NIH Director’s New Innovator Award
Posted on by Dr. Francis Collins
Courtesy of the Chen and Macosko labs
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 . 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?
 Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Rodriques SG, Stickels RR, Goeva A, Martin CA, Murray E, Vanderburg CR, Welch J, Chen LM, Chen F, Macosko EZ. Science. 2019 Mar 29;363(6434):1463-1467.
Single Cell Analysis (NIH)
Macosko Lab (Broad Institute of Harvard and MIT, Cambridge)
Chen Lab (Broad Institute)
NIH Support: National Institute on Aging; Common Fund
Posted on by Dr. Francis Collins
The purple pods that you see in this scanning electron micrograph are the H5N2 avian flu virus, a costly threat to the poultry and egg industry and, in very rare instances, a health risk for humans. However, these particular pods are unlikely to infect anything because they are trapped in a gray mesh of carbon nanotubes. Made by linking carbon atoms into a cylindrical pattern, such nanotubes are about 10,000 times smaller than width of a human hair.
The nanotubes above have been carefully aligned on a special type of silicon chip called a carbon-nanotube size-tunable-enrichment-microdevice (CNT-STEM). As described recently in Science Advances, this ultrasensitive device is designed to capture viruses rapidly based on their size, not their molecular characteristics . This unique feature enables researchers to detect completely unknown viruses, even when they are present in extremely low numbers. In proof-of-principle studies, CNT-STEM made it possible to collect and detect viruses in a sample at concentrations 100 times lower than with other methods, suggesting the device and its new approach will be helpful in the ongoing hunt for new and emerging viruses, including those that infect people.
Posted on by Dr. Francis Collins
One reason that I decided to share these LabTV profiles is that they put a human face on the amazingly wide range of NIH-supported research being undertaken every day in labs across the country. So far, we’ve met young scientists pursuing basic, translational, and clinical research related to the immune system, cancer, Alzheimer’s disease, and the brain’s natural aging process. Today, we head to Boston to visit a researcher who has set her sights on a major infectious disease challenge: tuberculosis, or TB.
Bree Aldridge, PhD, an assistant professor at Tufts University School of Medicine in Boston, runs a lab that’s combining microbiology and bioengineering in an effort to streamline treatment for TB, which leads to more than 2 million deaths worldwide every year . Right now, people infected with Mycobacterium tuberculosis—the microbe that causes TB—must take a combination of drugs for anywhere from six to nine months. When I was exposed to TB as a medical resident, I had to take a drug for a whole year. These lengthy regimens raise the risk that people will stop taking the drugs prematurely or that an opportunistic strain of M. tuberculosis will grow resistant to the therapy. By gaining a better basic understanding of both M. tuberculosis and the cells it infects, Aldridge and her colleagues hope to design therapies that will fight TB with greater speed and efficiency.