A maize lipid droplet-associated protein is modulated by a virus to promote viral multiplication and infection
Bibliographic record
Abstract
Abstract Pathogen infection induces massive reprogramming of host primary metabolism. Lipid and fatty acid metabolism is generally disrupted by pathogens and co-opted for their proliferation. Lipid droplets (LDs) that play important roles in regulating cellular lipid metabolism are utilized by a variety of pathogens in mammalian cells. However, the function of LDs during pathogenic infection in plants remains unknown. We show here that infection by rice black streaked dwarf virus (RBSDV) affects the lipid metabolism of maize, which causes elevated accumulation of C18 polyunsaturated fatty acids (PUFAs) leading to viral proliferation and symptom development. Overexpression of one of the two novel LD-associated proteins (LDAPs) of maize (ZmLDAP1 and ZmLDAP2) induces LD clustering. The core capsid protein P8 of RBSDV interacts with ZmLDAP2 and prevents its degradation through the ubiquitin-proteasome system mediated by a UBX domain-containing protein, PUX10. In addition, silencing of the ZmLDAP2 down-regulates expression of fatty acid desaturase genes in maize, leading to a decrease in C18 PUFAs levels and suppression of RBSDV accumulation. Our findings reveal that the plant virus recruits LDAP to regulate cellular fatty acid metabolism to promote viral multiplication and infection. These results expand the knowledge of the LD functions and viral infection mechanism in plants. One Sentence Summary Rice black streaked dwarf virus recruits a lipid droplet-associated protein to regulate cellular fatty acid metabolism for promoting viral multiplication and infection.
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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) | 0.003 | 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".