Robustness against additional noise in cellular information transmission

Area of Science:

• Systems Biology
• Biophysics
• Cellular Signaling

Background:

• Cellular responses are affected by internal (intrinsic) and external (extrinsic) noise.
• Higher intrinsic noise can paradoxically improve robustness against extrinsic noise, a phenomenon known as intrinsic noise-induced robustness (INIR).
• Previous studies focused on complex systems, leaving the input-output relationship and INIR mechanisms unclear.

Purpose of the Study:

• To investigate the relationship between intrinsic noise and system input-output dynamics.
• To elucidate the underlying mechanisms of intrinsic noise-induced robustness (INIR).
• To analyze INIR in simplified models to understand its fundamental properties.

Main Methods:

• Analysis of a linear input-output model to assess INIR.
• Investigation of a threshold model with varying threshold levels.
• Mathematical modeling of cellular noise and information transmission.

Main Results:

• Confirmed INIR in a linear model, showing robustness increases with intrinsic noise.
• Demonstrated that INIR is more pronounced when intrinsic noise variance exceeds input distribution variance.
• Observed that INIR is apparent in a threshold model when the threshold matches the input mean, but not always when the threshold is high (stochastic resonance).

Conclusions:

• INIR is a general phenomenon observable in simple systems.
• A trade-off exists between robustness and information transmission in linear and non-stochastic threshold models.
• Stochastic resonance in threshold models can allow simultaneous increases in robustness and information transmission.