SIGNALING MECHANISMS THAT CONTROL GAP JUNCTIONAL COUPLING BETWEEN RETINAL NEURONS

Gap junctions between neurons form the structural substrate for electrical synapses. Connexin 36 (Cx36, and its non-mammalian ortholog connexin 35) is the major neuronal gap junction protein in the central nervous system (CNS), and contributes to several important neuronal functions including neuronal synchronization, signal averaging, network oscillations, and motor learning. Connexin 36 is strongly expressed in the retina, where it is an obligatory component of the high-sensitivity rod photoreceptor pathway. A fundamental requirement of the retina is to adapt to broadly varying inputs in order to maintain a dynamic range of signaling output. Modulation of the strength of electrical coupling between networks of retinal neurons, including the Cx36-coupled AII amacrine cell in the primary rod circuit, is a hallmark of retinal luminance adaptation. However, very little is known about the mechanisms regulating dynamic modulation of Cx36-mediated coupling. The primary goal of this work was to understand how cellular signaling mechanisms regulate coupling through Cx36 gap junctions. We began by developing and characterizing phospho-specific antibodies against key regulatory phosphorylation sites on Cx36. Using these tools we showed that phosphorylation of Cx35 in fish models varies with light adaptation state, and is modulated by acute changes in background illumination. We next turned our focus to the well-studied and readily identifiable AII amacrine cell in mammalian retina. Using this model we showed that increased phosphorylation of Cx36 is directly related to increased coupling through these gap junctions, and that the dopamine-stimulated uncoupling of the AII network is mediated by dephosphorylation of Cx36 via protein kinase A-stimulated protein phosphatase 2A activity. We then showed that increased phosphorylation of Cx36 on the AII amacrine network is driven by depolarization of presynaptic ON-type bipolar cells as well as background light increments. This increase in phosphorylation is mediated by activation of extrasynaptic NMDA receptors associated with Cx36 gap junctions on AII amacrine cells and by Ca2+-calmodulin-dependent protein kinase II activation. Finally, these studies indicated that coupling is regulated locally at individual gap junction plaques. This work provides a framework for future study of regulation of Cx36-mediated coupling, in which increased phosphorylation of Cx36 indicates increased neuronal coupling.

Developmental Changes in the Structure and Composition of the Postsynaptic Density

The development of the brain and its underlying circuitry is dependent on the formation of trillions of chemical synapses, which are highly specialized contacts that regulate the flow of information from one neuron to the next. It is through these synaptic connections that neurons wire together into networks capable of performing specific tasks, and activity-dependent changes in their structural and physiological state is one way that the brain is thought to adapt and store information. At the ultrastructural level, developmental and activity-dependent changes in the size and shape of dendritic spines have been well documented, and it is widely believed that structural changes in spines are a hallmark sign of synapse maturation and alteration of synaptic physiology. While changes in spine structure have been studied extensively, changes in one of its most prominent components, the postsynaptic density (PSD), have largely evaded observation. The PSD is a protein-rich organelle on the cytoplasmic side of the postsynaptic membrane, where it sits in direct opposition to the presynaptic terminal. The PSD functions both to cluster neurotransmitter receptors at the cell surface as well as organize the intracellular signaling molecules responsible for transducing extracellular signals to the postsynaptic cell. Much is known about the chemical composition of the PSD, but the structural arrangement of its molecular components is not well documented. Adding to the difficulty of understanding such a complex mass of protein machinery is the fact that its protein composition is known to change in response to synaptic activity, meaning that its structure is plastic and no two PSDs are identical. Here, immuno-gold labeling and electron tomography of PSDs isolated throughout development was used to track changes in both the structure and molecular composition of the PSD. State-of-the-art cryo-electron tomography was used to study the fine structure of the PSD during development, and provides an unprecedented glimpse into its molecular architecture in an un-fixed, unstained and hydrated state. Through this analysis, large structural and compositional changes are apparent and suggest a model by which the PSD is first assembled as a mesh-like lattice of proteins that function as support for the later recruitment of various PSD components. Spatial analysis of the recruitment of proteins into the PSD demonstrated that its assembly has an underlying order.

