Stability on the edge : a combined experimental and theoretical investigation into the self-organization of actin at the leading edge of migrating cells
- Cellular life has evolved to reliably carry out a diverse array of complex biological functions, all of which fundamentally arise as emergent properties of an underlying system of macromolecules and their stochastic, nanometer-scale interactions. It remains an open question how molecular processes subject to such inherent stochasticity can drive robust cellular behaviors. Actin-based migration is one such behavior that plays an essential role in a variety of organisms spanning the eukaryotic tree of life. Performance of this function requires the continual polymerization of nanometer-sized actin monomers into vast micron-scale cytoskeletal structures that define the cell's shape and power motility. In the remarkable case of lamellipodial migration, cell types such as neutrophils and fish keratocytes can maintain a single, stable leading edge protrusion (referred to as the lamellipodium) of nearly-constant shape for time-scales of minutes to hours -- despite the aforementioned stochasticity intrinsic to actin polymerization. This thesis is dedicated to unraveling the biophysical mechanisms that bridge the scales between stochastic polymerization at the individual-filament level and long-timescale maintenance of a stable lamellipodium. To begin my investigation, I performed high-resolution imaging of migrating HL-60 cells at an exceptionally fast temporal resolution of 50ms. While the global, steady-state lamellipodial shape in these cells is fairly constant over long time-scales, high speed imaging revealed dynamic fine-scale (sub-second, sub-micron) fluctuations in the leading edge contour that continually erupt and then relax back to the steady state over time. In order to gain a quantitative handle on the observed behavior, I developed a novel image and data analysis pipeline to segment the leading edge shape, extract the fine-scale fluctuations, and quantify their dynamics using methods based on autocorrelation. These analyses showed that leading edge fluctuations stably return to the average cell shape in a manner consistent with simple viscous relaxation of an elastic material, thereby enabling maintenance of a steady-state lamellipodium. These experimental findings suggest that the suppression of stochastic fluctuations is somehow hard-wired into the molecular machinery driving lamellipodial protrusion. To determine the biophysical underpinnings of leading edge stability, I developed a bottom-up stochastic simulation of the cell leading edge that incorporates dendritically branched actin network growth against a simplified model membrane. This minimal model was remarkably able to reproduce quantitative features of the experimentally observed, stable leading edge fluctuation behavior -- without requiring invocation of additional feedback mechanisms -- implying that lamellipodial maintenance is an intrinsic, emergent property of branched actin growth against a membrane. Through a deeper investigation into this model, I identified a simple molecular mechanism underlying leading edge stability that is inherently dependent on the geometry of branched actin network growth, based on a synergy between membrane-proximal branching and filament spreading. Further, I found that the experimentally-observed branch geometry, the ~70-80˚ branching angle that has been conserved from protists to mammals, maximally suppresses leading edge shape and actin density fluctuations in the model. These results not only shed light on the decades-long mystery in actin-based motility of why this particular angle is so ubiquitous, but also reveal a novel biological noise-suppression mechanism based entirely on system geometry. The final portion of my thesis describes a separate line of work, focusing on my efforts to generate, validate, and quantitatively characterize a new cell line for use in future studies of actin-dependent cellular processes such as cell shape determination, motility, and phagocytosis. To this end, I employed modern CRISPR/Cas9 gene-editing technology to generate HL-60 cells expressing GFP--actin from the endogenous locus. Endogenous expression avoids some common pitfalls of traditional labeling methods, such as overexpression artifacts from ectopically-expressing constructs, or complications arising from the binding kinetics of actin-binding probes. I was able to generate both monoallelic and biallelic edited lines. The monoallelic edited line preferentially expresses the untagged allele, making these cells only dimly fluorescent. The biallelic edited cells, however, have no choice but to express their tagged allele, and therefore are amply bright for standard fluorescence imaging. I next performed a detailed functional characterization of the edited lines. This work showcases a myriad of quantitative techniques, including Bayesian inference-based analysis of motility, principal component analysis of cell shape, and differential gene expression analysis of RNA-sequencing data, which I integrated into a generalizable strategy to characterize key properties of any edited, motile cell line. Using this approach, I show that the edited cell lines have nearly-normal motility in 1D, 2D, and 3D migration assays and additionally have almost indistinguishable cell shape. Interestingly, the RNA-sequencing analysis revealed that the gene editing process itself induced a host of transcriptional changes, despite the minimal effect of the edit on cell shape and motility, revealing a potential topic for future studies. Overall, these cell lines and functional characterization strategy should prove to be useful tools for the broader cell biology community.
|Type of resource
|electronic resource; remote; computer; online resource
|1 online resource.
|Garner, Rikki Michelle
|Spakowitz, Andrew James
|Spakowitz, Andrew James
|Dunn, Alexander Robert
|Degree committee member
|Dunn, Alexander Robert
|Stanford University, Department of Biophysics
|Statement of responsibility
|Rikki Michelle Garner.
|Submitted to the Department of Biophysics.
|Thesis Ph.D. Stanford University 2021.
- © 2021 by Rikki Michelle Garner
Also listed in
Loading usage metrics...