By Ben Butkus

Stanford University researchers have published a method for using Fluidigm's digital PCR platform to conduct single-cell, real-time PCR to compare gene expression patterns of single cells.

The protocol is indicative of the increased use of Fluidigm's products for single-cell biology, an application area that the company has been heavily promoting over the past year.

In addition, the method may provide a powerful tool for understanding gene expression and differentiation in induced pluripotent stem cells and human embryonic stem cells for regenerative medicine, the researchers said.

In a paper published last week in Nature Protocols, researchers led by Joseph Wu, associate professor of medicine, cardiology, and radiology at Stanford University School of Medicine, described how they used Fluidigm's BioMark HD platform and Dynamic Array chips to analyze gene expression profiles of single iPSCs or hESCs approximately 11 hours after collection.

The team decided to publish the method after using it to conduct a study published last March in the Journal of Clinical Investigation that demonstrated how single-cell transcriptional profiling revealed heterogeneity in human iPSCs. "A lot of people asked us after that JCI paper how we exactly do this, so we decided to write a detailed protocol," Wu told PCR Insider.

Wu and colleagues began using Fluidigm's platform through the laboratory of fellow Stanford scientist Stephen Quake, a co-founder of the company and a co-author on the recent Nature Protocols paper.

According to Veronica Sanchez-Freire, a postdoc in Wu's lab and also a co-author on the paper, the group needed a tool to compare gene expression between individual cells in single colonies of iPSCs or hESCs with high sensitivity using a limiting amount of sample.

"We were interested in seeing how different gene expression could be in the cell depending on its position in the colony," Sanchez-Freire said. "We are looking at these iPS cells from different cell types and donors, and we always compare them to [human embryonic] stem cells, the gold standard but we also wanted to see how similar they are [to each other]."

Most traditional gene expression studies, using, for example, quantitative real-time PCR, extract RNA from a large population of cells for downstream expression analysis. "And we saw that when you do that, iPS cells and stem cells are very similar," Sanchez-Freire said. "But when you go to the single-cell level, we saw how the iPS cells are more heterogeneous than the ES cells."

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Stanford Group Publishes Fluidigm-Based Method for Gene Expression Profiling of Single Stem Cells