Project description:Here we describe the identification of a novel 37-kD actin monomer binding protein in budding yeast. This protein, which we named twinfilin, is composed of two cofilin-like regions. In our sequence database searches we also identified human, mouse, and Caenorhabditis elegans homologues of yeast twinfilin, suggesting that twinfilins form an evolutionarily conserved family of actin-binding proteins. Purified recombinant twinfilin prevents actin filament assembly by forming a 1:1 complex with actin monomers, and inhibits the nucleotide exchange reaction of actin monomers. Despite the sequence homology with the actin filament depolymerizing cofilin/actin-depolymerizing factor (ADF) proteins, our data suggests that twinfilin does not induce actin filament depolymerization. In yeast cells, a green fluorescent protein (GFP)-twinfilin fusion protein localizes primarily to cytoplasm, but also to cortical actin patches. Overexpression of the twinfilin gene (TWF1) results in depolarization of the cortical actin patches. A twf1 null mutation appears to result in increased assembly of cortical actin structures and is synthetically lethal with the yeast cofilin mutant cof1-22, shown previously to cause pronounced reduction in turnover of cortical actin filaments. Taken together, these results demonstrate that twinfilin is a novel, highly conserved actin monomer-sequestering protein involved in regulation of the cortical actin cytoskeleton.
Project description:Eukaryotic genome is organized in a set of chromosomes each of which consists of a chain of DNA and associated proteins. Processes involving DNA such as transcription, duplication, and repair, therefore, should be intrinsically related to the three-dimensional organization of the genome. In this article, we develop a computational model of the three-dimensional organization of the haploid genome of interphase budding yeast by regarding chromosomes as chains moving under the constraints of nuclear structure and chromatin-chromatin interactions. The simulated genome structure largely fluctuates with the diffusive movement of chromosomes. This fluctuation, however, is not completely random, as parts of chromosomes distribute in characteristic ways to form "territories" in the nucleus. By suitably taking account of constraints arising from the data of the chromosome-conformation-capture measurement, the model explains the observed fluorescence data of chromosome distributions and motions.
Project description:By combining astigmatism imaging with a dual-objective scheme, we improved the image resolution of stochastic optical reconstruction microscopy (STORM) and obtained <10-nm lateral resolution and <20-nm axial resolution when imaging biological specimens. Using this approach, we resolved individual actin filaments in cells and revealed three-dimensional ultrastructure of the actin cytoskeleton. We observed two vertically separated layers of actin networks with distinct structural organizations in sheet-like cell protrusions.
Project description:The cell cycle is the process by which eukaryotic cells replicate. Yeast cells cycle asynchronously with each cell in the population budding at a different time. Although there are several experimental approaches to synchronise cells, these usually work only in the short-term. Here, we build a cyber-genetic system to achieve long-term synchronisation of the cell population, by interfacing genetically modified yeast cells with a computer by means of microfluidics to dynamically change medium, and a microscope to estimate cell cycle phases of individual cells. The computer implements a controller algorithm to decide when, and for how long, to change the growth medium to synchronise the cell-cycle across the population. Our work builds upon solid theoretical foundations provided by Control Engineering. In addition to providing an avenue for yeast cell cycle synchronisation, our work shows that control engineering can be used to automatically steer complex biological processes towards desired behaviours similarly to what is currently done with robots and autonomous vehicles.
Project description:BackgroundParameter estimation from experimental data is critical for mathematical modeling of protein regulatory networks. For realistic networks with dozens of species and reactions, parameter estimation is an especially challenging task. In this study, we present an approach for parameter estimation that is effective in fitting a model of the budding yeast cell cycle (comprising 26 nonlinear ordinary differential equations containing 126 rate constants) to the experimentally observed phenotypes (viable or inviable) of 119 genetic strains carrying mutations of cell cycle genes.ResultsStarting from an initial guess of the parameter values, which correctly captures the phenotypes of only 72 genetic strains, our parameter estimation algorithm quickly improves the success rate of the model to 105-111 of the 119 strains. This success rate is comparable to the best values achieved by a skilled modeler manually choosing parameters over many weeks. The algorithm combines two search and optimization strategies. First, we use Latin hypercube sampling to explore a region surrounding the initial guess. From these samples, we choose ∼20 different sets of parameter values that correctly capture wild type viability. These sets form the starting generation of differential evolution that selects new parameter values that perform better in terms of their success rate in capturing phenotypes. In addition to producing highly successful combinations of parameter values, we analyze the results to determine the parameters that are most critical for matching experimental outcomes and the most competitive strains whose correct outcome with a given parameter vector forces numerous other strains to have incorrect outcomes. These "most critical parameters" and "most competitive strains" provide biological insights into the model. Conversely, the "least critical parameters" and "least competitive strains" suggest ways to reduce the computational complexity of the optimization.ConclusionsOur approach proves to be a useful tool to help systems biologists fit complex dynamical models to large experimental datasets. In the process of fitting the model to the data, the tool identifies suggestive correlations among aspects of the model and the data.
