Date of Award
Doctor of Philosophy (PhD)
Biomedical Engineering (ENAS)
Changes in the shape of cellular membranes are linked with viral replication, Alzheimer's, heart disease and an abundance of other maladies. Some membranous organelles, such as the endoplasmic reticulum and the Golgi, are only 50 nm in diameter. As such, membrane shape changes are conventionally studied with electron microscopy (EM), which preserves cellular ultrastructure and achieves a resolution of 2 nm or better. However, immunolabeling in EM is challenging, and often destroys the cell, making it difficult to study interactions between membranes and other proteins. Additionally, cells must be fixed in EM imaging, making it impossible to study mechanisms of disease. To address these problems, this thesis advances nanoscale imaging and analysis of membrane shape changes and their associated proteins using super-resolution single-molecule localization microscopy. This thesis is divided into three parts. In the first, a novel correlative orientation-independent differential interference contrast (OI-DIC) and single-molecule localization microscopy (SMLM) instrument is designed to address challenges with live-cell imaging of membrane nanostructure. SMLM super-resolution fluorescence techniques image with ~ 20 nm resolution, and are compatible with live-cell imaging. However, due to SMLM's slow imaging speeds, most cell movement is under-sampled. OI-DIC images fast, is gentle enough to be used with living cells and can image cellular structure without labelling, but is diffraction-limited. Combining SMLM with OI-DIC allows for imaging of cellular context that can supplement sparse super-resolution data in real time. The second part of the thesis describes an open-source software package for visualizing and analyzing SMLM data. SMLM imaging yields localization point clouds, which requires non-standard visualization and analysis techniques. Existing techniques are described, and necessary new ones are implemented. These tools are designed to interpret data collected from the OI-DIC/SMLM microscope, as well as from other optical setups. Finally, a tool for extracting membrane structure from SMLM point clouds is described. SMLM data is often noisy, containing multiple localizations per fluorophore and many non-specific localizations. SMLM's resolution reveals labelling discontinuities, which exacerbate sparsity of localizations. It is non-trivial to reconstruct the continuous shape of a membrane from a discrete set of points, and even more difficult in the presence of the noise profile characteristic of most SMLM point clouds. To address this, a surface reconstruction algorithm for extracting continuous surfaces from SMLM data is implemented. This method employs biophysical curvature constraints to improve the accuracy of the surface.
Connerty-Marin, Zachary Ryan, "Quantifying Membrane Topology at the Nanoscale" (2022). Yale Graduate School of Arts and Sciences Dissertations. 576.