Denitrification genotypes of endospore-forming <i>Bacillota</i>
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Denitrification is a key metabolic process in the global nitrogen cycle and is performed by taxonomically diverse microorganisms. Despite the widespread importance of this metabolism, challenges remain in identifying denitrifying populations and predicting their metabolic end-products based on their genotype. Here, genome-resolved metagenomics was used to explore the denitrification genotype of Bacillota enriched in nitrate-amended high temperature incubations with confirmed N2O and N2 production. A set of 12 hidden Markov models (HMMs) was created to target the diversity of denitrification genes in members of the phylum Bacillota. Genomic potential for complete denitrification was found in five metagenome-assembled genomes from nitrate-amended enrichments, including two novel members of the Brevibacillaceae family. Genomes of complete denitrifiers encode N2O reductase gene clusters with clade II-type nosZ and often include multiple variants of the nitric oxide reductase gene. The HMM set applied to all genomes of Bacillota from the Genome Taxonomy Database identified 17 genera inferred to contain complete denitrifiers based on their gene content. Among complete denitrifiers it was common for three distinct nitric oxide reductases to be present (qNOR, bNOR, and sNOR) that may reflect the metabolic adaptability of Bacillota in environments with variable redox conditions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
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 it