The University of British Columbia

This paper deals with the experimental construction, stochastic modeling and statistical signal processing of a novel biosensor comprising of biological ion channels. Such nano-scale biosensors are built by incorporating dimeric Gramicidin ion channels into the bilayer membranes of giant unilamellar liposomes and then excising small patches of the membrane loaded with ion channels. We show that target molecules affect the statistics of the gating mechanism of the dimeric Gramicidin ion channels and present statistical verifications on the adequacy of a Hidden Markov Model for modeling of the biosensor. A likelihood ratio test is then devised to detect the presence of target molecules. To test the sensitivity of this model we conducted patch-clamp experiments with and without the Methylbenzthonium Chloride compound. The real-time detection algorithm was able to accurately detect the presence of the compound from alterations in the patch-clamp recordings. This algorithm provides the sensitive detection system for ongoing development of lipid-based nano-sensors.