Jeffrey Perkel has been a scientific writer and editor since 2000. He holds a PhD in Cell and Molecular Biology from the University of Pennsylvania, and did postdoctoral work at the University of Pennsylvania and at Harvard Medical School.
Most cell biologists study cells in bulk, as in¬¬ cells, plural. Now, though, a small but growing group of researchers is bucking that trend and has taken up the challenge of single-cell biology.
As explained in a Nature Methods’ editorial naming single-cell sequencing as the 2013 Method of the Year, “Every cell is unique—it occupies an exclusive position in space, carries distinct errors in its copied genome and is subject to programmed and induced changes in gene expression. Yet most DNA and RNA sequencing is performed on tissue samples or cell populations, in which biological differences between cells can be obscured by averaging or mistaken for technical noise. Single-cell methods offer a way to dissect this heterogeneity” [1].
They also pose numerous technical challenges, says Cynthia Potter, global product manager for genomics at GE Healthcare Life Sciences. Improper sample handling, incomplete cell lysis, nucleic acid secondary structure or high GC content, residual histones—these factors and more can adversely impact the outcome of single-cell analyses.
That’s because single-cell biology involves, well, single cells. “The RNA, DNA and proteins in each cell in a tumor or tissue [are] incredibly variable, heterogeneous,” Potter says. “To capture that heterogeneity, you have to get the whole thing”—that is, the entire genome, transcriptome, proteome or metabolome. “And that’s where the challenge comes in: You don’t have that [cellular] redundancy,” states Potter.
Still, more and more researchers are trying. And they have a large and growing toolbox to help them out.
Working with single cells
Researchers have several options when it comes to single-cell isolation: physical micromanipulation, laser capture microdissection, flow cytometry and microfluidics.
For instance, researchers can sort individual cells directly into a single tube or well containing lysis buffer, using anything from the simple and automated S3e Cell Sorter from Bio-Rad Laboratories, which is pre-configured to sort into 8-well tube strips—to Beckman Coulter’s MoFlo Astrios EQ, which is capable of sorting individual cells into 1,536-well plates.
Of course, care is required to ensure each cell actually ends up in a well. Melissa Ma, global product manager at Bio-Rad Laboratories' Cell Biology Group, estimates the volume of a single, sorted droplet on the S3e measures just 3 nl. “Sometimes a cell can be lost if the sorter is not set up properly. The S3e offers ProDropTM Technology to ensure accurate sorting and maximizes recovery of the sorted individual cells,” she says.
The Fluidigm C1 represents a complementary approach to cell sorting, says Candia Brown, the company’s director of marketing for single-cell biology products. Researchers can use the C1—an automated microfluidics platform that deposits single cells into individual reaction chambers on a dedicated “integrated fluidic chip” (IFC) device for cell staining, visualization, lysis and amplification—on its own. But it also can be used downstream of FACS, Brown says, with the sorter used to isolate a specific cell subpopulation and the C1 used to bin those cells in discrete wells.
As Brown explains, the C1 was developed to facilitate the process of ramping single-cell analysis up to large numbers of cells. Previously, she says, cell-isolation and processing steps were “very laborious,” with researchers “cobbling together multiple different technologies” to drive their workflows. As a result, throughput was low, and so was reproducibility. “The C1 changes that game,” she says. “By integrating and standardizing [work onto a single platform], it makes the process reproducible and scalable.” Indeed, the C1 originally could handle 96 separate cells per IFC; today, that has increased to 800. With a workflow that processes two plates at a time, “you can process up to 1,600 cells in a day.”
Fluidigm also plans shortly to release a new instrumentation platform for single-cell functional genomics, Brown says. Announced in January and set to launch “in the next few weeks,” the Fluidigm Polaris system will enable researchers to test single cells under as many as 48 different environmental conditions—for instance, to test the gene expression impact of six drug doses on each of eight biological replicates.
Now what?
After you’ve obtained single cells, you need to figure out what their macromolecular content is.
One oft-required step is nucleic acid amplification. According to Potter, single human cells have about 6 picograms of DNA, far too little for next-generation DNA sequencing, variant analysis and other types of downstream work. So, most researchers amplify that material using some form of whole-genome amplification (WGA). “That’s especially important for single cells,” she says, “because you cannot get another cell—all the cells are different.”
Because single-cell studies consider each cell in isolation—that is, without averaging across populations—error rates and sequence coverage are particularly important considerations in selecting a WGA strategy. (See, for example, reference [2].) GE Healthcare Life Sciences’ illustra Single Cell GenomiPhi DNA Amplification Kit, for instance, uses the high-fidelity Phi29 DNA polymerase in an “isothermal multiple strand displacement” reaction to produce between 4 and 7 mg of DNA from single cells, Potter says.
For many researchers, NGS is the ultimate goal of single-cell workflows, whether exploring the genome or the transcriptome. Fluidigm now supports seven downstream NGS applications on its C1 system, according to Brown: targeted gene-expression analysis, microRNA profiling, single-cell mRNA sequencing, targeted DNA sequencing, whole-exome sequencing, whole-genome sequencing and an epigenetics workflow called ATAC-seq.
Probing cellular heterogeneity
But for those who need to quantify just a few transcripts, there are simpler alternatives, says Elaine Wong-Ho, senior product manager at Bio-Rad’s Digital Biology Center. Digital PCR, for instance, offers far lower transcript throughput than NGS but is also less expensive, faster and far easier to analyze. “Most biologists can do that analysis without computational help,” she says.
For instance, cells isolated on Bio-Rad’s S3e Cell Sorter can be deposited directly into lysis buffer made with the SingleShot Cell Lysis Kit and funneled into the company’s Droplet Digital™ PCR (ddPCR) workflow, Wong-Ho says. As each lysate provides enough material for two reactions, and each reaction can probe up to five transcripts, researchers can accurately quantify up to 10 mRNAs per cell with as few as 10 copies apiece.
There are other ways to probe cellular heterogeneity, as well. Flow cytometry is essentially a single-cell analysis platform, albeit one that focuses largely on cell surface protein expression. Or, for a broader view of the single-cell proteome, researchers can use Fluidigm’s Helios™ mass cytometer, which uses a mass spectrometer to quantify heavy metal-conjugated antibodies as cells flow individually into the mass analyzer, to quantify as many as 40 proteins per cell.
Researchers also can use the Amnis imaging flow cytometers from EMD Millipore (which have no sorting capabilities) to correlate cell morphology, protein localization and RNA expression using fluorescence in situ hybridization, says product manager Sherree Friend.
For the researchers that embrace them, such tools can reveal a sliver of the cellular heterogeneity that makes single-cell studies necessary in the first place. As more and more such tools make it to market, and as the methods for working with individual cells get ever easier, expect the interest in single-cell studies to increase. After all, the heterogeneity of cell populations isn’t going away.
References
[1] “Method of the Year 2013,” Nature Methods, 11:1, January 2014.
[2] Fu, Y, et al., “Uniform and accurate single-cell sequencing based on emulsion whole-genome amplification,” Proc Natl Acad Sci, doi:10.1073/pnas.1513988112, 2015. [PubMed ID: 26340991]
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