A team of Penn State and University of Washington researchers recently developed a new algorithm to help prevent the failure of engineered genetic systems, or organisms engineered to have new capabilities.
“Engineered genetic systems are the source of biotechnology’s revolution,” said Howard Salis, Penn State associate professor of biological engineering and chemical engineering and corresponding author of the study. “Engineered organisms produce a cornucopia of biorenewable products, including biodegradable plastic bottles, therapeutic proteins and nutritional supplements. Probiotic bacteria have been engineered to live in your gut and cure metabolic disease. The was made possible by engineering organisms to produce .”
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The Salis Lab at Penn State University created thousands of highly non-repetitive genetic parts for engineering organisms with much greater genetic stability, using a newly developed algorithm that uses graph theory to solve a challenging computational problem.
In synthetic biology, engineers select genetic parts and assemble them into engineered genetic systems. However, problems arise when engineers reuse genetic parts in multiple locations or choose genetic parts with similar DNA sequences, which include genes and their controlling sequences.
“Engineers often build systems by repeatedly using the same components, whether it’s a multi-truss bridge or a multi-core CPU,” Salis said. “However, when synthetic biologists apply the same strategy to add new capabilities to organisms, millions of dollars of R&D [research and development] effort can be lost overnight. The key challenge is that reusing genetic parts will introduce long repetitive sequences of DNA into an organism, which often causes the organism to spontaneously break this DNA, removing the newly added capabilities.”
Repetitive DNA is modified by a biological process called homologous recombination, where two regions of DNA with similar nucleotide sequences will swap locations or be deleted. When these sequences are modified, it disrupts the cell’s ability to produce RNA and protein molecules. This process severely limits synthetic biologists’ ability to engineer cells that produce several types of RNA and protein molecules at the same time, which is necessary for many biotechnology applications.
“Our research has solved this challenge by developing a novel algorithm, the Non-Repetitive Parts Calculator, and using it to rapidly create thousands of highly non-repetitive genetic parts with desired functionalities,” Salis said. “We now have enough characterized non-repetitive genetic parts to completely rebuild the genomes of simple organisms.”
As part of the study published in , the research team designed, constructed and characterized 4,350 highly non-repetitive bacterial promoters and 1,722 highly non-repetitive yeast promoters. Promoters are genetic parts that express genes, using transcription to produce corresponding RNA molecules.
“These promoters enable the co-expression of many genes at desired expression levels, all at the same time without inadvertently introducing repetitive DNA,” Salis said. “It increases the availability of characterized non-repetitive genetic parts from dozens to thousands.”
According to Salis, the team’s unique solution can prevent significant R&D losses when engineering organisms.
“Large Fortune 500 companies have spent many millions of dollars on engineering metabolic pathways in organisms to produce a desired product,” he said. “And then their engineered organism self-deletes the introduced DNA when grown overnight in a bioreactor, shutting down all production, a costly failure. Our non-repetitive genetic parts will prevent spontaneous failures like these from occurring.”
Along with Salis, other researchers involved in the study from Penn State include Ayaan Hossain, graduate research assistant in chemical engineering; and Sean Halper, Daniel Centar and Alexander Reis, graduate students in chemical engineering. Researchers from the University of Washington include Eirberto Lopez, research scientist/engineer; Devin Strickland, senior research scientist; and Eric Klavins, professor and chair of the Electrical and Computer Engineering Department.
The study was supported by funding from the Air Force Office of Scientific Research, the Defense Advanced Research Projects Agency, the United States Department of Energy, and a Graduate Research Innovation award to Hossain from Penn State’s Huck Institutes of the Life Sciences.
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