Download PDF

Adaptive nanopores: A bioinspired label-free approach for protein sequencing and identification

Nano Research volume 14, pages 328–333 (2021)Cite this article

Abstract

Single molecule protein sequencing would tremendously impact in proteomics and human biology and it would promote the development of novel diagnostic and therapeutic approaches. However, its technological realization can only be envisioned, and huge challenges need to be overcome. Major difficulties are inherent to the structure of proteins, which are composed by several different amino-acids. Despite long standing efforts, only few complex techniques, such as Edman degradation, liquid chromatography and mass spectroscopy, make protein sequencing possible. Unfortunately, these techniques present significant limitations in terms of amount of sample required and dynamic range of measurement. It is known that proteins can distinguish closely similar molecules. Moreover, several proteins can work as biological nanopores in order to perform single molecule detection and sequencing. Unfortunately, while DNA sequencing by means of nanopores is demonstrated, very few examples of nanopores able to perform reliable protein-sequencing have been reported so far. Here, we investigate, by means of molecular dynamics simulations, how a re-engineered protein, acting as biological nanopore, can be used to recognize the sequence of a translocating peptide by sensing the “shape” of individual amino-acids. In our simulations we demonstrate that it is possible to discriminate with high fidelity, 9 different amino-acids in a short peptide translocating through the engineered construct. The method, here shown for fluorescence-based sequencing, does not require any labelling of the peptidic analyte. These results can pave the way for a new and highly sensitive method of sequencing.

References

  1. [1]

    Steen, H.; Mann, M. The abc’s (and xyz’s) of peptide sequencing. Nat. Rev. Mol. Cell Biol. 2004, 5, 699–711.

    CAS  Google Scholar 

  2. [2]

    Shimonishi, Y.; Hong, Y. M.; Kitagishi, T.; Matsuo, T.; Matsuda, H.; Katakuse, I. Sequencing of peptide mixtures by edman degradation and field-desorption mass spectrometry. Eur. J. Biochem. 1980, 112, 251–264.

    CAS  Google Scholar 

  3. [3]

    Domon, B.; Aebersold, R. Options and considerations when selecting a quantitative proteomics strategy. Nat. Biotechnol. 2010, 28, 710–721.

    CAS  Google Scholar 

  4. [4]

    Restrepo-Pérez, L.; Joo, C.; Dekker, C. Paving the way to single-molecule protein sequencing. Nat. Nanotechnol. 2018, 13, 786–796.

    Google Scholar 

  5. [5]

    Ameur, A.; Kloosterman, W. P.; Hestand, M. S. Single-molecule sequencing: Towards clinical applications. Trends Biotechnol. 2019, 37, 72–85.

    CAS  Google Scholar 

  6. [6]

    Nivala, J.; Marks, D. B.; Akeson, M. Unfoldase-mediated protein translocation through an α-hemolysin nanopore. Nat. Biotechnol. 2013, 31, 247–250.

    CAS  Google Scholar 

  7. [7]

    Kennedy, E.; Dong, Z. X.; Tennant, C.; Timp, G. Reading the primary structure of a protein with 0.07 nm3 resolution using a subnanometre-diameter pore. Nat. Nanotechnol. 2016, 11, 968–976.

    CAS  Google Scholar 

  8. [8]

    Kolmogorov, M.; Kennedy, E.; Dong, Z. X.; Timp, G.; Pevzner, P. A. Single-molecule protein identification by sub-nanopore sensors. PLoS Comput. Biol. 2017, 13, e1005356.

    Google Scholar 

  9. [9]

    Wilson, J.; Sloman, L.; He, Z. R.; Aksimentiev, A. Graphene nanopores for protein sequencing. Adv. Funct. Mater. 2016, 26, 4830–4838.

    CAS  Google Scholar 

  10. [10]

    Asandei, A.; Rossini, A. E.; Chinappi, M.; Park, Y.; Luchian, T. Protein nanopore-based discrimination between selected neutral amino acids from polypeptides. Langmuir 2017, 33, 14451–14459.

