A double flow cytometric tag allows tracking of the dynamics of cell cycle progression of newborn Saccharomyces cerevisiae cells during balanced exponential growth

A Short-Term Advantage for Syngamy in the Origin of Eukaryotic Sex: Effects of Cell Fusion on Cell Cycle Duration and Other Effects Related to the Duration of the Cell Cycle-Relationship between Cell Growth Curve and the Optimal Size of the Species, and Circadian Cell Cycle in Photosynthetic Unicellular Organisms

The origin of sex is becoming a vexatious issue for Evolutionary Biology. Numerous hypotheses have been proposed, based on the genetic effects of sex, on trophic effects or on the formation of cysts and syncytia. Our approach addresses the change in cell cycle duration which would cause cell fusion. Several results are obtained through graphical and mathematical analysis and computer simulations. (1) In poor environments, cell fusion would be an advantageous strategy, as fusion between cells of different size shortens the cycle of the smaller cell (relative to the asexual cycle), and the majority of mergers would occur between cells of different sizes. (2) The easiest-to-evolve regulation of cell proliferation (sexual/asexual) would be by modifying the checkpoints of the cell cycle. (3) A regulation of this kind would have required the existence of the G2 phase, and sex could thus be the cause of the appearance of this phase. Regarding cell cycle, (4) the exponential curve is the only cell growth curve that has no effect on the optimal cell size in unicellular species; (5) the existence of a plateau with no growth at the end of the cell cycle explains the circadian cell cycle observed in unicellular algae.

Cell growth and cell cycle in Saccharomyces cerevisiae: basic regulatory design and protein-protein interaction network

In this review we summarize the major connections between cell growth and cell cycle in the model eukaryote Saccharomyces cerevisiae. In S. cerevisiae regulation of cell cycle progression is achieved predominantly during a narrow interval in the late G1 phase known as START (Pringle and Hartwell, 1981). At START a yeast cell integrates environmental and internal signals (such as nutrient availability, presence of pheromone, attainment of a critical size, status of the metabolic machinery) and decides whether to enter a new cell cycle or to undertake an alternative developmental program. Several signaling pathways, that act to connect the nutritional status to cellular actions, are briefly outlined. A Growth & Cycle interaction network has been manually curated. More than one fifth of the edges within the Growth & Cycle network connect Growth and Cycle proteins, indicating a strong interconnection between the processes of cell growth and cell cycle. The backbone of the Growth & Cycle network is composed of middle-degree nodes suggesting that it shares some properties with HOT networks. The development of multi-scale modeling and simulation analysis will help to elucidate relevant central features of growth and cycle as well as to identify their system-level properties. Confident collaborative efforts involving different expertises will allow to construct consensus, integrated models effectively linking the processes of cell growth and cell cycle, ultimately contributing to shed more light also on diseases in which an altered proliferation ability is observed, such as cancer.

Systems biology of the cell cycle of Saccharomyces cerevisiae: From network mining to system-level properties

Following a brief description of the operational procedures of systems biology (SB), the cell cycle of budding yeast is discussed as a successful example of a top-down SB analysis. After the reconstruction of the steps that have led to the identification of a sizer plus timer network in the G1 to S transition, it is shown that basic functions of the cell cycle (the setting of the critical cell size and the accuracy of DNA replication) are system-level properties, detected only by integrating molecular analysis with modelling and simulation of their underlying networks. A detailed network structure of a second relevant regulatory step of the cell cycle, the exit from mitosis, derived from extensive data mining, is constructed and discussed. To reach a quantitative understanding of how nutrients control, through signalling, metabolism and transcription, cell growth and cycle is a very relevant aim of SB. Since we know that about 900 gene products are required for cell cycle execution and control in budding yeast, it is quite clear that a purely systematic approach would require too much time. Therefore lines for a modular SB approach, which prioritises molecular and computational investigations for faster cell cycle understanding, are proposed. The relevance of the insight coming from the cell cycle SB studies in developing a new framework for tackling very complex biological processes, such as cancer and aging, is discussed.

