Microbial community analysis of biofilters reveals a dominance of either comammox <i>Nitrospira</i> or archaea as ammonia oxidizers in freshwater aquaria
Bibliographic record
Abstract
Abstract Nitrification by aquarium biofilters transforms toxic ammonia waste (NH 3 /NH 4 + ) to less toxic nitrate (NO 3 - ) via nitrite (NO 2 - ). Ammonia oxidation is mediated by ammonia-oxidizing bacteria (AOB), ammonia-oxidizing archaea (AOA), and the recently discovered complete ammonia oxidizing (comammox) Nitrospira . Prior to the discovery of comammox Nitrospira , previous research revealed that AOA dominate among ammonia oxidizers in freshwater biofilters. Here, we characterized the composition of aquarium filter microbial communities and quantified the abundance of all three known groups of ammonia oxidizers. Aquarium biofilter and water samples were collected from representative freshwater and saltwater systems in Southwestern Ontario, Canada. Using extracted DNA, we performed 16S rRNA gene sequencing and quantitative PCR (qPCR) to assess community composition and quantify the abundance of amoA genes, respectively. Our results show that aquarium biofilter microbial communities were consistently represented by putative heterotrophs of the Proteobacteria and Bacteroides phyla, with distinct profiles associated with fresh versus saltwater biofilters. Among nitrifiers, comammox Nitrospira amoA genes were detected in all 38 freshwater aquarium biofilter samples and were the most abundant ammonia oxidizer in 30 of these samples, with the remaining biofilters dominated by AOA, based on amoA gene abundances. In saltwater biofilters, AOA or AOB were differentially abundant, with no comammox Nitrospira detected. These results demonstrate that comammox Nitrospira play an important role in biofilter nitrification that has been previously overlooked and such microcosms are useful for exploring the ecology of nitrification for future research.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".