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