Multi-Organ Transcriptome Response of Lumpfish (Cyclopterus lumpus) to Aeromonas salmonicida Subspecies salmonicida Systemic Infection
Bibliographic record
Abstract
Lumpfish is utilized as a cleaner fish to biocontrol sealice infestations in Atlantic salmon farms. Aeromonas salmonicida, a Gram-negative facultative intracellular pathogen, is the causative agent of furunculosis in several fish species, including lumpfish. In this study, lumpfish were intraperitoneally injected with different doses of A. salmonicida to calculate the LD50. Samples of blood, head-kidney, spleen, and liver were collected at different time points to determine the infection kinetics. We determined that A. salmonicida LD50 is 102 CFU per dose. We found that the lumpfish head-kidney is the primary target organ of A. salmonicida. Triplicate biological samples were collected from head-kidney, spleen, and liver pre-infection and at 3- and 10-days post-infection for RNA-sequencing. The reference genome-guided transcriptome assembly resulted in 6246 differentially expressed genes. The de novo assembly resulted in 403,204 transcripts, which added 1307 novel genes not identified by the reference genome-guided transcriptome. Differential gene expression and gene ontology enrichment analyses suggested that A. salmonicida induces lethal infection in lumpfish by uncontrolled and detrimental blood coagulation, complement activation, inflammation, DNA damage, suppression of the adaptive immune system, and prevention of cytoskeleton formation.
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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".