硫醇酸是人體受到親電子性毒物暴露時，經由麩胱甘肽參與的代謝路徑所產生 的產物。這些代謝物會隨尿液排出，因此量測尿液中硫醇酸能夠幫助了解人體是否 遭受到親電子性化學毒物的暴露。然而要鑑定尿液中的硫醇酸至今仍有不少挑戰。 傳統的偵測方法大多依賴質譜分析中的中性丟失，特別是針對丟失129.0426 Da的 小分子訊號，即硫醇酸中N-乙醯半胱胺酸的特徵中性丟失。但不是所有硫醇酸在碎 裂時都會產生中性丟失訊號，導致部分硫醇酸無法經由此性質進行量測。此外目前 常用的圖譜與結構資料庫中收錄的硫醇酸的數量也非常有限，進一步限制了我們對 這類代謝物的鑑定。為了解決此問題，此處開發了一套新的硫醇酸分析流程，結合 aminoacylase-1 酵素的去乙醯作用，搭配超高效液相層析串聯高解析質儀進行中性丟 失訊號篩選。經由此酵素反應後，利用反應前後訊號的變化，進而篩選出不會產生 中性丟失訊號的硫醇酸。此外，我們自建了一個硫醇酸結構資料庫，利用常見的結 構資料庫，尋找資料庫內的親電子性毒物，並經由生物轉化程式，生成 734,170 個 硫醇酸的結構，後續結合SIRIUS軟體進行鑑定。在方法驗證方面，使用11種硫醇 酸標準探討本研究開發的方法應用於尿液中的可行性。接著，我們將此流程應用於 15 位受試者的尿液樣本，比較他們尿中的硫醇酸在正常飲食下與攝取油炸食物之後 的訊號變化。結果顯示，共鑑定出847個硫醇酸訊號。其中有多達581個化合物未 被HMDB或PubChem等常見的資料庫收錄，顯示這個方法在可以擴展鑑定更多的 硫醇酸。進一步分析發現，在攝取油炸食物後，有 58 個硫醇酸訊號明顯上升，10 個下降。上升的58硫醇酸中包含醛類、脂質氧化物等相關代謝物可能受到飲食影響 而產生變化。這項研究證實了使用高解析質譜的中性丟失策略與利用酵素反應，結 合自建硫醇酸資料庫的整合策略，可以提高硫醇酸的鑑定能力，也展示了該方法在 環境暴露研究方面的潛力。

Mercapturic acid conjugates (MACs) are end-products of detoxification formed through glutathione conjugation, followed by sequential enzymatic metabolism in the human body. These compounds provide insights into the exposome by tracing chemical transformations associated with reactive chemical species. However, comprehensive detection of MACs remains technically challenging due to the limitations of MS/MS spectral libraries and the insufficient coverage of MAC structures in existing structural databases. In this study, an analytical workflow was developed that integrates aminoacylase-1–assisted enzymatic deacetylation with ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS). This approach enables the detection of MACs that do not exhibit the characteristic neutral loss of 129.0426 Da, providing an orthogonal signal filtering approach to complement traditional neutral loss–based screening. For structure identification, a custom database consisting of 734,170 MAC structures was constructed using in silico biotransformation processing of known xenobiotic compounds. The resulting structures were matched with MS/MS data by SIRIUS software. The method was validated using 11 authentic MAC reference standards and applied to urine samples collected from 15 participants before and after a controlled deep-fried food diet. A total of 847 features was identified as MAC, of which 581 were not found in existing public databases such as HMDB or PubChem. Among the structurally identified MACs, 58 showed significantly increased intensities and 10 showed significant decreases in response to the deep-fried food diet. Further examination of these 58 significantly increased MACs identified metabolites associated with oxidative lipid degradation and reactive aldehyde clearance, consistent with MAC metabolic products previously reported in relation to deep-fried food intake. This workflow improves the detection and structural characterization of MACs and provides an extended approach for investigating environmental electrophilic exposures.

Albiach-Delgado A, Esteve-Turrillas FA, Fernández SF, Garlito B, Pardo O. 2022. Review of the state of the art of acrylamide human biomonitoring. Chemosphere 295:133880.
Bajaj P, Chowdhury SK, Yucha R, Kelly EJ, Xiao G. 2018. Emerging kidney models to investigate metabolism, transport, and toxicity of drugs and xenobiotics. Drug Metabolism and Disposition 46:1692-1702.
