CDEV-MS16

Mechanisms Underlying Cell Polarization and Its Role in Cell Development

Wednesday, June 16 at 07:45pm (PDT)
Thursday, June 17 at 03:45am (BST)
Thursday, June 17 11:45am (KST)

SMB2021 Follow Wednesday (Thursday) during the "MS16" time block.

Weitao Chen (University of California, Riverside, United States), Michael Trogdon (Salk Institute for Biological Studies, United States), Roya Zandi (University of California, Riverside, United States)

Description:

Cell polarization is an important process in which some signaling molecule or cell component, originally distributed symmetrically, becomes locally concentrated as a result of symmetry breaking. Cell polarization is widely observed during cell division in many different cell types, such as yeast cells, neurons, epithelial cells etc.. Such a process is required for cell differentiation and morphological change to give rise to specialized functions. Although lots of studies have been conducted to understand the mechanism underlying cell polarization, it still remains unclear for many biological systems, such as the initiation signal of cell polarity, the role of mechanical components in symmetry breaking, decision on the cell polarization sites etc.. Different modeling approaches have been developed to understand different biological systems, especially those requiring challenging experiments and involving complex structural changes. The goal of this minisymposium is to provide an opportunity for researchers in this field to exchange ideas about mathematical models and approaches to incorporate biological data.

Cole Zmurchok

(Vanderbilt University, United States)

"Mechanosensing can enhance adaptation to maintain polarity of migrating cells"

Migratory cells are known to adapt to environments that contain wide-ranging levels of chemoattractant. While biochemical models of adaptation have been previously proposed, here we discuss a different mechanism based on mechanosensing, where the interaction between biochemical signaling and cell tension facilitates adaptation. In this talk, we develop and analyze a model of mechanochemical-based adaptation consisting of a mechanics-based physical model coupled with the wave-pinning reaction-diffusion model for Rac GTPase activity. We use Local Perturbation Analysis to predict how cells adapt signaling parameters via feedback from mechanics to maintain polarity in response to chemoattractant levels. To confirm this prediction, we simulate the mechanochemical model in moving cells, demonstrating how mechanosensing results in persistent cell polarity when cells are stimulated with wide-ranging levels of chemoattractant in silico. These results demonstrate how mechanosensing may help cells adapt to maintain polarity in variable environments.

Nan Hao

(University of California, San Diego, United States)

"Modeling the landscape of divergent aging in yeast"

Cellular aging is a complex process that involves many interwoven molecular processes. Studies in model organisms have identified many individual genes and factors that have profound effects on lifespan. However, how these genes and factors interact and function collectively to drive the aging process remains unclear. We investigated single-cell aging dynamics throughout the replicative lifespans of S. cerevisiae, and found that isogenic cells diverge towards two aging paths, with distinct phenotypic changes and death forms. We further identified specific molecular pathways driving each aging fate and revealed that these pathways interact and operate dynamically to enable an early-life switch that governs the aging fate decision and the progression towards death. Based on the identified molecular circuit, we developed a computational model that can simulate the landscape of divergent aging trajectories under various conditions. Guided by the model, we genetically engineered a new mode of aging with a dramatically extended lifespan. Our work uncovers the interconnected molecular pathways that drives the aging process and opens up the possibility of designing interventions that simultaneously target multiple network nodes, instead of single genes, to more effectively extend the healthspan.

Kevin Tsai

(University of California, Riverside, United States)

"Yeast budding: linking shape generation with biochemical-mechanical feedback"

How cells regulate behaviors such as expansion, division, and dynamical shape change is a fundamental question in biological science. The budding of Saccharomyces cerevisiae (yeast) is a prime example of asymmetrical cell growth where reproduction takes the form of a local surface protrusion. During this reproduction event, biochemically the budding process requires the recruitment of cell surface materials and the polarization of growth-associated proteins such as Cdc42. On the other hand, the mechanical properties of the cell wall potentially play a crucial role in bud formation. In this work we developed a novel 3D coarse-grained cell model incorporating probabilistic remeshing and cell growth via surface expansion. We computationally investigated different cell surface weakening and growth patterns and observed both proper and improper bud generation arising from different prescribed conditions. Furthermore, we coupled our mechanical model with a biochemical signaling model to probe the influence of the interplay between the mechanical properties and the biochemical properties on bud development.

Wing Cheong Lo

(City University of Hong Kong, P. R. China)

"Deterministic and stochastic analysis for the spontaneous emergence of cell polarity in budding yeast"

Spontaneous emergence of cell polarity intrinsically lies at the localization of signaling molecules on a particular region of cell membrane. Such a process necessarily contains a positive feedback loop to amplify the localized cluster. To describe the polarizing process and explore different feedback functions involved, deterministic and stochastic models with various regulations will be discussed in this talk.

Hosted by SMB2021 Follow

Virtual conference of the Society for Mathematical Biology, 2021.