Chemosensing in microorganisms to practical biosensors

TL;DR

This paper revisits the Berg and Purcell model to analyze how physical limits affect the design of practical biosensors based on microorganism chemosensing, focusing on reaction-diffusion processes and long-term signal saturation.

Contribution

It provides a detailed modeling framework for biosensor kinetics, incorporating reaction-diffusion dynamics and long-term behavior, extending prior microorganism sensing models to practical sensor design.

Findings

Reaction-diffusion modeling characterizes biosensor behavior.

Long-term saturation time influences sensor efficiency.

Estimated kinetic constants inform sensor design.

Abstract

Microorganisms like bacteria can sense concentration of chemo-attractants in its medium very accurately. They achieve this through interaction between the receptors on their cell surface and the chemo-attractant molecules (like sugar). But the physical processes like diffusion set some limits on the accuracy of detection which was discussed by Berg and Purcell in the late seventies. We have a re-look at their work in order to assess what insight it may offer towards making efficient, practical biosensors. We model the functioning of a typical biosensor as a reaction-diffusion process in a confined geometry. Using available data first we characterize the system by estimating the kinetic constants for the binding/unbinding reactions between the chemo-attractants and the receptors. Then we compute the binding flux for this system which Berg and Purcell had discussed. But unlike in microorganisms where the interval between successive measurements determines the efficiency of the nutrient searching process, it turns out that biosensors depend on long time properties like signal saturation time which we study in detail. We also develop a mean field description of the kinetics of the system.