Evidence map›Paper›PMID 41808525›Full record

ReviewEnvironmental microbiology2026

Discovering PETases: An Interlink Between Engineering Enzymes and Microbiomes.

Diego Javier Jiménez, Alexandre Soares Rosado

Abstract readReview
In one paragraph

Review in Environmental microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Diego Javier JiménezBiological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Alexandre Soares RosadoBiological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.

Funding

King Abdullah University of Science and Technology BAS/1/1096-01-01
6 · The paper itself

Abstract

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.

Indexed as

BacteriaHydrolasesMicrobiotaPolyethylene TerephthalatesBiocatalysisBiodegradation, EnvironmentalMetagenomicsProtein EngineeringHydrolasesPolyethylene Terephthalatesbiocatalysismetagenomicsmicrobiome perturbationplastic degradationpolyethylene terephthalateterrestrial ecosystem

Identifiers

PMID41808525
PMCPMC12976661

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.