New technology enables predictive design of engineered human cells

Northwestern University synthetic biologist Joshua Leonard used to build devices as a child using electronic groups. Now he and his team have developed a design-driven process that uses parts of an entirely different kind of toolkit to construct complex cellular engineering genetic circuits.

One of the most exciting frontiers in medicine is the use of live cells as therapies. Using this approach to treating cancer, for example, many patients have been cured of a disease that could not be cured before. These advances use synthetic biology approaches, a growing field blending tools and concepts from biology and engineering.

Northwestern’s new technology uses computer modeling to more efficiently identify useful genetic designs before building them in the lab. Faced with myriad possibilities, modeling directs researchers to designs that provide real opportunity.

“To engineer a cell, we first encode the desired biological function into a piece of DNA, and then this DNA program is delivered to a human cell to direct its implementation of the desired function, such as activating a gene only in response to specific signals,” Leonard said. Bagheri from the University of Washington for this study.

Leonard is an Associate Professor of Chemical and Biological Engineering at the McCormick School of Engineering and a lead faculty member at the Northwestern Center for Synthetic Biology. His lab focuses on using this kind of programming ability to build therapies like engineered cells that activate the immune system to treat cancer.

Bagheri is an associate professor of biology and chemical engineering and an investigator at the Washington Research Foundation at the University of Washington in Seattle. Her lab uses mathematical models to better understand cell decisions – and thus control them. Leonard and Baqry co-counseled Joseph Muldoon, a recent PhD student and senior author of the newspaper.

“Model-directed design has been explored in cell types like bacteria and yeast, but this approach is relatively new in mammalian cells,” Mouldon said.

The study, in which dozens of genetic circuits have been designed and tested, will be published February 19 in the journal Science Advances. Like other synthetic biology techniques, the main feature of this approach is that it is assumed that it will be easily adopted by other bioengineering groups.

Even now, genetic software development remains challenging and time consuming when relying on trial and error. Other than the relatively simple ones, biological functions are also difficult to perform. The research team used a “toolkit” of genetic parts invented in Leonard’s lab and paired these parts with computational tools to simulate several potential genetic programs before experimenting. They found that a variety of genetic programs can be built, each performing a desirable and useful function in a human cell, so that each program works as expected. Not only that, but the designs succeeded the first time.

“In my experience, nothing works like that in science; nothing works the first time.” Leonard said, “We usually spend a lot of time debugging and refining any new genetic design before it works as intended.” If each design works. As expected, we will not limit ourselves to building by trial and error. Alternatively, we can spend our time evaluating which ideas might be helpful for hone truly great ideas. ”

“Powerful representational models can have a scientific and multi-faceted disruptive effect,” Bagheri added. “This development is just the tip of the iceberg.”

The genetic circuits developed and implemented in this study are also more complex than the previous state of the art. This advancement creates the opportunity to engineer cells to perform more complex functions and to make treatments safer and more effective.

“With this new ability, we’ve taken a big step in being able to really engineer biology,” Leonard said.


The research was supported by the National Institute of Biomedical Imaging and Bioengineering (award number 1R01EB026510), the National Institute of General Medical Sciences (award number T32GM008152) and the National Cancer Institute (award number F30CA203325).

The title of the paper is “Model-oriented design of mammalian genetic programs.”

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