Evidence map›Paper›PMID 41373776›Full record

ReviewInternational journal of molecular sciences2025

Engineering of Synthetic Microbial Consortia for Sustainable Management of Wastewater and Polyethylene Terephthalate: A Comprehensive Review.

Yiqun Zhou, Muhammad Zeeshan Ul Haq

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yiqun ZhouFaculty of Science, The University of Hong Kong, Hong Kong SAR 999077, China.
Muhammad Zeeshan Ul HaqSpice and Beverage Research Institute, Chinese Academy of Tropical Agriculture Science, Wanning 571533, China.ORCID 0009-0004-3746-616X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plastic pollution and wastewater have become the leading environmental concerns due to their harmful effects on human health and pose a severe threat to the biosphere. Polyethylene terephthalate (PET) is one of the most widely used plastics worldwide, but it is resistant to natural degradation. Additionally, the complex pollutants in wastewater demand advanced remediation strategies. Although physicochemical methods are commonly used for PET degradation and wastewater treatment, bioremediation with microorganisms offers a greener and more eco-friendly alternative. This review focuses on the molecular mechanisms and engineering of synthetic microbial consortia (SMC) for the bioremediation of wastewater and PET plastics. It examines the rational design of SMCs, utilizing both bottom-up and top-down methods, and emphasizes the importance of quorum sensing and metabolite cross-feeding in maintaining the stability and functionality of the consortium. Furthermore, the review critically assesses how CRISPR-Cas9 enables precise genome editing for robust pathway engineering and stress resilience, while Machine Learning provides predictive models to optimize consortium composition and function, thereby advancing SMC capabilities for both applications. These developments highlight SMC as a promising, eco-friendly, and efficient biological platform to tackle wastewater challenges and plastic pollution simultaneously.

Indexed as

Microbial ConsortiaPolyethylene TerephthalatesWastewaterWater Pollutants, ChemicalBiodegradation, EnvironmentalPolyethylene TerephthalatesWastewaterWater Pollutants, ChemicalCRISPR-Cas9cross-feedingenzyme engineeringmachine learningpolyethylene terephthalate (PET)quorum sensingsynthetic microbial consortiawastewater treatment

Identifiers

PMID41373776
PMCPMC12692444

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.