A Family of Helminth Molecules that Modulate Innate Cell Responses via Molecular Mimicry of Host Antimicrobial Peptides
Bibliographic record
Abstract
Over the last decade a significant number of studies have highlighted the central role of host antimicrobial (or defence) peptides in modulating the response of innate immune cells to pathogen-associated ligands. In humans, the most widely studied antimicrobial peptide is LL-37, a 37-residue peptide containing an amphipathic helix that is released via proteolytic cleavage of the precursor protein CAP18. Owing to its ability to protect against lethal endotoxaemia and clinically-relevant bacterial infections, LL-37 and its derivatives are seen as attractive candidates for anti-sepsis therapies. We have identified a novel family of molecules secreted by parasitic helminths (helminth defence molecules; HDMs) that exhibit similar biochemical and functional characteristics to human defence peptides, particularly CAP18. The HDM secreted by Fasciola hepatica (FhHDM-1) adopts a predominantly α-helical structure in solution. Processing of FhHDM-1 by F. hepatica cathepsin L1 releases a 34-residue C-terminal fragment containing a conserved amphipathic helix. This is analogous to the proteolytic processing of CAP18 to release LL-37, which modulates innate cell activation by classical toll-like receptor (TLR) ligands such as lipopolysaccharide (LPS). We show that full-length recombinant FhHDM-1 and a peptide analogue of the amphipathic C-terminus bind directly to LPS in a concentration-dependent manner, reducing its interaction with both LPS-binding protein (LBP) and the surface of macrophages. Furthermore, FhHDM-1 and the amphipathic C-terminal peptide protect mice against LPS-induced inflammation by significantly reducing the release of inflammatory mediators from macrophages. We propose that HDMs, by mimicking the function of host defence peptides, represent a novel family of innate cell modulators with therapeutic potential in anti-sepsis treatments and prevention of inflammation.
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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) | 0.001 | 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".