Glycogen Synthase Kinase 3 is Required for Optimal AKT Activation

The phosphatidylinositol 3-kinase (PI3K) pathway, through its major effector node AKT, is critical for the promotion of cell growth, division, motility and apoptosis evasion. This signaling axis is therefore commonly targeted in the form of mutations and amplifications in a myriad of malignancies. Glycogen synthase kinase 3 (GSK3) was first discovered as the kinase responsible for phosphorylating and inhibiting the activity of glycogen synthase, ultimately antagonizing the storage of glucose as glycogen. Its activity counteracts the effects of insulin in glucose metabolism and AKT has long been recognized as one of the key molecules capable of phosphorylating GSK3 and inhibiting its activity. However, here we demonstrate that GSK3 is required for optimal phosphorylation and activation of AKT in different malignant cell lines, and that this effect is independent of the type of growth factor stimulation and can happen even in basal states. Both GSK3 alpha and GSK3 beta isoforms are necessary for AKT to become fully active, displaying a redundant role in the setting. We also demonstrate that this effect of GSK3 on AKT phosphorylation and full activation is dependent on its kinase activity, since highly specific inhibitors targeting GSK3 catalytic activity also promote a reduction in phosphorylated AKT. Analysis of reverse phase protein array screening of MDA-MB-231 breast cancer cells treated with RNA interference targeting GSK3 unexpectedly revealed an increase in levels of phosphorylated MAPK14 (p38). Treatment with the selective p38 inhibitor SB 202190 rescued AKT activation in that cell line, corroborating the importance of unbiased proteomic analysis in exposing cross-talks between signaling networks and demonstrating a critical role for p38 in the regulation of AKT phosphorylation.

POPULATION CODING IN LAMINAR CORTICAL CIRCUITS

One of the fundamental questions in neuroscience is to understand how encoding of sensory inputs is distributed across neuronal networks in cerebral cortex to influence sensory processing and behavioral performance. The fact that the structure of neuronal networks is organized according to cortical layers raises the possibility that sensory information could be processed differently in distinct layers. The goal of my thesis research is to understand how laminar circuits encode information in their population activity, how the properties of the population code adapt to changes in visual input, and how population coding influences behavioral performance. To this end, we performed a series of novel experiments to investigate how sensory information in the primary visual cortex (V1) emerges across laminar cortical circuits. First, it is commonly known that the amount of information encoded by cortical circuits depends critically on whether or not nearby neurons exhibit correlations. We examined correlated variability in V1 circuits from a laminar-specific perspective and observed that cells in the input layer, which have only local projections, encode incoming stimuli optimally by exhibiting low correlated variability. In contrast, output layers, which send projections to other cortical and subcortical areas, encode information suboptimally by exhibiting large correlations. These results argue that neuronal populations in different cortical layers play different roles in network computations. Secondly, a fundamental feature of cortical neurons is their ability to adapt to changes in incoming stimuli. Understanding how adaptation emerges across cortical layers to influence information processing is vital for understanding efficient sensory coding. We examined the effects of adaptation, on the time-scale of a visual fixation, on network synchronization across laminar circuits. Specific to the superficial layers, we observed an increase in gamma-band (30-80 Hz) synchronization after adaptation that was correlated with an improvement in neuronal orientation discrimination performance. Thus, synchronization enhances sensory coding to optimize network processing across laminar circuits. Finally, we tested the hypothesis that individual neurons and local populations synchronize their activity in real-time to communicate information about incoming stimuli, and that the degree of synchronization influences behavioral performance. These analyses assessed for the first time the relationship between changes in laminar cortical networks involved in stimulus processing and behavioral performance.

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.

Fibulin-2 stabilizes tumor extracellular matrix and drives malignant progression of lung adenocarcinoma

