The mammalian olfactory system is capable of detecting thousands of airborne chemicals.  Signal transduction, i.e. a process of transferring chemical energy into electrical impulses, is mediated by a G-protein coupled cAMP signaling cascade in which the binding of odorants to odor receptors results in activation of the cyclic nucleotide gated (CNG) channels. Recently another signaling ion channel, TRPM5 was identified in some olfactory sensory neurons with unknown function.  UBM students will use electrophysiological recordings and mathematical modeling to determine the dynamic contribution of these ion channels. The picture shows an olfactory sensory neuron labeled with olfactory marker protein and TRPM5.

   

 

The JAK/STAT signaling pathway in a simple epithelium: A model for understanding molecular interpretation of spatial gradients.

Research mentors: Michelle Starz-Gaiano (Biological Sciences), and Brad Peercy (Mathematics and Statistics)

 

The JAK/STAT signaling pathway plays a critical role in stem cells, immune function, and the progression of some cancers.  We are studying JAK/STAT signaling in the somatic epithelial layer of Drosophila ovaries, where graded pathway activation is refined to instruct certain cells to become motile (those labeled in green in the egg chamber picture) while other cells remain behind in the epithelium (labeled in red).  We are developing mathematical models to determine critical parameters in this signaling system.  Our goal is to understand the minimal biological components that can convert a gradient of information into binary activation of a molecular pathway. UBM students working on this project will use a combination of genetic, cell biological, and mathematical approaches to address this aim. The picture shows an egg chamber in which border cells, marked in green have migrated away from their starting site, the anterior epitheliumk, shown on the left by the red cells.

     

The mouse light response of intrinsically photosensitive retinal ganglion cells: A model for understanding the second messenger pathway.
Research mentors: Phyllis R. Robinson (Biological Sciences), and
Kathleen A. Hoffman (Mathematics and Statistics)

Modeling of light entrainment of the mammalian circadian clock requires input exclusively from the retina. This photo-response is unique and also expresses melanopsin, a novel vertebrate opsin, which is necessary for initiating the light response in these cells.  Among all known vertebrate opsins, melanopsin is unique. These light sensitive ganglions cells were just discovered 10 years ago and the biochemistry underlying the light response remains to be definitively elucidated. The goal of our joint research project is to model the light dependent depolarization. The drawing depicts the crystallized molecular structure of melanopsin.

 

 

Simulating the evolution of transcription factors and their binding sites.
Research mentors: Ivan Erill (Biological Sciences), Matthias Gobbert (Mathematics/Statistics)

Transcription factors govern the regulation of genes by binding to specific locations in the promoter region of genes, enhancing or repressing their transcription by the RNA-polymerase holoenzyme. The mechanisms by which transcription factors recognize their cognate binding sites in DNA remain obscure and many questions about the evolution of these genetic elements remain unaddressed. Here we propose the use of UMBC parallel computing facilities to simulate the evolution of virtual transcription factors operating on synthetic genomes in order to analyze the evolutionary constraints operating on transcription factors and their binding sites. A combination of experimental data and combinatorial approaches to simulate evolutionary processes can shed light on the nature and evolution of transcription factor-finding motifs like the one depicted in this picture.

 

Evaluating Parallel Approaches for Evolutionary Trees

Research Mentors: Kevin Omland (Biological Sciences), Matthias K. Gobbert (Mathematics/Statistics)

One of Charles Darwin's main visions was reconstructing a "Tree of Life" showing evolutionary relationships among all species on the planet. Recently, evolutionary biologists have been using new genomic data to reconstruct many parets of the tree of life. However, determining relationships among closely related species remains one of the greatest challenges, especially because closely related species have evolved very few species-specific differences in theirDNA sequences. Our research group is using multiple gene regions from different parts of the genome to reconstruct these evolutionary family trees - phylogenies. Many new "species tree" algorithms have been developed to analyze such data for recently diverged species. We work on a genus of birds that has thirty species, plus multiple subspecies. Some of the new programs that we are using (e.g., BEST) require weeks to run on computer clusters for just five or ten species. To scale up our analyses to fifty or more species and subspecies, we need much more computationally efficient approaches, including parallelization. A newer perogram (*BEAST), which may allow parallel analyses, has just been released.