Analysis of protein distribution in budding yeast

Flow cytometry is a fast and sensitive method that allows monitoring of different cellular parameters on large samples of a population. Protein distributons give relevant information on growth dynamics, since they are related to the age distribution and depend on the law of growth of the population and the law of protein accumulation during the cell cycle. We analyzed protein distributions to evaluate alternative growth models for the budding yeast Saccharomyces cerevisiae and to monitor the changes in population dynamics that result from environmental modifications; such an analysis could potentially give parameters useful in the control of biotechnological processes. Theoretical protein distributions (taking into account the unequal division of yeast cells and the exponential law of protein accumulation during a cell cycle) quantitatively fit experimental distributions, once appropriate variability sources are introduced. Best fits are obtained when the protein threshold required for bud emergence increases at each new generation of parent cells.     

Heterologous gene expression in continuous cultures of budding yeast

Summary In a previous paper we have studied the expression of -galactosidase from Escherichia coli, driven from the inducible GAL1-10/CYC1 hybrid promoter, in batch cultures of budding Saccharomyces cerevisiae and have described operating conditions for maximal productivity. In this paper we show that the plasmid instability in continuous cultures can be overcome by utilizing appropriate selection markers and a high copy number vector. The maximal level of expression is influenced by the dilution rate. Moreover, enzyme accumulation appears to depend also upon the degree of oxygenation. A possible explanation of these modulations is discussed, taking into account the interactions of the UAS-GAL and TATA-CYC1 elements. Offprint requests to: D. Porro     

Homeostatic adjustment and metabolic remodeling in glucose-limited yeast cultures

We studied the physiological response to glucose limitation in batch and steady-state (chemostat) cultures of Saccharomyces cerevisiae by following global patterns of gene expression. Glucose-limited batch cultures of yeast go through two sequential exponential growth phases, beginning with a largely fermentative phase, followed by an essentially completely aerobic use of residual glucose and evolved ethanol. Judging from the patterns of gene expression, the state of the cells growing at steady state in glucose-limited chemostats corresponds most closely with the state of cells in batch cultures just before they undergo this "diauxic shift." Essentially the same pattern was found between chemostats having a fivefold difference in steady-state growth rate (the lower rate approximating that of the second phase respiratory growth rate in batch cultures). Although in both cases the cells in the chemostat consumed most of the glucose, in neither case did they seem to be metabolizing it primarily through respiration. Although there was some indication of a modest oxidative stress response, the chemostat cultures did not exhibit the massive environmental stress response associated with starvation that also is observed, at least in part, during the diauxic shift in batch cultures. We conclude that despite the theoretical possibility of a switch to fully aerobic metabolism of glucose in the chemostat under conditions of glucose scarcity, homeostatic mechanisms are able to carry out metabolic adjustment as if fermentation of the glucose is the preferred option until the glucose is entirely depleted. These results suggest that some aspect of actual starvation, possibly a component of the stress response, may be required for triggering the metabolic remodeling associated with the diauxic shift.     

Oscillations in continuous cultures of budding yeast: a segregated parameter analysis

Sustained oscillations have been observed in continuous cultures of Saccharomyces cerevisiae. These oscillations appear spontaneously under aerobic conditions and may constitute a severe limitation for process control. We have found that oscillations arise only in a well defined range of dilution rates and dissolved oxygen values. The period of the oscillations is related, but not equal, to the mass doubling time, and shows a relation ship with both the parent cells and daughter cells generation times. At high dilution rates two oscillatory regimens, with different periods, are observed. The analysis of the budding index shows a marked degree of synchronization of the culture, however significant differences, both in phase and in amplitude, are ob served if the budding index of parent cells and of daughter cells are considered separately. The complex changes of the cell population are clearly demonstrated by the continuous and periodic modification of both cell volume distributions and protein distributions. Ethanol is always accumulated before the drop of dissolved oxygen concentration and one of the peaks of budding index. We propose a model that explains the insurgence of these oscillation as a consequence of changes in cell cycle parameters due to alternate growth in glucose and in ethanol.     

Multiple stable states and hysteresis in continuous, oscillating cultures of budding yeast

The conditions that precede the onset of autonomous oscillations in continuous yeast cultures were studied in three different types of experiments. It was found that the final state of the culture depended on the protocol used to start up the reactor. Batch cultures, switched to continuous operation at different stages of the batch growth curve, all exhibited similar dynamics-ethanol depletion followed by autonomous oscillations. Small perturbations of the distribution of states in the reactor, achieved by addition of externally grown cells, were able to quench the oscillatory dynamics. Reaching the desired operating point by slow dilution rate changes gave rise to different final states, two oscillatory states and one steady state, depending on the rate of change in dilution rate. The multiplicity of stable states at a single operating point is not explained by any current distributed model and points toward a segregated mechanism of these oscillations.     

