Creating Clinically-Relevant Biosensors-Integrating Hierarchically Structured Transducers with Dynamic Signal Recognition Elements
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abstract
Biosensors combine biorecognition and signal transduction to analyze biologically-relevant species that are markers of disease or indicators of health. The performance metrics of biosensors, such as limit-of-detection and speed, are strongly influenced by the structure of the transducer. Designing material architectures that increase the sensor sensitivity, decrease background signals, and reduce analysis time is critical for entering biosensors into clinical decision making and health monitoring. Additionally, the specificity of biosensors are controlled by introducing biorecognition elements into the biosensing system. Developing biorecognition elements that specifically capture analytes of interest and effectively translate this capture to a detectible signal is the other critical piece of biosensor development. We have developed strategies for creating three-dimensional transducer architectures, combining them with dynamic biorecognition elements, and translating biorecognition into electrochemical signals. All-solution-processing is used to create three-dimensional biosensing electrodes. This method combines self-assembly, electroless deposition, electrodeposition, and shape memory polymer substrates to create porous and wrinkled hierarchical electrodes. Biorecognition is achieved using molecular machines that release an electroactive DNA barcode in response to a target analyte, which is analyzed at the electrode surface using electrochemical readout. Three-dimensional electrodes, biorecognition elements, and signal transduction components are integrated into microfluidic networks for sensing small molecules, nucleic acids, and proteins. This integrated biosensing platform is used for analyzing clinical samples, and a test with a clinically-relevant limit-of-detection is achieved.
