Modeling the temporal interplay of molecular signaling and gene expression by using dynamic nested effects models

Abstract

Cellular decision making in differentiation, proliferation or cell death is mediated by molecular signalling processes, which control the regulation and expression of genes. Vice versa, the expression of genes can trigger the activity of signalling pathways. We introduce and describe a statistical method called Dynamic Nested Effects Model (D-NEM) for analyzing the temporal interplay of cell signalling and gene expression. D-NEMs are Bayesian models of signal propagation in a network. They decompose observed time delays of multiple step signalling processes into single steps. Time delays are assumed to be exponentially distributed. Rate constants of signal propagation are model parameters, whose joint posterior distribution is assessed via Gibbs sampling. They hold information on the interplay of different forms of biological signal propagation. Molecular signalling in the cytoplasm acts at high rates, direct signal propagation via transcription and translation at intermediate rates, while secondary effects operate at low rates. D-NEMs allow the dissection of biological processes into signalling and expression events, and analysis of cellular signal flow. An application of D-NEMs to embryonic stem cell development in mice reveals a feed-forward loop dominated network, which stabilizes the differentiated state of cells and points to Nanog as the key sensitizer of stem cells for differentiation stimuli.