Physiological behaviour of Hanseniaspora guilliermondii in aerobic glucose-limited continuous cultures

The physiology of Hanseniaspora guilliermondii was studied under aerobic glucose-limited conditions using the accelerostat procedure (continuous acceleration of dilution rate) and classical chemostat cultures. By both cultivation techniques this yeast was found to be Crabtree-positive. Up to a dilution rate of 0.25 h(-1), glucose was completely metabolised into biomass, glycerol and carbon dioxide. Above this value, an increase in the dilution rate was accompanied by the production of other metabolites like ethanol, acetic and malic acids. Biomass yield during the purely oxidative growth was 0.49 g g(-1) and decreased to 0.26 g g(-1) for D=0.34 h(-1). A maximal specific ethanol production rate of 1.36 mmol g(-1) h(-1) and a maximal ethanol yield of 0.05 g g(-1) were achieved at D=0.34 h(-1).     

Involvement of a cell size control mechanism in the induction and maintenance of oscillations in continuous cultures of budding yeast

Spontaneous oscillations occur in glucose-limited continuous cultures of Saccharomyces cerevisiae under aerobic conditions. The oscillatory behavior is detectable as a periodic change of many bioparameters such as dissolved oxygen, ethanol production, biomass concentration, as well as cellular content of storage carbohydrates and is associated to a marked synchronization of the yeast population. These oscillations may be related to a periodic accumulation of ethanol produced by yeast in the culture medium.The addition of ethanol to oscillating yeast cultures supports this hypothesis: indeed, no effect was observed if ethanol was added when already present in the medium, while a marked phase oscillation shift was obtained when ethanol was added at any other time. Moreover, the addition of ethanol to a nonoscillating culture triggers new oscillations. An accurate analysis performed at the level of nonoscillating yeast populations perturbed by addition of ethanol showed that both the growth rate and the protein content required for cell division increased in the presence of mixed substrate (i.e., ethanol plus limiting glucose). A marked synchronization of the yeast population occurred when the added ethanol was exhausted and the culture resumed growth only on limiting glucose. A decrease of protein content required for cell division was also apparent. These experimental findings support a new model for spontaneous oscillations in yeast cultures in which the alternative growth on limiting glucose and limiting glucose plus ethanol modifies the critical protein content required for cell division.     

Hybrid filtering to rescue stable oscillations from noise-induced chaos in continuous cultures of budding yeast

In large-scale fermentations with oscillating microbial cultures, noise is commonly present in the feed stream(s). As this can destabilize the oscillations and even generate chaotic behavior, noise filters are employed. Here three types of filters were compared by applying them to a noise-affected continuous culture of Saccharomyces cerevisiae with chaotic oscillations. The aim was to restore the original noise-free stable oscillations. An extended Kalman filter was found to be the least efficient, a neural filter was better and a combined hybrid filter was the best. In addition, better filtering of noise was achieved in the dilution rate than in the oxygen mass transfer coefficient. These results suggest the use of hybrid filters with the dilution rate as the manipulated variable for bioreactor control.     

Predicting protein localization in budding yeast

MOTIVATION: Most of the existing methods in predicting protein subcellular location were used to deal with the cases limited within the scope from two to five localizations, and only a few of them can be effectively extended to cover the cases of 12-14 localizations. This is because the more the locations involved are, the poorer the success rate would be. Besides, some proteins may occur in several different subcellular locations, i.e. bear the feature of 'multiplex locations'. So far there is no method that can be used to effectively treat the difficult multiplex location problem. The present study was initiated in an attempt to address (1) how to efficiently identify the localization of a query protein among many possible subcellular locations, and (2) how to deal with the case of multiplex locations. RESULTS: By hybridizing gene ontology, functional domain and pseudo amino acid composition approaches, a new method has been developed that can be used to predict subcellular localization of proteins with multiplex location feature. A global analysis of the proteins in budding yeast classified into 22 locations was performed by jack-knife cross-validation with the new method. The overall success identification rate thus obtained is 70%. In contrast to this, the corresponding rates obtained by some other existing methods were only 13-14%, indicating that the new method is very powerful and promising. Furthermore, predictions were made for the four proteins whose localizations could not be determined by experiments, as well as for the 236 proteins whose localizations in budding yeast were ambiguous according to experimental observations. However, according to our predicted results, many of these 'ambiguous proteins' were found to have the same score and ranking for several different subcellular locations, implying that they may simultaneously exist, or move around, in these locations. This finding is intriguing because it reflects the dynamic feature of these proteins in a cell that may be associated with some special biological functions.     

