Rate-Limiting Steps in Yeast Protein Translation

Premal Shah,Yang Ding,Malwina Niemczyk,Grzegorz Kudla,Joshua B Plotkin

doi:10.1016/j.cell.2013.05.049

Premal Shah, Yang Ding + Show 3 more

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https://doi.org/10.1016/j.cell.2013.05.049

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Abstract

SummaryDeep sequencing now provides detailed snapshots of ribosome occupancy on mRNAs. We leverage these data to parameterize a computational model of translation, keeping track of every ribosome, tRNA, and mRNA molecule in a yeast cell. We determine the parameter regimes in which fast initiation or high codon bias in a transgene increases protein yield and infer the initiation rates of endogenous Saccharomyces cerevisiae genes, which vary by several orders of magnitude and correlate with 5′ mRNA folding energies. Our model recapitulates the previously reported 5′-to-3′ ramp of decreasing ribosome densities, although our analysis shows that this ramp is caused by rapid initiation of short genes rather than slow codons at the start of transcripts. We conclude that protein production in healthy yeast cells is typically limited by the availability of free ribosomes, whereas protein production under periods of stress can sometimes be rescued by reducing initiation or elongation rates.

Highlights

Protein translation is central to cellular life
Individual steps in translation such as the formation of the 43S preinitiation complex are known in intricate molecular detail, a global understanding of how these steps combine to set the pace of protein production for individual genes remains elusive (Jackson et al, 2010; Plotkin and Kudla, 2011)
We describe the factors that influence ribosomal pausing along messenger RNA (mRNA) molecules, as well as the effects of stress on translation

Summary

Introduction

Individual steps in translation such as the formation of the 43S preinitiation complex are known in intricate molecular detail, a global understanding of how these steps combine to set the pace of protein production for individual genes remains elusive (Jackson et al, 2010; Plotkin and Kudla, 2011) Factors such as biased codon usage, gene length, transcript abundance, and initiation rate are all known to modulate protein synthesis (Bulmer, 1991; Chamary et al, 2006; Cannarozzi et al, 2010; Tuller et al, 2010a; Shah and Gilchrist, 2011; Plotkin and Kudla, 2011; Gingold and Pilpel, 2011; Chu et al, 2011; Chu and von der Haar, 2012), but how they interact with one another to collectively determine translation rates of all transcripts in a cell is poorly understood. Biotechnical applications that exploit these processes stand to gain from a quantitative understanding of the global principles governing protein production (Gustafsson et al, 2004; Salis et al, 2009; Welch et al, 2009)

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