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results during qRT-PCR or dPCR, meaning that no genomic amplification occurred during our study (data not shown). To demonstrate that single cell qRT-PCR


resulted in the desired PCR fragments, we sequenced PCR products from individual neurogliaform and pyramidal cells. Although we used validated TaqMan probes in the present study, we sequenced PCR products for all of the amplified genes. Using BLASTN homology searches, we found a 100% match to each gene sequence (data not shown). Tese data confirm that minimal to no amplification of genomic DNA occurred and that amplifi- cations were highly specific.


Strengths and limitations One of the strengths of our PCR protocol


compared to other end-point amplification based PCR methods is that the detection of positive signals is based on individual real-time PCR read-outs. By using the calling algorithm in the OpenArray soſtware and having different thresholds for CT


confi-


dence intervals and cycle cutoff values, most of the false positive hits generated by primer dimers or nonspecific amplifications can be excluded. Partitioning the sample into hundreds


or thousands of independent reaction holes (in the case of OpenArray plates) or reaction chambers (using the Fluidigm technology) during dPCR increases the detection sensi- tivity of specific DNA molecules by increasing the target-to-background ratios (12,14,16). Here we described the combination of


whole-cell patch-clamp recording with digital analysis of specific mRNA or miRNA using high-density nanocapillary dPCR. The accuracy and sensitivity of the method was validated with spike-in templates as well as by detecting cDNA from genes with low levels of expression. One of the main advan- tages of this approach is that accurate digital gene expression analyses can be performed on electrophysiologically defined single neurons. Te real-time PCR based dPCR protocol, along with the application of different thresholds for confidence CT


and cycle cutoff values led to


low rates of false positive calls. However, the limitations of the technique are the relative high cost per sample and low-throughput, which restricts the number of genes that can be analyzed from the same cell.


Acknowledgments


Tis work was supported by the following grants: ERC Advanced Grant, EURYI, NIH N535915 and the Hungarian Academy of Sciences (G.T.), and GOP-1.1.1-11-2011-0003 from the National Investment Agency (NIH) (Avidin, BRC).


Vol. 54 | No. 6 | 2013


Competing interests Te authors declare no competing interests.


References


1. Monyer, H. and B. Lambolez. 1995. Molecular biology and physiology at the single-cell level. Curr. Opin. Neurobiol. 5:382-387.


2. Sugino, K., C.M. Hempel, M.N. Miller, A.M. Hattox, P. Shapiro, C. Wu, Z.J. Huang, and S.B. Nelson. 2006. Molecular taxonomy of major neuronal classes in the adult mouse forebrain. Nat. Neurosci. 9:99-107.


3. Hinkle, D., J. Glanzer, A. Sarabi, T. Pajunen, J. Zielinski, B. Belt, K. Miyashiro, T. McIntosh, and J. Eberwine. 2004. Single neurons as exper- imental systems in molecular biology. Prog. Neurobiol. 72:129-142.


4. Ståhlberg, A., D. Andersson, J. Aurelius, M. Faiz, M. Pekna, M. Kubista, and M. Pekny. 2011. Defining cell populations with single-cell gene expression profiling: correlations and identi- fication of astrocyte subpopulations. Nucleic Acids Res. 39:e24.


5. Gründemann, J., F. Schlaudraff, O. Haeckel, and B. Liss. 2008. Elevated alpha-synuclein mRNA levels in individual UV-laser-microdis- sected dopaminergic substantia nigra neurons in idiopathic Parkinson’s disease. Nucleic Acids Res. 36:e38.


6. Eberwine, J., H. Yeh, K. Miyashiro, Y. Cao, S. Nair, R. Finnell, M. Zettel, and P. Coleman. 1992. Analysis of gene expression in single live neurons. Proc. Natl. Acad. Sci. USA 89:3010- 3014.


7. Lambolez, B., E. Audinat, P. Bochet, F. Crepel, and J. Rossier. 1992. AMPA receptor subunits expressed by single Purkinje cells. Neuron 9:247- 258.


8. Bengtsson, M., A. Stahlberg, P. Rorsman, and M. Kubista. 2005. Gene expression profiling in single cells from the pancreatic islets of Langerhans reveals lognormal distribution of mRNA levels. Genome Res. 15:1388-1392.


9. Kalisky, T. and S.R. Quake. 2011. Single-cell genomics. Nat. Methods 8:311-314.


10. Vogelstein, B. and K.W. Kinzler. 1999. Digital PCR. Proc. Natl. Acad. Sci. USA 96:9236- 9241.


11. Zeng, Y., R. Novak, J. Shuga, M.T. Smith, and R.A. Mathies. 2010. High-performance single cell genetic analysis using microfluidic emulsion generator arrays. Anal. Chem. 82:3183-3190.