Balbo S, Turesky RJ, Villalta PW. 2014. DNA adductomics. Chem Res Toxicol 27:356-366.
Bijlsma S, Bobeldijk I, Verheij ER, Ramaker R, Kochhar S, Macdonald IA, et al. 2006. Large-scale human metabolomics studies:  A strategy for data (pre-) processing and validation. Analytical Chemistry 78:567-574.
Bloch R, Schütze S-E, Müller E, Röder S, Lehmann I, Brack W, et al. 2019. Non-targeted mercapturic acid screening in urine using lc-ms/ms with matrix effect compensation by postcolumn infusion of internal standard (pci-is). Anal Bioanal Chem 411:7771-7781.
Bloszies CS, Fiehn O. 2018. Using untargeted metabolomics for detecting exposome compounds. Current Opinion in Toxicology 8:87-92.
Chang C, Gangcheng W, Hui Z, Qingzhe J, and Wang X. 2020. Deep-fried flavor: Characteristics, formation mechanisms, and influencing factors. Critical Reviews in Food Science and Nutrition 60:1496-1514.
Chen Y-C, Wu H-Y, Chang C-W, Liao P-C. 2022. Post-deconvolution ms/ms spectra extraction with data-independent acquisition for comprehensive profiling of urinary glucuronide-conjugated metabolome. Anal Chem 94:2740-2748.
Chen Y-C, Hsu J-F, Chang C-W, Li S-W, Yang Y-C, Chao M-R, et al. 2023. Connecting chemical exposome to human health using high-resolution mass spectrometry-based biomonitoring: Recent advances and future perspectives. Mass Spectrometry Reviews 42:2466-2486.
Chen Y-C. 2025. Development of the biotransformation products elucidation tools to expand the structure annotation in untargeted metabolomics.
Chen Z-Q, Yang R-J, Zhu C-W, Li Y, Yan R, Wan J-B. 2024. Chemical isotope labeling and dual-filtering strategy for comprehensive profiling of urinary glucuronide conjugates. Anal Chem 96:13576-13587.
Choe E, Min DB. 2007. Chemistry of deep-fat frying oils. Journal of Food Science 72:R77-R86.
Cosman M, de los Santos C, Fiala R, Hingerty BE, Singh SB, Ibanez V, et al. 1992. Solution conformation of the major adduct between the carcinogen (+)-anti-benzo[a]pyrene diol epoxide and DNA. Proceedings of the National Academy of Sciences 89:1914-1918.
Crnogorac G, Schwack W. 2007. Determination of dithiocarbamate fungicide residues by liquid chromatography/mass spectrometry and stable isotope dilution assay. Rapid Communications in Mass Spectrometry 21:4009-4016.
Dai W, Yin P, Zeng Z, Kong H, Tong H, Xu Z, et al. 2014. Nontargeted modification-specific metabolomics study based on liquid chromatography–high-resolution mass spectrometry. Anal Chem 86:9146-9153.
de Bruyn Kops C, Šícho M, Mazzolari A, Kirchmair J. 2021. Gloryx: Prediction of the metabolites resulting from phase 1 and phase 2 biotransformations of xenobiotics. Chem Res Toxicol 34:286-299.
De Flora S, Izzotti A, Randerath K, Randerath E, Bartsch H, Nair J, et al. 1996. DNA adducts and chronic degenerative diseases. Pathogenetic relevance and implications in preventive medicine. Mutation Research/Reviews in Genetic Toxicology 366:197-238.
Djoumbou-Feunang Y, Pon A, Karu N, Zheng J, Li C, Arndt D, et al. 2019. Cfm-id 3.0: Significantly improved esi-ms/ms prediction and compound identification. Metabolites; doi: 10.3390/metabo9040072.
Dührkop K, Shen H, Meusel M, Rousu J, Böcker S. 2015. Searching molecular structure databases with tandem mass spectra using csi:Fingerid. Proceedings of the National Academy of Sciences 112:12580-12585.
Dührkop K, Fleischauer M, Ludwig M, Aksenov AA, Melnik AV, Meusel M, et al. 2019. Sirius 4: A rapid tool for turning tandem mass spectra into metabolite structure information. Nature Methods 16:299-302.
Frigerio G, Campo L, Mercadante R, Mielżyńska-Švach D, Pavanello S, Fustinoni S. 2020. Urinary mercapturic acids to assess exposure to benzene and other volatile organic compounds in coke oven workers. International Journal of Environmental Research and Public Health; doi: 10.3390/ijerph17051801.
