Browsing by Author "Haase, Steven B"

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Although it has been known for many years that B-cyclin/CDK complexes regulate the assembly of the mitotic spindle and entry into mitosis, the full complement of relevant CDK targets has not been identified. It has previously been shown in a variety of model systems that B-type cyclin/CDK complexes, kinesin-5 motors, and the SCFCdc4 ubiquitin ligase are required for the separation of spindle poles and assembly of a bipolar spindle. It has been suggested that in the budding yeast, Saccharomyces cerevisiae, B-type cyclin/CDK (Clb/Cdc28) complexes promote spindle pole separation by inhibiting the degradation of the kinesins-5 Kip1 and Cin8 by the anaphase-promoting complex (APCCdh1). I have determined, however, that the Kip1 and Cin8 proteins are actually present at wild-type levels in yeast in the absence of Clb/Cdc28 kinase activity. Here, I show that Kip1 and Cin8 are in vitro targets of Clb2/Cdc28, and that the mutation of conserved CDK phosphorylation sites on Kip1 inhibits spindle pole separation without affecting the protein's in vivo localization or abundance. Mass spectrometry analysis confirms that two CDK sites in the tail domain of Kip1 are phosphorylated in vivo. In addition, I have determined that Sic1, a Clb/Cdc28-specific inhibitor, is the SCFCdc4 target that inhibits spindle pole separation in cells lacking functional Cdc4. Based on these findings, I propose that Clb/Cdc28 drives spindle pole separation by direct phosphorylation of kinesin-5 motors.

In addition to the positive regulation of kinesin-5 function in spindle assembly, I have also found evidence that suggests CDK phosphorylation of kinesin-5 motors at different sites negatively regulates kinesin-5 activity to prevent premature spindle pole separation. I have also begun to characterize a novel putative role for the kinesins-5 in mitochondrial genome inheritance in S. cerevisiae that may also be regulated by CDK phosphorylation.

In the course of my dissertation research, I encountered problems with several established molecular biology tools used by yeast researchers that I have tried to address. I have constructed a set of 42 plasmid shuttle vectors based on the widely used pRS series for use in S. cerevisiae that can be propagated in the bacterium Escherichia coli. This set of pRSII plasmids includes new shuttle vectors that can be used with histidine and adenine auxotrophic laboratory yeast strains carrying mutations in the genes HIS2 and ADE1, respectively. My new pRSII plasmids also include updated versions of commonly used pRS plasmids from which common restriction sites that occur within their yeast-selectable biosynthetic marker genes have been removed in order to increase the availability of unique restriction sites within their polylinker regions. Hence, my pRSII plasmids are a complete set of integrating, centromere and 2 episomal plasmids with the biosynthetic marker genes ADE2, HIS3, TRP1, LEU2, URA3, HIS2 and ADE1 and a standardized selection of at least 16 unique restriction sites in their polylinkers. Additionally, I have expanded the range of drug selection options that can be used for PCR-mediated homologous replacement using pRS plasmid templates by replacing the G418-resistance kanMX4 cassette of pRS400 with MX4 cassettes encoding resistance to phleomycin, hygromycin B, nourseothricin and bialaphos. Finally, in the process of generating the new plasmids, I have determined several errors in existing publicly available sequences for several commonly used yeast plasmids. Using updated plasmid sequences, I constructed pRS plasmid backbones with a unique restriction site for inserting new markers in order to facilitate future expansion of the pRS/pRSII series.

The cell division cycle is the process in which the entirety of a cell's contents is duplicated completely and then equally segregated into two identical daughter cells. The order of the steps in the cell cycle must be followed with fidelity to guarantee two viable cells. Understanding the regulatory mechanisms that control cell-cycle events remains to be a fundamental question in cell biology. In this dissertation, I explore the mechanisms that coordinate and regulate cell-cycle progression in the budding yeast, Saccharomyces cerevisiae.

Cell-cycle events have been shown to be triggered by oscillations in the activity of cyclin dependent kinases (CDKs) when bound to cyclins. However, several studies have shown that some cell-cycle events, such as periodic transcription, can continue in the absence of CDK activity. How are periodic transcription and other cell-cycle events coupled to each other during a wild-type cell cycle? Currently, two models of cell-cycle regulation have been proposed. One model hypothesizes that oscillations in CDK activity controls the timing of cell-cycle events, including periodic transcription. The second model proposes that a transcription factor (TF) network oscillator controls the timing of cell-cycle events, via proper timing of gene expression, including cyclins. By measuring global gene expression dynamics in cells with persistent CDK activity, I show that periodic transcription continues. This result fits with the second model of cell-cycle regulation. Further, I show that during a wild-type cell cycle, checkpoints are responsible for arresting the bulk of periodic transcription. This finding adds a new layer of regulation to the second model, providing a mechanism that coordinates cell-cycle events with a TF network oscillator. Taken together, these data provide further insight into the regulation of the cell cycle.

