# Physical limit to concentration sensing in a changing environment

## TL;DR

This paper establishes a new physical limit on the accuracy of cellular concentration sensing in fluctuating environments, showing it scales differently than previous bounds and can be achieved by adaptive biochemical networks.

## Contribution

It formulates a non-linear field-theoretic model for sensing in fluctuating environments and derives a novel bound on sensing accuracy, contrasting with classical bounds.

## Key findings

- Derived a new physical bound: δc/c ∼ (Dacτ)^(-1/4)
- Showed the bound can be achieved by adaptive biochemical networks
- Contrasted the new bound with the classical Berg-Purcell limit

## Abstract

Cells adapt to changing environments by sensing ligand concentrations using specific receptors. The accuracy of sensing is ultimately limited by the finite number of ligand molecules bound by receptors. Previously derived physical limits to sensing accuracy have assumed that the concentration was constant and ignored its temporal fluctuations. We formulate the problem of concentration sensing in a strongly fluctuating environment as a non-linear field-theoretic problem, for which we find an excellent approximate Gaussian solution. We derive a new physical bound on the relative error in concentration $c$ which scales as $\delta c/c \sim (Dac\tau)^{-1/4}$ with ligand diffusivity $D$, receptor cross-section $a$, and characteristic fluctuation time scale $\tau$, in stark contrast with the usual Berg and Purcell bound $\delta c/c \sim (DacT)^{-1/2}$ for a perfect receptor sensing concentration during time $T$. We show how the bound can be achieved by a simple biochemical network downstream the receptor that adapts the kinetics of signaling as a function of the square root of the sensed concentration.