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Accurate and reliable single cell gene expression analysis using microfluidic PCR
· Achieve more accurate detection of single cell gene expression profile differences
· Avoid the disadvantages of measuring the average of all cells in a sample
· Identification of previously unresolved cell subpopulations and decomposition of new regulatory networks
In a nominally uniform cell population, single cells differ in size, protein level, and mRNA expression transcription, so by default each cell in your sample behaves exactly as a dangerous gamble, and the measurements are grouped together. The average of multiple cells would mask significant differences in gene expression between cells. Identifying cell-to-cell differences in seemingly uniform cell populations is critical to promoting stem cell research, understanding cancer cells, identifying immune responses, studying the effectiveness of biological therapy, and discovering the mechanisms of degenerative neurological diseases.
Geneticists and clinicians have been searching for a complete set of experimental procedures to detect single cells, group them according to their unique genome and transcriptome, while minimizing the noise of the technology.
Based on microfluidics, Fluidigm has developed a new single-cell gene expression assay that allows you to quickly and reliably separate, process, and analyze the genome of a single cell. Our family of instruments, chips, reagents, software, and kits, designed with Fluidigm, can help you perform cell separation, reverse transcription, and preamplification with a single technology. A series of experimental procedures such as monitoring and analyzing cellular activities.
The Fluidigm single-cell process can test the expression of hundreds of genes in hundreds of single cells in a matter of hours, and this experiment typically takes several days with conventional systems. It offers a simple process and a flexible reagent combination. With automated processes, ready-to-use reagents, and optimized chips, you can eliminate the burden of loading and sample mixing to achieve the productivity of “loading and movingâ€.
Fluidigm's microfluidic chip structure automates the mixing of samples and reagents, primer probes and creates thousands of PCR reactions using significantly smaller reagents than traditional systems. Each microfluidic chip can generate an equivalent of 24 standard 384-well plate data volumes.
The new Fluidigm single-cell approach opens new avenues for studying cell differentiation, measuring single cell response to specific stimuli, confirming important disease biomarkers, validating RNA interference silencing gene expression, and implementing drug candidate screening.
The process technology platform Fluidigm C1 automated preparative single cell system and the new PCR BioMark â„¢ HD microfluidic analysis system has been widely used in the expression of genes in a single cell.
C1 TM single cell automatic preparation system
96 single cells can be isolated and separated in 1 hour
BIOMARKTM HD System
9,216 qPCR reactions in 30 minutes
C1 automatic preparation system combines single cell BioMark â„¢ HD system effectively continuously optimized gene expression analysis, analysis support 96 up to 96 transcripts of a single cell. Significantly improved efficiency and further accelerated the study of single-cell gene expression profiles.
The entire process allows you to easily implement the following steps:
· Capture- group cells can be quickly separated into 96 separate reaction chambers in one step.
· Confirmation - QC node confirms the number of captured cells and distinguishes between live and dead cells
· Lysis - rapid and direct cell lysis method saves time and expense and does not require RNA purification steps
· Pre-amplification and reverse transcription - cDNA synthesis and amplification of specific fragment in a sample and does not require transfer of sample and reagent mixing
· Harvest - All amplification products were together, and to collect and transfer to the BioMark ™ HD system for real-time PCR analysis
· Transfer - C1 on the system diluted pre-amplification product was loaded onto a dynamic chip IFC
· Quantitative PCR - Place the dynamic chip IFC on the BioMarkTM HD system for PCR reactions and data acquisition, etc.
· Analysis - User-friendly interface software package for real-time viewing of amplification curves, acquisition of color heat maps and Ct data, etc.
