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SIRIUS-ly Toxic: Mapping Unknown Urinary Biomarkers Derived from Deep-Fried Foods

Every day, our bodies encounter millions of foreign chemical compounds. Among the most dangerous are reactive electrophilic species—unstable molecules that can bind to DNA and proteins, potentially leading to chronic diseases. Fortunately, our bodies fight back using glutathione conjugation, excreting these toxins as urinary mercapturic acid conjugates (MACs). But until now, checking urine to see exactly what toxins we’ve been exposed to was incredibly difficult because standard tracking methods miss highly unstable chemical structures. Researchers developed an analytical strategy that dramatically expands our ability to profile the urinary "adductome". By pairing high-resolution mass spectrometry with customized database construction and automated computational annotation using SIRIUS, this workflow uncovers hundreds of previously untraceable biomarkers.
A variety of crispy fried food dishes served together
Humans are exposed to millions of chemical compounds, including dangerous dietary electrophiles from deep-fried foods. (Photo by Tonia Kraakman on Unsplash.)

Neutralizing the troublemakers

Throughout their lifetimes, humans are exposed to millions of chemical compounds, including dangerous environmental or dietary electrophiles—reactive chemical species capable of binding to DNA, RNA, and proteins, forming adducts that can disrupt biological processes1,2 and ultimately lead to cancer and chronic degenerative diseases3,4. When the body is exposed to environmental or dietary electrophiles it neutralizes them via glutathione conjugation5. This protective detoxification pathway attaches a glutathione molecule to the electrophile. The glutathione conjugates are further metabolized into mercapturic acid conjugates (MACs) and naturally excreted from the body in urine6. This makes MACs highly effective and feasible urinary biomarkers for biomonitoring human exposure to environmental toxicants7. For example, SPMA (N-acetyl-S-phenyl-L-cysteine) is a well-established urinary biomarker commonly used to assess exposure to benzene from ubiquitous industrial and environmental sources (e.g. cigarette smoke or detergents)8.

By comprehensively screening and analyzing the vast array of urinary MACs—collectively referred to as the MAC “adductome”—scientists can monitor general toxicant exposure and discover previously unrecognized reactive chemical interactions within the body. However, exploring this adductome has historically been limited. Previous mass spectrometry studies generally identified only around 100 MACs because they relied on incomplete reference databases and screening rules that inadvertently missed hidden or unstable compounds. Standard tracking methods often depend strictly on filtering out signals with a characteristic neutral loss (C5H7NO3, 129.0426 Da)9, a behavior that is not universal and can cause highly unstable or labile chemical structures to be missed.

Expanding the observable exposome with SIRIUS

To overcome traditional screening limits, researchers from National Cheng Kung University, Taiwan, created a workflow combining a novel enzymatic deacetylation strategy with liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS)10. They used the enzyme aminoacylase-1 to detect fragile MACs that lack the typical neutral loss fragment, and they optimized a high-resolution data-independent acquisition (DIA) method. To identify these compounds, the team built a custom reference database of 734,170 putative MAC structures by pulling compounds from HMDB, Tox21, and T3DB, predicting their biotransformations with BioTransformer 3.0 and GLORYx.

Once potential MAC candidates were filtered via neutral loss filtering and enzymatic deacetylation metrics, their deconvoluted DIA-MS/MS spectra were imported into SIRIUS to improve the reliability of feature assignments. SIRIUS was used for molecular formula annotation and molecular structure annotation within the newly built custom MAC library, HMDB, and PubChem.

After validating this orthogonal screening approach using 11 spiked MAC standards in urine, the team applied the workflow to map urinary exposure biomarkers in 15 participants before and after they ate deep-fried foods.

Identifying previously unreported MACs

The developed workflow significantly expanded the observable MAC exposome, successfully mapping a total of 847 features to at least one MAC structure in the participant urine samples. This throughput drastically exceeds the ~100 MACs typically reported in previous literature. Out of these mapped features, the team annotated 624 unique chemical structures—581 of which were completely novel and absent from major public repositories like the Human Metabolome Database (HMDB) or PubChem.

Spiking validation proved that a labile subclass of MACs does not consistently exhibit the typical 129.0426 Da neutral loss under moderate-to-high collision energies due to rapid signal decay. However, these labile species were successfully captured via the enzymatic deacetylation pipeline, demonstrating the clear complementary value of the orthogonal screening layer.

