An enzyme variant created by engineers and scientists at The University of Texas at Austin can break down environment-throttling plastics that typically take centuries to degrade in just a matter of hours to days, according to the university. The discovery, published in “Nature,” could help solve one of the world’s most pressing environmental problems: what to do with the billions of tons of plastic waste piling up in landfills. The enzyme reportedly has the potential to supercharge recycling on a large scale that would allow major industries to reduce their environmental impact by recovering and reusing plastics at the molecular level.
“The possibilities are endless across industries to leverage this leading-edge recycling process,” says Hal Alper, professor in the McKetta Department of Chemical Engineering at UT Austin. “Beyond the obvious waste management industry, this also provides corporations from every sector the opportunity to take a lead in recycling their products. Through these more sustainable enzyme approaches, we can begin to envision a true circular plastics economy.”
The project focuses on polyethylene terephthalate (PET), a significant polymer found in most consumer packaging, which makes up 12% of all global waste, according to UT Austin. The enzyme reportedly was able to complete a “circular process” of breaking down the plastic into smaller parts (depolymerization) and then chemically putting it back together (repolymerization). In some cases, these plastics can be fully broken down to monomers in as little as 24 hours.
Researchers at the Cockrell School of Engineering and College of Natural Sciences used a machine learning model to generate novel mutations to a natural enzyme called PETase that allows bacteria to degrade PET plastics. The model predicts which mutations in these enzymes would accomplish the goal of quickly depolymerizing post-consumer waste plastic at low temperatures. Through this process, which included studying 51 different post-consumer plastic containers, five different polyester fibers and fabrics and water bottles all made from PET, the researchers proved the effectiveness of the enzyme, which they are calling FAST-PETase (functional, active, stable and tolerant PETase).
“This work really demonstrates the power of bringing together different disciplines, from synthetic biology to chemical engineering to artificial intelligence,” said Andrew Ellington, professor in the Center for Systems and Synthetic Biology whose team led the development of the machine learning model.
The team reportedly plans to work on scaling up enzyme production to prepare for industrial and environmental application. The researchers have filed a patent application for the technology and are eying several different uses. Cleaning up landfills and greening high waste-producing industries are the most obvious. But another key potential use is environmental remediation. The team is looking at a number of ways to get the enzymes out into the field to clean up polluted sites.
Alper, Ellington, associate professor of chemical engineering Nathaniel Lynd and Hongyuan Lu, a postdoctoral researcher in Alper’s lab, led the research. Danny Diaz, a member of Ellington’s lab, created the machine learning model. Other team members include from chemical engineering: Natalie Czarnecki, Congzhi Zhu and Wantae Kim; and from molecular biosciences: Daniel Acosta, Brad Alexander, Hannah O. Cole, Yan Jessie Zhang and Raghav Shroff. The work was funded by ExxonMobil’s research and engineering division as part of an ongoing research agreement with UT Austin.
For more information, visit: www.utexas.edu
