Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore.
Chan CaoPedro MagalhãesLucien F KrappJuan F Bada JuarezSimon Finn MayerVerena RukesAnass ChikiHilal A LashuelMatteo Dal PeraroPublished in: ACS nano (2023)
Protein post-translational modifications (PTMs) play a crucial role in countless biological processes, profoundly modulating protein properties on both spatial and temporal scales. Protein PTMs have also emerged as reliable biomarkers for several diseases. However, only a handful of techniques are available to accurately measure their levels, capture their complexity at a single molecule level, and characterize their multifaceted roles in health and disease. Nanopore sensing provides high sensitivity for the detection of low-abundance proteins, holding the potential to impact single-molecule proteomics and PTM detection, in particular. Here, we demonstrate the ability of a biological nanopore, the pore-forming toxin aerolysin, to detect and distinguish α-synuclein-derived peptides bearing single or multiple PTMs, namely, phosphorylation, nitration, and oxidation occurring at different positions and in various combinations. The characteristic current signatures of the α-synuclein peptide and its PTM variants could be confidently identified by using a deep learning model for signal processing. We further demonstrate that this framework can quantify α-synuclein peptides at picomolar concentrations and detect the C-terminal peptides generated by digestion of full-length α-synuclein. Collectively, our work highlights the advantage of using nanopores as a tool for simultaneous detection of multiple PTMs and facilitates their use in biomarker discovery and diagnostics.
Keyphrases
- single molecule
- deep learning
- amino acid
- living cells
- atomic force microscopy
- label free
- loop mediated isothermal amplification
- protein protein
- real time pcr
- healthcare
- small molecule
- public health
- binding protein
- machine learning
- mental health
- artificial intelligence
- risk assessment
- signaling pathway
- mass spectrometry
- copy number
- genome wide
- dna methylation
- nitric oxide
- human health
- quantum dots
- wastewater treatment