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    Proteomic Profiling of Animal Models of Motor Neuron Disease and Muscular Dystrophy


    Holland, Ashling (2015) Proteomic Profiling of Animal Models of Motor Neuron Disease and Muscular Dystrophy. PhD thesis, National University of Ireland Maynooth.

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    Abstract

    Proteomic profiling plays a decisive role in the identification of novel biomarkers of neuromuscular disorders and the elucidation of new pathobiochemical mechanisms that underlie these diseases. Detailed mass spectrometryQbased analysis of various diseased muscle groups from animal models of motor neuron disease and XQlinked muscular dystrophy is presented, in addition to motor neuron disease associated globozoospermia. This research has shown that both gel electrophoresis based and/or liquid chromatography for largeQscale protein separation, and labelQfree mass spectrometry basedQproteomics are highly suitable to determine changes in the isoform expression pattern of muscle and testis proteins. The work presented outlines major categories of protein families that have been identified by proteomicsQbased screening approaches in conjunction with biochemical verification analyses. This research has successfully established comprehensive biomarker signatures that have the potential to be used for the evaluation of new treatments and therapeutics, improve the understanding of pathobiochemical processes of the different diseases under investigation and diagnostics and prognostics of motor neuron disease, impaired spermiogenesis and XQlinked muscular dystrophy.
    Item Type: Thesis (PhD)
    Keywords: Proteomic Profiling; Animal Models; Motor Neuron Disease; Muscular Dystrophy;
    Academic Unit: Faculty of Science and Engineering > Biology
    Item ID: 6767
    Depositing User: IR eTheses
    Date Deposited: 12 Jan 2016 09:49
    URI: https://mural.maynoothuniversity.ie/id/eprint/6767
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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