Analysis and modeling of growing budding yeast populations at the single cell level

Model organisms and in particular the budding yeast Saccharomyces cerevisiae have been instrumental in advancing our understanding of cell cycle progression. The asymmetric division of the budding yeast and the tight coupling between cell growth and division have challenged the theoretical understanding of the cell size structure of growing yeast populations. Past efforts have centered on modeling the steady-state theoretical age distribution for asymmetric division from which a cell size distribution can be derived assuming dispersion of cell size within each age class. Different developments, especially in the field of flow cytometry, allowed the determination of a number of cellular properties and their joint distributions for the entire population and the different subpopulations as well. A new rigorous framework for modeling directly the dynamics of size distributions of structured yeast populations has been proposed, which readily extends to modeling of more complex conditions, such as transient growth. Literature on the structure of growing yeast populations and modeling of cell cycle progression is reviewed.

Dynamics and design principles of a basic regulatory architecture controlling metabolic pathways

The dynamic features of a genetic network's response to environmental fluctuations represent essential functional specifications and thus may constrain the possible choices of network architecture and kinetic parameters. To explore the connection between dynamics and network design, we have analyzed a general regulatory architecture that is commonly found in many metabolic pathways. Such architecture is characterized by a dual control mechanism, with end product feedback inhibition and transcriptional regulation mediated by an intermediate metabolite. As a case study, we measured with high temporal resolution the induction profiles of the enzymes in the leucine biosynthetic pathway in response to leucine depletion, using an automated system for monitoring protein expression levels in single cells. All the genes in the pathway are known to be coregulated by the same transcription factors, but we observed drastically different dynamic responses for enzymes upstream and immediately downstream of the key control point—the intermediate metabolite α-isopropylmalate (αIPM), which couples metabolic activity to transcriptional regulation. Analysis based on genetic perturbations suggests that the observed dynamics are due to differential regulation by the leucine branch-specific transcription factor Leu3, and that the downstream enzymes are strictly controlled and highly expressed only when αIPM is available. These observations allow us to build a simplified mathematical model that accounts for the observed dynamics and can correctly predict the pathway's response to new perturbations. Our model also suggests that transient dynamics and steady state can be separately tuned and that the high induction levels of the downstream enzymes are necessary for fast leucine recovery. It is likely that principles emerging from this work can reveal how gene regulation has evolved to optimize performance in other metabolic pathways with similar architecture.

Single-cell organisms must constantly adjust their gene expression programs to survive in a changing environment. Interactions between different molecules form a regulatory network to mediate these changes. While the network connections are often known, figuring out how the network responds dynamically by looking at a static picture of its structure presents a significant challenge. Measuring the response at a finer time scales could reveal the link between the network's function and its structure. The architecture of the system we studied in this work—the leucine biosynthesis pathway in yeast—is shared by other metabolic pathways: a metabolic intermediate binds to a transcription factor to activate the pathway genes, creating an intricate feedback structure that links metabolism with gene expression. We measured protein abundance at high temporal resolution for genes in this pathway in response to leucine depletion and studied the effects of various genetic perturbations on gene expression dynamics. Our measurements and theoretical modeling show that only the genes immediately downstream from the intermediate are highly regulated by the metabolite, a feature that is essential to fast recovery from leucine depletion. Since the architecture we studied is common, we believe that our work may lead to general principles governing the dynamics of gene expression in other metabolic pathways.

A quantitative, high-temporal resolution study of gene induction in a metabolic pathway reveals an intricate connection between the regulatory architecture and the dynamic response of the system, pointing to possible principles underlying the design of these pathways.

Optimization of yeast cell cycle analysis and morphological characterization by multispectral imaging flow cytometry

Budding yeast Saccharoymyces cerevisiae is a powerful model system for analyzing eukaryotic cell cycle regulation. Yeast cell cycle analysis is typically performed by visual analysis or flow cytometry, and both have limitations in the scope and accuracy of data obtained. This study demonstrates how multispectral imaging flow cytometry (MIFC) provides precise quantitation of cell cycle distribution and morphological phenotypes of yeast cells in flow. Cell cycle analysis of wild-type yeast, nap1Delta, and yeast overexpressing NAP1, was performed visually, by flow cytometry and by MIFC. Quantitative morphological analysis employed measurements of cellular length, thickness, and aspect ratio in an algorithm to calculate a novel feature, bud length. MIFC demonstrated reliable quantification of the yeast cell cycle compared to morphological and flow cytometric analyses. By employing this technique, we observed both the G2/M delay and elongated buds previously described in the nap1Delta strain. Using MIFC, we demonstrate that overexpression of NAP1 causes elongated buds yet only a minor disruption in the cell cycle. The different effects of NAP1 expression level on cell cycle and morphology suggests that these phenotypes are independent. Unlike conventional yeast flow cytometry, MIFC generates complete cell cycle profiles and concurrently offers multiple parameters for morphological analysis.

