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.

Not if but when nanopore protein sequencing meets single-cell proteomics

Nature Methods volume 20, pages 336–338 (2023)Cite this article

Subjects

The nanopore community is stepping toward a new frontier of single-molecule protein sequencing. Here, we offer our opinions on the unique potential for this emerging technology, with a focus on single-cell proteomics, and some challenges that must be overcome to realize it.

Compared to sequencing-by-synthesis technologies, the benefits of nanopore nucleic acid sequencing include long (or full-length) reads of single molecules, the ability to directly sequence epigenetic marks and RNA, and the delivery of real-time data streams from inexpensive, portable devices1. These features have contributed to impacts ranging from ultra-rapid whole-genome diagnostics in the clinic2 and genomic epidemiology in the field3 to the first complete, telomere-to-telomere sequence of the human genome4. Insights are also extending into single-cell biology. For instance, full-length RNA nanopore reads have enabled isoform-level characterization of transcripts within individual cells5.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Single-cell nanopore proteomics with highly multiplexable peptide sequence-based barcoding and highly parallel nanopore instruments.

References

  1. Jain, M., Olsen, H. E., Paten, B. & Akeson, M. Genome Biol. https://doi.org/10.1186/s13059-016-1103-0 (2016).

  2. Gorzynski, J. E. et al. N. Engl. J. Med. 386, 700–702 (2022).

    Article  PubMed  Google Scholar 

  3. Quick, J. et al. Nature 530, 228–232 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Nurk, S. et al. Science 376, 44–53 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Tian, L. et al. Genome Biol. 22, 310 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Hu, Z. L., Huo, M. Z., Ying, Y. L. & Long, Y. T. Angew. Chem. Int. Ed. Engl. 60, 14738–14749 (2021).

    Article  CAS  PubMed  Google Scholar 

  7. Nivala, J., Marks, D. B. & Akeson, M. Nat. Biotechnol. 31, 247–250 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Nivala, J., Mulroney, L., Li, G., Schreiber, J. & Akeson, M. ACS Nano 8, 12365–12375 (2014).

    Article  CAS  PubMed  Google Scholar 

  9. Zhang, S. et al. Nat. Chem 13, 1192–1199 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Brinkerhoff, H., Kang, A. S. W., Liu, J., Aksimentiev, A. & Dekker, C. Science 374, 1509–1513 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yan, S. et al. Nanÿo Lett 21, 6703–6710 (2021).

    Article  CAS  Google Scholar 

  12. Chen, Z. et al. Chem. Sci. (Camb.) 12, 15750–15756 (2021).

    Article  CAS  Google Scholar 

  13. Yu, L. et al. Nat. Biotechnol. https://doi.org/10.1038/s41587-022-01598-3 (2023).

  14. Timp, W. & Timp, G. Sci. Adv. https://doi.org/10.1126/sciadv.aax8978 (2020).

  15. Slavov, N. J. Proteome Res. 20, 4915–4918 (2021).

    Article  CAS  Google Scholar 

  16. Alfaro, J. A. et al. Nat. Methods 18, 604–617 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Howes, L. Chem. Eng. News https://doi.org/10.47287/cen-10003-cover (2022).

  18. Xie, P., Xiong, Q., Fang, Y., Qing, Q. & Lieber, C. M. Nat. Nanotechnol 7, 119–125 (2012).

    Article  CAS  Google Scholar 

  19. Li, J. et al. Nat. Methods 17, 399–404 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kennedy, E. et al. Nano Lett. 18, 4263–4272 (2018).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

K.M. is supported by awards from the Japan Agency for Medical Research and Development (AMED) and the Japan Society for the Promotion of Science (JSPS). We thank Ying Zhu (Genentech) for feedback on this piece. We also thank BioRender for helping create the figure.

Author information

Authors and Affiliations

  1. Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA

    Keisuke Motone & Jeff Nivala

  2. Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA

    Jeff Nivala

Authors
  1. Keisuke Motone
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jeff Nivala
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeff Nivala.

Ethics declarations

Competing interests

J.N. is a consultant to Oxford Nanopore Technologies. K.M. declares no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Motone, K., Nivala, J. Not if but when nanopore protein sequencing meets single-cell proteomics. Nat Methods 20, 336–338 (2023). https://doi.org/10.1038/s41592-023-01800-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-023-01800-7

Search

Advanced search

Quick links

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