Divergent bacterial landscapes: unraveling geographically driven microbiomes in Atlantic cod
Bibliographic record
Abstract
Establishing microbiome signatures is now recognized as a critical step toward identifying genetic and environmental factors shaping animal-associated microbiomes and informing the health status of a given host. In the present work, we prospectively collected 63 blood samples of the Atlantic cod population of the Southern Gulf of Saint Lawrence (GSL) and characterized their 16S rRNA circulating microbiome signature. Our results revealed that the blood microbiome signature was dominated at the phylum level by Proteobacteria, Bacteroidetes, Acidobacteria and Actinobacteria, a typical signature for fish populations inhabiting the GSL and other marine ecosystems. At the genus level, however, we identified two distinct cod groups. While the microbiome signature of the first group was dominated by Pseudoalteromonas, a genus we previously found in the microbiome signature of Greenland and Atlantic halibut populations of the GSL, the second group had a microbiome signature dominated by Nitrobacter and Sediminibacterium (approximately 75% of the circulating microbiome). Cods harboring a Nitrobacter/Sediminibacterium-rich microbiome signature were localized in the most southern part of the GSL, just along the northern coast of Cape Breton Island. Atlantic cod microbiome signatures did not correlate with the weight, length, relative condition, depth, temperature, sex, and salinity, as previously observed in the halibut populations. Our study provides, for the first time, a unique snapshot of the circulating microbiome signature of Atlantic cod populations and the potential existence of dysbiotic signatures associated with the geographical distribution of the population, probably linked with the presence of nitrite in the environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".