Duke University | Howard Hughes Undergraduate Program

2009 VIP Program Projects

1. Cell Systems

As of April 23, 2009, both undergraduate positions in this team have been filled. 

In this 2009 VIP project, Drs. Steven Haase (Biology), Sayan Mukherjee (IGSP) and John Harer (Mathematics) will lead a VIP team to examine the role of the transcription network oscillator in controlling the cell cycle period.

In early embryonic systems, cells undergo very rapid cleavage divisions. The period of the cell division cycle is determined by the kinetics of synthesis and destruction of cyclin, however, at the point when zygotic transcription is activated, the length of the cell cycle is extended. One interpretation of this observation is that the cell-cycle period is guided by the cyclin/CDK oscillator in early cleavage embryos, but when zygotic transcription is activated, cell cycle events become entrained to a new oscillator.

A transcription network model shows that the length of time it takes to traverse the cell cycle would be determined by the combined time required to successively transcribe and translate transcription factors (TFs), and to assemble activating TF complexes (or disassemble repressive complexes) at each promoter.  If the transcription network plays a central role in regulating cell cycle period, it should be possible to change the period of oscillations by manipulating TF expression.  This can be done relatively easily in budding yeast using TF gene knockouts, promoter swaps, and constitutive or conditional expression of TF genes. Kinetic data will then be used to construct mathematical models that describe network dynamics and make experimentally testable predictions about the network's function as a cell-cycle oscillator.  Statistical and mathematical modeling with a strong computational component will be central to this project.

Related publications:
David A. Orlando, Charles Y. Lin, Allister Bernard, Edwin S. Iversen, Alexander J. Hartemink and Steven B. Haase. 2006. A Probabilistic Model for Cell Cycle Distributions in Synchrony Experiments. Molecular and Cellular Biology Vol 26, No. 6. p. 2456-2466. Mar. (2006)

Orlando, D.A., Lin, C.Y., Bernard, A., Wang, J.Y., Socolar, J.E., Iversen, E.S., Hartemink, A.J., and Haase, S.B. (2008). Global control of cell-cycle transcription by coupled CDK and network oscillators. Nature 453, 944-947

2.  Cell Signaling

As of April 23, 2009, the two undergraduate positions in this team have been filled.  

The long-term goal of this 2009 project, directed by Dr. Linchong You (Biomedical Engineering and IGSP) and Dr. Joseph Nevins (Molecular Genetics and Microbiology and IGSP), is to establish a computational and experimental framework for an in-depth view of signaling pathways central to mammalian cell cycle entry and, building on this foundation, to engineer synthetic gene circuits for therapeutic applications by reprogramming the cell cycle. Specifically, we use both mathematical modeling and cell biology experiments to investigate the major dynamics involved in mammalian cell cycle entry, focusing on regulation of the restriction point (R-point), which represents a threshold for commitment to entry into the cell cycle. Underscoring its critical importance, the R-point is deregulated in virtually all human tumors that confer cancer cells growth advantages.

3. Information Signaling and Processing

As of April 23, 2009 the two undergraduate positions in this team have been filled.   

This 2009 VIP project, directed by Dr. Leslie Collins (Electrical and Computer Engineering) and Dr. Debara Tucci (Surgery, Duke Medical Center), will enable students to apply signal processing concepts to address biological system challenges. These system challenges drive enabling technology research to develop and optimize sensor systems, which in turn requires new computational algorithms for sensor optimization. This team will address the challenge posed in the development of cochlear implants and, specifically, how sensing and processing can be integrated in a neural prosthetic system to optimally stimulate the implant that is designed to provide speech information. Students will build implants and, in the process, pursue research on the physiology and the mechanisms of electrical stimulation of the cochlea; develop computational models and evaluate how well the algorithms are extracting data; and investigate the theoretical, experimental, and ethical issues associated with the design of an implantable electrode array system.

Related publications:
Remus, J. J., Throckmorton, C. S., and Collins, L. M., Expediting the identification of impaired channels in cochlear implants via analysis of speech-based confusion matrices, in press, IEEE Trans. Biomedical Engineering, March, 2007.

Throckmorton, C. S., Kucukoglu, M. S., Remus, J. J., and Collins, L. M., Encoding fine frequency structure for improved speech recognition in cochlear implant subjects: a multiple carrier frequency algorithm, Hearing Research, 218, August, 2006, 30-42.


4. Modeling Biological Systems

As of April 23, 2009, both undergraduate positions in this team have been filled.  

The goal of the 2009 project, directed by Dr. Philip Benfey (Biology) and Dr. Uwe Ohler (Biostatistics & Bioinformatics) is to identify gene regulatory networks operating in roots of the model plant Arabidopsis thaliana at cell type resolution.  Computational work will focus on analyzing lllumina sequencing data to identify and quantify both known and novel miRNAs found in the root, and on utilizing ChIP-chip or ChIP-seq data to elucidate transcriptional targets.  Experimental work will focus on generating transcriptional and translational fusions to verify computational anayses and explore both transcription factor-transcription factor and transcription factor-miRNA promoter interactions.  The synthesis of these approaches will lead to putative network modules whose biological function can be investigated.
 

Related publications:
Brady et al. 2007.  A High-Resolution Root Spatiotemporal Map Reveals Dominant Expression Patterns.  Science 318: 801-806

Lee JY, Colinas J, Wang JY, Mace D, Ohler U and Benfey PN (2006) Transcriptional and post-transcriptional regulation of transcription factor expression in Arabidopsis roots. PNAS 103:6055-6

Mace DL, Lee JY, Twigg RW, Colinas J, Benfey PN and Ohler U. (2006) Quantification of transcription factor expression from Arabidopsis images. Bioinformatics.  22:e323-31.


5. Models for Genetics and Evolution of Complex Systems

As of April 23, 2009, both undergraduate positions have been filled.

This 2009 VIP project, directed by Dr. Frederik Nijhout (Biology) and Dr. Michael Reed (Mathematics), will focus on how real genes, biochemical systems and physiological systems interact to produce observed properties of living systems. The team will develop mathematical simulation models to describe the details of specific complex systems in which all components are known and in which the dynamics and kinetics have been studied experimentally. Previous projects have involved the mechanism of vitamin B deficiency, the effect of anticancer drugs, and the mechanism and rescue of acetaminophen toxicity. The challenges are to evaluate and combine data obtained from such fields as genetics, biochemistry, physiology, and clinical medicine into a single model system that can be used by experimenters and clinicians to test specific experimental or therapeutic interventions. The mathematical models developed are also used to deduce plausible scenarios for the evolution of the system, since complex systems do not come into existence fully formed; a mathematical model makes it possible to study scenarios for the piecewise addition and modification of components.

Related publications:

A mathematical model of glutathione metabolism. [2008] Reed MC, Thomas R, Pavisic J, Nijhout HF, James SJ, Ulrich CM. Theoretical Biology and Medical Modelling 5, 8 doi:10.1186/1742-4682-5-8.

Mathematical modeling of folate metabolism: Predicted effects of genetic polymorphisms on mechanisms and biomarkers relevant to carcinogenesis. [2008] Ulrich CM, Neuhouser M, Liu A, Boynton A, Gregory JF, Shane B, James SJ, Reed MC, Nijhout HF. Cancer Epidemiol. Biomark. Prevent. 17, 1822-1831.

In silico experimentation with a model of hepatic mitochondrial folate metabolism. [2006] Nijhout HF, Reed MC, Lam S-L, Gregory JF, Ulrich CM. Theoretical Biology and Medical Modeling, 3:40.