Three-part diagram showing the SIRIUS annotation results for the mercapturic acid conjugate (MAC) of a phase I metabolite of 4-hydroxydecenal. Panel (a) displays a DIA MS/MS mass spectrum showing relative intensity versus m/z, with green-labeled peaks highlighting annotated substructure fragments. Panel (b) shows a highly branched molecular fragmentation tree colored by relative intensity. Panel (c) highlights the top-ranked structural match showing the chemical structure of the 4-hydroxydecenal conjugate, its substructures, its database source and CSI:FingerID Score.
The process of structural annotation based on SIRIUS software was illustrated using the MAC of a phase I metabolite of 4-hydroxydecenal.

SIRIUS enabled the in silico identification of complex conjugates. While comparison with authentic standards showed that computational predictions occasionally identified constitutional isomers rather than exact structural matches (e.g., swapping atom positions or misidentifying alkyl chains), the tool was fundamentally responsible for accurately capturing the core molecular scaffold of hundreds of unknown conjugate species.

Dietary alterations

Following the dietary intervention with deep-fried foods, 59 MACs significantly increased in abundance and 11 decreased. Clear temporal differences were observed when analyzing urine samples from different collection periods. Samples collected on day 4 captured the rapid clearance of xenobiotics with short biological half-lives immediately following dietary intake. Conversely, sampling on day 5 followed the cessation of deep-fried food consumption, revealing the accumulation and slower elimination kinetics of persistent biotransformation products.

Ultimately, this workflow establishes a highly effective analytical framework that can be expanded to profile a broader spectrum of the adductome across diverse cohort studies.

References
  1. R. M. LoPachin, A. P. DeCaprio. Protein Adduct Formation as a Molecular Mechanism in Neurotoxicity. Toxicol. Sci. (2005) https://doi.org/10.1093/toxsci/kfi197 ↩︎
  2. S. Balbo, R. J. Turesky, P. W. Villalta. DNA Adductomics. Chem. Res. Toxicol. (2014) https://doi.org/10.1021/tx4004352 ↩︎
  3. S. De Flora, A. Izzotti, K. Randerath, E. Randerath, H. Bartsch, J. Nair, R. Balansky, F. van Schooten, P. Degan, G. Fronza, D. Walsh, J. Lewtas. DNA adducts and chronic degenerative diseases. Pathogenetic relevance and implications in preventive medicine. Mutat. Res., Rev. Genet. Toxicol. (1996) https://doi.org/10.1016/S0165-1110(96)00043-7 ↩︎
  4. B. Hwa Yun, J. Guo, M. Bellamri, R. J. Turesky. DNA adducts: Formation, biological effects, and new biospecimens for mass spectrometric measurements in humans. Mass Spectrom. Rev. (2020) https://doi.org/10.1002/mas.21570 ↩︎
  5. Ketterer, B.; Coles, B.; Meyer, D. J. The role of glutathione in detoxication. Environ. Health Perspect. 1983, 49, 59– 69,  DOI: 10.1289/ehp.834959 ↩︎
  6. A. J. L. Cooper, M. H. Hanigan. Enzymes Involved in Processing Glutathione Conjugates. Comp. Toxicol. (2010) https://doi.org/10.1016/B978-0-08-046884-6.00417-6 ↩︎
  7. F. Seutter-Berlage, H. L. van Dorp, H. G. J. Kosse, P. T. Henderson. Urinary mercapturic acid excretion as a biological parameter of exposure to alkylating agents. Int. Arch. Occup. Environ. Health (1977) https://doi.org/10.1007/BF00381551 ↩︎
  8. C. P. Weisel. Benzene exposure: An overview of monitoring methods and their findings. Chem.-Biol. Interact. (2010) https://doi.org/10.1016/j.cbi.2009.12.030 ↩︎
  9. Jamin, E. L.; Costantino, R.; Mervant, L.; Martin, J.-F.; Jouanin, I.; Blas-Y-Estrada, F.; Guéraud, F.; Debrauwer, L. Global Profiling of Toxicologically Relevant Metabolites in Urine: Case Study of Reactive Aldehydes. Anal. Chem. 2020, 92 (2), 1746– 1754,  DOI: 10.1021/acs.analchem.9b03146  ↩︎
  10. Y.-C. Chen, M.-N. Zhuang, J.-Y. Hsu, Y.-C. Lin, H.-Y. Wu, P.-C. Liao. Comprehensive Profiling of Human Urinary Mercapturic Acid Conjugates Associated with Exposure to Reactive Chemical Species Using Enzymatic Deacetylation and High-Resolution Mass Spectrometry. Anal. Chem. (2026) https://doi.org/10.1021/acs.analchem.5c08181 ↩︎

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