Descripción del proyecto
Una plataforma innovadora para identificar proteínas individuales a nivel de célula única
La capacidad para identificar proteínas individuales a nivel de célula única transformaría la investigación en proteómica y biomedicina. En el proyecto NanoProt-ID, financiado con fondos europeos, se concebirá un método para el análisis de proteomas a nivel de proteína única. Estudios bioinformáticos han revelado que más del 99 % de las proteínas pueden identificarse por el orden en que aparecen los residuos de lisina, cisteína y metionina a lo largo de la cadena proteica. La hipótesis del proyecto es que etiquetar los tres residuos con fluorocromos diferentes y enhebrarlos a través de nanoporos de estado sólido equipados con amplificadores plasmónicos personalizados dará como resultado una representación temporal única con fluorescencia multicolor de las proteínas del proteoma. Los investigadores pretenden ampliar esta plataforma para poder analizar miles de proteínas diferentes en minutos.
Objetivo
To date, antibody-free protein identification methods have not reached single-molecule precision. Instead, they rely on averaging from many cells, obscuring the details of important biological processes. The ability to identify each individual protein from within a single cell would transform proteomics research and biomedicine. However, single protein identification (ID) presents a major challenge, necessitating a breakthrough in single-molecule sensing technologies.
We propose to develop a method for proteome-level analysis, with single protein resolution. Bioinformatics studies show that >99% of human proteins can be uniquely identified by the order in which only three amino-acids, Lysine, Cysteine, and Methionine (K, C and M, respectively), appear along the proteins’ chain. By specifically labelling K, C and M residues with three distinct fluorophores, and threading them, one by one, through solid-state nanopores equipped with custom plasmonic amplifiers, we hypothesize that we can obtain multi-color fluorescence time-trace fingerprints uniquely representing most proteins in the human proteome. The feasibility of our method will be established by attaining 4 main aims: i) in vitro K,C,M protein labelling, ii) development of a machine learning classifier to uniquely ID proteins based on their optical fingerprints, iii) fabrication of state-of-the-art plasmonic nanopores for high-resolution optical sensing of proteins, and iv) devising methods for regulating the translocation speed to enhance the signal to noise ratio. Next, we will scale up our platform to enable the analysis of thousands of different proteins in minutes, and apply it to sense blood-secreted proteins, as well as whole proteomes in pre- and post-metastatic cancer cells. NanoProt-ID constitutes the first and most challenging step towards the proteomic analysis of individual cells, opening vast research directions and applications in biomedicine and systems biology.
Ámbito científico
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsproteomics
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- medical and health sciencesclinical medicineoncology
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programa(s)
Régimen de financiación
ERC-ADG - Advanced GrantInstitución de acogida
32000 Haifa
Israel