Multi-pass, single-molecule nanopore reading of long protein strands

Keisuke Motone, Daphne Kontogiorgos-Heintz, Jasmine Wee, Kyoko Kurihara, Sangbeom Yang, Gwendolin Roote, Oren E. Fox, Yishu Fang, Melissa Queen, Mattias Tolhurst, Nicolas Cardozo, Miten Jain and Jeff Nivala ()
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Keisuke Motone: University of Washington
Daphne Kontogiorgos-Heintz: University of Washington
Jasmine Wee: University of Washington
Kyoko Kurihara: University of Washington
Sangbeom Yang: University of Washington
Gwendolin Roote: University of Washington
Oren E. Fox: University of Washington
Yishu Fang: University of Washington
Melissa Queen: University of Washington
Mattias Tolhurst: University of Washington
Nicolas Cardozo: University of Washington
Miten Jain: Northeastern University
Jeff Nivala: University of Washington

Nature, 2024, vol. 633, issue 8030, 662-669

Abstract: Abstract The ability to sequence single protein molecules in their native, full-length form would enable a more comprehensive understanding of proteomic diversity. Current technologies, however, are limited in achieving this goal1,2. Here, we establish a method for the long-range, single-molecule reading of intact protein strands on a commercial nanopore sensor array. By using the ClpX unfoldase to ratchet proteins through a CsgG nanopore3,4, we provide single-molecule evidence that ClpX translocates substrates in two-residue steps. This mechanism achieves sensitivity to single amino acids on synthetic protein strands hundreds of amino acids in length, enabling the sequencing of combinations of single-amino-acid substitutions and the mapping of post-translational modifications, such as phosphorylation. To enhance classification accuracy further, we demonstrate the ability to reread individual protein molecules multiple times, and we explore the potential for highly accurate protein barcode sequencing. Furthermore, we develop a biophysical model that can simulate raw nanopore signals a priori on the basis of residue volume and charge, enhancing the interpretation of raw signal data. Finally, we apply these methods to examine full-length, folded protein domains for complete end-to-end analysis. These results provide proof of concept for a platform that has the potential to identify and characterize full-length proteoforms at single-molecule resolution.

Date: 2024
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DOI: 10.1038/s41586-024-07935-7

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