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

Area of Science:

• Systems Biology
• Molecular Biology
• Computational Biology

Background:

• Cellular decisions like differentiation, proliferation, and death are governed by molecular signaling pathways regulating gene expression.
• Gene expression can, in turn, activate signaling pathways, creating complex feedback loops.

Purpose of the Study:

• To introduce and describe the Dynamic Nested Effects Model (D-NEM), a statistical method for analyzing the temporal interplay between cell signaling and gene expression.
• To dissect biological processes into distinct signaling and gene expression events and analyze cellular signal flow.

Main Methods:

• D-NEM utilizes Bayesian models to represent signal propagation within a biological network.
• The method decomposes time delays in multi-step signaling processes into individual steps, assuming exponential distribution for time delays.
• Rate constants for signal propagation are estimated using Gibbs sampling to assess their joint posterior distribution.

Main Results:

• D-NEM provides insights into the interplay of different biological signal propagation forms, correlating rates with mechanisms (cytoplasmic signaling: high; transcription/translation: intermediate; secondary effects: low).
• Application to mouse embryonic stem cell development identified a feed-forward loop-dominated network.
• This network structure was found to stabilize the differentiated state of cells.

Conclusions:

• The Dynamic Nested Effects Model (D-NEM) offers a powerful approach for dissecting complex cellular signaling and gene expression dynamics.
• The study identifies Nanog as a key factor sensitizing stem cells to differentiation stimuli within a stabilizing feed-forward network.