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Microbially driven microplastic degradation: From mining functional microbiota to enhancing remediation potential in diverse environments
Summary
Microplastics—tiny plastic bits linked to health concerns—are piling up in soil, water, and even animal guts, but scientists are finding a natural cleanup crew: bacteria and other microbes that can break them down. This review pulled together findings from 78 studies to identify which microbes work best in which environments (soil-dwelling ones were most effective overall), creating a roadmap for using these organisms in real-world pollution cleanup rather than just lab experiments. While this research focuses on environmental remediation rather than direct human health testing, reducing microplastic pollution at its source could ultimately lower our exposure through food, water
Microplastic (MPs) pollution poses a global threat to ecosystems and human health. Traditional physicochemical methods face limitations like high cost, inefficiency, and secondary pollution, underscoring the need for green remediation. While microbial degradation holds promise, research remains largely limited to lab studies of single environments, lacking systematic multi-environment strain collections and practical application assessments. This review summarizes common screening/validation methods, degradation mechanisms, and influencing factors of microplastic-degrading microorganisms (MPDMs). By reviewing 78 studies, 197 degrading microorganisms/taxa from four typical environments (soil, marine, freshwater, animal gut) were sorted, with 152 analyzed for degradation efficiency. The degradation efficiencies across different environments were compared, with the maximum efficiency order being soil > freshwater > marine > animal gut, and the overall average efficiency order being soil ≈ freshwater > marine ≈ animal gut. Recommendations for efficient culture conditions were proposed for different environments, and high-potential strains were recommended, including multi-environment efficient ones (e.g., Bacillus and multiple bacterial consortia) and environment-specific superior strains (e.g., Rhodococcus, Oceanimonas, and Enterobacter). Finally, methods such as dominant strain screening, acclimatization, genetic engineering modification, and synthetic taxa construction via machine learning are proposed to enhance practical applicability. This study not only establishes a scenario-specific microbial remediation resource pool and quantifies their degradation efficiencies, providing critical data support and strategic guidance for the development of in-situ microbial remediation technologies at targeted contaminated sites, but also lays a solid foundation for translating laboratory findings into practical field applications in future research.