T-cell epitope prediction and immune complex simulation using molecular dynamics:state of the art and persisting challenges

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.

Glutamatergic input-output properties of thalamic astrocytes

Astrocytes in the somatosensory ventrobasal (VB) thalamus of rats respond to glutamatergic synaptic input with metabotropic glutamate receptor (mGluR) mediated intracellular calcium ([Ca²?](i)) elevations. Astrocytes in the VB thalamus also release the gliotransmitter (GT) glutamate in a Ca²?-dependent manner. The tripartite synapse hypothesis posits that astrocytic [Ca²?](i) elevations resulting from synaptic input releases gliotransmitters that then feedback to modify the synapse. Understanding the dynamics of this process and the conditions under which it occurs are therefore important steps in elucidating the potential roles and impact of GT release in particular brain activities. In this study, we investigated the relationship between VB thalamus afferent synaptic input and astrocytic glutamate release by recording N-methyl-D-aspartate (NMDA) receptor-mediated slow inward currents (SICs) elicited in neighboring neurons. We found that Lemniscal or cortical afferent stimulation, which can elicit astrocytic [Ca²?](i) elevations, do not typically result in the generation of SICs in thalamocortical (TC) neurons. Rather, we find that the spontaneous emergence of SICs is largely resistant to acute afferent input. The frequency of SICs, however, is correlated to long-lasting afferent activity. In contrast to short-term stimulus-evoked GT release effects reported in other brain areas, astrocytes in the VB thalamus do not express a straightforward input-output relationship for SIC generation but exhibit integrative characteristics.

Proteomic analysis of a noninvasive human model of acute inflammation and its resolution:the twenty-one day gingivitis model

The 21-day experimental gingivitis model, an established noninvasive model of inflammation in response to increasing bacterial accumulation in humans, is designed to enable the study of both the induction and resolution of inflammation. Here, we have analyzed gingival crevicular fluid, an oral fluid comprising a serum transudate and tissue exudates, by LC-MS/MS using Fourier transform ion cyclotron resonance mass spectrometry and iTRAQ isobaric mass tags, to establish meta-proteomic profiles of inflammation-induced changes in proteins in healthy young volunteers. Across the course of experimentally induced gingivitis, we identified 16 bacterial and 186 human proteins. Although abundances of the bacterial proteins identified did not vary temporally, Fusobacterium outer membrane proteins were detected. Fusobacterium species have previously been associated with periodontal health or disease. The human proteins identified spanned a wide range of compartments (both extracellular and intracellular) and functions, including serum proteins, proteins displaying antibacterial properties, and proteins with functions associated with cellular transcription, DNA binding, the cytoskeleton, cell adhesion, and cilia. PolySNAP3 clustering software was used in a multilayered analytical approach. Clusters of proteins that associated with changes to the clinical parameters included neuronal and synapse associated proteins.

Astrocyte plasticity:implications for synaptic and neuronal activity

Astrocytes are increasingly implicated in a range of functions in the brain, many of which were previously ascribed to neurons. Much of the prevailing interest centers on the role of astrocytes in the modulation of synaptic transmission and their involvement in the induction of forms of plasticity such as long-term potentiation and long-term depression. However, there is also an increasing realization that astrocytes themselves can undergo plasticity. This plasticity may be manifest as changes in protein expression which may modify calcium activity within the cells, changes in morphology that affect the environment of the synapse and the extracellular space, or changes in gap junction astrocyte coupling that modify the transfer of ions and metabolites through astrocyte networks. Plasticity in the way that astrocytes release gliotransmitters can also have direct effects on synaptic activity and neuronal excitability. Astrocyte plasticity can potentially have profound effects on neuronal network activity and be recruited in pathological conditions. An emerging principle of astrocyte plasticity is that it is often induced by neuronal activity, reinforcing our emerging understanding of the working brain as a constant interaction between neurons and glial cells. © The Author(s) 2013.

The Cascade Orthogonal Neural Network

In the paper new non-conventional growing neural network is proposed. It coincides with the Cascade- Correlation Learning Architecture structurally, but uses ortho-neurons as basic structure units, which can be adjusted using linear tuning procedures. As compared with conventional approximating neural networks proposed approach allows significantly to reduce time required for weight coefficients adjustment and the training dataset size.

Self-Learning Fuzzy Spiking Neural Network as a Nonlinear Pulse-Position Threshold Detection Dynamic System Based on Second-Order Critically Damped Response Units

Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.

