Dr. Tomas Gedeon (Dept. of Mathematical Sciences, MSU)

02/06/2025 3:10pm

Abstract:

Gene regulatory networks with more than few genes can support different phenotypes in different conditions. These conditions may be external inputs like intercellular signaling, resource abundance or internal variability like abundance of ribosomes, RNAP or even copy number of different enzymes. The different conditions can be modeled as changes in parameters of a gene network model.

The mathematical challenge is to develop methods to describe, search and analyze behavior of models across large sets of parameters. I will illustrate the use of the techniques that we developed, which is based on combining discrete Boolean approaches with differential equations models, on two problems:

The first problem studies a problem where naive CD4+ cells differentiate into Th1, Th2, Th17 and Treg subsets which mutually inhibit each other. In our model we compare prevalence, across all parameters, of fully differentiated cell type to a cell type which combines characteristic of two of the four types. We find that such two type hybrid occurs more frequently. This suggests that differentiation to four types likely happens in a two-step process, rather than in a single step. The model is general, and conclusions may apply to other differentiation processes.

The second problem concerns the ability of the same cell cycle network in yeast to support two phenotypes: (a) regular cell cycle, and (b) endocycling, where cell duplicates the genome but does not go through mitosis. Endocycling can be induced experimentally by knocking down mitotic cyclin and we use the data to show that, indeed, a single network in different parameter regimes, can support these different phenotypes.

If interest and time remains, I will explain a bit of mathematics that allows us to do this type of analysis.