Studies on the dynamics of growth of single eukaryotic cells and their relationships with cell cycle regulations are generally carried out following cell synchronization procedures or, on a relatively low number of cells, by time-lapse studies. Establishment of both time-lapse studies and synchronous cell populations usually requires elaborate experimental efforts and is prone to perturb the physiological state of the cell. In this paper we use a new flow cytometric approach which allows, in asynchronous growing Saccharomyces cerevisiae populations, tagging of both the cell age and the cell protein content of a cohort of daughter cells at the different cell cycle set points. Since the cell protein content is a good estimation of the cell size, it is possible to follow the kinetics of the cell size increase during cell cycle progression. The experimental findings obtained indicate an exponential increase of the cell size during growth, that the daughter and the parent subpopulations grow with the same specific growth rate, that the average cell size increase rate of each individual cell is almost identical to the specific growth rate of the overall population and provide the opportunity to estimate the cell cycle length for the daughter cell population as well as the identification of the complex structure of asynchronously growing yeast populations.

To gain insight on the interrelationships of the cellular environment, the properties of growth, and cell cycle progression, we analyzed the dynamic reactions of individual Saccharomyces cerevisiae cells to changes and manipulations of their surroundings. We used a new flow cytometric approach which allows, in asynchronous growing S. cerevisiae populations, tagging of both the cell age and the cell protein content of cells belonging to the different cell cycle set points. Since the cell protein content is a good estimation of the cell size, it is possible to follow the kinetics of the cell size increase during cell cycle progression. The analysis of the findings obtained indicates that both during a nutritional shift-up (from ethanol to glucose) and following the addition of cyclic AMP (cAMP), two important delays are induced. The preexisting cells that at the moment of the nutritional shift-up were cycling before the Start phase delay their entrance into S phase, while cells that were cycling after Start are delayed in their exit from the cycle. The combined effects of the two delays allow the cellular population that preexisted the shift-up to quickly adjust to the new growth condition. The effects of a nutritional shift-down were also determined.

Industrial biotechnology and metabolic engineering can offer an innovative approach to solving energy and pollution problems. The potential industrial applications of yeast are reviewed here.

Flow cytometry allows one to measure relevant physical or chemical properties on a single cell, yielding the distribution of these properties in the cell population. Typically, flow cytometry has been used to determine DNA or protein distributions, but it could be extended to the determination of other relevant parameters, such as intracellular pH, membrane potential, intracellular Ca2+ concentration, mitochondrial activity, etc. In the present work, we used flow cytometry to determine the respiratory activity in intact Saccharomyces cerevisiae cells after staining with the cationic lipophilic dye rhodamine 123 (Rhl23). We found a good correlation between the Rh123 fluorescence distribution in yeast populations and the degree of respiratory activity, which can be varied by changing the carbon source used for yeast growth. In addition, we developed a vital staining procedure which allows one to measure fast changes in the respiratory activity. We used this technique to follow the kinetics of glucose repression and to measure the apparent Km for the substrate. Our results demonstrate that flow cytometry is a fast and very sensitive method to evaluate the respiratory activity in yeast cells and is also suitable for the determination of rapid changes in yeast metabolism. Biotech‐nological implications of this study are also discussed.

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