LDIP cooperates with SEIPIN and LDAP to facilitate lipid droplet biogenesis in Arabidopsis
Bibliographic record
Abstract
Cytoplasmic lipid droplets (LDs) are evolutionarily conserved organelles that store neutral lipids and play critical roles in plant growth, development, and stress responses. However, the molecular mechanisms underlying their biogenesis at the endoplasmic reticulum (ER) remain obscure. Here we show that a recently identified protein termed LD-associated protein [LDAP]-interacting protein (LDIP) works together with both endoplasmic reticulum-localized SEIPIN and the LD-coat protein LDAP to facilitate LD formation in Arabidopsis thaliana. Heterologous expression in insect cells demonstrated that LDAP is required for the targeting of LDIP to the LD surface, and both proteins are required for the production of normal numbers and sizes of LDs in plant cells. LDIP also interacts with SEIPIN via a conserved hydrophobic helix in SEIPIN and LDIP functions together with SEIPIN to modulate LD numbers and sizes in plants. Further, the co-expression of both proteins is required to restore normal LD production in SEIPIN-deficient yeast cells. These data, combined with the analogous function of LDIP to a mammalian protein called LD Assembly Factor 1, are discussed in the context of a new model for LD biogenesis in plant cells with evolutionary connections to LD biogenesis in other eukaryotes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".