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New Biotechnology
Article . 2025 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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ZENODO
Other literature type . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Conference object . 2024
License: CC BY
Data sources: Datacite
ZENODO
Conference object . 2024
License: CC BY
Data sources: Datacite
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Identification and expression of novel polyester-degrading enzymes for application on mixed plastic-containing waste

Authors: Allo, Chloe; Kremser, Klemens; Ribitsch, Doris; Gübit, Georg;

Identification and expression of novel polyester-degrading enzymes for application on mixed plastic-containing waste

Abstract

Identification and expression of novel polyester-degrading enzymes for application on mixed plastic-containing wasteAuthors: Chloé Allo, Klemens Kremser, Doris Ribitsch, Georg Gübitz Presented at ECB 2024, 30 June - 3 July 2024, Rotterdam. The MixMatters project develops an Integrated System to separate and valorise bio-waste and plastic fractions from the agri-food sector. This study focuses on the Valorisation Hub, where mixed waste streams, including plastic-contaminated fractions, are processed using enzymatic approaches. Two novel polyester-degrading enzymes (Abc and Scc), identified from soil and wastewater metagenomes, were successfully expressed in Escherichia coli and tested for their ability to hydrolyse plastic materials such as polyethylene terephthalate (PET). These enzymes could enable the step-wise recovery of plastic monomers, opening new possibilities for sustainable plastic waste valorisation. Their performance will be further evaluated on plastic-organic mixed waste streams from MixMatters, with the aim of integrating enzymatic plastic recycling into industrial biorefinery processes.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold