The different cell types in a living organism acquire their identity through
the process of cell differentiation in which the multipotent progenitor cells
differentiate into distinct cell types. Experimental evidence and analysis of
large-scale microarray data establish the key role played by a two-gene motif
in cell differentiation in a number of cell systems. The two genes express
transcription factors which repress each other's expression and autoactivate
their own production. A number of theoretical models have recently been
proposed based on the two-gene motif to provide a physical understanding of how
cell differentiation occurs. In this paper, we study a simple model of cell
differentiation which assumes no cooperativity in the regulation of gene
expression by the transcription factors. The latter repress each other's
activity directly through DNA binding and indirectly through the formation of
heterodimers. We specifically investigate how deterministic processes combined
with stochasticity contribute in bringing about cell differentiation. The
deterministic dynamics of our model give rise to a supercritical pitchfork
bifurcation from an undifferentiated stable steady state to two differentiated
stable steady states. The stochastic dynamics of our model are studied using
the approaches based on the Langevin equations and the linear noise
approximation. The simulation results provide a new physical understanding of
recent experimental observations. We further propose experimental measurements
of quantities like the variance and the lag-1 autocorrelation function in
protein fluctuations as the early signatures of an approaching bifurcation
point in the cell differentiation process.Comment: Cell Differentiation, Pichfork Bifurcation, Multilineage priming,
Slow reaction kinetics, Early signature