Robotic platform speeds up directed evolution

Researchers at the Massachusetts Institute of Technology (MIT) have developed a robotic platform to accelerate the directed evolution of molecules in the laboratory.

Natural evolution is a slow process that relies on a gradual accumulation of genetic mutations. Scientists have discovered ways to speed up the process on a small scale, allowing them to quickly make new proteins and other molecules.

Known as directed evolution, this technique has yielded new antibodies to treat cancer and other diseases, enzymes used in biofuel production, and magnetic resonance imaging (MRI) imaging agents.

The team, led by the MIT Media Lab’s assistant professor Kevin Esvelt said the robotic platform can run 100 times as many directed-evolution experiments in parallel, enabling real-time progress monitoring. In addition to helping researchers develop new molecules faster, the team said the technique could be used to simulate natural evolution and answer questions about how it works.

Directed evolution works by accelerating the accumulation and selection of new mutations. For example, to make 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 designed to express mammalian antibodies on their surface.

These cells would be exposed to the cancer protein that researchers want the antibody to bind to, and researchers would pick out those cells that bind best. Scientists would then introduce random mutations into the antibody sequence and rescreen these new proteins, repeating the process many times until the best candidate emerges.

A decade ago, Esvelt developed an approach to accelerate directed evolution, using bacteriophages (viruses that infect bacteria) to help proteins evolve faster toward a desired function.


The gene that researchers hope to optimize is linked to a gene necessary for bacteriophage survival, and the viruses compete with each other to optimize the protein. The selection process is performed continuously, shortening each round of mutations to the lifetime of the bacteriophage (about 20 minutes) and can be repeated many times without human intervention.

Using this method, known as phage-assisted continuous evolution (PACE), directed evolution can be performed a billion times faster than traditional experiments. However, evolution often doesn’t come up with a solution, forcing researchers to guess which new set of conditions will do better.

Described in Nature Methods, the MIT team’s system — called phage and robotics-assisted near-continuous evolution (PRANCE) — involves bacteriophage populations grown in wells of a 96-well plate rather than a single bioreactor. This allows more evolutionary trajectories to take place simultaneously, with each viral population being followed by a robot as it goes through the evolutionary process.

When the virus manages to generate the desired protein, it produces a fluorescent protein that the robot can detect.

Erika DeBenedictis, co-lead author of the study, said the robot can “watch” this population of viruses by measuring the readout so it can see if viruses are performing well. If the viruses struggle to survive, meaning the target protein doesn’t evolve in the desired way, the robot can replace the bacteria they infect with a different strain, making it easier for the viruses to multiply.

“We can tune these evolutions in real time, in direct response to how well these evolutions are happening,” added Emma Chory, co-lead author. “We can see when an experiment succeeds and we can change the environment, which gives us a lot more shots at the target, which is great from a bioengineering perspective and a basic science perspective.”

In experiments, researchers have used the platform to develop a molecule that allows viruses to encode their genes in a new way, and to develop a molecule that allows viruses to incorporate a synthetic amino acid into the proteins they make.

They are now using PRANCE to make new small-molecule drugs, with other potential applications, including the evolution of enzymes that break down plastic more efficiently.

Sajal Jain
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