Author response: A gene horizontally transferred from bacteria protects arthropods from host plant cyanide poisoning
Bibliographic record
Abstract
Hydrogen cyanide is a poison that is deadly for most forms of life. Also known as prussic acid, it has killed countless humans throughout history in accidents and during the Holocaust. Hydrogen cyanide is also used by plants to defend themselves against insects and other herbivorous animals. Many plants produce chemicals called cyanogenic glycosides that can be converted into hydrogen cyanide when the plant is eaten. This is an ancient and efficient defense against all sorts of herbivores, including humans. For instance, cassava is a key source of food in sub-Saharan Africa and South America, but it contains cyanogenic glucosides and is highly toxic if eaten in unprocessed form. However, some insects and mites can thrive on cyanogenic plants, often to the extent of becoming pests on these plants. Certain moths, such as burnet moths, have gone further and now depend on cyanogenic glucosides for their own defenses against predators such as birds. How these mites and insects are capable of fending off cyanide toxicity has long remained a mystery. Now Wybouw et al. have identified a mite enzyme that detoxifies hydrogen cyanide to produce a compound called beta-cyanoalanine. Remarkably, the DNA that encodes this enzyme did not evolve in animals but originally belonged to a bacterium. Wybouw et al. show that the gene was transferred to the genome of the spider mite Tetranychus urticae perhaps a few hundred million years ago. An equivalent gene was also found in moths and butterflies, which explains why these insects can thrive on plants that produce hydrogen cyanide. This lateral gene transfer from bacteria to animals is a remarkable coalition of two kingdoms against another, and illustrates a new aspect of the chemical warfare between plants and animals. This study also increases our awareness of the importance of laterally transferred genes in the genomes of higher organisms.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.255 | 0.090 |
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".