Brain type II calcium and calmodulin-dependent protein kinase: characterization of a brain-region specific isozyme and regulation by autophosphorylation

A variety of molecular approaches have been used to investigate the structural and enzymatic properties of rat brain type ll Ca^(2+) and calmodulin-dependent protein kinase (type ll CaM kinase). This thesis describes the isolation and biochemical characterization of a brain-region specific isozyme of the kinase and also the regulation the kinase activity by autophosphorylation.

The cerebellar isozyme of the type ll CaM kinase was purified and its biochemical properties were compared to the forebrain isozyme. The cerebellar isozyme is a large (500-kDa) multimeric enzyme composed of multiple copies of 50-kDa α subunits and 60/58-kDa β/β’ subunits. The holoenzyme contains approximately 2 α subunits and 8 β subunits. This contrasts to the forebrain isozyme, which is also composed of and β/β'subunits, but they are assembled into a holoenzyme of approximately 9 α subunits and 3 β/β ' subunits. The biochemical and enzymatic properties of the two isozymes are similar. The two isozymes differ in their association with subcellular structures. Approximately 85% of the cerebellar isozyme, but only 50% of the forebrain isozyme, remains associated with the particulate fraction after homogenization under standard conditions. Postsynaptic densities purified from forebrain contain the forebrain isozyme, and the kinase subunits make up about 16% of their total protein. Postsynaptic densities purified from cerebellum contain the cerebellar isozyme, but the kinase subunits make up only 1-2% of their total protein.

The enzymatic activity of both isozymes of the type II CaM kinase is regulated by autophosphorylation in a complex manner. The kinase is initially completely dependent on Ca^(2+)/calmodulin for phosphorylation of exogenous substrates as well as for autophosphorylation. Kinase activity becomes partially Ca^(2+) independent after autophosphorylation in the presence of Ca^(2+)/calmodulin. Phosphorylation of only a few subunits in the dodecameric holoenzyme is sufficient to cause this change, suggesting an allosteric interaction between subunits. At the same time, autophosphorylation itself becomes independent of Ca^(2+) These observations suggest that the kinase may be able to exist in at least two stable states, which differ in their requirements for Ca^(2+)/calmodulin.

The autophosphorylation sites that are involved in the regulation of kinase activity have been identified within the primary structure of the α and β subunits. We used the method of reverse phase-HPLC tryptic phosphopeptide mapping to isolate individual phosphorylation sites. The phosphopeptides were then sequenced by gas phase microsequencing. Phosphorylation of a single homologous threonine residue in the α and β subunits is correlated with the production of the Ca^(2+) -independent activity state of the kinase. In addition we have identified several sites that are phosphorylated only during autophosphorylation in the absence of Ca^(2+)/ calmodulin.

Identification of fucose-α(1-2)-galactose binding proteins in the mammalian brain

Fucose-α(1-2)-galactose (Fucα(1-2)Gal) carbohydrates have been implicated in cognitive functions. However, the underlying molecular mechanisms that govern these processes are not well understood. While significant progress has been made toward identifying glycoconjugates bearing this carbohydrate epitope, a major challenge remains the discovery of interactions mediated by these sugars. Here, we employ the use of multivalent glycopolymers to enable the proteomic identification of weak affinity, low abundant Fucα(1-2)Gal-binding proteins (i.e. lectins) from the brain. End-biotinylated glycopolymers containing photoactivatable crosslinkers were used to capture and enrich potential Fucα(1-2)Gal-specific lectins from rat brain lysates. Candidate lectins were tested for their ability to bind Fucα(1-2)Gal, and the functional significance of the interaction was investigated for one such candidate, SV2a, using a knock-out mouse system. Our results suggest an important role for this glycan-lectin interaction in facilitating synaptic changes necessary for neuronal communication. This study highlights the use of glycopolymer mimetics to discover novel lectins and identify functional interactions between fucosyl carbohydrates and lectins in the brain.

