CoChat
Sign Up
Cited by 30Advanced Fluorescence Microscopy TechniquesAdvanced biosensing and bioanalysis techniquesProtein Structure and Dynamics

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Full-length single-molecule protein fingerprinting

Open access
Filius, Mike, van Wee, Raman, de Lannoy, Carlos, Westerlaken, Ilja, Li, Zeshi, Kim, Sung Hyun, de Agrela Pinto, Cecilia, Wu, Yunfei, Boons, Geert-Jan, Pabst, Martin, de Ridder, Dick, Joo, Chirlmin·2024·Nature Nanotechnology
DOI 10.1038/s41565-023-01598-7

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Proteins are the primary functional actors of the cell. While proteoform diversity is known to be highly biologically relevant, current protein analysis methods are of limited use for distinguishing proteoforms. Mass spectrometric methods, in particular, often provide only ambiguous information on post-translational modification sites, and sequences of co-existing modifications may not be resolved. Here we demonstrate fluorescence resonance energy transfer (FRET)-based single-molecule protein fingerprinting to map the location of individual amino acids and post-translational modifications within single full-length protein molecules. Our data show that both intrinsically disordered proteins and folded globular proteins can be fingerprinted with a subnanometer resolution, achieved by probing the amino acids one by one using single-molecule FRET via DNA exchange. This capability was demonstrated through the analysis of alpha-synuclein, an intrinsically disordered protein, by accurately quantifying isoforms in mixtures using a machine learning classifier, and by determining the locations of two O-GlcNAc moieties. Furthermore, we demonstrate fingerprinting of the globular proteins Bcl-2-like protein 1, procalcitonin and S100A9. We anticipate that our ability to perform proteoform identification with the ultimate sensitivity may unlock exciting new venues in proteomics research and biomarker-based diagnosis.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41565-023-01598-7

