Identification of novel host defense peptides and the absence of α‐defensins in the bovine genome
Bibliographic record
Abstract
Host defense peptides (historically called antimicrobial peptides, AMPs) are key components in the mammalian innate immune system, and are responsible for both direct killing and immunomodulatory effects in host defense against pathogenic organisms. In order to identify novel host defense peptides by sequence analysis, we constructed the AMPer resource (http://www.cnbi2.com/cgi-bin/amp.pl) that utilizes hidden Markov models to recognize sequences of antimicrobial peptides. In the current work, we utilized the AMPer resource to search bovine expressed sequence tags from the NCBI dbEST project and the bovine genome sequence for novel host defense peptides. Of the 34 known bovine AMPs, 27 were identified with high confidence in the AMPs predicted from ESTs. A further potential 68 AMPs predicted from the EST data were found that appear to be novel giving a total estimate of 102 AMPs present in the genome. Two of these were cathelicidins and selected for experimental verification in RNA derived from bovine tissue. One predicted AMP, most similar to rabbit '15 kDa protein' AMP, was confirmed to be present in infected bovine intestinal tissue using PCR. These findings demonstrated the practical applicability of the developed bioinformatics approach and laid a foundation for future discoveries of gene-coded AMPs. No members of the alpha-defensin family were found in the bovine sequences. Since we could find no technical reasons these would be missed and no references to bovine alpha-defensins in the literature, this suggests that cattle lack this important family of host defense peptides.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".