Multiple biological processes occur in a time-dependent fashion. One of the most prevalent ways of regulating rhythmic biology is by controlling the timing and dosage of gene expression. Gene regulatory networks are groups of regulators that control target genes through multiple mechanisms, including direct DNA binding to alter expression dynamics, post-transcriptional activation, and protein degradation. Networks that control oscillating processes, such as circadian rhythms and cell cycles, have several hallmark properties, such as high interconnectedness and the disproportionate presence of certain patterns of regulator-target wiring (network motifs.) They are also self-sustaining and can control large suites of repeating, periodic gene expression.While circadian rhythms and cell cycles are fairly well-studied, there are still some prominent gaps in knowledge. Multiple parasites exhibit remarkably rhythmic life cycles, particularly the Plasmodium genus that causes malaria, but it is unknown whether these rhythms are driven by an oscillator within the parasite or are imposed by pre-existing host rhythms. In addition, the principles which guide oscillator gene regulatory network (oGRN) evolution are only partially understood, and lack examples of network-wide analysis on a finer scale. In this dissertation, I approach both questions primarily by examining the dynamics of periodic gene expression on a whole-transcriptome level. In Chapter 2, I investigate evidence for an innate oscillator in P. falciparum. I found multiple known hallmarks of oGRN-controlled gene expression—independent control of gene expression, conservation of ordering between strains, and genetic control of period length—and conclude that the parasite drives its own asexual reproduction cycle. In Chapter 3, I examine the dynamics of cell cycle-controlled transcription in two closely related species of the budding yeast Saccharomyces cerevisiae, S. paradoxus and S. uvarum. S. cerevisiae is a model organism for cell cycle research, providing a tractable system for studying oGRN evolution principles. I found intriguing differences between the species, including marked changes in the periodicity and gene expression levels of several known members of the core cell cycle oscillation machinery, warranting further study and validation. I conclude by discussing how studying oGRNs of both distantly- and closely-related species to model organisms furthers our understanding of governing evolutionary principles and our ability to form gene network hypotheses.

Cell division and growth are complex processes fundamental to all living organisms. In the budding yeast, Saccharomyces cerevisiae, these two processes are known to be coordinated with one another as a cell's mass must roughly double before division. Moreover, cell-cycle progression is dependent on cell size with smaller cells at birth generally taking more time in the cell cycle. This dependence is a signature of size control. Systems biology is an emerging field that emphasizes connections or dependencies between biological entities and processes over the characteristics of individual entities. Statistical models provide a quantitative framework for describing and analyzing these dependencies. In this dissertation, I take a statistical systems biology approach to study cell division and growth and the dependencies within and between these two processes, drawing on observations from richly informative microscope images and time-lapse movies. I review the current state of knowledge on these processes, highlighting key results and open questions from the biological literature. I then discuss my development of machine learning and statistical approaches to extract cell-cycle information from microscope images and to better characterize the cell-cycle progression of populations of cells. In addition, I analyze single cells to uncover correlation in cell-cycle progression, evaluate potential models of dependence between growth and division, and revisit classical assertions about budding yeast size control. This dissertation presents a unique perspective and approach towards comprehensive characterization of the coordination between growth and division.

The cell cycle is a series of ordered events that culminates in a single cell dividing into two daughter cells. These events must be properly coordinated to ensure the faithful passage of genetic material. How cell cycle events are carried out accurately remains a fundamental question in cell biology. In this dissertation, I investigate mechanisms orchestrating cell-cycle events in the yeast, Saccharomyces cerevisiae.

Cyclin dependent kinase (CDK) activity is thought to both form the fundamental cell-cycle oscillator and act as an effector of that oscillator, regulating cell-cycle events. By measuring transcript dynamics over time in cells lacking all CDK activity, I show that transcriptional oscillations are not dependent on CDK activity. This data indicates that CDKs do not form the underlying cell-cycle oscillator. I propose a model in which a transcription factor network rather than CDK activity forms the cell-cycle oscillator. In this model, CDKs are activated by the periodic transcription of cyclin genes and feedback on the network increasing the robustness of network oscillations in addition to regulating cell-cycle events.

