An Automated Electrophysiological Recording System with Electrical Resistance Feedback for Ion Channel Drug Discovery

Monitoring membrane proteins activity is of great importance to various biomedicalfields, including study of cell function and signaling pathway, disease research, drug screeningand discovery. Ion channels are highly specific membrane proteins that play a critical role incell communication and signaling by regulating the ion flow and generating the electricalsignal across the cell membrane. This process maintains proper functioning of different typesof cells such as neurons, cardiac and muscle cells. Many critical diseases and a diverse range ofdisorders are therefore associated with the malfunction of ion channels. However, the detailedmechanisms or processes of many ion-channel related diseases are still largely unknown.As ion channels act as the molecular targets for drug therapies, automated patch-clampelectrophysiology platforms have been extensively developed to automatically measure theelectrical signal through the specific ion channel, and increasingly used to investigate the effectof different drugs on the cell based on the acquired electrical signal. Thus far, it has still beenchallenging to achieve a high-yield measurement because the contact between themeasurement pipette tip and the cell has to be precisely controlled. In particular, it is extremelydifficult for the current automated system to determine the contact condition when the cells arein different sizes and properties. It further hinder the use of current automated patch-clampelectrophysiology platforms for studies of those cell types (such as neurons and cardiacmyocytes) that are grown in different sizes.We aim at developing a systematic approach to apply visual and electrical resistancefeedback for automated electrophysiology recording of cells with different sizes and properties.The visual feedback enables the real-time observation of the cells and the measurement pipettetip, while the contact condition of the measurement pipette tip and the selected cell can bedetermined based on electrical resistance feedback signals. Based on the correlation betweenthe electrical resistance feedback signals and the contact condition, a contact-to-patchalgorithm will be developed and implemented in a micro-robotic manipulation system toautomatically perform the electrical signal recording through the ion channels of the selectedcell. More importantly, the system will be equipped with another micro-pipette tip for drugdelivery and the electrical resistance feedback approach will be applied to allow the delivery ofthe drug into the selected cell precisely. This enables an on-line position tracking, drug deliveryand electrophysiological recording in the same platform.While most of the conventional automated patch-clamp electrophysiology platforms areonly designed for high-throughput screening of limited cell types, the proposed research furtherexpand the capability of conventional automated patch-clamp electrophysiology platforms todirectly study the ion channel activity of a diverse range of cells at single cell level moreprecisely and effectively. The information obtained from different types of ion channels isparticularly important for a wide range of biomedical research and studies, and the proposedresearch creates a significant impact in understanding the ion channel related diseases anddevelop the therapies that are specific and personalized.