| Advisor : | KEVIN D. CORBETT | ||
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| Abstract Title : | Meiotic Chromosomal Crossover in Mammals is Regulated by HORMA-Domain Containing Proteins and Specific Binding Partners | ||
| Abstract : | Meiosis is a eukaryote-specific cell division process that gives rise to haploid gametes through very careful recognition and segregation of nearly identical copies of each chromosome (homologs) that an organism inherits from its two parents. Chromosomal crossovers, the exchange of genetic information through a series of sequence-specific recombination events, occur before the two homologs are segregated. Crossovers are intimately controlled, as errors in the process can lead to serious consequences, such as Down?s Syndrome or other serious gene mutations. HORMA domain-containing proteins (named after a conserved domain in the Hop1, Rev7p, and Mad2 protein families) are crucial for the regulation of proper chromosomal crossover and synapsis, the pairing of the homologs that is necessary for proper crossover formation. Still undetermined is how the meiotic HORMA domain-containing proteins, specifically mammalian HORMAD-1/2, interact with each other; the synaptonemal complex (proteins that drive synapsis between neighboring homologs); the AAA+ ATPase Trip13 that checks for completion of synapsis and recombination and dissociates HORMAD proteins from the chromosome axis; as well as the cohesin ring complexes that later regulate the separation of sister chromatids. We are reconstituting HORMAD1 and HORMAD2 as well as their known and putative binding partners in order to characterize their interactions in vitro. With the use of x-ray crystallography, we hope to resolve the structures of HORMAD1/2 and their supposed interacting partners as well. Determining the structure and function of these highly conserved meiotic regulators is critical for a complete understanding of the regulation of meiotic crossover, and may lead to medical interventions to reduce or eliminate a host of human genetic disorders and fertility syndromes | ||
| Advisor : | DR. MADELINE BUTLER | ||
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| Abstract Title : | Functional Identification of Mycobacteriophage Weiss13 | ||
| Abstract : | Mycobacteriophages are a group of viruses that infect and replicate within mycobacteria, such as Mycobacterium tuberculosis and Mycobacterium smegmatis. Thus, the study of phages with mycobacterial hosts has high potential for learning about and combatting mycobacterial infections. The goal of this study is to identify the functions of putative genes within the genome of the mycobacteriophage Weiss13, which was isolated on the UCSD campus. In doing so, we hope to provide a resource for practical applications of the mycobacteriophage. We first analyzed the sequenced genome of the mycobacteriophage Weiss13 and identified putative genes using DNA Master. We then utilized the BLASTp program to identify the potential functions and conserved domains of each gene. Based on the BLAST similarity, we identified a number of genes that encode proteins involved in viral structure and assembly, DNA replication, and cell lysis, as well as bacterial genes such as beta lactamase and DNA methylase. | ||
| Advisor : | DR. MADELINE BUTLER | ||
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| Abstract Title : | Validating Gene Expression through Proteomics of Weiss13 | ||
| Abstract : | Mass spectrometry is a powerful proteomics technique that we utilized to validate changes to start site calls for putative genes as well as to validate gene expression in the Weiss13 mycobacteriophage. We first used DNA Master to identify putative genes in the Weiss13 DNA sequence and used BLASTp to identify possible functions of those genes. We then digested crude and partially purified phage particles with trypsin and used mass spectrometry to separate the peptides by mass and charge. The peptide sequences were matched to the putative gene calls and only peptide results with a 95% confidence were considered. Several genes that had putative functions as structural proteins also had a high number of peptide hits, thus reinforcing their hypothesized functions. We were also able to validate longer gene calls for four genes that DNA Master had miscalled. | ||
| Advisor : | RUBEN ABAGYAN AND IRINA KUFAREVA | ||
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| Abstract Title : | Computational Design of Crystallizable, Chimeric G-Protein Coupled Receptors | ||
| Abstract : | G Protein-Coupled Receptors (GPCRs) are the largest family of cell surface receptors that are involved in signal transduction and constitute the targets of 30-40% of pharmaceutical drugs. GPCRs are integral membrane proteins that are highly unstable and prone to aggregation in detergent solutions, which makes them extremely difficult targets for structure determination. One of the strategies for improving the crystallization behavior of GPCRs involves receptor engineering by grafting a soluble protein such as thermostabilized by replacing apocytochrome b562RIL (bRIL), T4 lysozyme (T4L), or rubredoxin, in place of the intercellular loop 3 (ICL3). Although this approach has led to several GPCR structures, its application to new GPCRs requires a lot of iterations of trial and error in the search for specific insertion points and linker sequences that result in the most well-expressing, stable, and soluble construct. Intraprotein grafting can be done on a variety of integral membrane proteins three main ways: replacing a loop with two flexible linkers connected to a protein, extending anti-parallel beta strands into a protein, or extending anti-parallel alpha helices into a protein. Here we propose an algorithm for in silico design of optimal ICL3 fusions for any GPCR starting from its models or structures. The algorithm involves conformational sampling of the fusion construct in search of the lowest energy conformation, and ranking of the multiple fusion constructs by their predicted stability. A helical protein such as bRIL is used as a fusion partner. The algorithm rank-orders possible ICL3 fusion designs for each input GPCR model eliminating the need for cloning, purification, and characterization of hundreds of experimental constructs. When retrospectively benchmarked on existing structures, the algorithm robustly ranks near-native conformations for the crystallographic sequence above non-native conformations, even when applied to a non-cognate structure of the receptor. Moreover, it ranks the crystallographic sequence above non-native conformations, even when applied to a non-cognate structure of the receptor. Moreover, it ranks the crystallographic designs (which are experimentally proven to be stable and crystallizable) in the top 9% of the list including all possible design variants for XXX or the XXX receptors tested. The prospective application of the algorithm to chemokine receptor CXCR7 is underway. | ||