Role of Interdomain Salt Bridges in the Pore-forming Ability of the Bacillus thuringiensis Toxins Cry1Aa and Cry1Ac
Bibliographic record
Abstract
The four salt bridges (Asp(222)-Arg(281), Arg(233)-Glu(288), Arg(234)-Glu(274), and Asp(242)-Arg(265)) linking domains I and II in Cry1Aa were abolished individually in alpha-helix 7 mutants D222A, R233A, R234A, and D242A. Two additional mutants targeting the fourth salt bridge (R265A) and the double mutant (D242A/R265A) were rapidly degraded during trypsin activation. Mutations were also introduced in the corresponding Cry1Ac salt bridge (D242E, D242K, D242N, and D242P), but only D242N and D242P could be produced. All toxins tested, except D242A, were shown by light-scattering experiments to permeabilize Manduca sexta larval midgut brush border membrane vesicles. The three active Cry1Aa mutants at pH 10.5, as well as D222A at pH 7.5, demonstrated a faster rate of pore formation than Cry1Aa, suggesting that increases in molecular flexibility due to the removal of a salt bridge facilitated toxin insertion into the membrane. However, all mutants were considerably less toxic to M. sexta larvae than to the respective parental toxins, suggesting that increased flexibility made the toxins more susceptible to proteolysis in the insect midgut. Interdomain salt bridges, especially the Asp(242)-Arg(265) bridge, therefore contribute greatly to the stability of the protein in the larval midgut, whereas their role in intrinsic pore-forming ability is relatively less important.
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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 | 0.000 |
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".