Thesis (Ph. D.)--University of Wyoming, 2006. / Title from PDF title page (viewed on Dec. 17, 2007). Includes bibliographical references (p. 94-118).

Thesis (M.S.)--University of Delaware, 2007. / Principal faculty advisor: Eric B. Kmiec, Dept. of Biological Sciences. Includes bibliographical references.

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Melinda K. Duncan, Dept. of Biological Sciences. Includes bibliographical references.

Thesis (M. Med. Sc.)--University of Hong Kong, 2006.

Apple proliferation (AP) is one of the most serious diseases of apple trees in Europe. It is caused by a phytoplasma, Candidatus Phytoplasma mali. The goal of the present study was to analyze transcriptional profiles of Malus pumila during infection by Ca. P. mali using cDNA-Amplified Fragment Length Polymorphism (cDNA-AFLP) technique in order to gain insight into molecular and physiological changes in diseased plants. We used a rootstock of apple (MM106) susceptible to Ca. P. mali to maximise the range of the potential host responses, and two strains (AP and AT) of the pathogen. Gene expression comparisons were studied in 3 categories of plant materials: healthy sample versus infected samples, symptomatic versus non-symptomatic sample, and AP-infected sample versus AT-infected sample. Forty-five genes whose steady-state levels of expression significantly changed in response to phytoplasma infection were isolated and identified. Of 45 partial cDNA sequences, twenty-seven showed similarity to international DNA or protein data bases. Of these, 18 were previously characterized in plants (the rest was related to unknown or hypothetical proteins). Eighteen out of 45 did not show any similarity with sequences in data bases, and so may be present novel genes. The majority of fragments were differently expressed between healthy sample and infected samples (fewer differences between symptomatic and non-symptomatic samples, or between the samples infected by different strains of phytoplasma). Quantitative Real-time RT-PCR (qRT-PCR) was used to confirm differential expression of sequences isolated by cDNA-AFLP. We chose the most stable reference housekeeping genes (GAPDH and actin) for normalisation of our data. The gene expression ratios were calculated by means of ΔΔCt method. Consequently, the second methodology (qRT-PCR) showed the similar profile expression as primary elucidation technique (cDNA-AFLP) for 11 known genes (between 18) and 13 unknown, hypothetical or novel genes (between 27). Changes in gene expression involved a wide spectrum of biological functions, including processes of metabolism, cell defence, senescence, photosynthesis, transport, transcription, signal transduction and protein synthesis. The possible effect of phytoplasma infection on these processes and their relationships with disease development, symptom appearance and probably plant defence system is discussed. A model is proposed to explain the mode of action of the Ca. P. mali in its host plant, apple tree. This is the first study of global gene profiling in plants in response to phytoplasma infections using cDNA-AFLP.

Gene expression, which connects genomic information to functional units in living cells, has received substantial attention since the completion of The Human Genome Project. Quantitative characterization of gene expression will provide valuable information for understanding the behavior of living cells, and possibilities of building synthetic gene circuits to control or modify the behavior of naturally occurring cells. Many aspects of quantitative gene expression have been studied, including gene expression dynamics and noise in E. coli. The gene expression process itself is stochastic, and modelling approaches have been broadly used to study gene expression noise; however, stochastic gene expression models are usually large and time intensive to simulate. To speed up simulations, we have developed a systematic method to simplify gene expression models with fast and slow dynamics, and investigated when we can ignore the gene expression from the background genome when modelling the gene expression from plasmids. When modelling the noise in gene expression, one usually neglected aspect is the slow maturation process of fluorescent proteins, necessary for the protein to give out fluorescence after it is produced. By modelling, we show that the maturation steps can bring large changes to both the mean protein number and the noise in the model. An unstudied aspect of gene expression dynamics is the time dependent gene expression behavior in E. coli batch culture. Contrary to the usual assumption, we have found, in E. coli batch culture gene expression, that there is no steady state in terms of both the mean number of proteins and the noise. Negative feedback is thought to be able to reduce the noise in a system, and experiments have shown that negative feedback indeed suppresses the noise in gene expression, but the modelling shows that negative feedback will increase the noise. We have found that the increase of noise by feedback is due to the exclusion of extrinsic noise from the model, and that negative feedback will suppress the extrinsic noise while increasing the intrinsic noise. Living cells are crowded with macromolecules, which will, predicted by modelling, make the reaction constant time dependent. Our experimental observation has confirmed this prediction.

