Abstract
The importance of mRNA translation models has been demonstrated across many fields of science and biotechnology. However, a whole cell model with codon resolution and biophysical dynamics is still lacking. We describe a whole cell model of translation for E. coli. The model simulates all major translation components in the cell: ribosomes, mRNAs and tRNAs. It also includes, for the first time, fundamental aspects of translation, such as competition for ribosomes and tRNAs at a codon resolution while considering tRNAs wobble interactions and tRNA recycling. The model uses parameters that are tightly inferred from large scale measurements of translation. Furthermore, we demonstrate a robust modelling approach which relies on state-of-the-art practices of translation modelling and also provides a framework for easy generalizations. This novel approach allows simulation of thousands of mRNAs that undergo translation in the same cell with common resources such as ribosomes and tRNAs in feasible time. Based on this model, we demonstrate, for the first time, the direct importance of competition for resources on translation and its accurate modelling. An effective supply-demand ratio (ESDR) measure, which is related to translation factors such as tRNAs, has been devised and utilized to show superior predictive power in complex scenarios of heterologous gene expression. The devised model is not only more accurate than the existing models, but, more importantly, provides a framework for analyzing complex whole cell translation problems and variables that haven't been explored before, making it important in various biomedical fields.
Highlights
Dozens of studies in recent years have demonstrated the advantages of using computational models of mRNA translation in basic science and biotechnology
We focused on incorporation of the following two aspects in a whole cell model of translation: 1) accurate elongation dynamics at a codon resolution; 2) finite resources pools of various types
To describe the translation elongation dynamics at a codon level, we have developed a generalized version of deterministic TASEP, which is described in sub-section Generalized deterministic TASEP and state machines
Summary
Dozens of studies in recent years have demonstrated the advantages of using computational models of mRNA translation in basic science and biotechnology (see, for example, [1,2,3,4,5,6,7,8,9,10,11]). According to a recent review [11], several computational and mathematical models related to competition for finite resources during translation have been suggested [12,13,14,15,16,17,18]. These models commonly address only a single resource type (ribosomes) and do not include aspects such as tRNA availability. In this study we aimed to bridge this gap by providing such model which is efficient enough to simulate real whole cell scenarios
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