Thesis (Ph.D.) -- University of Texas at Arlington, 2008.

No description available.

Thesis (PhD) - Swinburne University of Technology, Industrial Research Institute Swinburne - 2006. / A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy, Industrial Research Institute Swinburne, Swinburne University of Technology - 2006. Typescript. Includes bibliographical references (p. 184-197).

Thesis (Ph.D.)--University of Melbourne, Dept. of Otolaryngology (Eye & Ear Hospital), 2006. / Typescript. Includes bibliographical references (leaves 238-253).

Thesis(M.S.)--Auburn University, 2007. / Abstract. Vita. Includes bibliographic references.

Thesis (Ph. D.)--University of California, Riverside, 2010. / Includes abstract. Available via ProQuest Digital Dissertations. Title from first page of PDF file (viewed May 18, 2010). Includes bibliographical references. Also issued in print.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 278-288).

A transcription factor (TF) is a protein that binds to specific DNA sequences as part of the initiation stage of transcription. Various methods of finding these transcription factor binding sites (TFBS) have been developed. In vivo technologies analyze DNA binding regions known to have bound to a TF in a living cell. Most widely used in vivo methods at the moment are chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) and DNase I hypersensitive sites sequencing. In vitro methods derive TFBS based on experiments with TFs and DNA usually in artificial settings or computationally. An example is the Protein Binding Microarray which uses artificially constructed DNA sequences to determine the short sequences that are most likely to bind to a TF. The major drawback of this approach is that binding of TFs in vivo is also dependent on other factors such as chromatin accessibility and the presence of cofactors. Therefore TFBS derived from the PBM technique might not resemble the true DNA binding sequences. In this work, we use PBM data from the UniPROBE motif database, ChIP-seq data and DNase I hypersensitive sites data. Using the Spearman’s rank correlation and area under receiver operating characteristic curve, we compare the enrichment scores which the PBM approach assigns to its identified sequences and the frequency of these sequences in likely binding regions and the human genome as a whole. We also use central motif enrichment analysis (CentriMo) to compare the enrichment of UniPROBE motifs with in vivo derived motifs (from the JASPAR CORE database) in their respective TF ChIP-seq peak region. CentriMo is applied to 14 TF ChIP-seq peak regions from different cell lines. We aim to establish if there is a relationship between the occurrences of UniPROBE 8-mer patterns in likely binding regions and their enrichment score and how well the in vitro derived motifs match in vivo binding specificity. We did not come out with a particular trend showing failure of the PBM approach to predict in vivo binding specificity. Our results show Ets1, Hnf4a and Tcf3 show prediction failure by the PBM technique in terms of our Spearman’s rank correlation for ChIP-seq data and central motif enrichment analysis. However, the PBM technique also matched the in vivo binding specificities of FoxA2, Pou2f2 and Mafk. Failure of the PBM approach was found to be a result of variability in the TF’s binding specificity, the presence of cofactors, narrow binding specificity and the presence ubiquitous binding patterns.

Characterising transcription factor binding sites (TFBS) is an important problem in bioinformatics, since predicting binding sites has many applications such as predicting gene regulation. ChIP-seq is a powerful in vivo method for generating genome-wide putative binding regions for transcription factors (TFs). CentriMo is an algorithm that measures central enrichment of a motif and has previously been used as motif enrichment analysis (MEA) tool. CentriMo uses the fact that ChIP-seq peak calling methods are likely to be biased towards the centre of the putative binding region, at least in cases where there is direct binding. CentriMo calculates a binomial p-value representing central enrichment, based on the central bias of the binding site with the highest likelihood ratio. In cases where binding is indirect or involves cofactors, a more complex distribution of preferred binding sites may occur but, in many cases, a low CentriMo p-value and low width of maximum enrichment (about 100bp) are strong evidence that the motif in question is the true binding motif. Several other MEA tools have been developed, but they do not consider motif central enrichment. The study investigates the claim made by Zhao and Stormo (2011) that they have identified a simpler method than that used to derive the UniPROBE motif database for creating motifs from protein binding microarray (PBM) data, which they call BEEML-PBM (Binding Energy Estimation by Maximum Likelihood-PBM). To accomplish this, CentriMo is employed on 13 motifs from both motif databases. The results indicate that there is no conclusive difference in the quality of motifs from the original PBM and BEEML-PBM approaches. CentriMo provides an understanding of the mechanisms by which TFs bind to DNA. Out of 13 TFs for which ChIP-seq data is used, BEEML-PBM reports five better motifs and twice it has not had any central enrichment when the best PBM motif does. PBM approach finds seven motifs with better central enrichment. On the other hand, across all variations, the number of examples where PBM is better is not high enough to conclude that it is overall the better approach. Some TFs bind directly to DNA, some indirect or in combination with other TFs. Some of the predicted mechanisms are supported by literature evidence. This study further revealed that the binding specificity of a TF is different in different cell types and development stages. A TF is up-regulated in a cell line where it performs its biological function. The discovery of cell line differences, which has not been done before in any CentriMo study, is interesting and provides reasons to study this further.

The detection and quantification of biomolecules, and proteins in particular, are of great interest since these molecules are of fundamental importance to our well-being. Body fluids, as for instance human blood, are well suited for sampling of protein levels. However, the complexity of the fluids and the low abundance of many of the interesting biomolecules makes detection and quantification difficult. This has spurred an interest into the development of many protein detection methods, and of these, ligand assays have proven particularly suitable. In this thesis, different types of ligand assays for protein detection have been developed using affibody molecules as ligands. In a first study, a homogeneous competitive detection assay was investigated, based on antiidiotypic affibody molecule pairs and fluorescence resonance energy transfer (FRET) as reporting system. The individual members of two anti-idiotypic affibody pairs, each consisting of a target binding (idiotypic) and an anti-idiotypic affibody ligand, were labeled with a donor fluorophore and an acceptor fluorophore, respectively. Incubation with the two target proteins IgA and Taq DNA polymerase resulted in a concentration dependent decrease in the FRET signal, allowing for target protein detection and quantification. For Taq DNA polymerase, detection in 25% human plasma was also possible in the same concentration span as in buffer. In a second study, a homogeneous, non-competitive detection system was described. Affibody molecules of 58 amino acids directed against IgA and IgG were produced with chemical synthesis, and two fluorophores capable of FRET were site-specifically introduced. Binding of target protein induced a concentration-dependent change in the relative emission of the two fluorophores, which formed the basis for the detection system. In two studies, affibody molecules were evaluated and shown to function well as capture ligands on microarrays. Synthetic affibody molecules directed against Taq DNA polymerase and IgA were modified by the introduction of immobilization tags. Specific immobilization via a C-terminal cysteine or a biotin moiety, or random immobilization via amino groups, were studied in protein microarray experiments and SPR-based biosensor studies. The experiments showed that all immobilization chemistries resulted in functional capture molecules. A short spacer was also introduced, situated between the affibody and the cysteine and biotin moieties, which was shown to improve binding for all constructs. Multidomain affibody constructs of up to four N- to C-terminally linked domains were shown to increase the amount of bound target, compared to monomeric affibody ligands. Six dimeric affibody constructs directed against IgA, IgG, IgE, Taq DNA polymerase, TNF-α and insulin, respectively, showed low limits of detections for their targets and little or no cross-reactivity with the other target proteins. Dimeric affibody molecules directed against IgA and TNF-α were also shown to function in a sandwich format with antibodies for detection of targets in buffer and in human serum and plasma. Successful discrimination between normal and IgA-deficient sera showed that affibody molecules could be used for specific detection of protein in highly complex backgrounds on microarrays. / QC 20100916