Transient responses of budding yeast populations

The unequal-division model for budding yeast is used to formulate a population-balance model for the transient behavior of populations of these organisms. The model consists of linear partial differential equations coupled through algebraic equations. It is shown how the solution of this system of equations can be obtained in a systematic stepwise fashion. The special case of a population subjected to a step change in growth rate is described in some detail, and solutions for two special cases are determined for transients following an age-distribution perturbation. It is shown how experimental data on transient behavior of a cell population can yield information on single-cell mass-synthesis kinetics and on the manner in which individual cells control certain critical parameters in the cell cycle.     

Steady-State growth of budding yeast populations in well-mixed continous-flow microbial reactors

A population-balance mathematical model of microbial growth in a flow reactor is formulated which incorporates an asymmetric-division, budding-cycle model of coordinated cell and nuclear division cycles for the budding yeast Saccharomyces cerevisiae. Analytical solutions are obtained for limiting nutrient and cell-number concentrations in the reactor as functions of basic cell cycle parameters. Frequency functions for cell mass and DNA content in the resident yeast population are also derived under different assumptions concerning cell mass and DNA synthesis and bud scar accumulation. These results, which correspond to experimentally observable medium and population variables, provide new bases for evaluating budding-yeast-cell cycle models and for deducing kinetics of mass and DNA synthesis in single cells growing in steady-state, asynchronous populations.     

Structural heterogeneity in populations of the budding yeast Saccharomyces cerevisiae.

Bud scar analysis integrated with mathematical analysis of DNA and protein distributions obtained by flow microfluorometry have been used to analyze the cell cycle of the budding yeast Saccharomyces cerevisiae. In populations of this yeast growing exponentially in batch at 30 degrees C on different carbon and nitrogen sources with duplication times between 75 and 314 min, the budded period is always shorter (approximately 5 to 10 min) than the sum of the S + G2 + M + G1* phases (determined by the Fried analysis of DNA distributions), and parent cells always show a prereplicative unbudded period. The analysis of protein distributions obtained by flow microfluorometry indicates that the protein level per cell required for bud emergence increases at each new generation of parent cells, as observed previously for cell volume. A wide heterogeneity of cell populations derives from this pattern of budding, since older (and less frequent) parent cells have shorter generation times and produce larger (and with shorter cycle times) daughter cells. A possible molecular mechanism for the observed increase with genealogical age of the critical protein level required for bud emergence is discussed.     

Towards understanding of the complex structure of growing yeast populations

In a growing Saccharomyces cerevisiae population, cell size is finely modulated according to both the chronological and genealogical ages. This generates the complex heterogeneous structure typical of budding yeast populations. In recent years, there has been a growing interest in developing mathematical models capable of faithfully describing population dynamics at the single cell level. A multistaged morphologically structured model has been lately proposed based on the population balance theory. The model was able to describe the dynamics of the generation of a heterogeneous growing yeast population starting from a sub-population of daughter unbudded cells. In this work, which aims at validating the model, the simulated experiment was performed by following the release of a homogeneous population of daughter unbudded cells. A biparametric flow cytometric approach allowed us to analyse the time course joint distribution of DNA and protein contents at the single cell level; this gave insights into the coupling between growth and cell cycle progression that generated the final population structure. The comparison between experimental and simulated size distributions revealed a strong agreement for some unexpected features as well. Therefore, the model can be considered as validated and extendable to more complex situations.     

Plasmid stability in budding yeast populations: Steady-state growth with selection pressure

Plasmid gene product accumulation in a cell population depends on the fraction of plasmid-containing cells and the distribution of single-cell plasmid content. These important population properties have been related to plasmid replication regulation and kinetics and to plasmid segregation rules at the single-cell level using population balance mathematical models. Budding yeast populations are considered in detail because of the practical potential of yeast host-vector systems and because of the model complications introduced by the asymmetric division pattern observed for Saccharomyces cerevisiae at all but the largest growth rates. Solutions are presented for several different reasonable models of plasmid replication and segregation. The results offer potential for identification of important qualitative features of yeast plasmid replication and of model parameter values from average and segregated experimental data on yeast populations.     

