Abstract
The ability to correlate single-cell genetic information with cellular phenotypes is of great importance to biology and medicine, as it holds the potential to gain insight into disease pathways that is unavailable from ensemble measurements. We present a microfluidic approach to parallelized, rapid, quantitative analysis of messenger RNA from single cells via RT-qPCR. The approach leverages an array of single-cell RT-qPCR analysis units formed by a set of parallel microchannels concurrently controlled by elastomeric pneumatic valves, thereby enabling parallelized handling and processing of single cells in a drastically simplified operation procedure using a relatively small number of microvalves. All steps for single-cell RT-qPCR, including cell isolation and immobilization, cell lysis, mRNA purification, reverse transcription and qPCR, are integrated on a single chip, eliminating the need for off-chip manual cell and reagent transfer and qPCR amplification as commonly used in existing approaches. Additionally, the approach incorporates optically transparent microfluidic components to allow monitoring of single-cell trapping without the need for molecular labeling that can potentially alter the targeted gene expression and utilizes a polycarbonate film as a barrier against evaporation to minimize the loss of reagents at elevated temperatures during the analysis. We demonstrate the utility of the approach by the transcriptional profiling for the induction of the cyclin-dependent kinase inhibitor 1a and the glyceraldehyde 3-phosphate dehydrogenase in single cells from the MCF-7 breast cancer cell line. Furthermore, the methyl methanesulfonate is employed to allow measurement of the expression of the genes in individual cells responding to a genotoxic stress.
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References
Abbas T, Dutta A (2009) p21 in cancer: intricate networks and multiple activities. Nat Rev Cancer 9:400–414
Alberts B, Johnson A, Lewis J, Raff M, Roberts K (2002) Molecular biology of the cell. Garland Science, New York
Araci I, Quake S (2012) Microfluidic very large scale integration (mVLSI) with integrated micromechanical valves. Lab Chip 12:2803–2806
Bustin SA, Benes V, Garson JA et al (2009) The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55:611–622
Chattopadhyay PK, Gierahn TM, Roederer M, Love JC (2014) Single-cell technologies for monitoring immune systems. Nat Immunol 15:128–135
Cheow LF, Quake SR, Burkholder WF et al (2015) Multiplexed locus-specific analysis of DNA methylation in single cells. Nat Protoc 10:619–631
Choudhury AR, Ju Z, Djojosubroto MW et al (2006) Cdkn1a deletion improves stem cell function and lifespan of mice with dysfunctional telomeres without accelerating cancer formation. Nat Genet 39:99–105
de Bourcy CFA, De Vlaminck I, Kanbar JN et al (2014) A quantitative comparison of single-cell whole genome amplification methods. PLoS One 9:e105585
Dimov IK, Garcia-Cordero JL, O’Grady J et al (2008) Integrated microfluidic tmRNA purification and real-time NASBA device for molecular diagnostics. Lab Chip 8:2071–2078
Dun B, Sharma A, Xu H et al (2014) Transcriptomic changes induced by mycophenolic acid in gastric cancer cells. Am J Transl Res 6:28
Eastburn DJ, Sciambi A, Abate AR (2013) Ultrahigh-throughput mammalian single-cell reverse-transcriptase polymerase chain reaction in microfluidic drops. Anal Chem 85:8016–8021
Fluidigm Corporation (2014) The single-cell preparation guide. https://www.fluidigm.com
Han N, Shin JH, Han KH (2014) An on-chip RT-PCR microfluidic device, that integrates mRNA extraction, cDNA synthesis, and gene amplification. RSC Adv 4:9160–9165
Kim SH, He X, Kaneda S et al (2014) Quantifying genetically inserted fluorescent protein in single iPS cells to monitor Nanog expression using electroactive microchamber arrays. Lab Chip 14:730–736
Klemm S, Semrau S, Wiebrands K et al (2014) Transcriptional profiling of cells sorted by RNA abundance. Nat Methods 11:549–551
