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Title: Developing highly multiplexed technology for high-throughput super-resolution fluorescence microscopy
Author: Bento Carvalho Almada, Pedro Manuel
ISNI:       0000 0004 7229 3666
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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High-Throughput imaging can reconstruct complex signalling networks, reveal unknown interactions and capture rare cellular events. Simultaneously, the development of Single Molecule Localization Super Resolution Microscopy has enabled molecular-level structural information to be obtained in a single cell. But the increase in resolution comes at a trade-off for the amount of molecular species that can be imaged and the time it takes to acquire data, all of which limit the applicability of super-resolution to high-throughput work-flows. The present work details a framework to address this. It combines three independent approaches: a microscope hardware design approach to increase the amount of data that can be obtained in a Super-Resolution experiment; an optofluidics platform that can be wholly synchronized with most microscopes; and a sequential labelling framework to increase the number of species that can be imaged in Super-Resolution in a single cell. The hardware design is validated by performing Single Molecule Localization of cytoskeleton components and its throughput is shown to be up to an order of magnitude larger than a corresponding commercial system. We demonstrate a complete optofluidics platform to integrate microfluidics with a microscope, enabling live imaging, drug application, fixation, and staining in single cells synchronized with imaging protocols. Finally, we show an efficient sequential labelling protocol that is compatible with the optofluidics platform, enabling several molecular species to be imaged in the same cells. Overall, our approach increases the speed and amount of data that can be acquired in a single of Super-Resolution experiment, as well as, by performing on-line fixation, considerably improves our capacity for High-Throughput experiments in Super-Resolution imaging.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available