The growing obesity epidemic in America carries with it numerous health risks, including diabetes, increased serum lipid levels, and excess fat accumulation in the liver. If these conditions persist or become exacerbated, they may lead to the development of cardiovascular disease, the current leading cause of death among Americans, or to nonalcoholic fatty liver disease (NAFLD) which can progress to hepatocellular carcinoma (HCC), one of the deadliest forms of cancer. Better understanding of the genes involved in these diseases can lead to improved identification of at-risk individuals and treatment strategies. Our lab previously identified zinc fingers and homeoboxes 2 (Zhx2) as a regulator of hepatic gene expression. The BALB/cJ mouse strain has a hypomorphic mutation in the Zhx2 gene, causing a 95% reduction in Zhx2 protein expression. The near ablation of Zhx2 in BALB/cJ mice confers protection from cardiovascular disease when fed a high fat diet, yet these mice show increased hepatic lipid accumulation and liver damage. Microarray data indicates Zhx2 may be involved in the regulation of numerous genes involved in lipid metabolism. Recent GWAS studies indicate ZHX2 may contribute to the risk of cardiovascular disease and liver damage in humans as well. In this dissertation, I characterize the role of Zhx2 expression in the liver and how it affects the risk of both cardiovascular disease and liver damage. I generated liver-specific Zhx2 knockout mice and confirmed Zhx2 regulates several novel targets that could contribute to the fatty liver phenotype seen in BALB/cJ mice. Further studies revealed that hepatic Zhx2 expression is necessary for proper sex-specific expression of several Cyptochrome P450 (CYP) genes and could contribute to gender differences in disease susceptibility. Lastly, I performed studies into the functional role of the Zhx2 target gene Elovl3. A mouse model of HCC revealed that Elovl3 is completely repressed in HCC tumors. Cell viability and cell cycle assays indicate that Elovl3 expression slows cell proliferation and may be important for proper cell cycle checkpoints. Together, these data indicate that Zhx2 and/or its targets could be clinically relevant in the detection, prevention, or treatment of cardiovascular disease, fatty liver, and HCC.

No description available.

Fundamental aspects of biologically-inspired regulatory mechanisms are considered in a robotics context, using artificial neural-network control systems . Regulatory mechanisms are used to control expression of genes, adaptation of form and behavior in organisms. Traditional neural network control architectures assume networks of neurons are fixed and are interconnected by wires. However, these architectures tend to be specified by a designer and are faced with several limitations that reduce scalability and tractability for tasks with larger search spaces. Traditional methods used to overcome these limitations with fixed network topologies are to provide more supervision by a designer. More supervision as shown does not guarantee improvement during training particularly when making incorrect assumptions for little known task domains. Biological organisms often do not require such external intervention (more supervision) and have self-organized through adaptation. Artificial neural tissues (ANT) addresses limitations with current neural-network architectures by modeling both wired interactions between neurons and wireless interactions through use of chemical diffusion fields. An evolutionary (Darwinian) selection process is used to ‘breed’ ANT controllers for a task at hand and the framework facilitates emergence of creative solutions since only a system goal function and a generic set of basis behaviours need be defined. Regulatory mechanisms are formed dynamically within ANT through superpositioning of chemical diffusion fields from multiple sources and are used to select neuronal groups. Regulation drives competition and cooperation among neuronal groups and results in areas of specialization forming within the tissue. These regulatory mechanisms are also shown to increase tractability without requiring more supervision using a new statistical theory developed to predict performance characteristics of fixed network topologies. Simulations also confirm the significance of regulatory mechanisms in solving certain tasks found intractable for fixed network topologies. The framework also shows general improvement in training performance against existing fixed-topology neural network controllers for several robotic and control tasks. ANT controllers evolved in a low-fidelity simulation environment have been demonstrated for a number of tasks on hardware using groups of mobile robots and have given insight into self-organizing system. Evidence of sparse activity and use of decentralized, distributed functionality within ANT controller solutions are found consistent with observations from neurobiology.

