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Ma Junhao. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 111-123). / Abstracts in English and Chinese. / Thesis Committee --- p.i / Statement --- p.ii / Abstract --- p.iii / Acknowledgements --- p.vii / General Abbreviations --- p.ix / Abbreviations of Chemicals --- p.xi / Table of Contents --- p.xii / List of Figures --- p.xvi / List of Tables --- p.xix / Chapter 1. --- Literature review --- p.1 / Chapter 1.1 --- Importance of amino acid metabolism --- p.1 / Chapter 1.1.1 --- Rice as the important source of essential amino acids --- p.1 / Chapter 1.1.2 --- Rice seeds are nutritionally incomplete --- p.2 / Chapter 1.1.3 --- The nitrogen source for aspartate family amino acid synthesis --- p.3 / Chapter 1.1.4 --- Synthesis of aspartate family amino acids in plants --- p.4 / Chapter 1.1.5 --- Regulation of the aspartate pathway at free amino acid level --- p.12 / Chapter 1.2 --- Regulation of amino acid metabolism during seed development --- p.14 / Chapter 1.3 --- Signalling system for nitrogen metabolism --- p.17 / Chapter 1.3.1 --- Nitrogen signalling in plants --- p.18 / Chapter 1.3.2 --- GCN signalling: another nitrogen signalling pathway --- p.21 / Chapter 1.3.2.1 --- Mechanism of GCN signalling pathway in yeast --- p.21 / Chapter 1.3.2.2 --- GCN in mammalian --- p.24 / Chapter 1.3.2.3 --- GCN in higher plant --- p.24 / Chapter 1.3.3 --- Relationship between carbon and nitrogen metabolic signaling in plants --- p.26 / Chapter 1.3.4 --- Paradigm for elucidating new signal transduction pathways --- p.29 / Chapter 1.4 --- Hypothesis of this thesis work --- p.30 / Chapter 2. --- Materials and Methods --- p.32 / Chapter 2.1. --- Materials --- p.32 / Chapter 2.1.1 --- Plants --- p.32 / Chapter 2.1.2 --- Bacterial strains and vectors --- p.32 / Chapter 2.1.3 --- Chemicals and reagents --- p.33 / Chapter 2.1.4 --- Buffer，solution and gel --- p.33 / Chapter 2.1.5 --- Commercial kits --- p.33 / Chapter 2.1.6 --- Equipments and facilities used --- p.33 / Chapter 2.1.6 --- Growth medium --- p.34 / Chapter 2.2 --- Methods --- p.34 / Chapter 2.2.1 --- Profiling genes expression pattern in developing rice seeds --- p.34 / Chapter 2.2.1.1 --- Growth conditions of rice --- p.34 / Chapter 2.2.1.2 --- Collection of developing rice seeds --- p.35 / Chapter 2.2.1.3 --- Total RNA extraction from rice seeds --- p.37 / Chapter 2.2.1.4 --- Total RNA extraction from plant leaf --- p.37 / Chapter 2.2.1.5 --- Gel electrophoresis --- p.38 / Chapter 2.2.1.6 --- First strand cDNA synthesis from rice total RNA --- p.39 / Chapter 2.2.1.7 --- Search for the coding sequence of rice genes related to amino acid metabolism --- p.39 / Chapter 2.2.1.8 --- Alignment of homologous coding sequence between family member genes --- p.42 / Chapter 2.2.1.9 --- Primer design --- p.42 / Chapter 2.2.1.10 --- Quantitation of total RNA and determination of internal control --- p.45 / Chapter 2.2.1.11 --- PCR to amplify the DNA fragments --- p.45 / Chapter 2.2.1.12 --- DNA Sequencing --- p.46 / Chapter 2.2.1.13 --- Generation and testing of single-stranded DIG-labelled DNA probes --- p.46 / Chapter 2.2.1.14 --- Northern blot --- p.47 / Chapter 2.2.1.15 --- RT-PCR (Reverse-transcription polymerase chain reaction) --- p.48 / Chapter 2.2.2 --- Expression assay of selected genes in