Biological Nitrogen Removal Database
A manually curated data resource for microbial nitrogen removal
Biological Nitrogen Removal Database
A manually curated data resource for microbial nitrogen removal
Microorganism |
|---|
|
Uncultured Nitrospirae bacterium clone A2_NSP2 |
Taxonomy |
|---|
|
Electron Acceptor |
|---|
|
nan |
Electron Donor |
|---|
|
nan |
Information about Article |
|---|
|
Reference:Geets et al., 2007 Title:Real-time PCR assay for the simultaneous quantification of nitrifying and denitrifying bacteria in activated sludge Pubmed ID:17256118 Pubmed link:Link Full research link:Link Abstract: In order to improve wastewater treatment processes, a need exists for tools that rapidly give detailed insight into the community structure of activated sludge, supplementary to chemical and physical data. In this study, the advantages of microarrays and quantitative polymerase chin reaction (PCR) methods were combined into a real-time PCR assay that allows the simultaneous quantification of phylogenetic and functional genes involved in nitrification and denitrification processes. Simultaneous quantification was possible along a 5-log dynamic range and with high linear correlation (R 2 > 0.98). The specificity of the assay was confirmed by cloning and sequencing analyses of PCR amplicons obtained from activated sludge. The real-time assay was validated on mixed liquid samples of different treatment plants, which varied in nitrogen removal rate. The abundance of ammonia oxidizers was in the order of magnitude of 106 down to 104 ml−1, whereas nitrite oxidizers were less abundant (103–101 order of magnitude). The results were in correspondence with the nitrite oxidation rate in the sludge types. As for the nirS, nirK, and nosZ gene copy numbers, their abundance was generally in the order of magnitude of 108–105. When sludge samples were subjected to lab-scale perturbations, a decrease in nitrification rate was reflected within 18 h in the copy numbers of nitrifier genes (decrease with 1 to 5 log units), whereas denitrification genes remained rather unaffected. These results demonstrate that the method is a fast and accurate tool for the analysis of the (de)nitrifying community structure and size in both natural and engineered environmental samples. |