Landscape profiling of PET depolymerases using a natural sequence cluster framework

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Landscape profiling of PET depolymerases using a natural sequence cluster framework

Authors

Seo, H.; Hong, H.; Park, J.; Lee, S. H.; Ki, D.; Ryu, A.; Sagong, H.-Y.; Kim, K.-J.

Abstract

Since the demonstration that rapid polyethylene terephthalate (PET) decomposition using enzymes is feasible, a number of efficient depolymerases have been reported with the aim of resolving the plastic pollution issues. However, sporadic studies on enzymes with PET hydrolysis activity hinder the understanding of the distribution of potential PETases hidden in nature\'s repertoire, and subsequently, the identification of potent enzymes. Here, we present the clustering of 1,894 PETase candidates, which include the majority of known PETases, and describe their profiling. An archipelago landscape of 170 lineages shows distribution of 289 representative sequences with features associated with PET-degrading capabilities. A bird\'s-eye view of the landscape identifies three highly promising yet unexplored PETase lineages and two potent PETases, Mipa-P and Kubu-P. The engineered Mipa-PM19 and Kubu-PM12 variants exhibit both high PET hydrolysis activity and thermal stability. In particular, Kubu-PM12 outperformed the engineered benchmarks in terms of PET depolymerization in harsh environments, such as with high substrate load and ethylene glycol as the solvent. Our landscape framework and the identified variants assist in the understanding of how biological processes respond to solid-state and non-natural PET plastics.

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