Title
Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock.
Abstract
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.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.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.
Year
DOI
Venue
2006
10.1186/1471-2105-7-184
BMC Bioinformatics
Keywords
Field
DocType
heat shock response,feedback,heat shock,metabolic pathway,algorithms,signal transduction,mathematical model,enzyme activity,adaptive response,bioinformatics,gene expression,enzyme,computer simulation,heat shock proteins,microarrays
Gene,Biology,Heat shock,Gene expression,Signal transduction,Bioinformatics,Saccharomyces cerevisiae,Heat shock protein,Genetics,Adaptive response,DNA microarray
Journal
Volume
Issue
ISSN
7
1
1471-2105
Citations 
PageRank 
References 
26
1.25
5
Authors
3
Name
Order
Citations
PageRank
Ester Vilaprinyó1284.19
Rui Alves219632.99
Albert Sorribas3667.81