Abstract
The application of zero-valent iron particles (ZVI) for the treatment of heavily polluted environment and its biological effects have been studied for at least two decades. Still, information on the impact on bacterial metabolic pathways is lacking. This study describes the effect of microscale and nanoscale ZVI (mZVI and nZVI) on the abundance of different metabolic pathways in freshwater bacterial communities. The metabolic pathways were inferred from metabolism modelling based on 16S rRNA gene sequence data using paprica pipeline. The nZVI changed the abundance of numerous metabolic pathways compared to a less influencing mZVI. We identified the 50 most affected pathways, where 31 were related to degradation, 17 to biosynthesis, and 2 to detoxification. The linkage between pathways was two times higher in nZVI samples compared to mZVI, and was specifically higher considering the arsenate detoxification II pathway. Limnohabitans and Roseiflexus were linked to the same pathways in both nZVI and mZVI. The prediction of metabolic pathways increases our knowledge of the impacts of nZVI and mZVI on freshwater bacterioplankton.
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Acknowledgements
This study was financially supported by the Technical University of Liberec within the project “Environmental fate, behaviour and biological effects of engineered nanomaterials” Project No. 30001. The authors acknowledge the assistance provided by the Research Infrastructures NanoEnviCz (Project No. LM2018124) and Pro-NanoEnviCz (Project No. CZ.02.1.01/0.0/0.0/16_013/0001821), supported by the Ministry of Education, Youth and Sports of the Czech Republic.
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NHAN and AŠ designed the original experiment published in Nguyen et al. 2018. NHAN. Wrote most of the manuscript. RŠ performed bioinformatic analysis of 16S rRNA sequences and participated in writing the manuscript. PFL advised on shaping the article, and together with AŠ, corrected the text. NHAN and RŠ contributed equally to this article.
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Nguyen, N.H.A., Špánek, R., Falagan-Lotsch, P. et al. Impact of Zero-Valent Iron on Freshwater Bacterioplankton Metabolism as Predicted from 16S rRNA Gene Sequence Libraries. Curr Microbiol 78, 979–991 (2021). https://doi.org/10.1007/s00284-021-02362-7
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DOI: https://doi.org/10.1007/s00284-021-02362-7