Development of Novel Labelling Strategies for Imaging in Nanoscale Topography

Abstract

Many biological phenomena happen on spatial scales below Abbe’s diffraction limit, a physical resolution limit (~250nm) imposed upon optical systems by the diffraction of visible light. Thus, in order to better understand these processes, it is necessary to resolve the machinery of biological systems on nanometer scales. 3D single molecule localisation microscopy (3D-SMLM) techniques such as the double helix point spread function (DHPSF) enable the visualisation of these systems on the required spatial scales and take into account the inherently 3D nature of biology. However, the addition of axial information demands more stringent labelling requirements in terms of localisation density and greater experimental complexity compared to an analogous 2D experiment. This thesis outlines the development of a new labelling strategy (resPAINT) that combines existing methodologies based on transient binding with active control of probe photophysics. The thesis then goes on to describe how this leads to a substantial improvement in localisation rate (50-fold) relative to traditional labelling methodologies, without compromising contrast. Through use of multiple modes of photophysical control, and expanding this technique to multiple different transient binders, this thesis details that the developed method is a general principle which could expand the use of transient-binder based super-resolution imaging. In the latter portion of this thesis the developed technique is applied to the study of adaptive immunity; in particular to the study of T cell triggering, which is currently poorly understood. It is known, however, that this is problem that demands single molecule sensitivity, as it is a single T cell receptor engaging an antigen that can start the biochemical signalling cascade. Further, since membrane topography is known to play a role in signalling outcomes, it follows that the distribution of proteins must be considered in relation to the various structures exhibited on the membrane surface. The combination of these aforementioned challenges makes 3D-SMLM uniquely placed to address some common questions within the field. In particular the quantification of protein distribution in resting T cells would provide valuable insight into the triggering mechanism and, in this thesis, a pipeline has been provided that could allow direct correlation to topographical features in 3D for the first time.