Quantitative single-cell ion-channel gene expression profiling through an improved qRT-PCR technique combined with whole cell patch clampQuantitative single-cell ion-channel gene expression profiling through an improved qRT-PCR technique combined with whole cell patch clamp
Faculty of Pharmaceutical, Biomedical and Veterinary Sciences . Biomedical Sciences
Molecular biophysics, physiology and pharmacology
Journal of neuroscience methods. - Amsterdam
209(2012):1, p. 227-234
University of Antwerp
Cellular excitability originates from a concerted action of different ion channels. The genomic diversity of ion channels (over 100 different genes) underlies the functional diversity of neurons in the central nervous system (CNS) and even within a specific type of neurons large differences in channel expression have been observed. Patch-clamp is a powerful technique to study the electrophysiology of excitability at the single cell level, allowing exploration of cell-to-cell variability. Only a few attempts have been made to link electrophysiological profiling to mRNA transcript levels and most suffered from experimental noise precluding conclusive quantitative correlations. Here we describe a refinement to the technique that combines patch-clamp analysis with quantitative real-time (qRT) PCR at the single cell level. Hereto the expression of a housekeeping gene was used to normalize for cell-to-cell variability in mRNA isolation and the subsequent processing steps for performing qRT-PCR. However, the mRNA yield from a single cell was insufficient for performing a valid qRT-PCR assay; this was resolved by including a RNA amplification step. The technique was validated on a stable Ltk(-) cell line expressing the Kv2.1 channel and on embryonic dorsal root ganglion (DRG) cells probing for the expression of Kv2.1. Current density and transcript quantity displayed a clear correlation when the qRT-PCR assay was done in twofold and the data normalized to the transcript level of the housekeeping gene GAPD. Without this normalization no significant correlation was obtained. This improved technique should prove very valuable for studying the molecular background of diversity in cellular excitability. (c) 2012 Elsevier B.V. All rights reserved.