A new approach to real-time liquid-phase biomolecular sensing and discrimination at the single molecule level will be investigated. The system relies on stochastic measurements of ion transport across an array of biological nanopores in a microfluidic sensing platform, enabling single molecule mass measurements in a compact, low cost, and automated format. The microfluidic system will combine multiplexed arrays of individual ion channel sensing elements embedded in discrete bilayer lipid membranes within a disposable thermoplastic microfluidic chip, with multilayer channels enabling the dynamic delivery of analytes to the sensing sites. In its simplest form, the microfluidic chip will provide an alternative to traditional electrophysiological instruments for applications ranging from fundamental ion channel studies to drug target screening, allowing substantially higher analytical throughput without the need for manual operation by highly trained personnel. More significantly, the system will leverage recent results demonstrated by our team towards the identification and quantification of individual molecules on the basis of their molecular weight. Measurements will occur in real-time, providing time-resolved in-situ analysis within an aqueous environment without the need for gas-phase ionization, with direct control over the perfusion of analytes and other reagents to the multiplexed sensing sites. The resulting platform will be a unique enabling technology for a broad range of biomolecular analyses, and will be demonstrated for the identification and quantification of peptides within complex samples. )
Biosensor platforms capable of discriminating molecules on the basis of their molecule masses at the level of individual molecules offer significant promise towards advancing our fundamental understanding of biological processes. This project addresses the development of a unique microfluidic-enabled platform that will allow the mass-based identification of individual biomolecules within complex samples, providing a new window into the molecular networks that underlie disease state and progression.
