Single molecule tracking for live cell protein synthesis kinetics
This project aims to map the determinants of efficient synthesis, folding, and targeting of proteins in living bacterial cells, and to understand how antibiotic drugs inhibit these events. Our findings will be used to form a quant...
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Información proyecto SMACK
Duración del proyecto: 63 meses
Fecha Inicio: 2020-09-09
Fecha Fin: 2025-12-31
Líder del proyecto
UPPSALA UNIVERSITET
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Presupuesto del proyecto
2M€
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
This project aims to map the determinants of efficient synthesis, folding, and targeting of proteins in living bacterial cells, and to understand how antibiotic drugs inhibit these events. Our findings will be used to form a quantitative description of how the mRNA sequence ultimately determines how, where, and when a polypeptide should fold, which will help to design better E. coli-based production systems for recombinant proteins; both protein folding and targeting are currently severe bottlenecks. Further, by studying the effect of clinically relevant antibiotic drugs directly on ongoing protein synthesis, we will learn how the inhibitory action on the molecular level is translated into the response on cell and population level. This knowledge will help to improve the use of current drugs, as well as to provide clues regarding how new drugs should be designed.
To reach our goals, we will use and further develop our recently published fluorescence-based experimental and analytical system for live-cell single-molecule analysis of protein synthesis kinetics. Particularly, we will develop orthogonal translation systems to measure protein synthesis kinetics on defined mRNAs in an unperturbed cell background. We will also label and study key components of the universal pathway for Signal Recognition Particle-mediated cotranslational targeting of peptides to the membrane-bound peptide translocation complexes. In these applications we use small organic dyes for site-specific labeling of molecules, which allow recording of long diffusion trajectories inside cells. These trajectories are then fed to our machine-learning algorithms to deduce the binding kinetics.
With an increasing demand for therapeutic proteins, such as monoclonal antibodies for cancer treatment, there is an urgent need for microbial-based systems for cost-effective production of recombinant proteins. With our unique experimental and analytical system, we have the opportunity to aid in this development.