Descripción del proyecto
Correlación de la estructura y la dinámica de la adhesión focal con las características del sustrato a nanoescala
Las adhesiones focales son complejos proteicos asociados a la membrana celular. Estas adhesiones interactúan con la matriz extracelular (y con el citoesqueleto intercelular de actina), lo que modula la migración y función celulares. Comprender mejor cómo interactúan las células con sus sustratos aceleraría la ingeniería de futuros biomateriales para la medicina regenerativa. El equipo del proyecto FAKIR, financiado por el Consejo Europeo de Investigación, lo investigará fabricando superficies a nanoescala con escalas de longitud comparables a las de las unidades estructurales de las adhesiones focales. La microscopía de alta resolución y el aprendizaje automático permitirán clasificar los tipos de células en diversas nanotopografías, lo que relacionará los parámetros morfométricos con la estructura y la dinámica de la adhesión focal y dará lugar a un modelo para el futuro diseño de biomateriales.
Objetivo
The provision of advanced functional materials in the area of regenerative medicine and discovery applications depends on many different factors to provide the appropriate targeted function. As adherent cells also read their environment through substrate interactions there is a great interest in developing such substrates in a predictable manner. Their first point of contact is through their focal adhesions and it is also though them that forces are applied allowing the cell to migrate and establish cytoskeletal tension which in turn regulates cell function. The objective of this project is to investigate the cell-substrate interaction at the nanoscale and correlate that to the surface topography for predictable biomaterials. Through the application of state-of-the-art nanofabrication we will fabricate precise surface topographies with length scales comparable to the structural units found in the focal adhesions. The aim is to map and understand the topographical influence in the architectural arrangement of the proteins in the adhesions. Aided by high resolution microscopy we will classify cell types on different nanotopographies. Combining that information with machine learning, we will be able to gain information about cell characteristics from the rule set. That information can also be used in reverse to identify cell types with the previously defined characteristic. This approach is similar to face recognition seen on cameras and mobile phones.
The proposed research project will not only provide insight to an area of biomaterials not previously explored, yet aim to provide a blueprint for future design of biomaterials.
Ámbito científico
- natural sciencesphysical sciencesopticsmicroscopysuper resolution microscopy
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- engineering and technologyindustrial biotechnologybiomaterials
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencesbiological sciencesmolecular biology
Palabras clave
Programa(s)
Régimen de financiación
ERC-COG - Consolidator GrantInstitución de acogida
G12 8QQ Glasgow
Reino Unido