Gagnaire F, Marignac B, Ban M, Langlais C. 2001. The ototoxic effects induced in rats by treatment for 12 weeks with 2-butenenitrile, 3-butenenitrile and cis-2-pentenenitrile. Pharmacology & Toxicology 88:126-134.
Grootveld M, Percival BC, Leenders J, Wilson PB. 2020. Potential adverse public health effects afforded by the ingestion of dietary lipid oxidation product toxins: Significance of fried food sources. Nutrients; doi: 10.3390/nu12040974.
Hanna PE, and Anders MW. 2019. The mercapturic acid pathway. Critical Reviews in Toxicology 49:819-929.
Haufroid V, Lison D. 2005. Mercapturic acids revisited as biomarkers of exposure to reactive chemicals in occupational toxicology: A minireview. International Archives of Occupational and Environmental Health 78:343-354.
Hoet P, De Smedt E, Ferrari M, Imbriani M, Maestri L, Negri S, et al. 2009. Evaluation of urinary biomarkers of exposure to benzene: Correlation with blood benzene and influence of confounding factors. International Archives of Occupational and Environmental Health 82:985-995.
Horai H, Arita M, Kanaya S, Nihei Y, Ikeda T, Suwa K, et al. 2010. Massbank: A public repository for sharing mass spectral data for life sciences. Journal of Mass Spectrometry 45:703-714.
Jamin EL, Costantino R, Mervant L, Martin J-F, Jouanin I, Blas-Y-Estrada F, et al. 2020. Global profiling of toxicologically relevant metabolites in urine: Case study of reactive aldehydes. Anal Chem 92:1746-1754.
Jancova P, Siller M. 2012. Phase ii drug metabolism. In: Topics on drug metabolism, (Paxton JW, ed). Rijeka:IntechOpen.
Jia W, Ke X, Huang A, Zhuang P, Zhang Y, Wan X, et al. 2025. Ultra-high performance liquid chromatography–tandem mass spectrometry for profiling mercapturic acids in human urine after daily exposure to acrylamide, 3-monochloropropane-1,2-diol and glycidol. Anal Methods.
Ketterer B, Coles B, Meyer David J. 1983. The role of glutathione in detoxication. Environmental Health Perspectives 49:59-69.
Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, et al. 2025. Pubchem 2025 update. Nucleic Acids Research 53:D1516-D1525.
Liesenfeld S, Steliopoulos P, Wenig S, Gottstein V, Hamscher G. 2022. Comprehensive lc-hrms metabolomics analyses for the estimation of environmental inputs of altrenogest in pig breeding. Chemosphere 287:132353.
LoPachin RM, DeCaprio AP. 2005. Protein adduct formation as a molecular mechanism in neurotoxicity. Toxicological Sciences 86:214-225.
Miinalainen IJ, Schmitz W, Huotari A, Autio KJ, Soininen R, Ver Loren van Themaat E, et al. 2009. Mitochondrial 2,4-dienoyl-coa reductase deficiency in mice results in severe hypoglycemia with stress intolerance and unimpaired ketogenesis. PLOS Genetics 5:e1000543.
Miller GW, Jones DP. 2014. The nature of nurture: Refining the definition of the exposome. Toxicological Sciences 137:1-2.
Nakken CL, Berntssen MHG, Meier S, Bijlsma L, Mjøs SA, Sørhus E, et al. 2024. Exposure of polycyclic aromatic hydrocarbons (pahs) and crude oil to atlantic haddock (melanogrammus aeglefinus): A unique snapshot of the mercapturic acid pathway. Environmental Science & Technology 58:14855-14863.
Oesterle I, Pristner M, Berger S, Wang M, Verri Hernandes V, Rompel A, et al. 2023. Exposomic biomonitoring of polyphenols by non-targeted analysis and suspect screening. Anal Chem 95:10686-10694.
Pathmasiri W, Rushing BR, McRitchie S, Choudhari M, Du X, Smirnov A, et al. 2024. Untargeted metabolomics reveal signatures of a healthy lifestyle. Sci Rep 14:13630.
Poteser M, Laguzzi F, Schettgen T, Vogel N, Weber T, Murawski A, et al. 2022. Trends of exposure to acrylamide as measured by urinary biomarkers levels within the hbm4eu biomonitoring aligned studies (2000–2021). Toxics; doi: 10.3390/toxics10080443.
Reuter SE, Evans AM. 2012. Carnitine and acylcarnitines. Clinical Pharmacokinetics 51:553-572.
