Posttranscriptional Expression Regulation: What Determines Translation Rates?

Abstract

Recent analyses indicate that differences in protein concentrations are only 20%–40% attributable to variable mRNA levels, underlining the importance of posttranscriptional regulation. Generally, protein concentrations depend on the translation rate (which is proportional to the translational activity, TA) and the degradation rate. By integrating 12 publicly available large-scale datasets and additional database information of the yeast Saccharomyces cerevisiae, we systematically analyzed five factors contributing to TA: mRNA concentration, ribosome density, ribosome occupancy, the codon adaptation index, and a newly developed “tRNA adaptation index.” Our analysis of the functional relationship between the TA and measured protein concentrations suggests that the TA follows Michaelis–Menten kinetics. The calculated TA, together with measured protein concentrations, allowed us to estimate degradation rates for 4,125 proteins under standard conditions. A significant correlation to recently published degradation rates supports our approach. Moreover, based on a newly developed scoring system, we identified and analyzed genes subjected to the posttranscriptional regulation mechanism, translation on demand. Next we applied these findings to publicly available data of protein and mRNA concentrations under four stress conditions. The integration of these measurements allowed us to compare the condition-specific responses at the posttranscriptional level. Our analysis of all 62 proteins that have been measured under all four conditions revealed proteins with very specific posttranscriptional stress response, in contrast to more generic responders, which were nonspecifically regulated under several conditions. The concept of specific and generic responders is known for transcriptional regulation. Here we show that it also holds true at the posttranscriptional level. Large-scale mRNA concentration measurements are a hallmark of our post-genomic era. Usually they are taken as a surrogate for the corresponding protein concentrations. For most genes, proteins are the actual cellular players, but up to now it has been much more difficult to measure protein concentrations than mRNA concentrations. However, due to numerous posttranscriptional regulation mechanisms, mRNA levels only partly correlate with protein concentrations. Based on thoroughly composed reference datasets for protein and mRNA concentrations in yeast under standard growth conditions, we report the best corresponding correlation so far. We took into account additional factors, beyond mRNA concentrations, that influence protein levels in order to improve protein level predictions. Extending our previous approach, where ribosome occupancy and ribosome density were considered, we now also consider ORF-specific translation elongation rates. Different measures for elongation velocity were examined, and the codon adaptation index was found to be most appropriate. Moreover, saturation kinetics were introduced to better describe the translation process. The general findings were also applied to four stress conditions. Three new concepts, translation on demand, just-in-time translation, and general and specific posttranscriptional stress responders, are discussed.