Heat shock response in yeast involves changes in both transcription rates and mRNA stabilities

We have analyzed the heat stress response in the yeast Saccharomyces cerevisiae by determining mRNA levels and transcription rates for the whole transcriptome after a shift from 25uC to 37uC. Using an established mathematical algorithm, theoretical mRNA decay rates have also been calculated from the experimental data. We have verified the mathematical predictions for selected genes by determining their mRNA decay rates at different times during heat stress response using the regulatable tetO promoter. This study indicates that the yeast response to heat shock is not only due to changes in transcription rates, but also to changes in the mRNA stabilities. mRNA stability is affected in 62% of the yeast genes and it is particularly important in shaping the mRNA profile of the genes belonging to the environmental stress response. In most cases, changes in transcription rates and mRNA stabilities are homodirectional for both parameters, although some interesting cases of antagonist behavior are found. The statistical analysis of gene targets and sequence motifs within the clusters of genes with similar behaviors shows that both transcriptional and post-transcriptional regulons apparently contribute to the general heat stress response by means of transcriptional factors and RNA binding proteins.

Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock

Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. Results: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. Conclusion: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.