Characterization of a Subfamily of Beetle Odorant-binding Proteins Found in Hemolymph
Bibliographic record
Abstract
In insects, hydrophobic odorants are transported through the sensillar lymph to receptors on sensory neurons by odorant-binding proteins (OBPs). The beetle Tenebrio molitor, which is a pest of stored grain products, produces a set of 12-14-kDa OBP-like proteins in its hemolymph. The structure of one of these proteins and that of a moth pheromone-binding protein have been solved. Both proteins have at least six alpha-helices with an internal, hydrophobic, ligand-binding pocket, but the beetle OBP lacks one of the disulfide bonds immediately adjacent to this pocket. To explore this difference and to sample isoform diversity, T. molitor hemolymph OBPs were fractionated by size-exclusion chromatography and reversed-phase high performance liquid chromatography. Selected fractions were reduced and alkylated, and tryptic peptides were sequenced by tandem mass spectrometry. Partial sequences of 7 different isoforms were obtained and used to clone 9 new cDNAs encoding OBPs with identities from 32 to 99%. The more divergent isoforms have numerous substitutions of hydrophobic residues that presumably alter the shape and specificity of the ligand-binding pocket. These isoforms all lack the same third disulfide bridge and are more similar to one another than to any of the 38 OBPs in Drosophila melanogaster. They have presumably arisen via gene duplication following separation of the major insect orders.
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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 | 0.001 |
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".