Modeling cell decisions: two case studies

8 June 2012

James Faeder
Department of Computational Biology
University of Pittsburgh School of Medicine


In this talk I will discuss ongoing collaborative efforts to develop quantitative models of two cell signaling processes that have both basic and applied significance: bacterial spore germination and T cell differentiation.

Despite consuming undetectable amounts of energy, bacterial spores have the ability to sense small quantities of the nutrients in their environment and to re-enter a growing state within minutes. At the same time, a population of spores exhibits a high degree of heterogeneity in the response time. Here, I will present a quantitative model of bacterial spore germination that reproduces experimental data for heterogeneity in germination times with a single nutrient and that we have used to infer the mechanism for signal combination under conditions where two nutrients are present.

Peripheral naïve T-cells can differentiate into several types of effector cells and the relative numbers produced of each cell type are critical for many immune-related pathologies. To study this system, we have constructed a logic circuit model in which each molecule type is treated as a discrete variable and variable values are updated according to logic rules. The model reproduces several important experimental observations and its construction helps to clarify the logical relationships among molecular inputs at several key control points in the process. We also find that the interplay of stimulation strength and duration plays a critical role in cell fate decision. In particular, there appears to be a critical period of signaling during which removal of antigen stimulation can produce a wide range of phenotypes. Branching between these dominant phenotypes, T helper and T reg, is affected by the timing of activation or inhibition of several key biochemical pathways controlling the differentiation process.

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