ReviewFrontiers in microbiology2026
Engineered microbes to enable a circular economy for biodegradable plastics.
Review in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Plastic pollution resulting from the continued dominance of fossil-derived polymers is a major global environmental challenge. Although biodegradable plastics, such as polylactic acid (PLA), polyhydroxyalkanoates (PHAs), polybutylene succinate (PBS), polybutylene adipate terephthalate (PBAT), and related materials, are increasingly being deployed as alternatives, their environmental performance is frequently constrained by infrastructure gaps, uncontrolled carbon loss, and incomplete degradation under realistic conditions. Therefore, biodegradability alone does not guarantee circularity of the material. To address this, intentional rerouting of plastics and their monomers into upcycling streams offers a widely applicable solution. This review advances the circular bioeconomy framework built on engineered depolymerization and metabolic bio-funneling of biodegradable and selected synthetic plastics. We present recent progress in enzyme-mediated polyester breakdown, emphasizing hydrolases and oxidoreductases, the kinetic and structural determinants of activity, and protein engineering strategies that broaden substrate scope and enhance operational stability. We then organize bio-upcycling strategies according to key metabolic entry nodes: pyruvate, acetyl-CoA/β-oxidation, and aromatic/dicarboxylate pathways, to demonstrate how plastic-derived monomers can be systematically redirected toward platform chemicals, fuels, specialty monomers, and next-generation biopolymers through pathway rewiring, flux control, and redox balance. In addition to biological conversion, we evaluate chemo-biological hybrid systems and integrated techno-economic and life cycle considerations, including process efficiency, enzyme cost, toxicity mitigation, and infrastructure compatibility. We further highlight emerging tools, such as systems biology, adaptive laboratory evolution, synthetic consortia design, and machine-learning-guided protein optimization, which accelerate the design-build-test-learn cycle for scalable microbial platforms for plastic upcycling. Collectively, this study reframes biodegradable plastics not as materials designed merely to disappear but as programmable carbon reservoirs that can be captured, upgraded, and reintegrated into biomanufacturing value chains. Actively closing the loop through engineered bio-upcycling, rather than relying on passive environmental degradation, offers a practical pathway to align plastic utility with environmental sustainability and achieve a truly circular bioeconomy.
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Registered trials
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.