Chemically Stressed Bacterial Communities in Anaerobic Digesters Exhibit Resilience and Ecological Flexibility
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Anaerobic digestion is a technology known for its potential in terms of methane production. During the digestion process, multiple metabolites of high value are synthesized. However, recent works have demonstrated the high robustness and resilience of the involved microbiomes; these attributes make it difficult to manipulate them in such a way that a specific metabolite is predominantly produced. Therefore, an exact understanding of the manipulability of anaerobic microbiomes may open up a treasure box for bio-based industries. In the present work, the effect of nalidixic acid, γ-aminobutyric acid (GABA), and sodium phosphate on the microbiome of digested sewage sludge from a water treatment plant fed with glucose was investigated. Despite of the induced process perturbations, high stability was observed at the phylum level. However, strong variations were observed at the genus level, especially for the genera Trichococcus, Candidatus Caldatribacterium, and Phascolarctobacterium. Ecological interactions were analyzed based on the Lotka–Volterra model for Trichococcus, Rikenellaceae DMER64, Sedimentibacter, Candidatus Cloacimonas, Smithella, Cloacimonadaceae W5 and Longilinea. These genera dynamically shifted among positive, negative or no correlation, depending on the applied stressor, which indicates a surprisingly dynamic behavior. Globally, the presented work suggests a massive resilience and stability of the methanogenic communities coupled with a surprising flexibility of the particular microbial key players involved in the process.
Details
Original language | English |
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Article number | 867 |
Journal | Frontiers in microbiology |
Volume | 11 |
Publication status | Published - 12 May 2020 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0001-5081-2558/work/142255751 |
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Keywords
ASJC Scopus subject areas
Keywords
- anaerobic digestion, anaerobic microbiomes, Lotka–Volterra, microbiome manipulation, population modeling