Computational systems biology is an emerging area of research that focuses on understanding the holistic view of complex biological systems with the help of statistical, mathematical and computational techniques. The regulation of gene expression in gene regulatory network is a fundamental task performed by all known forms of life. In this subsystem, modelling the behaviour of the components and their interactions can provide useful biological insights. Statistical approaches for understanding biological phenomena such as gene regulation are proving to be useful for understanding the biological processes that are otherwise not comprehensible due to multitude of information and experimental difficulties. A combination of both the experimental and computational biology can potentially lead to system level understanding of biological systems. This thesis focuses on the problem of inferring the dynamics of gene regulation from the observed output of gene expression. Understanding of the dynamics of regulatory proteins in regulating the gene expression is a fundamental task in elucidating the hidden regulatory mechanisms. For this task, an initial fixed structure of the network is obtained using experimental biology techniques. Given this network structure, the proposed inference algorithms make use of the expression data to predict the latent dynamics of transcription factor proteins. The thesis starts with an introductory chapter that familiarises the reader with the physical entities in biological systems; then we present the basic framework for inference in transcriptional regulation and highlight the main features of our approach. Then we introduce the methods and techniques that we use for inference in biological networks in chapter 2; it sets the foundation for the remaining chapters of the thesis. Chapter 3 describes four well-known methods for inference in transcriptional regulation with pros and cons of each method. Main contributions of the thesis are presented in the following three chapters. Chapter 4 describes a model for inference in transcriptional regulation using state space models. We extend this method to cope with the expression data obtained from multiple independent experiments where time dynamics are not present. We believe that the time has arrived to package methods like these into customised software packages tailored for biologists for analysing the expression data. So, we developed an open-sources, platform independent implementation of this method (TFInfer) that can process expression measurements with biological replicates to predict the activities of proteins and their influence on gene expression in gene regulatory network. The proteins in the regulatory network are known to interact with one another in regulating the expression of their downstream target genes. To take this into account, we propose a novel method to infer combinatorial effect of the proteins on gene expression using a variant of factorial hidden Markov model. We describe the inference mechanism in combinatorial factorial hidden model (cFHMM) using an efficient variational Bayesian expectation maximisation algorithm. We study the performance of the proposed model using simulated data analysis and identify its limitation in different noise conditions; then we use three real expression datasets to find the extent of combinatorial transcriptional regulation present in these datasets. This constitutes chapter 5 of the thesis. In chapter 6, we focus on problem of inferring the groups of proteins that are under the influence of same external signals and thus have similar effects on their downstream targets. Main objectives for this work are two fold: firstly, identifying the clusters of proteins with similar dynamics indicate their role is specific biological mechanisms and therefore potentially useful for novel biological insights; secondly, clustering naturally leads to better estimation of the transition rates of activity profiles of the regulatory proteins. The method we propose uses Dirichlet process mixtures to cluster the latent activity profiles of regulatory proteins that are modelled as latent Markov chain of a factorial hidden Markov model; we refer to this method as DPM-FHMM. We extensively test our methods using simulated and real datasets and show that our model shows better results for inference in transcriptional regulation compared to a standard factorial hidden Markov model. In the last chapter, we present conclusions about the work presented in this thesis and propose future directions for extending this work.

Some upstream open reading frames (uORFs) regulate gene expression (i.e. they are functional) and can play key roles in keeping organisms healthy. However, how uORFs are involved in gene regulation is not het fully understood. In order to get a complete view of how uORFs are involved in gene regulation, it is expected that a large number of functional uORFs are needed. Unfortunately , lab experiments to verify that uORFs are functional are expensive. In this thesis, for the first time, the use of inductive logic programming (ILP) is explored for the task of learning which uORFs regulate gene expression in the yeast Saccharomyces cerevisiae. This work is directed to help select sets of candidate functional uORFs for experimental studies. With limited background knowledge, ILP can generate hypotheses which make the search for novel functional uORFs 17 times more efficient than random sampling. Adding mRNA secondary structure to the background knowledge results in hypotheses with significantly increased performance. This work is the first machine learning work to study both uORFs and mRNA secondary structures in the context of gene regulation. Using a novel combination of knowledge about biological conservation, gene ontology annotations and genes' response to different conditions results in hypotheses that are simple, informative, have an estimated sensitivity of 81% and provide provisional insights into biological characteristics of functional uORFs. The hypotheses predict 299 further genes to have 450 novel functional uORFs. A comparison with a related study suggests that 8 of these predicted functional uORFs (from 8 genes) are strong candidates for experimental studies.

