Active Autotrophic Ammonia-Oxidizing Bacteria in Biofilm Enrichments from Simulated Creek Ecosystems at Two Ammonium Concentrations Respond to Temperature Manipulation
Bibliographic record
Abstract
The first step of nitrification, the oxidation of ammonia to nitrite, is important for reducing eutrophication in freshwater environments when coupled with anammox (anaerobic ammonium oxidation) or denitrification. We analyzed active formerly biofilm-associated aerobic ammonia-oxidizing communities originating from Ammerbach (AS) and Leutra South (LS) stream water (683 ± 550 [mean ± standard deviation] and 16 ± 7 μM NH(4)(+), respectively) that were developed in a flow-channel experiment and incubated under three temperature regimens. By stable-isotope probing using (13)CO(2), we found that members of the Bacteria and not Archaea were the functionally dominant autotrophic ammonia oxidizers at all temperatures under relatively high ammonium loads. The copy numbers of bacterial amoA genes in (13)C-labeled DNA were lower at 30°C than at 13°C in both stream enrichment cultures. However, the community composition of the ammonia-oxidizing bacteria (AOB) in the (13)C-labeled DNA responded differently to temperature manipulation at two ammonium concentrations. In LS enrichments incubated at the in situ temperature (13°C), Nitrosomonas oligotropha-like sequences were retrieved with sequences from Nitrosospira AmoA cluster 4, while the proportion of Nitrosospira sequences increased at higher temperatures. In AS enrichments incubated at 13°C and 20°C, AmoA cluster 4 sequences were dominant; Nitrosomonas nitrosa-like sequences dominated at 30°C. Biofilm-associated AOB communities were affected differentially by temperature at two relatively high ammonium concentrations, implicating them in a potential role in governing contaminated freshwater AOB distributions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".