Sensor networks for geospatial event detection - theory and applications

This thesis presents theories, analyses, and algorithms for detecting and estimating parameters of geospatial events with today's large, noisy sensor networks. A geospatial event is initiated by a significant change in the state of points in a region in a 3-D space over an interval of time. After the event is initiated it may change the state of points over larger regions and longer periods of time. Networked sensing is a typical approach for geospatial event detection. In contrast to traditional sensor networks comprised of a small number of high quality (and expensive) sensors, trends in personal computing devices and consumer electronics have made it possible to build large, dense networks at a low cost. The changes in sensor capability, network composition, and system constraints call for new models and algorithms suited to the opportunities and challenges of the new generation of sensor networks. This thesis offers a single unifying model and a Bayesian framework for analyzing different types of geospatial events in such noisy sensor networks. It presents algorithms and theories for estimating the speed and accuracy of detecting geospatial events as a function of parameters from both the underlying geospatial system and the sensor network. Furthermore, the thesis addresses network scalability issues by presenting rigorous scalable algorithms for data aggregation for detection. These studies provide insights to the design of networked sensing systems for detecting geospatial events. In addition to providing an overarching framework, this thesis presents theories and experimental results for two very different geospatial problems: detecting earthquakes and hazardous radiation. The general framework is applied to these specific problems, and predictions based on the theories are validated against measurements of systems in the laboratory and in the field.

Nonlinear dynamic transfer functions for certain retinal neuronal systems

The applicability of the white-noise method to the identification of a nonlinear system is investigated. Subsequently, the method is applied to certain vertebrate retinal neuronal systems and nonlinear, dynamic transfer functions are derived which describe quantitatively the information transformations starting with the light-pattern stimulus and culminating in the ganglion response which constitutes the visually-derived input to the brain. The retina of the catfish, Ictalurus punctatus, is used for the experiments.

The Wiener formulation of the white-noise theory is shown to be impractical and difficult to apply to a physical system. A different formulation based on crosscorrelation techniques is shown to be applicable to a wide range of physical systems provided certain considerations are taken into account. These considerations include the time-invariancy of the system, an optimum choice of the white-noise input bandwidth, nonlinearities that allow a representation in terms of a small number of characterizing kernels, the memory of the system and the temporal length of the characterizing experiment. Error analysis of the kernel estimates is made taking into account various sources of error such as noise at the input and output, bandwidth of white-noise input and the truncation of the gaussian by the apparatus.

Nonlinear transfer functions are obtained, as sets of kernels, for several neuronal systems: Light → Receptors, Light → Horizontal, Horizontal → Ganglion, Light → Ganglion and Light → ERG. The derived models can predict, with reasonable accuracy, the system response to any input. Comparison of model and physical system performance showed close agreement for a great number of tests, the most stringent of which is comparison of their responses to a white-noise input. Other tests include step and sine responses and power spectra.

Many functional traits are revealed by these models. Some are: (a) the receptor and horizontal cell systems are nearly linear (small signal) with certain "small" nonlinearities, and become faster (latency-wise and frequency-response-wise) at higher intensity levels, (b) all ganglion systems are nonlinear (half-wave rectification), (c) the receptive field center to ganglion system is slower (latency-wise and frequency-response-wise) than the periphery to ganglion system, (d) the lateral (eccentric) ganglion systems are just as fast (latency and frequency response) as the concentric ones, (e) (bipolar response) = (input from receptors) - (input from horizontal cell), (f) receptive field center and periphery exert an antagonistic influence on the ganglion response, (g) implications about the origin of ERG, and many others.

An analytical solution is obtained for the spatial distribution of potential in the S-space, which fits very well experimental data. Different synaptic mechanisms of excitation for the external and internal horizontal cells are implied.

Selective data gathering in community sensor networks

Smartphones and other powerful sensor-equipped consumer devices make it possible to sense the physical world at an unprecedented scale. Nearly 2 million Android and iOS devices are activated every day, each carrying numerous sensors and a high-speed internet connection. Whereas traditional sensor networks have typically deployed a fixed number of devices to sense a particular phenomena, community networks can grow as additional participants choose to install apps and join the network. In principle, this allows networks of thousands or millions of sensors to be created quickly and at low cost. However, making reliable inferences about the world using so many community sensors involves several challenges, including scalability, data quality, mobility, and user privacy.

This thesis focuses on how learning at both the sensor- and network-level can provide scalable techniques for data collection and event detection. First, this thesis considers the abstract problem of distributed algorithms for data collection, and proposes a distributed, online approach to selecting which set of sensors should be queried. In addition to providing theoretical guarantees for submodular objective functions, the approach is also compatible with local rules or heuristics for detecting and transmitting potentially valuable observations. Next, the thesis presents a decentralized algorithm for spatial event detection, and describes its use detecting strong earthquakes within the Caltech Community Seismic Network. Despite the fact that strong earthquakes are rare and complex events, and that community sensors can be very noisy, our decentralized anomaly detection approach obtains theoretical guarantees for event detection performance while simultaneously limiting the rate of false alarms.

Effects of TI-299423 on Neuronal Nicotinic Acetylcholine Receptors

Nicotinic acetylcholine receptors (nAChRs) are pentameric, ligand-gated, cation channels found throughout the central and peripheral nervous system, whose endogenous ligand is acetylcholine, but which can also be acted upon by nicotine. The subunit compositions of nAChR determine their physiological and pharmacological properties, with different subunits expressed in different combinations or areas throughout the brain. The behavioral and physiological effects of nicotine are elicited by its agonistic and desensitizing actions selectively on neuronal nAChRs. The midbrain is of particular interest due to its population of nAChRs expressed on dopaminergic neurons, which are important for reward and reinforcement, and possibly contribute to nicotine dependence. The α6-subunit is found on dopaminergic neurons but very few other regions of the brain, making it an interesting drug target. We assayed a novel nicotinic agonist, called TI-299423 or TC299, for its possible selectivity for α6-containing nAChRs. Our goal was to isolate the role of α6-containing nAChRs in nicotine reward and reinforcement, and provide insight into the search for more effective smoking cessation compounds. This was done using a variety of in vitro and behavioral assays, aimed dually at understanding TI-299423’s exact mechanism of action and its downstream effects. Additionally, we looked at the effects of another compound, menthol, on nicotine reward. Understanding how reward is generated in the cholinergic system and how that is modulated by other compounds contributes to a better understand of our complex neural circuitry and provides insight for the future development of therapeutics.

Binding Studies of Neuronal Nicotinic Acetylcholine Receptors Expressing Unnatural Amino Acids

Nicotinic acetylcholine receptors are pentameric ligand-gated ion channels mediating fast synaptic transmission throughout the peripheral and central nervous systems. They have been implicated in various processes related to cognitive functions, learning and memory, arousal, reward, motor control and analgesia. Therefore, these receptors present alluring potential therapeutic targets for the treatment of pain, epilepsy, Alzheimer’s disease, Parkinson’s disease, Tourette’s syndrome, schizophrenia, anxiety, depression and nicotine addiction. The work detailed in this thesis focuses on binding studies of neuronal nicotinic receptors and aims to further our knowledge of subtype specific functional and structural information.

Chapter 1 is an introductory chapter describing the structure and function of nicotinic acetylcholine receptors as well as the methodologies used for the dissertation work described herein. There are several different subtypes of nicotinic acetylcholine receptors known to date and the subtle variations in their structure and function present a challenging area of study. The work presented in this thesis deals specifically with the α4β2 subtype of nicotinic acetylcholine receptor. This subtype assembles into 2 closely related stoichiometries, termed throughout this thesis as A3B2 and A2B3 after their respective subunit composition. Chapter 2 describes binding studies of select nicotinic agonists on A3B2 and A2B3 receptors determined by whole-cell recording. Three key binding interactions, a cation-π and two hydrogen bonds, were probed for four nicotinic agonists, acetylcholine, nicotine, smoking cessation drug varenicline (Chantix®) and the related natural product cytisine.

Results from the binding studies presented in Chapter 2 show that the major difference in binding of these four agonists to A3B2 and A2B3 receptors lies in one of the two hydrogen bond interactions where the agonist acts as the hydrogen bond acceptor and the backbone NH of a conserved leucine residue in the receptor acts as the hydrogen bond donor. Chapter 3 focuses on studying the effect of modulating the hydrogen bond acceptor ability of nicotine and epibatidine on A3B2 receptor function determined by whole-cell recording. Finally, Chapter 4 describes single-channel recording studies of varenicline binding to A2B3 and A3B2 receptors.