Analysis of single cells is appealing to researchers since the approach can provide deeper insight than cell population studies can into the molecular mechanisms underlying genetic changes. The applications for robust single-cell analysis are broad: the technique could enhance ultra high–throughput DNA sequencing and polymorphism characterization, improve forensic analysis and health care diagnostics, detect the presence of rare mutants within a circulating population for clinical diagnosis (such as early detection of chromosomal mutations leading to leukemia or lymphoma), and could even monitor for the presence of very small quantities of microbial pathogens in food. While the appeal of the approach is obvious, applications have been limited since the technology requires extreme precision, sensitivity, and accuracy for detection, not to mention a way to initially screen through several millions of cells.
Now, Richard Mathies’ group at the University of California, Berkeley (UC Berkeley) has developed a PCR-based tool for high-throughput single-cell analysis: microfabricated emulsion generator arrays (MEGAs). This device uses microfluidic technology to undertake massively parallel PCR amplification of DNA from single cells, providing accurate detection and quantification of rare mutants within a population (1). The use of small water droplets in oil to amplify single molecules is known as emulsion PCR; its power comes from the ability to miniaturize reactions into droplets and from using primer-coupled beads (2,3). In this way, all PCR products are the same (or clonal) and physically attached to the bead for easy retrieval.
“The reason we wanted to build this microfabricated device was to produce very uniform [small] droplets for PCR,” Yong Zeng, a postdoc in Mathies’ lab, told BioTechniques. Zeng is first author on a new study in Analytical Chemistry that describes this technology. “Conventionally, people use mechanical agitation to get PCR droplets.”
Mechanical agitation produces droplets that are poorly dispersed and not uniform, characteristics that affect reaction efficiency and limit quantitative measurements. By using a compact ring-shaped micropump, the group was able to sufficiently agitate their 4-nL PCR droplets to overcome the inherent limitations of traditional emulsion PCR. “[Obtaining] uniform droplets enables us to perform accurate statistical analysis and digital quantification of single cells,” said Zeng.
Zeng and colleagues built a 4-inch wafer containing 4-, 32,- or 96-channel droplet generators to analyze a large number of single-cell samples. Individual microbeads—conjugated with forward primers for specific target genes—were encapsulated with single cells into PCR reaction droplets containing reverse primers, each labeled with a unique fluorescent dye tag. After PCR amplification, the PCR products from the beads were recovered and rapidly sorted by flow cytometry. The number of fluorescent dyes that can be used is limited primarily by the flow cytometer, which commonly possesses only a five-color laser. This system differs from others because the beads are larger than the more commonly used small beads in similar techniques, allowing one to detect multiple pathogenic microorganisms in a single sample.
As a proof-of-principle experiment, the researchers mixed both normal Escherichia coli cells with a small amount of the bacterial foodborne pathogen O157 and used their device to identify the pathogen frequency in a mixture containing predominantly normal cells. The 96-channel droplet generator has a total throughput of 2.4 million PCR droplets per hour, allowing the entire procedure—from PCR thermal cycling to analysis by flow cytometry—to be completed in about four hours, which is more than 12 times faster than typical methods with similar sensitivity (4). In addition, the detection limit of this MEGA device was at least ten times higher compared to most PCR-based microdevices.
“We’re currently in the process of analyzing very early cancer biomarkers, specifically looking at lymphoma,” said Richard Novak, UC Berkeley bioengineering graduate student and co-author on the paper. “The goal is to look at environmental exposure to potential carcinogens or different chemicals/environmental compounds and see how they affect the genome in healthy people,” he said, in order to identify the presence of biomarkers that can predict early onset of lymphoma.
This analysis must be done at the single-cell level because it provides the sensitivity and the throughput needed to look at variable frequency mutations. According to Novak, healthy people have on the order of 1 in a 100,000 mutations before some chromosomal rearrangements or translocations occur; therefore, having a sensitivity of 1 in a 100,000 or greater is required to pick them up.
The lab is also currently using the approach to look at differences in gene expression at the single-cell level as well as integrating the technology into ‘lab-on-a-chip’ microanalysis systems, portable clinical health care monitors, and even miniaturized biochemical devices that can be sent to planets to look for signs of extraterrestrial life.
Although their microfabricated emulsion generator arrays are far from being commercialized, Zeng suspects that there is the potential to streamline its operation so every biological lab can use these devices for single-cell analysis. “I like working on single cells or single molecules, and believe that this is a revolutionary platform for quantitative biology.”
References
1. Zeng, Y., R. Novak, J. Shuga, M.T. Smith, and R.A. Mathies. 2010.
High-performance single cell genetic analysis using microfluidic emulsion
generator arrays. Anal Chem. 82:3183–3190.
2. Nakano, M., J. Komatsu, S. Matsuura, K. Takashima, S. Katsura, and A.
Mizuno. 2003. Single-molecule PCR using water-in-oil emulsion. J Biotechnol 102:117–124.
3. Dressman, D., H. Yan, G. Traverso, K.W. Kinzler, and B. Vogelstein. 2003.
Transforming single DNA molecules into fluorescent magnetic particles for
detection and enumeration of genetic variations. Proc Natl Acad Sci USA 100:8817–8822.
4. Batt, C.A. 2007. Materials science. Food pathogen detection. Science 316:1579–1580.