Nutrient-regulated protein kinases in budding yeast

The ability of cells to react appropriately to nutritional cues is of fundamental importance, and in budding yeast, a small number of intracellular protein kinases, PKA, Snf1p/AMP-activated kinase, TOR, Gcn2p, and the cyclin-dependent kinase Pho85p have key roles. A recently characterized enzyme, PAS kinase, may be a new member of this group of nutritional transducers.     

Flow cytometry and cell cycle kinetics in continuous and fed-batch fermentations of budding yeast.

Cell size distributions, obtained either as protein distribution by flow cytometry or as cell volume distribution by a Coulter counter, give relevant information about the growth conditions of populations of budding yeast Saccharomyces cerevisiae. We have previously found a good correlation between these distributions and the growth rate in continuous cultures (Ranzi et al., Biotechnol. Bioeng. 1986, 28, 185-190). We now present determinations of the protein distributions and cell volume distributions during different fed-batch fermentations performed with a simple on/off controller. Since during the fed-batch fermentation a true steady state is not obtained, the distributions continuously change with time, but nevertheless we observed a good correlation between the average of both distributions and the actual growth rate. The behavior of the cell size distributions can be interpreted on the basis of a two-threshold cell cycle model in which both the critical protein content at budding (Ps) and the critical protein content for cell division (Pm) are differently modulated by the growth rate. Additional findings will be presented showing that this model can be used to successfully explain the insurgence and the maintenance of oscillatory states in continuous cultures.     

Lipid rafts in protein sorting and cell polarity in budding yeast Saccharomyces cerevisiae

Cellular membranes contain many types and species of lipids. One of the most important functional consequences of this heterogeneity is the existence of microdomains within the plane of the membrane. Sphingolipid acyl chains have the ability of forming tightly packed platforms together with sterols. These platforms or lipid rafts constitute segregation and sorting devices into which proteins specifically associate. In budding yeast, Saccharomyces cerevisiae, lipid rafts serve as sorting platforms for proteins destined to the cell surface. The segregation capacity of rafts also provides the basis for the polarization of proteins at the cell surface during mating. Here we discuss some recent findings that stress the role of lipid rafts as key players in yeast protein sorting and cell polarity.     

The distribution of chromatin in budding yeast cells

Summary and conclusions A critical examination of well fixed yeast cells killed at different states in the growth cycle shows that the distribution of chromatin in the yeast cell varies depending on the stage in the growth cycle. Our data support the view (1) that the spindle is intravacuolar, (2) that mitosis occurs on the spindle, (3) that the chromosomes spin out after mitosis to extend into the vacuole, (4) that a large nucleolus appears in the nuclear vacuole of rapidly growing wellnourshed cells, and (5) that in the presence of adequate amounts of phosphate and otherwise favorable conditions the chromosomes are covered with metaphosphate. This work has been supported by grants from the National Cancer Institute of the National Institutes of Health, Public Health Service C-2140 and from the Illinois Division of the American Cancer Society.     

Development of cell polarity in budding yeast

The development of cell polarity involves virtually every aspect of cell biology. Yeast are less complex than cells traditionally used for studies on cell polarity and are amendable to sophisticated genetic analysis. This has resulted in a growing number of molecular markers for yeast cell polarity and an increasingly well-defined progression of molecular events required for bud formation. Together, these factors provide a favorable context in which to understand how the interplay between a large number of processes can polarize a cell. Many genes required for morphogenesis have been identified, and genetic interactions provide evidence that the products of these genes function together. Studies on cell polarity development in S. cerevisiae have demonstrated a requirement for small GTP-binding proteins and have established functional relationships between temporally coincident events. With the continued identification and analysis of genes required for morphogenesis, and the pursuit of these studies on a cytological and biochemical level, studies on yeast will continue to contribute to our understanding of cell polarity development.     

Predicting 22 protein localizations in budding yeast

According to the recent experiments, proteins in budding yeast can be distinctly classified into 22 subcellular locations. Of these proteins, some bear the multi-locational feature, i.e., occur in more than one location. However, so far all the existing methods in predicting protein subcellular location were developed to deal with only the mono-locational case where a query protein is assumed to belong to one, and only one, subcellular location. To stimulate the development of subcellular location prediction, an augmentation procedure is formulated that will enable the existing methods to tackle the multi-locational problem as well. It has been observed thru a jackknife cross-validation test that the success rate obtained by the augmented GO-FnD-PseAA algorithm [BBRC 320 (2004) 1236] is overwhelmingly higher than those by the other augmented methods. It is anticipated that the augmented GO-FunD-PseAA predictor will become a very useful tool in predicting protein subcellular localization for both basic research and practical application.     