    CAS  Google Scholar 

  11. [11]

    Farimani, A. B.; Heiranian, M.; Aluru, N. R. Identification of amino acids with sensitive nanoporous MoS2: Towards machine learning-based prediction. npj 2D Mater. Appl. 2018, 2, 14.

    Google Scholar 

  12. [12]

    Ohayon, S.; Girsault, A.; Nasser, M.; Shen-Orr, S.; Meller, A. Simulation of single-protein nanopore sensing shows feasibility for whole-proteome identification. PLoS Comput. Biol. 2019, 15, e1007067.

    CAS  Google Scholar 

  13. [13]

    Rosen, C. B.; Rodriguez-Larrea, D.; Bayley, H. Single-molecule site-specific detection of protein phosphorylation with a nanopore. Nat. Biotechnol. 2014, 32, 179–181.

    CAS  Google Scholar 

  14. [14]

    Van Ginkel, J.; Filius, M.; Szczepaniak, M.; Tulinski, P.; Meyer, A. S.; Joo, C. Single-molecule peptide fingerprinting. Proc. Natl. Acad. Sci. USA 2018, 115, 3338–3343.

    CAS  Google Scholar 

  15. [15]

    Zhao, Y. N.; Ashcroft, B.; Zhang, P. M.; Liu, H.; Sen, S. M.; Song, W. S.; Im, J.; Gyarfas, B.; Manna, S.; Biswas, S. et al. Single-molecule spectroscopy of amino acids and peptides by recognition tunnelling. Nat. Nanotechnol. 2014, 9, 466–473.

    CAS  Google Scholar 

  16. [16]

    Ohshiro, T.; Tsutsui, M.; Yokota, K.; Furuhashi, M.; Taniguchi, M.; Kawai, T. Detection of post-translational modifications in single peptides using electron tunnelling currents. Nat. Nanotechnol. 2014, 9, 835–840.

    CAS  Google Scholar 

  17. [17]

    Ouldali, H.; Sarthak, K.; Ensslen, T.; Piguet, F.; Manivet, P.; Pelta, J.; Behrends, J. C.; Aksimentiev, A.; Oukhaled, A. Electrical recognition of the twenty proteinogenic amino acids using an aerolysin nanopore. Nat. Biotechnol. 2020, 38, 176–181.

    CAS  Google Scholar 

  18. [18]

    Swaminathan, J.; Boulgakov, A. A.; Marcotte, E. M. A theoretical justification for single molecule peptide sequencing. PLoS Comput. Biol. 2015, 11, e1004080.

    Google Scholar 

  19. [19]

    Venkatesan, B. M.; Bashir, R. Nanopore sensors for nucleic acid analysis. Nat. Nanotechnol. 2011, 6, 615–624.

    CAS  Google Scholar 

  20. [20]

    Hu, R.; Tong, X.; Zhao, Q. Four aspects about solid-state nanopores for protein sensing: Fabrication, sensitivity, selectivity, and durability. Adv. Healthc Mater., in press, DOI: https://doi.org/10.1002/adhm.202000933.

  21. [21]

    Huang, J. A.; Mousavi, M. Z.; Giovannini, G.; Zhao, Y. Q.; Hubarevich, A.; Soler, M. A.; Rocchia, W.; Garoli, D.; De Angelis, F. Multiplexed discrimination of single amino acid residues in polypeptides in a single SERS hot spot. Angew. Chem., Int. Ed. 2020, 59, 11423–11431.

    CAS  Google Scholar 

  22. [22]

    Sheinerman, F. B.; Norel, R.; Honig, B. Electrostatic aspects of protein-protein interactions. Curr. Opin. Struct. Biol. 2000, 10, 153–159.

