EE Seminar: A Model for Competition for Ribosomes in the Cell
~~Speaker: Alon Raveh,
M.Sc. student under the supervision of Prof. Michael Margaliot
Wednesday, October 28th, 2015 at 15:30
Room 011, Kitot Bldg., Faculty of Engineering
A Model for Competition for Ribosomes in the Cell
Abstract
A single mammalian cell includes an order of 10^4−10^5 mRNA molecules and as many as 10^5−10^6 ribosomes. Large-scale simultaneous mRNA translation and the resulting competition for the available ribosomes has important implications to the cell’s functioning and evolution. Developing a better understanding of the intricate correlations between these simultaneous processes, rather than focusing on the translation of a single isolated transcript, should help in gaining a better understanding of mRNA translation regulation and the way elongation rates affect organismal fitness. A model of simultaneous translation is specifically important when dealing with highly expressed genes, as these consume more resources. In addition, such a model can lead to more accurate predictions that are needed in the interconnection of translational modules in synthetic biology.
We develop and analyze a general model for large-scale simultaneous mRNA translation and competition for ribosomes. This is based on combining several ribosome flow models (RFMs) interconnected via a pool of free ribosomes. We prove that the compound system always converges to a steady-state and that it always entrains or phase locks to periodically time-varying transition rates in any of the mRNA molecules. We use this model to explore the interactions between the various mRNA molecules and ribosomes at steady-state. We show that increasing the length of an mRNA molecule decreases the production rate of all the mRNAs. Increasing any of the codon translation rates in a specific mRNA molecule yields a local effect: an increase in the translation rate of this mRNA, and also a global effect: the translation rates in the other mRNA molecules all increase or all decrease.
These results suggest that the effect of codon decoding rates of endogenous and heterologous mRNAs on protein production is more complicated than previously thought.
