Dissecting the fission yeast regulatory network reveals phase-specific control elements of its cell cycle

Background  

Fission yeast Schizosaccharomyces pombe and budding yeast Saccharomyces cerevisiae are among the original model organisms in the study of the cell-division cycle. Unlike budding yeast, no large-scale regulatory network has been constructed for fission yeast. It has only been partially characterized. As a result, important regulatory cascades in budding yeast have no known or complete counterpart in fission yeast.     

YODA: Software to facilitate high-throughput analysis of chronological life span,growth rate,and survival in budding yeast

Background  

The budding yeast Saccharomyces cerevisiae is one of the most widely studied model organisms in aging-related science. Although several genetic modifiers of yeast longevity have been identified, the utility of this system for longevity studies has been limited by a lack of high-throughput assays for quantitatively measuring survival of individual yeast cells during aging.     

Germinating fission yeast spores delay in G1 in response to UV irradiation

Background  

Checkpoint mechanisms prevent cell cycle transitions until previous events have been completed or damaged DNA has been repaired. In fission yeast, checkpoint mechanisms are known to regulate entry into mitosis, but so far no checkpoint inhibiting S phase entry has been identified.     

Differential selection on gene translation efficiency between the filamentous fungus <Emphasis Type="Italic">Ashbya gossypii</Emphasis> and yeasts

Background  

The filamentous fungus Ashbya gossypii grows into a multicellular mycelium that is distinct from the unicellular morphology of its closely related yeast species. It has been proposed that genes important for cell cycle regulation play central roles for such phenotypic differences. Because A. gossypii shares an almost identical set of cell cycle genes with the typical yeast Saccharomyces cerevisiae, the differences might occur at the level of orthologous gene regulation. Codon usage patterns were compared to identify orthologous genes with different gene regulation between A. gossypii and nine closely related yeast species.     

Scalable Steady State Analysis of Boolean Biological Regulatory Networks

Background

Computing the long term behavior of regulatory and signaling networks is critical in understanding how biological functions take place in organisms. Steady states of these networks determine the activity levels of individual entities in the long run. Identifying all the steady states of these networks is difficult due to the state space explosion problem.

Methodology

In this paper, we propose a method for identifying all the steady states of Boolean regulatory and signaling networks accurately and efficiently. We build a mathematical model that allows pruning a large portion of the state space quickly without causing any false dismissals. For the remaining state space, which is typically very small compared to the whole state space, we develop a randomized traversal method that extracts the steady states. We estimate the number of steady states, and the expected behavior of individual genes and gene pairs in steady states in an online fashion. Also, we formulate a stopping criterion that terminates the traversal as soon as user supplied percentage of the results are returned with high confidence.

Conclusions

This method identifies the observed steady states of boolean biological networks computationally. Our algorithm successfully reported the G1 phases of both budding and fission yeast cell cycles. Besides, the experiments suggest that this method is useful in identifying co-expressed genes as well. By analyzing the steady state profile of Hedgehog network, we were able to find the highly co-expressed gene pair GL1-SMO together with other such pairs.

Availability

Source code of this work is available at http://bioinformatics.cise.ufl.edu/palSteady.html twocolumnfalse]     

Characterization of the minimum domain required for targeting budding yeast myosin II to the site of cell division

Background  

All eukaryotes with the exception of plants use an actomyosin ring to generate a constriction force at the site of cell division (cleavage furrow) during mitosis and meiosis. The structure and filament forming abilities located in the C-terminal or tail region of one of the main components, myosin II, are important for localising the molecule to the contractile ring (CR) during cytokinesis. However, it remains poorly understood how myosin II is recruited to the site of cell division and how this recruitment relates to myosin filament assembly. Significant conservation between species of the components involved in cytokinesis, including those of the CR, allows the use of easily genetically manipulated organisms, such as budding yeast (Saccharomyces cerevisiae), in the study of cytokinesis. Budding yeast has a single myosin II protein, named Myo1. Unlike most other class II myosins, the tail of Myo1 has an irregular coiled coil. In this report we use molecular genetics, biochemistry and live cell imaging to characterize the minimum localisation domain (MLD) of budding yeast Myo1.     

Screening the Budding Yeast Genome Reveals Unique Factors Affecting K2 Toxin Susceptibility

Background

Understanding how biotoxins kill cells is of prime importance in biomedicine and the food industry. The budding yeast (S. cerevisiae) killers serve as a convenient model to study the activity of biotoxins consistently supplying with significant insights into the basic mechanisms of virus-host cell interactions and toxin entry into eukaryotic target cells. K1 and K2 toxins are active at the cell wall, leading to the disruption of the plasma membrane and subsequent cell death by ion leakage. K28 toxin is active in the cell nucleus, blocking DNA synthesis and cell cycle progression, thereby triggering apoptosis. Genome-wide screens in the budding yeast S. cerevisiae identified several hundred effectors of K1 and K28 toxins. Surprisingly, no such screen had been performed for K2 toxin, the most frequent killer toxin among industrial budding yeasts.

Principal Findings

We conducted several concurrent genome-wide screens in S. cerevisiae and identified 332 novel K2 toxin effectors. The effectors involved in K2 resistance and hypersensitivity largely map in distinct cellular pathways, including cell wall and plasma membrane structure/biogenesis and mitochondrial function for K2 resistance, and cell wall stress signaling and ion/pH homeostasis for K2 hypersensitivity. 70% of K2 effectors are different from those involved in K1 or K28 susceptibility.