12. Fabian, G., N. Farago, L.Z. Feher, L.I. Nagy, S. Kulin, K. Kitajka, T. Bito, V. Tubak, et al. 2011. High-Density Real-Time PCR-Based in Vivo Toxicogenomic Screen to Predict Organ-Specific Toxicity. Int. J. Mol. Sci. 12:6116-6134.


13. Morrison, T., J. Hurley, J. Garcia, K. Yoder, A. Katz, D. Roberts, J. Cho, T. Kanigan, et al. 2006. Nanoliter high throughput quantitative PCR. Nucleic Acids Res. 34:e123.


14. Oehler, V.G., J. Qin, R. Ramakrishnan, G. Facer, S. Ananthnarayan, C. Cummings, M. Deininger, N. Shah, et al. 2009. Absolute quanti- tative detection of ABL tyrosine kinase domain point mutations in chronic myeloid leukemia using a novel nanofluidic platform and mutation- specific PCR. Leukemia 23:396-399.


15.Spurgeon, S.L., R.C. Jones, and R. Ramakrishnan. 2008. High throughput gene expression measurement with real time PCR in a microfluidic dynamic array. PloS One 3:e1662.


336 www.BioTechniques.com


16. Vass, L., J.Z. Kelemen, L.Z. Feher, Z. Lorincz,S. Kulin, S. Cseh, G. Dorman, and L.G. Puskas. 2009. Toxicogenomics screening of small molecules using high-density, nanocapillary real-time PCR. Int. J. Mol. Med. 23:65-74.


17. Oláh, S., M. Fule, G. Komlosi, C. Varga, R. Baldi, P. Barzo, and G. Tamas. 2009. Regulation of cortical microcircuits by unitary GABA-mediated volume transmission. Nature 461:1278-1281.


18. Cauli, B., J.T. Porter, K. Tsuzuki, B. Lambolez, J. Rossier, B. Quenet, and E. Audinat. 2000. Classi- fication of fusiform neocortical interneurons based on unsupervised clustering. Proc. Natl. Acad. Sci. USA 97:6144-6149.


19. Ferezou, I., S. Bolea, and C.C. Petersen. 2006. Visualizing the cortical representation of whisker touch: voltage-sensitive dye imaging in freely moving mice. Neuron 50:617-629.


20.Hestrin, S. and W.E. Armstrong. 1996. Morphology and physiology of cortical neurons in layer I. J. Neurosci. 16:5290-5300.


21. Kawaguchi, Y. 1995. Physiological subgroups of nonpyramidal cells with specific morphological characteristics in layer II/III of rat frontal cortex. J. Neurosci. 15:2638-2655.


22.Price, C.J., B. Cauli, E.R. Kovacs, A. Kulik, B. Lambolez, R. Shigemoto, and M. Capogna. 2005. Neurogliaform neurons form a novel inhib- itory network in the hippocampal CA1 area. J. Neurosci. 25:6775-6786.


23.Tamás, G., A. Lorincz, A. Simon, and J. Szabadics. 2003. Identified sources and targets of slow inhibition in the neocortex. Science 299:1902- 1905.


24. Zsiros, V. and G. Maccaferri. 2005. Electrical coupling between interneurons with different excitable properties in the stratum lacunosum- moleculare of the juvenile CA1 rat hippocampus. J. Neurosci. 25:8686-8695.


25.Tang, F., P. Hajkova, S.C. Barton, D. O’Carroll, C. Lee, K. Lao, and M.A. Surani. 2006. 220-plex microRNA expression profile of a single cell. Nat. Protoc. 1:1154-1159.


26. Grigorenko, E.V., E. Ortenberg, J. Hurley, A. Bond, and K. Munnelly. 2011. miRNA profiling on high-throughput OpenArray system. Methods Mol. Biol. 676:101-110.


27.Miller, B.H. and C. Wahlestedt. 2010. MicroRNA dysregulation in psychiatric disease. Brain Res. 1338:89-99.


28.Cadet, J.L., C. Brannock, B. Ladenheim, M.T. McCoy, G. Beauvais, A.B. Hodges, E. Lehrmann, W.H. Wood, et al. 2011. Methamphetamine preconditioning causes differential changes in striatal transcriptional responses to large doses of the drug. Dose Response. 9:165-181.


Received 07 January 2013; accepted 24 April 2013.


Address correspondence to László G. Puskás, Avidin Ltd., Szeged, Hungary. E-mail: laszlo@avidinbio- tech.com or to Gabor Tamás, Research Group for Cortical Microcircuits of the Hungarian Academy of Sciences Department of Physiology, Anatomy and Neuroscience, University of Szeged, Hungary. E-mail: gtamas@bio.u-szeged.hu.


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