Neural Modeling and Imaging of the Cortical Interactions Underlying Syllable Production

This paper describes a neural model of speech acquisition and production that accounts for a wide range of acoustic, kinematic, and neuroimaging data concerning the control of speech movements. The model is a neural network whose components correspond to regions of the cerebral cortex and cerebellum, including premotor, motor, auditory, and somatosensory cortical areas. Computer simulations of the model verify its ability to account for compensation to lip and jaw perturbations during speech. Specific anatomical locations of the model's components are estimated, and these estimates are used to simulate fMRI experiments of simple syllable production with and without jaw perturbations.National Institute on Deafness and Other Communication Disorders (R01 DC02852, RO1 DC01925

Pulling apart the intermolecular interactions of the Parkinson’s disease linked protein alpha synuclein

Amyloidoses are a group of protein misfolding diseases that are characterised by the abnormal accumulation of highly ordered filamentous assemblies known as amyloid. This phenomenon is associated with more than 50 human diseases, some of which are the most debilitating disorders that threaten human health today. Many of these disorders have age as the main contributing risk factor and, therefore, pose an ever-increasing risk in the developed world with aging societies. Despite intense research, much remains unknown about the fundamental processes driving protein aggregation in these diseases and there are few disease modifying treatments available. A protein that undergoes amyloid formation and causes disease is the intrinsically disordered neuronal protein α-synuclein (αSyn), the aggregation of which leads to several diseases including Parkinson’s disease (PD) which is the second-most common neurodegenerative disorder that affects 2–3% of the population ≥65 years of age. Importantly, the toxic species on the aggregation pathway are difficult to identify and determine in molecular detail. This thesis was motivated by this fact and aimed to study the initial intermolecular events in αSyn self-assembly (dimerisation) on a single molecule scale. Single molecule force spectroscopy (SMFS) methodologies were therefore utilised in order to study these early protein-protein interaction events. A display system was firstly designed and validated in which small regions of highly aggregation-prone sequences can be presented in a protein scaffold in a robust and reproducible manner for SMFS studies. It was demonstrated that intermolecular interactions of these sequences could be analysed by implementing this system. A novel heterodimeric interaction between the central aggregation-prone regions of αSyn (residues 71-82) and the same region of its human homologue γSynuclein (γSyn), were revealed by using this system. Further study led to the finding that this interaction played a role in the inhibiting the aggregation of αSyn. The dimerisation interaction of full length αSyn has also been analysed in this thesis and several important findings have been demonstrated. The SMFS experiments show that force-resistant structure forms in the dimeric species of αSyn and that this structure is dependent on the environmental conditions. SMFS utilising different immobilisation regimes of αSyn have also allowed the location of a novel interaction interface involving the N-terminal region of the protein. Further SMFS experiments investigating the effects of salt and hydrophobicity have on dimerisation, alongside bioinformatics analyses of the protein sequence led to the hypotheses that the dimeric interaction is driven by hydrophobic stretches in the N-terminal region, but modulated by local electrostatics. In vitro aggregation assays and SMFS on non-aggregation-prone synuclein homologues (β- and γSyn) indicated that that this interaction is protective against aggregation, considering these finding with existing literature prompted speculation that the interactions observed in SMFS may indeed be physiologically relevant. This may therefore be an important finding in regards to targeting the aggregation process with disease modifying agents

Nuclear inclusions of pathogenic ataxin-1 induce oxidative stress and perturb the protein synthesis machinery