G-quadruplex secondary structures are four-stranded globular nucleic acid structures that form in specific DNA and RNA G-rich sequences with biological significance, such as those found in human telomeres, oncogene promoter regions, replication initiation sites, and 5’- and 3’-untranslated (UTR) regions, which have been identified as novel drug targets. The non-canonical G-quadruplex secondary structures readily form under physiologically relevant ionic conditions, and exhibit great diversity in their topologies and loop conformations depending on the DNA or RNA sequences at hand. The structural diversity of these unique secondary structures is essential to their specific recognition by different regulatory proteins or small molecule compounds. A significant amount of research has been done in this field that provides compelling evidence for the existence, biological significance, and potential druggability of G-quadruplexes. In this dissertation, I explore G-quadruplex formation in the promoters of BCL2, PDGFR-β and c-Myc oncogenes and their interactions with small molecule compounds or proteins. Firstly, I investigated a newly-identified G-quadruplex (P1G4) forming immediately upstream of the human BCL2 gene, which has been found to be overexpressed in several human tumors. In this research, I have found that P1G4 acts as a transcription repressor, and that its inhibitory effect can be enriched by the G-quadruplex-interactive compound, TMPyP4. Both P1G4 and the previously reported Pu39 G-quadruplexes form independently in adjacent regions within the BCL2 P1 promoter, but P1G4 appears to play a more dominant role in repressing transcriptional activity. NMR and CD studies have shown that the P1G4 G-quadruplex appears to comprise a novel dynamic equilibrium of two parallel structures, one regular, with two 1-nt loops and a 12-nt middle loop, and another broken-stranded, with three 1-nt loops and an 11-nt middle loop; both structures adopt a novel hairpin (stem-loop duplex) conformation in the long central loop. This dynamic equilibrium of two closely-related G-quadruplex structures with a unique hairpin loop conformation may provide a specific target for small molecules to modulate BCL2 gene transcription. I also explored the 3’ end G-quadruplex that forms within the core promoter of PDGFR-β, which has also been observed to be present at abnormal levels in a variety of clinical pathologies, including malignancies. The 3′-end G-quadruplex formed in the PDGFR-β promoter NHE appears to be selectively stabilized by an ellipticine analog, GSA1129, which can shift the dynamic equilibrium in the full-length sequence to favor the 3′-end G-quadruplex, and can repress PDGFR-β activity in cancer cell lines. NMR studies in combination with biophysical experiments have shown that in the wild-type extended 3ʼ-end NHE sequences, two novel intramolecular G-quadruplexes can be formed in a potassium solution, one with a 3’-flanking distant guanine inserted into the 3’-external tetrad (3’-insertion G-quadruplex), and another with a 5’-flanking distant guanine inserted into the 5’-external tetrad (5’-insertion G-quadruplex). Further investigation of the elongated PDGFR-β 3′-end sequence containing both the 5’- and 3’- flanking guanine sequences showed the formation of a combination of the two G-quadruplexes existing in equilibrium. Importantly, it was observed that GSA1129 can bind to and increase the stability of each of the end-insertion G-quadruplexes, raising their Tₘ by 25 degrees. This study highlights the dynamic nature of the 3′-end NHE sequence and the importance of identifying the proper sequence for the formation of biologically relevant G-quadruplex structures. Significantly, the dynamic nature of the 3′-end G-quadruplex suggests that it may be an attractive target for drug regulation. I then analyzed two proteins, Nucleolin and NM23-H2, which interact with the c-Myc G-quadruplex structure that forms in the proximal promoter region of the c-Myc gene; this is one of the most commonly deregulated genes in the human neoplasm. Nucleolin is known to be a transcriptional repressor for c-Myc, binding to and stabilizing the c-Myc G-quadruplex, whereas NM23-H2 is known to be a transcriptional activator that unwinds and destabilizes the c-Myc G-quadruplex. An investigation of the molecular mechanisms of the interaction between the c-Myc G-quadruplex and nucleolin showed that the minimal binding domains required for a tight binding of the protein to the c-Myc G-quadruplex are the four RNA binding domains (RBDs) of nucleolin, referred to as Nuc1234, and that the RGG domain is unnecessary for c-Myc G-quadruplex binding. The stable G-quadruplex formed within Pu27 using G-tract runs I, II, IV and V was determined to be the best substrate (Myc1245T) for nucleolin binding, showing the highest affinity. 