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.
Take a plate of cultured cells and put them under a microscope. To all intents and purposes, they’ll look identical. Yet they aren’t. Whether at the level of DNA or RNA, proteins or metabolites, cells can vary widely in terms of molecular makeup—exhibiting differences that can have profound impact on cellular behavior, especially when considering not cells in a dish but tissues, tumors or the immune system.
For years, researchers have lacked the tools to interrogate those differences efficiently, but not anymore. Armed with next-generation DNA sequencers and mass spectrometers, researchers are probing cell-to-cell variability with ever-greater resolution, depth and throughput—particularly at the level of the single-cell transcriptome.
Approaches
Three approaches typically are used for single-cell isolation. One is fluorescence-activated cell sorting (FACS), in which cells are interrogated one by one for specific fluorescent markers as they pass a bank of lasers. Cells that meet some predetermined metric are captured, one cell to a well, and the rest are discarded.
According to Robert Balderas, vice president of biological sciences at BD Biosciences, FACS enables a level of control in single-cell isolation unmatched by other methods, thanks to the fine resolution afforded by multiplexing different colors.
“Flow is a binary method,” he explains. “If there are two colors and two antibodies, there are four possibilities; for 20 colors, it’s 2.2 million combinations.”
In one recent example. Levi Garraway of the Broad Institute of MIT and Harvard, and colleagues, used a simple scheme based on CD45 expression and cell viability to isolate and probe the transcriptomes of 4,645 tumor, immune and stromal cells from human melanomas [3].
BD Biosciences’ newest instrument, the BD FACSymphony A5 cell analyzer, offers 50-channel resolution—48 colors plus forward and side scatter, for 1.1 trillion theoretical combinations. Already, says Balderas, researchers can use that platform to realistically differentiate 30 channels, and 40 color panels should be feasible soon. A similarly outfitted sorter, Balderas says, “is being worked on.”
Another approach to cell isolation is micromanipulation—capturing cells one at a time using a micropipette. Although this can be an effective process (performed manually or via automated system), it still is a tedious procedure.
And the final option is microfluidics, in which cells are captured and manipulated within the confines of microscale fluidic chambers and channels.
When used with Fluidigm’s newest Single-Cell mRNA Seq HT chip, for instance, the Fluidigm C1™ enables capture, RNA isolation and cDNA synthesis from up to 800 cells in parallel. The company’s Polaris™ system incorporates the ability to capture, culture, stimulate and prepare samples from up to 48 cells in parallel, “thereby enabling researchers to explore the functional role of individual cells by directly correlating gene expression with environmental conditions and phenotypic information,” explains Michaeline Bunting, senior director of marketing at Fluidigm.
New microfluidic designs also are regularly reported in the literature. In January, for instance, Scott Manalis of Massachusetts Institute of Technology, and colleagues described a microfluidic “hydrodynamic trap array” capable of capturing and culturing cells; transcriptional changes are then probed and compared across generations as immune cells grow and divide [1].
After cells are isolated, researchers have a number of tools they can use to quantify gene-expression programs. Perhaps the most popular these days is single-cell RNA-seq, or its new variant, single-nucleus RNA-seq, in which single nuclei are isolated and sequenced [2].
Further analysis
10X Genomics recently described one particularly high-throughput variant of the RNA-seq approach in BioRxiv, a biology preprint archive. The company reported “a droplet-based system”—based on its GemCode® technology—“that enables 3’ mRNA counting of up to tens of thousands of single cells per sample,” and applied this approach to thousands of both blood and bone marrow-derived cells [4]. In one example, the company profiled 68,000 peripheral blood mononuclear cells and binned them based upon their transcriptional signatures, detecting all the expected cellular classes (e.g., T cells, B cells, natural killer cells and so on) in their anticipated abundances.
Another popular option is single-cell qPCR.
Or researchers can use RNA-in situ hybridization (ISH) and related methods. According to Rob Monroe, chief medical officer at Advanced Cell Diagnostics (ACD), RNA ISH is particularly useful as a validation to RNA-seq and PCR-based expression analyses, because what it lacks in throughput it gains in spatial detail.
RNA ISH “doesn’t have the throughput or multiplexing ability of next-gen sequencing,” Monroe says. “But what you gain from it is equally important: … the ability to see the expression of the RNA in the tissue context, in the morphological context of the cell and its surrounding tissues.”
ACD’s RNAscope technology provides one implementation of RNA ISH. Hybridization of two adjacent “Z-probes” side by side on a given transcript provides a scaffold for the assembly of a highly branched tree of detection probes, Monroe explains, which provides a substantial signal boost. A single binding event, he says, can scaffold as many as 400 label probe molecules, thereby providing 400-fold signal amplification.
According to Monroe, the system can be used to query two unique RNA targets simultaneously when using chromogenic reagents, or three targets with fluorescent reagents.
At Harvard University, Xiaowei Zhuang has extended RNA ISH to 1,000 transcripts per cell, if not more. Called MERFISH (multiplexed error-robust fluorescence in situ hybridization), Zhuang’s method works by effectively assigning each transcript a unique, 16-digit barcode—complete with built-in error checking—which is then read out in a series of hybridization, imaging and quenching steps [4].
In a 2014 commentary entitled “The Promise of Single-Cell Sequencing,” University of Pennsylvania researcher Jim Eberwine and colleagues wrote, “Although there is tremendous excitement about single-cell sequencing, it is still not a routine experimental procedure. Improvements in the basic technology as well as in data analysis and interpretation will be important for obtaining the precision of measurement and large sample sizes needed to understand the role of individual cells in their system-level function” [5].
The same could be said for other single-cell methods, as well. As more and more of those improvements are documented in the literature, expect to see ever more researchers making the leap to single-cell methodologies. And when they do, the biological complexity hidden within seemingly homogeneous cultures will finally come fully into focus.
References
[1] Kimmerling, RJ, et al., “A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages,” Nature Communications, 7:10220, 2016. [PMID: 26732280]
[2] Krishnaswami, SR, et al., “Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons,” Nature Protocols, 11(3):499-524, 2016. [PMID: 26890679]
[3] Tirosh, I, et al., “Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq,” Science, 352(6282):189-96, 2016. [PMID: 27124452]
[4] Chen, KH, et al., “RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells,” Science, 348(6233):aaa6090, 2015. [PMID: 25858977]
[5] Eberwine, J, et al., “The promise of single-cell sequencing,” Nature Methods, 11(1):25-7, 2014. [PMID: 24524134]
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