Posted on by Dr. Francis Collins
Most of our immune cells circulate throughout the bloodstream to serve as a roving security force against infection. But some immune cells don’t travel much at all and instead safeguard a specific organ or tissue. That’s what you are seeing in this electron micrograph of a type of scavenging macrophage, called a Kupffer cell (green), which resides exclusively in the liver (brown).
Normally, Kupffer cells appear in the liver during the early stages of mammalian development and stay put throughout life to protect liver cells, clean up old red blood cells, and regulate iron levels. But in their experimental system, Christopher Glass and his colleagues from University of California, San Diego, removed all original Kupffer cells from a young mouse to see if this would allow signals from the liver that encourage the development of new Kupffer cells.
The NIH-funded researchers succeeded in setting up the right conditions to spur a heavy influx of circulating precursor immune cells, called monocytes, into the liver, and then prompted those monocytes to turn into the replacement Kupffer cells. In a recent study in the journal Immunity, the team details the specific genomic changes required for the monocytes to differentiate into Kupffer cells . This information will help advance the study of Kupffer cells and their role in many liver diseases, including nonalcoholic steatohepatitis (NASH), which affects an estimated 3 to 12 percent of U.S. adults .
The new work also has broad implications for immunology research because it provides additional evidence that circulating monocytes contain genomic instructions that, when activated in the right way by nearby cells or other factors, can prompt the monocytes to develop into various, specialized types of scavenging macrophages. For example, in the mouse system, Glass’s team found that the endothelial cells lining the liver’s blood vessels, which is where Kupffer cells hang out, emit biochemical distress signals when their immune neighbors disappear.
While more details need to be worked out, this study is another excellent example of how basic research, including the ability to query single cells about their gene expression programs, is generating fundamental knowledge about the nature and behavior of living systems. Such knowledge is opening new possibilities to more precise ways of treating and preventing diseases all throughout the body, including those involving Kupffer cells and the liver.
 Liver-Derived Signals Sequentially Reprogram Myeloid Enhancers to Initiate and Maintain Kupffer Cell Identity. Sakai M, Troutman TD, Seidman JS, Ouyang Z, Spann NJ, Abe Y, Ego KM, Bruni CM, Deng Z, Schlachetzki JCM, Nott A, Bennett H, Chang J, Vu BT, Pasillas MP, Link VM, Texari L, Heinz S, Thompson BM, McDonald JG, Geissmann F3, Glass CK. Immunity. 2019 Oct 15;51(4):655-670.
 Recommendations for diagnosis, referral for liver biopsy, and treatment of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Spengler EK, Loomba R. Mayo Clinic Proceedings. 2015;90(9):1233–1246.
Liver Disease (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)
Glass Laboratory (University of California, San Diego)
NIH Support: National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences; National Cancer Institute
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 human genome contains more than 20,000 protein-coding genes, which carry the instructions for proteins essential to the structure and function of our cells, tissues and organs. Some of these genes are very similar to each other because, as the genomes of humans and other mammals evolve, glitches in DNA replication sometimes result in extra copies of a gene being made. Those duplicates can be passed along to subsequent generations and, on very rare occasions, usually at a much later point in time, acquire additional modifications that may enable them to serve new biological functions. By starting with a protein shape that has already been fine-tuned for one function, evolution can produce a new function more rapidly than starting from scratch.
Pretty cool! But it leads to a question that’s long perplexed evolutionary biologists: Why don’t duplicate genes vanish from the gene pool almost as soon as they appear? After all, instantly doubling the amount of protein produced in an organism is usually a recipe for disaster—just think what might happen to a human baby born with twice as much insulin or clotting factor as normal. At the very least, duplicate genes should be unnecessary and therefore vulnerable to being degraded into functionless pseudogenes as new mutations arise over time
An NIH-supported team offers a possible answer to this question in a study published in the journal Science. Based on their analysis of duplicate gene pairs in the human and mouse genomes, the researchers suggest that extra genes persist in the genome because of rapid changes in gene activity. Instead of the original gene producing 100 percent of a protein in the body, the gene duo quickly divvies up the job . For instance, the original gene might produce roughly 50 percent and its duplicate the other 50 percent. Most importantly, organisms find the right balance and the duplicate genes can easily survive to be passed along to their offspring, providing fodder for continued evolution.