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Plastic pollution and its global environmental impacts: a comprehensive review of microbial biodegradation mechanisms, plastic-degrading enzymes, emerging biotechnological strategies and artificial intelligence-driven approaches for sustainable plastic waste management
Summary
This review pulls together current research on using bacteria and enzymes to break down plastic waste instead of relying on landfills or incineration, which are costly and create their own pollution. Scientists are now pairing this "microbial recycling" with artificial intelligence to speed up the discovery of plastic-eating enzymes, though the technology still needs more real-world testing before it can be scaled up. This matters because plastic waste breaks down into micro- and nanoplastics that are turning up in our water, food and even our bodies, so finding better ways to eliminate plastic waste could reduce our long-term exposure to these particles.
Plastic pollution has emerged as a critical global environmental challenge due to the persistence, chemical complexity and resistance of synthetic polymers to natural degradation, resulting in the widespread accumulation of micro- and nanoplastics across terrestrial and aquatic ecosystems. Conventional plastic management approaches, including landfilling, incineration and physicochemical treatments, remain limited due to high energy demands, economic constraints and the generation of secondary pollutants. This review critically synthesizes current advances in microbial biodegradation, focusing on mechanistic pathways encompassing abiotic pretreatment, enzymatic depolymerization and microbial assimilation. It further emphasizes the use of artificial intelligence (AI) in the microbial degradation pathways providing a novel perspective that bridges experimental microbiology with data-driven enzyme discovery and process optimization. AI-based tools are critically evaluated for their ability to predict enzyme function, design microbial consortia and optimize degradation pathways, while also addressing current limitations related to data quality, model interpretability and experimental validation. Furthermore, this review identifies key research gaps, including the lack of standardized methodologies, limited scalability of laboratory findings and insufficient techno-economic assessments. These interdisciplinary advancements contribute toward the practice of sustainable plastic waste management and align strongly with the goals of United Nations Sustainable Development Goals (SDGs), particularly, SDG 6 for clean water and sanitation, SDG 12 for responsible consumption and production of plastic polymers and SDG 13 for sustainable climate.