Polyethylene terephthalate (PET), an abundant synthetic polyester, is the only plastic that has been enzymatically recycled at an industrial scale. Over the last decades, research efforts have focused on screening and engineering PET-degrading hydrolases (PETases), aiming to identify variants that can operate efficiently in both environmental and industrial settings. The detection of potential PETases from marine and terrestrial ecosystems has primarily been conducted via metagenomics using homology strategies. However, the use of benchmark PETases as references has limited the searches, narrowing the sequence landscape. Currently, there remains a need to identify efficient thermophilic, halotolerant and pH-robust PETases for the industrial biocatalysis of PET. In line with this, in this article, we discuss recent findings related to the following topics: (i) the identification of suitable ecosystems for mining PETases; (ii) the discovery of PETases via the restructuring of microbiomes; (iii) advancements in metagenomics and artificial intelligence (AI)-based approaches for the detection and ranking of PETases and (iv) the future of PET biocatalysis. Overall, we suggest that disrupting microbiomes with polyester-rich substrates, combined with innovative computational and AI-based strategies, can be an effective pathway for the discovery of PETases that can be used as scaffolds for protein engineering and biotechnological applications.
Jiménez et al. (Sun,) studied this question.