    CAS  Google Scholar 

  23. [23]

    Cao, C.; Long, Y. T. Biological nanopores: Confined spaces for electrochemical single-molecule analysis. Acc. Chem. Res. 2018, 51, 331–341.

    CAS  Google Scholar 

  24. [24]

    Lee, B.; Richards, F. M. The interpretation of protein structures: Estimation of static accessibility. J. Mol. Biol. 1971, 55, 379–400, IN3-IN4.

    CAS  Google Scholar 

  25. [25]

    Honig, B.; Nicholls, A. Classical electrostatics in biology and chemistry. Science 1995, 268, 1144–1149.

    CAS  Google Scholar 

  26. [26]

    Allen, M. P.; Tildesley, D. J. Computer Simulation of Liquids; Oxford University Press: Oxford, 2017.

    Google Scholar 

  27. [27]

    Angelucci, F.; Miele, A. E.; Ardini, M.; Boumis, G.; Saccoccia, F.; Bellelli, A. Typical 2-Cys peroxiredoxins in human parasites: Several physiological roles for a potential chemotherapy target. Mol. Biochem. Parasitol. 2016, 206, 2–12.

    CAS  Google Scholar 

  28. [28]

    Wang, H. Y.; Li, Y.; Qin, L. X.; Heyman, A.; Shoseyov, O.; Willner, I.; Long, Y. T.; Tian, H. Single-molecule DNA detection using a novel SP1 protein nanopore. Chem. Commun. 2013, 49, 1741–1743.

    CAS  Google Scholar 

  29. [29]

    Ying, Y. L.; Cao, C.; Long, Y. T. Single molecule analysis by biological nanopore sensors. Analyst 2014, 139, 3826–3835.

    CAS  Google Scholar 

  30. [30]

    Giovannini, G.; Ardini, M.; Maccaferri, N.; Zambrana-Puyalto, X.; Panella, G.; Angelucci, F.; Ippoliti, R.; Garoli, D.; De Angelis, F. Bioassisted tailored synthesis of plasmonic silver nanorings and site-selective deposition on graphene arrays. Adv. Opt. Mater. 2020, 8, 1901583.

    CAS  Google Scholar 

  31. [31]

    Asandei, A.; Chinappi, M.; Lee, J. K.; Seo, C. H.; Mereuta, L.; Park, Y.; Luchian, T. Placement of oppositely charged aminoacids at a polypeptide termini determines the voltage-controlled braking of polymer transport through nanometer-scale pores. Sci. Rep. 2015, 5, 10419.

    CAS  Google Scholar 

  32. [32]

    Restrepo-Pérez, L.; John, S.; Aksimentiev, A.; Joo, C.; Dekker, C. SDS-assisted protein transport through solid-state nanopores. Nanoscale 2017, 9, 11685–11693.

    Google Scholar 

  33. [33]

    Cressiot, B.; Braselmann, E.; Oukhaled, A.; Elcock, A. H.; Pelta, J.; Clark, P. L. Dynamics and energy contributions for transport of unfolded pertactin through a protein nanopore. ACS Nano 2015, 9, 9050–9061.

    CAS  Google Scholar 

  34. [34]

    Chinappi, M.; Luchian, T.; Cecconi, F. Nanopore tweezers: Voltage-controlled trapping and releasing of analytes. Phys. Rev. E 2015, 92, 032714.

    Google Scholar 

  35. [35]

    Pastoriza-Gallego, M.; Breton, M. F.; Discala, F.; Auvray, L.; Betton, J. M.; Pelta, J. Evidence of unfolded protein translocation through a protein nanopore. ACS Nano 2014, 8, 11350–11360.

    CAS  Google Scholar 

  36. [36]

    Kim, H. J.; Choi, U. J.; Kim, H.; Lee, K.; Park, K. B.; Kim, H. M.; Chi, S. W.; Lee, J. S.; Kim, K. B. Translocation of DNA and protein through a sequentially polymerized polyurea nanopore. Nanoscale 2019, 11, 444–453.

