Establishing the hierarchies in regulation .... in time

Humans, animals, plants and even living creatures so small that we can not see them with our naked eye (such as the yeasts that make our bread and beer), can adapt remarkably well to changes in their environment. The latter include changes in temperature, food supply, and exposure to toxic chemicals such as nicotin and alcohol. The adaptation is often much better than the adaptation of man-made systems. Hence we are eager to learn from Biology how the adaptation can be so effective. One might think that this should be easy now, with 'DNA-sequencing based functional genomics' delivering so many experimental results. However, the amounts of new results are so staggering that it is hard to see the forest for the trees. The scientists are in need of straightforward ways to interpret those results in terms of what they imply for adaptation and the regulation thereof. We recently obtained evidence suggesting that biological adaptation is so effective because it invokes a succession of regulatory mechanisms. The mechanisms that come into play first may be ones that are always on stand-bye but less efficient. The ones that are onvoked subsequently, may be more effective ultimately but are too 'expensive' to keep on stand-bye all the time. We here propose a research project that will establish a precise method to prove this experimentally. The new method that we shall develop here is called time-dependent regulation analysis. It will be demonstrated completely for yeast cells that are adapting to a shortage of nitrogen (or sugar). We expect to learn how Biology still beats man-made systems in terms of subtle and efficient regulation. This has the perspective of improving man-made control systems, as well as the environmentally friendly production of beer, bread and new biologicals.

The continued functioning of living organisms depends on optimal responses to dynamic variations in various external and internal conditions. This is particularly so for unicellular microorganisms, such as baker's yeast. The corresponding regulation of the various processes that make up a living cell's function must proceed in significant coherence. This view does not sit easily with the traditional paradigms for studying regulation, which focus either on metabolic or on transcriptional regulation. Although results in functional genomics now suggest that for many processes regulation is not confined to the level of transcription, there has been no method to quantify how much regulation is metabolic and how much transcriptional, at various points in time. We will here develop and apply such a method. The method proposed is different from metabolic control analysis, as are the issues the two methods address. Yet, the new method is also fortified by theorems that will be proven mathematically, demonstrated numerically, and put to practice experimentally. The analysis includes regulation at the levels of mRNA life time, translation, protein modification, and protein stability. The method will be applied to the regulatory events of central carbon and energy metabolism in yeast that occur when growth conditions change dynamically. We shall here further improve the precision at which process rates and mRNA and protein concentrations/modifications are measured. Deliverables include insight into the extent to which the various regulatory mechanisms in the cell contribute at various successive phases of dynamic regulatory transients. They will suggest new ways of engineering cellular processes by interfering at the best possible time at various points of the cell's regulation, rather than by interfering once then being thwarted by the subsequent adaptations of the cell.