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12 December 2024 Identification of seasonal differences in freshwater biofouling organisms on flexible sensor substrates using next generation sequencing
Emma A. Loder, Emma S. Goodwyn, R Sophia, Antonopoulos Raithel, Qihua Wu, Paul L. Durham
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Abstract

There is an increasing demand for development of sensors that continuously monitor freshwater safety and quality. Developing sensors with flexible substrates is of interest due to their malleability, cost-effectiveness, and durability. The accuracy and performance of sensors submerged in water for long times can be reduced by biofouling. The goal of this study was to investigate seasonal variation in biofouling microorganisms on two flexible substrates suspended in river and pond water obtained during the summer, winter, or spring. Next generation sequencing of the 16S and 18S rRNA genes was used to identify the most abundant adherent prokaryotic and eukaryotic microorganisms on flexible substrates cyclic olefin copolymer (COC) and polyethylene terephthalate (PET). At the domain level, Bacteria were the most abundant biofouling organisms on both COC and PET in river and pond water samples during each season. Protista were the next most abundant microorganism in river water during the summer. Fungi and Archaea were the next most abundant phyla in winter river and pond water. At the lower taxonomic levels, differences in biofouling organisms were observed seasonally and between river and pond water samples. Therefore, different strategies may be required to minimize their adherence to freshwater sensors made from flexible substrates.

Emma A. Loder, Emma S. Goodwyn, R Sophia, Antonopoulos Raithel, Qihua Wu, and Paul L. Durham "Identification of seasonal differences in freshwater biofouling organisms on flexible sensor substrates using next generation sequencing," BIOS 95(4), 220-231, (12 December 2024). https://doi.org/10.1893/BIOS-D-24-00011
Received: 21 May 2024; Accepted: 19 September 2024; Published: 12 December 2024
KEYWORDS
biofouling
microorganisms
next-generation sequencing
pond
river
sensors
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