A note on modelling the dynamics of budding yeast populations using branching processes

A multitype branching process is proposed as a model for the behaviour of populations of the budding yeast Saccharomyces Cerevisiae. Using the idea of branching processes counted by random characteristics, we are able to obtain explicit expressions describing different aspects of the asymptotic composition of such populations. The main purpose of this note is to show that the branching process approach is an alternative to deterministic population models based on differential equation methods.Supported by the Swedish Natural Science Research Council     

The centromere of budding yeast

Stable maintenance of genetic information during meiosis and mitosis is dependent on accurate chromosome transmission. The centromere is a key component of the segregational machinery that couples chromosomes with the spindle apparatus. Most of what is known about the structure and function of the centromeres has been derived from studies on yeast cells. In Saccharomyces cerevisiae, the centromere DNA requirements for mitotic centromere function have been defined and some of the proteins required for an active complex have been identified. Centromere DNA and the centromere proteins form a complex that has been studied extensively at the chromatin level. Finally, recent findings suggest that assembly and activation of the centromere are integrated in tethe cell cycle.     

Sociobiology of the budding yeast

Social theory has provided a useful framework for research with microorganisms. Here I describe the advantages and possible risks of using a well-known model organism, the unicellular yeast Saccharomyces cerevisiae, for sociobiological research. I discuss the problems connected with clear classification of yeast behaviour based on the fitness-based Hamilton paradigm. Relevant traits include different types of communities, production of flocculins, invertase and toxins, and the presence of apoptosis.     

酵母菌与其“芽体”

从细胞生物学和分子生物学的层面对酵母菌的芽体形成过程及芽体与母体细胞的相关性作了综合评述。     

Clathrin-mediated endocytosis in budding yeast

Clathrin-mediated endocytosis in the budding yeast Saccharomyces cerevisiae involves the ordered recruitment, activity and disassembly of nearly 60 proteins at distinct sites on the plasma membrane. Two-color live-cell fluorescence microscopy has proven to be invaluable for in vivo analysis of endocytic proteins: identifying new components, determining the order of protein arrival and dissociation, and revealing even very subtle mutant phenotypes. Yeast genetics and functional genomics facilitate identification of complex interaction networks between endocytic proteins and their regulators. Quantitative datasets produced by these various analyses have made theoretical modeling possible. Here, we discuss recent findings on budding yeast endocytosis that have advanced our knowledge of how -60 endocytic proteins are recruited, perform their functions, are regulated by lipid and protein modifications, and are disassembled, all with remarkable regularity.     

Mitochondrial inheritance in budding yeast

During the past decade significant advances were made toward understanding the mechanism of mitochondrial inheritance in the yeast Saccharomyces cerevisiae . A combination of genetics, cell-free assays and microscopy has led to the discovery of a great number of components. These fall into three major categories: cytoskeletal elements, mitochondrial membrane components and regulatory proteins. These proteins mediate activities, including movement of mitochondria from mother cells to buds, segregation of mitochondria and mitochondrial DNA, and equal distribution of the organelle between mother cells and buds during yeast cell division.     

Single-cell phenomics in budding yeast

The demand for phenomics, a high-dimensional and high-throughput phenotyping method, has been increasing in many fields of biology. The budding yeast Saccharomyces cerevisiae, a unicellular model organism, provides an invaluable system for dissecting complex cellular processes using high-resolution phenotyping. Moreover, the addition of spatial and temporal attributes to subcellular structures based on microscopic images has rendered this cell phenotyping system more reliable and amenable to analysis. A well-designed experiment followed by appropriate multivariate analysis can yield a wealth of biological knowledge. Here we review recent advances in cell imaging and illustrate their broad applicability to eukaryotic cells by showing how these techniques have advanced our understanding of budding yeast.     

