Summary
Life has evolved diverse protein machines and bacteria provide many fascinating examples. Despite being unicellular organisms of relatively small size, bacteria produce sophisticated nanomachines with a high degree of self-organization. The motility organelle of bacteria, the flagellum, is a prime example of complex bacterial nanomachines. Flagella are by far the most prominent extracellular structures known in bacteria and made through self-assembly of several dozen different kinds of proteins and thus represents an ideal model system to study sub-cellular compartmentalization and self-organization. The flagellum can function as a macromolecular motility machine only if its many building blocks assemble in a coordinated manner. However, previous studies have focused on phenotypic and genetic analyses, or the characterization of isolated sub-components. Crucially, how bacteria orchestrate the many different cellular processes in time and space in order to construct a functional motility organelle remains enigmatic. The present proposal constitutes a comprehensive research program with the aim to obtain a holistic understanding of the underlying principles that allow bacteria to control and coordinate the simultaneous self-assembly processes of several multi-component nanomachines within a single cell. Towards this goal, we will combine for the first time the visualization of the dynamic self-assembly of individual flagella with quantitative single-cell gene expression analyses, re-engineering of the genetic network and biophysical modeling in order to develop a biophysical model of flagella self-assembly. This novel, integrative approach will allow us to move beyond the classical, descriptive characterization of protein complexes towards an engineering-type understanding of the extraordinarily robust and coordinated assembly of a multi-component molecular machine.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/864971 |
| Start date: | 01-10-2020 |
| End date: | 30-09-2025 |
| Total budget - Public funding: | 1 934 950,00 Euro - 1 934 950,00 Euro |
Cordis data
Original description
Life has evolved diverse protein machines and bacteria provide many fascinating examples. Despite being unicellular organisms of relatively small size, bacteria produce sophisticated nanomachines with a high degree of self-organization. The motility organelle of bacteria, the flagellum, is a prime example of complex bacterial nanomachines. Flagella are by far the most prominent extracellular structures known in bacteria and made through self-assembly of several dozen different kinds of proteins and thus represents an ideal model system to study sub-cellular compartmentalization and self-organization. The flagellum can function as a macromolecular motility machine only if its many building blocks assemble in a coordinated manner. However, previous studies have focused on phenotypic and genetic analyses, or the characterization of isolated sub-components. Crucially, how bacteria orchestrate the many different cellular processes in time and space in order to construct a functional motility organelle remains enigmatic. The present proposal constitutes a comprehensive research program with the aim to obtain a holistic understanding of the underlying principles that allow bacteria to control and coordinate the simultaneous self-assembly processes of several multi-component nanomachines within a single cell. Towards this goal, we will combine for the first time the visualization of the dynamic self-assembly of individual flagella with quantitative single-cell gene expression analyses, re-engineering of the genetic network and biophysical modeling in order to develop a biophysical model of flagella self-assembly. This novel, integrative approach will allow us to move beyond the classical, descriptive characterization of protein complexes towards an engineering-type understanding of the extraordinarily robust and coordinated assembly of a multi-component molecular machine.Status
SIGNEDCall topic
ERC-2019-COGUpdate Date
27-04-2024
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