This study examined the differential gene expression patterns between endothelial cells (EC) from 2D monolayer and EC from angiogenic capillary-like network in 3D matrices. Our microarray analysis comparing 3D to 2D EC cultures detected upregulation of 854 protein-coding genes and downregulation of 863 genes. We show that Notch signaling pathway is highly regulated in angiogenesis, induced by change in ECM dimension. Notch target genes Hey1, HeyL, Hes1 and Hes4 transcription factors were upregulated in 3D angiogenic EC, which were confirmed with qRT-PCR. Moreover, we are the first to report enrichment of FoxS1 transcription factor mRNA during angiogenesis in 3D ECM. Next, we asked whether epigenetic mechanisms partly mediate cis-trans response in angiogenesis. Our sodium bisulfite sequencing analyses did not indicate a role for DNA methylation in the expression of key Notch signaling components. However, our pilot studies indicate a potential role for lncRNAs in controlling EC phenotype in angiogenic response.

This study examined the differential gene expression patterns between endothelial cells (EC) from 2D monolayer and EC from angiogenic capillary-like network in 3D matrices. Our microarray analysis comparing 3D to 2D EC cultures detected upregulation of 854 protein-coding genes and downregulation of 863 genes. We show that Notch signaling pathway is highly regulated in angiogenesis, induced by change in ECM dimension. Notch target genes Hey1, HeyL, Hes1 and Hes4 transcription factors were upregulated in 3D angiogenic EC, which were confirmed with qRT-PCR. Moreover, we are the first to report enrichment of FoxS1 transcription factor mRNA during angiogenesis in 3D ECM. Next, we asked whether epigenetic mechanisms partly mediate cis-trans response in angiogenesis. Our sodium bisulfite sequencing analyses did not indicate a role for DNA methylation in the expression of key Notch signaling components. However, our pilot studies indicate a potential role for lncRNAs in controlling EC phenotype in angiogenic response.

Gene expression, which connects genomic information to functional units in living cells, has received substantial attention since the completion of The Human Genome Project. Quantitative characterization of gene expression will provide valuable information for understanding the behavior of living cells, and possibilities of building synthetic gene circuits to control or modify the behavior of naturally occurring cells. Many aspects of quantitative gene expression have been studied, including gene expression dynamics and noise in E. coli. The gene expression process itself is stochastic, and modelling approaches have been broadly used to study gene expression noise; however, stochastic gene expression models are usually large and time intensive to simulate. To speed up simulations, we have developed a systematic method to simplify gene expression models with fast and slow dynamics, and investigated when we can ignore the gene expression from the background genome when modelling the gene expression from plasmids. When modelling the noise in gene expression, one usually neglected aspect is the slow maturation process of fluorescent proteins, necessary for the protein to give out fluorescence after it is produced. By modelling, we show that the maturation steps can bring large changes to both the mean protein number and the noise in the model. An unstudied aspect of gene expression dynamics is the time dependent gene expression behavior in E. coli batch culture. Contrary to the usual assumption, we have found, in E. coli batch culture gene expression, that there is no steady state in terms of both the mean number of proteins and the noise. Negative feedback is thought to be able to reduce the noise in a system, and experiments have shown that negative feedback indeed suppresses the noise in gene expression, but the modelling shows that negative feedback will increase the noise. We have found that the increase of noise by feedback is due to the exclusion of extrinsic noise from the model, and that negative feedback will suppress the extrinsic noise while increasing the intrinsic noise. Living cells are crowded with macromolecules, which will, predicted by modelling, make the reaction constant time dependent. Our experimental observation has confirmed this prediction.

Coral reefs are one of the world s most valuable ecosystems but are declining at an accelerating rate. Common stressors impacting coral health include elevated temperatures, changes in light intensity, sedimentation, and increased exposure to pollutants. Traditionally, physiological responses have been measured to assess coral health but usually do not identify the stressor or the underlying mechanisms causing a response. In addition, coral may be stressed beyond recovery by the time a physiological response is observed. Changes in gene expression are key elements of the stress response, usually occur before physiological damage is evident, and can be directly related to the causative agent of stress. My research focuses on detecting sublethal responses to stress in Scleractinian coral using genetic biomarkers and gene expression profiling. Through the application of molecular technology, I have developed a coral stress gene microarray to investigate the responses of coral to various stressors. Results from controlled laboratory exposures provide evidence for unique gene expression profiles associated with specific stressors. Results from field studies reveal the feasibility of using array technology to investigate changes in gene expression of natural coral populations across time and between sites. For example, the array has been used to detect stress in coral populations related to seasonal events, such as precipitation as well as point source stress, such as xenobiotics. The temporal and spatial regulation of specific genes within a genome determines the metabolic activity of an organism and can be used to identify changes in cellular responses to various stimuli. These cellular events precede population-level changes and could be useful biomarkers if linked to specific physiological or ecological events. This research is important because it identifies stress at a sub-lethal level and can aid resource managers in decision making by prioritizing the stressors impacting coral reefs.