Highly Extensible Programmed Biosensing Circuits with Fast Memory.

摘要

The overall aim of the project is to develop a robust platform for an array based detector that could sense, distinguish and quantify diverse collections of environmental analytes. We have previously developed cell based reporters that afford the ability to recognize a large number of chemicals, built around G-protein coupled receptors (GPCRs), which provide high diversity and broad specificity. To render this detector system able to function in real time, we are applying synthetic biology approaches to engineer cells with a fast, phosphorylation based memory circuit. This solves two problems: the readout is based on protein phosphorylation and thus occurs within seconds. Second, the response, once established, remains fixed, so that the readout can be analyzed without a transient loss of signal. In order to interpret the results we obtain from the proposed array detector, we have developed a Bayesian-based computational method for extracting the identities and amounts of compounds in a mixture. Applying our computation approach to results obtained with a prototype GPCR-based array, we were able to extract the identity and amounts of compounds in complex mixtures. This provides validation of the method, which could be of broad use for any array based detector system.