herbicide treated plants --- p.49 / Chapter 2.2.2.1 --- Growing conditions and herbicide treatments --- p.49 / Chapter 2.2.2.2 --- GCN2 homologue in Arabidopsis and rice --- p.51 / Chapter 2.2.2.3 --- RT-PCR to analyze the change in expression level of selected genes in herbicide treated plants --- p.53 / Chapter 2.2.3 --- Generation of transgenic Arabidopsis --- p.56 / Chapter 2.2.3.1 --- Preparation of T-vector for T-ligation --- p.56 / Chapter 2.2.3.2 --- Cloning of Arabidopsis GCN2 gene --- p.56 / Chapter 2.2.3.3 --- Transformation of the plasmid into DH5a competent cell --- p.57 / Chapter 2.2.3.4 --- Screening of right recombinants --- p.58 / Chapter 2.2.3.5 --- Construction of chimeric AtGCN2 genes --- p.59 / Chapter 2.2.3.6 --- Transformation of electro-competent Agrobacterium cell --- p.60 / Chapter 2.2.3.7 --- Transformation of Arabidopsis by vacuum infiltration --- p.61 / Chapter 2.2.3.8 --- Selection of hemizygous and homozygous transgenic plants --- p.61 / Chapter 2.2.3.9 --- Screening of the T3 transformants --- p.63 / Chapter 2.2.3.10 --- Expression analysis of homozygous AtGCN2 transgenic Arabidopsis --- p.63 / Chapter 3. --- Results --- p.63 / Chapter 3.1 --- Profiling genes expression pattern in developing rice seeds --- p.63 / Chapter 3.1.1 --- Quantification of total RNA from seeds at different developing stages --- p.63 / Chapter 3.1.2 --- DNA sequence analysis --- p.66 / Chapter 3.1.3 --- Profiling the gene expression in developing rice seeds --- p.67 / Chapter 3.1.3.1 --- Expression profiles of nitrogen assimilation related genes --- p.67 / Chapter 3.1.3.2 --- Expression profiles of aspartate pathway genes --- p.72 / Chapter 3.1.3.3 --- Expression profiles of branched-chain amino acid synthesis pathway genes --- p.78 / Chapter 3.2 --- Relationship between GCN2 and amino acid metabolism in plants --- p.82 / Chapter 3.2.1 --- GCN2 homologue in A. thaliana and rice --- p.82 / Chapter 3.2.2 --- GCN2 and amino acid starvation --- p.85 / Chapter 3.2.3 --- Effects of amino acid starvation on GCN2 expression --- p.90 / Chapter 3.2.3 --- Changes in the expression level AK and BCAT genes in herbicide treated rice and A. thaliana --- p.93 / Chapter 3.3 --- Characterization of GCN2 transgenic A. thaliana --- p.96 / Chapter 3.3.1 --- Construct of pBI121-AtGCN2 --- p.96 / Chapter 3.3.2 --- Construction of GCN2 transgenic A. thaliana --- p.96 / Chapter 3.3.3 --- Expression of GCN2 in transgenic A. thaliana --- p.97 / Chapter 3.3.4 --- Expression level changes of AK and BCAT in transgenic A. thaliana --- p.99 / Chapter 4. --- Discussions --- p.101 / Chapter 4.1 --- Expression pattern of selected metabolic genes in developing plant seeds --- p.101 / Chapter 4.1.1 --- Most genes studied displayed a similar pattern --- p.101 / Chapter 4.1.2 --- Regulation of gene expression in developing rice seeds --- p.105 / Chapter 4.2 --- GCN2 and its role in higher plants --- p.106 / Chapter 4.2.1 --- The existence of the GCN2 gene in rice --- p.106 / Chapter 4.2.2 --- GCN2 responses solely to amino acid starvation --- p.106 / Chapter 5. --- Conclusion and Prospective --- p.109 / Reference --- p.111 / Appendix I: Chemicals and reagents --- p.124 / "Appendix II: Buffer, solution and gel" --- p.126 / Appendix III: Commercial kits --- p.128 / Appendix IV: Equipments and facilities used --- p.128

