Computational identification of plastic-degrading enzymes in ocean microbiomes

With about 7 billion metric tons of plastic waste already in our environment and over 20 million metric tons of plastic produced annually, plastic waste has become a major global problem. Current methods to address this problem, such as incineration and landfills, are unsustainable and environmentally harmful. More trending approaches, such as plastic degradation using microbial enzymes, are rarely efficient enough to be applied industrially. To fill this gap in our knowledge, we developed a computational method called IPDE (Identification of Plastic Degrading Enzymes) to systematically identify promising enzymes, enzyme combinations, and microbial species for effective plastic waste degradation. Using IPDE, we discovered 50 and 86 enzymes in ocean and topsoil microbiomes, respectively, with at least 46% of these 136 enzymes highly likely to have a role in plastic degradation. Additionally, we identified 43 ocean enzyme combinations and 12 topsoil enzyme combinations, 20% of which contain enzymes that co-occur in the same metabolic pathways. Furthermore, we found 72 operational taxonomic units, with genus-level information available for 20 of them and 18 (25%) of them suggested in literature to be associated with plastic degradation. Our study identified promising plastic-degrading enzyme candidates for future experimental validation, functional studies, protein engineering, and industrial applications. The IPDE tool, which can be applied to other samples for further validation, is freely accessible at https://github.com/SophieL8/Plastic-degrading-enzymes .

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-05-02
DOI
https://doi.org/10.1038/s41598-025-99275-3
Citations
3
Primary Topic
Microplastics and Plastic Pollution
Type
article
Field-Weighted Citation Impact
1.51
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Computational identification of plastic-degrading enzymes in ocean microbiomes

Wen Cai Zhang, Sophie Li
3 citations
Scientific Reports
Microplastics and Plastic Pollution
1.51
article

Computational identification of plastic-degrading enzymes in ocean microbiomes

Wen Cai Zhang, Sophie Li
article en
3 citations

Abstract

With about 7 billion metric tons of plastic waste already in our environment and over 20 million metric tons of plastic produced annually, plastic waste has become a major global problem. Current methods to address this problem, such as incineration and landfills, are unsustainable and environmentally harmful. More trending approaches, such as plastic degradation using microbial enzymes, are rarely efficient enough to be applied industrially. To fill this gap in our knowledge, we developed a computational method called IPDE (Identification of Plastic Degrading Enzymes) to systematically identify promising enzymes, enzyme combinations, and microbial species for effective plastic waste degradation. Using IPDE, we discovered 50 and 86 enzymes in ocean and topsoil microbiomes, respectively, with at least 46% of these 136 enzymes highly likely to have a role in plastic degradation. Additionally, we identified 43 ocean enzyme combinations and 12 topsoil enzyme combinations, 20% of which contain enzymes that co-occur in the same metabolic pathways. Furthermore, we found 72 operational taxonomic units, with genus-level information available for 20 of them and 18 (25%) of them suggested in literature to be associated with plastic degradation. Our study identified promising plastic-degrading enzyme candidates for future experimental validation, functional studies, protein engineering, and industrial applications. The IPDE tool, which can be applied to other samples for further validation, is freely accessible at https://github.com/SophieL8/Plastic-degrading-enzymes .

Scientific ReportsVol. 15(1)
University of Central Florida (US)
Life below water
Openalex Percentile: Top 19%
Microplastics and Plastic Pollution
1.51
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Computational identification of plastic-degrading enzymes in ocean microbiomes — Wen Cai Zhang, Sophie Li · Scientific Reports (2025) | TGRS Research Map | TGRS