CDEV Subgroup Contributed Talks

Mikahl Banwarth-Kuhn

University of California Merced

"Multiscale Modeling of Neurodegenerative Diseases"

Prion proteins are associated with fatal neurodegenerative diseases in mammals, but they are also responsible for a number of harmless heritable phenotypes in yeast. Under certain experimental conditions, changes in protein aggregation dynamics between neighboring cells result in sectored colonies corresponding to loss of the prion phenotype. The resulting phenotypic organization provides a rich data set that can be used to uncover the non-intuitive relationships between protein aggregation mechanisms across multiple scales. In this talk, we introduce a novel, two-dimensional agent-based model of a budding yeast colony with detailed representation of cell-type specific biological processes, including budding, variation in cell-cycle length, and asymmetric protein segregation. The model is used to study the impact of budding cell division, nutrient limitation and yeast colony organization on yeast colony phenotypes. In the model, prion dynamics are simulated within each individual cell using simplified intracellular dynamics, and spatial arrangement of cells is modeled using a center-based modeling approach. The multiscale model may have the potential to predict mechanisms underlying experimentally observed phenomena such as sectored prion phenotypes in yeast colonies and serve as a tool for future hypothesis generation and testing.

Benjamin Brindle

Lehigh University

"Bifurcation Analysis in a Mathematical Model for Red Blood Cell Dynamics"

Red blood cells are one of the most important components of life in humans. Loss of red blood cells has consequences, such as anemia or even death. Such a loss could be the result of parasitemia, viral infection, or phlebotomy. Red blood cell dynamics within a human involve several stages of precursor cells before a red blood cell fully matures to an erythrocyte. After blood loss, a feedback mechanism contingent on loss and level of erythrocytes causes the production of more precursor cells to return the blood dynamics to equilibrium. We seek to understand these dynamics from a biological perspective by using mathematics to model specific loss scenarios. We model this process using a system of nonlinear, deterministic, ordinary differential equations. Functions describing this feedback, the stem cell recruitment, and the erythrocyte loss are chosen to examine the system dynamics. Some parameter choices cause a Hopf bifurcation, while others lead to death, stable steady states, or limit cycles. Numerical methods are used to display bifurcation diagrams and transient dynamics. By understanding red blood cell dynamics through the utilization of mathematical modeling and dynamical systems tools, diseases can be mitigated as we understand the scenarios in which they occur.

Marcos Gouveia

CFisUC-Center of Physics of the University of Coimbra, University of Coimbra

" * Tip cell migration in sprouting angiogenesis: The role of extracellular matrix mechanics'"

Sprouting angiogenesis is the process by which new blood vessels grow from preexisting ones. It is a fundamental process during embryo development, as well as in many physiological (vascular remodeling, wound healing) and pathological phenomena (solid tumor growth, diabetic retinopathy). Angiogenesis is heavily dependent on a number of factors such as: the concentration of oxygen in the surrounding tissues, chemical signaling and endothelial cell coordination and proliferation. Cell migration is key for sprouting angiogenesis to occur since the new sprouts need to reach the cells in hypoxia. Thus, studying the forces exerted by cells on the extracellular matrix (ECM) and how the matrix's mechanical properties affect cell migration can help us understand the role angiogenesis plays in different processes.We have developed a mathematical model using the phase field method taking into account the elastic interactions between endothelial tissue and ECM, as well as the adhesion and traction forces exerted by cells. At the same time, we have used in vitro, aortic ring assays using mouse aorta slicesto quantify the cell's migration potential in gels with different rigidities.Both studies show that there is a value of ECM rigidity that results in an optimal migration distance.

David Hardman

Usher Institute, University of Edinburgh

"A combined in vitro/agent-based modelling approach for optimising muscle cell culture medium"

We present a combined in silico / in vitro approach to optimising experimental muscle cell culturing protocols using an agent-based model (ABM). Functions of experimentally derived and inferred cell behaviours are applied as inputs and levels of myocyte-myotube fusion, an indicator of experimental success, as an output. We conducted sets of in vitro experiments to obtain fixed and time-lapse images of myocyte differentiation and myotube maturation under a range of media serum concentrations and concentrations of N2B27 neuron differentiation medium. Metrics of myoblast motion and proliferation were quantified from time-lapse imaging and used to inform a cell residence-time dependent ABM of myoblast-myotube fusion. An Approximate Bayesian Computation method was applied to infer the myocyte residence-time threshold by comparing ABM simulations with cell fusion data extrapolated from stained images.Once validated, the ABM was used to run in silico experiments over a range of media conditions to predict the conditions most likely to produce quality muscle tissue. A sweep of the behavioural parameters defining the ABM was conducted to assess the relative effect size of individual cell behaviours on cell fusion.We also discuss extending the protocol to analyse the spatial distribution of nuclei as a quality indicator.