The Electrical Interface between Solid-State Electronics and Biology: Applications in Biomolecular Sensing and Electrophysiological Interrogations

Abstract

Electrical interactions between biology and integrated electronics enable biomolecular detection and electrophysiological investigations to be performed at the chip-scale, for low-cost, and in a highly parallelized manner. Biomolecules and electrogenic cells can be electrically sensed by solid-state devices through their inherent charge or through their voltage/current response in solution. Integrated analog and digital circuitry then enables signal amplification for improved signal-to-noise ratio, highly parallelized measurements through multiplexing, and real-time controllability. Furthermore, stimulation circuitry can electrically influence biomolecules and cells through the application of voltages/currents to the solution. Here, the development, focusing on the electrical design and measurement, of several solid-state/biological interfaces is discussed. To start, a graphene array is developed and utilized in dual roles to demonstrate a path towards all-electrical multiplexed DNA arrays. It is first used as a sensing FET, detecting the charge of hybridized DNA with high sensitivity, and second, as an electrophoretic electrode for site-specific probe DNA immobilization. Complementary metal-oxide semiconductor (CMOS) technology is then used to create an ion-sensitive field-effect transistor (ISFET) array with the aim of highly parallelized biomolecular detection. A thorough study on the optimization of the charge sensitivity through geometry and biasing is presented and verified by DNA hybridization experiments. For electrophysiological interrogations, a custom designed CMOS integrated circuit (IC) is combined with nanoscale electrodes to form the CMOS nanoelectrode array (CNEA). The small diameter of the vertical nanoelectrodes allows membrane penetration for intracellular access whereas proximate circuitry in the underlying CMOS IC enables recording, stimulation, and operation at the network-level. The first generation CNEA, containing 1,024 pixels, is demonstrated to simultaneously record intracellular membrane potentials from hundreds of connected cardiomyocytes and performs network-level manipulation through voltage-based stimulation. A second generation CNEA, containing 4,096 pixels and additional functionality, is then presented. The combination of a better signal to noise ratio and the inclusion of a current stimulator suggest increased performance in future biological experiments.