Genetic potential for exopolysaccharide synthesis in activated sludge bacteria uncovered by genome-resolved metagenomics

Morten Kam Dahl Dueholm*, Maaike Besteman, Emil Juel Zeuner, Marie Riisgaard-Jensen, Morten Eneberg Nielsen, Sofie Zacho Vestergaard, Søren Heidelbach, Nicolai Sundgaard Bekker, Per Halkjær Nielsen

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

24 Citations (Scopus)

Abstract

A good floc formation of activated sludge (AS) is crucial for solid-liquid separation and production of clean effluent during wastewater treatment. Floc formation is partly controlled by self-produced extracellular polymeric substances (EPS) such as exopolysaccharides, proteins, and nucleic acids. Little is known about the composition, structure, and function of EPS in AS and which bacteria produce them. To address this knowledge gap for the exopolysaccharides, we took advantage of 1083 high-quality metagenome-assembled genomes (MAGs) obtained from 23 Danish wastewater treatment plants. We investigated the genomic potential for exopolysaccharide biosynthesis in bacterial species typical in AS systems based on genome mining and gene synteny analyses. Putative gene clusters associated with the biosynthesis of alginate, cellulose, curdlan, diutan, hyaluronic acids, Pel, poly-β-1,6-N-acetyl-D-glucosamine (PNAG), Psl, S88 capsular polysaccharide, salecan, succinoglycan, and xanthan were identified and linked to individual MAGs, providing a comprehensive overview of the genome-resolved potential for these exopolysaccharides in AS bacteria. The approach and results provide a starting point for a more comprehensive understanding of EPS composition in wastewater treatment systems, which may facilitate a more refined regulation of the activated sludge process for improved stability.

Original languageEnglish
Article number119485
JournalWater Research
Volume229
DOIs
Publication statusPublished - 1 Feb 2023

Keywords

  • Activated sludge
  • EPS
  • Exopolysaccharides
  • Genome mining

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