Spinocerebellar ataxia type-1 (SCA1) is caused by an abnormally expanded polyglutamine (polyQ) tract in ataxin-1. These expansions are responsible for protein misfolding and self-assembly into intranuclear inclusion bodies (IIBs) that are somehow linked to neuronal death. However, owing to lack of a suitable cellular model, the downstream consequences of IIB formation are yet to be resolved. Here, we describe a nuclear protein aggregation model of pathogenic human ataxin-1 and characterize IIB effects. Using an inducible Sleeping Beauty transposon system, we overexpressed the ATXN1(Q82) gene in human mesenchymal stem cells that are resistant to the early cytotoxic effects caused by the expression of the mutant protein. We characterized the structure and the protein composition of insoluble polyQ IIBs which gradually occupy the nuclei and are responsible for the generation of reactive oxygen species. In response to their formation, our transcriptome analysis reveals a cerebellum-specific perturbed protein interaction network, primarily affecting protein synthesis. We propose that insoluble polyQ IIBs cause oxidative and nucleolar stress and affect the assembly of the ribosome by capturing or down-regulating essential components. The inducible cell system can be utilized to decipher the cellular consequences of polyQ protein aggregation. Our strategy provides a broadly applicable methodology for studying polyQ diseases

A Knowledge-based Integrative Modeling Approach for <em>In-Silico</em> Identification of Mechanistic Targets in Neurodegeneration with Focus on Alzheimer’s Disease

Dementia is the progressive decline in cognitive function due to damage or disease in the body beyond what might be expected from normal aging. Based on neuropathological and clinical criteria, dementia includes a spectrum of diseases, namely Alzheimer's dementia, Parkinson's dementia, Lewy Body disease, Alzheimer's dementia with Parkinson's, Pick's disease, Semantic dementia, and large and small vessel disease. It is thought that these disorders result from a combination of genetic and environmental risk factors. Despite accumulating knowledge that has been gained about pathophysiological and clinical characteristics of the disease, no coherent and integrative picture of molecular mechanisms underlying neurodegeneration in Alzheimer’s disease is available. Existing drugs only offer symptomatic relief to the patients and lack any efficient disease-modifying effects. The present research proposes a knowledge-based rationale towards integrative modeling of disease mechanism for identifying potential candidate targets and biomarkers in Alzheimer’s disease. Integrative disease modeling is an emerging knowledge-based paradigm in translational research that exploits the power of computational methods to collect, store, integrate, model and interpret accumulated disease information across different biological scales from molecules to phenotypes. It prepares the ground for transitioning from ‘descriptive’ to “mechanistic” representation of disease processes. The proposed approach was used to introduce an integrative framework, which integrates, on one hand, extracted knowledge from the literature using semantically supported text-mining technologies and, on the other hand, primary experimental data such as gene/protein expression or imaging readouts. The aim of such a hybrid integrative modeling approach was not only to provide a consolidated systems view on the disease mechanism as a whole but also to increase specificity and sensitivity of the mechanistic model by providing disease-specific context. This approach was successfully used for correlating clinical manifestations of the disease to their corresponding molecular events and led to the identification and modeling of three important mechanistic components underlying Alzheimer’s dementia, namely the CNS, the immune system and the endocrine components. These models were validated using a novel in-silico validation method, namely biomarker-guided pathway analysis and a pathway-based target identification approach was introduced, which resulted in the identification of the MAPK signaling pathway as a potential candidate target at the crossroad of the triad components underlying disease mechanism in Alzheimer’s dementia

Investigating the neuroprotective effects of histone deacetylase inhibitors in Parkinson's Disease

Parkinson’s disease (PD) is the most common movement disorder and the second most common neurodegenerative disease affecting around 4 million people worldwide. Movement symptoms in PD are primarily due to degeneration of dopaminergic nigrostriatal neurons. These symptoms can be partially controlled by dopamine replacement therapies, however long term use of these drugs lead to debilitating side-effects and more importantly do not protect degenerating dopaminergic neurons from death. Hence novel neuroprotective strategies are sought. Recent evidence implicates αSynuclein accumulation, the hallmark of degenerating neurons in PD, with perturbed epigenetic acetylation of histone proteins around which DNA is coiled. A misbalance between the activities of the two enzyme classes responsible for control of histone acetylation, histone acetyltransferases and histone deacetylases (HDACs), have been linked to cell death in animal models of neurodegeneration. It is therefore hypothesised that if this pathogenic imbalance can be rectified with the use of HDAC inhibitors (HDACIs) then neurodegeneration observed in PD can be avoided. Here, the first evidence of altered histone acetylation and perturbed HDAC isoform expression in degenerating regions of the human Parkinsonian brain are demonstrated. Cell culture studies using dopaminergic neuronal and microglial cell lines demonstrate that dependent on the HDAC class(s) or isoform(s) inhibited, HDACIs are capable of inducing neuroprotection and reduction of microglial activation in vitro. Study of two broad-spectrum HDACIs in vivo, in the lactacystin rat model of PD demonstrate that, also dependent on isoform inhibition, HDACIs cause dose-dependent histone acetylation and upregulated expression of neurotrophic and neuroprotective factors, resulting in dopaminergic nigrostriatal neuroprotection and reduction of morphological changes and motor behavioural deficits detected through magnetic resonance imaging and behavioural testing respectively. Taken together the data herein provide compelling evidence to support the concept that dependent on isoform specificity, HDACIs represent a novel class of neuroprotective therapeutics for the treatment of PD.Open Acces