Kinase C substrates and synaptic plasticity in Aplysia

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Contribution des réserves calciques présynaptiques et gliales dans la modulation de la transmission synaptique à la jonction neuromusculaire de la grenouille Rana pipiens

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

RNA Localization and Translational Regulation on the Endoplasmic Reticulum

mRNA localization is emerging as a critical cellular mechanism for the spatiotemporal regulation of protein expression and serves important roles in oogenesis, embryogenesis, cell fate specification, and synapse formation. Signal sequence-encoding mRNAs are localized to the endoplasmic reticulum (ER) membrane by either of two mechanisms, a canonical mechanism of translation on ER-bound ribosomes (signal recognition particle pathway), or a poorly understood direct ER anchoring mechanism. In this study, we identify that the ER integral membrane proteins function as RNA-binding proteins and play important roles in the direct mRNA anchoring to the ER. We report that one of the ER integral membrane RNA-binding protein, AEG-1 (astrocyte elevated gene-1), functions in the direct ER anchoring and translational regulation of mRNAs encoding endomembrane transmembrane proteins. HITS-CLIP and PAR-CLIP analyses of the AEG-1 mRNA interactome of human hepatocellular carcinoma cells revealed a high enrichment for mRNAs encoding endomembrane organelle proteins, most notably encoding transmembrane proteins. AEG-1 binding sites were highly enriched in the coding sequence and displayed a signature cluster enrichment downstream of encoded transmembrane domains. In overexpression and knockdown models, AEG-1 expression markedly regulates translational efficiency and protein functions of two of its bound transcripts, MDR1 and NPC1. This study reveals a molecular mechanism for the selective localization of mRNAs to the ER and identifies a novel post-transcriptional gene regulation function for AEG-1 in membrane protein expression.

Kinase C substrates and synaptic plasticity in Aplysia

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Contribution des réserves calciques présynaptiques et gliales dans la modulation de la transmission synaptique à la jonction neuromusculaire de la grenouille Rana pipiens

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Spike-timing dependent plasticity and connectivity in primate sensorimotor cortex

Thesis (Ph.D.)--University of Washington, 2016-06

Democratization in a passive dendritic tree: an analytical investigation

One way to achieve amplification of distal synaptic inputs on a dendritic tree is to scale the amplitude and/or duration of the synaptic conductance with its distance from the soma. This is an example of what is often referred to as “dendritic democracy”. Although well studied experimentally, to date this phenomenon has not been thoroughly explored from a mathematical perspective. In this paper we adopt a passive model of a dendritic tree with distributed excitatory synaptic conductances and analyze a number of key measures of democracy. In particular, via moment methods we derive laws for the transport, from synapse to soma, of strength, characteristic time, and dispersion. These laws lead immediately to synaptic scalings that overcome attenuation with distance. We follow this with a Neumann approximation of Green’s representation that readily produces the synaptic scaling that democratizes the peak somatic voltage response. Results are obtained for both idealized geometries and for the more realistic geometry of a rat CA1 pyramidal cell. For each measure of democratization we produce and contrast the synaptic scaling associated with treating the synapse as either a conductance change or a current injection. We find that our respective scalings agree up to a critical distance from the soma and we reveal how this critical distance decreases with decreasing branch radius.

I. Quantal effects in biochemical cooperativity and a proposed mechanism for the differentiation of calcium signaling in synaptic plasticity. II. Evolutionary algorithms for the optimization of methods in computational chemistry

In Part 1 of this thesis, we propose that biochemical cooperativity is a fundamentally non-ideal process. We show quantal effects underlying biochemical cooperativity and highlight apparent ergodic breaking at small volumes. The apparent ergodic breaking manifests itself in a divergence of deterministic and stochastic models. We further predict that this divergence of deterministic and stochastic results is a failure of the deterministic methods rather than an issue of stochastic simulations.

Ergodic breaking at small volumes may allow these molecular complexes to function as switches to a greater degree than has previously been shown. We propose that this ergodic breaking is a phenomenon that the synapse might exploit to differentiate Ca$^{2+}$ signaling that would lead to either the strengthening or weakening of a synapse. Techniques such as lattice-based statistics and rule-based modeling are tools that allow us to directly confront this non-ideality. A natural next step to understanding the chemical physics that underlies these processes is to consider \textit{in silico} specifically atomistic simulation methods that might augment our modeling efforts.

