Occurrence and metabolic properties of bacteria from the genus Novosphingobium indicate their use as model organisms for studying biodegradation processes in activated carbon filters in advanced wastewater purification
Yulduzkhon Abdullaeva , Stephanie Rochau , Marie Löwe , Johannes Holert , Bodo Philipp
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引用次数: 0
Abstract
Activated carbon filters are increasingly being installed in sewage treatment plants to adsorb organic micropollutants from purified wastewater. Biodegradation also contributes to micropollutant removal in the filters, but the respective microorganisms and underlying processes are largely unexplored. Particularly, it is unknown to which extent active desorption of micropollutants takes place and which molecular mechanisms are involved. For addressing these questions microbial model organisms are required. In this study, the prokaryotic microbiome of a newly installed activated carbon filter in a fourth clarification stage of a municipal wastewater treatment plant was analyzed over 12 months by 16S rRNA gene amplicon sequencing. Bacterial families with relative abundancies above 1% stabilized after 2 months and included the potential micropollutant degraders Hyphomonadaceae and Sphingomonadaceae. Among the latter, members of the genus Novosphingobium were frequently found and closely related to the type strain N. aromaticivorans DSM 12444, which is known to degrade synthetic chemicals. Strain DSM 12444 and the Pseudomonadaceae strains Teo15 and Salic, which were isolated from enrichment cultures with filter material but not detected in the microbiome, were selected as model organisms for laboratory growth experiments with granulated activated carbon loaded with benzoate and salicylate. Strain DSM 12444 reached a significantly higher final optical density when grown on granular activated carbon pre-loaded with either benzoate or salicylate compared to strains Teo15 and Salic, respectively. Extraction of residual benzoate and salicylate from activated carbon granules indicated that more than 95 % of the aromatic compounds had been depleted by strain DSM 12444 compared to about 70 % and 50 % by strains Teo15 and Salic, respectively. Transcriptomic analysis indicated differential gene expression of strain DSM1244 during growth with benzoate in the presence and absence of GAC. These results qualify N. aromaticivorans as a feasible model organism to study the mechanisms of bacterial growth with organic substrates adsorbed to activated carbon which could support the design of bioaugmentation strategies for enhancing micropollutant removal.
期刊介绍:
Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include:
•Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management;
•Urban hydrology including sewer systems, stormwater management, and green infrastructure;
•Drinking water treatment and distribution;
•Potable and non-potable water reuse;
•Sanitation, public health, and risk assessment;
•Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions;
•Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment;
•Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution;
•Environmental restoration, linked to surface water, groundwater and groundwater remediation;
•Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts;
•Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle;
•Socio-economic, policy, and regulations studies.