The well established phenomenon of ribosome drop-off plays crucial roles in translational accuracy and nutrient starvation responses during protein translation. When cells are under stress conditions, such as amino acid starvation or aminoacyl-tRNA depletion due to a high level of recombinant protein expression, ribosome drop-off can substantially affect the efficiency of protein expression. Here we introduce a mathematical model that describes the effects of ribosome drop-off on the ribosome density along the mRNA and on the concomitant protein synthesis rate. Our results show that ribosome premature termination may lead to non-intuitive ribosome density profiles, such as a ribosome density which increases from the 5’ to the 3’ end. Importantly, the model predicts that the effects of ribosome drop-off on the translation rate are mRNA-specific, and we quantify their resilience to drop-off, showing that the mRNAs which present ribosome queues are much less affected by ribosome drop-off than those which do not. Moreover, among those mRNAs that do not present ribosome queues, resilience to drop-off correlates positively with the elongation rate, so that sequences using fast codons are expected to be less affected by ribosome drop-off. This result is consistent with a genome-wide analysis of S. cerevisiae, which reveals that under favourable growth conditions mRNAs coding for proteins involved in the translation machinery, known to be highly codon biased and using preferentially fast codons, are highly resilient to ribosome drop-off. Moreover, in physiological conditions, the translation rate of mRNAs coding for regulatory, stress-related proteins, is less resilient to ribosome drop-off. This model therefore allows analysis of variations in the translational efficiency of individual mRNAs by accounting for the full range of known ribosome behaviours, as well as explaining mRNA-specific variations in ribosome density emerging from ribosome profiling studies.
Bibliographical noteIS and MCR were supported by the Biotechnology and Biological Sciences Research Council (BBSRC) (http://www.bbsrc.ac.uk) BB/N017161/1. IS was supported by the Biotechnology and Biological Sciences Research Council (BBSRC) (http://www.bbsrc.ac.uk) BB/I020926/1. PB and MCR were supported by the Scottish Universities Life Sciences Alliance (SULSA) (http://www.sulsa.ac.uk). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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- School of Natural & Computing Sciences, Physics - Personal Chair
- Institute for Complex Systems and Mathematical Biology (ICSMB)
- School of Medicine, Medical Sciences & Nutrition, Molecular and Cellular Function
- School of Medicine, Medical Sciences & Nutrition, Medical Sciences - School Director of Research, Personal Chair
- School of Medicine, Medical Sciences & Nutrition, Institute of Medical Sciences