The ECM of epithelial carcinomas undergoes structural remodeling during periods of uncontrolled growth, creating regional heterogeneity and torsional stress. How tumors maintain ECM integrity in the face of dynamic biophysical forces is still largely unclear. This study addresses these deficiencies using mouse models of human lung adenocarcinoma. Spontaneous lung tumors were marked by disorganized basement membranes, dense collagen networks, and increased tissue stiffness. Metastasis-prone lung adenocarcinoma cells secreted fibulin-2 (Fbln2), a matrix glycoprotein involved in ECM supra-molecular assembly. Fibulin-2 depletion in tumor cells decreased the intra-tumoral abundance of matrix metalloproteinases and reduced collagen cross-linking and tumor compressive properties resulting in inhibited tumor growth and metastasis. Fbln2 deposition within intra-tumoral fibrotic bands was a predictor of poor clinical outcome in patients. Collectively, these findings support a feed-forward model in which tumor cells secrete matrix-stabilizing factors required for the assembly of ECM that preferentially favors malignant progression. To our knowledge, this is the first evidence that tumor cells directly regulate the integrity of their surrounding matrix through the secretion of matrix-stabilizing factors such as fibulin-2. These findings open a new avenue of research into matrix assembly molecules as potential therapeutic targets in cancer patients.

REGULATION OF ALTERNATIVE CARBON METABOLISM IN CANDIDA ALBICANS

Candida albicans is the most important fungal pathogen of humans. Transcript profiling studies show that upon phagocytosis by macrophages, C. albicans undergoes a massive metabolic reorganization activating genes involved in alternative carbon metabolism, including the glyoxylate cycle, β-oxidation and gluconeogenesis. Mutations in key enzymes such as ICL1 (glyoxylate cycle) and FOX2 (fatty acid β-oxidation) revealed that alternative carbon metabolic pathways are required for full virulence in C. albicans. These studies indicate C. albicans uses non-preferred carbon sources allowing its adaptation to microenvironments were nutrients are scarce. It has become apparent that the regulatory networks required for regulation of alternative carbon metabolism in C. albicans are considerably different from the Saccharomyces cerevisiae paradigm and appear more analogous to the Aspergillus nidulans systems. Well-characterized transcription factors in S. cerevisiae have no apparent phenotype or are missing in C. albicans. CTF1 was found to be a single functional homolog of the A. nidulans FarA/FarB proteins, which are transcription factors required for fatty acid utilization. Both FOX2 and ICL1 were found to be part of a large CTF1 regulon. To increase our understanding of how CTF1 regulates its target genes, including whether regulation is direct or indirect, the FOX2 and ICL1 promoter regions were analyzed using a combination of bioinformatics and promoter deletion analysis. To begin characterizing the FOX2 and ICL1 promoters, 5’ rapid amplification of cDNA ends (5’RACE) was used to identify two transcriptional initiation sites in FOX2 and one in ICL1. GFP reporter assays show FOX2 and ICL1 are rapidly expressed in the presence of alternative carbon sources. Both FOX2 and ICL1 harbor the CCTCGG sequence known to be bound by the Far proteins, hence rendering the motif as a putative CTF1 DNA binding element. In this study, the CCTCGG sequence was found to be essential for FOX2 regulation. However, this motif does not appear to be equally important for the regulation of ICL1. This study supports the notion that although C. albicans has diverged from the paradigms of model fungi, C. albicans has made specific adaptations to its transcription-based regulatory network that may contribute to its metabolic flexibility.

Pathway Semantics: An Algebraic Data Driven Algorithm to Generate Hypotheses about Molecular Patterns Underlying Disease Progression

The overarching goal of the Pathway Semantics Algorithm (PSA) is to improve the in silico identification of clinically useful hypotheses about molecular patterns in disease progression. By framing biomedical questions within a variety of matrix representations, PSA has the flexibility to analyze combined quantitative and qualitative data over a wide range of stratifications. The resulting hypothetical answers can then move to in vitro and in vivo verification, research assay optimization, clinical validation, and commercialization. Herein PSA is shown to generate novel hypotheses about the significant biological pathways in two disease domains: shock / trauma and hemophilia A, and validated experimentally in the latter. The PSA matrix algebra approach identified differential molecular patterns in biological networks over time and outcome that would not be easily found through direct assays, literature or database searches. In this dissertation, Chapter 1 provides a broad overview of the background and motivation for the study, followed by Chapter 2 with a literature review of relevant computational methods. Chapters 3 and 4 describe PSA for node and edge analysis respectively, and apply the method to disease progression in shock / trauma. Chapter 5 demonstrates the application of PSA to hemophilia A and the validation with experimental results. The work is summarized in Chapter 6, followed by extensive references and an Appendix with additional material.