Latest articles published using the platform
· Narayanan G, Poonepalli A, Chen J, Sankaran S, Hariharan S, Yu YH, Robson P, Yang H, Ahmed S. July 26, 2012. Single-cell mRNA profling identifies progenitor subclasses in neurospheres. Stem Cells and Development
· Surmacz, B., Fox, H., Gutteridge, A., Lubitz, S. Whiting, P. June 5, 2012. Directing Differentiation of Human Embryonic Stem Cells towards Anterior Neural Ectoderm Using Small Molecules. Stem Cells
· Jeffrey, SS, Powell, AA et al . May 7, 2012. Single Cell Profiling of Circulating Tumor Cells: Transcriptional Heterogeneity and Diversity from Breast Cancer Cell Lines . PLoS one
· Sanchez-Freire, Ebert, AD, Kalisky, T., Quake, SR, Wu, JC April 5, 2012. Microfluidic single-cell real-time PCR for comparative analysis of gene expression traits . Nature Protocols
· Luc, S., Jacobsen, SEW, et al. February 19, 2012. The earliest thymic T cell progenitors sustain B cell and myloid lineage potential. Nature Immunology
· Pina, C., Fugazza, C., Tipping, AJ, Brown, J., Soneji, S., Teles, J., Peterson, C., Enver, T. February 19, 2012. Inferring rules of lineage commitment in Haematopoiesis . Nature Cell Biology
· Spike, BT, Engle, DD, Lin, JC, Cheung, SK, La, J., Wahl, GM February 2, 2012. A Mammary Stem Cell Population Identified and Characterized in Late Embryogenesis Reveals Similarities to Human Breast Cancer. Cell Stem Cell
· Oyolu, C., Zakharia, F., Baker, J. December 20, 2011. Distinguishing Human Cell Types Based on Housekeeping Gene Signatures. Stem Cells
· Vincent, JJ, Ziwei Li, Z., Lee, SA, Liu, X., Etter, MO, Diaz-Perez, SV, Taylor, SK, Sofia Gkountela, S., Lindgren, AG, Clark, AT December 15, 2011. Single Cell Analysis Facilitates Staging of Blimp1-Dependent Primordial Germ Cells Derived from Mouse Embryonic Stem Cells . PLoS ONE
· Citri, A., Pang, ZP , Südhof, TC, Wernig, M., Malenka, RC December 22, 2011. Comprehensive qPCR profiling of gene expression in single neuronal cells. Nature Protocols
Virant-Klun, I., Skutella, T., Stimpfel, M., Sinkovec, J. December 6, 2011. Ovarian surface epithelium in patients with severe ovarian infertility: a potential source of cells expressing markers of pluripotent/multipotent stem cells . Journal of Biomedicine and Biotechnology
· Yin, H., Marshall, D. November 29, 2011. Microfluidics for single cell analysis. Current Opinion in Biotechnology
· Dalerba, P., Kalisky, T., Sahoo, D., Rajendran, PS, Rothenber, ME, Leyrat, A., Sim, S., Okamoto, J., Johnston, DM, Qian, D., Zabala, M., Bueno, J., Neff, NF, Wang, J., Shelton, AA, Visser, B., Hisamori, S., Shimono, Y., van de Wetering, M., Clevers, H., Clarke, MF, Quake, SR November 13, 2011. Single-cell dissection of transcriptional heterogeneity in human colon tumors. Nature Biotechnology
· Vadigepalli R, Gonye GE, Paton JF, Schwaber JS. October 14, 2011. Adaptive transcriptional dynamics of A2 neurons and central cardiovascular control pathways. Experimental Physiology
· Brevik, A., Rusnakova, V., Duale, N., Slagsvold, HH, Olsen, AK, Storeng, R., Kubista, M., Brunborg, G., Lindeman, B. September 29, 2011. Preconceptional paternal Glycidamide exposure affects embryonic gene expression: Single embryo gene expression study following in vitro fertilization. Reproductive Toxicology
· Marro, S., Pang, ZP, Yang, N., Tsai, MC, Qu, K., Chang, HY, Su ̈ dhof, TC, Wernig, M. September 29, 2011. Direct Lineage Conversion of Terminally Differentiated Hepatocytes To Functional Neurons. Cell Stem Cell
· Kikushige, Y., Ishikawa, F., Miyamoto, T., Shima, T., Urata, S., Yoshimoto, G., Mori, Y., Iino, T., Yamauchi, T., Eto, T. , Niiro, H., Iwasaki, H., Takenaka, K., Akashi, K. August 16, 2011. Self-Renewing Hematopoietic Stem Cell is the Primary Target in Pathogenesis of Human Chronic Lymphocytic Leukemia. Cancer Cell
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