A Sweet Story: Bean pod mottle virus Transmission Dynamics by Mexican Bean Beetles (Epilachna varivestis)
Bibliographic record
Abstract
Worldwide crop losses due to plant diseases exceed $60 billion annually. Next to fungi, viruses represent the greatest contributor to those losses, and these are transmitted in nature primarily by insects. Mexican bean beetles (Epilachna varivestis) are formidable pests of soybean, as well as efficient vectors of several soybean-infecting viruses, including Bean pod mottle virus (BPMV). Beetle-borne viruses have a unique mode of transmission, though their interactions with host plants and vectors remain poorly understood. In these studies, we implemented targeted metabolite profiling and high throughput RNA sequencing approaches to explore metabolic and molecular changes in soybean leaves infected with BPMV. The virus-infected plants showed altered defence signaling and amino acid concentrations—and most strikingly—had dramatically higher sucrose levels. Based on the results, we performed a series of E. varivestis behavioral bioassays using near-isogenic soybean lines of differing foliar sucrose levels in an attempt to more directly associate sucrose content and E. varivestis feeding preferences. Choice assays revealed E. varivestis is more attracted to BPMV-infected soybean than to healthy plants. Moreover, no-choice assays indicated that beetles consume less foliage per plant but ultimately feed on more plants in a given time period if they are higher in sucrose. Importantly, these virus-driven changes to beetle feeding preferences are likely to increase BPMV spread in natural environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".