Periodic Reporting for period 3 - NanoProt-ID (Proteome profiling using plasmonic nanopore sensors)
Berichtszeitraum: 2022-08-01 bis 2024-01-31
The overall scientific objectives of NanoProt-ID are to develop a new type of protein identification method, based on ultra-sensitive nanotechnologies. The method includes five main layers: 1) Demonstration of the ability to fluorescently label specific amino-acids in proteins with high yield. 2) The ability to separate and image individual proteins according to their mass, prior to nanopore-based sensing. 3) The construction of an ultra-sensitive apparatus, integrating advanced electro-optical sensing in the nanopore system. 4) Fabrication of solid-state nanopore devices for electro-optical sensing of individual proteins. 5) Development of sophisticated artificial intelligence signal analysis algorithm for protein identification.
The technologies developed in the context of NanoProt-ID will directly impact basic research capabilities, by providing new ways to analyze cellular heterogeneity and single cell proteomics. In a parallel way to which next generation DNA sequencing (NGS) technologies have transformed basic research in life sciences in the past 20 years, and are routinely used for clinical diagnostics and precision medicine, it is expected that single molecule proteomics will impact society to even larger extent. In fact, emerging Single Molecule Proteomics methods are directly applicable for clinical protein biomarker classification for precision medicine and precision diagnostics.
1) We have improved and implemented the amino-acids (protein) labelling chemistries using multiple fluorophore conjugates.
2) Developed a novel way to fabricate sub 5 nm solid-state nanopores, in-situ, using a tightly focused laser drilling technology and demonstrated the ability of these nanopores to sense single biomolecules.
3) We have demonstrated the ability to sense individual proteins in PAGE-SDS-filled nano channels in order to separate single proteins by mass prior to their sensing.
4) We have performed numerical simulations shown that plasmonic nanopores made from simple metal nano-rings can provide sufficient light enhancement to enable single protein identification.
5) We developed a Convolutional Neural Network based AI algorithm for the accurate identification of proteins as the translocate through solid-state nanopores, labelled only in three amino-acids.
6) We have designed, constructed and validated a custom apparatus for high-resolution optical sensing of solid-state nanopores in multiple excitation/emission wavelengths.
A recent Perpective Review paper on this field has been published in Nature Methods. It can be freely accessed here:
https://www.nature.com/articles/s41592-021-01143-1.epdf?sharing_token=U2brURic6A6-XKGszhyzL9RgN0jAjWel9jnR3ZoTv0PTwIpACT_avaqY1Te013vQ4WOdIPR3iLEbJA3AkhLYin90-WTGc1b7URaPp5PWhYi9Lx2CjWvljvTxSS45rKJ9KSWQehq-uQr5zKhAUi7Tj3gBM0PvdS4k3iOMiws6i8c%3D