Project description:Rationale Microplastics are a pressing global concern and inhalation of microplastic fibers has been associated with interstitial and bronchial inflammation in flock workers. However, how microplastic fibers affect the lungs is unknown. Objectives Our aim was to assess the effects of 12x31 µm nylon 6,6 (nylon) and 15x52 µm polyethylene terephthalate (polyester) textile microplastic fibers on lung epithelial growth and differentiation. Methods We used human and murine alveolar and airway-type organoids as well as air-liquid interface cultures derived from primary lung epithelial progenitor cells and incubated these with either nylon or polyester fibers or nylon leachate. In addition, mice received one dose of nylon fibers or nylon leachate and 7 days later organoid-forming capacity of isolated epithelial cells was investigated. Results We observed that nylon microfibers, more than polyester, inhibited developing airway organoids and not established ones. This effect was mediated by components leaching from nylon. Epithelial cells isolated from mice exposed to nylon fibers or leachate, also formed fewer airway organoids, suggesting long-lasting effects of nylon components on epithelial cells. Part of these effects were recapitulated in human air-liquid interface cultures. Transcriptome analysis revealed upregulation of Hoxa5 post-exposure to nylon fibers. Inhibiting Hoxa5 protein during nylon exposure restored airway organoid formation, confirming Hoxa5's pivotal role in the effects of nylon. Conclusions These results suggest that components leaching from nylon 6,6 may especially harm developing airways and/or airways undergoing repair and we strongly encourage to characterize both hazard of and exposure to microplastic fibers in more detail.
Project description:Textile industry wastewater effluent dominated by Shewanellaceae, Bacteroidaceae and Pseudomonadaceae harbouring genes encoding catalytic enzymes for textile dye degradation potential from Gujarat, India
Project description:Microbiome site model is a Named Entity Recognition (NER) model that identifies and annotates the site of microbiome samples in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with site metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