Individual-based and continuum models of growing cell populations: a comparison

In this paper we compare two alternative theoretical approaches for simulating the growth of cell aggregates in vitro: individual cell (agent)-based models and continuum models. We show by a quantitative analysis of both a biophysical agent-based and a continuum mechanical model that for densely packed aggregates the expansion of the cell population is dominated by cell proliferation controlled by mechanical stress. The biophysical agent-based model introduced earlier (Drasdo and Hoehme in Phys Biol 2:133-147, 2005) approximates each cell as an isotropic, homogeneous, elastic, spherical object parameterised by measurable biophysical and cell-biological quantities and has been shown by comparison to experimental findings to explain the growth patterns of dense monolayers and multicellular spheroids. Both models exhibit the same growth kinetics, with initial exponential growth of the population size and aggregate diameter followed by linear growth of the diameter and power-law growth of the cell population size. Very sparse monolayers can be explained by a very small or absent cell-cell adhesion and large random cell migration. In this case the expansion speed is not controlled by mechanical stress but by random cell migration and can be modelled by the Fisher-Kolmogorov-Petrovskii-Piskounov (FKPP) reaction-diffusion equation. The growth kinetics differs from that of densely packed aggregates in that the initial spread, as quantified by the radius of gyration, is diffusive. Since simulations of the lattice-free agent-based model in the case of very large random migration are too long to be practical, lattice-based cellular automaton (CA) models have to be used for a quantitative analysis of sparse monolayers. Analysis of these dense monolayers leads to the identification of a critical parameter of the CA model so that eventually a hierarchy of three model types (a detailed biophysical lattice-free model, a rule-based cellular automaton and a continuum approach) emerge which yield the same growth pattern for dense and sparse cell aggregates.     

Vacuolar dynamics in synchronously budding yeast

Summary A simple and rapid method for obtaining synchronously budding cultures of Saccharomyces cerevisiae is described. Synchronous cultures were started with homogeneous cell fractions isolated from exponentially growing cultures by isopycnic centrifugation in osmotically inactive media. The technique of fractionation is based on changes of cell density throughout the budding cycle. These changes are correlated with vacuolar changes observed in the light and electron microscope. During bud initiation the large vacuoles in late budding cells shrink and fragment into small vacuoles. Simultaneously the density of the cells increases. Later stages of the budding cycle are characterized by the distribution of the small vacuoles between mother and daughter cell, followed by their fusion and expansion, and by a decreasing density of the cells. The relative changes in cell density and dry weight and in the content of different macromolecules during the budding cycle suggest a cyclic change between utilization of endogenous and exogenous substrates. This is discussed in terms of a cyclic consumption and accumulation of vacuolar pools.     

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.     

Computer evaluation of network dynamics models with application to cell cycle control in budding yeast

Cellular processes are governed by complex networks of interacting genes and proteins. Theoretical molecular biologists attempt to describe these processes via mathematical models by writing biochemical reaction equations. Modellers are building increasingly larger and complex mathematical models to describe these cellular processes, making model evaluation a time consuming and difficult task. The authors describe an automatable process for model evaluation and a software system that implements this process. The software is adaptable to many types of models and is freely available along with all needed data files. The cell cycle control system for budding yeast is known in fine detail and constrained by more than 100 phenotypic observations in mutant strains. As an example, the authors apply their process to a model of cell cycle control in budding yeast containing dozens of regulatory equations and explaining nearly all of the known mutant phenotypes.     

The spindle cycle in budding yeast

The mitotic spindle of the budding yeast Saccharomyces cerevisiae will probably be the first such organelle to be understood in molecular detail. Here we describe the mitotic spindle cycle of budding yeast using electron-microscope-derived structures and dynamic live-cell imaging. Recent work has revealed that many general aspects of mitosis are conserved, making budding yeast an excellent model for the study of mitosis.