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

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.

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Correspondence to Walter Rocchia or Francesco De Angelis.

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

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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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Keywords

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