Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Nature Communications
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. nature communications
  3. articles
  4. article
Single-cell thiol profiling enabled by live-cell labeling reveals metabolic heterogeneity in ferroptosis
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 03 March 2026

Single-cell thiol profiling enabled by live-cell labeling reveals metabolic heterogeneity in ferroptosis

  • Daiyu Miao  ORCID: orcid.org/0000-0002-6874-94431,
  • Qiuning Li1,
  • Yi Zhang  ORCID: orcid.org/0009-0007-7558-75891,
  • Shaojie Qin1,
  • Ying Wang2,
  • Xiaoyun Liu  ORCID: orcid.org/0000-0001-7083-52632 &
  • …
  • Yu Bai  ORCID: orcid.org/0000-0003-1542-02971 

Nature Communications , Article number:  (2026) Cite this article

  • 4182 Accesses

  • 1 Altmetric

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Cell death
  • Mass spectrometry
  • Metabolomics

Abstract

Thiols serve indispensable biochemical functions across catalysis, redox homeostasis and energy metabolism. However, profiling multiple thiols at the single-cell level remains challenging due to their trace amount and susceptibility to oxidation. Herein, we report an integrated strategy for thiol profiling at the single-cell level which combines live-cell labeling with organic mass cytometry. The live-cell labeling strategy facilitates the comprehensive measurement of intrinsic thiols with expanded coverage and improved sensitivity, while organic mass cytometry enables simultaneous quantification of 27 labeled thiols and 355 other metabolites from single cells. Assessment of metabolic fluctuation upon stimulation demonstrates practicability and accuracy of this integrated methodology which is capable of pathway activity monitoring, metabolic network mapping and untargeted metabolome profiling. Further application of this method in investigating RSL3-triggered ferroptosis reveals that RSL3 inhibits glutathione synthesis via nuclear factor E2-related factor 2- glutathione axis and results in heterogenous glutathione metabolism between subtypes.

Similar content being viewed by others

Charting unknown metabolic reactions by mass spectrometry-resolved stable-isotope tracing metabolomics

Article Open access 31 May 2025

Spatial patterns of hepatocyte glucose flux revealed by stable isotope tracing and multi-scale microscopy

Article Open access 01 July 2025

Spatial isotope deep tracing deciphers inter-tissue metabolic crosstalk

Article Open access 26 August 2025

Data availability

The metabolomic MS raw data have been deposited to MetaboLights with the dataset identifier MTBLS13900. The data that support the findings of this study are available in the supplementary material of this article. Source data are provided with this paper.

Code availability

The code developed in this manuscript has been submitted to Code Ocean59.

References

  1. Ryan, S. K. et al. Microglia ferroptosis is regulated by SEC24B and contributes to neurodegeneration. Nat. Neurosci. 26, 12–26 (2023).

    Google Scholar 

  2. Niemann, B. et al. Oxidative stress and cardiovascular risk: obesity, diabetes, smoking, and pollution: part 3 of a 3-part series. J. Am. Coll. Cardiol. 70, 230–251 (2017).

    Google Scholar 

  3. Hayes, J. D., Dinkova-Kostova, A. T. & Tew, K. D. Oxidative stress in cancer. Cancer Cell 38, 167–197 (2020).

    Google Scholar 

  4. Dixon, S. J. et al. Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell 149, 1060–1072 (2012).

    Google Scholar 

  5. Kang, N. et al. Stimuli-responsive ferroptosis for cancer therapy. Chem. Soc. Rev. 52, 3955–3972 (2023).

    Google Scholar 

  6. Proneth, B. & Conrad, M. Ferroptosis and necroinflammation, a yet poorly explored link. Cell Death Differ. 26, 14–24 (2019).

    Google Scholar 

  7. Fülöp, A. et al. New derivatization reagent for detection of free thiol-groups in metabolites and proteins in matrix-assisted laser desorption/ionization mass spectrometry Imaging. Anal. Chem. 92, 6224–6228 (2020).

    Google Scholar 

  8. Rossi, R. et al. Blood glutathione disulfide: in vivo factor or in vitro artifact? Clin. Chem. 45, 742–753 (2002).

    Google Scholar 

  9. Levison, M. E., Josephson, A. S. & Kirschenbaum, D. M. Reduction of biological substances by water-soluble phosphines: γ-globulin (IgG). Experientia 25, 126–127 (1969).

    Google Scholar 

  10. Winterbourn, C. C. & Hampton, M. B. Thiol chemistry and specificity in redox signaling. Free Radic. Bio. Med. 45, 549–561 (2008).

    Google Scholar 

  11. Yue, Y. K., Huo, F. J. & Yin, C. X. The chronological evolution of small organic molecular fluorescent probes for thiols. Chem. Sci. 12, 1220–1226 (2021).