I also investigate CDK-dependent and -independent mechanism regulating the duplication of the yeast centrosome, the spindle pole body (SPB). It is critical for the formation of a bipolar spindle in mitosis that the SPB duplicates once and only once per cell cycle. Through a combination of genetic and microscopic techniques I show that three distinct mechanisms regulate SPB duplication, ensuring its restriction to once per cell cycle.

Together, the data presented in this dissertation support a model in which CDKs, periodic transcription, and a TF-network oscillator are all important cell-cycle regulatory mechanisms that collaborate to regulate the intricate collection of events that constitute the cell cycle.

A periodic transcriptional program is a conserved feature of the eukaryotic cell cycle, yet there have been contrasting views on whether it is predominantly controlled by a CDK-APC/C network or a transcription factor (TF) network. I have sought to determine how the components in the CDK-APC/C network regulate the systems-level behaviors of the TF network. In this dissertation, I will establish these feedback regulations and propose an integrated model for the control of the cell-cycle transcriptional program in budding yeast Saccharomyces cerevisiae.

First, by re-examining the transcriptomic dynamics in cyclin mutants from previous reports drawing conflicting conclusions, I show that these data are fully compatible with an integrated model in which both CDK activities and the TF network contribute to the cell-cycle transcriptional program in wild-type cells. Using a quantitative model, I validate that network TFs can still retain their function even when transcript levels are substantially reduced in cyclin mutant cells. These results highlight the critical roles of both the TF network and the CDK feedbacks in generating the cell-cycle transcriptional program.

I have further dissected the precise roles of CDK-APC/C in regulating the TF network. Using an integrated genetic-genomic approach, I establish that G1 cyclin-CDKs stimulate network TFs both directly by inhibiting transcriptional corepressors Whi5/Stb1 and indirectly by inhibiting APC/C. Significantly, the dynamics of the cell-cycle transcriptional program can be greatly restored in a cdk1 apc whi5Δ stb1Δ quadruple mutant. These results suggest a model in which the TF network is inhibited by multiple mechanisms in early G1, which are relieved by CDKs to initiate global cell-cycle transcription after cell cycle commitment.

Next, I have sought to determine how multiple cycles of transcription persist in cells arrested with constitutively high CDK activity. I show that the transcriptional repressors for G1/S transcription are down-regulated by mitotic cyclin-CDKs, leading to prompt re-initiation of cell-cycle transcription when mitotic progression is genetically perturbed. Finally, I tested the hypothesis that timely mitotic exit prevents uncoupled dynamics of the cell-cycle transcriptional program. I characterized the transcriptomic dynamics in cells arrested at mitotic exit and showed that substantial transcript dynamics persist during the anaphase/telophase arrests. By comparing the transcriptome datasets from various mutants, I establish the physiological roles of APC/CCdc20 and mitotic exit pathways in regulating the activities of the TF network.

Taken together, this dissertation establishes the first mechanistic model for an integrated network that controls the robust cell-cycle transcriptional program in budding yeast.

Biological systems are highly dynamic, yet our temporal resolution of such

dynamical processes is often limited or difficult to test in the laboratory. The 24-hour

circadian rhythm and the approximately 75-minute cell cycle of a budding yeast cell are

both examples of dynamical processes that contain precisely ordered events, repeating

over each cycle. Organisms utilize such biological clock processes to time a particular

function. Dynamic cellular events are ordered, in part, by coordinated programs of

periodic gene expression. Up to 40% of all mouse genes are periodically expressed with

respect to the circadian cycle, and almost 20% of all yeast genes are periodic during the

cell cycle. Furthermore, more than half of the most frequently prescribed drugs in human

patients target an effector whose expression is under circadian control. Given the large

proportion of genes that are periodically expressed across different biological processes,

it is critically important to understand mechanisms that regulate dynamics in biology.

In this dissertation, I focus on two biological processes that are dynamic and are

not yet fully understood: the eukaryotic cell cycle and malaria parasite development.

Large programs of periodic genes emerge when these biological clock processes are

synchronized and profiled over time. Gene regulatory networks composed of

transcription factors, kinases, and other transcriptional regulators play a critical role in

generating periodicity in gene expression programs, ordering clock events, and

maintaining oscillations in subsequent cycles.

