Thesis (Ph. D.)--University of Chicago, Committe on Genetics, December 2003. / Includes bibliographical references. Also available on the Internet.

Thesis (M. Sc.)--York University, 2001. / Typescript. Includes bibliographical references (leaves 69-89). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pMQ67745.

published_or_final_version / Zoology / Doctoral / Doctor of Philosophy

published_or_final_version / Biological Sciences / Master / Master of Philosophy

Not available / text

Previously a t(2;14)(p13;q32) translocation was characterized in four unusually aggressive cases of B cell chronic lymphocytic leukemia (B-CLL). A gene located near the 2p13 breakpoint, B cell lymphoma/leukemia 11A (BCL11A), was shown to overexpress 3 isoforms (BCL11A-XL, L and S). Bcl11a knockout mice are severely impaired in B cell development at the early (pro-B) stage. I have further characterized BCL11A, focusing on the most abundant and evolutionarily conserved isoform, BCL11A-XL (XL). I demonstrated that XL resides in the nuclear matrix, is modified by ubiquitination, and is destabilized by B cell antigen receptor ligation. I identified domains within XL required for its localization within nuclear paraspeckles and for its transcriptional repression. While BCL11A-XL represses model promoters in non-B cells, its biologically relevant targets in B lymphocytes were unknown. I have identified and confirmed a number of XL targets which are both up- and down-regulated by XL over-expression in B cell lines. A number of these genes have been implicated in B cell function, including the V(D)J recombination activating (RAG) genes. Both RAG1 and RAG2 transcripts were up-regulated by XL. XL binds to the RAG1 promoter and RAG enhancer (Erag) in vivo as well as in vitro. Unexpectedly, XL repressed RAG1 transcription in non-B cells, indicating that additional B cell-specific factors are required for activation. Overexpression of XL in a V(D)J recombination-competent pre-B cell line markedly induced RAG expression and VDJ recombination. IRF4 and IRF8, transcription factors previously shown to be required for early B cell development, were also induced by BCL11A-XL. I propose that the early B cell progenitor block in Bcl11a knockout mice is, at least in part, a direct result of BCL11A-XL regulation of V(D)J recombination. Further experiments are required to establish how other XL targets promote B cell lineage development and how malignant transformation such as in B-CLL may corrupt BCL11A function.

In unstimulated cells, the transcription factor NF-κB is held in the cytoplasm in an inactive state by IκB inhibitor proteins. Activation of NF--KB is mediated by signal induced degradation of IκBα via the ubiquitin proteasome-dependent pathway. Targeting the proteins for ubiquitin-mediated proteolysis is an irrevocable decision, and as such, the process needs to be highly specific and tightly regulated. This task is achieved by conjugation and deconjugation enzymes that act in a dynamic and coordinated mechanism. In a yeast two hybrid screen designed to identify proteins involved in IκBα signalling Ubch9 was found to interact with the N-terminal regulatory region of IκBα. Although Ubch9 is an enzyme homologous to E2 ubiquitin conjugating enzymes we have shown that is unable to form a thioester with ubiquitin but it is capable to form a thioester with the small ubiquitin-like protein SUMO- 1. To fully characterise the SUMO-1 modification reaction we have purified the proteins and cloned the genes encoding the SUMO-1 activating enzyme (SAEl/SAE2) and shown that it is homologous to enzymes involved in the activation of ubiquitin, Smt3p, the yeast SUMO-1 homologue, and Rublp/Nedd8, another ubiquitin-like protein. SUMO-1 is conjugated to target proteins by a pathway that is distinct from, but analogous to, ubiquitin conjugation. SUMO-1 was efficiently conjugated, both in vivo and in vitro, to IκBα on lysine 21, which is also utilised for ubiquitin modification. Thus, by blocking ubiquitination SUMO-1 modification acts antagonistically to generate a pool of IκBα resistant to proteasome-mediated degradation which consequently inhibits NF-κB dependent transcription activation. In view of several lines of similarity between NF-kB and p53, the involvement of SUMO-1 modification in the metabolism of the tumour supressor p53 was investigated. We have shown that p53 is modified by SUMO-1 at a single site, lysine 386 in the C-terminus of p53. Although p53 is regulated by ubiquitination, SUMO-1 and ubiquitin modification do not compete for the same lysine in p53. However, overexpression of SUMO-1 activates the transcriptional activity of wild type p53, but not K386R p53 where the SUMO-1 acceptor site has been mutated. A consensus sequence was obtained by comparison of the sequences surrounding the SUMO-1 acceptor lysine in proteins that have been shown to be modified by SUMO-1 and revealed a possible recognition site for SUMO-1 conjugation machinery. Tagging of proteins with SUMO-1 regulates transcriptional activation, either by interfering with subcellular location or with the ubiquitination pathway. The pathway may represent a novel target for drug development.

published_or_final_version / abstract / toc / Zoology / Master / Master of Philosophy

published_or_final_version / abstract / toc / Zoology / Master / Master of Philosophy

Nowadays, RNA is extensively acknowledged an important role in the functions of information transfer, structural components, gene regulation and etc. The secondary structure of RNA becomes a key to understand structure-function relationship. Computational prediction of RNA secondary structure does not only provide possible structures, but also elucidates the mechanism of RNA folding. Conventional prediction programs are either derived from evolutionary perspective, or aimed to achieve minimum free energy. In vivo, RNA folds during transcription, which indicates that native RNA structure is a result from both thermodynamics and kinetics. In this thesis, I first reviewed the current leading kinetic folding programs and demonstrate that these programs are not able to predict secondary structure accurately. Upon that, I proposed a new sequential folding program called GTkinetics. Given an RNA sequence, GTkinetics predicts a secondary structure and a series of RNA folding trajectories. It treats the RNA as a growing chain, and adds stable local structures sequentially. It is featured with a Z-score to evaluate stability of local structures, which is able to locate native local structures with high confidence. Since all stable local structures are captured in GTkinetics, it results in some false positives, which prevents the native structure to form as the chain grows. This suggests a refolding model to melt the false positive hairpins, probable intermediate structures, and to fold the RNA into a new structure with reliable long-range helices. By analyzing suboptimal ensemble along the folding pathway, I suggested a refolding mechanism, with which refolding can be evaluated whether or not to take place. Another way to favor local structures over long-distance structures, we introduced a distance penalty function into the free energy calculation. I used a sigmoidal function to compute the energy penalty according to the distance in the primary sequence between two nucleotides of a base pair. For both the training dataset and the test dataset, the distance function improves the prediction to some extent. In order to characterize the differences between local and long-range helices, I carried out analysis of standardized local nucleotide composition and base pair composition according to the two groups. The results show that adenine accumulates on the 5' side of local structure, but not on that of long-range helices. GU base pairs occur significantly more frequent in the local helices than that in the long-range helices. These indicate that the mechanisms to form local and long range helices are different, which is encoded in the sequence itself. Based on all the results, I will draw conclusions and suggest future directions to enhance the current sequential folding program.