    Google Scholar 

  12. Huang, T. J., Armbruster, M. R., Coulton, J. B. & Edwards, J. L. Chemical tagging in mass spectrometry for systems biology. Anal. Chem. 91, 109–125 (2019).

    Google Scholar 

  13. Lotto, J. et al. Single-cell transcriptomics reveals early emergence of liver parenchymal and non-parenchymal cell lineages. Cell 183, 702–716 (2020).

    Google Scholar 

  14. Altschuler, S. J. & Wu, L. F. Cellular heterogeneity: do differences make a difference? Cell 141, 559–563 (2010).

    Google Scholar 

  15. Li, Z. et al. Single-cell lipidomics with high structural specificity by mass spectrometry. Nat. Commun. 12, 2869 (2021).

    Google Scholar 

  16. Zhu, H. Y. et al. Metabolomic profiling of single enlarged lysosomes. Nat. Methods 18, 788–798 (2021).

    Google Scholar 

  17. Lombard-Banek, C. et al. In vivo subcellular mass spectrometry enables proteo-metabolomic single-cell systems biology in a chordate embryo developing to a normally behaving tadpole (X. laevis). Angew. Chem. Int. Ed. 60, 12852–12858 (2021).

    Google Scholar 

  18. Passarelli, M. K. et al. The 3D OrbiSIMS-label-free metabolic imaging with subcellular lateral resolution and high mass-resolving power. Nat. Methods 14, 1175–1183 (2017).

    Google Scholar 

  19. Yin, R. C. et al. High spatial resolution imaging of mouse pancreatic islets using nanospray desorption electrospray ionization mass spectrometry. Anal. Chem. 90, 6548–6555 (2018).

    Google Scholar 

  20. Castro, D. C., Xie, Y. R., Rubakhin, S. S., Romanova, E. V. & Sweedler, J. V. Image-guided MALDI mass spectrometry for high-throughput single-organelle characterization. Nat. Methods 18, 1233–1238 (2021).

    Google Scholar 

  21. Liu, Q. L. et al. High-throughput single-cell mass spectrometry reveals abnormal lipid metabolism in pancreatic ductal adenocarcinoma. Angew. Chem. Int. Ed. 60, 24534–24542 (2021).

    Google Scholar 

  22. Shen, Z. et al. Dynamic metabolic change of cancer cells induced by natural killer cells at the single-cell level studied by label-free mass cytometry. Chem. Sci. 13, 1641–1647 (2022).

    Google Scholar 

  23. Spitzer, M. H. & Nolan, G. P. Mass cytometry: single cells, many features. Cell 165, 780–791 (2016).

    Google Scholar 

  24. Yao, H. et al. Label-free mass cytometry for unveiling cellular metabolic heterogeneity. Anal. Chem. 91, 9777–9783 (2019).

    Google Scholar 

  25. Xu, S. T., Liu, M. X., Bai, Y. & Liu, H. W. Multi-dimensional organic mass cytometry: simultaneous analysis of proteins and metabolites on single cells. Angew. Chem. Int. Ed. 60, 1806–1812 (2021).

    Google Scholar 

  26. Qin, S. J. et al. In-depth organic mass cytometry reveals differential contents of 3-hydroxybutanoic acid at the single-cell level. Nat. Commun. 15, 4387 (2024).

    Google Scholar 

  27. Zhang, Y. et al. Dynamic single-cell metabolomics reveals cell-cell interaction between tumor cells and macrophages. Nat. Commun. 16, 4582 (2025).

  28. Huo, F. J. et al. Colorimetric detection of thiols using a chromene molecule. Org. Lett. 11, 4918–4921 (2009).

    Google Scholar 

  29. Huo, F. J. et al. Chromene “lock”, thiol “key”, and mercury(ii) ion “hand”: a single molecular machine recognition system. Org. Lett. 12, 4756–4759 (2010).

    Google Scholar 

  30. Yang, Y. T. et al. Thiol-chromene “click” reaction triggered self-immolative for mr visualization of thiol flux in physiology and pathology of living cells and mice. J. Am. Chem. Soc. 142, 1614–1620 (2020).

    Google Scholar 

  31. Meister, A. & Anderson, M. E. Glutathione. Annu. Rev. Biochem. 52, 711–760 (1983).

    Google Scholar 

  32. Wang, L. F. et al. Fluorescent probes and mass spectrometry-based methods to quantify thiols in biological systems. Antioxid. Redox Sign. 36, 354–365 (2022).

    Google Scholar 

  33. Kemna, E. W. M. et al. High-yield cell ordering and deterministic cell-in-droplet encapsulation using Dean flow in a curved microchannel. Lab Chip 12, 2881–2887 (2012).

