Diversity of nitrogen assimilation pathways among microbial photosynthetic eukaryotes
Bibliographic record
Abstract
In an effort to better understand the diversity of genes coding for nitrogen (N) uptake and assimilation pathways among microalgae, we analyzed the transcriptomes of five phylogenetically diverse single celled algae originally isolated from the same high arctic marine region. The five photosynthetic flagellates (a pelagophyte, dictyochophyte, chrysoph-yte, cryptophyte and haptophyte) were grown on standard media and media with only urea or nitrate as a nitrogen source; cells were harvested during late exponential growth. Based on homolog protein sequences, transcriptomes of each alga were interrogated to retrieve genes potentially associated with nitrogen uptake and utilization pathways. We further investigated the phylogeny of poorly characterized genes and gene families that were identified. While the phylogeny of the active urea transporter (DUR3) was taxonomically coherent, those for the urea transporter superfamily, putative nitrilases and amidases indicated complex evolutionary histories, and preliminary evidence for horizontal gene transfers. All five algae expressed genes for ammonium assimilation and all but the chrysophyte expressed genes involved in nitrate utilization and the urea cycle. Among the four algae with nitrate transporter transcripts, we detected lower expression levels in three of these (the dictyochophyte, pelagophyte, and cryptophyte) grown in the urea only medium compared with cultures from the nitrate only media. The diversity of N pathway genes in the five algae, and their ability to grow using urea as a nitrogen source, suggest that these flagellates are able to use a variety of organic nitrogen sources, which would be an advantage in an inorganic nitrogen - limited environment, such as the Arctic Ocean.
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 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 | 0.000 | 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) | 0.000 | 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 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".