approach was demonstrated by the three biotransformation products of di(2-ethylhexyl)phthalate (DEHP). Comprehensive identification was carried out, and 24 and 13 biotransformation products of two xenobiotics, DEHP and 4'-Methoxy-α-pyrrolidinopentiophenone (4-MeO-α-PVP), were annotated, respectively. The number of 4-MeO-α-PVP biotransformation product candidates in the FragAssembler calculation results was approximately 2.1 times lower than that generated by BioTransformer 3.0. Our study indicates that the proposed approach has great potential for efficiently and reliably identifying xenobiotic biotransformation products, which is attributed to the fact that FragAssembler eliminates false-positive reactions and chemical structures and distinguishes modified moieties on isomeric biotransformation products. The FragAssembler software and associated tutorial are freely available at https://cosbi.ee.ncku.edu.tw/FragAssembler/ and the source code can be found at https://github.com/YuanChihChen/FragAssembler.

Using a high-resolution mass spectrometry-based metabolomics strategy for comprehensively screening and identifying biomarkers of phthalate exposure: Method development and application

Di-(2-propylheptyl) phthalate (DPHP) is an alternative plasticizer that can replace other phthalates currently being scrutinized, and its use and production volumes are increasing. This study aimed to develop a high-resolution mass spectrometry (HRMS)-based metabolomics strategy to comprehensively screen urinary biomarkers of DPHP exposure and filter out potentially useful DPHP exposure markers for human exposure assessments. This strategy included three stages: screening of biomarkers, verification of dose-response relationships in laboratory animals, and application in human subjects. The multivariate data analysis method known as orthogonal partial least-squares discriminant analysis (OPLS-DA) was used to screen and find meaningful signals in an MS dataset generated from urine samples collected from DPHP-administered rats. Thirty-six MS signals were verified as exposure marker candidates by assessing dose-response relationships in an animal feeding study. A biotransformation product of DPHP, mono-(2-propyl-7-dihydroxy-heptyl) phthalate, was suggested as a DPHP exposure marker for general human exposure assessments after the human application study and chemical structure identification. Three previously oxidized DPHP biotransformation products might be suitable for human exposure assessments in high-level exposure groups but not in the general population due to their low sensitivity.

Exposure marker discovery of di-2(propylheptyl) phthalate using ultra-performance liquid chromatography-mass spectrometry and a rat model

Di-(2-propylheptyl) phthalate (DPHP) is a plasticizer and has been suggested to be a subchronic toxicant in rats. DPHP has been approved to be used in food containers and handling by the U.S. Food and Drug Administration. The use of DPHP is still increasing, and the risk of human exposure to DPHP via food may be high. Exposure markers measured in human samples are commonly used to monitor human exposure levels. Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and a rat model were used to discover tentative DPHP exposure markers. DPHP and mono-(2-propylheptyl) phthalate (MPHP) were used as the precursors for calculating metabolite candidates using biotransformation mass changes of known enzymatic reactions. A rat model was designed to validate these metabolite candidates as tentative exposure markers. A total of 28 signals show dose–response relationships and these signals contain a few isomers. The chemical structures of 15 tentative exposure marker signals were speculated based on the product ion mass spectra from MS/MS analysis. These 15 signals included 7 chemical structures and some of them may be isomers. The different arrangement of the atoms in space of these isomers should be validated by standard compounds in the future studies. Among the 7 speculated chemical structures, 2 structures were novel tentative DPHP metabolites, and 5 structures have been previously reported in the literature. The results indicate that using UPLC-MS and a rat model can be used to identify tentative toxicant exposure markers.

Profiling and comparison of toxicant metabolites in hair and urine using a mass spectrometry-based metabolomic data processing method

Urine and hair are used for assessing human exposure to toxicants. Urine tests can show acute toxicant exposure. Hair analysis can be used to determine chronic toxicant exposure after months to years; however, compared to urine, hair analysis in exposure assessments is much less frequently investigated. Urine and hair are different matrices, and their mechanisms of toxicant metabolite incorporation are different. The toxicant metabolites present in urine and hair may also be different. To clarify this issue, a procedure was developed to identify toxicant metabolites in rat samples using a mass spectrometry-based metabolomic data processing method. Di-(2-propylheptyl) phthalate (DPHP), an industrial plasticizer, was used as the model toxicant. The developed procedure identified not only known DPHP metabolites (mono-(propyl-6-oxo-heptyl) phthalate, mono-(propyl-6-hydroxyheptyl) phthalate, and mono-(propyl-6-carboxyhexyl) phthalate) but also novel metabolites that were structurally related to DPHP in the rat samples, indicating that the developed procedure successfully identified toxicant metabolites in in vivo samples. Among the 62 tentative metabolites identified from the 7^th-day urine and the 28^th-day hair samples, 33 were detected in only the urine samples, 19 were detected in only the hair samples, and 10 were identified in both the urine and hair samples. A total of 15 out of the 62 metabolites were confirmed as DPHP structure-related metabolites based on MS/MS analysis. Among the 15 DPHP structure-related metabolites, only 2 metabolites were present in both the urine and hair samples. These results suggested that the metabolites identified in urine could not be applied to exposure assessments based on hair analysis.