    Google Scholar 

  34. Shao, Y. L. et al. Intact living-cell electrolaunching ionization mass spectrometry for single-cell metabolomics. Chem. Sci. 13, 8065–8073 (2022).

    Google Scholar 

  35. Zhong, K. L. et al. A colorimetric and NIR fluorescent probe for ultrafast detecting bisulfite and organic amines and its applications in food, imaging, and monitoring fish freshness. Food Chem. 438, 137987 (2024).

    Google Scholar 

  36. Katoh, M., Hiratake, J., Kato, H. & Oda, J. Mechanism-based inactivation of E-coli gamma-glutamylcysteine synthetase by phosphinic acid- and sulfoximine-based transition-state analogues. Bioorg. Med. Chem. Lett. 6, 1437–1442 (1996).

    Google Scholar 

  37. Söhretoglu, D., Baran, M. Y., Arroo, R. & Kuruüzüm-Uz, A. Recent advances in chemistry, therapeutic properties and sources of polydatin. Phytochem. Rev. 17, 973–1005 (2018).

    Google Scholar 

  38. Chen, P. et al. High-throughput screening suggests glutathione synthetase as an anti-tumor target of polydatin using human proteome chip. Int. J. Biol. Macromol. 161, 1230–1239 (2020).

    Google Scholar 

  39. Mele, L. et al. A new inhibitor of glucose-6-phosphate dehydrogenase blocks pentose phosphate pathway and suppresses malignant proliferation and metastasis in vivo. Cell Death Dis. 9, 572 (2018).

    Google Scholar 

  40. Li, R. P. et al. Polydatin protects learning and memory impairments in a rat model of vascular dementia. Phytomedicine 19, 677–681 (2012).

    Google Scholar 

  41. Ravagnan, G. et al. Polydatin, a natural precursor of resveratrol, Induces β-defensin oroduction and reduces inflammatory response. Inflammation 36, 26–34 (2013).

    Google Scholar 

  42. Yang, W. S. et al. Regulation of ferroptotic cancer cell death by GPX4. Cell 156, 317–331 (2014).

    Google Scholar 

  43. Tonelli, C., Chio, I. I. C. & Tuveson, D. A. Transcriptional regulation by Nrf2. Antioxid. Redox Sign. 29, 1727–1745 (2018).

    Google Scholar 

  44. Namgaladze, D., Fuhrmann, D. C. & Brüne, B. Interplay of Nrf2 and BACH1 in inducing ferroportin expression and enhancing resistance of human macrophages towards ferroptosis. Cell Death Discov. 8, 327 (2022).

    Google Scholar 

  45. Yang, J. W. et al. Cetuximab promotes RSL3-induced ferroptosis by suppressing the Nrf2/HO-1 signalling pathway in KRAS mutant colorectal cancer. Cell Death Dis. 12, 1079 (2021).

    Google Scholar 

  46. Shin, D., Kim, E. H., Lee, J. & Roh, J. L. Nrf2 inhibition reverses resistance to GPX4 inhibitor-induced ferroptosis in head and neck cancer. Free Radic. Biol. Med. 129, 454–462 (2018).

    Google Scholar 

  47. Benjamin, D. I. et al. Multiomics reveals glutathione metabolism as a driver of bimodality during stem cell aging. Cell Metab. 35, 472–486 (2023).

    Google Scholar 

  48. Lu, H. Y., Zhang, H. & Li, L. J. Chemical tagging mass spectrometry: an approach for single-cell omics. Anal. Bioanal. Chem. 415, 6901–6913 (2023).

    Google Scholar 

  49. Patti, G. J., Yanes, O. & Siuzdak, G. Metabolomics: the apogee of the omics trilogy. Nat. Rev. Mol. Cell Biol. 13, 263–269 (2012).

    Google Scholar 

  50. Meng, C. J. et al. The deubiquitinase USP11 regulates cell proliferation and ferroptotic cell death via stabilization of NRF2 USP11 deubiquitinates and stabilizes NRF2. Oncogene 40, 1706–1720 (2021).

    Google Scholar 

  51. Zhang, W. L. et al. The RSL3 induction of lung adenocarcinoma cell ferroptosis by inhibition of USP11 activity and the NRF2-GSH axis. Cancers 14, 5233 (2022).

    Google Scholar 

  52. Chen, X. et al. SIRT1 activated by AROS sensitizes glioma cells to ferroptosis via induction of NAD plus depletion-dependent activation of ATF3. Redox Biol. 69, 103030 (2024).