by Vong Puinga Queenie Maria. / "August 2002." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (p. 176-194). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

DNA microarray technology is the most notable high throughput technology which emerged for functional genomics in recent years. Patterns in microarray data provide clues of gene functions, cell types, and interactions among genes or gene products. Since the scale of microarray data keeps on growing, there is an urgent need for the development of methods and tools for the analysis of these huge amounts of complex data. / Interesting patterns in microarray data can be patterns appearing with significant frequencies or patterns appearing special trends. Firstly, an algorithm to find biclusters with coherent values is proposed. For these biclusters the subset of genes (or samples) show some similarities, such as low Euclidean distance or high Pearson correlation coefficient. We propose Average Correlation Value (ACV) to measure the homogeneity of a bicluster. ACV outperforms other alternatives for being applicable for biclusters of more types. Our algorithm applies dominant set approach to create sets of sorting vectors for rows of the data matrix. In this way, the co-expressed rows of the data matrix could be gathered. By alternatively sorting and transposing the data matrix the blocks of co-expressed subset are gathered. Weighted correlation coefficient is used to measure the similarity in the gene level and the sample level. Their weights are updated each time using the sorting vector of the previous iteration. Genes/samples which are assigned higher weights contribute more to the similarity measure when they are used as features for the other dimension. Unlike the two-way clustering or divide and conquer algorithm, our approach does not break the structure of the whole data and can find multiple overlapping biclusters. Also the method has low computation cost comparing to the exhaustive enumeration and distribution parameter identification methods. / Next, algorithms to find biclusters with coherent evolutions, more specific, the order preserving patterns, are proposed. In an Order Preserving Cluster (OP-Cluster) genes induce the same relative order on samples, while the exact magnitude of the data are not regarded. By converting each gene expression vector into an ordered label sequence, we transfer the problem into finding frequent orders appearing in the sequence set. Two heuristic algorithms, Growing Prefix and Suffix (GPS) and Growing Frequent Position (GFP) are presented. The results show these methods both have good scale-up properties. They output larger OP-Clusters more efficiently and have lower space and computation space cost comparing to the existing methods. / We propose the idea of Discovering Distinct Patterns (DDP) in gene expression data. The distinct patterns correspond to genes with significantly different patterns. DDP is useful to scale-down the analysis when there is little prior knowledge. A DDP algorithm is proposed by iteratively picking out pairs of genes with the largest dissimilarities. Experiments are implemented on both synthetic data sets and real microarray data. The results show the effectiveness and efficiency in finding functional significant genes. The usefulness of genes with distinct patterns for constructing simplified gene regulatory network is further discussed. / Teng, Li. / Adviser: Laiwan Chan. / Source: Dissertation Abstracts International, Volume: 71-01, Section: B, page: 0446. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 118-128). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese.

by Timothy W.L. Wong. / "July 2000." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (p. 200-238). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Chum Wing Yan Winnie. / "August 2006." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 190-223). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese.

Antibody engineering is an innovative field of research that has generated a wide range of novel antibody-based formats that both exploit and improve natural antibody properties. Novel format antibodies have the potential to offer significant advantages over natural antibodies when used as biopharmaceuticals, however these non-natural structures often pose a great challenge to the host cell used for their manufacture. Protein expression is a highly regulated process, and quality control mechanisms at each stage can result in a block, or "bottleneck" in expression. This can impact product yield, cost of goods and entry into the clinical pipeline. The molecular determinants that govern novel-format expression in host cells are poorly defined, however there is growing evidence that limited variations in both nucleotide and amino acid sequence can have a severe impact on antibody expression. Therefore this Thesis aims to investigate the consequences of sequence variation on the expression of a novel antibody format (mAbdAb) in mammalian host cells in order to determine the molecular mechanisms that govern their expression. A diverse panel of mAbdAbs with sequence variations limited to the dAb domain were generated through phage display and cloning technologies. It was determined that amino acid variations located within the CDRs of the dAb results in a range of expression titres in both transient HEK and stable CHO expression platforms. In vitro translation of mAbdAb heavy chain proteins in rabbit reticulocyte lysates (RRL) showed no difference in expression between sequence variants, therefore cell-free translation was suggested as a potential expression platform. Examination of each stage of expression in stable CHO cells revealed that the amount of mRNA was not limiting to expression and distinct expression profiles were observed at the protein level. The majority of mAbdAb constructs showed little evidence of intracellular heavy chain polypeptide which was not altered through chemical inhibition of proteolytic degradation pathways, indicating that degradation was not responsible for poor expression. This led to the hypothesis that low titres were related to how the CHO cell utilises the heavy chain message.

