Advanced biotechnological tools towards achieving United Nations Sustainable Development Goals (UNSDGs) for mitigation of microplastics from environments: a review
Abstract These days, we can use molecular biology methods like genetic engineering and gene editing to create modified microorganisms that can efficiently degrade microplastics. The background to recognize new species of microorganisms, gene pools, interaction networks, and pathways of reaction from...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-04-01
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| Series: | Discover Sustainability |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s43621-025-01080-5 |
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| Summary: | Abstract These days, we can use molecular biology methods like genetic engineering and gene editing to create modified microorganisms that can efficiently degrade microplastics. The background to recognize new species of microorganisms, gene pools, interaction networks, and pathways of reaction from different microbial consortiums is provided by techniques like metagenomics, meta-transcriptomics, meta-proteomics, metabolomics, microbiomics, etc. High-level expression of enzymes that break down plastic, including reductases, hydrolases, depolymerases, and esterases, has also been found using meta-omics techniques. These methods’ great accuracy, speed, and sensitivity make them applicable to studies on the role of microbiota in the breakdown of microplastics (MPs). Furthermore, these new enzymes’ attachment to the polymer substrate can be predicted using computational tools like molecular docking and computational biology, and this prediction can be verified in vitro for environmentally viable applications. In the literature that is currently accessible, the Sustainable Development Goals (SDGs) of the United Nations (UN) are also examined in relation to microplastic (MP) reduction. In order to comprehend the potential of microbes in the microplastics degradation, this review examines the role of meta-omics and computational tools to achieve the SDGs of the United Nations (UN) in a cumulative way. Future directions have also been covered, and the review also emphasizes the difficulties encountered when applying genome engineering and meta-omics techniques. |
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| ISSN: | 2662-9984 |