Quantification of noise in bifunctionality-induced post-translational modification.

Area of Science:

• Systems biology
• Biophysics
• Molecular biology

Background:

• Bacterial two-component systems (TCS) are crucial for signal transduction.
• Understanding signal noise and its impact on cellular processes is vital.
• Bifunctionality in sensor kinases introduces complexity in signal processing.

Purpose of the Study:

• To develop a generic analytical scheme for quantifying signal transduction fluctuations in bacterial TCS.
• To analyze the impact of post-translational modifications and enzyme kinetics on signal noise.
• To investigate how noise affects gene regulation in response to dynamic promoter activity.

Main Methods:

• Development of a mathematical model incorporating elementary phosphotransfer kinetics.
• Application of Langevin equations to describe sources of fluctuation.
• Solution of equations using linear noise approximation (LNA).
• Analysis of noise profiles in single and branched TCS pathways.

Main Results:

• Derived analytical expressions for phosphorylated response regulators.
• Quantified noise profiles in various biologically relevant pathways.
• Demonstrated noise enhancement via phosphate outflux and reduction via influx in branched systems.
• Analyzed the role of output fluctuations in promoter regulation with random dynamics.

Conclusions:

• The proposed analytical scheme effectively quantifies signal noise in bacterial TCS.
• Phosphorylation kinetics and bifunctionality significantly influence signal transduction fidelity.
• Signal noise plays a regulatory role in gene expression, particularly under dynamic conditions.