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Thesis

Imaging molecular processes of neural plasticity

Abstract:

Memories are believed to be encoded by changes in the efficacy of synaptic connections between neurons in the brain. Neurons are highly specialised cells which receive input and send outputs through morphologically and functionally distinct cellular compartments known as axons and dendrites. This polarised morphology requires that neurons asymmetrically distribute cellular components between compartments. To achieve this, neurons regulate the asymmetric distribution of specific mRNA transcripts as a means of spatially and temporally regulating gene expression within functional compartments. In recent years, the development of single-molecule mRNA imaging techniques has revolutionised the study of mRNA biology. Such techniques include single molecule fluorescent in situ hybridisation (smFISH) and MS2 labelling. smFISH involves labelling an mRNA of interest with a set of fluorescently-labelled oligonucleotide probes. While the MS2 system involves the binding of fluorescent coat proteins to RNA hairpin structures engineered into an mRNA of interest, enabling mRNA to be visualised live. In this thesis, both techniques were applied to visualise mRNA in the brain of the fruit fly Drosophila melanogaster. mRNA localised within axonal and dendritic compartments of memory-relevant neurons in the whole Drosophila brain were visualised at single-neuron resolution. Specific mRNAs were found to localise within neuronal compartments in a manner that recapitulated the localisation of the encoded protein product. Moreover, dynamic behaviours were visualised in real-time. These developments enable the molecular correlates of plasticity to be visualised within the well described memory circuitry of the Drosophila mushroom body.

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Institution:
University of Oxford
Division:
MSD
Department:
Physiology Anatomy & Genetics
Role:
Author

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Role:
Supervisor


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
UUID:
uuid:42b1a2ca-afde-4f0e-bc49-0f2df4e694b3
Deposit date:
2019-06-13
ARK identifier:

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