Significance

Our work demonstrates that despite the fact that K1 and K2 toxins share some aspects of their killing strategies, they largely rely on different sets of effectors. Since the vast majority of the host factors identified here is exclusively active towards K2, we conclude that cells have acquired a specific K2 toxin effectors set. Our work thus indicates that K1 and K2 have elaborated different biological pathways and provides a first step towards the detailed characterization of K2 mode of action.     

A Stochastic Model Correctly Predicts Changes in Budding Yeast Cell Cycle Dynamics upon Periodic Expression of CLN2

In this study, we focus on a recent stochastic budding yeast cell cycle model. First, we estimate the model parameters using extensive data sets: phenotypes of 110 genetic strains, single cell statistics of wild type and cln3 strains. Optimization of stochastic model parameters is achieved by an automated algorithm we recently used for a deterministic cell cycle model. Next, in order to test the predictive ability of the stochastic model, we focus on a recent experimental study in which forced periodic expression of CLN2 cyclin (driven by MET3 promoter in cln3 background) has been used to synchronize budding yeast cell colonies. We demonstrate that the model correctly predicts the experimentally observed synchronization levels and cell cycle statistics of mother and daughter cells under various experimental conditions (numerical data that is not enforced in parameter optimization), in addition to correctly predicting the qualitative changes in size control due to forced CLN2 expression. Our model also generates a novel prediction: under frequent CLN2 expression pulses, G1 phase duration is bimodal among small-born cells. These cells originate from daughters with extended budded periods due to size control during the budded period. This novel prediction and the experimental trends captured by the model illustrate the interplay between cell cycle dynamics, synchronization of cell colonies, and size control in budding yeast.     

Improved Flow Cytometric Analysis of the Budding Yeast Cell Cycle

The budding yeast, Saccharomyces cerevisiae has been a remarkably useful model system for the study of eukaryotic cell cycle regulation. Flow cytometric analysis of DNA content in budding yeast has become a standard tool for the analysis of cell cycle progression. However, popular protocols utilizing the DNA binding dye, propidium iodide, suffer from a number of drawbacks that confound accurate analysis by flow cytometry. Here we show the utility of the DNA binding dye, SYTOX Green, in the cell cycle analysis of yeast. Samples analyzed using SYTOX Green exhibited better coefficients of variation, improved linearity between DNA content and fluorescence, and decreased peak drift associated with changes in dye concentration, growth conditions or cell size.

Key Words:

Flow cytometry, Cell cycle, Saccharomyces cerevisiae, SYTOX Green, Propidium iodide     

Logical analysis of the budding yeast cell cycle

The budding yeast Saccharomyces cerevisiae is a model organism that is commonly used to investigate control of the eukaryotic cell cycle. Moreover, because of the extensive experimental data on wild type and mutant phenotypes, it is also particularly suitable for mathematical modelling and analysis. Here, I present a new Boolean model of the budding yeast cell cycle. This model is consistent with a wide range of wild type and mutant phenotypes and shows remarkable robustness against perturbations, both to reaction times and the states of component genes/proteins. Because of its simple logical nature, the model is suitable for sub-network analysis, which can be used to identify a four node core regulatory circuit underlying cell cycle regulation. Sub-network analysis can also be used to identify key sub-dynamics that are essential for viable cell cycle control, as well as identifying the sub-dynamics that are most variable between different mutants.     

Molecular basis of cell integrity and morphogenesis in Saccharomyces cerevisiae.

In fungi and many other organisms, a thick outer cell wall is responsible for determining the shape of the cell and for maintaining its integrity. The budding yeast Saccharomyces cerevisiae has been a useful model organism for the study of cell wall synthesis, and over the past few decades, many aspects of the composition, structure, and enzymology of the cell wall have been elucidated. The cell wall of budding yeasts is a complex and dynamic structure; its arrangement alters as the cell grows, and its composition changes in response to different environmental conditions and at different times during the yeast life cycle. In the past few years, we have witnessed a profilic genetic and molecular characterization of some key aspects of cell wall polymer synthesis and hydrolysis in the budding yeast. Furthermore, this organism has been the target of numerous recent studies on the topic of morphogenesis, which have had an enormous impact on our understanding of the intracellular events that participate in directed cell wall synthesis. A number of components that direct polarized secretion, including those involved in assembly and organization of the actin cytoskeleton, secretory pathways, and a series of novel signal transduction systems and regulatory components have been identified. Analysis of these different components has suggested pathways by which polarized secretion is directed and controlled. Our aim is to offer an overall view of the current understanding of cell wall dynamics and of the complex network that controls polarized growth at particular stages of the budding yeast cell cycle and life cycle.     

The terminal region of the E. coli chromosome localises at the periphery of the nucleoid

Background  

Bacterial chromosomes are organised into a compact and dynamic structures termed nucleoids. Cytological studies in model rod-shaped bacteria show that the different regions of the chromosome display distinct and specific sub-cellular positioning and choreographies during the course of the cell cycle. The localisation of chromosome loci along the length of the cell has been described. However, positioning of loci across the width of the cell has not been determined.