Biological shot-noise and quantum-limited signal-to-noise ratio in affinity-based biosensors

We study the statistical behavior of affinity-based biosensors. The detection uncertainty and noise in such devices originates primarily from probabilistic molecular-level bindings within the sensing regions, and the stochastic mass-transfer processes within the reaction chamber. In this paper, we model the dynamic behavior of these sensory systems by a Markov process, which enables us to estimate the sensor inherent noise power spectral density (PSD) and response time. We also present the methods by which the Markov parameters are extracted from the reaction kinetic rates, diffusion coefficients, and reaction chamber boundary conditions. Using this model, we explain why Poisson shot noise has been reported in such biosensors and additionally predict a Lorentzian profile for the fluctuation PSD. Furthermore, we demonstrate that affinity-based biosensors have a quantum-limited signal-to-noise ratio (SNR). We also show that the SNR decreases as the dimensions are isomorphically scaled down while the biosensor response speed increases, substantiating a fundamental trade-off between biosensor speed and accuracy. (C) 2005 American Institute of Physics.