New Evidence for the Role of Pituitary Adenylate Cyclase-Activating Polypeptide as an Antimicrobial Peptide in Teleost Fish
Bibliographic record
Abstract
Pituitary Adenylate Cyclase-Activating Polypeptide (PACAP) is a multifunctional neuropeptide that is widely distributed and conserved across species. We have previously shown that in teleost fish, PACAP not only possesses direct antimicrobial properties but also immunomodulatory effects against the bacterial pathogens Flavobacterium psychrophilum and Pseudomonas aeruginosa using in vitro and in vivo experiments. These previous results suggest PACAP can be used as an alternative to antibiotics to prevent and/or treat bacterial infections in the aquaculture industry. To accomplish this goal, more studies are needed to better understand the effect of PACAP on pathogens affecting fish in live infections. In the present study, the transcripts PACAP, PRP/PACAP, and VPAC2 receptor were examined in rainbow trout (Oncorhynchus mykiss) naturally infected with Yersinia ruckeri, which exhibited an increase in their expression in the spleen when compared to healthy fish. Synthetic Clarias gariepinus PACAP-38 has direct antimicrobial activity on Y. ruckeri and inhibits up to 60% of the bacterial growth when the peptide is at concentrations between 50 and 100 µM in TSB. The growth inhibition increased up to 90% in the presence of 12.5 µM of PACAP-38 when salt-free LB broth was used instead of TSB. It was also found to inhibit Y. ruckeri growth in a dose-dependent manner when the rainbow trout monocyte/macrophage-like cell line (RTS11) was pre-treated with lower concentrations of the peptide (0.02 and 0.1 µM) before going through infection. Differential gene expression was analyzed in this in vitro model. Overall, the results revealed new evidence to support the role of PACAP as an antimicrobial and immunomodulatory peptide treatment in teleosts.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".