Extracellular electrophysiological based sensor to monitor cancer cells cooperative migration and cell-cell connections.

Herein, we describe an electrophysiological based sensor that reproducibly monitors and quantifies in real-time collective migration and the formation of cell-cell junctions by C6 glioma cells seeded on top of electrodes. The signal amplitude and frequency generated by the migrating cells changed over time and these parameters were used to accurately calculate the migration speed. Electrophysiological measurements could also distinguish individual from collective cell migration. The migration of densely packed cells generated strong signals, while dispersed cells showed weak bioelectrical activity. We propose this electrophysiological technique as a cell-based biosensor to gain insight into the mechanisms of cooperative migration of cancer cells. Possible applications include screening for anti-migratory compounds, which may lead to the development of novel strategies for antineoplastic chemotherapy.

Extracellular electrical recording of pH-triggered bursts in C6 glioma cell populations.

Glioma patients often suffer from epileptic seizures because of the tumor's impact on the brain physiology. Using the rat glioma cell line C6 as a model system, we performed long-term live recordings of the electrical activity of glioma populations in an ultrasensitive detection method. The transducer exploits large-area electrodes that maximize double-layer capacitance, thus increasing the sensitivity. This strategy allowed us to record glioma electrical activity. We show that although glioma cells are nonelectrogenic, they display a remarkable electrical burst activity in time. The low-frequency current noise after cell adhesion is dominated by the flow of Na+ ions through voltage-gated ion channels. However, after an incubation period of many hours, the current noise markedly increased. This electric bursting phenomenon was not associated with apoptosis because the cells were viable and proliferative during the period of increased electric activity. We detected a rapid cell culture medium acidification accompanying this event. By using specific inhibitors, we showed that the electrical bursting activity was prompted by extracellular pH changes, which enhanced Na+ ion flux through the psalmotoxin 1-sensitive acid-sensing ion channels. Our model of pH-triggered bursting was unambiguously supported by deliberate, external acidification of the cell culture medium. This unexpected, acidosis-driven electrical activity is likely to directly perturb, in vivo, the functionality of the healthy neuronal network in the vicinity of the tumor bulk and may contribute to seizures in glioma patients.

Electrochemical noise and impedance of Au electrode/electrolyte interfaces enabling extracellular detection of glioma cell populations.

Microelectrode arrays (MEA) record extracellular local field potentials of cells adhered to the electrodes. A disadvantage is the limited signal-to-noise ratio. The state-of-the-art background noise level is about 10 µVpp. Furthermore, in MEAs low frequency events are filtered out. Here, we quantitatively analyze Au electrode/electrolyte interfaces with impedance spectroscopy and noise measurements. The equivalent circuit is the charge transfer resistance in parallel with a constant phase element that describes the double layer capacitance, in series with a spreading resistance. This equivalent circuit leads to a Maxwell-Wagner relaxation frequency, the value of which is determined as a function of electrode area and molarity of an aqueous KCl electrolyte solution. The electrochemical voltage and current noise is measured as a function of electrode area and frequency and follow unambiguously from the measured impedance. By using large area electrodes the noise floor can be as low as 0.3 µVpp. The resulting high sensitivity is demonstrated by the extracellular detection of C6 glioma cell populations. Their minute electrical activity can be clearly detected at a frequency below about 10 Hz, which shows that the methodology can be used to monitor slow cooperative biological signals in cell populations.