A group of scientists at the University of Texas at Austin have created a modified enzyme that can break down plastics that would otherwise take centuries to degrade in a matter of days.
The researchers, who published their findings in the peer-reviewed journal Nature last week, used machine learning to land on mutations to create a fast-acting protein that can break down building blocks of polyethylene terephthalate (PET), a synthetic resin used in fibers for clothing and plastic that, per the study, accounts for 12 percent of global waste.
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It does so through a process called depolymerization, in which a catalyst separates the building blocks that make up PET into their original monomers, which can then be repolymerized—built back into virgin plastic—and converted into other products. Most impressively, the enzymes broke down the plastic in one week.
“One thing we can do is we can break this down into its initial monomers,” Hal Alper, professor in Chemical Engineering and author on the paper, told Motherboard over the phone. “And that’s what the enzyme does. And then once you have your original monomer, it’s as if you’re making fresh plastic from scratch, with the benefit that you don’t need to use additional petroleum resources.”
“This has advantages over traditional belt recycling,” Alper added. “If you were to melt the plastic and then remold it, you’d start to lose the integrity of the plastic each round that you go through with recycling. Versus here, if you’re able to depolymerize and then chemically repolymerize, you can be making virgin PET plastic each and every time.”
Their work adds to an existing line of query on plastic-eating enzymes, which were first recorded in 2005 and have since been followed by the discovery of 19 distinct enzymes, the paper notes. These are derived from naturally occurring bacteria that have been located living on plastic in the environment.
But many of these naturally-occurring enzymes are made up of permutations of proteins that function well in their specific environments, but are limited by temperature and pH conditions, and thus can’t be used in a wide range of settings, like across recycling centers, the authors argue. The enzyme Alper and his team discovered, by contrast, can break down 51 types of PET across a range of temperature and pH conditions.
The researchers named the enzyme FAST-PETase, acronymic for “functional, active, stable, and tolerant PETase,” and they landed on its exact structure using machine learning. An algorithm was fed with 19,000 protein structures and taught to predict the positions of amino acids in a structure that are not optimized for their local environments. They also used the formula to rearrange amino acids from existing types of PETase into new positions, identified improved combinations, and landed on one structure that saw 2.4 times more activity than an existing PETase enzyme at 40 degrees Celsius and 38 times more activity at 50 degrees Celsius.
It was then tested across a range of temperatures and pH conditions, and continued to outperform existing variants.
“What you see in nature is probably somewhat optimal, at least within the local environment around each and every one of those amino acids,” Alper said. “We can start looking at the protein of interest, and start going through each and every one of the amino acids in there and looking at its own microenvironment and seeing what fits and what doesn’t fit.”
Alper and his team’s hope is that their enzyme will be more scalable than most, and will truly put PET-ase to the test of tackling the global plastics crisis. Already able to withstand a range of conditions, FAST-PETase must now prove that it can be both “portable and affordable at large industrial scale.”
First, Alper says, he and his team must test FAST-PETase on the wide range of different types of PET found in the waste stream, and the detritus that’s often found in plastic bottles or on top of plastic containers when it’s recycled. Should the researchers find an enzyme or group of enzymes with the robustness to be used practically, they believe it can help tackle the “billions of tons” of waste in our environment.
