(180e) Deciphering Translation - a Genome-Wide Analysis of Translation Limitations and Competitions in Saccharomyces Cerevisiae

Protein synthesis is one of the central elements in every living cell. For this process, the mRNAs coding for different genes are simultaneously competing for the same translation machinery, i.e. for the same ribosomes and for the same protein building blocks, the amino acids. But the ultimate determinants of cellular functions are the proteins, it is therefore of crucial importance to understand well this translation process. Nowadays, it is possible to measure the changes in the levels of all mRNAs and proteins in the cell, under different environmental and genetic perturbations. The large amount of data from transcriptomic and proteomic studies requires development of efficient systems-wide mathematical and computational frameworks to analyze and interpret the data.

For this purpose, we developed a genome-wide, mechanistic, mathematical model for the translation machinery in S. cerevisiae. This model includes information on the translation state of each mRNA (i.e. polysome size of each mRNA), and mRNA length, and can be used to estimate genome-scale kinetics of the protein synthesis machinery. It is then used to quantify the rate limiting steps of the translation process and gain insights into the mechanism of regulation of expression between different proteins. This framework allows us therefore to quantify the effect of a change in the total number of ribosomes, or also the effect of varying the level of a single mRNA on the various proteins. This information is then used to determine functional couplings in the yeast genome. We find that while 95% of the mRNA species are initiation and elongation limited, approximately 5% are elongation limited and have higher specific protein synthesis rates. We also observed that the mRNAs with ribosomal coverage greater than 0.8 display a decrease in the specific protein production rate with increasing coverage, and can be acting as sinks for system resources like ribosomes. It was also possible to determine which mRNA species have the most / least influence on the other, and we found that the most influential mRNA species are linked to proteins which form structural constituents of ribosomes, proteins related to translation elongation factor activity or key enzymes of the central carbon metabolism. Thus a perturbation to these key mRNA species has the maximum impact on protein synthesis from other mRNA species.

Our results thus have implications in the understanding of the translation machinery response to perturbations and of the global systems response.