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Record W4399857338 · doi:10.1128/aem.00104-24

Comammox <i>Nitrospira</i> among dominant ammonia oxidizers within aquarium biofilter microbial communities

2024· article· en· W4399857338 on OpenAlexafffund
Michelle M. McKnight, Josh D. Neufeld

Bibliographic record

VenueApplied and Environmental Microbiology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaMcKnight Foundation
KeywordsNitrospiraBiofilterNitrificationArchaeaEnvironmental chemistryHeterotrophAmmoniaBiologyAnammoxMicrobial population biologyAlkalinityEcologyChemistryBacteriaNitriteDenitrificationNitrateEnvironmental scienceEnvironmental engineeringDenitrifying bacteriaBiochemistryNitrogen

Abstract

fetched live from OpenAlex

ABSTRACT Nitrification by aquarium biofilters transforms ammonia waste (NH 3 /NH 4 + ) to less toxic nitrate (NO 3 - ) via nitrite (NO 2 - ). Prior to the discovery of complete ammonia-oxidizing (“comammox” or CMX) Nitrospira , previous research revealed that ammonia-oxidizing archaea (AOA) dominated over ammonia-oxidizing bacteria (AOB) in freshwater aquarium biofilters. Here, we profiled aquarium biofilter microbial communities and quantified the abundance of all three known ammonia oxidizers using 16S rRNA gene sequencing and quantitative PCR (qPCR), respectively. Biofilter and water samples were each collected from representative residential and commercial freshwater and saltwater aquaria. Distinct biofilter microbial communities were associated with freshwater and saltwater biofilters. Comammox Nitrospira amoA genes were detected in all 38 freshwater biofilter samples (average CMX amoA genes: 2.2 × 10 3 ± 1.5 × 10 3 copies/ng) and dominant in 30, whereas AOA were present in 35 freshwater biofilter samples (average AOA amoA genes: 1.1 × 10 3 ± 2.7 × 10 3 copies/ng) and only dominant in 7 of them. The AOB were at relatively low abundance within biofilters (average of 3.2 × 10 1 ± 1.1 × 10 2 copies of AOB amoA genes/ng of DNA), except for the aquarium with the highest ammonia concentration. For saltwater biofilters, AOA or AOB were differentially abundant, with no comammox Nitrospira detected. Additional sequencing of Nitrospira amoA genes revealed differential distributions, suggesting niche adaptation based on water chemistry (e.g., ammonia, carbonate hardness, and alkalinity). Network analysis of freshwater microbial communities demonstrated positive correlations between nitrifiers and heterotrophs, suggesting metabolic and ecological interactions within biofilters. These results demonstrate that comammox Nitrospira plays a previously overlooked, but important role in home aquarium biofilter nitrification. IMPORTANCE Nitrification is a crucial process that converts toxic ammonia waste into less harmful nitrate that occurs in aquarium biofilters. Prior research found that ammonia-oxidizing archaea (AOA) were dominant over ammonia-oxidizing bacteria (AOB) in freshwater aquarium biofilters. Our study profiled microbial communities of aquarium biofilters and quantified the abundance of all currently known groups of aerobic ammonia oxidizers. The findings reveal that complete ammonia-oxidizing (comammox) Nitrospira were present in all freshwater aquarium biofilter samples in high abundance, challenging our previous understanding of aquarium nitrification. We also highlight niche adaptation of ammonia oxidizers based on salinity. The network analysis of freshwater biofilter microbial communities revealed significant positive correlations among nitrifiers and other community members, suggesting intricate interactions within biofilter communities. Overall, this study expands our understanding of nitrification in aquarium biofilters, emphasizes the role of comammox Nitrospira , and highlights the value of aquaria as microcosms for studying nitrifier ecology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.170
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2024
Admission routes2
Has abstractyes

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