Periodic Reporting for period 4 - NanoProt-ID (Proteome profiling using plasmonic nanopore sensors)
Reporting period: 2024-02-01 to 2024-07-31
Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Therefore, there is an unmet need for the development of novel methods for sensing and identification of proteins, at the single-molecule level, to ultimately address whole proteome single-cell analyses as well as a broad range of clinical protein sensing applications.
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 and chemo-selectivity. 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.
NanoProt-ID has achieved all the main goals and aims using two complementary and novel methodologies: (i) Solid-state nanopore biosensors, and (ii) Custom silicon-based Nano-channels. These advancement has led to a series of publications and patent applications.
For the solid-state nanopore aim, we have shown that proteins can be linearized and threaded through sub 5 nm pores, and that their dwell time during the translocation process is proportional to their chain length. Then we investigated the role of the anionic surfactant SDS, in generating an electro-osmotic flow that slows down the proteins translocation allowing for much improved SNR in electro-optical measurements. Finally, we constructed and calibrated the "optipore" system for simultaneous electro-optical multi-color sensing of the nanopore system showing that we can classify proteins and DNAs via the electrical and optical signals.
For the nano-channels technology, we developed a general method for single protein molecule separation, tracking, identification and quantification. This method fits the main goals of NanoProit-ID, and further extend its potential use cases in real-life medical applications.
Our new NanoProt-ID developed method involved a number of key elements:
(i) Optimized protein tagging by chemo-selective dual amino-acid specific labels.
(ii) Single protein molecule separation by mass and charge using gel electrophoresis in solid-state nanochannels.
(iii) Single protein tracking at high resolution in subwavelength deep nanochannels with an ultra-high length/height aspect ratio.
(iv) Single protein identification and quantification based on a multi-dimensional molecular feature extraction.
Using this groundbreaking technique, we demonstrated the ability to dynamically track thousands of single protein molecules, leading to an extremely fast, quantitative discrimination among protein species. Importantly, we accomplished ultra-fast full-length protein sensing, bypassing many of the challenges posed by the current gold standard techniques, including loss of molecular integrity due to protein fragmentation, biases introduced by antibodies affinity, difficulty in accurate identification of similar proteoforms and low throughputs. Notably, our method can deliver single proteins to nanopores, thereby significantly improving the accuracy of protein identification and allowing high throughput complex sample analysis.
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.
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 and chemo-selectivity. 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.
NanoProt-ID has achieved all the main goals and aims using two complementary and novel methodologies: (i) Solid-state nanopore biosensors, and (ii) Custom silicon-based Nano-channels. These advancement has led to a series of publications and patent applications.
For the solid-state nanopore aim, we have shown that proteins can be linearized and threaded through sub 5 nm pores, and that their dwell time during the translocation process is proportional to their chain length. Then we investigated the role of the anionic surfactant SDS, in generating an electro-osmotic flow that slows down the proteins translocation allowing for much improved SNR in electro-optical measurements. Finally, we constructed and calibrated the "optipore" system for simultaneous electro-optical multi-color sensing of the nanopore system showing that we can classify proteins and DNAs via the electrical and optical signals.
For the nano-channels technology, we developed a general method for single protein molecule separation, tracking, identification and quantification. This method fits the main goals of NanoProit-ID, and further extend its potential use cases in real-life medical applications.
Our new NanoProt-ID developed method involved a number of key elements:
(i) Optimized protein tagging by chemo-selective dual amino-acid specific labels.
(ii) Single protein molecule separation by mass and charge using gel electrophoresis in solid-state nanochannels.
(iii) Single protein tracking at high resolution in subwavelength deep nanochannels with an ultra-high length/height aspect ratio.
(iv) Single protein identification and quantification based on a multi-dimensional molecular feature extraction.
Using this groundbreaking technique, we demonstrated the ability to dynamically track thousands of single protein molecules, leading to an extremely fast, quantitative discrimination among protein species. Importantly, we accomplished ultra-fast full-length protein sensing, bypassing many of the challenges posed by the current gold standard techniques, including loss of molecular integrity due to protein fragmentation, biases introduced by antibodies affinity, difficulty in accurate identification of similar proteoforms and low throughputs. Notably, our method can deliver single proteins to nanopores, thereby significantly improving the accuracy of protein identification and allowing high throughput complex sample analysis.
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.
To advance our Nanopore-based single molecule protein identification method, we worked in parallel on several different fronts:
1) We have improved and implemented the chemo-selective amino-acids (protein) conjugation 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-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.
7) We were able to track individual proteins during the electrophoretic migration in the nano-channels, extracting multidimensional information from each proteins, that permit proteins identification and classification.
1) We have improved and implemented the chemo-selective amino-acids (protein) conjugation 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-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.
7) We were able to track individual proteins during the electrophoretic migration in the nano-channels, extracting multidimensional information from each proteins, that permit proteins identification and classification.
All the above described progress is beyond the state of the art, and have already been published in multiple original research papers (listed under "Publications")
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(opens in new window)
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(opens in new window)