Environmental identification of novel enzymes against heteroatomic plastics

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Abstract

Better enzymes are needed to develop sustainable methods to recycle plastics with C-X heterobonds such as polyurethane (PUR) and nylon, for which no industrial-scale solutions exist. Current methods rely largely on sequence mining based on a small number of known enzymes. Here we expand the pool of PURases and nylonases by bioprospecting legacy plastic waste with fluorophore plastic mimics combined with FACS. We identify 29 plastic-degrading bacteria, from which 12 enzymes are identified by mass spectrometry and homology searches. Compared to existing enzymes, these enzymes are superior in thermostability and the ability to hydrolyse different high-molecular weight PUR oligomers and nylon textiles. To our knowledge, this is the first reported example of enzymes capable of hydrolysing longer chains of PUR and nylon. This study significantly increases the number of known PURases and nylonases and provides starting points for optimization campaigns through protein engineering and for in silico discovery.
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Abstract Better enzymes are needed to develop sustainable methods to recycle plastics with C-X heterobonds such as polyurethane (PUR) and nylon, for which no industrial-scale solutions exist. Current methods rely largely on sequence mining based on a small number of known enzymes. Here we expand the pool of PURases and nylonases by bioprospecting legacy plastic waste with fluorophore plastic mimics combined with FACS. We identify 29 plastic-degrading bacteria, from which 12 enzymes are identified by mass spectrometry and homology searches. Compared to existing enzymes, these enzymes are superior in thermostability and the ability to hydrolyse different high-molecular weight PUR oligomers and nylon textiles. To our knowledge, this is the first reported example of enzymes capable of hydrolysing longer chains of PUR and nylon. This study significantly increases the number of known PURases and nylonases and provides starting points for optimization campaigns through protein engineering and for in silico discovery. Competing Interest Statement The authors have declared no competing interest.

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europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
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License: CC-BY-NC-ND-4.0