Vilaprinyo Ester, Alves Rui, Sorribas Albert
Departament de Ciències Mèdiques Bàsiques, Universitat de Lleida, Montserrat Roig 2, 25008-Lleida, Spain.
BMC Bioinformatics. 2006 Apr 3;7:184. doi: 10.1186/1471-2105-7-184.
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.
了解基因表达变化、酶活性改变与生物体对环境线索相应生理适应性反应之间的关系，对于解释细胞如何应对压力至关重要。例如，酵母对热休克的适应涉及糖酵解途径及其一些分支中编码酶的基因表达水平变化的特征性模式。基因表达谱变化的实验测定提供了对应激适应性反应的描述性图景。然而，它并未解释为何针对任何给定反应会选择特定的模式。
我们使用数学模型和对计算机模拟基因表达谱（GEP）的分析，以了解基因表达变化如何与酵母细胞对热休克的有效反应相关联。模拟并分析了一组详尽的GEP，将其与相应的酶活性集相匹配。根据相关生理和功能标准评估每种模式在热休克反应中的有效性。热休克后导致有效生理反应的GEP小子集被确定为几种进化标准调整的结果。实验观察到的热休克反应中的转录变化属于该集合，并且可以通过生理水平上的定量设计原则来解释，这些原则最终限制了基因表达的变化。
我们的理论方法提出了一种理解多个基因表达变化对代谢途径活性的综合影响，进而对细胞代谢适应热休克的影响的方法。该方法确定了有助于理解细胞对应激反应的定量设计原则。
