Comparison of cell expression formats for the characterization of GABA(A) channels using a microfluidic patch clamp system
Qin Chen, Nina Yuan*, Peter Yim**,Juliette Johnson, Steve Smith, Cristian Ionescu-Zanetti, Leggy A. Arnold*, Charles Emala**
*Department of Chemistry and Biochemistry, University of Wisconsin-Milwaukee, Milwaukee, WI 53211 **Department of Anesthesiology, Columbia University, New York, New York 10032
Fluxion Biosciences, South San Francisco, CA 94080
Ensemble recording and microfluidic perfusion are recently introduced techniques aimed at removing the laborious nature and low recording success rates of manual patch clamp. Here, we present assay characteristics for these features integrated into one automated electrophysiology platform as applied to the study of GABAA channels. A variety of cell types and methods of GABAA channel expression were successfully studied (defined as IGABA > 500pA) including stably transfected HEK cells expressing 132 GABAA channels, frozen “ready to assay” (RTA)HEK cells expressing 132 or 332 GABAA channels, transiently transfected HEK293T cells expressing 132 GABAA channels, and immortalized cultures of human airway smooth muscle cells endogenously express- ing GABAA channels. We obtained success rates above 95% for transiently or stably transfected HEK cells and frozen “ready to assay” HEK cells expressing GABAA channels. Current measurements were successfully studied in multiple cell types with multiple modes of channel expression in response to several classic GABAA channel agonists, antagonists and allosteric modulators. Tissue- derived immortalized cultures of airway smooth muscle cells exhibited a slightly lower recording success rate of 75% using automated patch, which was much higher than the 5% success rate using manual patch clamp. In all cases, responses to agonists, antagonists and allosteric modulators compared well to previously reported manual patch results. The data demonstrate that both the bio- physics and pharmacologic characterization of GABAA channels in a wide variety of cell formats can be performed using IonFlux.
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