Project description:During cell division, aberrant DNA structures are detected by regulators called checkpoints that slow division to allow error correction. In addition to checkpoint-induced delay, it is widely assumed, though rarely shown, that merely slowing the cell cycle might allow more time for error detection and correction, thus resulting in a more stable genome. Fidelity by a slowed cell cycle might be independent of checkpoints. Here we tested the hypothesis that a slowed cell cycle stabilizes the genome, independent of checkpoints, in the budding yeast Saccharomyces cerevisiae We were led to this hypothesis when we identified a gene (ERV14, an ER cargo membrane protein) that when mutated, unexpectedly stabilized the genome, as measured by three different chromosome assays. After extensive studies of pathways rendered dysfunctional in erv14 mutant cells, we are led to the inference that no particular pathway is involved in stabilization, but rather the slowed cell cycle induced by erv14 stabilized the genome. We then demonstrated that, in genetic mutations and chemical treatments unrelated to ERV14, a slowed cell cycle indeed correlates with a more stable genome, even in checkpoint-proficient cells. Data suggest a delay in G2/M may commonly stabilize the genome. We conclude that chromosome errors are more rarely made or are more readily corrected when the cell cycle is slowed (even ∼15 min longer in an ∼100-min cell cycle). And, some chromosome errors may not signal checkpoint-mediated responses, or do not sufficiently signal to allow correction, and their correction benefits from this "time checkpoint."
Project description:Actin cables, bundles of actin filaments that align along the long axis of budding yeast, are crucial for establishment of cell polarity. We fused green fluorescent protein (GFP) to actin binding protein 140 (Abp140p) and visualized actin cable dynamics in living yeast. We detected two populations of actin cables: (i) bud-associated cables, which extend from the bud along the mother-bud axis, and (ii) randomly oriented cables, which are relatively short. Time-lapse imaging of Abp140p-GFP revealed an apparent increase in the length of bud-associated actin cables. Analysis of movement of Abp140p-GFP fiduciary marks on bud-associated cables and fluorescence loss in photobleaching experiments revealed that this apparent elongation occurs by assembly of new material at the end of the cable within the bud and movement of the opposite end of the cable toward the tip of the mother cell distal to the bud. The rate of extension of the tip of an elongating actin cable is 0.29 +/- 0.08 microm/s. Latrunculin A (Lat-A) treatment completely blocked this process. We also observed movement of randomly oriented cables around the cortex of cells at a rate of 0.59 +/- 0.14 microm/s. Mild treatment with Lat-A did not affect the velocity of movement of randomly oriented cables. However, Lat-A treatment did increase the number of randomly oriented, motile cables per cell. Our observations suggest that establishment of bud-associated actin cables during the cell cycle is accomplished not by realignment of existing cables but by assembly of new cables within the bud or bud neck, followed by elongation.
