Honey bee protein atlas at organ-level resolution
Bibliographic record
Abstract
Genome sequencing has provided us with gene lists but cannot tell us where and how their encoded products work together to support life. Complex organisms rely on differential expression of subsets of genes/proteins in organs and tissues, and, in concert, evolved to their present state as they function together to improve an organism's overall reproductive fitness. Proteomics studies of individual organs help us understand their basic functions, but this reductionist approach misses the larger context of the whole organism. This problem could be circumvented if all the organs in an organism were comprehensively studied by the same methodology and analyzed together. Using honey bees (Apis mellifera L.) as a model system, we report here an initial whole proteome of a complex organism, measuring 29 different organ/tissue types among the three honey bee castes: queen, drone, and worker. The data reveal that, e.g., workers have a heightened capacity to deal with environmental toxins and queens have a far more robust pheromone detection system than their nestmates. The data also suggest that workers altruistically sacrifice not only their own reproductive capacity but also their immune potential in favor of their queen. Finally, organ-level resolution of protein expression offers a systematic insight into how organs may have developed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.003 |
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; both teacher heads agree on what is shown here.
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".