Digital PCR to Determine the Number of Transcripts from Single Neurons after Patch-clamp Recording
Poster Sep 18, 2014
Nóra Faragó1,2, Ágnes K. Kocsis3, Sándor Lovas3, Gábor Molnár3, Márton Rózsa3, Viktor Szemenyei3, Ágnes Zvara2, Gábor Tamás3, László G Puskás1,2
Individual cells exhibit a large degree of variability in their gene expression profile. Whole-cell patch-clamp recording enables detecting electrophysiological signals from neurons, and RNA can be harvested into the patch pipette from the cells. Until recently, only QRT-PCR has been used to detect the expression of genes in single neurons. However, RNA profiling experiments based on sample amplification protocols on single cells, including traditional QRT-PCR lack exact quantitation due to experimental variations caused by the limited amount of nucleic acids. We have optimized a dPCR protocol for determining exact transcript numbers in single neurons after patch-clamp recording by using dPCR based on high-density nanocapillary PCR. Our method is suitable for the identification of individual genes participating in the maintenance of particular neuronal phenotypes, deconvolve different neuronal cell types and discover the exact distribution or variability of gene expression profiles of the electrophysiologically phenotyped cells more precisely than classical single cell QRT-PCR. We also provide comparative information on the applicability and sensitivity of other digital PCR technologies for single cell genomic analysis. We used our methods to profile single neurons from live brain slices prepared from rats, mice, as well as from human specimens.
In order to generate a robust protocol for MEA recording on hiPSC- derived neurons, we evaluated several conditions, which could affect culture performance (1.neuron seeding density; 2.seeding medium; 3.astrocyt eco-culture). These conditions were evaluated with BrainXell’s hiPSC-derived spinal motor neurons, cortical glutamatergic neurons and mixed cortical neurons.READ MORE