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 55

  1. Kim, H. K., Pham, M. H. C., Ko, K. S., Rhee, B. D. & Han, J. Alternative splicing isoforms in health and disease. Pflügers Arch. 470, 995–1016 (2018). · DOI
  2. Paronetto, M. P., Passacantilli, I. & Sette, C. Alternative splicing and cell survival: from tissue homeostasis to disease. Cell Death Differ. 23, 1919–1929 (2016). · DOI
  3. Lin, H. & Caroll, K. S. Introduction: posttranslational protein modification. Chem. Rev. 118, 887–888 (2018). · DOI
  4. Carbonara, K., Andonovski, M. & Coorssen, J. R. Proteomes are of proteoforms: embracing the complexity. Proteomes 9, 38 (2021). · DOI
  5. Benson, M. D., Ngo, D., Ganz, P. & Gerszten, R. E. Emerging affinity reagents for high throughput proteomics: trust, but verify. Circulation 140, 1610–1612 (2019). · DOI
  6. Čaval, T., Tian, W., Yang, Z., Clausen, H. & Heck, A. J. R. Direct quality control of glycoengineered erythropoietin variants. Nat. Commun. 9, 3342 (2018). · DOI
  7. Wang, Y., Zhao, Y., Bollas, A., Wang, Y. & Au, K. F. Nanopore sequencing technology, bioinformatics and applications. Nat. Biotechnol. 39, 1348–1365 (2021). · DOI
  8. Ardui, S., Ameur, A., Vermeesch, J. R. & Hestand, M. S. Single molecule real-time (SMRT) sequencing comes of age: applications and utilities for medical diagnostics. Nucleic Acids Res. 46, 2159–2168 (2018). · DOI
  9. Restrepo-Pérez, L., Joo, C. & Dekker, C. Paving the way to single-molecule protein sequencing. Nat. Nanotechnol. 13, 786–796 (2018). · DOI
  10. Alfaro, J. A. et al. The emerging landscape of single-molecule protein sequencing technologies. Nat. Methods 18, 604–617 (2021). · DOI
  11. Floyd, B. M. & Marcotte, E. M. Protein sequencing, one molecule at a time. Annu. Rev. Biophys. 51, 181–200 (2022). · DOI
  12. Timp, W. & Timp, G. Beyond mass spectrometry, the next step in proteomics. Sci. Adv. 6, eaax8978 (2020). · DOI
  13. Swaminathan, J., Boulgakov, A. A. & Marcotte, E. M. A theoretical justification for single molecule peptide sequencing. PLoS Comput. Biol. 11, e1004080 (2015). · DOI
  14. Rodriques, S. G., Marblestone, A. H. & Boyden, E. S. A theoretical analysis of single molecule protein sequencing via weak binding spectra. PLoS ONE 14, e0212868 (2019). · DOI
  15. Yao, Y., Docter, M., Van Ginkel, J., De Ridder, D. & Joo, C. Single-molecule protein sequencing through fingerprinting: computational assessment. Phys. Biol. 12, 10–16 (2015). · DOI
  16. de Lannoy, C. V. et al. Evaluation of FRET X for single-molecule protein fingerprinting. iScience 24, 103239 (2021). · DOI · Paper page
  17. Yu, L. et al. Unidirectional single-file transport of full-length proteins through a nanopore. Nat. Biotechnol. 41, 1130–1139 (2023). · DOI
  18. van Ginkel, J. et al. Single-molecule peptide fingerprinting. Proc. Natl Acad. Sci. USA 115, 3338–3343 (2018). · DOI
  19. Swaminathan, J. et al. Highly parallel single-molecule identification of proteins in zeptomole-scale mixtures. Nat. Biotechnol. 36, 1076–1082 (2018). · DOI
  20. Shrestha, P. et al. Single-molecule mechanical fingerprinting with DNA nanoswitch calipers. Nat. Nanotechnol. 16, 1362–1370 (2021). · DOI
  21. Filius, M., Kim, S. H., Severins, I. & Joo, C. High-resolution single-molecule FRET via DNA exchange (FRET X). Nano Lett. 21, 3295–3301 (2021). · DOI
  22. Filius, M., van Wee, R. & Joo, C. in Single Molecule Analysis: Methods and Protocols (eds Heller, I. et al.) 203–213 (Springer, 2024). · DOI
  23. Van Wee, R., Filius, M. & Joo, C. Completing the canvas: advances and challenges for DNA-PAINT super-resolution imaging. Trends Biochem. Sci. 11, 918–930 (2021). · DOI
  24. Schnitzbauer, J., Strauss, M. T., Schlichthaerle, T., Schueder, F. & Jungmann, R. Super-resolution microscopy with DNA-PAINT. Nat. Protoc. 12, 1198–1228 (2017). · DOI · Paper page
  25. Shi, X. et al. Quantitative fluorescence labeling of aldehyde-tagged proteins for single-molecule imaging. Nat. Methods 9, 499–503 (2012). · DOI
  26. Schuler, B. & Hofmann, H. Single-molecule spectroscopy of protein folding dynamics—expanding scope and timescales. Curr. Opin. Struct. Biol. 23, 36–47 (2013). · DOI
  27. Yang, X. & Qian, K. Protein O-GlcNAcylation: emerging mechanisms and functions. Nat. Rev. Mol. Cell Biol. 18, 452–465 (2017). · DOI
  28. Vellosillo, P. & Minguez, P. A global map of associations between types of protein posttranslational modifications and human genetic diseases. iScience 24, 102917 (2021). · DOI
  29. Mauri, T. et al. O-GlcNAcylation prediction: an unattained objective. Adv. Appl. Bioinform. Chem. 14, 87–102 (2021). · DOI
  30. Shi, J., Ruijtenbeek, R. & Pieters, R. J. Demystifying O-GlcNAcylation: hints from peptide substrates. Glycobiology 28, 814–824 (2018). · DOI
  31. Shen, D. L. et al. Catalytic promiscuity of O-GlcNAc transferase enables unexpected metabolic engineering of cytoplasmic proteins with 2-azido-2-deoxy-glucose. ACS Chem. Biol. 12, 206–213 (2017). · DOI
  32. Mayer, A., Gloster, T. M., Chou, W. K., Vocadlo, D. J. & Tanner, M. E. 6′-Azido-6′-deoxy-UDP-N-acetylglucosamine as a glycosyltransferase substrate. Bioorg. Med. Chem. Lett. 21, 1199–1201 (2011). · DOI
  33. Macdonald, J. I., Munch, H. K., Moore, T. & Francis, M. B. One-step site-specific modification of native proteins with 2-pyridinecarboxyaldehydes. Nat. Chem. Biol. 11, 326–331 (2015). · DOI
  34. Vijayan, A. L. et al. Procalcitonin: a promising diagnostic marker for sepsis and antibiotic therapy. J. Intensive Care 5, 51 (2017). · DOI · Paper page
  35. Senior, A. W. et al. Improved protein structure prediction using potentials from deep learning. Nature 577, 706–710 (2020). · DOI · Paper page
  36. Jungmann, R. et al. Multiplexed 3D cellular super-resolution imaging with DNA-PAINT and Exchange-PAINT. Nat. Methods 11, 313–318 (2014). · DOI
  37. Erickson, H. P. Size and shape of protein molecules at the nanometer level determined by sedimentation, gel filtration, and electron microscopy. Biol. Proced. Online 11, 32–51 (2009). · DOI · Paper page
  38. Ree, R., Varland, S. & Arnesen, T. Spotlight on protein N-terminal acetylation. Exp. Mol. Med. 50, 1–13 (2018). · DOI
  39. Bloom, S. et al. Decarboxylative alkylation for site-selective bioconjugation of native proteins via oxidation potentials. Nat. Chem. 10, 205–211 (2018). · DOI
  40. Ramirez, D. H. et al. Engineering a proximity-directed O-GlcNAc transferase for selective protein O-GlcNAcylation in cells. ACS Chem. Biol. 15, 1059–1066 (2020). · DOI
  41. Yang, Y.-Y., Ascano, J. M. & Hang, H. C. Bioorthogonal chemical reporters for monitoring protein acetylation. J. Am. Chem. Soc. 132, 3640–3641 (2010). · DOI
  42. Westcott, N. P., Fernandez, J. P., Molina, H. & Hang, H. C. Chemical proteomics reveals ADP-ribosylation of small GTPases during oxidative stress. Nat. Chem. Biol. 13, 302–308 (2017). · DOI
  43. Rabuka, D., Hubbard, S. C., Laughlin, S. T., Argade, S. P. & Bertozzi, C. R. A chemical reporter strategy to probe glycoprotein fucosylation. J. Am. Chem. Soc. 128, 12078–12079 (2006). · DOI
  44. Boeggeman, E. et al. Direct identification of nonreducing GlcNAc residues on N-glycans of glycoproteins using a novel chemoenzymatic method. Bioconjugate Chem. 18, 806–814 (2007). · DOI
  45. van Geel, R. et al. Chemoenzymatic conjugation of toxic payloads to the globally conserved N-glycan of native mAbs provides homogeneous and highly efficacious antibody–drug conjugates. Bioconjugate Chem. 26, 2233–2242 (2015). · DOI
  46. Tate, E. W., Kalesh, K. A., Lanyon-Hogg, T., Storck, E. M. & Thinon, E. Global profiling of protein lipidation using chemical proteomic technologies. Curr. Opin. Chem. Biol. 24, 48–57 (2015). · DOI
  47. Anderson, N. L. & Anderson, N. G. The human plasma proteome: history, character, and diagnostic prospects. Mol. Cell. Proteom. 1, 845–867 (2002). · DOI · Paper page
  48. Han, X., Aslanian, A. & Yates, J. R. Mass spectrometry for proteomics. Curr. Opin. Chem. Biol. 12, 483–490 (2008). · DOI
  49. Filius, M. et al. High-speed super-resolution imaging using protein-assisted DNA-PAINT. Nano Lett. 20, 2264–2270 (2020). · DOI
  50. Kim, S. H., Kim, H., Jeong, H. & Yoon, T. Y. Encoding multiple virtual signals in DNA barcodes with single-molecule FRET. Nano Lett. 21, 1694–1701 (2021). · DOI
  51. McCann, J. J., Choi, U. B., Zheng, L., Weninger, K. & Bowen, M. E. Optimizing methods to recover absolute FRET efficiency from immobilized single molecules. Biophys. J. 99, 961–970 (2010). · DOI
  52. Cristianini, N. & Shawe-Taylor, J. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods (Cambridge University Press, 2000). · DOI · Paper page
  53. Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
  54. Pabst, M. et al. A general approach to explore prokaryotic protein glycosylation reveals the unique surface layer modulation of an anammox bacterium. ISME J. 16, 346–357 (2022). · DOI
  55. Chuh, K. N., Zaro, B. W., Piller, F., Piller, V. & Pratt, M. R. Changes in metabolic chemical reporter structure yield a selective probe of O-GlcNAc modification. J. Am. Chem. Soc. 136, 12283–12295 (2014). · DOI

