SLDP and LIPA mediate lipid droplet-plasma membrane tethering in <i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
ABSTRACT Membrane contact sites (MCS) are inter-organellar connections that allow for the direct exchange of molecules, such as lipids or Ca 2+ between organelles, but can also serve to tether organelles at specific locations within cells. Here we identified and characterised three proteins that form a lipid droplet (LD)-plasma membrane (PM) tethering complex in plant cells, namely LD-localised SEED LD PROTEIN (SLDP) 1 and 2 and PM-localised LD-PLASMA MEMBRANE ADAPTOR (LIPA). Using proteomics and different protein-protein interaction assays, we show that both SLDPs associate with LIPA. Disruption of either SLDP1 and 2 expression, or that of LIPA , leads to an aberrant clustering of LDs in Arabidopsis seedlings. Ectopic co-expression of one of the SLDPs with LIPA on the other hand is sufficient to reconstitute LD-PM tethering in Nicotiana tabacum pollen tubes, a cell type characterised by dynamically moving LDs in the cytosolic streaming. Further, confocal laser scanning microscopy revealed both SLDP2.1 and LIPA to be enriched at LD-PM contact sites in seedlings. These and other results suggest that SLDP and LIPA interact to form a tethering complex that anchors a subset of LDs to the PM during post-germinative seedling growth in Arabidopsis thaliana . One-sentence summary SEED LIPID DROPLET PROTEIN1 and 2 and LIPID DROPLET PLASMA MEMBRANE ADAPTOR tether lipid droplets to the plasma membrane in seedlings of Arabidopsis thaliana .
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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 | 0.001 |
| 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".