Increased Insect Virulence in <i>Beauveria bassiana</i> Strains Overexpressing an Engineered Chitinase
Bibliographic record
Abstract
Entomopathogenic fungi are currently being used for the control of several insect pests as alternatives or supplements to chemical insecticides. Improvements in virulence and speed of kill can be achieved by understanding the mechanisms of fungal pathogenesis and genetically modifying targeted genes, thus improving the commercial efficacy of these biocontrol agents. Entomopathogenic fungi, such as Beauveria bassiana, penetrate the insect cuticle utilizing a plethora of hydrolytic enzymes, including chitinases, which are important virulence factors. Two chitinases (Bbchit1 and Bbchit2) have previously been characterized in B. bassiana, neither of which possesses chitin-binding domains. Here we report the construction and characterization of several B. bassiana hybrid chitinases where the chitinase Bbchit1 was fused to chitin-binding domains derived from plant, bacterial, or insect sources. A hybrid chitinase containing the chitin-binding domain (BmChBD) from the silkworm Bombyx mori chitinase fused to Bbchit1 showed the greatest ability to bind to chitin compared to other hybrid chitinases. This hybrid chitinase gene (Bbchit1-BmChBD) was then placed under the control of a fungal constitutive promoter (gpd-Bbchit1-BmChBD) and transformed into B. bassiana. Insect bioassays showed a 23% reduction in time to death in the transformant compared to the wild-type fungus. This transformant also showed greater virulence than another construct (gpd-Bbchit1) with the same constitutive promoter but lacking the chitin-binding domain. We utilized a strategy where genetic components of the host insect can be incorporated into the fungal pathogen in order to increase host cuticle penetration ability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| 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".