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UBC Team with Fluidigm Link Develops High-Throughput Single-Cell RT-qPCR Device

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By Ben Butkus

University of British Columbia researchers have developed a fully integrated microfluidic device for performing reverse transcription quantitative PCR and measuring single-cell gene expression in hundreds of cells in parallel, according to a study published this week.

The invention is expected to enable scientists to measure mRNA and miRNA expression in single cells at a much higher throughput and lower cost than currently available technologies, and may eventually be useful as a diagnostic tool for heterogeneous cell populations such as tumors, Carl Hansen, a UBC professor and corresponding author on the study, told PCR Insider.

In addition, the technology may have a commercial route through Fluidigm, according to Hansen, who is a longstanding member of the company's scientific advisory board and whose lab last month unveiled a high-density, chip-based digital PCR device that Fluidigm has licensed (PCR Insider 7/14/11).

Hansen said this week that his group is "very keen" to commercialize the new high-throughput, single-cell RT-qPCR device, and that "again [Fluidigm] is our preferred partner, and we're … working with them to license it … but there needs to be a final agreement of terms, which should be pretty quick."

Hansen, who had a hand in developing some of the microfluidic technologies currently found in Fluidigm's commercial products, added that the new technology "leverages the Fluidigm valve technology pretty heavily, so they are a natural fit for this. It also fits right into their interests."

In an e-mail to PCR Insider, Fluidigm spokesperson Howard High confirmed that the company is "working with Carl on a number of projects. This is one of the projects."

High also noted that more than half of the sales of the company's BioMark HD system in Q1 were targeted at single-cell genomics work and the company currently has five single-cell protocols for use with the platform.

However, as a matter of company policy High declined to provide details on a potential licensing agreement with UBC or commercial product based on the new single-cell analysis technology.

Hansen and colleagues at UBC described the microfluidic single-cell expression analysis device and several experiments demonstrating its utility in a paper published online this week in the Proceedings of the National Academy of Sciences.

As described in the paper, the prototype device consists of six independent sample-loading lanes, each containing 50 cell-processing units and reaction chambers, providing a total of 300 RT-qPCR reactions using about 20 µL of reagents.

In order to reduce device complexity and eliminate the need for RNA purification, the researchers optimized their device to be compatible with commercially available PCR protocols that require only the sequential addition of reagents into a single reaction vessel. As such, each 0.6-nL cell-capture chamber features an integrated cell trap to capture cells passing through the loading lane; as well as a 10-nL reverse transcription chamber and a 50-nL PCR chamber.

The scientists also aimed to reduce cost and complexity by using peripheral hardware such as a CCD detector for fluorescence detection and a flatbed thermocycler plate for temperature control.

To test the sensitivity of their device, the researchers measured GAPDH expression over a serial dilution of total RNA purified from K562 cells — a BCR-ABL-positive human cell line derived from a patient with chronic myeloid leukemia — and found that it afforded higher sensitivity than tube-based qPCR using the same serial dilutions.

They also evaluated the efficiency and reliability of cell processing on the chip by comparing their GAPDH measurements of purified RNA to measurements performed directly from single K562 cells, and found that on-chip single-cell lysis and mRNA extraction was equal to yields of RNA purified from large numbers of cells.

Then, to demonstrate the robustness and throughput of the technology, Hansen and colleagues successfully assayed 1,672 single K562 cells for single-cell variability in the expression of nine miRNAs spanning a wide range of abundance, including one, miR16, that is known to be consistently expressed over many cell types; and also measured a high degree of expression variability of a single miRNA, miR-223, which is implicated in myeloid differentiation.

Finally, the researchers used multiplexed measurements of mRNA single nucleotide variants to assess the genomic heterogeneity of a primary tumor sample by using 117 single cells isolated from a metastatic breast cancer. Specifically, they examined the expression of a single-nucleotide variant mutant of the transcription factor SP1, previously identified by deep sequencing.

The observed frequencies of mutant and wild-type alleles suggested a mutant-to-wild-type SP1 ratio of 11.2 percent – not completely in agreement with subsequent digital PCR analysis, which yielded a ratio of 18.7 percent; or a previously reported ratio of 21.9 percent obtained with deep sequencing. The researchers noted that the lower frequency of mutant cells observed with single-cell analysis may have been due to allelic expression bias or an amplification of the SP1 mutant allele; and concluded that this experiment more importantly showed that the metastasis of the tumor was a result of multiple cancer cell lineages.

Overall, the researchers noted that their device was able to perform 300 high-precision single-cell RT-qPCR measurements per run, surpassing the throughput of previous microfluidic systems about 100-fold. The device also demonstrated a dynamic range of at least 104, measurement precision of better than 10 percent, single-molecule sensitivity, and specificity capable of discriminating the relative abundance of alleles differing by a single nucleotide.

"Where I see this having an immediate impact for research is to [enable] the analysis of large numbers of cells — hundreds or thousands, even," Hansen told PCR Insider. "Currently the prototype is set up to do one gene, but we can envision quite easily … being able to do tens of genes, so you can imagine a device where in an afternoon you're able to get a few hundred single-cell measurements [of] 10 genes, and do that for very low cost, and do it reliably."

In fact, cost is one of the main drivers for development of the device, Hansen said. The researchers claimed in their paper that the nanoliter-scale volumes used result in a 1,000-fold reduction in reagent consumption as compared to tube-based single-cell RT-qPCR.

"In the near term, it will make it much more accessible for a lot of people to implement single-cell analysis in their research," Hansen said. "And I think one of the strengths is that it is … really amenable to automation. You can imagine setting up a single-cell RT-qPCR instrument where you put the sample in, and everything is turnkey, and you just get results at the end."

Lastly, much farther down the road, the research group envisions their device setting the stage for performing diagnostic tests based on single-cell analysis.

"This is not proven, and we need to do the application development — but because we can automate it; it's sensitive; and we are confident in the results, we can envision using this as a diagnostic test," Hansen said. "Imagine looking at a cancer sample and making measurements of single-cell gene expression as a diagnostic."

The technological hurdles to this are fairly straightforward and relatively minimal, Hansen added. "I think technologically the version of the device that we reported could actually do this. I think the reason it's forward looking is: What exactly are you going to be looking for? How are you going to find the biomarkers? What diseases will it work for? And what will be the issues with sample prep and other things?

"Any type of single-cell analysis will have issues around how you go from a sample to a suspension of single cells," Hansen added. "In solid tumors, that's a tricky problem. In other cases it's easier."


Have topics you'd like to see covered in PCR Insider? Contact the editor at bbutkus [at] genomeweb [.] com.

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