Dynamic sampling and information encoding in biochemical networks

TL;DR

This study explores how fibroblast cells encode environmental information through calcium response dynamics, revealing that information encoding depends on sampling rate, noise, and acts as a low-pass filter, highlighting cellular information processing limits.

Contribution

It introduces a vectorial measure for dynamic information encoding in biochemical responses and shows the decoding mechanism's role as a low-pass filter, independent of detailed dynamics.

Findings

Information depends on sampling rate and memory capacity.

Intrinsic and extrinsic noise affect information differently.

Decoding acts as a simple low-pass filter regardless of dynamics.

Abstract

Cells use biochemical networks to translate environmental information into intracellular responses. These responses can be highly dynamic, but how the information is encoded in these dynamics remains poorly understood. Here we investigate the dynamic encoding of information in the ATP-induced calcium responses of fibroblast cells, using a vectorial, or multi-time-point, measure from information theory. We find that the amount of extracted information depends on physiological constraints such as the sampling rate and memory capacity of the downstream network, and is affected differentially by intrinsic vs. extrinsic noise. By comparing to a minimal physical model, we find, surprisingly, that the information is often insensitive to the detailed structure of the underlying dynamics, and instead the decoding mechanism acts as a simple low-pass filter. These results demonstrate the mechanisms and limitations of dynamic information storage in cells.