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Single-Cell Analysis: Powerful Drops in the Bucket

If you’re curious what innovations are coming out of the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, take a look at this video shot via a microscope. What at first glance looks like water dripping through pipes is actually a cool new technology for swiftly and efficiently analyzing the gene activity of thousands of individual cells. You might have to watch this video several times and use the pause button to catch all of the steps, but it provides a quick overview of how the Drop-seq microfluidic device works.

First, a nanoliter-sized droplet of lysis buffer containing a bead with a barcoded sequencing primer on its surface slides downward through the straight channel at the top of the screen. At the same time, fluid containing individual cells flows through the curved channels on either side of the bead-bearing channel—you can catch a fleeting glimpse of a tiny cell in the left-hand channel about 5 seconds into the video. The two streams (barcoded-bead primers and cells) feed into a single channel where they mix, pass through an oil flow, and get pinched off into oily drops. Most are empty, but some contain a bead or a cell—and a few contain both. At the point where the channel takes a hard left, these drops travel over a series of bumps that cause the cell to rupture and release its messenger RNA—an indicator of what genes are active in the cell. The mRNAs are captured by the primer on the bead from which, after the drops are broken, they can be transcribed, amplified, and sequenced to produce STAMPS (single-cell transcriptomes attached to microparticles). Because each bead contains its own unique barcode that enables swift identification of the transcriptomes of individual cells, this process can be done simultaneously on thousands of cells in a single reaction.

Drop-seq and a similar droplet-based approach, called inDrop, were independently developed by two NIH-supported research teams. In papers published in the journal Cell, both teams say their technologies offer rapid, inexpensive, and precise ways to analyze the gene activity of thousands of individual cells derived from virtually any place in the body.

Why do scientists want to barcode the transcriptomes of thousands of individual cells like overnight packages? The simple answer is to enable them to sort through these vast heaps of data in a quick, efficient manner. Until now, researchers have mainly been limited to profiling the gene activity of tissues, which often contain many types and subtypes of cells that may vary greatly in gene activity. That becomes a real problem when you wish to study a structure as complex as the human brain. It consists of nearly 86 billion neurons, plus billions of other types of cells and trillions of connections!

The BRAIN Initiative, a bold, multi-agency effort led by NIH, will enable the development and use of innovative technologies to build a more dynamic, higher-resolution picture of the human brain. Ultimately, technologies developed through the BRAIN Initiative may improve our understanding of a vast array of brain disorders and provide new ways to treat, cure, and prevent conditions such as Alzheimer’s disease, Parkinson’s disease, epilepsy, autism, and schizophrenia. But an early challenge is to develop a much more complete census of the cell types that make up the brain.

Drop-seq, which was developed by Evan Macosko, Aviv Regev, Steven McCarroll, and their colleagues at Harvard Medical School, Boston, and the Broad Institute, Cambridge, MA, is one of the first potentially game-changing technologies to arise from BRAIN Initiative funding. In their paper, the researchers used their device to analyze the gene activity of more than 44,800 cells from the retina of a mouse’s eye—leading to the identification of 39 distinct subtypes of retinal cells, based upon their gene activity profiles [1]. This new development sets the stage for analyzing scores of cells beyond the eye, including within the much more complex circuitry of the brain. In fact, the Harvard team has already begun such work.

Macosko and McCarroll say their goal is to construct a global architecture of brain cells in an effort to gain a clear understanding of the gene activity involved in normal neurological development. They also plan to explore which cell populations are missing or malfunctioning in schizophrenia, autism, and other brain disorders, and then examine how various forms of physical and mental stress may lead to changes in the gene activity of these cells.

What makes the idea of carrying out such ambitious research projects feasible is Drop-seq’s relatively low cost and high speed. Using Drop-seq, it costs about 7 cents to analyze the gene activity of a single cell. What’s more, the process is so efficient, that just one scientist can analyze about 10,000 of these cells per day.

Another Harvard team, led by Allon Klein and Marc Kirschner, set out to tackle the same challenge of single-cell analysis in a generally similar, but somewhat different way. This group used its new technology, dubbed inDrop, to analyze thousands of differentiated and embryonic stem cells from mice [2]. Embryonic stem cells have the capacity to remain stem cells or to become any cell type in the body.

In contrast to Drop-seq, which has 16 million barcodes in its bead library, the inDrop method generated only about 150,000 unique barcodes, which means it can process fewer cells in a single run. However, inDrop may have the advantage when it comes to situations when researchers want to analyze very small samples of tissue—because it captures a greater percentage of cells than does Drop-seq, in which only a few thousand of the millions of oily drops it generates per hour contain both a bead and a cell.

Already, these new tools have revealed rare subtypes of cells never before described in detail. Clearly, the journey toward gaining a better understanding of the activity of individual cells and the inner workings of the human body has begun in earnest. It’s going to be an exciting ride.

References:

[1] Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, Tirosh I, Bialas AR, Kamitaki N, Martersteck EM, Trombetta JJ, Weitz DA, Sanes JR, Shalek AK, Regev A, McCarroll SA. Cell. 2015 May 21;161(5):1202-14.

[2] Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V, Peshkin L, Weitz DA, Kirschner MW. Cell. 2015 May 21;161(5):1187-201.

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Source: NIH Director’s Blog

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