Model-Driven Experimental Design of TOR Signaling

The complexity of biological systems and the flood of information from modern measurement technologies put today’s life scientists into situations where logical and intuitive reasoning is no longer sufficient. Mathematical models are the obvious solution, but their application is severely limited.

Increasingly, we struggle in generating hypotheses, designing conclusive experiments, and achieving a more comprehensive understanding of how a biological system works – from simple bacteria to humans. Mathematical models are severely limited by our uncertainty as to which components interact and the quantitative nature of these interactions. Computational methods that aid human intuition in the face of this inevitable uncertainty have not been available. The progenitor project YeastX developed prototypes of these missing computational methods.

Efficiently designing optimal experiments

In contrast to the canonical first-measure-then-model approach, where feedback from the computational analyses into experiments is often scarce and the information content of the expensive experiments is far from optimal, these YeastX-developed methods enable the present SignalX project to efficiently design optimal experiments. We will apply this approach to the eukaryotic Target Of Rapamycin (TOR) signaling network that integrates multiple input signals to regulate key cellular functions such as ribosome biogenesis, proliferation and metabolism.

Understanding a dynamic system

To understand TOR signaling as a dynamic system, SignalX will address 3 general problems of signaling research:

• what precisely do the cells sense,
• how is the signal processed and relayed
• how are the multiple feedback mechanisms from the controlled processes integrated to achieve homeostasis?

Beyond addressing these problems individually, SignalX will integrate signal sensing, processing, and feedback and set us on a path towards a comprehensive mechanistic model of the dynamic and interpenetrative regulation of TOR signaling and metabolism.

Updated June 2014