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Adaptive nanopores: A bioinspired label-free approach for protein sequencing and identification
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  • Research Article
  • Open Access
  • Published: 30 September 2020

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

  • Andrea Spitaleri1,2 na1,
  • Denis Garoli3,4 na1,
  • Moritz Schütte5,
  • Hans Lehrach5,6,
  • Walter Rocchia1 &
  • …
  • Francesco De Angelis3 

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

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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.

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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.

Authors and 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
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  2. Denis Garoli
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  6. Francesco De Angelis
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Corresponding authors

Correspondence to Walter Rocchia or Francesco De Angelis.

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Funding note

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

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

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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

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  • Received: 02 June 2020

  • Revised: 30 August 2020

  • Accepted: 03 September 2020

  • Published: 30 September 2020

  • Issue Date: January 2021

  • DOI: https://doi.org/10.1007/s12274-020-3095-z

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Keywords

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