MicroRNAs can affect individual cells’ epigenetic modifications in a variety of biological processes such as cell cycle regulation, apoptosis, cell differentiation and maintenance of stemness. These modifications can be largely heterogeneous depending on the internal and external factors. However, traditional tube- based qPCR or microarray system is lack of sensitivity and requires intensive labor and time input. Current integrated single- cell miRNA detection platforms are lack of the capacity of handling thousands of cells at the same time for statistical meaningful data acquisition. Here, we established a high throughput single-cell miRNA quantification method based on microfluidic flow cell technology and novel n2 amplification in replacement of PCR. The advantages of this method are: • Single-cell addressability: Reliable single-cell trapping and miRNA capturing within isolated microchambers ensures clearly readable signals from single cells. • Higher throughput: process more than 5000 single cells’ target miRNA level in one operation. • More precise and faster quantification than PCR: Instead of real-time PCR, we developed an n2 isothermal amplification method that enables precise quantification of miRNA using snapshots of single-time-point signals within 35mins. • Fast and easy cell-to-signal results: By using a picoliter-reactor array in flow cell format, whole process of sample preparation is easily completed by capillary flow within 15 mins. The cell- to-signal process takes less than 1 hour. • Good flexibility: Time dependent perfusion and stimulation of captured single-cells is available on the spot of analysis; protein and miRNA correlation study is available within one set of experiment by combining with protein detection. This method is promising in the use of fast screening of miRNA candidates. We have quantified heterogeneous distribution of single- cell miRNAs in human breast cancer cell line MCF-7 and its doxorubicin- resistant population. The results showed miRNA sub- populations and their changes upon drug treatment. Furthermore, we detected the correlation between miRNAs and the transcription factor NANOG in genetically modified mouse embryonic stem cells (mESCs). The result indicated that several miRNAs may contributes to the heterogeneous distribution of NANOG among mESCs as downstream regulators of NANOG.
Project end date: 08/26/15