Visualization of metabolic processes at the single cell level – use of a genetically coded biosensor paired with AI

A new imaging and machine learning technique developed at the University of Chicago enables scientists to observe how cells break down glucose, potentially leading to new ways to treat a variety of diseases, including cancer and COVID-19. Photo credit: Courtesy of Wu et. al.

Understanding cell metabolism – how a cell uses energy – could be key to treating a wide variety of diseases, including vascular disease and cancer.

While many techniques can measure these processes in tens of thousands of cells, researchers have not been able to measure them at the single cell level.

Researchers at the University of Chicago’s Pritzker School of Molecular Engineering and Biological Sciences Division have developed a combined imaging and machine learning technique that can, for the first time, measure a metabolic process at both the cellular and subcellular levels.

Using a genetically encoded biosensor paired with artificial intelligence, the researchers were able to measure glycolysis, the process of converting glucose into energy, of individual endothelial cells, the cells that line blood vessels.

They found that when these cells move and contract, they use more glucose, and they also found that cells take up glucose through a previously unknown receptor. Understanding this process could lead to better treatments for cancer and vascular disease, including COVID-19.

The research published in Nature Metabolism was supported by Assoc. Prof. Yun Fang and co-director of Asst. Prof. Jun Huang, former postdoctoral fellow and now Asst. Prof. David Wu and PhD student in biophysics Devin Harrison.

“Understanding cell metabolism is universally important,” said Huang. “By measuring individual cell metabolism, we may have a new way of treating a wide variety of diseases.”

“This is the first time that we can visualize cell metabolism on different temporal and spatial scales, even at the subcellular level, which could fundamentally change the language and approach for researchers to study cell metabolism,” said Fang.

Measurement of glycolysis

Endothelial cells usually form a dense layer in the blood vessels, but can contract and leave gaps in this layer when they need the help of the immune system. An abnormal contraction can lead to leaky blood vessels, which can lead to a heart attack or stroke. Such contraction of the blood vessels around the lungs can also cause fluid to enter, which is the case in acute respiratory distress syndrome. (This is common in patients with severe cases of COVID-19.)

To better understand how cells metabolize energy to promote this contraction, researchers turned to Förster resonance energy transfer sensors – genetically encoded biosensors that can measure the amount of lactate in cells. Lactate is the by-product of glycolysis.

Although the researchers did not develop the sensors, by combining the sensors with machine learning algorithms, they developed an even more powerful technique that enabled them to image cells, analyze the data, and analyze glycolysis reactions at the cellular and subcellular levels.

“Can we ultimately reprogram cells through our metabolism?”

– Asst. Prof. Jun Huang

“Now we can look at and understand details within the cells, such as certain areas of the cell where glycolysis is increasing,” said Fang. “This is a key technological innovation.”

They were able to measure how much glucose the cells were using as they contracted and moved, and they also found a new mechanism of glucose transport mediated by the cell’s cytoskeleton – a receptor called GLUT3 – which these cells use to take up glucose use.

Create new treatments

Understanding how glycolysis works at the cellular level could ultimately lead to treatments that inhibit this process if necessary – for example, for leaky blood vessels in patients with atherosclerosis. It could also help patients whose immune systems are overreacting to COVID-19, for example, and need help closing the gaps in their endothelial cells around their lungs.

“If we can find a way to stop the contraction, we could reduce acute respiratory distress syndrome in COVID-19 patients,” said Fang.

It also has important implications for cancer treatment. Endothelial migration and proliferation, driven by glycolysis, are important cellular processes involved in vascular growth necessary for tumor survival and growth. Understanding how this works could help researchers destroy tumors and stunt tumor growth.

It could also be useful in CAR-T cell therapy, which the body’s immune system recruits to fight tumors. While therapy has been life-saving for some, many patients do not respond to it. Because endothelial cells are important for T cells to infiltrate tumors and because cell metabolism is critical to T cell function, researchers believe that modulating cell metabolism could help create a better immunotherapy system.

Researchers are currently testing such inhibitors for the treatment of COVID-19-induced acute respiratory distress syndrome at the Argonne National Laboratory.

“Can we ultimately reprogram cells through metabolism?” Said Huang. “This is an important question and we need to understand how the metabolism works. There is huge potential here, and that’s just the beginning. “

Reference: “Single-cell metabolic imaging shows an SLC2A3-dependent glycolytic outbreak in motile endothelial cells” by David Wu, Devin L. Harrison, Teodora Szasz, Chih-Fan Yeh, Tzu-Pin Shentu, Angelo Meliton, Ru-Ting Huang, Zhengjie Zhou, Gökhan M. Mutlu, Jun Huang and Yun Fang, May 24, 2021, natural metabolism.
DOI: 10.1038 / s42255-021-00390-y

Other authors of the paper include Teodora Szasz, Chih-Fan Yeh, Tzu-Pin Shentu, Angelo Meliton, Ru-Ting Huang, Zhenjie Zhou, and Gökhan Mutlu.

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