{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/347872"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/347872","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Three-Dimensional Single-Molecule Localisation Microscopy and Visualisation Techniques","abstract":"Quantitative imaging in complex biological samples requires techniques such as, super-resolution (SR) imaging to better understand the morphology and stoichiometry of proteins below the diffraction limit. 3 Dimensional (3D) SR tools such as the 3D double helix-point spread function (DH-PSF) and 3D single-molecule light field microscopy (SMLFM) are techniques which have an increased depth of field (4 µm and 8 µm respectively) and are capable of isotropic resolutions of 25 nm (DHPSF). This makes 3D SR highly compatible to investigate biological processes such as sub-synaptic diversity in a physiologically relevant environment. This thesis demonstrates the development of visualisation software for 3D SR and the development of 3D SR techniques to push the boundaries of thick biological sample imaging. Through developing virtual reality (VR) visualisation software for single-molecule localisation microscopy (SMLM), we were able to explore, segment, analyse and export data through an intuitive medium. This thesis presents the first DH-PSF brain tissue imaging to understand the organisation of a scaffolding protein known as postsynaptic density 95 (PSD95). PSD95 is known to form nanoclusters which make up the basic structural unit of an excitatory synapse, however, through the sensitivity of 3D DH-PSF imaging, we were able to observe the presence of diffuse PSD95 protein. We have developed a series of quantitative imaging analysis algorithms to compare the role of inter and intra synaptic diversity in the hippocampus. This will further contribute to understanding how the organisation of PSD95 can lead to schizophrenia, learning disabilities, and autism. Finally, 3D SMLFM is able to improve acquisition time, labelling density, optical sectioning and signal-to-noise ratio in comparison to 3D DH-PSF for biological imaging. In summary, this thesis shows the development of visualisation software (vLUME), improved depth of field imaging (SMLFM) and utilised DH-PSF imaging to understand the role of PSD95 nanocluster and diffuse protein organisation in the brain.","abstract_html":"Quantitative imaging in complex biological samples requires techniques such as, super-resolution (SR) imaging to better understand the morphology and stoichiometry of proteins below the diffraction limit. 3 Dimensional (3D) SR tools such as the 3D double helix-point spread function (DH-PSF) and 3D single-molecule light field microscopy (SMLFM) are techniques which have an increased depth of field (4 µm and 8 µm respectively) and are capable of isotropic resolutions of 25 nm (DHPSF). This makes 3D SR highly compatible to investigate biological processes such as sub-synaptic diversity in a physiologically relevant environment. This thesis demonstrates the development of visualisation software for 3D SR and the development of 3D SR techniques to push the boundaries of thick biological sample imaging. Through developing virtual reality (VR) visualisation software for single-molecule localisation microscopy (SMLM), we were able to explore, segment, analyse and export data through an intuitive medium. This thesis presents the first DH-PSF brain tissue imaging to understand the organisation of a scaffolding protein known as postsynaptic density 95 (PSD95). PSD95 is known to form nanoclusters which make up the basic structural unit of an excitatory synapse, however, through the sensitivity of 3D DH-PSF imaging, we were able to observe the presence of diffuse PSD95 protein. We have developed a series of quantitative imaging analysis algorithms to compare the role of inter and intra synaptic diversity in the hippocampus. This will further contribute to understanding how the organisation of PSD95 can lead to schizophrenia, learning disabilities, and autism. Finally, 3D SMLFM is able to improve acquisition time, labelling density, optical sectioning and signal-to-noise ratio in comparison to 3D DH-PSF for biological imaging. 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