Evaluating Primers for Profiling Anaerobic Ammonia Oxidizing Bacteria within Freshwater Environments
Bibliographic record
Abstract
Anaerobic ammonia oxidizing (anammox) bacteria play an important role in transforming ammonium to nitrogen gas and contribute to fixed nitrogen losses in freshwater environments. Understanding the diversity and abundance of anammox bacteria requires reliable molecular tools, and these are not yet well established for these important Planctomycetes. To help validate PCR primers for the detection of anammox bacteria within freshwater ecosystems, we analyzed representative positive controls and selected samples from Grand River and groundwater sites, both from Ontario, Canada. The objectives of this study were to identify a suitable anammox denaturing gradient gel electrophoresis (DGGE) fingerprint method by using GC-clamp modifications to existing primers, and to verify the specificity of anammox-specific primers used for DGGE, cloning and qPCR methods. Six primer combinations were tested from four published primer sets (i.e. A438f/A684r, Amx368f/Amx820r, An7f/An1388r, and Pla46/1392r) for both direct and nested PCR amplifications. All PCR products were run subsequently on DGGE gels to compare the resulting patterns. Two anammox-specific primer combinations were also used to generate clone libraries and quantify anammox bacterial 16S rRNA genes with qPCR. The primer set A438f/A684r was highly specific to anammox bacteria, provided reliable DGGE fingerprints and generated a high proportion of anammox-related clones. A second primer set (Amx368f/Amx820r) was anammox specific, based on clone library analysis, but PCR products from different candidate species of anammox bacteria resolved poorly using DGGE analysis. Both DGGE and cloning results revealed that Ca. Brocadia and an uncharacterized anammox bacterial cluster represented the majority of anammox bacteria found in Grand River sediment and groundwater samples, respectively. Together, our results demonstrate that although Amx368f/Amx820r was useful for anammox-specific qPCR and clone library analysis, A438f/A684r was the most suitable primer set for multiple molecular assessments of anammox bacteria in freshwater environments.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".