Fourier analysis and systems identification of the p53 feedback loop

Area of Science:

• Cellular dynamics and signaling pathways
• Systems biology and quantitative modeling
• Molecular mechanisms of DNA damage response

Background:

• The p53-mdm2 feedback loop is crucial for cellular response to DNA damage.
• This circuit exhibits noisy oscillations in individual human cells post-DNA breaks.
• Understanding in vivo interactions within this circuit is essential for cell cycle control and cancer research.

Purpose of the Study:

• To quantify in vivo interactions within the p53-mdm2 feedback loop using systems identification.
• To analyze the role of biological noise in sustaining cellular oscillations.
• To develop a quantitative model for predicting circuit dynamics and estimating kinetic parameters.

Main Methods:

• Application of systems identification techniques to analyze cellular power spectra.
• Measurement of p53 and Mdm2 protein oscillation time courses in hundreds of human cells.
• Fourier spectral analysis to characterize system dynamics and model fitting using a third-order linear model with white noise.

Main Results:

• Characteristic power spectra with distinct low-frequency components were identified.
• A third-order linear model with white noise accurately described the observed p53-mdm2 dynamics, both with and without DNA damage.
• The model successfully identified the sign and strength of known interactions, suggesting noise can trigger and maintain oscillations.

Conclusions:

• Systems identification provides a powerful engineering approach to quantify in vivo cellular circuit design.
• Natural biological noise acts as a diagnostic tool, stimulating systems across multiple frequencies.
• This methodology is applicable to diverse biological systems for understanding their dynamic behavior and regulatory mechanisms.