Read our COVID-19 research and news.

New methods can map the activity of myriad genes (colored dots) in cells (blue outlines) across a tissue.


‘Total game changer’: Pinpointing gene activity in tissues is aiding studies of COVID-19, Alzheimer’s

As with real estate, location matters greatly for cells. Douglas Strand confirmed that truth last year when he used a new technique to map gene activity in bladder cancers. Until recently, scientists wanting to know all the genes at work in a tissue could analyze single cells without knowing their position, or they could measure average activity levels of genes across thousands of cells. Now, an emerging technology called spatial transcriptomics combines precision and breadth, mapping the work of thousands of genes in individual cells at pinpoint locations in tissue. That, Strand says, has been a “total game changer” for his research.

The virtual Advances in Genome Biology and Technology (AGBT) meeting this month was a big coming-out party for the technique, which is revealing whole new landscapes of gene expression. Strand, for example, reported finding that cells surrounding bladder tumors, though outwardly normal, display many of the same gene activity changes as the cancer. “They looked more like tumor than normal tissue,” says Strand, who works at the University of Texas Southwestern Medical Center. He found surprises within the tumors, too: hidden patterns of gene activity suggesting some of the cells are more likely than others to spread beyond the bladder.

Other biologists at the meeting reported using the technique to study Alzheimer’s disease, track the dynamics of different types of T cells, and study lung, heart, and other tissues in COVID-19 patients. “The field is developing very, very fast,” says Aparna Bhaduri of the University of California, Los Angeles, who uses it to examine developing human brains.

Scientists studying cells have long been able to examine the activity of a few, select genes in intact tissue—for example, by engineering a gene to tack on a fluorescent tag to the protein it encodes. By 2010, traditional transcriptomics, which examines cellular activity of many, if not all, known genes by probing for the messenger RNA (mRNA) transcripts they encode, took off. But those studies require tissues to be ground up first, so the data represent the average activity of genes in millions of cells.

More recently, biologists have begun to monitor all the genes of single cells, uncovering vast differences in gene activity between different cell types and variation even within types. But because those cells are extracted from tissue with enzymes or teased out with lasers, microscopic tweezers, or other methods, the influence of their precise location and neighbor cells is lost. “We could see the individual parts, but we didn’t know how the parts fit together,” explains Joseph Beechem, a biophysicist at NanoString Technologies, a leading company for spatial transcriptomics and related methods.

Then in 2016, Swedish researchers described in Science how they managed to keep track of cells’ locations while assessing the activity of about 200 of their genes. The group put thin slices of a tissue onto slides precoated with short, known sequences of DNA, meant to act like identifiable barcodes, attached to other DNA designed to latch nonspecifically onto any mRNA nearby. The team treated the tissue with detergent to make cells leak their mRNA, which linked to the anchored, barcoded DNA, marking which cell the mRNA came from. Then, they added enzymes and DNA bases to the slice to translate each mRNA into a complementary DNA strand. Sequencing that strand along with its position-identifying barcode revealed the active parent gene and its position. Those data enabled computer programs to reconstruct the tissue locations of all the active genes.

Multiple companies have begun to sell expensive machines that conduct such spatial transcriptomics analyses, making it possible to study thousands of genes in hundreds of cells in their proper places. That “can tell you a lot about how cell communication might break down in disease,” says Aviv Regev, a computation and systems biologist who heads the Genentech Research and Early Development unit of Roche.

A magnified view (inset) of a slice of mouse brain reveals genes active in cells (marked by white nuclei).


Christopher Mason, a geneticist at Weill Cornell Medicine (WCM), and colleagues have performed spatial transcriptomics on fresh or preserved tissue samples from autopsied COVID-19 patients, comparing them with lung tissue of healthy adults and people who died of other acute respiratory infections or flu. The commercial devices they used, one based on the Swedish approach, can assess lots of genes but can’t completely pinpoint their activity to single cells. (Other methods are limited to far fewer genes, but specify locations better.) The team, including WCM’s Robert Schwartz and Alain Borczuk and others, mapped the activity of the gene for angiotensin-converting enzyme 2, the cell-surface receptor targeted by SARS-CoV-2, and other identifying immune cells called macrophages and neutrophils.

In normal lung tissue, macrophages make up less than 4% of the cells; in COVID-19 lungs, they sometimes topped 50%, Mason reported at the AGBT meeting. The lung itself changes as well, he and his colleagues discovered by looking at gene activity in these lung samples. Late in the disease, the organ’s normal cellular architecture was disrupted, and cells adjacent to blood vessels had changed.

The WCM group and others have done spatial analyses of gene activity for other parts of the COVID-19–ravaged body. The coronavirus seems to turn off genes in nasal cells that sense smells and causes a reorganization of the cells in the lining of the nose; those changes may contribute to the loss of smell and taste infected people often experience. The hearts of COVID-19 patients also betrayed an impact. Under the microscope they appear to have a normal number of muscle cells, Mason says, “but if you look at gene expression, it seems the cells have forgotten what they are supposed to be doing.”

Stanford University neuroscientist Andrew Yang has done a similar gene activity comparison of preserved human brain tissue to understand why some people with protein deposits called amyloid plaques don’t develop Alzheimer’s disease and others do. In tissue from Alzheimer’s patients, nonneuronal cells close to these plaques show increased activity of genes whose proteins mark nerve cell connections called synapses for destruction. Other revved up genes suggest increased action by scavenger cells called microglia, which prune synapses and cause potentially harmful inflammation. “We’re beginning to understand what makes for a good or bad response to these aggregates,” Yang says.

These early results only begin to address the potential of spatial transcriptomics. The current methods don’t yet work robustly in all types of tissues, and analyses can take days to complete. Companies continue to upgrade their instruments, but so far, none can really quantify all the active genes in a tissue at the single-cell level.

At about $300,000 each, some of the machines are also prohibitively expensive for many labs. The Broad Institute has come up with a cheaper DIY version. Called “Slide-seq,” the technique uses a layer of tiny beads, coated with pieces of barcoded DNA, on a slide to help mark the positions of mRNA from thousands of genes. At the AGBT meeting, Broad genomicist Robert Stickels described version 2.0, which crams much more DNA onto each bead and can put up to 1 million beads on a slide, making the gene-activity mapping more precise by an order of magnitude.

The entire protocol is public, Stickels says. “It really empowers other labs to do it.” For example, Abhishek Sampath Kumar, a graduate student at the Max Planck Institute for Molecular Genetics, now gets slides from Broad. “This technique is easy to apply,” says Kumar, who is studying mammalian heart development. “You don’t need any special instruments compared to other methods.”

Both industrial and academic labs are racing to improve spatial transcriptomics and to extend cell-by-cell mapping to other key indicators. “Soon there will be technologies that give you more and more types of data all together at the same time, spatial information, RNA, DNA, chromatin, protein, temporal information about cellular histories, metabolite profiling, you name it, at single-cell resolution,” Stickels predicts.

Many biologists are thrilled at the prospects. “I think we will be rewriting the textbook on how organisms develop, and we are going to understand how the body responds to drugs in a way that nobody has been able to do before,” Beechem says. “Spatial biology is providing the next revolution in biology.”