Bud-site selection and cell polarity in budding yeast

Polarized growth involves a hierarchy of events such as selection of the growth site, polarization of the cytoskeleton to the selected growth site, and transport of secretory vesicles containing components required for growth. The budding yeast Saccharomyces cerevisiae is an excellent model system for the study of polarized cell growth. A large number of proteins have been found to be involved in these processes, although their mechanisms of action are not yet well-understood. Recent discoveries have helped elucidate many of the processes involved in cell polarity and bud-site selection in yeast and have modified the traditional view of cellular structures involved in these processes. This review focuses on recent advances on the roles of cortical tags, GTPases and the cytoskeleton in the generation and maintenance of cell polarity in yeast.     

蛋白质的磷酸化作用和泛肽化降解作用与芽殖酵母细胞周期的调控

在芽殖酵母（Ｓａｃｃｈａｒｏｍｙｃｅｓｃｅｒｅｖｉｓｉａｅ）细胞中，Ｇ１期的三种ｃｙｃｌｉｎｓ和Ｓ、Ｍ期的五种ｃｙｃｌｉｎｓ之周期性的合成和分解调节着Ｃｄｃ２８的活性，驱动细胞周期的正常运转。除了ＣＤＫ的磷酸化作用外，蛋白质的泛肽化降解作用间接或直接调控细胞周期：ＣＤＣ３４泛肽化途径通过降解Ｃｄｃ２８的专一抑制子而起始ＤＮＡ复制；ＡＰＣ泛肽化途径通过降解Ｍ期后期的抑制子和Ｍ期ｃｙｃｌｉｎｓ，使姐妹染色体分离和Ｍ期终止。     

A retention mechanism for distribution of mitochondria during cell division in budding yeast.

Mitochondria are indispensable for normal eukaryotic cell function. As they cannot be synthesized de novo and are self-replicating, mitochondria must be transferred from mother to daughter cells. Studies in the budding yeast Saccharomyces cerevisiae indicate that mitochondria enter the bud immediately after bud emergence, interact with the actin cytoskeleton for linear, polarized movement of mitochondria from mother to bud, but are equally distributed among mother and daughter cells [1] [2] [3]. It is not clear how the mother cell maintains its own supply of mitochondria. Here, we found that mother cells retain mitochondria by immobilization of some mitochondria in the 'retention zone', the base of the mother cell distal to the bud. Retention requires the actin cytoskeleton as mitochondria colocalized with actin cables in the retention zone, and mutations that perturb actin dynamics or actin-mitochondrial interactions produced retention defects. Our results support the model that equal distribution of mitochondria during cell division is a consequence of two actin-dependent processes: movement of some mitochondria into the daughter bud and immobilization of others in the mother cell.     

Automated image analysis of protein localization in budding yeast

MOTIVATION: The yeast Saccharomyces cerevisiae is the first eukaryotic organism to have its genome completely sequenced. Since then, several large-scale analyses of the yeast genome have provided extensive functional annotations of individual genes and proteins. One fundamental property of a protein is its subcellular localization, which provides critical information about how this protein works in a cell. An important project therefore was the creation of the yeast GFP fusion localization database by the University of California, San Francisco, USA (UCSF). This database provides localization data for 75% of the proteins believed to be encoded by the yeast genome. These proteins were classified into 22 distinct subcellular location categories by visual examination. Based on our past success at building automated systems to classify subcellular location patterns in mammalian cells, we sought to create a similar system for yeast. RESULTS: We developed computational methods to automatically analyze the images created by the UCSF yeast GFP fusion localization project. The system was trained to recognize the same location categories that were used in that study. We applied the system to 2640 images, and the system gave the same label as the previous assignments to 2139 images (81%). When only the highest confidence assignments were considered, 94.7% agreement was observed. Visual examination of the proteins for which the two approaches disagree suggests that at least some of the automated assignments may be more accurate. The automated method provides an objective, quantitative and repeatable assignment of protein locations that can be applied to new collections of yeast images (e.g. for different strains or the same strain under different conditions). It is also important to note that this performance could be achieved without requiring colocalization with any marker proteins. AVAILABILITY: The original images analyzed in this article are available at http://yeastgfp.ucsf.edu, and source code and results are available at http://murphylab.web.cmu.edu/software.