Molecular insights into RBR E3 ligase ubiquitin transfer mechanisms

National Institute of General Medical Sciences R01 GM0880555T32 GM007270, Francis Crick Institute FCI01, Cancer Research UK, Medical Research Council U117565398, Wellcome Trus

Characterization of the Interaction between the Parkin Ubiquitin-like domain and Ataxin-3 Ubiquitin Interacting Domains

The ubiquitin signaling pathway (USP) consists of hundreds of enzymes which are tightly regulated for proper maintenance of intracellular protein level homeostasis. The main goals of this thesis were to characterize the interaction of two proteins involved in the USP, the E3 ubiquitin ligase called parkin, and the Deubiquitinating (DUB) enzyme, ataxin-3. The effect of disease-state substitutions in the parkin ubiquitin-like domain (UbLD) on the interaction with ataxin-3 was investigated through NMR 1H-15N HSQC titration experiments and affinity binding assays. The three UIM regions in ataxin-3bind the hydrophobic patch of parkin UbLD (KD = 680 μM) and are proposed to use a multivalent binding mechanism. The disease-state UbLD proteins (UbLDV15M, UbLDR33Q, UbLDK48A) retain their interaction with ataxin-3. Other DUB enzymes and E3 ligases have been reported to have regulatory interplay, which has triggered interest in studying protein pairings such as ataxin-3 and parkin

Investigating reach and grasp in Parkinson's disease cognitive impairment

Reach and grasp are evolutionary conserved motor actions controlled by highly specialised neural pathways that have major nodes in the posterior parietal and premotor frontal cortices. Mild cognitive impairment is an important non-motor symptom of Parkinson’s disease (PD) and there is evidence that the risk of transition between PD mild cognitive impairment (PD-MCI) and Parkinson’s disease dementia (PDD) is dependent on which neurotransmitter systems within the brain are most dysfunctional. Studies of reach and grasp in PD subjects with normal cognition (PD-NC) suggest a greater dependence on visual feedback to guide reach and grasp compared with controls.The primary aim of this thesis is to explore how cognitive impairment influences reach and grasp in PD. Twenty two PD-NC, 23 PD-MCI, ten PDD and 19 controls reached and grasped for a target whilst wearing movement sensing equipment in four conditions: full vision, a darkened room with an illuminated target, with eyes closed at a natural speed and as quickly as possible in full vision. All PD subjects were tested whilst on. Kinematic parameters of reach and grasp were extracted from the movement data and analysed using standard statistical methods.Our results show a spectrum of change to kinematic reach parameters when reaching and grasping with eyes closed: PD-NC are disproportionately affected compared to controls and PDD are disproportionately affected compared to PD-NC. Parameters of reach and grasp were similar between PD-NC and PD-MCI in all conditions. These results have been discussed in the context of abnormal integration of sensorimotor functions and impaired spatial working memory in PD. Reaction time when reaching and grasping as quickly as possible is significantly associated with global cognition in the PD subjects after controlling for age, motor signs and disease duration. This supports a role for reaction time as a potential biomarker for cognitive impairment in PD