Introduction

Microplastic particles (MPs), defined as plastic fragments smaller than 5 mm, are pervasive pollutants that accumulate in ecosystems and the human food chain (1). Literature points at various health risks, including the induction of carcinogenesis (2). Emerging evidence from animal models (3) suggests that MPs may influence the gut microbiome, but the impact on the human gut microbiome remains poorly understood.

Aims & Methods

This study aimed to evaluate how various MP types influence gut microbial composition and metabolism using an ex vivo bioreactor model, with a focus on exploring potential carcinogenic effects arising from MP–microbiome interactions.
Stool samples from healthy donors were used to inoculate bioreactor cultures, which were maintained under anaerobic conditions for five days with daily nutrient feeding. These cultures were exposed to five common MP types—polystyrene (PS), polypropylene (PP), low-density polyethylene (LDPE), poly(methyl methacrylate) (PMMA), and polyethylene terephthalate (PET)—at concentrations mimicking both estimated human exposure (4) and higher doses to assess dose-dependence. Cell viability and total bacterial counts, as well as culture pH, were measured throughout the experiment. To further explore potential microbiome and metabolic alterations, 16S rRNA gene sequencing and targeted metabolomics were performed.

Results

MP exposure did not lead to significant changes in total or viable bacterial cell counts. However, MP-treated cultures exhibited a consistent and significant decrease in pH compared to controls, suggesting changes in microbial metabolic activity. Microbiome sequencing revealed plastic-type-dependent alterations in microbial composition, with certain bacterial taxa increasing or decreasing in abundance depending on the MP type. These shifts occurred across multiple genera within diverse families, including Lachnospiraceae, Oscillospiraceae, Enterobacteriaceae, and Ruminococcaceae, with the majority of changes occurring withing the phylum Bacillota. These compositional changes were accompanied by shifts in the metabolomic profiles, some of which correlated with the observed pH changes. Several plastic types induced changes in valeric acid levels, while individual MP types were associated with alterations in distinct metabolites such as uracil, lactic acid, and acetic acid.

Conclusion

This study demonstrates that MPs can affect gut microbial activity and metabolism without significantly altering overall bacterial abundance in the short term. The variation in microbiome response across plastic types highlights the complexity of MP-microbiome interactions. Changes in faecal pH are known to be associated with various gastrointestinal diseases (5). Interestingly, some of the MP-induced changes in microbial composition resembled patterns linked to diseases such as depression and colorectal cancer. In contrast, other changes showed patterns that differed from those typically associated with conditions like Parkinson’s disease and irritable bowel syndrome, highlighting the complexity of these associations and the dependency on the context. The bioreactor model provided a controlled environment for identifying direct MP-microbiome interactions; however, in humans, additional factors like diet, immune response, and individual microbiome variations play a role in determining long-term effects. Exposure duration may also play a critical role in shaping the extent and nature of microbiome alterations (6), underscoring the need for further research into the effects of chronic MP exposure and associated health risks.

References

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(2) Kumar, R., Manna, C., Padha, S., Verma, A., Sharma, P., Dhar, A., Ghosh, A., & Bhattacharya, P. (2022). Micro(nano)plastics pollution and human health: How plastics can induce carcinogenesis to humans?. Chemosphere, 298, 134267. https://doi.org/10.1016/j.chemosphere.2022.134267
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(5) Yamamura, R., Inoue, K. Y., Nishino, K., & Yamasaki, S. (2023). Intestinal and fecal pH in human health. Frontiers in Microbiomes, 2, 1192316.
(6) Yin, L., Yang, M., Teng, A., Ni, C., Wang, P., & Tang, S. (2025). Unraveling Microplastic Effects on Gut Microbiota across Various Animals Using Machine Learning. ACS nano, 19(1), 369–380. https://doi.org/10.1021/acsnano.4c07885