Summary
Today, antimicrobial resistance is emerging as a global burden, endangering our lives. Drug-resistant pathogens kill about 25,000 infected people solely in the European Union every year. In the fight against this crisis, rapid Antimicrobial Susceptibility Testing (AST) plays a crucial role. Although effective in discerning the right concentration of antibiotics required to inhibit the growth of a pathogen, conventional AST techniques are not fit for point-of-care, since they are slow and require large microbial inocula.
The advent of graphene, and the ability to fabricate one-atom thick membranes, has made it possible to make miniaturised sensors that are extremely sensitive to nanoscale forces. During the research project ENIGMA carried out in the framework of the ERC Starting Grant no. 802093, we have developed a methodology that can probe nanomechanical motion of graphene membranes in the presence of bacterial cells. Here, I propose to further validate this technology and realize a proof-of-concept demonstrator that offers automated high throughput AST using massively parallelized graphene membranes. By eliminating the need for culturing large number of bacterial cells, GRAPHFITI has the potential to shift the current paradigm of AST technologies towards the use of atomically thin membranes with single bacterial cell sensitivity, thus enabling diagnostic tools for fast point-of-care screening of antimicrobial resistance.
The advent of graphene, and the ability to fabricate one-atom thick membranes, has made it possible to make miniaturised sensors that are extremely sensitive to nanoscale forces. During the research project ENIGMA carried out in the framework of the ERC Starting Grant no. 802093, we have developed a methodology that can probe nanomechanical motion of graphene membranes in the presence of bacterial cells. Here, I propose to further validate this technology and realize a proof-of-concept demonstrator that offers automated high throughput AST using massively parallelized graphene membranes. By eliminating the need for culturing large number of bacterial cells, GRAPHFITI has the potential to shift the current paradigm of AST technologies towards the use of atomically thin membranes with single bacterial cell sensitivity, thus enabling diagnostic tools for fast point-of-care screening of antimicrobial resistance.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/966720 |
| Start date: | 01-04-2021 |
| End date: | 30-09-2022 |
| Total budget - Public funding: | - 150 000,00 Euro |
Cordis data
Original description
Today, antimicrobial resistance is emerging as a global burden, endangering our lives. Drug-resistant pathogens kill about 25,000 infected people solely in the European Union every year. In the fight against this crisis, rapid Antimicrobial Susceptibility Testing (AST) plays a crucial role. Although effective in discerning the right concentration of antibiotics required to inhibit the growth of a pathogen, conventional AST techniques are not fit for point-of-care, since they are slow and require large microbial inocula.The advent of graphene, and the ability to fabricate one-atom thick membranes, has made it possible to make miniaturised sensors that are extremely sensitive to nanoscale forces. During the research project ENIGMA carried out in the framework of the ERC Starting Grant no. 802093, we have developed a methodology that can probe nanomechanical motion of graphene membranes in the presence of bacterial cells. Here, I propose to further validate this technology and realize a proof-of-concept demonstrator that offers automated high throughput AST using massively parallelized graphene membranes. By eliminating the need for culturing large number of bacterial cells, GRAPHFITI has the potential to shift the current paradigm of AST technologies towards the use of atomically thin membranes with single bacterial cell sensitivity, thus enabling diagnostic tools for fast point-of-care screening of antimicrobial resistance.
Status
CLOSEDCall topic
ERC-2020-POCUpdate Date
27-04-2024
Geographical location(s)
