Computational assessment of the feasibility of protonation-based protein sequencing

PLoS One. 2020 Sep 11;15(9):e0238625. doi: 10.1371/journal.pone.0238625. eCollection 2020.

Abstract

Recent advances in DNA sequencing methods revolutionized biology by providing highly accurate reads, with high throughput or high read length. These read data are being used in many biological and medical applications. Modern DNA sequencing methods have no equivalent in protein sequencing, severely limiting the widespread application of protein data. Recently, several optical protein sequencing methods have been proposed that rely on the fluorescent labeling of amino acids. Here, we introduce the reprotonation-deprotonation protein sequencing method. Unlike other methods, this proposed technique relies on the measurement of an electrical signal and requires no fluorescent labeling. In reprotonation-deprotonation protein sequencing, the terminal amino acid is identified through its unique protonation signal, and by repeatedly cleaving the terminal amino acids one-by-one, each amino acid in the peptide is measured. By means of simulations, we show that, given a reference database of known proteins, reprotonation-deprotonation sequencing has the potential to correctly identify proteins in a sample. Our simulations provide target values for the signal-to-noise ratios that sensor devices need to attain in order to detect reprotonation-deprotonation events, as well as suitable pH values and required measurement times per amino acid. For instance, an SNR of 10 is required for a 61.71% proteome recovery rate with 100 ms measurement time per amino acid.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acids / chemistry*
  • Amino Acids / genetics
  • Fluorescent Dyes / chemistry
  • Peptides / chemistry
  • Peptides / genetics
  • Proteins / chemistry*
  • Proteins / genetics
  • Proteome / chemistry
  • Proteome / genetics*
  • Protons
  • Sequence Analysis, DNA / methods
  • Sequence Analysis, Protein / methods*
  • Signal-To-Noise Ratio

Substances

  • Amino Acids
  • Fluorescent Dyes
  • Peptides
  • Proteins
  • Proteome
  • Protons

Grants and funding

This work is funded by imec vzw. Giles Miclotte, Koen Martens and Jan Fostier are employees of imec vzw, Belgium; Giles Miclotte and Jan Fostier are employees of Ghent University, Ghent, Belgium. The funder provided support in the form of salaries for authors [GM, KM, JF], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of each author is articulated in the “author contributions” section.