Abstract
We present a microfluidic device for rapid gene expression profiling in single cells using multiplexed quantitative polymerase chain reaction (qPCR). This device integrates all processing steps, including cell isolation and lysis, complementary DNA synthesis, pre-amplification, sample splitting, and measurement in twenty separate qPCR reactions. Each of these steps is performed in parallel on up to 200 single cells per run. Experiments performed on dilutions of purified RNA establish assay linearity over a dynamic range of at least 104, a qPCR precision of 15%, and detection sensitivity down to a single cDNA molecule. We demonstrate the application of our device for rapid profiling of microRNA expression in single cells. Measurements performed on a panel of twenty miRNAs in two types of cells revealed clear cell-to-cell heterogeneity, with evidence of spontaneous differentiation manifested as distinct expression signatures. Highly multiplexed microfluidic RT-qPCR fills a gap in current capabilities for single-cell analysis, providing a rapid and cost-effective approach for profiling panels of marker genes, thereby complementing single-cell genomics methods that are best suited for global analysis and discovery. We expect this approach to enable new studies requiring fast, cost-effective, and precise measurements across hundreds of single cells.
Highlights
Single-cell analysis preserves a wealth of information that is lost when measurements are instead taken by averaging cells together
A key element of our design addresses this potential shortcoming with the inclusion of fluidics that allow for a low-cycle multiplexed pre-amplification step prior to simplex quantitative polymerase chain reaction (qPCR)
We have presented a microfluidic device for performing highly multiplexed quantitative PCR on hundreds of single cells
Summary
Single-cell analysis preserves a wealth of information that is lost when measurements are instead taken by averaging cells together. While the importance of maintaining this resolution is well appreciated, techniques with the requisite sensitivity and scalability for single-cell molecular analysis have only recently been available. Perhaps the most significant advancement in this field is the development of technologies for measuring the variations in and expression of nucleic acids, the main thrust of which has been measurements of mRNA expression levels. This rapid advancement of evermore powerful measurement technologies has, in turn, spurred the development of new single-cell analytics that meet the unique challenges associated with interpreting large single-cell data sets [1, 2].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
