3.8 Article

Differential utilisation of dissolved organic matter compound fractions by different biofilter microbial communities

Journal

AQUA-WATER INFRASTRUCTURE ECOSYSTEMS AND SOCIETY
Volume 72, Issue 10, Pages 1837-1851

Publisher

IWA PUBLISHING
DOI: 10.2166/aqua.2023.036

Keywords

biofiltration; community assembly; dissolved organic matter; LC-OCD; microbial degradation

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This study investigated the abilities of microbial communities from different parts of a biofilter to process DOM. The bottom community showed the highest growth rate on DOM and had a higher preference for complex DOM fractions. The higher relative abundance of the Curvibacter genus in the bottom community suggests its crucial role in degrading complex DOM fractions.
Dissolved organic matter (DOM) is a complex mixture of carbon-based compounds present in natural aquatic systems, which significantly affects drinking water treatment processes. Biofiltration, utilising biologically active beds of porous medium, offers a low-energy and low-chemical solution for controlling bioavailable DOM. However, the impact of microbial community composition on DOM degradation in biofilters remains poorly understood. This study aimed to explore the abilities of microbial communities from the top, middle, and bottom (TOP, MID, and BOT) of a biofilter to process DOM. We showed varying growth rates on the DOM, with bottom community exhibiting the highest cell abundance at the end of the experiment (1.83 x 10(6) +/- 9 x 10(3); 2.06 x 10(6) +/- 1 x 10(4); 2.15 x 10(6) +/- 7 x 10(3) cells/mL for the TOP, MID, and BOT, respectively). The three communities showed different preferences for utilising specific DOM fractions, with the bottom community targeting more complex ones. The microbial communities from the bottom of the biofilter had a higher relative abundance of the Curvibacter genus, suggesting it could play a crucial role in degrading complex DOM fractions. These findings highlight the influence of microbial community composition on DOM degradation in biofilters, providing valuable insights for optimising their performance.

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