Tailoring the Specificity of a Plant Cystatin toward Herbivorous Insect Digestive Cysteine Proteases by Single Mutations at Positively Selected Amino Acid Sites
Bibliographic record
Abstract
Plant cystatins, similar to other defense proteins, include hypervariable, positively selected amino acid sites presumably impacting their biological activity. Using 29 single mutants of the eighth domain of tomato (Solanum lycopersicum) multicystatin, SlCYS8, we assessed here the potential of site-directed mutagenesis at positively selected amino acid sites to generate cystatin variants with improved inhibitory potency and specificity toward herbivorous insect digestive cysteine (Cys) proteases. Compared to SlCYS8, several mutants (22 out of 29) exhibited either improved or lowered potency against different model Cys proteases, strongly suggesting the potential of positively selected amino acids as target sites to modulate the inhibitory specificity of the cystatin toward Cys proteases of agronomic significance. Accordingly, mutations at positively selected sites strongly influenced the inhibitory potency of SlCYS8 against digestive Cys proteases of the insect herbivore Colorado potato beetle (Leptinotarsa decemlineata). In particular, several variants exhibited improved potency against both cystatin-sensitive and cystatin-insensitive digestive Cys proteases of this insect. Of these, some variants also showed weaker activity against leaf Cys proteases of the host plant (potato [Solanum tuberosum]) and against a major digestive Cys protease of the two-spotted stinkbug Perillus bioculatus, an insect predator of Colorado potato beetle showing potential for biological control. Overall, these observations suggest the usefulness of site-directed mutagenesis at positively selected amino acid sites for the engineering of recombinant cystatins with both improved inhibitory potency toward the digestive proteases of target herbivores and weaker potency against nontarget Cys proteases in the host plant or the environment.
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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".