Kulkarni RP, Che J, Dhar M, Carlo DD (2014) Research highlights: microfluidic single-cell analysis from nucleic acids to proteins to functions. Lab Chip 14:3663–3667
Levesque MJ, Raj A (2013) Single-chromosome transcriptional profiling reveals chromosomal gene expression regulation. Nat Methods 10:246–248
Lubeck E, Coskun AF, Zhiyentayev T, Ahmad M, Cai L (2014) Single-cell in situ RNA profiling by sequential hybridization. Nat Methods 11:360–361
Ludlow AT, Robin JD, Sayed M et al (2014) Quantitative telomerase enzyme activity determination using droplet digital PCR with single cell resolution. Nucleic Acids Res 42:e104–e104
Nagrath S, Sequist LV, Maheswaran S et al (2007) Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature 450:1235–1239
Pollen AA, Nowakowski TJ, Shuga J et al (2014) Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat Biotechnol 32:1053–1058
Ramakers C, Ruijter JM, Deprez RHL, Moorman AF (2003) Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neurosci Lett 339:62–66
Rival A, Jary D, Delattre C et al (2014) An EWOD-based microfluidic chip for single-cell isolation, mRNA purification and subsequent multiplex qPCR. Lab Chip 14:3739–3749
Schmittgen TD, Zakrajsek BA (2000) Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. J Biochem Biophys Methods 46:69–81
Ståhlberg A, Rusnakova V, Forootan A, Anderova M, Kubista M (2013) RT-qPCR work-flow for single-cell data analysis. Methods 59:80–88
Stott SL, Hsu CH, Tsukrov DI et al (2010) Isolation of circulating tumor cells using a microvortex-generating herringbone-chip. Proc Natl Acad Sci 107:18392–18397
Sun T, Morgan H (2010) Single-cell microfluidic impedance cytometry: a review. Microfluid Nanofluid 8(4):423–443
Sun H, Olsen T, Lin Q et al (2015) A bead-based microfluidic approach to integrated single-cell gene expression analysis by quantitative RT-PCR. RSC Adv 5:4886–4893
Taylor P (2013) Analytical and preparative instrumentation. J Biomol Screen 18:143–145
Thege FI, Lannin TB, Saha TN et al (2014) Microfluidic immunocapture of circulating pancreatic cells using parallel EpCAM and MUC1 capture: characterization, optimization and downstream analysis. Lab Chip 14:1775–1784
Toriello NM, Douglas ES, Thaitrong N et al (2008) Integrated microfluidic bioprocessor for single-cell gene expression analysis. Proc Natl Acad Sci 105:20173–20178
Volpatti LR, Yetisen AK (2014) Commercialization of microfluidic devices. Trends Biotechnol 32:347–350
Wang J, Fan HC, Behr B et al (2012) Genome-wide single-cell analysis of recombination activity and de novo mutation rates in human sperm. Cell 150:402–412
White AK, VanInsberghe M, Petriv I et al (2011) High-throughput microfluidic single-cell RT-qPCR. Proc Natl Acad Sci 108:13999–14004
Yin H, Marshall M (2012) Microfluidics for single-cell analysis. Curr Opin Biotechnol 23(1):110–119
Yu Z, Lu S, Huang Y, Yu Z, Lu S, Huang Y (2014) Microfluidic whole genome amplification device for single cell sequencing. Anal Chem 86:9386–9390
Zhang H, Jenkins G, Zou Y, Zhu J, Yang CJ (2012) Massively parallel single-molecule and single-cell emulsion reverse transcription polymerase chain reaction using agarose droplet microfluidics. Anal Chem 84:3599–3606
Acknowledgments
We gratefully acknowledge financial support from the National Institutes of Health (Award Nos. 5U19AI067773, 8R21GM104204 and 2P41EB002033-19A1). H.S. acknowledges a national scholarship award from the China Scholarship Council (Award No. 201206120110). We would also like to thank Dr. Laura Kaufman for granting access to an Olympus IX 71 fluorescent microscope.
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Sun, H., Olsen, T., Zhu, J. et al. A microfluidic approach to parallelized transcriptional profiling of single cells. Microfluid Nanofluid 19, 1429–1440 (2015). https://doi.org/10.1007/s10404-015-1657-2
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DOI: https://doi.org/10.1007/s10404-015-1657-2