3D NMR experiments performed on the free protein Nuc1234 and its complex with the Myc1245T G-quadruplex have shown that upon complex formation, only the disordered linker regions of the protein display significant chemical shift changes, whereas most other residues show chemical shift values similar to those of the free protein. The c-Myc G-quadruplex has three loops that flip outward in a solvent containing K⁺, according to its structure. The hypothesis for this association is that nucleolin wraps around the G-quadruplex and interacts specifically with the flipped-outward loop regions of the c-Myc G-quadruplex via its own inter-RBD linker regions, with little structural change in the RBDs themselves. A definitive determination of the 3D molecular structure of nucleolin and its complex with Myc1245T is currently in development. Biophysical and structural studies were then conducted to investigate the interactions of the protein NM23-H2/NDP kinase B with the c-Myc G-quadruplex. NM23-H2 binds to single-stranded guanine- and cytosine-rich sequences, but not to double-stranded DNA in the NHE III₁ region; the binding therefore appears structure-specific, rather than sequence-specific. Moreover, increasing concentrations of the strong G-quadruplex-interactive compound TMPyP4, a porphyrin-based drug, inhibits the binding of NM23-H2 to the NHE III₁ region; this suggests that the stabilization of the G-quadruplex hinders the recognition and remodeling function of the NM23-H2. By conducting Forster Resonance Energy Transfer (FRET) assays in combination with Circular Dichroism (CD) studies, I demonstrated that NM23-H2 can actively resolve the c-Myc G-quadruplex. Taken together, these results show that the use of small molecules to prevent NM23-H2 from binding to and resolving the NHE III₁ region G-quadruplex may have the potential to inhibit c-Myc transcription for cancer therapeutic purposes. This underlines the importance of understanding the mechanism of function operating between NM23-H2 and the c-Myc G-quadruplex. Understanding molecular mechanism between NM23-H2 and c-Myc is under investigation.

Transcription lies at the centre of gene expression. In eukaryotes, transcription occurs not only at genes but also across the non-coding portion of the genome, an apparently pervasive process that gives rise to a wide array of different transcripts. In recent years, it has emerged that genes themselves are frequently subject to non-coding transcription of their antisense strand. This antisense transcription is evident in eukaryotes from yeast to mammals; however its general genome-wide role, if indeed it has one, remains elusive. Here, the nature of antisense transcription in the budding yeast Saccharomyces cerevisiae is explored on a genome-wide scale. Antisense transcription is ubiquitous and often abundant, and appears to be driven by a promoter architecture at the 3’ end of genes, one which shows evidence of regulation, and which mirrors that found at the 5’ end. Furthermore, antisense transcription shows evidence of changing gene behaviour. It is associated with a drastically altered chromatin environment at the 5’ promoter and across the gene body; however it is not associated with a change in the level of gene transcription itself. Rather, these chromatin changes appear to enforce a change in the mode of gene transcription, promoting rapid bursts of transcription re-initiation that result in noisier gene expression – a hitherto unknown role of antisense transcription. It is proposed that antisense transcription represents a fundamental layer of gene regulation, and that it should be considered a canonical feature of eukaryotic genes.

