RESUMO
BACKGROUND: Electrophysiological recording with glass electrodes is one of the best techniques to measure membrane potential dynamics and ionic currents of voltage-gated channels in neurons. However, artifactual variability of the biophysical state variables that determine recording quality can be caused by insufficient affinity between the electrode and cell membrane during the recording. NEW METHOD: We introduce a phospholipid membrane coating on glass electrodes to improve intracellular electrophysiology recording quality. Membrane-coated electrodes were prepared with a tip-dip protocol for perforated-patch, sharp-electrode current-clamp, and cell-attached patch-clamp recordings from specific circadian clock neurons in Drosophila. We perform quantitative comparisons based on the variability of functional biophysical parameters used in various electrophysiological methods, and advanced statistical comparisons based on the degree of stationariness and signal-to-noise ratio. RESULTS: Results indicate a dramatic reduction in artifactual variabilities of functional parameters from enhanced stability. We also identify significant exclusions of a statistically estimated noise component in a time series of membrane voltage signals, improving signal-to-noise ratio. COMPARISON WITH EXISTING METHODS: Compared to standard glass electrodes, using membrane-coated glass electrodes achieves improved recording quality in intracellular electrophysiology. CONCLUSIONS: Electrophysiological recordings from Drosophila central neurons can be technically challenging, however, membrane-coated electrodes will possibly be beneficial for reliable data acquisition and improving the technical feasibility of axonal intracellular activities measurements and single-channel recordings. The improved electrical stability of the recordings should also contribute to increased mechanical stability, thus facilitating long-term stable measurements of neural activity. Therefore, it is possible that membrane-coated electrodes will be useful for any model system.