18 Aug 2005
Dept of Cellular and Molecular Physiology
Sackler School of Biomedical Sciences
Many cell signaling pathways can encode more than one outcome in a context-dependent manner, reducing the number of unique signaling pathways required for development. Without knowing how signals are processed, however, assigning a biological function to an individual pathway becomes difficult. For example, the MAP (mitogen-activated protein) kinase pathway is one of the most well-studied signal transduction systems to date. Its molecular, cellular and genetic properties are well-known; however, we still do not know how it processes information. It can promote cell growth, proliferation, death or differentiation in a context-dependent manner. In fact, changing the duration of MAP kinase signaling alone can shift cell fate.
In the first half, I will present a molecular network capable of switching gene expression profiles by varying the MAP kinase signaling duration. Progression through the cell cycle serves as an internal clock, sensing the duration of signaling. Cell cycle-regulated transcriptional repressors (i.e. Rb, histone deacetylases) inhibit MAP kinase-dependent differentiation genes at specific points along the cell cycle, altering its gene expression profile. MAP kinase signaling and the cell cycle comprise a state-dependent decoder of cellular signals. This mechanism links cell division with cell fate, possibly explaining how cell differentiation follows rapid proliferation and why pluripotency can be lost with repeated cell divisions.
In the second half, I will discuss the relationship between biological information and complexity. The main aim is to emphasize the importance of state-dependent signal processing, in addition to the classic notion of signal transmission. State-dependent decoding of developmental signaling can evolve naturally from a scale-free network. It functions to compress information, reducing the cost associated with laying down multiple signaling networks. By incorporating cell division, it can process cell fate signaling while creating complex multi-cellular patterns. The concept of biological complexity based on state-dependent signaling has important implications for theoretical and experimental models.