These colorful lights might look like a video vignette from one of the spectacular evening light shows taking place this holiday season. But they actually aren’t. These lights are illuminating the way to a much fuller understanding of the mammalian brain.
The video features a new research method called BARseq (Barcoded Anatomy Resolved by Sequencing). Created by a team of NIH-funded researchers led by Anthony Zador, Cold Spring Harbor Laboratory, NY, BARseq enables scientists to map in a matter of weeks the location of thousands of neurons in the mouse brain with greater precision than has ever been possible before.
How does it work? With BARseq, researchers generate uniquely identifying RNA barcodes and then tag one to each individual neuron within brain tissue. As reported recently in the journal Cell, those barcodes allow them to keep track of the location of an individual cell amid millions of neurons [1]. This also enables researchers to map the tangled paths of individual neurons from one region of the mouse brain to the next.
The video shows how the researchers read the barcodes. Each twinkling light is a barcoded neuron within a thin slice of mouse brain tissue. The changing colors from frame to frame correspond to one of the four letters, or chemical bases, in RNA (A=purple, G=blue, U=yellow, and C=white). A neuron that flashes blue, purple, yellow, white is tagged with a barcode that reads GAUC, while yellow, white, white, white is UCCC.
By sequencing and reading the barcodes to distinguish among seemingly identical cells, the researchers mapped the connections of more than 3,500 neurons in a mouse’s auditory cortex, a part of the brain involved in hearing. In fact, they report they’re now able to map tens of thousands of individual neurons in a mouse in a matter of weeks.
What makes BARseq even better than the team’s previous mapping approach, called MAPseq, is its ability to read the barcodes at their original location in the brain tissue [2]. As a result, they can produce maps with much finer resolution. It’s also possible to maintain other important information about each mapped neuron’s identity and function, including the expression of its genes.
Zador reports that they’re continuing to use BARseq to produce maps of other essential areas of the mouse brain with more detail than had previously been possible. Ultimately, these maps will provide a firm foundation for better understanding of human thought, consciousness, and decision-making, along with how such mental processes get altered in conditions such as autism spectrum disorder, schizophrenia, and depression.
Here’s wishing everyone a safe and happy holiday season. It’s been a fantastic year in science, and I look forward to bringing you more cool NIH-supported research in 2020!
A few years ago, I highlighted a really cool technology called Drop-seq for simultaneously analyzing the gene expression activity inside thousands of individual cells. Today, one of its creators, Evan Macosko, reports significant progress in developing even better tools for single-cell analysis—with support from an NIH Director’s New Innovator Award.
In a paper in the journal Science, Macosko, Fei Chen, and colleagues at the Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, recently unveiled another exciting creation called Slide-seq [1]. This technology acts as a GPS-like system for mapping the exact location of each of the thousands of individual cells undergoing genomic analysis in a tissue sample.
This 3D video shows the exquisite precision of this new cellular form of GPS, which was used to generate a high-resolution map of the different cell types found in a tiny cube of mouse brain tissue. Specifically, it provides locations of the cell types and gene expression in the hippocampal regions called CA1 (green), CA2/3 (blue), and dentate gyrus (red).
Because using Slide-seq in the lab requires no specialized imaging equipment or skills, it should prove valuable to researchers across many different biomedical disciplines who want to look at cellular relationships or study gene activity in tissues, organs, or even whole organisms.
How does Slide-seq work? Macosko says one of the main innovations is an inexpensive rubber-coated glass slide nicknamed a puck. About 3 millimeters in diameter, pucks are studded with tens of thousands of 10 micron-sized beads, each one decorated with a random snippet of genetic material—an RNA barcode—that serves as its unique identifier of the bead.
The barcodes are sequenced en masse, and the exact location of each barcoded bead is indexed using innovative software developed by a team led by Chen, who is an NIH Director’s Early Independence awardee.
Then, the researchers place a sample of fresh-frozen tissue (typically, 10 micrometers, or 0.00039 inches, thick) on the puck and dissolve the tissue, lysing the cells and releasing their messenger RNA (mRNA). That leaves only the barcoded beads binding the mRNA transcripts expressed by the cells in the tissue—a biological record of the genes that were turned on at the time the sample was frozen.
The barcoded mRNA is then sequenced. The spatial position of each mRNA molecule can be inferred, using the reference index on the puck. This gives researchers a great deal of biological information about the cells in the tissue, often including their cell type and their gene expression pattern. All the data can then be mapped out in ways similar to those seen in this video, which was created using data from 66 pucks.
Slide-seq has been tested on a range of tissues from both mouse and human, replicating results from similar maps created using existing approaches, but also uncovering new biology. For example, in the mouse cerebellum, Slide-seq allowed the researchers to detect bands of variable gene activity across the tissues. This intriguing finding suggests that there may be subpopulations of cells in this part of the brain that have gene activity influenced by their physical locations.
Such results demonstrate the value of combining cell location with genomic information. In fact, Macosko now hopes to use Slide-seq to study the response of brain cells that are located near the buildup of damaged amyloid protein associated with the early-stage Alzheimer’s disease. Meanwhile, Chen is interested in pursuing cell lineage studies in a variety of tissues to see how and where changes in the molecular dynamics of tissues can lead to disease.
These are just a few examples of how Slide-seq will add to the investigative power of single-cell analysis in the years ahead. In meantime, the Macosko and Chen labs are working hard to develop even more innovative approaches to this rapidly emerging areas of biomedical research, so who knows what “seq” we will be talking about next?