Epigenetics is the study of heritable changes in gene expression that do not involve changes in the underlying DNA sequence. Epigenetic pathways appeared in eukaryotes where multicellular organisms differentiate into different cell types, associated with different phenotypes. The differentiation process is achieved by modifications of the chromatin structure which, by altering the access of trans-factors to the DNA, result in gene activation and repression. Epigenetic mechanisms are therefore viewed as an "extra" layer of information that modulate the genetic information in time and space, necessary for the development and the response to environment stimuli. Although the recent development of high-throughput sequencing technologies has provided an unprecedented insight into epigenetic pathways, the mechanisms controlling the chromatin dynamic as well as their downstream effects on cellular processes are far from being fully understood. In this thesis, our focus will be restricted to mechanisms acting on the nucleosome level. The first chapter will present the factors known to influence nucleosome positioning as well as the challenges related to the measurement of the nucleosome architecture. The second chapter will introduce a statistical approach, NucleoFinder, capable of identifying nucleosomes consistently positioned in a population of cells. In chapter three, we will make use of NucleoFinder to investigate the importance of cis and trans-factors on the nucleosome architecture in human and show that, despite variation across functional regions, cis-factors have a very modest in influence on nucleosome positioning. Finally, in chapter four, we will aim to identify clusters of histone modifications specific to functionally distinct regions, characterize their function and their association with gene expression level.

OBJECTIVES: The role of heterogeneous nuclear ribonucleoproteins in controlling hormone production is not well-understood. This study aims to determine the regulatory roles of hnRNP L and LL in hormone production. RESULTS: HnRNP LL knockdown dramatically reduced the mRNA level of growth hormone (GH) and prolactin (PRL) in GH3 pituitary cells, which was efficiently rescued by a Myc-hnRNP LL. In contrast, hnRNP L knockdown caused a 93-nucleotide intron retention with a decrease in the full-length Prl, which was rescued by a FLAG-hnRNP L. Double knockdown of hnRNPs indicates the interactions of hnRNPs for particular effects. The essential role of hnRNP LL for the secretion of GH and PRL was verified in primary pituitary cultures. Using RNA sequencing, a group of genes in hormone production that were differentially regulated by hnRNP L or LL were identified. CONCLUSION: These findings demonstrate the differential functions of two paralogous RNA processing factors in hormone production. / February 2016

<p>The growing complexity of scientific research demands further development of advanced gene regulation systems. For instance, the ultimate goal of tissue engineering is to develop constructs that functionally and morphologically resemble the native tissue they are expected to replace. This requires patterning of gene expression and control of cellular phenotype within the tissue engineered construct. In the field of synthetic biology, gene circuits are engineered to elucidate mechanisms of gene regulation and predict the behavior of more complex systems. Such systems require robust gene switches that can quickly turn gene expression on or off. Similarly, basic science requires precise genetic control to perturb genetic pathways or understand gene function. Additionally, gene therapy strives to replace or repair genes that are responsible for disease. The safety and efficacy of such therapies require control of when and where the delivered gene is expressed in vivo.</p><p>Unfortunately, these fields are limited by the lack of gene regulation systems that enable both robust and flexible cellular control. Most current gene regulation systems do not allow for the manipulation of gene expression that is spatially defined, temporally controlled, reversible, and repeatable. Rather, they provide incomplete control that forces the user to choose to control gene expression in either space or time, and whether the system will be reversible or irreversible.</p><p>The recent emergence of the field of optogenetics--the ability to control gene expression using light--has made it possible to regulate gene expression with spatial, temporal, and dynamic control. Light-inducible systems provide the tools necessary to overcome the limitations of other gene regulation systems, which can be slow, imprecise, or cumbersome to work with. However, emerging light-inducible systems require further optimization to increase their efficiency, reliability, and ease of use.