Biosensor Barcodes Track Cancer Cell Communications

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BALTIMORE, Dec. 7, 2021 — Johns Hopkins University researchers have developed a method for identifying and tracking cells in a manner similar to the way barcodes are used to identify and track products. The team used the method to study the way that cancer cells “talk” with one another.

“When cancer cells communicate, numerous proteins constantly change how they interact with one another,” said senior author Chuan-Hsiang (Bear) Huang, assistant professor of pathology at the Johns Hopkins University School of Medicine. “Studying this signaling in depth and in real time has traditionally been difficult, so we needed a method that could simultaneously image, track, and analyze everything happening in the network, and therefore, reveal the true relationships among these activities.”

The method is composed of different combinations of patterns and colors. Each set is tied to a specific biochemical activity in the communication network.
Cells labeled by “biosensor barcodes” of different colors and spatial patterns within those cells. A Johns Hopkins Medicine study demonstrated how barcoding tools can be used to concurrently identify and track communication signals among cells, including those driving cancer formation. Courtesy of Jr-Ming Yang and Chuan-Hsiang Huang, Johns Hopkins Medicine.
Cells labeled by 'biosensor barcodes' of different colors and spatial patterns within those cells. A Johns Hopkins study demonstrated how barcoding tools can be used to concurrently identify and track communication signals among cells, including those driving cancer formation. Courtesy of Jr-Ming Yang and Chuan-Hsiang Huang, Johns Hopkins School of Medicine.
Genetically encoded fluorescent biosensors have been used in the past to study cellular protein functions, including signaling activities in cancer cells, Huang said. The biosensors are protein fragments tagged with fluorophores — fluorescent molecules that glow by absorbing light energy of a specific wavelength, and then reemitting light at a longer wavelength — and each color is linked to a specific activity in the cell. Using a fluorescent microscope to image the type, location, and intensity of the colors exhibited by the sensors, the researchers can accurately and precisely document proteins in action in different cellular regions.

“For example, changes in the intensity of specific colors, their locations within cells and the ratio of one color to another shed light on the activity levels of the proteins being studied and how they interact with one another in real time,” Huang said.

However, the usefulness of fluorescent biosensors was limited when the team needed to track a complex system like a cancer cell communications network. Different biosensors often had very similar colors and could be distinguished from one another when imaged as a whole.

“In the past, if you wanted to look at dozens of biosensors that tracked the activities of different proteins in a signaling network, each biosensor had to be imaged in separate experiments that lasted hours,” said study lead author Jr-Ming Yang, a research associate at the Johns Hopkins University School of Medicine. “Moreover, to understand the communication network’s properties, those experiments had to be repeated. Besides the time investment, separate imaging runs increased the likelihood of variations popping up, making it difficult to ascertain that the changes in activity were from real effects.”

Huang and his colleagues combined fluorescent proteins of different colors and localization patterns to create “biosensor barcodes” — tools that can concurrently identify and track a larger number of biosensors for various proteins, including those driving cancer formation.

“To track multiple signaling protein activities in parallel, we pair our different biosensors with specific barcodes in individual cells, and then mix and image them using time-lapse microscopy,” Huang said. “Since each cell has a different barcode, we also can use this method to identify different populations of cells in the mix and investigate how they communicate with one another.”

The images, Huang said, are analyzed with a machine learning system created by study co-author Wei-Yu Chi, a postdoctoral fellow in his laboratory.

The AI analysis enabled the team to read the barcodes in seconds rather than hours.

“Using biosensor barcodes, we hope to get more insights and more comprehensive views than ever before of how oncogenes [genes that initiate the development of cancer cells] affect communication among cancer cells, and with other networks such as those used by the immune system,” Huang said. “These findings could help direct new interventions and treatments.”

The research was published in Cell (

Published: December 2021
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