Visualizing unusual mammalian cell environments at the nanoscale with advanced fluorescence super-resolution microscopy methods
Abstract/Contents
- Abstract
- Fluorescence microscopy methods are powerful imaging tools that can provide insights into biological function. Increasingly, super-resolution (SR) fluorescence microscopy approaches have been used to visualize specific biological structures that are not observable with traditional diffraction-limited methods. One powerful and simple SR method is single-molecule active control microscopy (SMACM). SMACM can achieve ~10 nm precision and is defined by two key principles. First, the images of single molecules (the point spread function or "PSF') are super-localized with high precision. Second, some type of "active control mechanism" is used to stochastically keep the concentration of emitters low in any imaging frame to prevent PSF spatial overlap. Localizations from many acquired frames are then combined to reconstruct an image with nanoscale detail. In this dissertation, I will describe the development of several novel experimental and computational SMACM methods. These approaches are applied to study mammalian cell environments that were not observable using previous imaging technologies. In Chapter 1, I describe the fundamentals of fluorescence, SMACM, and 3D PSF imaging methods. Chapter 2 will then detail SMACM experimental and computational workflows that are the foundation for all experiments described in this dissertation. The first new SR imaging technology is described in Chapter 3 where I introduce a new general method to explore the nanoscale distribution of proteins at the cell-nanopillar interface using three-dimensional (3D) SMACM. A substrate provides 100 nm diameter nanofabricated pillars upon which cells can grow, imprinting well defined membrane curvatures and potentially influencing processes such as endocytosis. I combined SMACM, 3D double-helix point spread function engineering approaches, and silicone-oil aberration-mitigating objectives to image along the cell-nanopillar interface with 10-20 nm precision in 3D. The method was validated by imaging the 3D shape of surface-labeled nanopillars and comparing the results to electron microscopy measurements. With 3D nanoscale detail, I observed that the cytoplasmic proteins AP-2 and actin accumulate at high membrane curvature and interact with the pillar curvature constraints in different ways. In Chapter 4, I describe a robust, general, and easy-to-implement deep learning method (BGnet) to accurately and rapidly estimate arbitrarily structured background (sBG) in photon-limited images of single molecules. Any sBG can seriously degrade the localization process, but addressing this problem has been challenging. To this end, simulated data was used to train a convolutional neural network that predicts structured background from single PSF images, enabling the background removal. BGnet works both for conventional microscopes and also for complex 3D designs based on engineering the PSF. Compared to conventional background removal approaches, the method significantly improves precision, accuracy, and, ultimately, SR image quality. Finally, Chapter 5 describes a two-color SR imaging workflow to visualize viral RNA and protein components in coronavirus infected cells. While the scientific community has studied coronavirus biology using genomics, biochemistry, cryoelectron microscopy, and electron tomography, how coronavirus RNA is spatially organized in the cell at the different stages of the viral replication cycle at nanoscale resolution is largely unknown. Using the model human coronavirus HCoV-229E and specifically labeled viral targets, I visualized their spatial localization patterns within MRC5 lung fibroblast cells. The 10-nm resolution achieved by two-color imaging approach uncovered a striking spatial organization of genomic coronavirus RNA (gRNA) and double-stranded RNA (dsRNA) into three distinct structures. Several striking spatial relationships could be observed between the various viral targets. First, spike proteins and gRNA rarely assemble into a virion in the cellular cytoplasm. Second, in contrast to previous observations, gRNA and dsRNA spatially separate. These observations provide insights into coronavirus RNA replication, organization, and virion exportation.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Roy, Anish Raj |
|---|---|
| Degree supervisor | Moerner, W. E. (William Esco), 1953- |
| Thesis advisor | Moerner, W. E. (William Esco), 1953- |
| Thesis advisor | Cui, Bianxiao |
| Thesis advisor | Ting, Alice Y |
| Degree committee member | Cui, Bianxiao |
| Degree committee member | Ting, Alice Y |
| Associated with | Stanford University, Department of Chemistry |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Anish R. Roy. |
|---|---|
| Note | Submitted to the Department of Chemistry. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/cn540px0724 |
Access conditions
- Copyright
- © 2022 by Anish Raj Roy
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...