Investigating Transcription Factor Networks That Drive Biological Clocks and Oscillators

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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.





Kelliher, Christina Marie (2017). Investigating Transcription Factor Networks That Drive Biological Clocks and Oscillators. Dissertation, Duke University. Retrieved from


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.