Initiation of the transcriptional response to hyperosmotic shock correlates with the potential for volume recovery.

The control of activity and localization of transcription factors is critical for appropriate transcriptional responses. In eukaryotes, signal transduction components such as mitogen-activated protein kinase (MAPK) shuttle into the nucleus to activate transcription. It is not known in detail how different amounts of nuclear MAPK over time affect the transcriptional response. In the present study, we aimed to address this issue by studying the high osmolarity glycerol (HOG) system in Saccharomyces cerevisiae. We employed a conditional osmotic system, which changes the period of the MAPK Hog1 signal independent of the initial stress level. We determined the dynamics of the Hog1 nuclear localization and cell volume by single-cell analysis in well-controlled microfluidics systems and compared the responses with the global transcriptional output of cell populations. We discovered that the onset of the initial transcriptional response correlates with the potential of cells for rapid adaptation; cells that are capable of recovering quickly initiate the transcriptional responses immediately, whereas cells that require longer time to adapt also respond later. This is reflected by Hog1 nuclear localization, Hog1 promoter association and the transcriptional response, but not Hog1 phosphorylation, suggesting that a presently uncharacterized rapid adaptive mechanism precedes the Hog1 nuclear response. Furthermore, we found that the period of Hog1 nuclear residence affects the amplitude of the transcriptional response rather than the spectrum of responsive genes.

Time course gene expression profiling of yeast spore germination reveals a network of transcription factors orchestrating the global response.

BACKGROUND: Spore germination of the yeast Saccharomyces cerevisiae is a multi-step developmental path on which dormant spores re-enter the mitotic cell cycle and resume vegetative growth. Upon addition of a fermentable carbon source and nutrients, the outer layers of the protective spore wall are locally degraded, the tightly packed spore gains volume and an elongated shape, and eventually the germinating spore re-enters the cell cycle. The regulatory pathways driving this process are still largely unknown. Here we characterize the global gene expression profiles of germinating spores and identify potential transcriptional regulators of this process with the aim to increase our understanding of the mechanisms that control the transition from cellular dormancy to proliferation. RESULTS: Employing detailed gene expression time course data we have analysed the reprogramming of dormant spores during the transition to proliferation stimulated by a rich growth medium or pure glucose. Exit from dormancy results in rapid and global changes consisting of different sequential gene expression subprograms. The regulated genes reflect the transition towards glucose metabolism, the resumption of growth and the release of stress, similar to cells exiting a stationary growth phase. High resolution time course analysis during the onset of germination allowed us to identify a transient up-regulation of genes involved in protein folding and transport. We also identified a network of transcription factors that may be regulating the global response. While the expression outputs following stimulation by rich glucose medium or by glucose alone are qualitatively similar, the response to rich medium is stronger. Moreover, spores sense and react to amino acid starvation within the first 30 min after germination initiation, and this response can be linked to specific transcription factors. CONCLUSIONS: Resumption of growth in germinating spores is characterized by a highly synchronized temporal organisation of up- and down-regulated genes which reflects the metabolic reshaping of the quickening spores.

Case study in systematic modelling: thiamine uptake in the yeast Saccharomyces cerevisiae.

In recent years, with important advances in molecular biology, experimental and measurement technologies, it has become possible to generate the quantitative data that are needed for building mathematical models of complex biochemical processes. Cartoon-like diagrams of biological pathways can be turned into dynamical models, allowing simulation and analysis to gain an insight into the underlying control mechanisms and the behaviour of the overall system. This kind of system-level understanding has not been reachable from the study of the components of pathways in isolation. However, mathematical modelling does not only integrate the available knowledge about a certain system with newly generated experimental results. During the process of modelling, questions need to be addressed that lead to an increased quantitative understanding of the system. Models can be used to optimize experimental approaches and protocols and to test different hypotheses about the underlying biological mechanisms. Finally, a validated mathematical model can be used to perform in silico experiments that might be hard or impossible to do in the laboratory. In this chapter we present a case study of a systematic modelling approach applied to the thiamine uptake system of the yeast Saccharomyces cerevisiae. This example is part of our broader effort to model the whole of thiamine metabolism in yeast, which involves several additional processes such as thiamine utilization, biosynthesis and gene regulation. Our main goal is to describe how systematic modelling has improved the knowledge about the system under study.