Role for urea in nitrification by polar marine Archaea
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the high abundance of Archaea in the global ocean, their metabolism and biogeochemical roles remain largely unresolved. We investigated the population dynamics and metabolic activity of Thaumarchaeota in polar environments, where these microorganisms are particularly abundant and exhibit seasonal growth. Thaumarchaeota were more abundant in deep Arctic and Antarctic waters and grew throughout the winter at surface and deeper Arctic halocline waters. However, in situ single-cell activity measurements revealed a low activity of this group in the uptake of both leucine and bicarbonate (<5% Thaumarchaeota cells active), which is inconsistent with known heterotrophic and autotrophic thaumarchaeal lifestyles. These results suggested the existence of alternative sources of carbon and energy. Our analysis of an environmental metagenome from the Arctic winter revealed that Thaumarchaeota had pathways for ammonia oxidation and, unexpectedly, an abundance of genes involved in urea transport and degradation. Quantitative PCR analysis confirmed that most polar Thaumarchaeota had the potential to oxidize ammonia, and a large fraction of them had urease genes, enabling the use of urea to fuel nitrification. Thaumarchaeota from Arctic deep waters had a higher abundance of urease genes than those near the surface suggesting genetic differences between closely related archaeal populations. In situ measurements of urea uptake and concentration in Arctic waters showed that small-sized prokaryotes incorporated the carbon from urea, and the availability of urea was often higher than that of ammonium. Therefore, the degradation of urea may be a relevant pathway for Thaumarchaeota and other microorganisms exposed to the low-energy conditions of dark polar waters.
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.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it