The poultry industry has successfully applied breeding and production programmes to meet growing consumer demands for chicken meat and eggs. Over the last four decades, poultry breeders have selected birds not only for productivity, but also for improved health, welfare, fitness and environmental robustness. Intensive production settings contribute to faster spread of diseases and greater losses in production due to increased morbidity and mortality of the flock. Traditional methods of disease treatment and prevention have played a critical role in control of disease. However, growing resistance of pathogens to therapeutic measures and consumer concerns led to the withdrawal of antibiotics as growth promoting additives in chicken feed. In addition, some vaccines have been overcome by increasing variation and virulence of pathogens and are no longer successful in disease prevention. The emergence of virulent and drug resistant pathogens have emphasised the need to focus on other solutions to disease, particularly natural genetic resistance. Genetic loci or gene expression patterns associated with the differential resistance of lines to specific pathogens have been identified, providing valuable markers for selective breeding. However, to date relatively few of these have been successfully incorporated into commercial lines. An ability to suppress or resist multiple pathogens, by selection for improved innate immune robustness has also been studied but it has not been introduced in commercial production, partly as the phenotype is ill-defined. Previous studies that focused on pro-inflammatory cytokines and their mRNA levels expressed by innate immune effector cells (heterophils and macrophages) identified differences between resistant and susceptible chicken lines, with the former producing stronger responses, supporting efforts to select poultry with an efficient early innate response. Here, small-scale qPCR screening and cellular techniques were evaluated with the conclusion that a more rapid, cheaper and reproducible method needs to be applied. The main objective of this project was therefore to design and validate a diagnostic tool that could be used to phenotype the immune responses of chickens at the level of innate immunity. For this purpose, a panel of 89 genes was selected based on previously published infection studies and on RNA-seq results obtained from stimulation of heterophils, macrophages and dendritic cells with lipopolysaccharide (LPS). Target genes were cloned and sequenced to optimise the design of qPCR reactions and primers. A multiplex qPCR platform, the Fluidigm 96.96 Dynamic Array, was selected as the tool of choice with the capacity to measure transcription of 96 genes of interest in 96 samples simultaneously. The preamplification reaction was optimised and the platform validated using a commercial line of chickens housed in clean or pathogen-challenged environments. Lymphoid tissues, including bursa of Fabricius, spleen, ileum with Peyer’s patches, caecal tonsils, and blood leukocytes were isolated and transcript levels for immune-related genes defined between organs, birds and farms. For qPCR analysis, a panel of reference genes was normalised and TBP, ACTB and GAPDH genes were selected and validated as the most stable. The high-throughput qPCR analysis identified peripheral blood leukocytes as a potentially reliable indicator of immune responses among all the tissues tested with the highest number of genes significantly differentially expressed between birds housed in varying hygienic environments. The research described here could potentially aid the selection of poultry for improved immune robustness. The technical optimisation and validation of a new tool to simultaneously quantify expression of tens of relevant immune-related genes will prime research in many areas of avian biology, especially to define baseline immune gene expression for selection, the basis of differential resistance, and host responses to infection, vaccination or immuno-modulatory substances.

The regulation of gene expression is the driver of cellular differentiation in multicellular organisms; the result is a diverse range of cell types each with their own unique profile of expression. Within these cell types the transcriptional product of a gene is up or down regulated in response to intrinsic and extrinsic stimuli according to its own regulatory programme encoded within the cell. The complexity of this regulatory programme depends on the requirements of the gene to change expression states in different cell lineages or temporally in response to a range of conditions. In the case of many housekeeping genes integral to the survival of the cell, this programme is simple - switch on the gene and leave it on, whereas often the required level and precision of regulatory control is much more involved and lends to subtle changes in expression. This raises many questions of precisely where and how that regulatory information is encoded and whether different biological systems encode it in the same way. This project attempts to answer these questions through the development of novel approaches in quantifying the output of this regulatory programme according to the state changes as observed from the expression profile of a given gene. Measures of complexity in gene expression are calculated over a wide range of cell types and conditions collected using CAGE, which provides a quantitative estimate of gene expression that precisely defines the promoter utilised to initiate that expression. As expected, housekeeping genes were found to be amongst the least complex, as a result of their uniform expression profiles, as well as those genes highly restricted in their expression. The genes most complex in their expression output were those associated with the presence of H3K27me3 repressive marks; genes poised for activation in a specific set of cell types, as well as those enriched in DNAse I hypersensitive sites in their upstream region but not necessarily conserved in that region. Evidence also suggests that different promoters associated with a gene contribute in different ways to its resultant regulatory complexity, suggesting that certain promoters may be more crucial in driving the regulation of some genes. This allows for the targeting of such promoters in the analysis of certain diseases implicated by changes in regulatory regions. Indeed, genes known to be associated with diseases such as leukaemia and Alzheimer’s are found to be highly complex in their expression.

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