Morphologically-structured models of growing budding yeast populations

It has been well recognized that many key aspects of cell cycle regulation are encoded into the size distributions of growing budding yeast populations due to the tight coupling between cell growth and cell division present in this organism. Several attempts have been made to model the cell size distribution of growing yeast populations in order to obtain insight on the underlying control mechanisms, but most were based on the age structure of asymmetrically dividing populations. Here we propose a new framework that couples a morphologically-structured representation of the population with population balance theory to formulate a dynamic model for the size distribution of growing yeast populations. An advantage of the presented framework is that it allows derivation of simpler models that are directly identifiable from experiments. We show how such models can be derived from the general framework and demonstrate their utility in analyzing yeast population data. Finally, by employing a recently proposed numerical scheme, we proceed to integrate numerically the full distributed model to provide predictions of dynamics of the cell size structure of growing yeast populations.

SFP1 is involved in cell size modulation in respiro-fermentative growth conditions

Saccharomyces cerevisiae grows fast on glucose, while growth slows down on ethanol as cells move from glucose fermentation to oxidative metabolism. The type of carbon source influences both the specific growth rate and cell cycle progression, as well as cell size. Yeast cells grown on glucose have a larger size than cells grown on ethanol. Here, we analysed the behaviour of a sfp1 null mutant during balanced and transitory states of growth in batch in response to changes in the growth medium carbon sources. In a screening for mutants affected in cell size at Start, SFP1 has been identified as a gene whose deletion caused one of the smallest whi phenotype. Findings presented in this work indicate that in the sfp1 null mutant the reduction in cell size is not only a consequence of the reduced growth rate but it is tightly linked to the cellular metabolism. The SFP1 gene product is required to sustain the increase of both rRNA and protein content that in wild-type cells takes place in respiro-fermentative growth conditions, while it seems dispensable for growth on non-fermentable carbon sources. It follows that sfp1 cells growing on ethanol have a larger size than cells growing on glucose and, noticeably, the former enter the S phase with a critical cell size higher than the latter. These features, combined with the role of Sfp1p as a transcriptional factor, suggest that Sfp1p could be an important element in the control of the cell size modulated by nutrients.

Affinity of singleS. cerevisiaecells to 2-NBDglucose under changing substrate concentrations

BACKGROUND

Saccharomyces cerevisiae is a widely employed microorganism in biotechnological processes. Since proliferation and product formation depend on the capacity of the cell to access and metabolize a carbon source, a technique was developed to enable for analyzing the S. cerevisiae H155 cells' affinity to extracellular glucose concentrations.

METHODS

The fluorescent glucose analogue 2-NBDglucose was employed as a functional parameter to analyze the cells' affinity to glucose. Structural parameters (proliferation, neutral lipid content, granularity, and cell size) were also investigated. Cells were grown both in batches and in chemostat regimes.

RESULTS

The 2-NBDglucose uptake in individual cells proceeds in a time- and concentration-dependent manner and is affected by respiratory and respirofermentative modes of growth. The process is inhibited by D-glucose, D-fructose, D-mannose, and sucrose, but not L-glucose, D-galactose or lactose; maltose is a weak inhibitor. The affinity of the individual cells to 2-NBDglucose was found to be high at low extracellular glucose concentrations, and weak at high concentrations. An additional, underlying pattern in the cells' affinity to glucose was detected, illustrated by the recurrent appearance of two subpopulations showing distinctly differing quantities of this substrate.