</p><p>Initially, we engineered a light-inducible gene regulation system that combines zinc finger protein technology and the light-inducible interaction between Arabidopsis thaliana plant proteins GIGANTEA (GI) and the light oxygen voltage (LOV) domain of FKF1. Zinc finger proteins (ZFPs) can be engineered to target almost any DNA sequence through tandem assembly of individual zinc finger domains that recognize a specific three base-pair DNA sequence. Fusion of three different ZFPs to GI (GI-ZFP) successfully targeted the fusion protein to the specific DNA target sequence of the ZFP. Due to the interaction between GI and LOV, co-expression of GI-ZFP with a fusion protein consisting of LOV fused to three copies of the VP16 transactivation domain (LOV-VP16) enabled blue-light dependent recruitment of LOV-VP16 to the ZFP target sequence. We showed that placement of three to nine copies of a ZFP target sequence upstream of a luciferase or eGFP transgene enabled expression of the transgene in response to blue-light. Gene activation was both reversible and tunable based on duration of light exposure, illumination intensity, and the number of ZFP binding sites upstream of the transgene. Gene expression could also be spatially patterned by illuminating the cell culture through photomasks containing various patterns.</p><p>Although this system was useful for controlling the expression of a transgene, for many applications it is useful to control the expression of a gene in its natural chromosomal position. Therefore we capitalized on recent advances in programmed gene activation to engineer an optogenetic tool that could easily be targeted to new, endogenous DNA sequences without re-engineering the light inducible proteins. This approach took advantage of CRISPR/Cas9 technology, which uses a gene-specific guide RNA (gRNA) to facilitate Cas9 targeting and binding to a desired sequence, and the light-inducible heterodimerizers CRY2 and CIB1 from Arabidopsis thaliana to engineer a light-activated CRISPR/Cas9 effector (LACE) system. We fused the full-length (FL) CRY2 to the transcriptional activator VP64 (CRY2FL-VP64) and the N-terminal fragment of CIB1 to the N-, C-, or N- and C- terminus of a catalytically inactive Cas9. When CRY2-VP64 and one of the CIBN/dCas9 fusion proteins are expressed with a gRNA, the CIBN/dCas9 fusion protein localizes to the gRNA target. In the presence of blue light, CRY2FL binds to CIBN, which translocates CRY2FL-VP64 to the gene target and activates transcription. Unlike other optogenetic systems, the LACE system can be targeted to new endogenous loci by solely manipulating the specificity of the gRNA without having to re-engineer the light-inducible proteins. We achieved light-dependent activation of the IL1RN, HBG1/2, or ASCL1 genes by delivery of the LACE system and four gene-specific gRNAs per promoter region. For some gene targets, we achieved equivalent activation levels to cells that were transfected with the same gRNAs and the synthetic transcription factor dCas9-VP64. Gene activation was also shown to be reversible and repeatable through modulation of the duration of blue light exposure, and spatial patterning of gene expression was achieved using an eGFP reporter and a photomask. </p><p>Finally, we engineered a light-activated genetic "on" switch (LAGOS) that provides permanent gene expression in response to an initial dose of blue light illumination. LAGOS is a lentiviral vector that expresses a transgene only upon Cre recombinase-mediated DNA recombination. We showed that this vector, when used in conjunction with a light-inducible Cre recombinase system,1 could be used to express MyoD or the synthetic transcription factor VP64-MyoD2 in response to light in multiple mammalian cell lines, including primary mouse embryonic fibroblasts. We achieved light-mediated upregulation of downstream myogenic markers myogenin, desmin, troponin T, and myosin heavy chains I and II as well as fusion of C3H10T½ cells into myotubes that resembled a skeletal muscle cell phenotype. We also demonstrated LAGOS functionality in vivo by engineering the vector to express human VEGF165 and human ANG1 in response to light. HEK 293T cells stably expressing the LAGOS vector and transiently expressing the light-inducible Cre recombinase proteins were implanted into mouse dorsal window chambers. Mice that were illuminated with blue light had increased microvessel density compared to mice that were not illuminated. Analysis of human VEGF and human ANG1 levels by enzyme-linked immunosorbent assay (ELISA) revealed statistically higher levels of VEGF and ANG1 in illuminated mice compared to non-illuminated mice.</p><p>In summary, the objective of this work was to engineer robust light-inducible gene regulation systems that can control genes and cellular fate in a spatial and temporal manner. These studies combine the rapid advances in gene targeting and activation technology with natural light-inducible plant protein interactions. Collectively, this thesis presents several optogenetic systems that are expected to facilitate the development of multicellular cell and tissue constructs for use in tissue engineering, synthetic biology, gene therapy, and basic science both in vitro and in vivo.</p> / Dissertation