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dc.contributor.advisorNair, Deepak
dc.contributor.authorKedia, Shekhar
dc.date.accessioned2020-11-12T11:17:11Z
dc.date.available2020-11-12T11:17:11Z
dc.date.submitted2020
dc.identifier.urihttps://etd.iisc.ac.in/handle/2005/4671
dc.description.abstractAmyloid Precursor Protein (APP) is a key player in Alzheimer’s disease (AD). Despite intuitive insights into differential proteolysis of APP, there is a little understanding of how the amyloidogenic machinery is distributed at the synapses. This is largely due to the lack of information on the localization and trafficking of amyloidogenic machinery within/outside functional zones of individual synapses. Here, we combined confocal microscopy, multiple paradigms of super-resolution imaging (dSTORM and STED), high-frequency single particle tracking (sptPALM) and novel analytical methods to decipher the number, nanoscale localization and segregation of APP molecules on the dendritic compartments and within the functional zones of an excitatory synapse. We show that APP is differentially distributed in these synaptic zones into functional domains. Furthermore, we show that APP molecules are exchanged in and out of these domains by lateral diffusion. We populated this actual distribution and kinetics of APP exchange in a specific CA1 dendritic shaft of a neuropil from stratum radiatum of the hippocampus. We used this recreation of canonical spines with distinct APP localization to carry out “insilico” experiments to study their dynamics. In the next part, we correlated the localization of β- and - secretases in the synaptic compartments and evaluated the association of these molecules on postsynaptic density (PSD) and endocytic zone (EZ). We further evaluated the association of APP with secretases as well as between secretases. This information on the molecular detail was used to reconstruct an average dendritic spine mimicking the realistic nanoscale distribution of the core components of the machinery involved in the amyloidogenic pathway. Distribution of APP and secretases at EZ was used to predict the average number of molecules in a unitary endocytic vesicle to validate the role of molecular determinants that would affect the rate of product formation inside an endocytic compartment of a defined volume. We then compared these molecular determinants between wild type APP (APP-WT) and a variant of APP implicated in the familial AD (APP-Swe). We show that depending upon the segregation of APP and secretases on EZ, individual synapses can have a dynamic range of APP processing. This dynamic range can vary between synapses, which indeed is directly dependent on each unitary endocytic process. We further confirm that alteration in these local signatures of the machinery is a key determinant in deciding the shift in equilibrium towards β-amyloidogenic pathway. This study identifies fundamental mechanisms where the local signature of the machinery becomes a key determinant in deciding the shift in equilibrium towards β-amyloidogenic pathway and thus, contributing towards long term deficits like those seen in AD.en_US
dc.language.isoen_USen_US
dc.rightsI grant Indian Institute of Science the right to archive and to make available my thesis or dissertation in whole or in part in all forms of media, now hereafter known. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertationen_US
dc.subjectExcitatory synapseen_US
dc.subjectSuper-resolution microscopyen_US
dc.subjectNanoscale organizationen_US
dc.subjectAlzheimer's Diseaseen_US
dc.subjectNanodomainen_US
dc.subjectAmyloid Precursor Proteinen_US
dc.subjectSecretasesen_US
dc.subjectreaction-diffusion modelen_US
dc.subject.classificationNeuroscienceen_US
dc.titleSuper-Resolution Imaging Reveals Localization and Regulation of Nanoscale Machinery Involved in the Amyloidogenic Pathwayen_US
dc.typeThesisen_US
dc.degree.namePhDen_US
dc.degree.levelDoctoralen_US
dc.degree.grantorIndian Institute of Scienceen_US
dc.degree.disciplineFaculty of Scienceen_US


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