    Google Scholar 

  53. Fu, X., Wu, H. S., Li, C. J., Deng, G. & Chen, C. YAP1 inhibits RSL3-induced castration-resistant prostate cancer cell ferroptosis by driving glutamine uptake and metabolism to GSH. Mol. Cell. Biochem. 479, 2415–2427 (2024).

    Google Scholar 

  54. Wang, L. L., Mai, Y. Z., Zheng, M. H., Yan, G. H. & Jin, J. Y. A single fluorescent probe to examine the dynamics of mitochondria-lysosome interplay and extracellular vesicle role in ferroptosis. Dev. Cell 59, 517–528 (2024).

    Google Scholar 

  55. Li, P. Y. et al. Inhibition of cannabinoid receptor type 1 sensitizes triple-negative breast cancer cells to ferroptosis via regulating fatty acid metabolism. Cell Death Dis. 13, 808 (2022).

    Google Scholar 

  56. Shui, S. F., Zhao, Z. L., Wang, H., Conrad, M. & Liu, G. Q. Non-enzymatic lipid peroxidation initiated by photodynamic therapy drives a distinct ferroptosis-like cell death pathway. Redox Biol. 45, 102056 (2021).

    Google Scholar 

  57. Jiang, Y. Z. et al. Genomic and transcriptomic landscape of triple-negative breast cancers: subtypes and treatment strategies. Cancer Cell 35, 428–440 (2019).

    Google Scholar 

  58. Yang, F. et al. Ferroptosis heterogeneity in triple-negative breast cancer reveals an innovative immunotherapy combination strategy. Cell Metab. 35, 84–100 (2022).

    Google Scholar 

  59. Miao, D. Y. & Bai, Y. Single-cell thiol profiling enabled by live-cell labeling reveals metabolic heterogeneity in ferroptosis. Code Ocean. https://doi.org/10.24433/CO.9501996.v9501991 (2026).

Download references

Acknowledgements

This work was financially supported by the Natural Science Foundation of China (No. 22125401 to Y.B.) and the National Key R&D Program of China (2022YFC3400700 and 2023YFF1205900 to Y.B.).

Author information

Authors and Affiliations

  1. Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, China

    Daiyu Miao, Qiuning Li, Yi Zhang, Shaojie Qin & Yu Bai

  2. Department of Microbiology and Infectious Disease Center, NHC Key Laboratory of Medical Immunology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China

    Ying Wang & Xiaoyun Liu

Authors
  1. Daiyu Miao
    View author publications

    Search author on:PubMed Google Scholar

  2. Qiuning Li
    View author publications

    Search author on:PubMed Google Scholar

  3. Yi Zhang
    View author publications

    Search author on:PubMed Google Scholar

  4. Shaojie Qin
    View author publications

    Search author on:PubMed Google Scholar

  5. Ying Wang
    View author publications

    Search author on:PubMed Google Scholar

  6. Xiaoyun Liu
    View author publications

    Search author on:PubMed Google Scholar

  7. Yu Bai
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Y.B. proposed the study concept and strategy. D.M. designed and performed the experiments and data analysis. Q.L. assisted with the data analysis of untargeted metabolome library. Y.Z. involved in the construction of organic mass cytometry. Y.W. and X.L. helped with the western blot experiments. Y.Z. and S.Q. involved in the discussion. D.M., Q.L., Y.Z., S.Q. and Y.B. wrote the manuscript.

Corresponding author

Correspondence to Yu Bai.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Communications thanks Rosario M. Sanchez-Martin, who co-reviewed with Victoria Cano-Cortés, Tong Zhang, and the other anonymous reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information (download PDF )

Description of Additional Supplementary Information (download PDF )

Supplementary Data 1 (download XLSX )

Supplementary Data 2 (download XLSX )

Supplementary Data 3 (download XLSX )

Reporting Summary (download PDF )

Transparent Peer Review file (download PDF )

Source data

Source Data (download XLSX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Miao, D., Li, Q., Zhang, Y. et al. Single-cell thiol profiling enabled by live-cell labeling reveals metabolic heterogeneity in ferroptosis. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70336-z

Download citation

  • Received: 31 July 2025

  • Accepted: 25 February 2026

  • Published: 03 March 2026

  • DOI: https://doi.org/10.1038/s41467-026-70336-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Download PDF

Advertisement

Explore content

  • Research articles
  • Reviews & Analysis
  • News & Comment
  • Videos
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • Aims & Scope
  • Editors
  • Journal Information
  • Open Access Fees and Funding
  • Calls for Papers
  • Editorial Values Statement
  • Journal Metrics
  • Editors' Highlights
  • Contact
  • Editorial policies
  • Top Articles

Publish with us

  • For authors
  • For Reviewers
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Nature Communications (Nat Commun)

ISSN 2041-1723 (online)

nature.com footer links

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research