    CAS  Google Scholar 

  37. [37]

    Mereuta, L.; Roy, M.; Asandei, A.; Lee, J. K.; Park, Y.; Andricioaei, I.; Luchian, T. Slowing down single-molecule trafficking through a protein nanopore reveals intermediates for peptide translocation. Sci. Rep. 2014, 4, 3885.

    Google Scholar 

  38. [38]

    Plesa, C.; Kowalczyk, S. W.; Zinsmeester, R.; Grosberg, A. Y.; Rabin, Y.; Dekker, C. Fast translocation of proteins through solid state nanopores. Nano Lett. 2013, 13, 658–663.

    CAS  Google Scholar 

  39. [39]

    Rodriguez-Larrea, D.; Bayley, H. Multistep protein unfolding during nanopore translocation. Nat. Nanotechnol. 2013, 8, 288–295.

    CAS  Google Scholar 

  40. [40]

    Ayub, M.; Bayley, H. Engineered transmembrane pores. Curr. Opin. Chem. Biol. 2016, 34, 117–126.

    CAS  Google Scholar 

  41. [41]

    Roy, R.; Hohng, S.; Ha, T. A practical guide to single-molecule FRET. Nat. Methods 2008, 5, 507–516.

    CAS  Google Scholar 

  42. [42]

    Dimura, M.; Peulen, T. O.; Hanke, C. A.; Prakash, A.; Gohlke, H.; Seidel, C. A. M. Quantitative FRET studies and integrative modeling unravel the structure and dynamics of biomolecular systems. Curr. Opin. Struct. Biol. 2016, 40, 163–185.

    CAS  Google Scholar 

  43. [43]

    Hoefling, M.; Grubmüller, H. In silico FRET from simulated dye dynamics. Comput. Phys. Commun. 2013, 184, 841–852.

    CAS  Google Scholar 

Download references

Acknowledgements

The research leading to these results has received funding from the Horizon 2020 Program, FET-Open: PROSEQO, Grant Agreement no. [687089]. We acknowledge PRACE for awarding us access to Marconi at CINECA, Italy.

Author information

Author notes

  1. Andrea Spitaleri and Denis Garoli contributed equally to this work.

Affiliations

  1. CONCEPT Lab, Istituto Italiano di Tecnologia, Via Morego 30, Genova, I-16163, Italy

    Andrea Spitaleri & Walter Rocchia

  2. Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Via Olgettina 58, Milano, I-20132, Italy

    Andrea Spitaleri

  3. Plasmon Nanotechnology Unit, Istituto Italiano di Tecnologia, Via Morego 30, Genova, I-16163, Italy

    Denis Garoli & Francesco De Angelis

  4. AB ANALITICA s.r.l., Via Svizzera 16, I-35127, Padova, Italy

    Denis Garoli

  5. Alacris Theranostics GmbH, Max-Planck-Strasse 3, D-12489, Berlin, Germany

    Moritz Schütte & Hans Lehrach

  6. Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195, Berlin, Germany

    Hans Lehrach

Authors
  1. Andrea Spitaleri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Denis Garoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Moritz Schütte
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hans Lehrach
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Walter Rocchia
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Francesco De Angelis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Walter Rocchia or Francesco De Angelis.

Additional information

Funding note

Open Access funding provided by Istituto Italiano di Tecnologia within the CRUICARE Agreement.

Electronic Supplementary Material

Rights and permissions

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 changes were made.

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/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Spitaleri, A., Garoli, D., Schütte, M. et al. Adaptive nanopores: A bioinspired label-free approach for protein sequencing and identification. Nano Res. 14, 328–333 (2021). https://doi.org/10.1007/s12274-020-3095-z

Download citation

Keywords

  • nanopores
  • single molecule sequencing
  • protein sequencing
  • luorescence resonance energy transfer (FRET)
  • amino-acids
  • fluorescence