The Energetic Costs of Cellular Computation

TL;DR

This paper quantifies the energy required for cells to perform environmental sensing computations, revealing that more accurate sensing demands higher energy expenditure, which constrains cellular network design in resource-limited settings.

Contribution

It provides an explicit calculation of the energetic costs of ligand concentration sensing in cellular networks, linking energy consumption to computational accuracy.

Findings

Energy consumption increases with the accuracy of ligand concentration estimation.

Breaking detailed balance is necessary for cellular computation, requiring energy.

Energetic costs may limit cellular network functions in resource-scarce environments.

Abstract

Cells often perform computations in response to environmental cues. A simple example is the classic problem, first considered by Berg and Purcell, of determining the concentration of a chemical ligand in the surrounding media. On general theoretical grounds (Landuer's Principle), it is expected that such computations require cells to consume energy. Here, we explicitly calculate the energetic costs of computing ligand concentration for a simple two-component cellular network that implements a noisy version of the Berg-Purcell strategy. We show that learning about external concentrations necessitates the breaking of detailed balance and consumption of energy, with greater learning requiring more energy. Our calculations suggest that the energetic costs of cellular computation may be an important constraint on networks designed to function in resource poor environments such as the spore germination networks of bacteria.