Metadata

Authors
Filius, M., van Wee, R., de Lannoy, C., Westerlaken, I., Li, Z., Kim, S. H., de Agrela Pinto, C., Wu, Y., Boons, G.-J., Pabst, M., de Ridder, D., & Joo, C.
Affiliations
  • Delft University of Technology (NL)
  • Wageningen University & Research (NL)
  • Ewha Womans University (KR)
  • Utrecht University (NL)
Corresponding author
Joo, Chirlmin
ORCID
Venue
Nature Nanotechnology
Publisher
Springer Science and Business Media LLC
Published
2024-02-13
Volume
19
Issue
5
Pages
652-659
ISSN
  • 1748-3387 (ISSN-L)
  • 1748-3395
DOI
10.1038/s41565-023-01598-7
OpenAlex
W4391779771
Cited by
30
References
6
Citations by year
2026: 9 · 2025: 13 · 2024: 8
FWCI
5.80
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Nanotechnology (publishedVersion)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (submittedVersion)
Funders
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek (SMPS, Vici, SMPS3)
  • National Research Foundation of Korea
  • Chinese Scholarship Council (CSC) Grant
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Keywords
fluorescence resonance energy transfer, post-translational modification, proteoforms, intrinsically disordered proteins, alpha-synuclein, O-GlcNAc, isoform quantification, procalcitonin, S100A9
MeSH terms
Machine Learning, Single Molecule Imaging, Humans, Peptide Mapping, Protein Processing, Post-Translational, Fluorescence Resonance Energy Transfer, alpha-Synuclein, Intrinsically Disordered Proteins

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review