Protective Role of the Neuropeptide Urocortin II against Experimental Sepsis and Leishmaniasis by Direct Killing of Pathogens
Bibliographic record
Abstract
We currently face an alarming resurgence in infectious diseases characterized by antimicrobial resistance and therapeutic failure. This has generated the urgent need of developing new therapeutic approaches that include agents with nontraditional modes of action. A recent interest focused on approaches based on our natural immune defenses, especially on peptides that combine innate antimicrobial activity against diverse pathogens and immunoregulatory functions. In this study, to our knowledge, we describe for the first time the antimicrobial activity of the neuropeptide urocortin II (UCNII) against a panel of Gram-positive and Gram-negative bacteria and tropical parasites of the genus Leishmania. Importantly, this cytotoxicity was selective for pathogens, because UCNII did not affect mammalian cell viability. Structurally, UCNII has a cationic and amphipathic design that resembles antimicrobial peptides. Using mutants and UCNII fragments, we determined the structural requirements for the interaction between the peptide and the surface of pathogen. Following its binding to pathogen, UCNII caused cell death through different membrane-disrupting mechanisms that involve aggregation and membrane depolarization in bacteria and pore formation in Leishmania. Noteworthily, UCNII killed the infective form of Leishmania major even inside the infected macrophages. Consequently, UCNII prevented mortality caused by polymicrobial sepsis and ameliorated pathological signs of cutaneous leishmaniasis. Besides its presence in body physical and mucosal barriers, we found that innate immune cells produce UCNII in response to infections. Therefore, UCNII could be considered as an ancient highly-conserved host peptide involved in the natural antimicrobial defense and emerge as an attractive alternative to current treatments for microbial disorders with associated drug resistances.
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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".