Current single molecule localisation microscopy methods allow for multicolour imaging of macromolecules in cells, and for a degree quantification on molecule numbers in one colour. However, that has not yet been an attempt to develop tools capable of quantitative imaging with multiple colours in cells. This work addressed this challenge by designing linker peptides with chemospecific groups to allow attachment of activator and emitter dyes for STORM imaging, and a targeting module. The design ensured a stoichiometric ratio of targeting module to activator and emitter dyes. Peptides with HaloTag ligands attached were labelled with various activator and emitter pairs and used to label HaloTag fusions of S. pombe and mouse embryonic stem cells. These peptides were found to bind non-specifically to various areas of both cell types, and did not localise to HaloTag protein, whereas controls did. Another peptide was also labelled with activator-emitter pairs and attached to expressed anti-GFP and ant-mCherry nanobodies via native chemical ligation. The labelled anti-GFP nanobody was to demonstrate ensemble and single molecule imaging in S. pombe, as well as characterisation on single molecule surfaces in comparison to a conventional randomly labelled antibody. The stoichiometrically labelled nanobody had a more consistent number of photons detected per localisation, number of localisation per molecule and number of blinks per molecule, which implied that it could be more useful than randomly labelled nanobodies for counting experiments. It was also shown to be capable of specific laser activation for STORM imaging with both an Alexa405Cy5 and Cy3Cy5 pairs. These anti-GFP and anti-mCherry nanobodies and peptide linker are new tools for both counting and multicolour imaging in super-resolution, which could be widely applied to constructs that are already tagged with GFP or mCherry.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:763666 |
Date | January 2018 |
Creators | Taylor, Edward John Robert |
Contributors | Laue, Ernest |
Publisher | University of Cambridge |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://www.repository.cam.ac.uk/handle/1810/284553 |
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