Project description:Coordination of cell cycle with metabolism exists in all cell types that grow by division. It serves to build a new cell, (i) fueling building blocks for the synthesis of proteins, nucleic acids, and membranes, and (ii) producing energy through glycolysis. Cyclin-dependent kinases (Cdks) play an essential role in this coordination, thereby in the regulation of cell division. Cdks are functional homologs across eukaryotes and are the engines that drive cell cycle events and the clocks that time them. Their function is counteracted by stoichiometric inhibitors; specifically, inhibitors of cyclin-cyclin dependent kinase (cyclin/Cdk) complexes allow for their activity at specific times. Here, we provide a new perspective about the yet unknown cell cycle mechanisms impacting on metabolism. We first investigated the effect of the mitotic cyclin/Cdk1 complex Cyclin B/Cdk1-functional homolog in mammalian cells of the budding yeast Clb2/Cdk1-on yeast metabolic enzymes of, or related to, the glycolysis pathway. Six glycolytic enzymes (Glk1, Hxk2, Pgi1, Fba1, Tdh1, and Pgk1) were subjected to in vitro Cdk-mediated phosphorylation assays. Glucose-6-phosphate dehydrogenase (Zwf1), the first enzyme in the pentose phosphate pathway that is important for NADPH production, and 6-phospho-fructo-2-kinase (Pfk27), which catalyzes fructose-2,6-bisphosphate synthesis, a key regulator of glycolysis, were also included in the study. We found that, among these metabolic enzymes, Fba1 and Pgk1 may be phosphorylated by Cdk1, in addition to the known Cdk1-mediated phosphorylation of Gph1. We then investigated the possible effect of Sic1, stoichiometric inhibitor of mitotic cyclin/Cdk1 complexes in budding yeast, on the activities of three most relevant glycolytic enzymes: Hxk2, Glk1, and Tdh1. We found that Sic1 may have a negative effect on Hxk2. Altogether, we reveal possible new routes, to be further explored, through which cell cycle may regulate cellular metabolism. Because of the functional homology of cyclin/Cdk complexes and their stoichiometric inhibitors across evolution, our findings may be relevant for the regulation of cell division in eukaryotes.
Project description:Budding yeast cells irreversibly commit to a new division cycle at a regulatory transition called Start. This essential decision-making step involves the activation of the SBF/MBF transcription factors. SBF/MBF promote expression of the G1 cyclins encoded by CLN1 and CLN2. Cln1,2 can activate their own expression by inactivating the Whi5 repressor of SBF/MBF. The resulting transcriptional positive feedback provides an appealing, but as yet unproven, candidate for generating irreversibility of Start. Here, we investigate the logic of the Start regulatory module by quantitative single-cell time-lapse microscopy, using strains in which expression of key regulators is efficiently controlled by changes of inducers in a microfluidic chamber. We show that Start activation is ultrasensitive to G1 cyclin. In the absence of CLN1,2-dependent positive feedback, we observe that Start transit is reversible, due to reactivation of the Whi5 transcriptional repressor. Introduction of the positive feedback loop makes Whi5 inactivation and Start activation irreversible, which therefore guarantees unidirectional entry into S phase. A simple mathematical model to describe G1 cyclin turn on at Start, entirely constrained by empirically measured parameters, shows that the experimentally measured ultrasensitivity and transcriptional positive feedback are necessary and sufficient dynamical characteristics to make the Start transition a bistable and irreversible switch. Our study thus demonstrates that Start irreversibility is a property that arises from the architecture of the system (Whi5/SBF/Cln2 loop), rather than the consequence of the regulation of a single component (e.g., irreversible protein degradation).
Project description:Budding yeast, Saccharomyces cerevisiae, is widely used as a model organism to study the genetics underlying eukaryotic cellular processes and growth critical to cancer development, such as cell division and cell cycle progression. The budding yeast cell cycle is also one of the best-studied dynamical systems owing to its thoroughly resolved genetics. However, the dynamics underlying the crucial cell cycle decision point called the START transition, at which the cell commits to a new round of DNA replication and cell division, are under-studied. The START machinery involves a central cyclin-dependent kinase; cyclins responsible for starting the transition, bud formation, and initiating DNA synthesis; and their transcriptional regulators. However, evidence has shown that the mechanism is more complicated than a simple irreversible transition switch. Activating a key transcription regulator SBF requires the phosphorylation of its inhibitor, Whi5, or an SBF/MBF monomeric component, Swi6, but not necessarily both. Also, the timing and mechanism of the inhibitor Whi5's nuclear export, while important, are not critical for the timing and execution of START. Therefore, there is a need for a consolidated model for the budding yeast START transition, reconciling regulatory and spatial dynamics. We built a detailed mathematical model (START-BYCC) for the START transition in the budding yeast cell cycle based on established molecular interactions and experimental phenotypes. START-BYCC recapitulates the underlying dynamics and correctly emulates key phenotypic traits of ~150 known START mutants, including regulation of size control, localization of inhibitor/transcription factor complexes, and the nutritional effects on size control. Such a detailed mechanistic understanding of the underlying dynamics gets us closer towards deconvoluting the aberrant cellular development in cancer.