Single Cell Measurements and Modeling and Computation of Decision Making Errors in a Molecular Signaling System with Two Output Molecules

Abstract

A cell constantly receives signals and takes different fates accordingly. Given the uncertainty rendered by signal transduction noise, the cell may incorrectly perceive the signals. It may mistakenly behave as if there is a signal - although there is none, or may miss the presence of a signal that actually exists. In this paper, we consider a signaling system that has two outputs, and introduce and develop methods to model and compute key cell decision making parameters based on the two outputs, and in response to the input signal. In the considered system, the tumor necrosis factor (TNF) regulates the two transcription factors, the nuclear factor {kappa}B (NF{kappa}B) and the activating transcription factor-2 (ATF-2). These two system outputs are involved in important physiological functions such as cell death and survival, viral replication, and pathological conditions such as autoimmune diseases and different types of cancer. Using the introduced methods, we compute and show what the decision thresholds are, based on the single cell measured concentration levels of NF{kappa}B and ATF-2. We also define and compute the decision error probabilities, i.e., false alarm and miss probabilities, based on the concentration levels of the two outputs. By considering the joint response of the two outputs of a signaling system, one can learn more about complex cellular decision making processes, the corresponding decision error rates, and their possible involvement in the development of some pathological conditions.