New label-free imaging method can distinguish active T cells from non-working T cells

Reviewed by Emily Henderson, B.Sc.July 27, 2020

T cells Immune soldiers at the forefront of the battle against invasive pathogens that try to cause disease. New research published in Biomedical engineering Describes a new label-free imaging technique that can distinguish active T cells from non-workers.

This method helps assess T cell involvement in cancer therapy and immunotherapy of autoimmune diseases.

“T cells have metabolic switches that regulate their activity,” says Melissa Skala, a principal investigator at the Morgridge Institute and associate professor of biomedical engineering at UW-Madison. In healthy individuals, most T cells are quiescent. They are inactive, but waiting for signals to participate in active combat against invading viruses and bacteria.

“We wanted to test whether our imaging technology could tell the difference between quiescent and activated T cells.”

Most methods to characterize T cells are antibody-based such as flow cytometry and immunohistochemistry. They require staining with antibodies or contrast agents, a process that destroys cells.

Alternatively, Walsh and Scala’s method detects autofluorescence from molecules within cells that spontaneously luminesce when imaged with a microscope combined with an infrared laser. This label-free process does not damage or change the behavior of cells. This technique can be applied to cells in plates and dishes, tissue samples, or even in vivo imaging of complete organisms.

It’s a super novel. Most people do not use these techniques. Many autofluorescence studies are not found in immunology. “

Melissa Skala, Principal Investigator, Morgissa Institute

To validate their approach, researchers obtained blood samples from healthy donors, isolated T cells, and analyzed the autofluorescence of two molecules involved in cell metabolism, NAD(P)H and FAD. I measured it.

“We kept some T cells quiescent and then added antibodies to the group to activate them,” says Walsh.

Images of quiescent and activated cells revealed differences in metabolic function, especially changes in NAD (P) H autofluorescence in activated T cell populations. They also observed that active T cells were slightly larger in size than resting cells.

Skala says the activation protocol and imaging features help produce CAR-T cells used in immunotherapy. These reengineered T cells are often co-cultured with other cells, such as cancer cells, to test their reactivity.

However, the use of additional harsh reagents or antibody labels to further characterize T cells is a bottleneck for CAR-T cell makers. The autofluorescence approach provides an attractive way to perform these experiments by imaging the same cells over multiple time points in a non-damaging manner.

“We have shown that our imaging technology can solve the changes over time,” says Walsh. “Within a few minutes of adding the activating antibody, we were able to see changes in the imaging endpoint.”

Walsh adds that it is difficult to identify these dynamic changes using flow cytometry, as the time required for staining and incubation makes it difficult to capture multiple time points.

Skala Labs will continue this series of studies to better understand how T cells in cancer patients respond to tumor growth or when treated with immunotherapy.

“These technologies could tell us something we didn’t know about tumors and T-cell production,” Skala adds, “a way to monitor T-cell behavior over time. Because there was no.

While this new method has many advantages over the old method, it still has its limitations. First, autofluorescence imaging is not very sensitive.

“We don’t really depend on a particular label, but on the metabolism of the cell,” says Skala. “It just gets you by distinguishing cell types so far.”

In addition, this technique requires experienced people to perform microscopic image processing to analyze the data, Walsh says.

Skala Labs is working on a prototype that leverages the imaging capabilities of a large microscope to transform it into a “box size” system.

“You don’t have to be a professional optical engineer to use it,” Scala says. “That is the direction we are aiming for. We are working to make it more accessible.”