Software for Programming Microbes
Genetically modified microbes could perform many useful jobs, from making biofuels and drugs, to cleaning up toxic waste. But designing the complex biochemical pathways inside such microbes is a time-consuming process of trial and error.
Christopher Voigt, an associate professor at the University of California, San Francisco, hopes to change that with software that automates the creation of “genetic circuits” in microbes. These circuits are the pathways of genes, proteins, and other biomolecules that the cells use to perform a particular task, such as breaking down sugar and turning it into fuel. Voigt and colleagues have so far made basic circuit components in E. coli. They are working with the large California biotechnology company Life Technologies to develop software that would let bioengineers design complete genetic circuits more easily.
Designing a microbe for a particular task would then be much like writing a new computer program, says Voigt. Just as programmers do not have to think about how electrons move through the gates in an integrated circuit, he says, biological engineers may eventually be able to design circuits for genes, proteins, and other biomolecules at a level of abstraction. “If we apply computational processes to things that bacteria can already do, we can get complete control over making spider silk, or drugs, or other chemicals,” he says.
Certain types of circuits could, for instance, help regulate the activity of bacteria that produce biofuels. Instead of outside controls, internal circuits could maintain the chemical levels and other conditions needed to keep bacteria producing at high yields. “We’re trying to make the cell understand where it is and what it should be doing based on its understanding of the world,” says Voigt. Trying to design such a control circuit without the help of a computer would take a lot of trial and error.
Voigt has now made a type of circuit component called a NOR gate in E. coli bacteria. NOR gates can be combined to perform any logical operation. In work described in the journal Nature, Voigt’s group also showed they could improve the quality of the output of bacterial circuits by having them work collectively, forming a circuit of NOR gates, one in each cell. Voigt has designed bacterial circuits to hook into natural bacterial communication systems called quorum sensing, so that the cells can “vote” on an output. This increases the quality of the computation peformed.
“This breakthrough work in synthetic biology expands our capacity to construct functional, programmable bacteria,” says James Collins, professor of biomedical engineering at Boston University who is not affiliated with Voigt’s team. Collins observes that the California researchers have learned to combine simple circuits in individual cells to make a more complex circuit at the population level. “This represents an important step towards harnessing the power of synthetic ecosystems for biotech applications,” he says.
The University of California researchers are now entering the second year of a research agreement with Life Technologies to develop software to automate the biological design process. “The vision is to take these software modules and develop them so that the process of biological parts selection and circuit design is far more automated and simplified than it is today,” says Todd Peterson, vice president of synthetic biology research and development at the company. The company hopes to incorporate most of the software modules being designed by Voigt’s group into its Vector NTI software by the end of spring 2012.
The inside story of how ChatGPT was built from the people who made it
Exclusive conversations that take us behind the scenes of a cultural phenomenon.
Sam Altman invested $180 million into a company trying to delay death
Can anti-aging breakthroughs add 10 healthy years to the human life span? The CEO of OpenAI is paying to find out.
ChatGPT is about to revolutionize the economy. We need to decide what that looks like.
New large language models will transform many jobs. Whether they will lead to widespread prosperity or not is up to us.
GPT-4 is bigger and better than ChatGPT—but OpenAI won’t say why
We got a first look at the much-anticipated big new language model from OpenAI. But this time how it works is even more deeply under wraps.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.