Natural evolution is a slow process that relies on gradual accumulation of genetic mutations. Scientists have discovered ways to speed up the process on a small scale, allowing them to rapidly create new proteins and other molecules.
This technique, known as directed evolution, has yielded new antibodies to treat cancer and other diseases, enzymes used in biofuel production and imaging agents for magnetic resonance imaging (MRI).
The team, led by the MIT Media Lab's assistant professor Kevin Esvelt, said its robotic platform can perform 100 times as many directed-evolution experiments in parallel, allowing for real-time progress monitoring. In addition to helping researchers develop new molecules more rapidly, the team said its technique could be used to simulate natural evolution and answer questions about how it works.
Directed evolution works by speeding up the accumulation and selection of novel mutations. For example, to create an antibody that binds to a cancerous protein, scientists would start with a test tube of hundreds of millions of yeast cells or other microbes that have been engineered to express mammalian antibodies on their surfaces.
These cells would be exposed to the cancer protein that researchers want the antibody to bind to, and researchers would pick out those that bind the best. Scientists would then introduce random mutations into the antibody sequence and screen these new proteins again, repeating the process many times until the best candidate emerges.
Esvelt developed an approach to speeding up directed evolution ten years ago, which harnessed bacteriophages (viruses that infect bacteria) to help proteins evolve faster toward a desired function.
The gene that researchers hope to optimise is linked to a gene needed for bacteriophage survival, and the viruses compete against each other to optimise the protein. The selection process is run continuously, shortening each mutation round to the lifespan of the bacteriophage (around 20 minutes) and can be repeated many times with no human intervention.
Using this method, known as phage-assisted continuous evolution (PACE), directed evolution can be performed one billion times faster than traditional experiments. However, evolution often fails to come up with a solution, requiring researchers to guess which new set of conditions will do better.
Described in Nature Methods, the MIT team’s system — named phage and robotics-assisted near-continuous evolution (PRANCE) — involves bacteriophage populations grown in wells of a 96-well plate instead of a single bioreactor. This allows for more evolutionary trajectories to occur simultaneously, with each viral population monitored by a robot as it goes through the evolution process.
When the virus succeeds in generating the desired protein, it produces a fluorescent protein that the robot can detect.
Erika DeBenedictis, co-lead author of the study, said that the robot can ‘babysit’ this population of viruses by measuring the readout, allowing it to see whether viruses are performing well. If the viruses are struggling to survive, meaning the target protein is not evolving in the desired way, the robot can replace the bacteria they’re infecting with a different strain making it easier for the viruses to replicate.
“We can tune these evolutions in real-time, in direct response to how well these evolutions are occuring,” added Emma Chory, co-lead author. “We can tell when an experiment is succeeding and we can change the environment, which gives us many more shots on goal, which is great from a bioengineering perspective and a basic science perspective.”
In experiments, researchers have used the platform to engineer a molecule that allows viruses to encode their genes in a new way, as well as evolving a molecule that allows viruses to incorporate a synthetic amino acid into the proteins they make.
They are now using PRANCE to try to make novel small-molecule drugs, with other possible applications including the evolution of enzymes that degrade plastics more efficiently.