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Record W4410630875 · doi:10.1186/s12950-025-00446-w

LL-37 and citrullinated-LL-37 modulate IL-17A/F-mediated responses and selectively suppress Lipocalin-2 in bronchial epithelial cells

2025· article· en· W4410630875 on OpenAlexafffund
Anthony Altieri, Dylan Lloyd, Padmanie Ramotar, Anne M. van der Does, Mahadevappa Hemshekhar, Neeloffer Mookherjee

Bibliographic record

VenueJournal of Inflammation · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of ManitobaUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaChildren's Hospital Research Institute of ManitobaReseau canadien de recherche respiratoireResearch Manitoba
KeywordsLipocalinInflammationChemokineImmunologyChemotaxisCell biologyTranscription factorInterleukin 17Proinflammatory cytokineBiologyChemistryReceptorEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Levels of the human cationic antimicrobial host defence peptide LL-37 are enhanced in the lungs during neutrophilic airway inflammation. LL-37 drives Th17 differentiation, and Th17 cells produce IL-17A and IL-17F which form the biologically active heterodimer IL-17A/F. While IL-17 is a critical mediator of neutrophilic airway inflammation, LL-37 exhibits contradictory functions; LL-37 can both promote and mitigate neutrophil recruitment depending on the inflammatory milieu. The impact of LL-37 on IL-17-induced responses in the context of airway inflammation remains largely unknown. Therefore, we examined signaling intermediates and downstream responses mediated by the interplay of IL-17A/F and LL-37 in human bronchial epithelial cells (HBEC). As LL-37 can become citrullinated during airway inflammation, we also examined LL-37-mediated downstream responses compared to that with citrullinated LL-37 (citLL-37) in HBEC. RESULTS: Using an aptamer-based proteomics approach, we identified proteins that are altered in response to IL-17A/F in HBEC. Proteins enhanced in response to IL-17A/F were primarily neutrophil chemoattractants, including chemokines and proteins associated with neutrophil migration such as lipocalin-2 (LCN-2). We showed that selective depletion of LCN-2 mitigates neutrophil migration, functionally demonstrating LCN-2 as a critical neutrophil chemoattractant. We further demonstrated that LL-37 and citLL-37 selectively suppress IL-17A/F-induced LCN-2 abundance in HBEC. Mechanistic studies revealed that LL-37 and citLL-37 suppresses IL-17 A/F-mediated enhancement of C/EBPβ, a transcription factor required for LCN-2 production. In contrast, LL-37 and citLL-37 enhance the abundance of ribonuclease Regnase-1, which is a negative regulator of IL-17 and LCN-2 in HBEC. In an animal model of allergen-challenged airway inflammation with elevated IL-17A/F and neutrophil elastase in the lungs, we demonstrated that CRAMP (mouse orthologue of LL-37) negatively correlates with LCN-2. CONCLUSIONS: Overall, our findings showed that LL-37 and citLL-37 can selectively suppress the abundance of IL-17A/F-mediated LCN-2, a protein that is critical for neutrophil migration in HBEC. These results suggest that LL-37, and its modified citrullinated form, have the potential to negatively regulate IL-17-mediated neutrophil migration during airway inflammation. To our knowledge, this is the first study to report that the immunomodulatory function of LL-37 enhances the RNA binding protein Regnase-1, suggesting that a post-transcriptional mechanism of action is mediated by the peptide.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.221
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2025
Admission routes2
Has abstractyes

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