Defining the Distinct Skin and Gut Microbiomes of the Northern Pike (Esox lucius)
Bibliographic record
Abstract
The microbiome of freshwater fish has important implications for both commercial and recreational fishing as it is known to have significant impacts on host heath and susceptibility to disease. The aqueous environment serves as a possible avenue for continuous introduction of microbes to an animal host, but little is known about how the surrounding microbiota contribute to piscine microbiomes. To better understand the composition of the fish microbiome exposed to the natural environment, we profiled the microbial composition of the gut and the skin mucosal surface (SMS) of northern pike (Esox lucius) and the surrounding river water. We collected fish samples from eight sites along the Chochocouane River in Quebec, Canada and analyzed the microbial composition via 16S rRNA sequencing. Our results reveal robust taxonomic differences between the SMS and the gut, indicating a divergence between the microbiomes. The gut community was characterized by a lower alpha diversity compared to the SMS and a large proportion of Cetobacterium, a genus previously linked to carnivorous species. On the other hand, the SMS was more similar to the water than the gut at the family level but divergent at lower taxonomic levels, with fewer than 30% of OTUs shared between the SMS and water. In total, our results suggest the establishment of distinct communities across the two fish sites and a distinct separation from the microbes in surrounding waters. These data indicate that despite continuous exposure to water, pike are able to establish and maintain unique microbial communities.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".