A High-Throughput Screening Platform for Engineering Poly(ethylene Terephthalate) Hydrolases

Thomas Groseclose, Erin Kober, Matilda Clark, Benjamin Moore, Shounak Banerjee, Victoria Bemmer, Gregg Beckham, Andrew Pickford, Taraka Dale, Hau Nguyen

Research output: Contribution to journalArticlepeer-review

Abstract

The ability of enzymes to hydrolyze the ubiquitous polyester, poly(ethylene terephthalate) (PET), has enabled the potential for bioindustrial recycling of this waste plastic. To date, many of these PET hydrolases have been engineered for improved catalytic activity and stability, but current screening methods have limitations in screening large libraries, including under high-temperature conditions. Here, we developed a platform that can simultaneously interrogate PET hydrolase libraries of 10^4-10^5 variants (per round) for protein solubility, thermostability, and activity via paired, plate-based split green fluorescent protein and model substrate screens. We then applied this platform to improve the performance of a benchmark PET hydrolase, leaf-branch compost cutinase, by directed evolution. Our engineered enzyme exhibited higher catalytic activity relative to the benchmark, LCC-ICCG, on amorphous PET film coupon substrates (~9.4% crystallinity) in pH-controlled bioreactors at both 65 degrees C (8.5% higher conversion at 48 h and 38% higher maximum rate, at 2.9% substrate loading) and 68 degrees C (11.2% higher conversion at 48 h and 43% higher maximum rate, at 16.5% substrate loading), up to 48 h, highlighting the potential of this screening platform to accelerate enzyme development for PET recycling.
Original languageAmerican English
Pages (from-to)14622-14638
Number of pages17
JournalACS Catalysis
Volume14
Issue number19
DOIs
StatePublished - 2024

NREL Publication Number

  • NREL/JA-2A00-90489

Keywords

  • directed evolution
  • enzymatic plastic degradation
  • high-throughput screening
  • PET hydrolase
  • plastic recycling
  • poly(ethylene terephthalate) (PET)
  • protein engineering
  • split GFP

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