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Engineering microbial division of labor for plastic upcycling

Environmental Studies and Forestry

Engineering microbial division of labor for plastic upcycling

T. Bao, Y. Qian, et al.

Discover how a synthetic microbial consortium created by researchers Teng Bao, Yuanchao Qian, Yongping Xin, James J. Collins, and Ting Lu offers a groundbreaking solution to plastic pollution by efficiently upcycling polyethylene terephthalate (PET) into valuable chemicals. This innovative approach showcases enhanced degradation capabilities and the production of useful bioproducts.

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~3 min • Beginner • English
Abstract
Plastic pollution is rapidly increasing worldwide, causing adverse impacts on the environment, wildlife and human health. One tempting solution to this crisis is upcycling plastics into products with engineered microorganisms; however, this remains challenging due to complexity in conversion. Here we present a synthetic microbial consortium that efficiently degrades polyethylene terephthalate hydrolysate and subsequently produces desired chemicals through division of labor. The consortium involves two Pseudomonas putida strains, specializing in terephthalic acid and ethylene glycol utilization respectively, to achieve complete substrate assimilation. Compared with its monoculture counterpart, the consortium exhibits reduced catabolic cross-talk and faster deconstruction, particularly when substrate concentrations are high or crude hydrolysate is used. It also outperforms monoculture when polyhydroxyalkanoates serves as a target product and confers flexible tuning through population modulation for cis-cis muconate synthesis. This work demonstrates engineered consortia as a promising, effective platform that may facilitate polymer upcycling and environmental sustainability.
Publisher
Nature Communications
Published On
Sep 26, 2023
Authors
Teng Bao, Yuanchao Qian, Yongping Xin, James J. Collins, Ting Lu
Tags
plastic pollution
microbial consortia
polyethylene terephthalate
upcycling
bioproducts
Pseudomonas putida
sustainability
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