In the second part of this thesis, we use evolutionary algorithms to optimize \textit{in silico} methods that might be used to describe biochemical processes at the subcellular and molecular levels. While we have applied evolutionary algorithms to several methods, this thesis will focus on the optimization of charge equilibration methods. Accurate charges are essential to understanding the electrostatic interactions that are involved in ligand binding, as frequently discussed in the first part of this thesis.

Biochemical studies of postsynaptic density signaling proteins with a focus on synaptic GTPase activating protein and PDZ domains

Memory storage in the brain involves adjustment of the strength of existing synapses and formation of new neural networks. A key process underlying memory formation is synaptic plasticity, the ability of excitatory synapses to strengthen or weaken their connections in response to patterns of activity between their connected neurons. Synaptic plasticity is governed by the precise pattern of Ca²⁺ influx through postsynaptic N-methyl-D-aspartate-type glutamate receptors (NMDARs), which can lead to the activation of the small GTPases Ras and Rap. Differential activation of Ras and Rap acts to modulate synaptic strength by promoting the insertion or removal of 2-amino-3-(3-hydroxy-5-methyl-isoxazol-4-yl)propanoic acid receptors (AMPARs) from the synapse. Synaptic GTPase activating protein (synGAP) regulates AMPAR levels by catalyzing the inactivation of GTP-bound (active) Ras or Rap. synGAP is positioned in close proximity to the cytoplasmic tail regions of the NMDAR through its association with the PDZ domains of PSD-95. SynGAP’s activity is regulated by the prominent postsynaptic protein kinase, Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) and cyclin-dependent kinase 5 (CDK5), a known binding partner of CaMKII. Modulation of synGAP’s activity by phosphorylation may alter the ratio of active Ras to Rap in spines, thus pushing the spine towards the insertion or removal of AMPARs, subsequently strengthening or weakening the synapse. To date, all biochemical studies of the regulation of synGAP activity by protein kinases have utilized impure preparations of membrane bound synGAP. Here we have clarified the effects of phosphorylation of synGAP on its Ras and Rap GAP activities by preparing and utilizing purified, soluble recombinant synGAP, Ras, Rap, CaMKII, CDK5, PLK2, and CaM. Using mass spectrometry, we have confirmed the presence of previously identified CaMKII and CDK5 sites in synGAP, and have identified novel sites of phosphorylation by CaMKII, CDK5, and PLK2. We have shown that the net effect of phosphorylation of synGAP by CaMKII, CDK5, and PLK2 is an increase in its GAP activity toward HRas and Rap1. In contrast, there is no effect on its GAP activity toward Rap2. Additionally, by assaying the GAP activity of phosphomimetic synGAP mutants, we have been able to hypothesize the effects of CDK5 phosphorylation at specific sites in synGAP. In the course of this work, we also found, unexpectedly, that synGAP is itself a Ca²⁺/CaM binding protein. While Ca²⁺/CaM binding does not directly affect synGAP activity, it causes a conformational change in synGAP that increases the rate of its phosphorylation and exposes additional phosphorylation sites that are inaccessible in the absence of Ca²⁺/CaM.

The postsynaptic density (PSD) is an electron-dense region in excitatory postsynaptic neurons that contains a high concentration of glutamate receptors, cytoskeletal proteins, and associated signaling enzymes. Within the PSD, three major classes of scaffolding molecules function to organize signaling enzymes and glutamate receptors. PDZ domains present in the Shank and PSD-95 scaffolds families serve to physically link AMPARs and NMDARs to signaling molecules in the PSD. Because of the specificity and high affinity of PDZ domains for their ligands, I reasoned that these interacting pairs could provide the core components of an affinity chromatography system, including affinity resins, affinity tags, and elution agents. I show that affinity columns containing the PDZ domains of PSD-95 can be used to purify active PDZ domain-binding proteins to very high purity in a single step. Five heterologously expressed neuronal proteins containing endogenous PDZ domain ligands (NMDAR GluN2B subunit Tail, synGAP, neuronal nitric oxide synthase PDZ domain, cysteine rich interactor of PDZ three and cypin) were purified using PDZ domain resin, with synthetic peptides having the sequences of cognate PDZ domain ligands used as elution agents. I also show that conjugation of PDZ domain-related affinity tags to Proteins Of Interest (POIs) that do not contain endogenous PDZ domains or ligands does not alter protein activity and enables purification of the POIs on PDZ domain-related affinity resins.