Elucidating mechanisms of CAR T-cell activation using high resolution optical microscopy

Chimeric Antigen Receptor (CAR) T-cells are a cancer immunotherapy treatment in which patient T-cells are collected, reprogrammed to express a synthetic CAR, and reinfused back into the patient. These CARs can bind to a protein of interest on a cancer cell surface, an interaction that triggers the T-cell to kill the cancer cell. Understanding how these CAR T-cells organize themselves can provide new insights into the logic behind why certain CAR designs yield better therapeutic results than others. Advances in biological sample preparation for high resolution optical microscopy and bioimage analysis have expanded opportunities to uncover subcellular arrangements to connect spatial information to function. Here, I present my work developing experimental and analysis tools to elucidate biological properties and mechanisms of Chimeric Antigen Receptor (CAR) T-cells in 4 studies: (1) assessing CAR mobility within single CAR T-cells, (2) examining the role of ezrin-radixin-moesin (ERM) proteins in CAR T-cells, (3) elucidating spatial mechanisms of antigen-independent CAR T-cell activation, and (4) using computational methods to enhance Airyscan confocal microscopy resolution. In the first study, I developed an experimental setup to estimate the mobility of CAR molecules along T-cell membranes. CARs contain extracellular, transmembrane, and intracellular portions that all contribute to triggering an activation response upon interaction with a target cancer cell. Ideally, CARs are highly expressed and trafficked to the cell membrane to maximize sensitivity cancer cells to the extracellular environment. However, little is known about the dynamic movement of these CARs once they get to the cell membrane. In this study, I used confocal microscopy to observe CAR organization in resting cells. I then use fluorescence recovery after photobleaching (FRAP) to measure how quickly CAR molecules move along the cell periphery to replenish a photobleached portion of the membrane. I found that CARs exhibited high mobility along the cell membrane. In the second study, I investigated factors influencing CAR organization at the membrane, and how proteins associated with cell protrusions may influence this organization. T-cells naturally contain a highly protrusive, tiny finger-like microvilli along their surface. These microvilli have been theorized to play a role in cell sensing, as they contain membrane proteins that can bind to opposing cells as the microvilli scan the extracellular environment. How CAR T-cell microvilli are organized and how this organization can influence cell sensing is less explored. I developed an experimental approach to characterize CAR T-cell protrusion organization using high resolution Airyscan confocal microscopy. I found that protrusions were enriched with ERM proteins, a family of proteins that link plasma membrane proteins to filamentous (F)-actin. Disturbing one of the ERM proteins, ezrin, abrogated CAR T-cell protrusions. I then used this insight to design CAR constructs that can directly interact with ERM proteins in order to potentially localize to tips of microvilli. In the third, I characterized the 3D localization of 3 different CARs in resting cells. Certain CAR designs have been more successful than others in yielding functional cell therapies. One reason identified to explain this difference is the propensity of the CAR to self-aggregate or cluster within a resting cell. CAR clustering in the presence of target cancer antigen has been linked to cell activation. However, clustering in the absence of antigen has been correlated to undesirable antigen-independent activation, in which cells activate without cancer antigen present. In this study, I used high resolution Airyscan microscopy to understand the relationship between CAR clustering and activation. I found that CAR clustering alone does not correlate directly to activation. Instead, large patch assemblies of CAR clusters form to propagate an activation signal independently of cancer antigen. Lastly, I evaluate the abilities of two emerging computational methods to enhance Airyscan confocal lateral resolution of biological sample images. Airyscan confocal microscopy already provides a relatively accessible super resolution methodology to cell biologists, achieving an impressive 120 nm lateral resolution. However, efforts to understand the role of molecular clustering in cells generally require resolutions below 100 nm to be able to distinguish the nanoscale profile. Two methods involving additional computational post-processing after acquiring Airyscan images have been advertised to increase resolution to 90 nm and below: joint deconvolution (jDCV) and super resolution radial fluctuations (SRRF) processing (combined with Airyscan to be fluctuation-enhanced Airyscan technology (FEAST)). Here, I tested these processing methodologies to explore their limitations in resolving structures in biological samples. I find that jDCV mildly increases resolution and signal to noise ratios in biological Airyscan images, while SRRF processing sharpens signal but may not accurately resolve structures. Taken together, these studies illustrate how powerful optical microscopy experimentation and analytical tools can be in piecing together cellular structures and processes.

Keywords: Engineering.
Chemical Engineering.
Advisor: Dunn Alexander
Gao Xiaojing
Majzner Robbie