Many previous studies have profiled gene expression during the cell cycle in the

budding yeast Saccharomyces cerevisiae. I have added to this detailed body of work by

demonstrating that regulatory motifs involving negative feedback are required to

maintain normal gene expression levels. Additionally, I showed that many periodic

mRNAs are also periodically abundant at the protein level during the cell cycle. Both

projects provide evidence for the hypothesis that cell-cycle dynamics are driven by a

network of transcription factors with complex protein dynamics and with negative

feedback motifs. Using this ground truth cell-cycle network in S. cerevisiae, I next

performed a comparative transcriptomics study on cell-cycle genes in the less studied,

but more human health relevant fungal pathogen, Cryptococcus neoformans. This work

not only begins to identify a cell-cycle network in C. neoformans but also has

implications for future antifungal drug development, as some genes that are important

for fungal virulence were found to be expressed periodically during the cell cycle.

During infection, the human malaria parasite Plasmodium falciparum cyclically

develops and re-infects red blood cells. Many groups have shown that a very large

program of gene expression occurs during this red blood cell developmental cycle. In

this dissertation, I deploy the experimental and analysis tools that I used to characterize

the fungal cell cycle to ask if a network of transcription factors can explain

developmental gene expression dynamics and cycle period control in malaria.

Biological systems are highly dynamic to respond to environmental signals, grow,

and survive. As the application of genetics and genomics has moved toward

characterizing complex diseases, host-pathogen interactions, or even the cell cycle of a

single yeast cell, it has become increasingly clear that networks of interacting genes are

required to explain biological mechanisms. Results from this dissertation where I

investigate dynamic gene regulatory networks are broadly applicable to our

understanding of both basic molecular biology and of human infectious diseases.

Many important biological processes are temporally regulated. For periodic biological processes—such as the cell cycle, the circadian rhythm, and the malaria developmental cycle—temporal ordering of dynamic cellular events is controlled by large programs of periodic gene expression. A large portion of the genome oscillates in these dynamic biological processes (between 20 and 90 percent of the genome for the dynamic biological processes above). These coordinated programs of gene expression are controlled by gene regulatory networks (GRNs) consisting of transcription factors (TFs), kinases, and ubiquitin ligases. GRNs serve to generate and transmit a pulse of transcription, order temporal events, and maintain oscillations over multiple cycles. Historically, uncovering these regulatory mechanisms has taken coordinated effort over decades. An important challenge in biology today is accelerating the rate of discovery for these high-dimensional and complex biological phenomena. To this end, high-dimensional data and complex analytical tools are required. Time-series transcriptomic analyses have uncovered many important insights into dynamic processes, as they enable the characterization of gene-expression profiles for thousands of genes simultaneously. Furthermore, these time-series transcriptomic datasets can be used to infer GRN models from the data. However, these analyses can be complex. Many new computational tools have been developed to enable complex analyses. In Chapters 2, 3, and 4 of this dissertation, I describe methods for analysis of time-series transcriptomic data, network inference, and comparison across experiments. These computational tools were then applied to the Saccharomyces cerevisiae cell cycle to understand the regulation of the cell-cycle period in unfavorable growth conditions. The cell cycle is a vitally important dynamic biological process, which relies on multiple layers of regulation to ensure correct temporal ordering of cell-cycle events and the cell-cycle transcriptional program. Checkpoints monitor cell-cycle progression to ensure correct temporal ordering without catastrophic errors. This ordering is vital to guarantee faithful duplication of the cell. Cell-cycle progression is also affected by environmental conditions. In response to acute environmental stress, the S. cerevisiae cell cycle halts or pauses as a stress responsive and preparative mechanism. In response to chronic environmental stress, the cell-cycle period slows, providing mild stress-resistance. However, the mechanism underlying cell-cycle period control remains under debate. Early studies suggested that this regulation occurs in late G1 via a size or resource threshold at START. More recent studies show that cell-cycle period regulation can occur outside of G1 as well, indicating a need for other regulatory models. One such alternative model comes from the GRN models described above. Turning to other biological oscillators, the circadian period is controlled by the complex circadian GRN. The circadian period is tightly regulated to ensure a 24-hour cycle, matching the natural day-night cycle. However, the circadian period is altered upon experimental perturbation of GRN components, indicating that the circadian GRN controls the period of oscillation. Similarly, perturbation of the cell-cycle GRN alters the cell-cycle period, indicating that the cell-cycle period could similarly be controlled by its regulatory network. Using the computational tools outlined in Chapter 2, 3, and 4, Chapter 5 of this dissertation seeks to understand the mechanisms by which the cell-cycle period slows in response to unfavorable growth conditions. I propose a network model for cell-cycle period control, consisting of stress-regulatory interactions with the cell-cycle GRN. These regulatory models serve as experimental guidance, thus enabling more rapid identification of regulatory mechanisms for complex and high-dimensional biological processes.