Biological olfactory receptors appear to function as protein-based spectroscopes, converting vibrational mode information encoding odorant identity into neuronal action potentials within the olfactory bulb. A tunneling electron transitioning between electron-rich and electron-deficient domains of the receptor is surmised to transduce the information about the frequency of odorant vibrational modes by the inelastic exchange of energy between the electron and odorant vibrations. A multi-layer network of interconnected neuronal glomeruli and mitral cells is trained experientially to fingerprint and ‘recognize’ odors from the multiplicity of signals emanating from the receptors, thereby creating a reference database that is leveraged to characterize unknown species.
We have demonstrated an electrochemical platform that mimics the operational principles of the olfactory system, the Quantum Tunneling Electronic Platform (QTEP), where the analyte signature is encoded in the tunneling current at the electrochemical interface. The partial specificity of the signal generating-front end eliminates the need for carefully designed and engineered probes, and the electronic nature of the transduction mechanism precludes the need for labels. The adaptive back-end for the proposed platform identifies unknown biomarker analytes by comparing the signatures from clinical sample with the fingerprints in the reference database, thereby eliminating the need to customize the sensor for specific targets making the detection paradigm broad spectrum in nature.
We have optimized the design of the nano-electrochemical sensor, based on an analytical model for the electrochemical exchange of a single electronic charge between the discrete electronic energy levels of a metallic electrode and a redox active species in a polar electrolyte. The complete spectrum of tunneling electron energy is accessed via a quasi-static sweep of the voltage bias at the interface. The analytics backend for the nano-electrochemical sensor is being developed to be capable of recognizing a biomarker of interest from within a complex matrix, like serum, by recognizing the characteristic vibronic signature fingerprints of the marker which may be derived from reference measurements.