Recent Advances in Microbial and Enzymatic Bioremediation of Recalcitrant Contaminants: Integrating Metabolic Pathways with Frontier Technologies and Machine Learning

Environmental pollution is a pressing global issue, characterized by diverse contaminants and the unsustainability of traditional treatment methods. Biodegradation offers an effective strategy to address this challenge, targeting pollutants such as antibiotics, pharmaceuticals, pesticides, dyes, polycyclic aromatic hydrocarbons, petroleum-derived compounds, plastics, persistent polymers, gaseous substances and so on. This review systematically summarizes recent advances in the use of microorganisms and enzymes for pollutant removal or transformation. Studies on microorganisms and enzymes capable of degrading different pollutant classes are presented, along with their degradation mechanisms and practical feasibility, providing guidance for researchers and industry practitioners and highlighting candidates with higher degradation potential. Furthermore, emerging approaches, including enzyme evolution and gene editing, synergistic strategies, immobilization technologies, and machine-learning-assisted optimization, are discussed as ways to enhance biodegradation stability and efficiency. Notably, directed evolution has achieved up to 400-fold enhancement in catalytic efficiency, while machine-learning models have reached high classification accuracy (AUC = 0.99) in predicting pollutant degradation.

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Publication Details

Journal
Microorganisms
Published
2026-10-22
DOI
https://doi.org/10.3390/microorganisms14112414
Primary Topic
Microbial bioremediation and biosurfactants
Type
article
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article

Recent Advances in Microbial and Enzymatic Bioremediation of Recalcitrant Contaminants: Integrating Metabolic Pathways with Frontier Technologies and Machine Learning

Jijie Zhang, Chen Shen, Wenchao Peng, Zijian Zhang et al.
Microorganisms
Microbial bioremediation and biosurfactants
article

Recent Advances in Microbial and Enzymatic Bioremediation of Recalcitrant Contaminants: Integrating Metabolic Pathways with Frontier Technologies and Machine Learning

Jijie Zhang, Chen Shen, Wenchao Peng, Zijian Zhang, Jiayao Li, Xiaomeng Guo, Ning Li
article en

Abstract

Environmental pollution is a pressing global issue, characterized by diverse contaminants and the unsustainability of traditional treatment methods. Biodegradation offers an effective strategy to address this challenge, targeting pollutants such as antibiotics, pharmaceuticals, pesticides, dyes, polycyclic aromatic hydrocarbons, petroleum-derived compounds, plastics, persistent polymers, gaseous substances and so on. This review systematically summarizes recent advances in the use of microorganisms and enzymes for pollutant removal or transformation. Studies on microorganisms and enzymes capable of degrading different pollutant classes are presented, along with their degradation mechanisms and practical feasibility, providing guidance for researchers and industry practitioners and highlighting candidates with higher degradation potential. Furthermore, emerging approaches, including enzyme evolution and gene editing, synergistic strategies, immobilization technologies, and machine-learning-assisted optimization, are discussed as ways to enhance biodegradation stability and efficiency. Notably, directed evolution has achieved up to 400-fold enhancement in catalytic efficiency, while machine-learning models have reached high classification accuracy (AUC = 0.99) in predicting pollutant degradation.

MicroorganismsVol. 14(11)
Tianjin University of Science and Technology (CN), Tianjin University (CN), Nankai University (CN), Hebei University of Science and Technology (CN)
Openalex Percentile: Top 25%
Microbial bioremediation and biosurfactants
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Recent Advances in Microbial and Enzymatic Bioremediation of Recalcitrant Contaminants: Integrating Metabolic Pathways with Frontier Technologies and Machine Learning — Jijie Zhang, Chen Shen, et al. · Microorganisms (2026) | TGRS Research Map | TGRS