Researchers at Weill Cornell Medicine have created a computational technique to map the anatomy of human tissues in unprecedented detail. Their methodology promises to quicken research on cellular interactions at the organ scale and may open the door to potent new diagnostic approaches for a variety of disorders.
The method, which was released on October 31 in Nature Methods, was the result of the researchers’ irritation with the discrepancy between traditional microscopy and contemporary single-cell molecular analysis. According to senior author Junbum Kim, a graduate student in physiology and biophysics at Weill Cornell Medicine, “looking at human tissues under the microscope, you find a bunch of cells that are grouped together spatiallyinyou see that organization in images practically instantly.” “Cell biologists are now concentrating on the cells instead of focusing on the tissue structure because they have gotten the ability to investigate individual cells in tremendous detail, down to the genes each cell is expressing,” he said.
However, according to senior author Dr. Olivier Elemento, director of the Englander Institute for Precision Medicine and professor of physiology, biophysics, and computational genomics in computational biomedicine at Weill Cornell Medicine, “it’s crucial for researchers to learn more about the details of tissue structure; fundamental changes in the relationships between cells within a tissue drive both healthy and diseased organ function.”
However, it is difficult and laborious to manually combine maps of tissue structure with single cell data. The amount of data that can be utilized to train machine learning algorithms limits their ability to automate the process. In order to solve this, Kim and his colleagues created an unsupervised computational method that defines structural regions inside a tissue by combining single-cell gene expression profiles with cell locations.
Dr. André Rendeiro, a co-senior author and main investigator at the Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna, Austria, compares the new technique to mapping a city like New York. He was a postdoctoral fellow at Weill Cornell Medicine throughout the study. One method would be to visit each junction and count the number of each type of building: is it residential, commercial, or is it a store or restaurant? One may combine the two matrices and search for trends by first putting all of the data into one matrix and the positions of the buildings into another.
In essence, Dr. Rendeiro said, “we could begin to make general statements about where the different neighborhoods are and where their borders are based on, say, the abundance of residential versus commercial buildings—jjust as anyone walking through the Upper East Side, Midtown, or Downtown would do based on their observations.”
In order to detect and quantify novel elements of microanatomy—the patterns that arise at a tiny scale when cells interact and affect the eventual function of tissues—the researchers employed the new technology to create precise maps of several types of human tissues. Together with a lung disease expert from the University of North Carolina at Chapel Hill, they also showed that their method could distinguish between various disease states in a tissue in subtle ways.
Detailed microanatomy may aid in the diagnosis and treatment of more severe illnesses, even though cancer and other chronic diseases frequently result in significant changes in tissue structure. In severe COVID-19, for instance, “there are a lot of immune cells that go into the neighborhood, and there’s really dramatic alteration in the lung tissue,” says Rendeiro. To better understand how changes in tissue organization underpin its function in a healthy state and its malfunction in sickness, the team is currently applying their new technique to a variety of tissues.
