Transcriptome analysis revealed immune responses in the kidney of Atlantic salmon (Salmo salar) co-infected with sea lice (Lepeophtheirus salmonis) and infectious salmon anemia virus
Bibliographic record
Abstract
Sea lice (Lepeophtheirus salmonis) and infectious salmon anemia virus (ISAv) are two of the most important pathogens in Atlantic salmon (Salmo salar) farming and typically cause substantial economic losses to the industry. However, the immune interactions between hosts and these pathogens are still unclear, especially in the scenario of co-infection. In this study, we artificially infected Atlantic salmon with sea lice and ISAv, and investigated the gene expression patterns of Atlantic salmon head kidneys in response to both lice only and co-infection with lice and ISAv by transcriptomic analysis. The challenge experiment indicated that co-infection resulted in a cumulative mortality rate of 47.8 %, while no mortality was observed in the lice alone infection. We identified 240 differentially expressed genes (DEGs) under the lice alone infection, of which 185 were down-regulated and 55 were up-regulated, while a total of 994 DEGs were identified in the co-infection, of which 206 were down-regulated and 788 were significantly up-regulated. The pathway enrichment analysis revealed that single-infection significantly suppressed the innate immune system (e.g., the complement system), whereas co-infection induced a strong immune response, leading to the activation of immune-related signaling pathways such as Toll-like receptors and NOD-like receptors pathways, as well as significant upregulation of genes related to the activation of interferon and MH class I protein complex. Our results provide the first global transcriptomic study of gene expression in the Atlantic salmon head kidney in response to co-infection with sea lice and ISAv, and provided the baseline knowledge for understanding the immune responses during co-infection.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".