Richard AM, Huang R, Waidyanatha S, Shinn P, Collins BJ, Thillainadarajah I, et al. 2021. The tox21 10k compound library: Collaborative chemistry advancing toxicology. Chem Res Toxicol 34:189-216.
Ross DH, Xu L. 2021. Determination of drugs and drug metabolites by ion mobility-mass spectrometry: A review. Analytica Chimica Acta 1154:338270.
Ruttkies C, Schymanski EL, Wolf S, Hollender J, Neumann S. 2016. Metfrag relaunched: Incorporating strategies beyond in silico fragmentation. Journal of Cheminformatics 8:3.
Sterz K, Köhler D, Schettgen T, Scherer G. 2010. Enrichment and properties of urinary pre-s-phenylmercapturic acid (pre-spma). Journal of Chromatography B 878:2502-2505.
Stevens JF, Maier CS. 2008. Acrolein: Sources, metabolism, and biomolecular interactions relevant to human health and disease. Molecular Nutrition & Food Research 52:7-25.
Szabo D, Fischer S, Mathew AP, Kruve A. 2024. Prioritization, identification, and quantification of emerging contaminants in recycled textiles using non-targeted and suspect screening workflows by lc-esi-hrms. Anal Chem 96:14150-14159.
Townsend DM, Findlay VL, Tew KD. 2005. Glutathione s‐transferases as regulators of kinase pathways and anticancer drug targets. In: Methods in enzymology, Vol. 401, (Sies H, Packer L, eds):Academic Press, 287-307.
Tsugawa H, Cajka T, Kind T, Ma Y, Higgins B, Ikeda K, et al. 2015. Ms-dial: Data-independent ms/ms deconvolution for comprehensive metabolome analysis. Nature Methods 12:523-526.
Vašková J, Kočan L, Vaško L, Perjési P. 2023. Glutathione-related enzymes and proteins: A review. Molecules; doi: 10.3390/molecules28031447.
Wang B, Yu L, Liu W, Yang M, Fan L, Zhou M, et al. 2022. Cross-sectional and longitudinal associations of acrolein exposure with pulmonary function alteration: Assessing the potential roles of oxidative DNA damage, inflammation, and pulmonary epithelium injury in a general adult population. Environment International 167:107401.
Wang M, Carver JJ, Phelan VV, Sanchez LM, Garg N, Peng Y, et al. 2016. Sharing and community curation of mass spectrometry data with global natural products social molecular networking. Nature Biotechnology 34:828-837.
Wang R, Yin Y, Zhu Z-J. 2019. Advancing untargeted metabolomics using data-independent acquisition mass spectrometry technology. Anal Bioanal Chem 411:4349-4357.
Weisel CP. 2010. Benzene exposure: An overview of monitoring methods and their findings. Chemico-Biological Interactions 184:58-66.
Wishart D, Arndt D, Pon A, Sajed T, Guo AC, Djoumbou Y, et al. 2015. T3db: The toxic exposome database. Nucleic Acids Research 43:D928-D934.
Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, et al. 2007. Hmdb: The human metabolome database. Nucleic Acids Research 35:D521-D526.
Wishart DS, Guo A, Oler E, Wang F, Anjum A, Peters H, et al. 2022a. Hmdb 5.0: The human metabolome database for 2022. Nucleic Acids Research 50:D622-D631.
Wishart DS, Tian S, Allen D, Oler E, Peters H, Lui Vicki W, et al. 2022b. Biotransformer 3.0—a web server for accurately predicting metabolic transformation products. Nucleic Acids Research 50:W115-W123.
Xie Z, Chen JY, Gao H, Keith RJ, Bhatnagar A, Lorkiewicz P, et al. 2023. Global profiling of urinary mercapturic acids using integrated library-guided analysis. Environmental Science & Technology 57:10563-10573.
Yan LL, Zaher HS. 2019. How do cells cope with rna damage and its consequences? Journal of Biological Chemistry 294:15158-15171.
Zamora R, Aguilar I, Granvogl M, Hidalgo FJ. 2016. Toxicologically relevant aldehydes produced during the frying process are trapped by food phenolics. J Agric Food Chem 64:5583-5589.
Zhang L, Chen J, Zhao X, Wang Y, Yu X. 2022. Influence of roasting on the thermal degradation pathway in the glucosinolates of fragrant rapeseed oil: Implications to flavour profiles. Food Chemistry: X 16:100503.