Kwong Lab Opens the Gates

<p>Gabe Kwong, assistant professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory</p>

Gabe Kwong, assistant professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory

The ability to engineer the body’s immune system has transformed human health, the most recent and dramatic example being the development of T-cell therapies for cancer. Helping to drive this new age of medicine forward is the creation and development of better tools and biotechnologies in the detection and treatment of disease.

For example, researchers’ capacity to analyze and isolate cells based on the expression of specific surface markers has increased the overall understanding of cell biology, and led to numerous applications for biomedicine. The challenge, though, with established cell-sorting platforms, such as flow cytometry, is that they rely on colored labels which are limited in number.

“The short story is that existing cell sorting platforms only allow us to analyze a small handful of cells at a time,” says Gabe Kwong, a researcher in the Petit Institute for Bioengineering and Bioscience, whose lab is tightly focused on creating new and more effective tools to analyze the body’s immune system.

So Kwong, assistant professor Wallace H. Coulter Department of Biomedical Engineering (BME) at the Georgia Institute of Technology and Emory University, and his research team have tried to improve the situation by developing a new multiplexed cell-sorting platform called DNA-gated sorting (DGS) that capture, release, and recover target cells from complex biological specimens.

Kwong and his colleagues explain it all in a research paper published recently in the journal PNAS (Proceedings of the National Academy of Sciences), entitled, “Individually addressable and dynamic DNA gates for multiplexed cell sorting.”

“Biological specimens, such as whole blood, contain main different types of cells that have important applications for monitoring health, including tracking vaccine efficacy and HIV progression, and for treating complex diseases, like cancer,” the researchers write.

Take T-cells, for example. There are hundreds of millions of subtypes. Current cell-sorting technologies, requiring expensive and large pieces of equipment, can only isolate a few types of cells at one time, “only three to five T-cells at a time,” says Kwong. “So it’s a huge limitation. The reason for that is, these platforms use color to sort and label the cells. So basically, you might label one red, another green, and so forth. Before long, you run out of colors, so you can’t label that many different cells.”

Kwong and his team developed something different. They designed a cell-sorting platform by engineering dynamic DNA devices (DNA gates) that can label, sort, and recover different cell populations at high purity, en masse. Their DNA-based nanotechnology efficiently gathers more than one set of data from the same sample, and can potentially be expanded to exceed the capacity of current methods for sorting multiple cell types, improve biomedical diagnostics, and provide new insights into cell biology.

“The long-term goal of this project and platform is to build a piece of technology that allows us to look at T cells that could not be looked at before,” says Kwong, whose lab focused on two primary application areas – infectious diseases and cancer.

The research team worked with the lab of Rafi Ahmed, a professor at Emory, where he is director of the Emory Vaccine Center.

“We’re asking fundamental questions,” Kwong says. “Like, when someone is infected with a virus, how many different T-cell clones respond to that virus? How do these T cells expand over time in response to these antigens? This platform will allow us to start counting the frequencies and different types of cells involved in viral responses. We also want to improve T-cell therapies for cancer.”

T-cells can be engineered to recognize tumor antigens, then attack and kill tumor cells, or shrink tumors.

“The limitation there is, we actually don’t know what kind of tumor antigens the tumor cells express,” Kwong says.  

Tumor antigens contain proteins that T-cells recognize, but there are many different types of potential tumor antigens, Kwong explains, and many different types of T cells that could potentially recognize them.

“The value of this platform as we envision it is, we can take a tumor sample and biopsy core from a patient, run it through our DNA gate system, and identify the T cells that can recognize tumor antigens,” Kwong says. “The goal is to be able to analyze cells downstream to make better immunotherapies. That’s something we’re very excited about.”

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This research was funded by an NIH Director’s New Innovator Award and by the National Center for Advancing Translational Sciences of the NIH. In addition to Kwong, the research team included first author Shreyas Dahotre (BME graduate student); Yun Min Chang (a graduate student in BME as well as microbiology and immunology at Georgia Tech and Emory), Andreas Wieland (postdoctoral researcher at Emory), and BME undergraduate student Samantha Stammen.


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