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Multi-Omics Approach on the Ecotoxicological Assessment of Microplastics
Summary
This review examines the application of multi-omics approaches — including genomics, transcriptomics, proteomics, and metabolomics — to the ecotoxicological assessment of microplastics in living organisms. The authors synthesize how these integrated molecular tools are advancing understanding of the mechanistic pathways by which microplastics disrupt biological systems, offering a more comprehensive picture than single-endpoint toxicity studies.
In recent years, the production of plastic materials has shown dramatic growth worldwide. Their ever-expanding use leads to their subsequent entry into the environment, where these substances pose a significant risk to living organisms. Particularly, microplastics (MPs) are a new type of pollutant, including very small (<5-mm) pieces of plastic. The continuous increase in their concentration has recently become a major environmental issue because of their persistence, ubiquitous occurrence, and potential toxicity in aquatic habitats. Several ecotoxicological studies have reported the potential effects of MPs on aquatic and terrestrial environments. However, there are only a few studies that aim to understand the toxicological analysis of MPs with environmental pollutants in aquatic environments. In addition, MP's toxicological effects on freshwater aquatic organisms are still scarce. Most studies have reported the occurrence and distribution of MPs in freshwater and marine environments, but a comprehensive study of the effects of different types and sizes of MPs on freshwater aquatic organisms is lacking. Therefore, the objective of this study was to assess the ecotoxicological effect of MPs on zebrafish using the multi-omics approach, including genomics, transcriptomics, and metabolomics, to explore the ecotoxicological effects of MPs on gut microbiomes, metabolomic profiles, and genome-wide expression profiles is the scant research of ecotoxicology based on multi-omics (i.e., metabolomics and transcriptomics).