CONCLUSIONS

A multiparameter flow cytometry approach is presented that enables, for the first time, for analysis of the affinity of individual S. cerevisiae cells to glucose. Besides the adjustment of the yeast cell metabolism to extracellular glucose concentrations by altering their affinity to glucose, at least one further mechanism is clearly involved. Two subpopulations of cells were resolved, with different affinities not correlated with other cellular parameters measured.

Mutations of the CK2 phosphorylation site of Sic1 affect cell size and S-Cdk kinase activity in Saccharomyces cerevisiae

By sequence analysis we found an amino acid stretch centred on Serine201 matching a stringent CK2 consensus site within the C-terminal, inhibitory domain of Sic1. Here we show by direct mass spectrometry analysis that Sic1, but not a mutant protein whose CK2 phospho-acceptor site has been mutated to alanine, Sic1S201A, is actually phosphorylated in vitro by CK2 on Serine 201. Mutation of Serine 201 alters the coordination between growth and cell cycle progression. A significant increase of average protein content and of the average protein content at the onset of DNA synthesis is observed for exponentially growing cells harbouring the Sic1S201A protein. A strong reduction of the same parameters is observed in cells harbouring Sic1S201E. The deregulated coordination between cell size and cell cycle is also apparent at the level of S-Cdk activity.

Glucose metabolism and cell size in continuous cultures of Saccharomyces cerevisiae

A detailed analysis of the cell size, monitored as protein content, has been performed in glucose-limited continuous cultures, so as to obtain the values of the average protein content for various subpopulations at different cell cycle stages, as a function of the growth rate. Glucose metabolism appears to affect cell size, since there is an increase of the average protein content of the population when cells produce ethanol above the critical dilution rate. If the production of ethanol is forced at low growth rates by the addition of formate, the average protein content increases. These results indicate a link between glucose metabolism and cell size in budding yeast, as observed for mammalian cells.

Relating growth dynamics and glucoamylase excretion of individual Saccharomyces cerevisiae cells

We have developed a novel flow cytometric procedure that allows determinations of properties of protein excretion in the growth medium on a cell-by-cell basis in Saccharomyces cerevisiae. The procedure is based on labelling of a periplasmically secreted protein with antibodies conjugated to a fluorescent marker such as fluorescein isothiocyanate (FITC). The staining conditions did not perturb cell growth after resuspension of stained cells in growth medium. Decrease in fluorescence was found to correlate with excretion of glucoamylase into the growth medium. The analysis of the staining pattern over time provides information on the behaviour of individual cells belonging to different cell-cycle phases and can be used to calculate the specific excretion rate of the overall population.

Instrumentation of biotechnological processes

Modern bioprocesses are monitored by on-line sensing devices mounted either in situ or externally. In addition to sensor probes, more and more analytical subsystems are being exploited to monitor the state of a bioprocess on-line and in real time. Some of these subsystems deliver signals that are useful for documentation only, other, less delayed systems generate signals useful for closed loop process control. Various conventional and non-conventional monitoring instruments are evaluated; their usefulness, benefits and associated pitfalls are discussed.

Control by nutrients of growth and cell cycle progression in budding yeast, analyzed by double-tag flow cytometry

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.

Identification of different daughter and parent subpopulations in an asynchronously growing Saccharomyces cerevisiae population

Under all growth conditions, a growing Saccharomyces cerevisiae yeast population is extremely heterogeneous, since individual cells differ in their cell size; this is due to their position in the cell division cycle and their genealogical age. To gain insight into the structure of a growing yeast population, we used a recently developed flow cytometric approach which enables, in asynchronously growing S. cerevisiae populations, tagging of both the cell age and the protein content of individual cells. This approach enabled the identification of daughter cells belonging to different cell cycle positions (i.e. newborn, G1, S + G2 + M + G1*, and dividing), thus yielding information about the relative fraction in the whole population, cell size and variability. More limited information could be obtained for the parent subpopulation; however, we were able to identify and characterize the dividing parent cells. The coefficient of variation (CV) of the protein content distribution for the dividing parents (27) was much higher than the CV of dividing daughters (18). Further findings obtained indicated a large overlap between the cell protein content distributions of daughter and parent cells as well as between the protein content of cells of the same subpopulation but belonging to different stages of the cell division cycle. The analysis of these differences enables a better understanding of the complex structure of an asynchronously growing yeast population.