Creating Ultrafast Biosensors for Neuroscience
Doctoral thesis, 2019
Neuronal communication is the basis for all our brain function and relies on regulated exocytosis, a cell function that involves release of quantal amounts of neurotransmitters into the gap space between interconnected neurons to serve as chemical signals. To study exocytosis, which is a fast process that occurs on the timescale of sub-milliseconds to milliseconds, a toolbox of analytical methods has been developed where the electrochemical based techniques offer quantitative and sufficient high temporal recording speed. However, neuronal activity involving non-electroactive neurotransmitters such as acetylcholine and glutamate have long time suffered from a limited detection speed about 3 orders of magnitude slow for capturing the rapid transients from exocytosis release by these non-electroactive compounds. In this work, we have focused on a new approach for the development of amperometric enzyme-nanoparticle-based sensors that significantly improve recording speed of important non-electroactive brain analytes and are suitable for ultrafast recording in neuroscience research.
In Paper I, an acetylcholine sensor was designed and fabricated by modifying the sensor surface with gold nanoparticles (AuNPs) and two sequential enzymes, where the enzyme coating was limited to a monolayer in thickness to minimize enzyme product diffusion distance to be detected by the electrode surface. This novel sensor provided the first proof of concept to improving enzyme-based sensors speed by 2 orders of magnitude compared to existing technology and was fast enough to temporally resolve single millisecond vesicle release events of acetylcholine from an artificial cell model that mimics exocytosis.
In Paper II, a new and analytical method was introduced that provided a significantly faster and a non-toxic way to quantify AuNP immobilized enzymes during sensor surface characterization in comparison to the previous method used in Paper I that involved using toxic cyanide solutions. This method was based on electrochemical stripping of AuNPs from the electrode surface after enzymes were attached, followed by quantifying the number of enzymes released, to determine the average number of enzymes attached to each single nanoparticle.
In Paper III, an ultrafast glutamate sensor was developed by careful characterization of the conditions for controlling the enzyme coverage on a AuNP decorated electrode surface to a monolayer. By placing this novel sensor in the Nucleus Accumbens of rodent brain slice, recording of spontaneous glutamate activity and various isolated dynamic current transients from single exocytotic events on the sub-millisecond timescale were captured.
In Paper IV, the conjugation of enzyme glucose oxidase (GOx) to AuNP surfaces was used to study how physical crowding affects enzyme stability and activity when immobilized at a highly curved nanoparticle surface. This work showed that by crowding a gold nanoparticle surface with its maximum number of enzymes that can theoretically fit, while maintaining a monolayer coverage, the retained enzymatic activity of immobilized enzyme improved 300% compared to GOx free in solution. Implementing these findings to a nanostructured electrochemical biosensor for glucose confirmed a recording speed for glucose on the millisecond timescale
In Paper V, using our novel ultrafast glutamate sensor, a novel method was developed for quantification of the quantal glutamate content in single synaptic vesicles, and quantification of the quantal amount glutamate released from single exocytosis events in rodent brain tissue.