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Vibrations of viral particles scatter light

Project description

A light-driven method to identify viruses down to a single particle

Viruses can vibrate in unique ways based on their size, shape and structure. The EIC-funded VIRUSong project aims to identify viruses by measuring these vibrations using light-based techniques. Researchers will develop two innovative techniques to overcome the limitations of traditional methods, which are ineffective because viruses scatter light only weakly. First, they will use nanoparticles as tiny antennas to amplify virus vibrations. Second, they will employ advanced light-scattering techniques to collect and identify viruses without labels. The mechanical properties of different viruses will be analysed and artificial intelligence will be used to match their unique vibrational patterns. This will help create a fast, highly sensitive technology that can identify viruses in a few minutes, even down to a single viral particle.

Objective

Viruses are nanoparticles with well-defined size, shape and elasticity in which acoustic waves are confined. This leads to the appearance of new vibration modes that correspond to the vibration of the virus particle as a whole object. The VIRUSong project aims at implementing and realizing a simple and radically new way to identify viral particles on the basis of these vibrations. Inelastic light scattering spectroscopy (Raman and Brillouin) is usually a tool of choice to measure these vibrations, but for viruses, the effective scattering cross section is small. To overcome this drawback, the VIRUSong project will mainly focus on a few viruses of different size and structure and two parallel strategies will be explored. (a) the coupling of viruses with nanoparticles of hard materials which are very simple nano resonators (NPRs). The project VIRUSong project aims at using them as antennas to collect and amplify the song of the virus particles (i.e. the vibrations of the virions). (b) the use of Stimulated low-frequency inelastic spectroscopy that will allow the label-free detection of any type of virus. To achieve these objectives, the project will analyze each selected familly of viruses to determine their composition, size, shape and mechanical properties. Finally, all this information will be correlated using artificial intelligence to identify a given virus based on its vibrational spectra. By pushing the current limits of stimulated inelastic light scattering spectroscopy, designing nanoparticle resonators (NPRs) and implementing efficient artificial intelligence models, this project aims to develop the proof of concept of a new technology capable of identifying viral particles by light in a few minutes, while achieving high selectivity (specific vibrational signature) and high sensitivity (down to the single viral particle).

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-EIC - HORIZON EIC Grants

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Call for proposal

(opens in new window) HORIZON-EIC-2022-PATHFINDEROPEN-01

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Coordinator

UNIVERSITE LYON 1 CLAUDE BERNARD
Net EU contribution
€ 766 276,25
Address
BOULEVARD DU 11 NOVEMBRE 1918 NUM43
69622 Villeurbanne Cedex
France
Region
Auvergne-Rhône-Alpes Rhône-Alpes Rhône
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 766 276,25

Participants (8)