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A Minimal Model of Ribosome Allocation Dynamics Captures Trade-offs in Expression between Endogenous and Synthetic Genes

  • Cells contain a finite set of resources that must be distributed across many processes to ensure survival. Among them, the largest proportion of cellular resources is dedicated to protein translation. Synthetic biology often exploits these resources in executing orthogonal genetic circuits, yet the burden this places on the cell is rarely considered. Here, we develop a minimal model of ribosome allocation dynamics capturing the demands on translation when expressing a synthetic construct together with endogenous genes required for the maintenance of cell physiology. Critically, it contains three key variables related to design parameters of the synthetic construct covering transcript abundance, translation initiation rate, and elongation time. We show that model-predicted changes in ribosome allocation closely match experimental shifts in synthetic protein expression rate and cellular growth. Intriguingly, the model is also able to accurately infer transcript levels and translation times after further exposure to additional ambientCells contain a finite set of resources that must be distributed across many processes to ensure survival. Among them, the largest proportion of cellular resources is dedicated to protein translation. Synthetic biology often exploits these resources in executing orthogonal genetic circuits, yet the burden this places on the cell is rarely considered. Here, we develop a minimal model of ribosome allocation dynamics capturing the demands on translation when expressing a synthetic construct together with endogenous genes required for the maintenance of cell physiology. Critically, it contains three key variables related to design parameters of the synthetic construct covering transcript abundance, translation initiation rate, and elongation time. We show that model-predicted changes in ribosome allocation closely match experimental shifts in synthetic protein expression rate and cellular growth. Intriguingly, the model is also able to accurately infer transcript levels and translation times after further exposure to additional ambient stress. Our results demonstrate that a simple model of resource allocation faithfully captures the redistribution of protein synthesis resources when faced with the burden of synthetic gene expression and environmental stress. The tractable nature of the model makes it a versatile tool for exploring the guiding principles of efficient heterologous expression and the indirect interactions that can arise between synthetic circuits and their host chassis because of competition for shared translational resources.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Thomas E. Gorochowski, Irem Aycilar-Kucukgoze, Roel A. L. Bovenberg, Johannes A. Roubos, Zoya Ignatova
DOI:https://doi.org/10.1021/acssynbio.6b00040
ISSN:2161-5063
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/27112032
Titel des übergeordneten Werks (Englisch):ACS synthetic biology
Verlag:American Chemical Society
Verlagsort:Washington
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Jahr der Erstveröffentlichung:2016
Erscheinungsjahr:2016
Datum der Freischaltung:22.03.2020
Freies Schlagwort / Tag:protein biosynthesis; synthetic biology; systems biology; translation
Band:5
Seitenanzahl:11
Erste Seite:710
Letzte Seite:720
Fördernde Institution:European Commission [289384]; BrisSynBio; BBSRC/EPSRC Synthetic Biology Research Centre [BB/L01386X/1]
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
Peer Review:Referiert
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