Absence of a functional gut microbiome impairs host amino acid metabolism in the Pacific spiny dogfish (<i>Squalus suckleyi</i>)
Bibliographic record
Abstract
Nitrogen recycling and amino acid synthesis are two notable ways in which the gut microbiome can contribute to host metabolism, and these processes are especially important in nitrogen-limited animals. Marine elasmobranchs are nitrogen limited as they require substantial amounts of this element to support urea-based osmoregulation. However, following antibiotic-induced depletion of the gut microbiome, elasmobranchs are known to experience a significant decline in circulating urea and employ compensatory nitrogen conservation strategies such as reduced urea and ammonia excretion. We hypothesized that the elasmobranch gut microbiome transforms dietary and recycled nutrients into amino acids, supporting host carbon and nitrogen balance. Here, using stable isotope analyses, we found that depleting the gut microbiome of Pacific spiny dogfish (Squalus suckleyi) resulted in a significant reduction to the incorporation of supplemented dietary 15N into plasma amino acids, notably those linked to nitrogen handling and energy metabolism, but had no effect on gut amino acid transport. These results demonstrate the importance of gut microbes to host amino acid pools and the unique nitrogen handling strategy of marine elasmobranchs. More broadly, these results elucidate how the gut microbiome contributes to organismal homeostasis, which is likely a ubiquitous phenomenon across animal populations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".