Demixing of simultaneously co-expressed four phase-separating proteins in the endoplasmic reticulum lumen
Bibliographic record
Abstract
Abstract Intracellular protein crystallization represents an intriguing form of biomolecular self-assembly. While the list of such crystallizing proteins is growing and their physiological roles are beginning to be elucidated, the underlying requirements and processes for intracellular protein crystallogenesis remain largely unknown. This study examines how simultaneously co-expressed phase-separating proteins influence each other’s phase-separation event in the endoplasmic reticulum (ER) lumen by using four cargoes selected based on their ability to produce distinctive crystals and droplet inclusion bodies. The co-expressed model proteins independently reached their respective threshold concentrations and spontaneously phase-separated into inclusions in the ER without losing their signature morphologic characteristics. The fact that protein crystals and droplets continued to grow in size over time suggests that nascent cargo proteins were continuously synthesized and folded in the ER to fuel the growth of corresponding inclusion bodies. Namely, despite the highly crowded molecular environment, overexpressed cargoes find their mates by self-association and propagate into microscale structures in the ER. This study demonstrates that cells can accommodate up to four distinct phase separation events simultaneously in the ER lumen, and the phase separation events proceed without interfering with each other and without morphological or content mixing.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".