In situ artificial contact sites (ISACS) between synthetic and endogenous organelle membranes allow for quantification of protein-tethering activities
Bibliographic record
Abstract
Membrane contact sites are specialized areas where the membranes of two distinct organelles are physically connected and allow for the exchange of molecules and for signaling processes. Understanding the mechanisms whereby proteins localize to and function in these structures is of special interest; however, methods allowing for reconstitution of these contact sites are few and only based on synthetic membranes and recombinant proteins. Here, we devised a strategy to create in situ artificial contact sites between synthetic and endogenous organelle membranes. Liposomes functionalized with a peptide containing a two phenylalanines in an acidic tract (FFAT) motif were added to adherent cells whose plasma membrane was perforated. Confocal and super-resolution microscopy revealed that these liposomes associated with the endoplasmic reticulum via the specific interaction of the FFAT motif with endoplasmic reticulum-resident vesicle-associated membrane protein-associated proteins. This approach allowed for quantification of the attachment properties of peptides corresponding to FFAT motifs derived from distinct proteins and of a protein construct derived from steroidogenic acute regulatory protein-related lipid transfer domain-3. Collectively, these data indicate that the creation of in situ artificial contact sites represents an efficient approach for studying the membrane-tethering activity of proteins and for designing membrane contact site reconstitution assays in cellular contexts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".