Programming Language Simplifies Design of Biological Circuits

Bioengineers have created a programming language that allows to rapidly design complex DNA-encoded circuits that provide new functions to living cells. In a first application, genetic circuits generated on plasmids expressed in Escherichia coli bacteria successfully regulated cellular functions in response to multiple environmental signals.

The word was led by researchers at Massachusetts Institute of Technology (Cambridge, MA, USA) in collaboration with researchers at Boston University (Boston, MA, USA) and National Institute of Standards and Technology (Gaithersburg, MD, USA). They applied principles from electronic design automation (EDA) to simplify the process of incorporating synthetic gene regulation into cells and to enable increased circuit complexity.


“It is literally a programming language for bacteria,” says Christopher Voigt, professor, MIT, “You use a text-based language, just like you’re programming a computer. Then you take that text and you compile it and it turns it into a DNA sequence that you put into the cell, and the circuit runs inside the cell.”

Over the past 15 years, scientists have designed many genetic parts (e.g., sensors, memory switches, biological clocks) that can be combined to modify existing cell functions and add new ones. However, designing each circuit is a laborious process that requires expertise and often much trial and error. “You have to have this really intimate knowledge of how those pieces are going to work,” said Prof. Voigt. Users of the new programming language, however, need no special knowledge of genetic engineering. “You could be completely naive as to how any of it works. That’s what’s really different about this,” he said, “You could be a student in high school and go onto the Web-based server and type out the program you want, and it spits back the DNA sequence.”

The language is based on the hardware description language Verilog commonly used to program computer chips. To create a version that would work for cells, the researchers designed computing elements (such as logic gates and sensors) that can be encoded in DNA. The sensors can detect different compounds, such as oxygen or glucose, as well as light, temperature, acidity, and other environmental conditions. Users can also add their own sensors. “It’s very customizable,” said Prof. Voigt.

Another advantage of this technique is its speed. Until now, “it would take years to build these types of circuits. Now you just hit the button and immediately get a DNA sequence to test,” said Prof. Voigt. This approach simplifies incorporation of genetic circuits for decision-making, control, sensing, or spatial organization. The user specifies the desired circuit function in Verilog code, and this is automatically transformed into a DNA sequence. Algorithms build a circuit diagram, assign and connect gates, and simulate performance.

In the study, out of 60 circuits programmed for different functions, 45 worked correctly the first time tested. Many of the circuits were designed to measure and respond to one or more environmental conditions, such as oxygen level or glucose concentration. Another circuit was designed to rank three different inputs and then respond based on the priority of each.

In the current version, the genetic parts are optimized for E. coli. The researchers are expanding the language for other strains of bacteria, as well as the yeast Saccharomyces cerevisiae. This would allow users to write a single program and then compile it for different organisms to get the right DNA sequence for each.

The team plans to develop applications such as bacteria that can be swallowed to aid in digestion of lactose; bacteria that can live on plant roots and produce insecticide if they sense the plant is under attack; bacteria that can produce a cancer drug upon detecting a tumor; and yeast cells that can halt their own fermentation process if too many toxic byproducts build up in a reactor.

The study, by Nielsen AAK et al, was published April 1, 2016, in the journal Science.

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