Simultaneous induction of distinct protein phase separation events in multiple subcellular compartments of a single cell
Bibliographic record
Abstract
Intracellular protein crystallization occurs under various physiological and pathological settings, yet the underlying cellular processes remain enigmatic. After validating individual crystallization events using cellular proteins that readily crystallize in the ER (NEU1), cytosol (crystallin-γD mutant) or nucleus (CLC protein), I demonstrate three independent crystallization events can take place concurrently in different subcellular compartments of a single cell without compromising cell viability. By co-expressing NEU1 and previously reported two human monoclonal antibodies that undergo crystallization and liquid-liquid phase separation in the ER, I additionally demonstrate two independent phase separation events can be simultaneously induced in the ER lumen of a single cell without mixing or interfering each other's phase separation behaviors. Intracellular protein crystallization thus takes place in a crowded physiological cellular environment and does not require high protein purity. Furthermore, I report a simple method to increase the yield of intracellular protein crystals by treating the cells with a topoisomerase II inhibitor that blocks cell division without preventing cell size growth. This study not only presents accessible model tools for studying cryptic in vivo protein crystallization events, but also paves a way toward establishing the intracellular protein crystallization as a novel platform for recombinant protein expression and purification.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".